Science.gov

Sample records for multivariate condition monitoring

  1. Two simple multivariate procedures for monitoring planetary gearboxes in non-stationary operating conditions

    NASA Astrophysics Data System (ADS)

    Zimroz, Radoslaw; Bartkowiak, Anna

    2013-07-01

    This paper deals with the diagnostics of planetary gearboxes under nonstationary operating conditions. In most diagnostics applications, energy of vibration signals (calculated directly from time series or extracted from spectral representation of signal) is used. Unfortunately energy based features are sensitive to load conditions and it makes diagnostics difficult. In this paper we used energy based 15D data vectors (namely spectral amplitudes of planetary mesh frequency and its harmonics) in order to investigate if it is possible to improve diagnostics efficiency in comparison to previous, one dimensional, approaches proposed for the same problem. Two multivariate methods, Principal Component Analysis (PCA) and Canonical Discriminant Analysis (CDA), were used as techniques for data analysis. We used these techniques in order to investigate dimensionality of the data and to visualize data in 3D and 2D spaces in order to understand data behavior and assess classification ability. As a case study the data from two planetary gearboxes used in complex mining machines (one in bad condition and the other in good condition) were analyzed. For these two machines more than 2000 15D vectors were acquired. It should be noted that due to non-stationarity of loading conditions, previous diagnostics results obtained using other techniques were moderately good (ca. 80% recognition efficiency); however there is still some need to improve diagnostics classification ability. After application of the proposed approaches it was found that the entire data could be reduced to 2 dimensions whereby data instances became visible and a good discriminant function (characterized by a misclassification rate of .0023, i.e. only 5 erroneous classifications for a total of 2183 instances) could be derived. This paper suggests a novel way for condition monitoring of planetary gearboxes based on multivariate statistics. The emphasis is put on the algebraic and geometric interpretations of the PCA

  2. Bioharness™ Multivariable Monitoring Device: Part. I: Validity

    PubMed Central

    Johnstone, James A.; Ford, Paul A.; Hughes, Gerwyn; Watson, Tim; Garrett, Andrew T.

    2012-01-01

    The Bioharness™ monitoring system may provide physiological information on human performance but there is limited information on its validity. The objective of this study was to assess the validity of all 5 Bioharness™ variables using a laboratory based treadmill protocol. 22 healthy males participated. Heart rate (HR), Breathing Frequency (BF) and Accelerometry (ACC) precision were assessed during a discontinuous incremental (0-12 km·h-1) treadmill protocol. Infra-red skin temperature (ST) was assessed during a 45 min-1 sub-maximal cycle ergometer test, completed twice, with environmental temperature controlled at 20 ± 0.1 °C and 30 ± 0.1 °C. Posture (P) was assessed using a tilt table moved through 160°. Adopted precision of measurement devices were; HR: Polar T31 (Polar Electro), BF: Spirometer (Cortex Metalyser), ACC: Oxygen expenditure (Cortex Metalyser), ST: Skin thermistors (Grant Instruments), P:Goniometer (Leighton Flexometer). Strong relationships (r = .89 to .99, p < 0.01) were reported for HR, BF, ACC and P. Limits of agreement identified differences in HR (-3.05 ± 32.20 b·min-1), BF (-3.46 ± 43.70 br·min-1) and P (0.20 ± 2.62°). ST established a moderate relationships (-0.61 ± 1.98 °C; r = 0.76, p < 0.01). Higher velocities on the treadmill decreased the precision of measurement, especially HR and BF. Global results suggest that the BioharressTM is a valid multivariable monitoring device within the laboratory environment. Key pointsDifferent levels of precision exist for each variable in the Bioharness™ (Version 1) multi-variable monitoring deviceAccelerometry and posture variables presented the most precise dataData from the heart rate and breathing frequency variable decrease in precision at velocities ≥ 10 km·h-1Clear understanding of the limitations of new applied monitoring technology is required before it is used by the exercise scientist PMID:24149346

  3. Bioharness™ Multivariable Monitoring Device: Part. II: Reliability

    PubMed Central

    Johnstone, James A.; Ford, Paul A.; Hughes, Gerwyn; Watson, Tim; Garrett, Andrew T.

    2012-01-01

    The Bioharness™ monitoring system may provide physiological information on human performance but the reliability of this data is fundamental for confidence in the equipment being used. The objective of this study was to assess the reliability of each of the 5 Bioharness™ variables using a treadmill based protocol. 10 healthy males participated. A between and within subject design to assess the reliability of Heart rate (HR), Breathing Frequency (BF), Accelerometry (ACC) and Infra-red skin temperature (ST) was completed via a repeated, discontinuous, incremental treadmill protocol. Posture (P) was assessed by a tilt table, moved through 160°. Between subject data reported low Coefficient of Variation (CV) and strong correlations(r) for ACC and P (CV< 7.6; r = 0.99, p < 0.01). In contrast, HR and BF (CV~19.4; r~0.70, p < 0.01) and ST (CV 3.7; r = 0.61, p < 0.01), present more variable data. Intra and inter device data presented strong relationships (r > 0.89, p < 0.01) and low CV (<10.1) for HR, ACC, P and ST. BF produced weaker relationships (r < 0.72) and higher CV (<17.4). In comparison to the other variables BF variable consistently presents less reliability. Global results suggest that the Bioharness™ is a reliable multivariable monitoring device during laboratory testing within the limits presented. Key pointsHeart rate and breathing frequency data increased in variance at higher velocities (i.e. ≥ 10 km.h-1)In comparison to the between subject testing, the intra and inter reliability presented good reliability in data suggesting placement or position of device relative to performer could be important for data collectionUnderstanding a devices variability in measurement is important before it can be used within an exercise testing or monitoring setting PMID:24149347

  4. Monitoring Quality of Biotherapeutic Products Using Multivariate Data Analysis.

    PubMed

    Rathore, Anurag S; Pathak, Mili; Jain, Renu; Jadaun, Gaurav Pratap Singh

    2016-07-01

    Monitoring the quality of pharmaceutical products is a global challenge, heightened by the implications of letting subquality drugs come to the market on public safety. Regulatory agencies do their due diligence at the time of approval as per their prescribed regulations. However, product quality needs to be monitored post-approval as well to ensure patient safety throughout the product life cycle. This is particularly complicated for biotechnology-based therapeutics where seemingly minor changes in process and/or raw material attributes have been shown to have a significant effect on clinical safety and efficacy of the product. This article provides a perspective on the topic of monitoring the quality of biotech therapeutics. In the backdrop of challenges faced by the regulatory agencies, the potential use of multivariate data analysis as a tool for effective monitoring has been proposed. Case studies using data from several insulin biosimilars have been used to illustrate the key concepts. PMID:27044370

  5. A direct-gradient multivariate index of biotic condition

    USGS Publications Warehouse

    Miranda, Leandro E.; Aycock, J.N.; Killgore, K. J.

    2012-01-01

    Multimetric indexes constructed by summing metric scores have been criticized despite many of their merits. A leading criticism is the potential for investigator bias involved in metric selection and scoring. Often there is a large number of competing metrics equally well correlated with environmental stressors, requiring a judgment call by the investigator to select the most suitable metrics to include in the index and how to score them. Data-driven procedures for multimetric index formulation published during the last decade have reduced this limitation, yet apprehension remains. Multivariate approaches that select metrics with statistical algorithms may reduce the level of investigator bias and alleviate a weakness of multimetric indexes. We investigated the suitability of a direct-gradient multivariate procedure to derive an index of biotic condition for fish assemblages in oxbow lakes in the Lower Mississippi Alluvial Valley. Although this multivariate procedure also requires that the investigator identify a set of suitable metrics potentially associated with a set of environmental stressors, it is different from multimetric procedures because it limits investigator judgment in selecting a subset of biotic metrics to include in the index and because it produces metric weights suitable for computation of index scores. The procedure, applied to a sample of 35 competing biotic metrics measured at 50 oxbow lakes distributed over a wide geographical region in the Lower Mississippi Alluvial Valley, selected 11 metrics that adequately indexed the biotic condition of five test lakes. Because the multivariate index includes only metrics that explain the maximum variability in the stressor variables rather than a balanced set of metrics chosen to reflect various fish assemblage attributes, it is fundamentally different from multimetric indexes of biotic integrity with advantages and disadvantages. As such, it provides an alternative to multimetric procedures.

  6. Multivariate Spatial Condition Mapping Using Subtractive Fuzzy Cluster Means

    PubMed Central

    Sabit, Hakilo; Al-Anbuky, Adnan

    2014-01-01

    Wireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining. PMID:25313495

  7. Multivariate spatial condition mapping using subtractive fuzzy cluster means.

    PubMed

    Sabit, Hakilo; Al-Anbuky, Adnan

    2014-01-01

    Wireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining. PMID:25313495

  8. Multivariate monitoring of wastewater treatment processes in pulp and paper industry

    SciTech Connect

    Mujunen, S.

    1999-05-19

    The objective of this thesis was to study factors affecting the treatment efficiency in pulp and paper mills activated sludge plants. Another objective was to develop a process monitoring system based on statistical multivariate methods. A short review of activated sludge plants within pulp and paper industry and basic theory of multivariate data analysis is given at the beginning. The effects of pulp and paper mill effluents and their treatment with the activated sludge process are discussed in the first experimental part. The process and control parameters of the process are studied in the next chapters. Effluent quality and sludge settling ability are studied with PLS (Partial Least Squares) models. The main process parameters affecting each effluent quality parameter are selected and the parameters were modeled separately. Lack of relevant information is discussed and a new monitoring parameter, ATP pool, is introduced. The objective of this luminometric assay study is to provide an easy to measure quantity that would quickly give a sufficiently accurate estimate of the amount of biologically active sludge. The experimental data determined in laboratory and mill conditions are presented. Finally, the principal idea of a monitoring system is introduced and evaluated by using experimental data measured at three pulp and paper mills. The goal is to develop a process monitoring system, that would detect the approaching process drift, e.g., bulking state, on its early stage and by this manner enable right control actions in time.

  9. Rocket engine condition monitoring system

    SciTech Connect

    Hagar, S.K.; Alcock, J.F.

    1989-01-01

    It is expected that the Rocket Engine Condition Monitoring System (RECMS) program will define engine monitoring technologies and an integration approach which can be applied to engine development in support of advanced launch system objectives. The RECMS program approaches engine monitoring as a system which is fully integrated with the engine controller, vehicle monitoring system, and ground processing systems to ensure mission success in addition to engine reliability. The system components are monitored through health and performance sensors; they are analyzed with the diagnostic and prognostic algorithms and demonstrated by system testing with hardware from other advanced development programs.

  10. Oil Analysis and Condition Monitoring

    NASA Astrophysics Data System (ADS)

    Toms, A.; Toms, L.

    Lubricants are essential and expensive components of machine systems needing sampling, analysis and monitoring. Monitoring can be either performance testing or oil condition monitoring. Knowledge of the system's critical failure modes is essential for cost-effective oil and machinery monitoring. Contamination occurs by water, fuel, glycol, dirt, wrong oil, metal particulate, soot, oil degradation and additive depletion. Oil test methods include in situ or laboratory FT-IR, electronic particle counting, elemental metal measurement, X-ray fluorescence, viscosity, gas chromatography, water determination and RULER®. Condition monitoring data must be managed by storage, analysis and interpretation. Status levels must be established from the database and reported upon for individual and sequential runs of samples as condition indicators.

  11. Beer fermentation: monitoring of process parameters by FT-NIR and multivariate data analysis.

    PubMed

    Grassi, Silvia; Amigo, José Manuel; Lyndgaard, Christian Bøge; Foschino, Roberto; Casiraghi, Ernestina

    2014-07-15

    This work investigates the capability of Fourier-Transform near infrared (FT-NIR) spectroscopy to monitor and assess process parameters in beer fermentation at different operative conditions. For this purpose, the fermentation of wort with two different yeast strains and at different temperatures was monitored for nine days by FT-NIR. To correlate the collected spectra with °Brix, pH and biomass, different multivariate data methodologies were applied. Principal component analysis (PCA), partial least squares (PLS) and locally weighted regression (LWR) were used to assess the relationship between FT-NIR spectra and the abovementioned process parameters that define the beer fermentation. The accuracy and robustness of the obtained results clearly show the suitability of FT-NIR spectroscopy, combined with multivariate data analysis, to be used as a quality control tool in the beer fermentation process. FT-NIR spectroscopy, when combined with LWR, demonstrates to be a perfectly suitable quantitative method to be implemented in the production of beer. PMID:24594186

  12. Atmospheric conditions, lunar phases, and childbirth: a multivariate analysis.

    PubMed

    Ochiai, Angela Megumi; Gonçalves, Fabio Luiz Teixeira; Ambrizzi, Tercio; Florentino, Lucia Cristina; Wei, Chang Yi; Soares, Alda Valeria Neves; De Araujo, Natalucia Matos; Gualda, Dulce Maria Rosa

    2012-07-01

    Our objective was to assess extrinsic influences upon childbirth. In a cohort of 1,826 days containing 17,417 childbirths among them 13,252 spontaneous labor admissions, we studied the influence of environment upon the high incidence of labor (defined by 75th percentile or higher), analyzed by logistic regression. The predictors of high labor admission included increases in outdoor temperature (odds ratio: 1.742, P = 0.045, 95%CI: 1.011 to 3.001), and decreases in atmospheric pressure (odds ratio: 1.269, P = 0.029, 95%CI: 1.055 to 1.483). In contrast, increases in tidal range were associated with a lower probability of high admission (odds ratio: 0.762, P = 0.030, 95%CI: 0.515 to 0.999). Lunar phase was not a predictor of high labor admission (P = 0.339). Using multivariate analysis, increases in temperature and decreases in atmospheric pressure predicted high labor admission, and increases of tidal range, as a measurement of the lunar gravitational force, predicted a lower probability of high admission. PMID:21744100

  13. Atmospheric conditions, lunar phases, and childbirth: a multivariate analysis

    NASA Astrophysics Data System (ADS)

    Ochiai, Angela Megumi; Gonçalves, Fabio Luiz Teixeira; Ambrizzi, Tercio; Florentino, Lucia Cristina; Wei, Chang Yi; Soares, Alda Valeria Neves; De Araujo, Natalucia Matos; Gualda, Dulce Maria Rosa

    2012-07-01

    Our objective was to assess extrinsic influences upon childbirth. In a cohort of 1,826 days containing 17,417 childbirths among them 13,252 spontaneous labor admissions, we studied the influence of environment upon the high incidence of labor (defined by 75th percentile or higher), analyzed by logistic regression. The predictors of high labor admission included increases in outdoor temperature (odds ratio: 1.742, P = 0.045, 95%CI: 1.011 to 3.001), and decreases in atmospheric pressure (odds ratio: 1.269, P = 0.029, 95%CI: 1.055 to 1.483). In contrast, increases in tidal range were associated with a lower probability of high admission (odds ratio: 0.762, P = 0.030, 95%CI: 0.515 to 0.999). Lunar phase was not a predictor of high labor admission ( P = 0.339). Using multivariate analysis, increases in temperature and decreases in atmospheric pressure predicted high labor admission, and increases of tidal range, as a measurement of the lunar gravitational force, predicted a lower probability of high admission.

  14. A Computer Interview for Multivariate Monitoring of Psychiatric Outcome.

    ERIC Educational Resources Information Center

    Stevenson, John F.; And Others

    Application of computer technology to psychiatric outcome measurement offers the promise of coping with increasing demands for extensive patient interviews repeated longitudinally. Described is the development of a cost-effective multi-dimensional tracking device to monitor psychiatric functioning, building on a previous local computer interview…

  15. The Multi-Isotope Process Monitor: Multivariate Analysis of Gamma Spectra

    SciTech Connect

    Orton, Christopher R.; Rutherford, Crystal E.; Fraga, Carlos G.; Schwantes, Jon M.

    2011-10-30

    The International Atomic Energy Agency (IAEA) has established international safeguards standards for fissionable material at spent fuel reprocessing plants to ensure that significant quantities of nuclear material are not diverted from these facilities. Currently, methods to verify material control and accountancy (MC&A) at these facilities require time-consuming and resource-intensive destructive assay (DA). The time delay between sampling and subsequent DA provides a potential opportunity to divert the material out of the appropriate chemical stream. Leveraging new on-line nondestructive assay (NDA) techniques in conjunction with the traditional and highly precise DA methods may provide a more timely, cost-effective and resource efficient means for MC&A verification at such facilities. Pacific Northwest National Laboratory (PNNL) is developing on-line NDA process monitoring technologies, including the Multi-Isotope Process (MIP) Monitor. The MIP Monitor uses gamma spectroscopy and pattern recognition software to identify off-normal conditions in process streams. Recent efforts have been made to explore the basic limits of using multivariate analysis techniques on gamma-ray spectra. This paper will provide an overview of the methods and report our on-going efforts to develop and demonstrate the technology.

  16. Reverse inference of memory retrieval processes underlying metacognitive monitoring of learning using multivariate pattern analysis.

    PubMed

    Stiers, Peter; Falbo, Luciana; Goulas, Alexandros; van Gog, Tamara; de Bruin, Anique

    2016-05-15

    Monitoring of learning is only accurate at some time after learning. It is thought that immediate monitoring is based on working memory, whereas later monitoring requires re-activation of stored items, yielding accurate judgements. Such interpretations are difficult to test because they require reverse inference, which presupposes specificity of brain activity for the hidden cognitive processes. We investigated whether multivariate pattern classification can provide this specificity. We used a word recall task to create single trial examples of immediate and long term retrieval and trained a learning algorithm to discriminate them. Next, participants performed a similar task involving monitoring instead of recall. The recall-trained classifier recognized the retrieval patterns underlying immediate and long term monitoring and classified delayed monitoring examples as long-term retrieval. This result demonstrates the feasibility of decoding cognitive processes, instead of their content. PMID:26883066

  17. Monitoring of an industrial process by multivariate control charts based on principal component analysis.

    PubMed

    Marengo, Emilio; Gennaro, Maria Carla; Gianotti, Valentina; Robotti, Elisa

    2003-01-01

    The control and monitoring of an industrial process is performed in this paper by the multivariate control charts. The process analysed consists of the bottling of the entire production of 1999 of the sparkling wine "Asti Spumante". This process is characterised by a great number of variables that can be treated with multivariate techniques. The monitoring of the process performed with classical Shewhart charts is very dangerous because they do not take into account the presence of functional relationships between the variables. The industrial process was firstly analysed by multivariate control charts based on Principal Component Analysis. This approach allowed the identification of problems in the process and of their causes. Successively, the SMART Charts (Simultaneous Scores Monitoring And Residual Tracking) were built in order to study the process in its whole. In spite of the successful identification of the presence of problems in the monitored process, the Smart chart did not allow an easy identification of the special causes of variation which casued the problems themselves. PMID:12911145

  18. Wind Turbine Drivetrain Condition Monitoring - An Overview

    SciTech Connect

    Sheng, S; Veers, P.

    2011-10-01

    This paper provides an overview of wind turbine drivetrain condition monitoring based on presentations from a condition monitoring workshop organized by the National Renewable Energy Laboratory in 2009 and on additional references.

  19. Use of multivariate calibration models based on UV-Vis spectra for seawater quality monitoring in Tianjin Bohai Bay, China.

    PubMed

    Liu, Xianhua; Wang, Lili

    2015-01-01

    A series of ultraviolet-visible (UV-Vis) spectra from seawater samples collected from sites along the coastline of Tianjin Bohai Bay in China were subjected to multivariate partial least squares (PLS) regression analysis. Calibration models were developed for monitoring chemical oxygen demand (COD) and concentrations of total organic carbon (TOC). Three different PLS models were developed using the spectra from raw samples (Model-1), diluted samples (Model-2), and diluted and raw samples combined (Model-3). Experimental results showed that: (i) possible nonlinearities in the signal concentration relationships were well accounted for by the multivariate PLS model; (ii) the predicted values of COD and TOC fit the analytical values well; the high correlation coefficients and small root mean squared error of cross-validation (RMSECV) showed that this method can be used for seawater quality monitoring; and (iii) compared with Model-1 and Model-2, Model-3 had the highest coefficient of determination (R2) and the lowest number of latent variables. This latter finding suggests that only large data sets that include data representing different combinations of conditions (i.e., various seawater matrices) will produce stable site-specific regressions. The results of this study illustrate the effectiveness of the proposed method and its potential for use as a seawater quality monitoring technique. PMID:26442484

  20. Effect of altered sensory conditions on multivariate descriptors of human postural sway

    NASA Technical Reports Server (NTRS)

    Kuo, A. D.; Speers, R. A.; Peterka, R. J.; Horak, F. B.; Peterson, B. W. (Principal Investigator)

    1998-01-01

    Multivariate descriptors of sway were used to test whether altered sensory conditions result not only in changes in amount of sway but also in postural coordination. Eigenvalues and directions of eigenvectors of the covariance of shnk and hip angles were used as a set of multivariate descriptors. These quantities were measured in 14 healthy adult subjects performing the Sensory Organization test, which disrupts visual and somatosensory information used for spatial orientation. Multivariate analysis of variance and discriminant analysis showed that resulting sway changes were at least bivariate in character, with visual and somatosensory conditions producing distinct changes in postural coordination. The most significant changes were found when somatosensory information was disrupted by sway-referencing of the support surface (P = 3.2 x 10(-10)). The resulting covariance measurements showed that subjects not only swayed more but also used increased hip motion analogous to the hip strategy. Disruption of vision, by either closing the eyes or sway-referencing the visual surround, also resulted in altered sway (P = 1.7 x 10(-10)), with proportionately more motion of the center of mass than with platform sway-referencing. As shown by discriminant analysis, an optimal univariate measure could explain at most 90% of the behavior due to altered sensory conditions. The remaining 10%, while smaller, are highly significant changes in posture control that depend on sensory conditions. The results imply that normal postural coordination of the trunk and legs requires both somatosensory and visual information and that each sensory modality makes a unique contribution to posture control. Descending postural commands are multivariate in nature, and the motion at each joint is affected uniquely by input from multiple sensors.

  1. Sustainable microbial water quality monitoring programme design using phage-lysis and multivariate techniques.

    PubMed

    Nnane, Daniel Ekane

    2011-11-15

    Contamination of surface waters is a pervasive threat to human health, hence, the need to better understand the sources and spatio-temporal variations of contaminants within river catchments. River catchment managers are required to sustainably monitor and manage the quality of surface waters. Catchment managers therefore need cost-effective low-cost long-term sustainable water quality monitoring and management designs to proactively protect public health and aquatic ecosystems. Multivariate and phage-lysis techniques were used to investigate spatio-temporal variations of water quality, main polluting chemophysical and microbial parameters, faecal micro-organisms sources, and to establish 'sentry' sampling sites in the Ouse River catchment, southeast England, UK. 350 river water samples were analysed for fourteen chemophysical and microbial water quality parameters in conjunction with the novel human-specific phages of Bacteroides GB-124 (Bacteroides GB-124). Annual, autumn, spring, summer, and winter principal components (PCs) explained approximately 54%, 75%, 62%, 48%, and 60%, respectively, of the total variance present in the datasets. Significant loadings of Escherichia coli, intestinal enterococci, turbidity, and human-specific Bacteroides GB-124 were observed in all datasets. Cluster analysis successfully grouped sampling sites into five clusters. Importantly, multivariate and phage-lysis techniques were useful in determining the sources and spatial extent of water contamination in the catchment. Though human faecal contamination was significant during dry periods, the main source of contamination was non-human. Bacteroides GB-124 could potentially be used for catchment routine microbial water quality monitoring. For a cost-effective low-cost long-term sustainable water quality monitoring design, E. coli or intestinal enterococci, turbidity, and Bacteroides GB-124 should be monitored all-year round in this river catchment. PMID:21962927

  2. Plant Condition Remote Monitoring Technique

    NASA Technical Reports Server (NTRS)

    Fotedar, L. K.; Krishen, K.

    1996-01-01

    This paper summarizes the results of a radiation transfer study conducted on houseplants using controlled environmental conditions. These conditions included: (1) air and soil temperature; (2) incident and reflected radiation; and (3) soil moisture. The reflectance, transmittance, and emittance measurements were conducted in six spectral bands: microwave, red, yellow, green, violet and infrared, over a period of three years. Measurements were taken on both healthy and diseased plants. The data was collected on plants under various conditions which included: variation in plant bio-mass, diurnal variation, changes in plant pathological conditions (including changes in water content), different plant types, various disease types, and incident light wavelength or color. Analysis of this data was performed to yield an algorithm for plant disease from the remotely sensed data.

  3. A multivariate conditional model for streamflow prediction and spatial precipitation refinement

    NASA Astrophysics Data System (ADS)

    Liu, Zhiyong; Zhou, Ping; Chen, Xiuzhi; Guan, Yinghui

    2015-10-01

    The effective prediction and estimation of hydrometeorological variables are important for water resources planning and management. In this study, we propose a multivariate conditional model for streamflow prediction and the refinement of spatial precipitation estimates. This model consists of high dimensional vine copulas, conditional bivariate copula simulations, and a quantile-copula function. The vine copula is employed because of its flexibility in modeling the high dimensional joint distribution of multivariate data by building a hierarchy of conditional bivariate copulas. We investigate two cases to evaluate the performance and applicability of the proposed approach. In the first case, we generate one month ahead streamflow forecasts that incorporate multiple predictors including antecedent precipitation and streamflow records in a basin located in South China. The prediction accuracy of the vine-based model is compared with that of traditional data-driven models such as the support vector regression (SVR) and the adaptive neuro-fuzzy inference system (ANFIS). The results indicate that the proposed model produces more skillful forecasts than SVR and ANFIS. Moreover, this probabilistic model yields additional information concerning the predictive uncertainty. The second case involves refining spatial precipitation estimates derived from the tropical rainfall measuring mission precipitationproduct for the Yangtze River basin by incorporating remotely sensed soil moisture data and the observed precipitation from meteorological gauges over the basin. The validation results indicate that the proposed model successfully refines the spatial precipitation estimates. Although this model is tested for specific cases, it can be extended to other hydrometeorological variables for predictions and spatial estimations.

  4. Monitoring task loading with multivariate EEG measures during complex forms of human-computer interaction

    NASA Technical Reports Server (NTRS)

    Smith, M. E.; Gevins, A.; Brown, H.; Karnik, A.; Du, R.

    2001-01-01

    Electroencephalographic (EEG) recordings were made while 16 participants performed versions of a personal-computer-based flight simulation task of low, moderate, or high difficulty. As task difficulty increased, frontal midline theta EEG activity increased and alpha band activity decreased. A participant-specific function that combined multiple EEG features to create a single load index was derived from a sample of each participant's data and then applied to new test data from that participant. Index values were computed for every 4 s of task data. Across participants, mean task load index values increased systematically with increasing task difficulty and differed significantly between the different task versions. Actual or potential applications of this research include the use of multivariate EEG-based methods to monitor task loading during naturalistic computer-based work.

  5. Optical Spectroscopy and Multivariate Analysis for Biodosimetry and Monitoring of Radiation Injury to the Skin

    SciTech Connect

    Levitskaia, Tatiana G.; Bryan, Samuel A.; Creim, Jeffrey A.; Curry, Terry L.; Luders, Teresa; Thrall, Karla D.; Peterson, James M.

    2012-08-01

    In the event of an intentional or accidental release of ionizing radiation in a densely populated area, timely assessment and triage of the general population for the radiation exposure is critical. In particular, a significant number of the victims may sustain cutaneous radiation injury, which increases the mortality and worsens the overall prognosis of the victims suffered from combined thermal/mechanical and radiation trauma. Diagnosis of the cutaneous radiation injury is challenging, and established methods largely rely on visual manifestations, presence of the skin contamination, and a high degree of recall by the victim. Availability of a high throughput non-invasive in vivo biodosimetry tool for assessment of the radiation exposure of the skin is of particular importance for the timely diagnosis of the cutaneous injury. In the reported investigation, we have tested the potential of an optical reflectance spectroscopy for the evaluation of the radiation injury to the skin. This is technically attractive because optical spectroscopy relies on well-established and routinely used for various applications instrumentation, one example being pulse oximetry which uses selected wavelengths for the quantification of the blood oxygenation. Our method relies on a broad spectral region ranging from the locally absorbed, shallow-penetrating ultraviolet and visible (250 to 800 nm) to more deeply penetrating near-Infrared (800 – 1600 nm) light for the monitoring of multiple physiological changes in the skin upon irradiation. Chemometrics is a multivariate methodology that allows the information from entire spectral region to be used to generate predictive regression models. In this report we demonstrate that simple spectroscopic method, such as the optical reflectance spectroscopy, in combination with multivariate data analysis, offers the promise of rapid and non-invasive in vivo diagnosis and monitoring of the cutaneous radiation exposure, and is able accurately predict

  6. Multivariate, non-linear trend analysis of heterogeneous water quality monitoring data

    NASA Astrophysics Data System (ADS)

    Lischeid, Gunnar; Kalettka, Thomas; Steidl, Jörg; Merz, Christoph; Lehr, Christian

    2014-05-01

    Comprehensive water quality monitoring is considered a necessary prerequisite for sound water resources management and a valuable source for science. In practice, however, use of large monitoring data sets is often limited due to heterogeneous data sources, spatially and temporally variable monitoring schemes, non-equidistant sampling, large natural variability, and, last but not least, by the sheer size of the data sets that makes identification of unexpected peculiarities a tedious task. As a consequence, any initiation of gradual long-term system shifts can hardly be detected, especially as long as it is restricted to a small fraction of sampling sites. In addition, trends might be limited to a rather small subset of sampling sites or to certain periods of time and might thus escape attention. Usually, numerous solutes are monitored in parallel, but trend analyses are performed for each solute separately. However, in water quality samples trends are hardly restricted to single solutes, but affect various solutes synchronously in a characteristic way. Thus performing joint multivariate trend analyses would not only save effort and time, but would yield more robust assessments of system shifts. We present a non-linear multivariate data visualization approach that allows a rapid assessment of non-linear, possibly local trends and unexpected behaviour in large water quality monitoring data sets. It consists of a combination of Self-Organizing Maps and Sammon's Mapping (SOM-SM). The approach was applied to a data set of 2900 water samples, each comprising 13 solutes, compiled from various monitoring programs in the Federal State of Brandenburg (Germany). In total, 128 stream water, groundwater and small pond sites had been sampled between 1994 and 2012 at different and irregular time intervals. The SOM-SM product is a graph where every sample is represented by a symbol. Location of the symbols in the graph is optimized such that the distance between any two symbols

  7. Bayesian Analysis of the Conditional Correlation Between Stock Index Returns with Multivariate Stochastic Volatility Models

    NASA Astrophysics Data System (ADS)

    Pajor, A.

    2006-11-01

    In the paper we compare the modelling ability of discrete-time multivariate Stochastic Volatility (SV) models to describe the conditional correlations between stock index returns. We consider four tri-variate SV models, which differ in the structure of the conditional covariance matrix. Specifications with zero, constant and time-varying conditional correlations are taken into account. As an example we study tri-variate volatility models for the daily log returns on the WIG, S&P 500, and FTSE 100 indexes. In order to formally compare the relative explanatory power of SV specifications we use the Bayesian principles of comparing statistic models. Our results are based on the Bayes factors and implemented through Markov Chain Monte Carlo techniques. The results indicate that the most adequate specifications are those that allow for time-varying conditional correlations and that have as many latent processes as there are conditional variances and covariances. The empirical results clearly show that the data strongly reject the assumption of constant conditional correlations.

  8. Web-based machine tool condition monitoring

    NASA Astrophysics Data System (ADS)

    Ebrahimi, Morteza; Victory, J. L.

    2000-12-01

    This paper looks at the advantages of using the Internet, as the basis for the implementation of low-cost condition monitoring systems, in the manufacturing industry. A model based condition monitoring system, is presented where a number of machining stations dispersed at different physical locations can be inspected via Internet access and the signals from the process analyzed in a dedicated condition monitoring center. Incentive for the new approach to the system health monitoring, logging and surveillance are presented. These extend into advantages of using model-based techniques and the need for an appropriate mathematical model of the machine tool. Finally, the data acquisition and communication system to be used in this application for Internet access will be explained.

  9. Water O-H stretching Raman signature for strong acid monitoring via multivariate analysis.

    PubMed

    Casella, Amanda J; Levitskaia, Tatiana G; Peterson, James M; Bryan, Samuel A

    2013-04-16

    A distinct need exists for real time information on an acid concentration of industrial aqueous streams. Acid strength affects efficiency and selectivity of many separation processes, including nuclear fuel reprocessing. Despite the seeming simplicity of the problem, no practical solution has been offered yet, particularly for the large-scale schemes involving toxic streams such as highly radioactive nuclear wastes. The classic potentiometric technique is not amiable for online measurements due to the requirements of frequent calibration/maintenance and poor long-term stability in aggressive chemical and radiation environments. Therefore, an alternative analytical method is needed. In this work, the potential of using Raman spectroscopic measurements for online monitoring of strong acid concentration in solutions relevant to dissolved used nuclear fuel was investigated. The Raman water signature was monitored for solution systems containing nitric and hydrochloric acids and their sodium salts of systematically varied composition, ionic strength, and temperature. The trivalent neodymium ion simulated the presence of multivalent f metals. The gaussian deconvolution analysis was used to interpret observed effects of the solution nature on the Raman water O-H stretching spectrum. The generated Raman spectroscopic database was used to develop predictive multivariate regression models for the quantification of the acid and other solution components, as well as selected physicochemical properties. This method was validated using independent experiments conducted in a flow solvent extraction system. PMID:23472939

  10. Strategies to optimize monitoring schemes of recreational waters from Salta, Argentina: a multivariate approach

    PubMed Central

    Gutiérrez-Cacciabue, Dolores; Teich, Ingrid; Poma, Hugo Ramiro; Cruz, Mercedes Cecilia; Balzarini, Mónica; Rajal, Verónica Beatriz

    2014-01-01

    Several recreational surface waters in Salta, Argentina, were selected to assess their quality. Seventy percent of the measurements exceeded at least one of the limits established by international legislation becoming unsuitable for their use. To interpret results of complex data, multivariate techniques were applied. Arenales River, due to the variability observed in the data, was divided in two: upstream and downstream representing low and high pollution sites, respectively; and Cluster Analysis supported that differentiation. Arenales River downstream and Campo Alegre Reservoir were the most different environments and Vaqueros and La Caldera Rivers were the most similar. Canonical Correlation Analysis allowed exploration of correlations between physicochemical and microbiological variables except in both parts of Arenales River, and Principal Component Analysis allowed finding relationships among the 9 measured variables in all aquatic environments. Variable’s loadings showed that Arenales River downstream was impacted by industrial and domestic activities, Arenales River upstream was affected by agricultural activities, Campo Alegre Reservoir was disturbed by anthropogenic and ecological effects, and La Caldera and Vaqueros Rivers were influenced by recreational activities. Discriminant Analysis allowed identification of subgroup of variables responsible for seasonal and spatial variations. Enterococcus, dissolved oxygen, conductivity, E. coli, pH, and fecal coliforms are sufficient to spatially describe the quality of the aquatic environments. Regarding seasonal variations, dissolved oxygen, conductivity, fecal coliforms, and pH can be used to describe water quality during dry season, while dissolved oxygen, conductivity, total coliforms, E. coli, and Enterococcus during wet season. Thus, the use of multivariate techniques allowed optimizing monitoring tasks and minimizing costs involved. PMID:25190636

  11. Strategies to optimize monitoring schemes of recreational waters from Salta, Argentina: a multivariate approach.

    PubMed

    Gutiérrez-Cacciabue, Dolores; Teich, Ingrid; Poma, Hugo Ramiro; Cruz, Mercedes Cecilia; Balzarini, Mónica; Rajal, Verónica Beatriz

    2014-12-01

    Several recreational surface waters in Salta, Argentina, were selected to assess their quality. Seventy percent of the measurements exceeded at least one of the limits established by international legislation becoming unsuitable for their use. To interpret results of complex data, multivariate techniques were applied. Arenales River, due to the variability observed in the data, was divided in two: upstream and downstream representing low and high pollution sites, respectively, and cluster analysis supported that differentiation. Arenales River downstream and Campo Alegre Reservoir were the most different environments, and Vaqueros and La Caldera rivers were the most similar. Canonical correlation analysis allowed exploration of correlations between physicochemical and microbiological variables except in both parts of Arenales River, and principal component analysis allowed finding relationships among the nine measured variables in all aquatic environments. Variable's loadings showed that Arenales River downstream was impacted by industrial and domestic activities, Arenales River upstream was affected by agricultural activities, Campo Alegre Reservoir was disturbed by anthropogenic and ecological effects, and La Caldera and Vaqueros rivers were influenced by recreational activities. Discriminant analysis allowed identification of subgroup of variables responsible for seasonal and spatial variations. Enterococcus, dissolved oxygen, conductivity, E. coli, pH, and fecal coliforms are sufficient to spatially describe the quality of the aquatic environments. Regarding seasonal variations, dissolved oxygen, conductivity, fecal coliforms, and pH can be used to describe water quality during dry season, while dissolved oxygen, conductivity, total coliforms, E. coli, and Enterococcus during wet season. Thus, the use of multivariate techniques allowed optimizing monitoring tasks and minimizing costs involved. PMID:25190636

  12. Oxidation management of white wines using cyclic voltammetry and multivariate process monitoring.

    PubMed

    Martins, Rui C; Oliveira, Raquel; Bento, Fatima; Geraldo, Dulce; Lopes, Vitor V; Guedes de Pinho, Paula; Oliveira, Carla M; Silva Ferreira, Antonio C

    2008-12-24

    The development of a fingerprinting strategy capable to evaluate the "oxidation status" of white wines based on cyclic voltammetry is proposed here. It is known that the levels of specific antioxidants and redox mechanisms may be evaluated by cyclic voltammetry. This electrochemical technique was applied on two sets of samples. One group was composed of normal aged white wines and a second group obtained from a white wine forced aging protocol with different oxygen, SO(2), pH, and temperature regimens. A study of antioxidant additions, namely ascorbic acid, was also made in order to establish a statistical link between voltammogram fingerprints and chemical antioxidant substances. It was observed that the oxidation curve presented typical features, which enables sample discrimination according to age, oxygen consumption, and antioxidant additions. In fact, it was possible to place the results into four significant orthogonal directions, compressing 99.8% of nonrandom features. Attempts were made to make voltammogram fingerprinting a tool for monitoring oxidation management. For this purpose, a supervised multivariate control chart was developed using a control sample as reference. When white wines are plotted onto the chart, it is possible to monitor the oxidation status and to diagnose the effects of oxygen regimes and antioxidant activity. Finally, quantification of substances implicated in the oxidation process as reagents (antioxidants) and products (off-flavors) was tried using a supervised algorithmic the partial least square regression analysis. Good correlations (r > 0.93) were observed for ascorbic acid, Folin-Ciocalteu index, total SO(2), methional, and phenylacetaldehyde. These results show that cyclic voltammetry fingerprinting can be used to monitor and diagnose the effects of wine oxidation. PMID:19053361

  13. Infrared thermography for condition monitoring - A review

    NASA Astrophysics Data System (ADS)

    Bagavathiappan, S.; Lahiri, B. B.; Saravanan, T.; Philip, John; Jayakumar, T.

    2013-09-01

    Temperature is one of the most common indicators of the structural health of equipment and components. Faulty machineries, corroded electrical connections, damaged material components, etc., can cause abnormal temperature distribution. By now, infrared thermography (IRT) has become a matured and widely accepted condition monitoring tool where the temperature is measured in real time in a non-contact manner. IRT enables early detection of equipment flaws and faulty industrial processes under operating condition thereby, reducing system down time, catastrophic breakdown and maintenance cost. Last three decades witnessed a steady growth in the use of IRT as a condition monitoring technique in civil structures, electrical installations, machineries and equipment, material deformation under various loading conditions, corrosion damages and welding processes. IRT has also found its application in nuclear, aerospace, food, paper, wood and plastic industries. With the advent of newer generations of infrared camera, IRT is becoming a more accurate, reliable and cost effective technique. This review focuses on the advances of IRT as a non-contact and non-invasive condition monitoring tool for machineries, equipment and processes. Various conditions monitoring applications are discussed in details, along with some basics of IRT, experimental procedures and data analysis techniques. Sufficient background information is also provided for the beginners and non-experts for easy understanding of the subject.

  14. Generation of multivariate near shore extreme wave conditions based on an extreme value copula for offshore boundary conditions.

    NASA Astrophysics Data System (ADS)

    Leyssen, Gert; Mercelis, Peter; De Schoesitter, Philippe; Blanckaert, Joris

    2013-04-01

    Near shore extreme wave conditions, used as input for numerical wave agitation simulations and for the dimensioning of coastal defense structures, need to be determined at a harbour entrance situated at the French North Sea coast. To obtain significant wave heights, the numerical wave model SWAN has been used. A multivariate approach was used to account for the joint probabilities. Considered variables are: wind velocity and direction, water level and significant offshore wave height and wave period. In a first step a univariate extreme value distribution has been determined for the main variables. By means of a technique based on the mean excess function, an appropriate member of the GPD is selected. An optimal threshold for peak over threshold selection is determined by maximum likelihood optimization. Next, the joint dependency structure for the primary random variables is modeled by an extreme value copula. Eventually the multivariate domain of variables was stratified in different classes, each of which representing a combination of variable quantiles with a joint probability, which are used for model simulation. The main variable is the wind velocity, as in the area of concern extreme wave conditions are wind driven. The analysis is repeated for 9 different wind directions. The secondary variable is water level. In shallow waters extreme waves will be directly affected by water depth. Hence the joint probability of occurrence for water level and wave height is of major importance for design of coastal defense structures. Wind velocity and water levels are only dependent for some wind directions (wind induced setup). Dependent directions are detected using a Kendall and Spearman test and appeared to be those with the longest fetch. For these directions, wind velocity and water level extreme value distributions are multivariately linked through a Gumbel Copula. These distributions are stratified into classes of which the frequency of occurrence can be

  15. A Framework and Algorithms for Multivariate Time Series Analytics (MTSA): Learning, Monitoring, and Recommendation

    ERIC Educational Resources Information Center

    Ngan, Chun-Kit

    2013-01-01

    Making decisions over multivariate time series is an important topic which has gained significant interest in the past decade. A time series is a sequence of data points which are measured and ordered over uniform time intervals. A multivariate time series is a set of multiple, related time series in a particular domain in which domain experts…

  16. Assessing a quick monitoring method using rocky intertidal communities as a bioindicator: a multivariate approach in Algeciras Bay.

    PubMed

    Guerra-García, J M; Maestre, M J; González, A R; García-Gómez, J C

    2006-05-01

    A multivariate approach was used to test the value of intertidal communities as a bioindicator of environmental conditions at Algeciras Bay, southern Spain. The study area is located in the Strait of Gibraltar and it is subjected to a variety of anthropic impacts. Eight localities (5 inside and 3 outside the bay) were selected, and four transects were undertaken in each locality to characterise the fauna and flora. The spatial distribution of the intertidal species reflected the physico-chemical conditions of Algeciras Bay. The stations located outside the bay, characterised by high hydrodynamism and dissolved oxygen and low sedimentation and turbidity, had a higher diversity and species richness than the inner stations. According to the BIO-ENV procedure and CCA, water turbidity was the factor which best correlated with the intertidal assemblages. SIMPER showed that the molluscs Chtamalus stellatus, Mytilus cf edulis, Littorina neritoides and Balanus perforatus, and the algae Gelidium pusillum, Corallina elongata, Asparagopsis armata, Colpomenia sinuosa and Fucus spiralis were the species that most contributed to the dissimilarity between internal and external sites. The present study, based on the spatial distribution of intertidal taxa, yielded similar results to those previously obtained in the area with costly physico-chemical analysis based on complex matrices of subtidal epifaunal communities. Consequently, the intertidal sampling method proposed in this study is presented here as a quick, effective alternative strategy, and can be useful in environmental monitoring programs, since these communities are easily accessible and amenable to sample, and the sessile nature of the majority of the species makes future, long-term monitoring relatively simple. PMID:16779601

  17. Electrical condition monitoring method for polymers

    DOEpatents

    Watkins, Jr. Kenneth S.; Morris, Shelby J.; Masakowski, Daniel D.; Wong, Ching Ping; Luo, Shijian

    2010-02-16

    An electrical condition monitoring method utilizes measurement of electrical resistivity of a conductive composite degradation sensor to monitor environmentally induced degradation of a polymeric product such as insulated wire and cable. The degradation sensor comprises a polymeric matrix and conductive filler. The polymeric matrix may be a polymer used in the product, or it may be a polymer with degradation properties similar to that of a polymer used in the product. The method comprises a means for communicating the resistivity to a measuring instrument and a means to correlate resistivity of the degradation sensor with environmentally induced degradation of the product.

  18. Reusable rocket engine turbopump condition monitoring

    NASA Technical Reports Server (NTRS)

    Hampson, M. E.; Barkhoudarian, S.

    1985-01-01

    Significant improvements in engine readiness with attendant reductions in maintenance costs and turnaround times can be achieved with an engine condition monitoring system (CMS). The CMS provides real time health status of critical engine components, without disassembly, through component monitoring with advanced sensor technologies. Three technologies were selected to monitor the rotor bearings and turbine blades: the isotope wear detector and fiber optic deflectometer (bearings), and the fiber optic pyrometer (blades). Signal processing algorithms were evaluated and ranked for their utility in providing useful component health data to unskilled maintenance personnel. Design modifications to current configuration Space Shuttle Main Engine (SSME) high pressure turbopumps and the MK48-F turbopump were developed to incorporate the sensors.

  19. Characterization of Used Nuclear Fuel with Multivariate Analysis for Process Monitoring

    SciTech Connect

    Dayman, Kenneth J.; Coble, Jamie B.; Orton, Christopher R.; Schwantes, Jon M.

    2014-01-01

    The Multi-Isotope Process (MIP) Monitor combines gamma spectroscopy and multivariate analysis to detect anomalies in various process streams in a nuclear fuel reprocessing system. Measured spectra are compared to models of nominal behavior at each measurement location to detect unexpected changes in system behavior. In order to improve the accuracy and specificity of process monitoring, fuel characterization may be used to more accurately train subsequent models in a full analysis scheme. This paper presents initial development of a reactor-type classifier that is used to select a reactor-specific partial least squares model to predict fuel burnup. Nuclide activities for prototypic used fuel samples were generated in ORIGEN-ARP and used to investigate techniques to characterize used nuclear fuel in terms of reactor type (pressurized or boiling water reactor) and burnup. A variety of reactor type classification algorithms, including k-nearest neighbors, linear and quadratic discriminant analyses, and support vector machines, were evaluated to differentiate used fuel from pressurized and boiling water reactors. Then, reactor type-specific partial least squares models were developed to predict the burnup of the fuel. Using these reactor type-specific models instead of a model trained for all light water reactors improved the accuracy of burnup predictions. The developed classification and prediction models were combined and applied to a large dataset that included eight fuel assembly designs, two of which were not used in training the models, and spanned the range of the initial 235U enrichment, cooling time, and burnup values expected of future commercial used fuel for reprocessing. Error rates were consistent across the range of considered enrichment, cooling time, and burnup values. Average absolute relative errors in burnup predictions for validation data both within and outside the training space were 0.0574% and 0.0597%, respectively. The errors seen in this

  20. Condition Monitoring of the SSE Generation Fleet

    NASA Astrophysics Data System (ADS)

    Twiddle, J.; Muthuraman, S.; Connolly, N.

    2012-05-01

    SSE (previously known as Scottish and Southern Energy) operates a diverse portfolio of generation plant, including coal, gas and renewable plant with a total generation capacity of 11,375MW (Sept 2011). In recent years a group of specialists dedicated to providing condition monitoring services has been established at the Equipment Performance Centre (EPC) based at Knottingley, West Yorkshire. We aim to illustrate the role of the EPC and the methods used for monitoring the generation fleet with the objective of maintaining asset integrity, reducing risk of plant failure and unplanned outages and describe the challenges which have been overcome in establishing the EPC. This paper describes methods including vibration and process data analysis, model-based techniques and on-site testing used for monitoring of generation plant, including gas turbines, steam turbines, generators and steam raising plant. These condition monitoring processes utilise available data, adding value to the business, by bringing services in-house and capturing knowledge of plant operation for the benefit of the whole fleet.

  1. A Resilient Condition Assessment Monitoring System

    SciTech Connect

    Humberto Garcia; Wen-Chiao Lin; Semyon M. Meerkov

    2012-08-01

    An architecture and supporting methods are presented for the implementation of a resilient condition assessment monitoring system that can adaptively accommodate both cyber and physical anomalies to a monitored system under observation. In particular, the architecture includes three layers: information, assessment, and sensor selection. The information layer estimates probability distributions of process variables based on sensor measurements and assessments of the quality of sensor data. Based on these estimates, the assessment layer then employs probabilistic reasoning methods to assess the plant health. The sensor selection layer selects sensors so that assessments of the plant condition can be made within desired time periods. Resilient features of the developed system are then illustrated by simulations of a simplified power plant model, where a large portion of the sensors are under attack.

  2. Fourier Transform Infrared Spectroscopy and Multivariate Analysis for Online Monitoring of Dibutyl Phosphate Degradation Product in Tributyl Phosphate/n-Dodecane/Nitric Acid Solvent

    SciTech Connect

    Tatiana G. Levitskaia; James M. Peterson; Emily L. Campbell; Amanda J. Casella; Dean R. Peterman; Samuel A. Bryan

    2013-12-01

    In liquid–liquid extraction separation processes, accumulation of organic solvent degradation products is detrimental to the process robustness, and frequent solvent analysis is warranted. Our research explores the feasibility of online monitoring of the organic solvents relevant to used nuclear fuel reprocessing. This paper describes the first phase of developing a system for monitoring the tributyl phosphate (TBP)/n-dodecane solvent commonly used to separate used nuclear fuel. In this investigation, the effect of extraction of nitric acid from aqueous solutions of variable concentrations on the quantification of TBP and its major degradation product dibutylphosphoric acid (HDBP) was assessed. Fourier transform infrared (FTIR) spectroscopy was used to discriminate between HDBP and TBP in the nitric acid-containing TBP/n-dodecane solvent. Multivariate analysis of the spectral data facilitated the development of regression models for HDBP and TBP quantification in real time, enabling online implementation of the monitoring system. The predictive regression models were validated using TBP/n-dodecane solvent samples subjected to high-dose external ?-irradiation. The predictive models were translated to flow conditions using a hollow fiber FTIR probe installed in a centrifugal contactor extraction apparatus, demonstrating the applicability of the FTIR technique coupled with multivariate analysis for the online monitoring of the organic solvent degradation products.

  3. Fourier Transform Infrared Spectroscopy and Multivariate Analysis for Online Monitoring of Dibutyl Phosphate Degradation Product in Tributyl Phosphate /n-Dodecane/Nitric Acid Solvent

    SciTech Connect

    Levitskaia, Tatiana G.; Peterson, James M.; Campbell, Emily L.; Casella, Amanda J.; Peterman, Dean; Bryan, Samuel A.

    2013-11-05

    In liquid-liquid extraction separation processes, accumulation of organic solvent degradation products is detrimental to the process robustness and frequent solvent analysis is warranted. Our research explores feasibility of online monitoring of the organic solvents relevant to used nuclear fuel reprocessing. This paper describes the first phase of developing a system for monitoring the tributyl phosphate (TBP)/n-dodecane solvent commonly used to separate used nuclear fuel. In this investigation, the effect of extraction of nitric acid from aqueous solutions of variable concentrations on the quantification of TBP and its major degradation product dibutyl phosphoric acid (HDBP) was assessed. Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy was used to discriminate between HDBP and TBP in the nitric acid-containing TBP/n-dodecane solvent. Multivariate analysis of the spectral data facilitated the development of regression models for HDBP and TBP quantification in real time, enabling online implementation of the monitoring system. The predictive regression models were validated using TBP/n-dodecane solvent samples subjected to the high dose external gamma irradiation. The predictive models were translated to flow conditions using a hollow fiber FTIR probe installed in a centrifugal contactor extraction apparatus demonstrating the applicability of the FTIR technique coupled with multivariate analysis for the online monitoring of the organic solvent degradation products.

  4. Electrical condition monitoring method for polymers

    DOEpatents

    Watkins, Jr., Kenneth S.; Morris, Shelby J.; Masakowski, Daniel D.; Wong, Ching Ping; Luo, Shijian

    2008-08-19

    An electrical condition monitoring method utilizes measurement of electrical resistivity of an age sensor made of a conductive matrix or composite disposed in a polymeric structure such as an electrical cable. The conductive matrix comprises a base polymer and conductive filler. The method includes communicating the resistivity to a measuring instrument and correlating resistivity of the conductive matrix of the polymeric structure with resistivity of an accelerated-aged conductive composite.

  5. Quaternion Based Thermal Condition Monitoring System

    NASA Astrophysics Data System (ADS)

    Wong, Wai Kit; Loo, Chu Kiong; Lim, Way Soong; Tan, Poi Ngee

    In this paper, we will propose a new and effective machine condition monitoring system using log-polar mapper, quaternion based thermal image correlator and max-product fuzzy neural network classifier. Two classification characteristics namely: peak to sidelobe ratio (PSR) and real to complex ratio of the discrete quaternion correlation output (p-value) are applied in the proposed machine condition monitoring system. Large PSR and p-value observe in a good match among correlation of the input thermal image with a particular reference image, while small PSR and p-value observe in a bad/not match among correlation of the input thermal image with a particular reference image. In simulation, we also discover that log-polar mapping actually help solving rotation and scaling invariant problems in quaternion based thermal image correlation. Beside that, log-polar mapping can have a two fold of data compression capability. Log-polar mapping can help smoother up the output correlation plane too, hence makes a better measurement way for PSR and p-values. Simulation results also show that the proposed system is an efficient machine condition monitoring system with accuracy more than 98%.

  6. Monitoring of pigmented and wooden surfaces in accelerated ageing processes by FT-Raman spectroscopy and multivariate control charts.

    PubMed

    Marengo, Emilio; Robotti, Elisa; Liparota, Maria Cristina; Gennaro, Maria Carla

    2004-07-01

    Two of the most suitable analytical techniques used in the field of cultural heritage are NIR (near-infrared) and Raman spectroscopy. FT-Raman spectroscopy coupled to multivariate control charts is applied here for the development of a new method for monitoring the conservation state of pigmented and wooden surfaces. These materials were exposed to different accelerated ageing processes in order to evaluate the effect of the applied treatments on the goods surfaces. In this work, a new approach based on the principles of statistical process control (SPC) to the monitoring of cultural heritage, has been developed: the conservation state of samples simulating works-of-art has been treated like an industrial process, monitored with multivariate control charts, owing to the complexity of the spectroscopic data collected. The Raman spectra were analysed by principal component analysis (PCA) and the relevant principal components (PCs) were used for constructing multivariate Shewhart and cumulative sum (CUSUM) control charts. These tools were successfully applied for the identification of the presence of relevant modifications occurring on the surfaces. CUSUM charts however proved to be more effective in the identification of the exact beginning of the applied treatment. In the case of wooden boards, where a sufficient number of PCs were available, simultaneous scores monitoring and residuals tracking (SMART) charts were also investigated. The exposure to a basic attack and to high temperatures produced deep changes on the wooden samples, clearly identified by the multivariate Shewhart, CUSUM and SMART charts. A change on the pigment surface was detected after exposure to an acidic solution and to the UV light, while no effect was identified on the painted surface after the exposure to natural atmospheric events. PMID:18969526

  7. Condition monitoring system of wind turbine generators

    NASA Astrophysics Data System (ADS)

    Abdusamad, Khaled B.

    The development and implementation of the condition monitoring systems (CMS) play a significant role in overcoming the number of failures in the wind turbine generators that result from the harsh operation conditions, such as over temperature, particularly when turbines are deployed offshore. In order to increase the reliability of the wind energy industry, monitoring the operation conditions of wind generators is essential to detect the immediate faults rapidly and perform appropriate preventative maintenance. CMS helps to avoid failures, decrease the potential shutdowns while running, reduce the maintenance and operation costs and maintain wind turbines protected. The knowledge of wind turbine generators' faults, such as stator and rotor inter-turn faults, is indispensable to perform the condition monitoring accurately, and assist with maintenance decision making. Many techniques are utilized to avoid the occurrence of failures in wind turbine generators. The majority of the previous techniques that are applied to monitor the wind generator conditions are based on electrical and mechanical concepts and theories. An advanced CMS can be implemented by using a variety of different techniques and methods to confirm the validity of the obtained electrical and mechanical condition monitoring algorithms. This thesis is focused on applying CMS on wind generators due to high temperature by contributing the statistical, thermal, mathematical, and reliability analyses, and mechanical concepts with the electrical methodology, instead of analyzing the electrical signal and frequencies trends only. The newly developed algorithms can be compared with previous condition monitoring methods, which use the electrical approach in order to establish their advantages and limitations. For example, the hazard reliability techniques of wind generators based on CMS are applied to develop a proper maintenance strategy, which aims to extend the system life-time and reduce the potential

  8. Condition Monitoring of Large-Scale Facilities

    NASA Technical Reports Server (NTRS)

    Hall, David L.

    1999-01-01

    This document provides a summary of the research conducted for the NASA Ames Research Center under grant NAG2-1182 (Condition-Based Monitoring of Large-Scale Facilities). The information includes copies of view graphs presented at NASA Ames in the final Workshop (held during December of 1998), as well as a copy of a technical report provided to the COTR (Dr. Anne Patterson-Hine) subsequent to the workshop. The material describes the experimental design, collection of data, and analysis results associated with monitoring the health of large-scale facilities. In addition to this material, a copy of the Pennsylvania State University Applied Research Laboratory data fusion visual programming tool kit was also provided to NASA Ames researchers.

  9. OTVE turbopump condition monitoring, task E.5

    NASA Technical Reports Server (NTRS)

    Coleman, Paul T.; Collins, J. J.

    1989-01-01

    Recent work has been carried out on development of isotope wear analysis and optical and eddy current technologies to provide bearing wear measurements and real time monitoring of shaft speed, shaft axial displacement and shaft orbit of the Orbit Transfer Vehicle hydrostatic bearing tester. Results show shaft axial displacement can be optically measured (at the same time as shaft orbital motion and speed) to within 0.3 mils by two fiberoptic deflectometers. Evaluation of eddy current probes showed that, in addition to measuring shaft orbital motion, they can be used to measure shaft speed without having to machine grooves on the shaft surface as is the usual practice for turbomachinery. The interim results of this condition monitoring effort are presented.

  10. Condition Monitoring of Cables Task 3 Report: Condition Monitoring Techniques for Electric Cables

    SciTech Connect

    Villaran, M.; Lofaro, R.; na

    2009-11-30

    For more than 20 years the NRC has sponsored research studying electric cable aging degradation, condition monitoring, and environmental qualification testing practices for electric cables used in nuclear power plants. This report summarizes several of the most effective and commonly used condition monitoring techniques available to detect damage and measure the extent of degradation in electric cable insulation. The technical basis for each technique is summarized, along with its application, trendability of test data, ease of performing the technique, advantages and limitations, and the usefulness of the test results to characterize and assess the condition of electric cables.

  11. Intelligent monitoring of ball bearing conditions

    NASA Astrophysics Data System (ADS)

    Liu, T. I.; Mengel, J. M.

    1992-09-01

    Ball bearings are widely used in various kinds of robots, manufacturing machines, and equipment. In order to enhance productivity and improve product quality, an on-line monitoring system is essential to check the status of ball bearings. In this work, peak amplitude in the frequency domain, peak RMS, and the power spectrum were used as indirect indices to develop a system for monitoring and classifying ball bearing defects. These indices were then processed by artificial neural networks. Six different cases of ball bearing states were observed. The data from these observations were then input into neural networks with different architectures to train these neural networks in a learning process. All the trained neural networks are capable of distinguishing the normal bearings from defective bearings with a 100 percent success rate. They can also classify the bearing conditions into six different states with a success rate of up to 97 per cent. The effects of training set sizes and neural network structures on the monitoring performance have also been investigated.

  12. Using Patterns for Multivariate Monitoring and Feedback Control of Linear Accelerator Performance: Proof-of-Concept Research

    SciTech Connect

    Cordes, Gail Adele; Van Ausdeln, Leo Anthony; Velasquez, Maria Elena

    2002-04-01

    The report discusses preliminary proof-of-concept research for using the Advanced Data Validation and Verification System (ADVVS), a new INEEL software package, to add validation and verification and multivariate feedback control to the operation of non-destructive analysis (NDA) equipment. The software is based on human cognition, the recognition of patterns and changes in patterns in time-related data. The first project applied ADVVS to monitor operations of a selectable energy linear electron accelerator, and showed how the software recognizes in real time any deviations from the optimal tune of the machine. The second project extended the software method to provide model-based multivariate feedback control for the same linear electron accelerator. The projects successfully demonstrated proof-of-concept for the applications and focused attention on the common application of intelligent information processing techniques.

  13. Intelligent tool condition monitoring in milling operation

    SciTech Connect

    Fu, P.; Hope, A.D.; King, G.A.

    1998-09-01

    One of the most important features of the modern machining system in an `unmanned` factory is to change tools that have been subjected to wear and damage. An integrated system composed of multi-sensors, signal processing device and intelligent decision making plans is a necessary requirement for automatic manufacturing process. An intelligent tool wear monitoring system for milling operation will be introduced in this report. The system is equipped with four kinds of sensors, signal transforming and collecting apparatus and microcomputer. A unique ANN (artificial neural network) driven fuzzy pattern recognition algorithm has been developed from this research. It can fuse the information from multiple sensors and has strong learning and noise suppression ability. This lead to successful tool wear classification under a range of machining conditions.

  14. Multivariate probability distribution for sewer system vulnerability assessment under data-limited conditions.

    PubMed

    Del Giudice, G; Padulano, R; Siciliano, D

    2016-01-01

    The lack of geometrical and hydraulic information about sewer networks often excludes the adoption of in-deep modeling tools to obtain prioritization strategies for funds management. The present paper describes a novel statistical procedure for defining the prioritization scheme for preventive maintenance strategies based on a small sample of failure data collected by the Sewer Office of the Municipality of Naples (IT). Novelty issues involve, among others, considering sewer parameters as continuous statistical variables and accounting for their interdependences. After a statistical analysis of maintenance interventions, the most important available factors affecting the process are selected and their mutual correlations identified. Then, after a Box-Cox transformation of the original variables, a methodology is provided for the evaluation of a vulnerability map of the sewer network by adopting a joint multivariate normal distribution with different parameter sets. The goodness-of-fit is eventually tested for each distribution by means of a multivariate plotting position. The developed methodology is expected to assist municipal engineers in identifying critical sewers, prioritizing sewer inspections in order to fulfill rehabilitation requirements. PMID:26901717

  15. Monitoring Polaris and Seeing Conditions at PARI

    NASA Astrophysics Data System (ADS)

    Crawford, April

    2016-01-01

    Pisgah Astronomical Research Institute (PARI) was originally built by NASA to track and collect data from satellites. The location in the Pisgah National Forest was chosen due to the excellent ability of the surrounding mountains to block radio interference and light pollution. The PARI observatory has been monitoring Polaris for over 10 years and has amassed a large collection of images of the star and those surrounding it. While several telescopes have been used throughout the project, we are currently using a Omni XLT Series Celestron and an SBIG ST-8300M CCD camera with a 0.70 arcsecond/pixel ratio. The software is run on Windows, however, we will be making a switch to Linux and implementing a new program to control the camera. The new images, once converted to a usable format (ST10 to FITS), can be automatically fed into an in-house Java program to track the variability of the star and simultaneously determine the seeing conditions experienced on the campus. Since we have several years worth of data, the program will also be used to provide a history of variability and seeing conditions. We ultimately hope to be able to track the possible changes in variability of Polaris, as it's current location on the HR diagram is being studied. The data could also prove valuable for our on-site scientists and many visiting students to study on campus. We are also developing a relative scale for our seeing conditions, accompanied by FWHM measurements in arcseconds that will can be compared to those of surrounding observatories in mountainous areas.

  16. Condition Monitoring for Helicopter Data. Appendix A

    NASA Technical Reports Server (NTRS)

    Wen, Fang; Willett, Peter; Deb, Somnath

    2000-01-01

    In this paper the classical "Westland" set of empirical accelerometer helicopter data is analyzed with the aim of condition monitoring for diagnostic purposes. The goal is to determine features for failure events from these data, via a proprietary signal processing toolbox, and to weigh these according to a variety of classification algorithms. As regards signal processing, it appears that the autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; it has also been found that augmentation of these by harmonic and other parameters can improve classification significantly. As regards classification, several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior on training data and is thus able to quantify probability of error in an exact manner, such that features may be discarded or coarsened appropriately.

  17. 40 CFR 141.625 - Conditions requiring increased monitoring.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 23 2014-07-01 2014-07-01 false Conditions requiring increased monitoring. 141.625 Section 141.625 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... Requirements § 141.625 Conditions requiring increased monitoring. (a) If you are required to monitor at...

  18. 40 CFR 141.625 - Conditions requiring increased monitoring.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 24 2012-07-01 2012-07-01 false Conditions requiring increased monitoring. 141.625 Section 141.625 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... Requirements § 141.625 Conditions requiring increased monitoring. (a) If you are required to monitor at...

  19. 40 CFR 141.625 - Conditions requiring increased monitoring.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Conditions requiring increased monitoring. 141.625 Section 141.625 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... Requirements § 141.625 Conditions requiring increased monitoring. (a) If you are required to monitor at...

  20. 40 CFR 141.625 - Conditions requiring increased monitoring.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 24 2013-07-01 2013-07-01 false Conditions requiring increased monitoring. 141.625 Section 141.625 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... Requirements § 141.625 Conditions requiring increased monitoring. (a) If you are required to monitor at...

  1. Multivariate statistical analysis of water chemistry conditions in three wastewater stabilization ponds with algae blooms and pH fluctuations.

    PubMed

    Wallace, Jack; Champagne, Pascale; Hall, Geof

    2016-06-01

    The wastewater stabilization ponds (WSPs) at a wastewater treatment facility in eastern Ontario, Canada, have experienced excessive algae growth and high pH levels in the summer months. A full range of parameters were sampled from the system and the chemical dynamics in the three WSPs were assessed through multivariate statistical analysis. The study presents a novel approach for exploratory analysis of a comprehensive water chemistry dataset, incorporating principal components analysis (PCA) and principal components (PC) and partial least squares (PLS) regressions. The analyses showed strong correlations between chl-a and sunlight, temperature, organic matter, and nutrients, and weak and negative correlations between chl-a and pH and chl-a and DO. PCA reduced the data from 19 to 8 variables, with a good fit to the original data matrix (similarity measure of 0.73). Multivariate regressions to model system pH in terms of these key parameters were performed on the reduced variable set and the PCs generated, for which strong fits (R(2) > 0.79 with all data) were observed. The methodologies presented in this study are applicable to a wide range of natural and engineered systems where a large number of water chemistry parameters are monitored resulting in the generation of large data sets. PMID:27038585

  2. A Poisson-lognormal conditional-autoregressive model for multivariate spatial analysis of pedestrian crash counts across neighborhoods.

    PubMed

    Wang, Yiyi; Kockelman, Kara M

    2013-11-01

    This work examines the relationship between 3-year pedestrian crash counts across Census tracts in Austin, Texas, and various land use, network, and demographic attributes, such as land use balance, residents' access to commercial land uses, sidewalk density, lane-mile densities (by roadway class), and population and employment densities (by type). The model specification allows for region-specific heterogeneity, correlation across response types, and spatial autocorrelation via a Poisson-based multivariate conditional auto-regressive (CAR) framework and is estimated using Bayesian Markov chain Monte Carlo methods. Least-squares regression estimates of walk-miles traveled per zone serve as the exposure measure. Here, the Poisson-lognormal multivariate CAR model outperforms an aspatial Poisson-lognormal multivariate model and a spatial model (without cross-severity correlation), both in terms of fit and inference. Positive spatial autocorrelation emerges across neighborhoods, as expected (due to latent heterogeneity or missing variables that trend in space, resulting in spatial clustering of crash counts). In comparison, the positive aspatial, bivariate cross correlation of severe (fatal or incapacitating) and non-severe crash rates reflects latent covariates that have impacts across severity levels but are more local in nature (such as lighting conditions and local sight obstructions), along with spatially lagged cross correlation. Results also suggest greater mixing of residences and commercial land uses is associated with higher pedestrian crash risk across different severity levels, ceteris paribus, presumably since such access produces more potential conflicts between pedestrian and vehicle movements. Interestingly, network densities show variable effects, and sidewalk provision is associated with lower severe-crash rates. PMID:24036167

  3. Validation of the Enterococci indicator for bacteriological quality monitoring of beaches in Malaysia using a multivariate approach.

    PubMed

    Ahmad, Asmat; Dada, Ayokunle C; Usup, Gires; Heng, Lee Y

    2013-01-01

    There is currently no established bacteriological beach quality monitoring (BQM) program in place in Malaysia. To initiate cost-effective, sustainable bacteriological BQM schemes for the ultimate goal of protecting public health, policy decision makers need to be provided robust, indigenous empirical findings that validate appropriate water quality parameters for inclusion in such monitoring programs. This is the first study that assesses the validity of enterococci as an ideal indicator for bacteriological BQM in Malaysia using a multivariate approach. Beach water and sand samples from 7 beach locations were analyzed for a total of twenty-one microbial and non-microbial water quality parameters. A multivariate approach incorporating cluster analyses (CA), principal component analyses (PCA), and factor analysis (FA) was also adopted. Apart from the weak correlations of Staphylococcus aureus with concentrations of Vibro species (r = 0.302, p = 0.037) and total coliforms (r = 0.392, p = 0.006) in seawater, no correlation existed between S. aureus concentration and other parameters. Faecal coliforms failed to correlate with any of the tested parameters. Enterococci also correlated with more quality parameters than faecal coliforms or any other indicator. Multiple linear regressions highlighted a significant, best fit model that could predict enterococci concentrations in relation to other parameters with a maximum predictive success of 69.64%. PCA/FA clearly delineated enterococci and faecal coliforms as parameters that weighed strongly for BQM while Staphylococcus aureus, faecal coliforms and enterococci weighed strongly for beach sand quality monitoring. On the whole, higher correlations of enterococci levels with other parameters than was observed for faecal coliforms suggest that the former be considered a preferred parameter of choice for BQM in Malaysia. Our findings provide meaningful evidence particularly as it relates to the correlation of

  4. Water O–H Stretching Raman Signature for Strong Acid Monitoring via Multivariate Analysis

    SciTech Connect

    Casella, Amanda J.; Levitskaia, Tatiana G.; Peterson, James M.; Bryan, Samuel A.

    2013-04-16

    Spectroscopic techniques have been applied extensively for quantification and analysis of solution compositions. In addition to static measurements, these techniques have been implemented in flow systems providing real-time solution information. A distinct need exists for information regarding acid concentration as it affects extraction efficiency and selectivity of many separation processes. Despite of the seeming simplicity of the problem, no practical solution has been offered yet particularly for the large-scale schemes involving toxic streams such as highly radioactive nuclear wastes. Classic potentiometric technique is not amiable for on-line measurements in nuclear fuel reprocessing due to requirements of frequent calibration/maintenance and poor long-term stability in the aggressive chemical and radiation environments. In this work, the potential of using Raman spectroscopic measurements for on-line monitoring of strong acid concentration in the solutions relevant to the dissolved used fuel was investigated. The Raman water signature was monitored and recorded for nitric and hydrochloric acid solution systems of systematically varied chemical composition, ionic strength, and temperature. The generated Raman spectroscopic database was used to develop predictive chemometric models for the quantification of the acid concentration (H+), neodymium concentration (Nd3+), nitrate concentration (NO3-), density, and ionic strength. This approach was validated using a flow solvent extraction system.

  5. Multivariate analysis comparing microbial air content of an air-conditioned building and a naturally ventilated building over one year

    NASA Astrophysics Data System (ADS)

    Parat, Sylvie; Perdrix, Alain; Fricker-Hidalgo, Hélène; Saude, Isabelle; Grillot, Renee; Baconnier, Pierre

    Heating, ventilation and air-conditioning (HVAC) may be responsible for the production and spread of airborne microorganisms in office buildings. In order to compare airborne microbiological flora in an air-conditioned building with that in a naturally ventilated building, eight sets of measurements were made over a 1-year period. Concurrently with other environmental measurements, air samples were collected in each building, from three offices and from the outdoor air, using the Andersen single-stage sampler. Three different media were used to culture fungi, staphylococci and mesophilic bacteria. Multivariate analysis revealed a group of offices more contaminated than others, and a marked seasonal variation in fungal concentrations. A comparison of mean levels of microorganisms measured in the two buildings showed that the air microbial content was significantly higher and more variable in the naturally ventilated building than in the air-conditioned building. Moreover, in the naturally ventilated building, the interior fungal content was strongly dependent on the outdoor content, while in the air-conditioned building fungal concentrations remained constant despite significant variations measured outside. This was confirmed by a statistical comparison of the correlation coefficients between indoor and outdoor concentrations. No difference was observed regarding gaseous pollutants and temperature, but relative humidity was significantly higher in the air-conditioned building. The effect of HVAC was to prevent the intake of outdoor particles and to dilute the indoor concentrations. These results are consistent with the presence of high-efficiency filters and a steam humidifier in the HVAC system under study.

  6. Technique based on LED multispectral imaging and multivariate analysis for monitoring the conservation state of the Dead Sea Scrolls.

    PubMed

    Marengo, Emilio; Manfredi, Marcello; Zerbinati, Orfeo; Robotti, Elisa; Mazzucco, Eleonora; Gosetti, Fabio; Bearman, Greg; France, Fenella; Shor, Pnina

    2011-09-01

    The aim of this project is the development of a noninvasive technique based on LED multispectral imaging (MSI) for monitoring the conservation state of the Dead Sea Scrolls (DSS) collection. It is well-known that changes in the parchment reflectance drive the transition of the scrolls from legible to illegible. Capitalizing on this fact, we will use spectral imaging to detect changes in the reflectance before they become visible to the human eye. The technique uses multivariate analysis and statistical process control theory. The present study was carried out on a "sample" parchment of calfskin. The monitoring of the surface of a commercial modern parchment aged consecutively for 2 h and 6 h at 80 °C and 50% relative humidity (ASTM) was performed at the Imaging Lab of the Library of Congress (Washington, DC, U.S.A.). MSI is here carried out in the vis-NIR range limited to 1 μm, with a number of bands of 13 and bandwidths that range from about 10 nm in UV to 40 nm in IR. Results showed that we could detect and locate changing pixels, on the basis of reflectance changes, after only a few "hours" of aging. PMID:21777009

  7. Predictive modeling in Clostridium acetobutylicum fermentations employing Raman spectroscopy and multivariate data analysis for real-time culture monitoring

    NASA Astrophysics Data System (ADS)

    Zu, Theresah N. K.; Liu, Sanchao; Germane, Katherine L.; Servinsky, Matthew D.; Gerlach, Elliot S.; Mackie, David M.; Sund, Christian J.

    2016-05-01

    The coupling of optical fibers with Raman instrumentation has proven to be effective for real-time monitoring of chemical reactions and fermentations when combined with multivariate statistical data analysis. Raman spectroscopy is relatively fast, with little interference from the water peak present in fermentation media. Medical research has explored this technique for analysis of mammalian cultures for potential diagnosis of some cancers. Other organisms studied via this route include Escherichia coli, Saccharomyces cerevisiae, and some Bacillus sp., though very little work has been performed on Clostridium acetobutylicum cultures. C. acetobutylicum is a gram-positive anaerobic bacterium, which is highly sought after due to its ability to use a broad spectrum of substrates and produce useful byproducts through the well-known Acetone-Butanol-Ethanol (ABE) fermentation. In this work, real-time Raman data was acquired from C. acetobutylicum cultures grown on glucose. Samples were collected concurrently for comparative off-line product analysis. Partial-least squares (PLS) models were built both for agitated cultures and for static cultures from both datasets. Media components and metabolites monitored include glucose, butyric acid, acetic acid, and butanol. Models were cross-validated with independent datasets. Experiments with agitation were more favorable for modeling with goodness of fit (QY) values of 0.99 and goodness of prediction (Q2Y) values of 0.98. Static experiments did not model as well as agitated experiments. Raman results showed the static experiments were chaotic, especially during and shortly after manual sampling.

  8. Support vector machine in machine condition monitoring and fault diagnosis

    NASA Astrophysics Data System (ADS)

    Widodo, Achmad; Yang, Bo-Suk

    2007-08-01

    Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

  9. Wind Turbine Drivetrain Condition Monitoring - An Overview (Presentation)

    SciTech Connect

    Sheng, S.; Yang, W.

    2013-07-01

    High operation and maintenance costs still hamper the development of the wind industry despite its quick growth worldwide. To reduce unscheduled downtime and avoid catastrophic failures of wind turbines and their components have been and will be crucial to further raise the competitiveness of wind power. Condition monitoring is one of the key tools for achieving such a goal. To enhance the research and development of advanced condition monitoring techniques dedicated to wind turbines, we present an overview of wind turbine condition monitoring, discuss current practices, point out existing challenges, and suggest possible solutions.

  10. Monitoring breath markers under controlled conditions.

    PubMed

    Righettoni, Marco; Ragnoni, Alessandro; Güntner, Andreas T; Loccioni, Claudio; Pratsinis, Sotiris E; Risby, Terence H

    2015-12-01

    Breath analysis has the potential to detect and monitor diseases as well as to reduce the corresponding medical costs while improving the quality of a patient's life. Herein, a portable prototype, consisting of a commercial breath sampler modified to work as a platform for solid-state gas sensors was developed. The sensor is placed close to the mouth (<10 cm) and minimizes the mouth-to-sensor path to avoid contamination and dilution of the target breath marker. Additionally with an appropriate cooling concept, even high sensor operating temperatures (e.g. 350 °C) could be used. Controlled sampling is crucial for accurate repeatable analysis of the human breath and these concerns have been addressed by this novel prototype. The device helps a subject control their exhaled flow rate which increases reproducibility of intra-subject breath samples. The operation of this flame-made selective chemo-resistive gas sensor is demonstrated by the detection of breath acetone. PMID:26469378

  11. Using the motor to monitor pump conditions

    SciTech Connect

    Casada, D.

    1996-12-01

    When the load of a mechanical device being driven by a motor changes, whether in response to changes in the overall process or changes in the performance of the driven device, the motor inherently responds. For induction motors, the current amplitude and phase angle change as the shaft load changes. By examining the details of these changes in amplitude and phase, load fluctuations of the driven device can be observed. The usefulness of the motor as a transducer to improve the understanding of devices with high torque fluctuations, such as positive displacement compressors and motor-operated valves, has been recognized and demonstrated for a number of years. On such devices as these, the spectrum of the motor current amplitude, phase, or power normally has certain characteristic peaks associated with various load components, such as the piston stroke or gear tooth meshing frequencies. Comparison and trending of the amplitudes of these peaks has been shown to provide some indication of their mechanical condition. For most centrifugal pumps, the load fluctuations are normally low in torque amplitude, and as a result, the motor experiences a correspondingly lower level of load fluctuation. However, both laboratory and field test data have demonstrated that the motor does provide insight into some important pump performance conditions, such as hydraulic stability and pump-to-motor alignment. Comparisons of other dynamic signals, such as vibration and pressure pulsation, to motor data for centrifugal pumps are provided. The effects of inadequate suction head, misalignment, mechanical and hydraulic unbalance on these signals are presented.

  12. REGIONAL MONITORING OF CORAL CONDITION IN THE FLORIDA KEYS

    EPA Science Inventory

    Fisher, William S. and Deborah L. Santavy. 2004. Regional Monitoring of Coral Condition in Florida Keys (Abstract). Presented at the Monitoring Science and Technology Symposium, 20-24 September 2004, Denver, CO. 1 p. (ERL,GB R1020).

    Coral reefs have experienced unpreceden...

  13. Investigation of Various Wind Turbine Drivetrain Condition Monitoring Techniques (Presentation)

    SciTech Connect

    Sheng, S.

    2011-08-01

    This presentation was given at the 2011 Wind Turbine Reliability Workshop sponsored by Sandia National Laboratories in Albuquerque, NM on August 2-3, 2011. It discusses work for the Gearbox Reliability Collaborative including downtime caused by turbine subsystems, annual failure frequency of turbine subsystems, cost benefits of condition monitoring (CM), the Gearbox Reliability Collaborative's condition monitoring approach and rationale, test setup, and results and observations.

  14. Realtime Monitoring of the Extreme Oceanic Conditions in the Kangjin Bay, South Sea, Korea

    NASA Astrophysics Data System (ADS)

    Ro, Y.; Jung, K.

    2006-05-01

    Realtime(RT) monitoring system for the oceanic state variables was developed and has been operating since April, 2004 in the Kangjin Bay, South Sea, Korea shown. The RT production of data stream and display on the Internet web page are made possible in continuous functions of various system elements. Detailed technical information for the RT monitoring system can be referred to Ro et al. (2004). The water quality parameters, current and meteorological conditions are continuously monitored with very high sampling resolution (10 min.) throughout the year and are being published on the Internet web pages (http://oceaninfo.co.kr/kangjin). The research project encompass several important subjects focusing on the extreme oceanic conditions such as very cold water mass formation during the wintertime cold outbreak, highly diluted sea water during the dam water discharge in the summertime monsoon and the subsequent formation of the hypoxia in the shallow Kangjin Bay. These are the typical extreme events captured possibly by the RT monitoring system, without which could never have been observed and understood. These extreme conditions would exert dramatic ecological impact to the local aqua-culture ecology. This study would elucidate the series of physico-chemical processes and its implication of the local eco-system. To understand the complicated processes, various research tools have been employed such as numerical modeling of tidal circulation, density-driven current, water-quality and formation of hypoxia, time series analyses of various water quality properties including multi-variate correlation.

  15. The CMS Beam Conditions and Radiation Monitoring System

    NASA Astrophysics Data System (ADS)

    Castro, E.; Bacchetta, N.; Bell, A. J.; Dabrowski, A.; Guthoff, M.; Hall-Wilton, R.; Hempel, M.; Henschel, H.; Lange, W.; Lohmann, W.; Müller, S.; Novgorodova, O.; Pfeiffer, D.; Ryjov, V.; Stickland, D.; Schimdt, R.; Walsh, R.

    The Compact Muon Solenoid (CMS) is one of the two large, general purpose experiments situated at the LHC at CERN. As with all high energy physics experiments, knowledge of the beam conditions and luminosity is of vital importance. The Beam Conditions and Radiation Monitoring System (BRM) is installed in CMS to protect the detector and to provide feedback to LHC on beam conditions. It is composed of several sub-systems that measure the radiation level close to or inside all sub-detectors, monitor the beam halo conditions with different time resolution, support beam tuning and protect CMS in case of adverse beam conditions by firing a beam abort signal. This paper presents three of the BRM subsystems: the Fast Beam Conditions Monitor (BCM1F), which is designed for fast flux monitoring, measuring with nanosecond time resolution, both the beam halo and collision products; the Beam Scintillator Counters (BSC), that provide hit rates and time information of beam halo and collision products; and the Beam Conditions Monitors (BCM) used as a protection system that can trigger a beam dump when beam losses occur in order to prevent damage to the pixel and tracker detectors. A description of the systems and a characterization on the basis of data collected during LHC operation is presented.

  16. GEOGLAM Crop Monitor Assessment Tool: Developing Monthly Crop Condition Assessments

    NASA Astrophysics Data System (ADS)

    McGaughey, K.; Becker Reshef, I.; Barker, B.; Humber, M. L.; Nordling, J.; Justice, C. O.; Deshayes, M.

    2014-12-01

    The Group on Earth Observations (GEO) developed the Global Agricultural Monitoring initiative (GEOGLAM) to improve existing agricultural information through a network of international partnerships, data sharing, and operational research. This presentation will discuss the Crop Monitor component of GEOGLAM, which provides the Agricultural Market Information System (AMIS) with an international, multi-source, and transparent consensus assessment of crop growing conditions, status, and agro-climatic conditions likely to impact global production. This activity covers the four primary crop types (wheat, maize, rice, and soybean) within the main agricultural producing regions of the AMIS countries. These assessments have been produced operationally since September 2013 and are published in the AMIS Market Monitor Bulletin. The Crop Monitor reports provide cartographic and textual summaries of crop conditions as of the 28th of each month, according to crop type. This presentation will focus on the building of international networks, data collection, and data dissemination.

  17. Spatial and temporal information fusion for crop condition monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop growth condition information is critical for crop management and yield estimation. In order to monitor crop conditions from space, high spatial and temporal resolution remote sensing data are required. Data fusion approach provides a way to generate such data set from multiple remote sensing da...

  18. Data-driven nonlinear technique for condition monitoring

    SciTech Connect

    Hively, L.M.

    1997-04-01

    This paper describes a sensitive technique for distinguishing changes in a nonlinear process. The method obtains a phase-space (PS) representation of the process, which in turn is converted into a probability density function (PDF). Condition change is monitored by comparing two PS-PDFs via a {chi}{sup 2} statistical measure. One example application involves monitoring of brain waves to distinguish various states in an epileptic patient. A second example distinguishes different drilling conditions from spindle motor current data. A third example distinguishes balanced and unbalanced pumping conditions from power data.

  19. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M. , Gentile; Ann C. , Marzouk; Youssef M. , Hale; Darrian J. , Thompson; David C.

    2010-07-13

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  20. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M.; Gentile, Ann C.; Marzouk, Youssef M.; Hale, Darrian J.; Thompson, David C.

    2011-01-25

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  1. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M.; Gentile, Ann C.; Marzouk, Youssef M.; Hale, Darrian J.; Thompson, David C.

    2011-01-04

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  2. Machine Condition Monitoring Software Agent Using JADE and Data Mining

    NASA Astrophysics Data System (ADS)

    Anandan, R.

    2015-03-01

    In recent days there is a huge demand to increase the production of any mechanical components without any disturbance or mechanical faults in the machine. Therefore, to increase the productivity, it is necessary to monitor the running machine at regular intervals. To overcome such difficulties, a new machine condition monitoring software is designed using the multi agent software. This software is designed using the JADE framework and the data are analyzed using free open source Weka explorer for statistical calculations.

  3. Condition Monitoring of Helicopter Gearboxes by Embedded Sensing

    NASA Technical Reports Server (NTRS)

    Suryavanashi, Abhijit; Wang, Shengda; Gao, Robert; Danai, Kourosh; Lewicki, David G.

    2002-01-01

    Health of helicopter gearboxes is commonly assessed by monitoring the housing vibration, thus it is challenged by poor signal-to-noise ratio of the signal measured away from the source. It is hypothesized that vibration measurements from sensors placed inside the gearbox will be much clearer indicators of faults and will eliminate many of the difficulties faced by present condition monitoring systems. This paper outlines our approach to devising such a monitoring system. Several tasks have been outlined toward this objective and the strategy to address each has been described. Among the tasks are wireless sensor design, antenna design, and selection of sensor locations.

  4. Wireless pilot monitoring system for extreme race conditions.

    PubMed

    Pino, Esteban J; Arias, Diego E; Aqueveque, Pablo; Melin, Pedro; Curtis, Dorothy W

    2012-01-01

    This paper presents the design and implementation of an assistive device to monitor car drivers under extreme conditions. In particular, this system is designed in preparation for the 2012 Atacama Solar Challenge to be held in the Chilean desert. Actual preliminary results show the feasibility of such a project including physiological and ambient sensors, real-time processing algorithms, wireless data transmission and a remote monitoring station. Implementation details and field results are shown along with a discussion of the main problems found in real-life telemetry monitoring. PMID:23367054

  5. Model based condition monitoring in lithium-ion batteries

    NASA Astrophysics Data System (ADS)

    Singh, Amardeep; Izadian, Afshin; Anwar, Sohel

    2014-12-01

    In this paper, a model based condition monitoring technique is developed for lithium-ion battery condition monitoring. Here a number of lithium-ion batteries are cycled using two separate over discharge test regimes and the resulting shift in battery parameters is recorded. The battery models are constructed using the equivalent circuit methodology. The condition monitoring setup consists of a model bank representing the different degree of parameter shift due to overdischarge in the lithium ion battery. Extended Kalman filters (EKF) are used to maintain increased robustness of the condition monitoring setup while estimating the terminal voltage of the battery cell. The information carrying residuals are generated and evaluation process is carried out in real-time using multiple model adaptive estimation (MMAE) methodology. The condition evaluation function is used to generate probabilities that indicate the presence of a particular operational condition. Using the test data, it is shown that the performance shift in lithium ion batteries due to over discharge can be accurately detected.

  6. Tolkku - a toolbox for decision support from condition monitoring data

    NASA Astrophysics Data System (ADS)

    Saarela, Olli; Lehtonen, Mikko; Halme, Jari; Aikala, Antti; Raivio, Kimmo

    2012-05-01

    This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning.

  7. Wind Turbine Gearbox Oil Filtration and Condition Monitoring

    SciTech Connect

    Sheng, Shuangwen

    2015-10-25

    This is an invited presentation for a pre-conference workshop, titled advances and opportunities in lubrication: wind turbine, at the 2015 Society of Tribologists and Lubrication Engineers (STLE) Tribology Frontiers Conference held in Denver, CO. It gives a brief overview of wind turbine gearbox oil filtration and condition monitoring by highlighting typical industry practices and challenges. The presentation starts with an introduction by covering recent growth of global wind industry, reliability challenges, benefits of oil filtration and condition monitoring, and financial incentives to conduct wind operation and maintenance research, which includes gearbox oil filtration and condition monitoring work presented herein. Then, the presentation moves on to oil filtration by stressing the benefits of filtration, discussing typical main- and offline-loop practices, highlighting important factors considered when specifying a filtration system, and illustrating real-world application challenges through a cold-start example. In the next section on oil condition monitoring, a discussion on oil sample analysis, oil debris monitoring, oil cleanliness measurements and filter analysis is given based on testing results mostly obtained by and at NREL, and by pointing out a few challenges with oil sample analysis. The presentation concludes with a brief touch on future research and development (R and D) opportunities. It is hoping that the information presented can inform the STLE community to start or redirect their R and D work to help the wind industry advance.

  8. An overview of crop growing condition monitoring in China agriculture remote sensing monitoring system

    NASA Astrophysics Data System (ADS)

    Huang, Qing; Zhou, Qing-bo; Zhang, Li

    2009-07-01

    China is a large agricultural country. To understand the agricultural production condition timely and accurately is related to government decision-making, agricultural production management and the general public concern. China Agriculture Remote Sensing Monitoring System (CHARMS) can monitor crop acreage changes, crop growing condition, agriculture disaster (drought, floods, frost damage, pest etc.) and predict crop yield etc. quickly and timely. The basic principles, methods and regular operation of crop growing condition monitoring in CHARMS are introduced in detail in the paper. CHARMS can monitor crop growing condition of wheat, corn, cotton, soybean and paddy rice with MODIS data. An improved NDVI difference model was used in crop growing condition monitoring in CHARMS. Firstly, MODIS data of every day were received and processed, and the max NDVI values of every fifteen days of main crop were generated, then, in order to assessment a certain crop growing condition in certain period (every fifteen days, mostly), the system compare the remote sensing index data (NDVI) of a certain period with the data of the period in the history (last five year, mostly), the difference between NDVI can indicate the spatial difference of crop growing condition at a certain period. Moreover, Meteorological data of temperature, precipitation and sunshine etc. as well as the field investigation data of 200 network counties were used to modify the models parameters. Last, crop growing condition was assessment at four different scales of counties, provinces, main producing areas and nation and spatial distribution maps of crop growing condition were also created.

  9. A Wavelet-Based Methodology for Grinding Wheel Condition Monitoring

    SciTech Connect

    Liao, T. W.; Ting, C.F.; Qu, Jun; Blau, Peter Julian

    2007-01-01

    Grinding wheel surface condition changes as more material is removed. This paper presents a wavelet-based methodology for grinding wheel condition monitoring based on acoustic emission (AE) signals. Grinding experiments in creep feed mode were conducted to grind alumina specimens with a resinoid-bonded diamond wheel using two different conditions. During the experiments, AE signals were collected when the wheel was 'sharp' and when the wheel was 'dull'. Discriminant features were then extracted from each raw AE signal segment using the discrete wavelet decomposition procedure. An adaptive genetic clustering algorithm was finally applied to the extracted features in order to distinguish different states of grinding wheel condition. The test results indicate that the proposed methodology can achieve 97% clustering accuracy for the high material removal rate condition, 86.7% for the low material removal rate condition, and 76.7% for the combined grinding conditions if the base wavelet, the decomposition level, and the GA parameters are properly selected.

  10. Aero-Engine Condition Monitoring Based on Support Vector Machine

    NASA Astrophysics Data System (ADS)

    Zhang, Chunxiao; Wang, Nan

    The maintenance and management of civil aero-engine require advanced monitor approaches to estimate aero-engine performance and health in order to increase life of aero-engine and reduce maintenance costs. In this paper, we adopted support vector machine (SVM) regression approach to monitor an aero-engine health and condition by building monitoring models of main aero-engine performance parameters(EGT, N1, N2 and FF). The accuracy of nonlinear baseline models of performance parameters is tested and the maximum relative error does not exceed ±0.3%, which meets the engineering requirements. The results show that SVM nonlinear regression is an effective method in aero-engine monitoring.

  11. Reality Monitoring and Metamemory in Adults with Autism Spectrum Conditions.

    PubMed

    Cooper, Rose A; Plaisted-Grant, Kate C; Baron-Cohen, Simon; Simons, Jon S

    2016-06-01

    Studies of reality monitoring (RM) often implicate medial prefrontal cortex (mPFC) in distinguishing internal and external information, a region linked to autism-related deficits in social and self-referential information processing, executive function, and memory. This study used two RM conditions (self-other; perceived-imagined) to investigate RM and metamemory in adults with autism. The autism group showed a deficit in RM, which did not differ across source conditions, and both groups exhibited a self-encoding benefit on recognition and source memory. Metamemory for perceived-imagined information, but not for self-other information, was significantly lower in the autism group. Therefore, reality monitoring and metamemory, sensitive to mPFC function, appear impaired in autism, highlighting a difficulty in remembering and monitoring internal and external details of past events. PMID:26899724

  12. Energy harvesting to power embedded condition monitoring hardware

    NASA Astrophysics Data System (ADS)

    Farinholt, Kevin; Brown, Nathan; Siegel, Jake; McQuown, Justin; Humphris, Robert

    2015-04-01

    The shift toward condition-based monitoring is a key area of research for many military, industrial, and commercial customers who want to lower the overall operating costs of capital equipment and general facilities. Assessing the health of rotating systems such as gearboxes, bearings, pumps and other actuation systems often rely on the need for continuous monitoring to capture transient signals that are evidence of events that could cause (i.e. cavitation), or be the result of (i.e. spalling), damage within a system. In some applications this can be accomplished using line powered analyzers, however for wide-spread monitoring, the use of small-scale embedded electronic systems are more desirable. In such cases the method for powering the electronics becomes a significant design factor. This work presents a multi-source energy harvesting approach meant to provide a robust power source for embedded electronics, capturing energy from vibration, thermal and light sources to operate a low-power sensor node. This paper presents the general design philosophy behind the multi-source harvesting circuit, and how it can be extended from powering electronics developed for periodic monitoring to sensing equipment capable of providing continuous condition-based monitoring.

  13. Fast beam condition monitor for CMS: Performance and upgrade

    NASA Astrophysics Data System (ADS)

    Leonard, Jessica L.; Bell, Alan; Burtowy, Piotr; Dabrowski, Anne; Hempel, Maria; Henschel, Hans; Lange, Wolfgang; Lohmann, Wolfgang; Odell, Nathaniel; Penno, Marek; Pollack, Brian; Przyborowski, Dominik; Ryjov, Vladimir; Stickland, David; Walsh, Roberval; Warzycha, Weronika; Zagozdzinska, Agnieszka

    2014-11-01

    The CMS beam and radiation monitoring subsystem BCM1F (Fast Beam Condition Monitor) consists of 8 individual diamond sensors situated around the beam pipe within the pixel detector volume, for the purpose of fast bunch-by-bunch monitoring of beam background and collision products. In addition, effort is ongoing to use BCM1F as an online luminosity monitor. BCM1F will be running whenever there is beam in LHC, and its data acquisition is independent from the data acquisition of the CMS detector, hence it delivers luminosity even when CMS is not taking data. A report is given on the performance of BCM1F during LHC run I, including results of the van der Meer scan and on-line luminosity monitoring done in 2012. In order to match the requirements due to higher luminosity and 25 ns bunch spacing, several changes to the system must be implemented during the upcoming shutdown, including upgraded electronics and precise gain monitoring. First results from Run II preparation are shown.

  14. USING CONDITION MONITORING TO PREDICT REMAINING LIFE OF ELECTRIC CABLES.

    SciTech Connect

    LOFARO,R.; SOO,P.; VILLARAN,M.; GROVE,E.

    2001-03-29

    Electric cables are passive components used extensively throughout nuclear power stations to perform numerous safety and non-safety functions. It is known that the polymers commonly used to insulate the conductors on these cables can degrade with time; the rate of degradation being dependent on the severity of the conditions in which the cables operate. Cables do not receive routine maintenance and, since it can be very costly, they are not replaced on a regular basis. Therefore, to ensure their continued functional performance, it would be beneficial if condition monitoring techniques could be used to estimate the remaining useful life of these components. A great deal of research has been performed on various condition monitoring techniques for use on electric cables. In a research program sponsored by the U.S. Nuclear Regulatory Commission, several promising techniques were evaluated and found to provide trendable information on the condition of low-voltage electric cables. These techniques may be useful for predicting remaining life if well defined limiting values for the aging properties being measured can be determined. However, each technique has advantages and limitations that must be addressed in order to use it effectively, and the necessary limiting values are not always easy to obtain. This paper discusses how condition monitoring measurements can be used to predict the remaining useful life of electric cables. The attributes of an appropriate condition monitoring technique are presented, and the process to be used in estimating the remaining useful life of a cable is discussed along with the difficulties that must be addressed.

  15. The Thirty Meter Telescope Site Conditions Monitoring System

    NASA Astrophysics Data System (ADS)

    Skidmore, Warren; Travouillon, Tony

    2015-04-01

    We examine the experiences and ideas from operating observatories regarding the measurements of the characteristics of the atmosphere that must be gathered within the locality of the observatory in order to support safe, efficient and scientifically optimized observatory operations as well as commissioning, performance monitoring and support the scientific analysis of telescope observations. We describe the expected requirements for the measurement capabilities of the the TMT Site Conditions Monitoring System (SCMS) and discuss how these plans are being developed with input from staff at operating observatories and active observational astronomers.

  16. Beam monitoring and conditioning working group 4 report

    SciTech Connect

    Wang, X.J.

    1997-01-01

    The highlights of Seventh Advanced Accelerator Concepts (AAC) working group IV (Beam Monitoring, Conditioning and Control at High Frequencies and Ultrafast Timescales) are presented in this report. The talks given at the working group covered wide range of subjects of beam monitoring. They including a new technique of measuring sub- picosecond electron beam bunch length, optical stochastic cooling experiment, timing jitter measurement of photocathode injector, and proposed experiment of measuring micro-bunching of IFEL accelerator. Working group IV also carried out extensive discussion on the longitudinal and transverse emittance characterization of short (sub- picosecond) low emittance (normalized rms emittance < 1 mm-mrad) electron beam, and beam diagnostics requirements for Muon collider.

  17. A suite of optical fibre sensors for structural condition monitoring

    NASA Astrophysics Data System (ADS)

    Sun, T.; Grattan, K. T. V.; Carlton, J.

    2015-05-01

    This paper is to review the research activities at City University London in the development of a range of fibre Bragg grating (FBG)-based sensors, including strain, temperature, relative humidity, vibration and acoustic sensors, with an aim to meet the increasing demands from industry for structural condition monitoring. As a result, arrays of optical fibre sensors have been instrumented into various types of structures, including concrete, limestone, marine propellers, pantograph and electrical motors, allowing for both static and dynamic monitoring and thus enhanced structural reliability and integrity.

  18. Vibration condition monitoring of planetary gearbox under varying external load

    NASA Astrophysics Data System (ADS)

    Bartelmus, W.; Zimroz, R.

    2009-01-01

    The paper shows that for condition monitoring of planetary gearboxes it is important to identify the external varying load condition. In the paper, systematic consideration has been taken of the influence of many factors on the vibration signals generated by a system in which a planetary gearbox is included. These considerations give the basis for vibration signal interpretation, development of the means of condition monitoring, and for the scenario of the degradation of the planetary gearbox. Real measured vibration signals obtained in the industrial environment are processed. The signals are recorded during normal operation of the diagnosed objects, namely planetary gearboxes, which are a part of the driving system used in a bucket wheel excavator, used in lignite mines. It is found that a planetary gearbox in bad condition is more susceptible to load than a gearbox in good condition. The estimated load time traces obtained by a demodulation process of the vibration acceleration signal for a planetary gearbox in good and bad conditions are given. It has been found that the most important factor of the proper planetary gearbox condition is connected with perturbation of arm rotation, where an arm rotation gives rise to a specific vibration signal whose properties are depicted by a short-time Fourier transform (STFT) and Wigner-Ville distribution presented as a time frequency map. The paper gives evidence that there are two dominant low-frequency causes that influence vibration signal modulation, i.e. the varying load, which comes from the nature of the bucket wheel digging process, and the arm/carrier rotation. These two causes determine the condition of the planetary gearboxes considered. Typical local faults such as cracking or breakage of a gear tooth, or local faults in rolling element bearings, have not been found in the cases considered. In real practice, local faults of planetary gearboxes have not occurred, but heavy destruction of planetary gearboxes have

  19. Bridge condition assessment based on long-term strain monitoring

    NASA Astrophysics Data System (ADS)

    Sun, LiMin; Sun, Shouwang

    2011-04-01

    In consideration of the important role that bridges play as transportation infrastructures, their safety, durability and serviceability have always been deeply concerned. Structural Health Monitoring Systems (SHMS) have been installed to many long-span bridges to provide bridge engineers with the information needed in making rational decisions for maintenance. However, SHMS also confronted bridge engineers with the challenge of efficient use of monitoring data. Thus, methodologies which are robust to random disturbance and sensitive to damage become a subject on which many researches in structural condition assessment concentrate. In this study, an innovative probabilistic approach for condition assessment of bridge structures was proposed on the basis of long-term strain monitoring on steel girder of a cable-stayed bridge. First, the methodology of damage detection in the vicinity of monitoring point using strain-based indices was investigated. Then, the composition of strain response of bridge under operational loads was analyzed. Thirdly, the influence of temperature and wind on strains was eliminated and thus strain fluctuation under vehicle loads is obtained. Finally, damage evolution assessment was carried out based on the statistical characteristics of rain-flow cycles derived from the strain fluctuation under vehicle loads. The research conducted indicates that the methodology proposed is qualified for structural condition assessment so far as the following respects are concerned: (a) capability of revealing structural deterioration; (b) immunity to the influence of environmental variation; (c) adaptability to the random characteristic exhibited by long-term monitoring data. Further examination of the applicability of the proposed methodology in aging bridge may provide a more convincing validation.

  20. Model-based condition monitoring for lithium-ion batteries

    NASA Astrophysics Data System (ADS)

    Kim, Taesic; Wang, Yebin; Fang, Huazhen; Sahinoglu, Zafer; Wada, Toshihiro; Hara, Satoshi; Qiao, Wei

    2015-11-01

    Condition monitoring for batteries involves tracking changes in physical parameters and operational states such as state of health (SOH) and state of charge (SOC), and is fundamentally important for building high-performance and safety-critical battery systems. A model-based condition monitoring strategy is developed in this paper for Lithium-ion batteries on the basis of an electrical circuit model incorporating hysteresis effect. It systematically integrates 1) a fast upper-triangular and diagonal recursive least squares algorithm for parameter identification of the battery model, 2) a smooth variable structure filter for the SOC estimation, and 3) a recursive total least squares algorithm for estimating the maximum capacity, which indicates the SOH. The proposed solution enjoys advantages including high accuracy, low computational cost, and simple implementation, and therefore is suitable for deployment and use in real-time embedded battery management systems (BMSs). Simulations and experiments validate effectiveness of the proposed strategy.

  1. Monitoring of Double Stud Wall Moisture Conditions in the Northeast

    SciTech Connect

    Ueno, K.

    2015-03-01

    Double-stud walls insulated with cellulose or low-density spray foam can have R-values of 40 or higher. However, double stud walls have a higher risk of interior-sourced condensation moisture damage, when compared with high-R approaches using exterior insulating sheathing.; Moisture conditions in double stud walls were monitored in Zone 5A (Massachusetts); three double stud assemblies were compared.

  2. Monitoring vegetation conditions from LANDSAT for use in range management

    NASA Technical Reports Server (NTRS)

    Haas, R. H.; Deering, D. W.; Rouse, J. W., Jr.; Schell, J. A.

    1975-01-01

    A summary of the LANDSAT Great Plains Corridor projects and the principal results are presented. Emphasis is given to the use of satellite acquired phenological data for range management and agri-business activities. A convenient method of reducing LANDSAT MSS data to provide quantitative estimates of green biomass on rangelands in the Great Plains is explained. Suggestions for the use of this approach for evaluating range feed conditions are presented. A LANDSAT Follow-on project has been initiated which will employ the green biomass estimation method in a quasi-operational monitoring of range readiness and range feed conditions on a regional scale.

  3. Distributed multisensor fusion for machine condition monitoring fault diagnosis

    NASA Astrophysics Data System (ADS)

    Wang, Xue; Zhao, Guohua; Xie, Xin

    2001-09-01

    This paper presents a new general framework for multisensor fusion based on a distributed detection. Parallel processing and distributed multisensor fusion, as rapidly emerging and promising technologies, provides powerful tools for solving this difficult problem, The distribution and parallelism of proposing and confirming of hypothesis in condition and diagnostic is prosed. A combination serial and parallel reconfiguration of n sensors for decision fusion is analyzed. It shows the result for a real-time parallel distributed complex machine condition monitor and fault diagnostic system.

  4. Surface Acoustic Wave (SAW) Resonators for Monitoring Conditioning Film Formation.

    PubMed

    Hohmann, Siegfried; Kögel, Svea; Brunner, Yvonne; Schmieg, Barbara; Ewald, Christina; Kirschhöfer, Frank; Brenner-Weiß, Gerald; Länge, Kerstin

    2015-01-01

    We propose surface acoustic wave (SAW) resonators as a complementary tool for conditioning film monitoring. Conditioning films are formed by adsorption of inorganic and organic substances on a substrate the moment this substrate comes into contact with a liquid phase. In the case of implant insertion, for instance, initial protein adsorption is required to start wound healing, but it will also trigger immune reactions leading to inflammatory responses. The control of the initial protein adsorption would allow to promote the healing process and to suppress adverse immune reactions. Methods to investigate these adsorption processes are available, but it remains difficult to translate measurement results into actual protein binding events. Biosensor transducers allow user-friendly investigation of protein adsorption on different surfaces. The combination of several transduction principles leads to complementary results, allowing a more comprehensive characterization of the adsorbing layer. We introduce SAW resonators as a novel complementary tool for time-resolved conditioning film monitoring. SAW resonators were coated with polymers. The adsorption of the plasma proteins human serum albumin (HSA) and fibrinogen onto the polymer-coated surfaces were monitored. Frequency results were compared with quartz crystal microbalance (QCM) sensor measurements, which confirmed the suitability of the SAW resonators for this application. PMID:26007735

  5. Surface Acoustic Wave (SAW) Resonators for Monitoring Conditioning Film Formation

    PubMed Central

    Hohmann, Siegfried; Kögel, Svea; Brunner, Yvonne; Schmieg, Barbara; Ewald, Christina; Kirschhöfer, Frank; Brenner-Weiß, Gerald; Länge, Kerstin

    2015-01-01

    We propose surface acoustic wave (SAW) resonators as a complementary tool for conditioning film monitoring. Conditioning films are formed by adsorption of inorganic and organic substances on a substrate the moment this substrate comes into contact with a liquid phase. In the case of implant insertion, for instance, initial protein adsorption is required to start wound healing, but it will also trigger immune reactions leading to inflammatory responses. The control of the initial protein adsorption would allow to promote the healing process and to suppress adverse immune reactions. Methods to investigate these adsorption processes are available, but it remains difficult to translate measurement results into actual protein binding events. Biosensor transducers allow user-friendly investigation of protein adsorption on different surfaces. The combination of several transduction principles leads to complementary results, allowing a more comprehensive characterization of the adsorbing layer. We introduce SAW resonators as a novel complementary tool for time-resolved conditioning film monitoring. SAW resonators were coated with polymers. The adsorption of the plasma proteins human serum albumin (HSA) and fibrinogen onto the polymer-coated surfaces were monitored. Frequency results were compared with quartz crystal microbalance (QCM) sensor measurements, which confirmed the suitability of the SAW resonators for this application. PMID:26007735

  6. Evaluation of Diesel Exhaust Continuous Monitors in Controlled Environmental Conditions

    PubMed Central

    Yu, Chang Ho; Patton, Allison P.; Zhang, Andrew; Fanac, Zhi-Hua (Tina); Weisel, Clifford P.; Lioy, Paul J.

    2015-01-01

    Diesel exhaust (DE) contains a variety of toxic air pollutants, including diesel particulate matter (DPM) and gaseous contaminants (e.g., carbon monoxide (CO)). DPM is dominated by fine (PM2.5) and ultrafine particles (UFP), and can be representatively determined by its thermal-optical refractory as elemental carbon (EC) or light-absorbing characteristics as black carbon (BC). The currently accepted reference method for sampling and analysis of occupational exposure to DPM is the National Institute for Occupational Safety and Health (NIOSH) Method 5040. However, this method cannot provide in-situ short-term measurements of DPM. Thus, real-time monitors are gaining attention to better examine DE exposures in occupational settings. However, real-time monitors are subject to changing environmental conditions. Field measurements have reported interferences in optical sensors and subsequent real-time readings, under conditions of high humidity and abrupt temperature changes. To begin dealing with these issues, we completed a controlled study to evaluate five real-time monitors: Airtec real-time DPM/EC Monitor, TSI SidePak Personal Aerosol Monitor AM510 (PM2.5), TSI Condensation Particle Counter 3007, microAeth AE51 BC Aethalometer, and Langan T15n CO Measurer. Tests were conducted under different temperatures (55, 70, and 80 °F), relative humidity (10, 40, and 80%), and DPM concentrations (50 and 200 µg/m3) in a controlled exposure facility. The 2-hour averaged EC measurements from the Airtec instrument showed relatively good agreement with NIOSH Method 5040 (R2=0.84; slope=1.17±0.06; N=27) and reported ~17% higher EC concentrations than the NIOSH reference method. Temperature, relative humidity, and DPM levels did not significantly affect relative differences in 2-hour averaged EC concentrations obtained by the Airtec instrument versus the NIOSH method (p<0.05). Multiple linear regression analyses, based on 1-min averaged data, suggested combined effects of up to 5

  7. Urban air quality assessment using monitoring data of fractionized aerosol samples, chemometrics and meteorological conditions.

    PubMed

    Yotova, Galina I; Tsitouridou, Roxani; Tsakovski, Stefan L; Simeonov, Vasil D

    2016-01-01

    The present article deals with assessment of urban air by using monitoring data for 10 different aerosol fractions (0.015-16 μm) collected at a typical urban site in City of Thessaloniki, Greece. The data set was subject to multivariate statistical analysis (cluster analysis and principal components analysis) and, additionally, to HYSPLIT back trajectory modeling in order to assess in a better way the impact of the weather conditions on the pollution sources identified. A specific element of the study is the effort to clarify the role of outliers in the data set. The reason for the appearance of outliers is strongly related to the atmospheric condition on the particular sampling days leading to enhanced concentration of pollutants (secondary emissions, sea sprays, road and soil dust, combustion processes) especially for ultra fine and coarse particles. It is also shown that three major sources affect the urban air quality of the location studied-sea sprays, mineral dust and anthropogenic influences (agricultural activity, combustion processes, and industrial sources). The level of impact is related to certain extent to the aerosol fraction size. The assessment of the meteorological conditions leads to defining of four downwind patterns affecting the air quality (Pelagic, Western and Central Europe, Eastern and Northeastern Europe and Africa and Southern Europe). Thus, the present study offers a complete urban air assessment taking into account the weather conditions, pollution sources and aerosol fractioning. PMID:26942452

  8. Wind Turbine Gearbox Condition Monitoring Round Robin Study - Vibration Analysis

    SciTech Connect

    Sheng, S.

    2012-07-01

    The Gearbox Reliability Collaborative (GRC) at the National Wind Technology Center (NWTC) tested two identical gearboxes. One was tested on the NWTCs 2.5 MW dynamometer and the other was field tested in a turbine in a nearby wind plant. In the field, the test gearbox experienced two oil loss events that resulted in damage to its internal bearings and gears. Since the damage was not severe, the test gearbox was removed from the field and retested in the NWTCs dynamometer before it was disassembled. During the dynamometer retest, some vibration data along with testing condition information were collected. These data enabled NREL to launch a Wind Turbine Gearbox Condition Monitoring Round Robin project, as described in this report. The main objective of this project was to evaluate different vibration analysis algorithms used in wind turbine condition monitoring (CM) and find out whether the typical practices are effective. With involvement of both academic researchers and industrial partners, the project sets an example on providing cutting edge research results back to industry.

  9. Optimization of Remediation Conditions using Vadose Zone Monitoring Technology

    NASA Astrophysics Data System (ADS)

    Dahan, O.; Mandelbaum, R.; Ronen, Z.

    2010-12-01

    Success of in-situ bio-remediation of the vadose zone depends mainly on the ability to change and control hydrological, physical and chemical conditions of subsurface. These manipulations enables the development of specific, indigenous, pollutants degrading bacteria or set the environmental conditions for seeded bacteria. As such, the remediation efficiency is dependent on the ability to implement optimal hydraulic and chemical conditions in deep sections of the vadose zone. Enhanced bioremediation of the vadose zone is achieved under field conditions through infiltration of water enriched with chemical additives. Yet, water percolation and solute transport in unsaturated conditions is a complex process and application of water with specific chemical conditions near land surface dose not necessarily result in promoting of desired chemical and hydraulic conditions in deeper sections of the vadose zone. A newly developed vadose-zone monitoring system (VMS) allows continuous monitoring of the hydrological and chemical properties of the percolating water along deep sections of the vadose zone. Implementation of the VMS at sites that undergoes active remediation provides real time information on the chemical and hydrological conditions in the vadose zone as the remediation process progresses. Manipulating subsurface conditions for optimal biodegradation of hydrocarbons is demonstrated through enhanced bio-remediation of the vadose zone at a site that has been contaminated with gasoline products in Tel Aviv. The vadose zone at the site is composed of 6 m clay layer overlying a sandy formation extending to the water table at depth of 20 m bls. The upper 5 m of contaminated soil were removed for ex-situ treatment, and the remaining 15 m vadose zone is treated in-situ through enhanced bioremedaition. Underground drip irrigation system was installed below the surface on the bottom of the excavation. Oxygen and nutrients releasing powder (EHCO, Adventus) was spread below the

  10. Tunable Vibration Energy Harvester for Condition Monitoring of Maritime Gearboxes

    NASA Astrophysics Data System (ADS)

    Hoffmann, D.; Willmann, A.; Folkmer, B.; Manoli, Y.

    2014-11-01

    This paper reports on a new tuning concept, which enables the operation of a vibration generator for energy autonomous condition monitoring of maritime gearboxes. The tuning concept incorporates a circular tuning magnet, which interacts with a coupling magnet attached to the active transducer element. The tuning range can be tailored to the application by careful design of the gap between tuning magnet and coupling magnet. A total rotation angle of only 180° is required for the tuning magnet in order to obtain the full frequency bandwidth. The tuning concept is successfully demonstrated by charging a 0.6 F capacitor on the basis of physical vibration profiles taken from a gearbox.

  11. Suitability of MEMS Accelerometers for Condition Monitoring: An experimental study

    PubMed Central

    Albarbar, Alhussein; Mekid, Samir; Starr, Andrew; Pietruszkiewicz, Robert

    2008-01-01

    With increasing demands for wireless sensing nodes for assets control and condition monitoring; needs for alternatives to expensive conventional accelerometers in vibration measurements have been arisen. Micro-Electro Mechanical Systems (MEMS) accelerometer is one of the available options. The performances of three of the MEMS accelerometers from different manufacturers are investigated in this paper and compared to a well calibrated commercial accelerometer used as a reference for MEMS sensors performance evaluation. Tests were performed on a real CNC machine in a typical industrial environmental workshop and the achieved results are presented.

  12. The ATLAS Beam Condition and Beam Loss Monitors

    NASA Astrophysics Data System (ADS)

    Dolenc, I.

    2010-04-01

    The primary goal of ATLAS Beam Condition Monitor (BCM) and Beam Loss Monitor (BLM) is to protect the ATLAS Inner Detector against damaging LHC beam incidents by initiating beam abort in case of beam failures. Poly-crystalline Chemical Vapour Deposition (pCVD) diamond was chosen as the sensor material for both systems. ATLAS BCM will provide real-time monitoring of instantaneous particle rates close to the interaction point (IP) of ATLAS spectrometer. Using fast front-end and signal processing electronics the time-of-flight and pulse amplitude measurements will be performed to distinguish between normal collisions and background events due to natural or accidental beam losses. Additionally, BCM will also provide coarse relative luminosity information. A second system, the ATLAS BLM, is an independent system which was recently added to complement the BCM. It is a current measuring system and was partially adopted from the BLM system developed by the LHC beam instrumentation group with pCVD diamond pad sensors replacing the ionisation chambers. The design of both systems and results of operation in ATLAS framework during the commissioning with cosmic rays will be reported in this contribution.

  13. Condition monitoring of reciprocating seal based on FBG sensors

    NASA Astrophysics Data System (ADS)

    Zhao, Xiuxu; Zhang, Shuanshuan; Wen, Pengfei; Zhen, Wenhan; Ke, Wei

    2016-07-01

    The failure of hydraulic reciprocating seals will seriously affect the normal operation of hydraulic reciprocating machinery, so the potential fault condition monitoring of reciprocating seals is very important. However, it is extremely difficult because of the limitation of reciprocating motion and the structure constraints of seal groove. In this study, an approach using fiber Bragg grating (FBG) sensors is presented. Experimental results show that the contact strain changes of a reciprocating seal can be detected by FBG sensors in the operation process of the hydraulic cylinders. The failure condition of the reciprocating seal can be identified by wavelet packet energy entropy, and the center frequency of power spectrum analysis. It can provide an effective solution for the fault prevention and health management of reciprocating hydraulic rod seals.

  14. VegScape: U.S. Crop Condition Monitoring Service

    NASA Astrophysics Data System (ADS)

    mueller, R.; Yang, Z.; Di, L.

    2013-12-01

    Since 1995, the US Department of Agriculture (USDA)/National Agricultural Statistics Service (NASS) has provided qualitative biweekly vegetation condition indices to USDA policymakers and the public on a weekly basis during the growing season. Vegetation indices have proven useful for assessing crop condition and identifying the areal extent of floods, drought, major weather anomalies, and vulnerabilities of early/late season crops. With growing emphasis on more extreme weather events and food security issues rising to the forefront of national interest, a new vegetation condition monitoring system was developed. The new vegetation condition portal named VegScape was initiated at the start of the 2013 growing season. VegScape delivers web mapping service based interactive vegetation indices. Users can use an interactive map to explore, query and disseminate current crop conditions. Vegetation indices like Normal Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and mean, median, and ratio comparisons to prior years can be constructed for analytical purposes and on-demand crop statistics. The NASA MODIS satellite with 250 meter (15 acres) resolution and thirteen years of data history provides improved spatial and temporal resolutions and delivers improved detailed timely (i.e., daily) crop specific condition and dynamics. VegScape thus provides supplemental information to support NASS' weekly crop reports. VegScape delivers an agricultural cultivated crop mask and the most recent Cropland Data Layer (CDL) product to exploit the agricultural domain and visualize prior years' planted crops. Additionally, the data can be directly exported to Google Earth for web mashups or delivered via web mapping services for uses in other applications. VegScape supports the ethos of data democracy by providing free and open access to digital geospatial data layers using open geospatial standards, thereby supporting transparent and collaborative government

  15. Self-powered sensing for mechanical system condition monitoring

    NASA Astrophysics Data System (ADS)

    Gao, Robert X.; Kazmer, David O.; Zhang, Li; Theurer, Charles B.; Cui, Yong

    2004-07-01

    A self-powered wireless sensing module for the condition monitoring of mechanical systems and high energy manufacturing processes is described, with injection molding as a special application. The design and analysis of three constituent components in such a sensing module: an energy converter consisting of a piezoceramic stack, an energy regulator based on a pair of bipolar transistors, and a piezoelectric transmitter that transmits ultrasound signals proportional to the pressure within the injection mold, are presented in this paper. The energy extraction mechanism is investigated based on the interactions between the mechanical strain and the electric field developed within the piezoceramic stack. Analytical models for the energy modulator and signal transmitter are also established. Quantitative results are obtained that describe the energy flow among the three components and guide the parametric design of the three constituent components. Simulations and experimental studies have validated the functionality of each component. The models established can be used to subsequently optimize the design of the entire sensor module in terms of minimizing the energy requirement for the sensor and identifying the minimum level of signal intensity required to ensure successful detection of the signal by the signal receiver on the outside of the injection mold. The proposed self-powered sensing technique enables a new generation of sensors that can be employed for the condition monitoring and health diagnosis of a wide range of mechanical and civil systems that are characterized by high energy contents.

  16. Condition Monitoring for Shinkansen Bogies Based on Vibration Analysis

    NASA Astrophysics Data System (ADS)

    Oba, Takuya; Yamada, Koichi; Okada, Nobuyuki; Tanifuji, Katsuya

    Rolling stock has generally been inspected and maintained on the basis of preventive maintenance. However, the reliability of sensors and information technology has drastically improved and, with this background, the objective of this research is to develop a condition monitoring system for the bogies of Shinkansen cars. This paper describes two algorithms for detecting faults in some parts of bogies. These algorithms are based on the statistical analysis of vibration acceleration during some periods. One algorithm detects the difference in the vibration peak distribution between normal operation and operation with faulty parts. The other algorithm compares the vibration states between the front and rear bogies in the same car when one bogie has faulty parts. To examine the details of the vibration characteristics of the bogie with some faults, experiments simulating some faults in bogie parts are conducted in the rolling stock field simulator at Komaki Research Center of JR Central. Through this experiments and analysis, we can demonstrate the reliability and validity of the schemes developed in this study for monitoring the conditions of Shinkansen bogies.

  17. Application of TRIZ approach to machine vibration condition monitoring problems

    NASA Astrophysics Data System (ADS)

    Cempel, Czesław

    2013-12-01

    Up to now machine condition monitoring has not been seriously approached by TRIZ1TRIZ= Russian acronym for Inventive Problem Solving System, created by G. Altshuller ca 50 years ago. users, and the knowledge of TRIZ methodology has not been applied there intensively. However, there are some introductory papers of present author posted on Diagnostic Congress in Cracow (Cempel, in press [11]), and Diagnostyka Journal as well. But it seems to be further need to make such approach from different sides in order to see, if some new knowledge and technology will emerge. In doing this we need at first to define the ideal final result (IFR) of our innovation problem. As a next we need a set of parameters to describe the problems of system condition monitoring (CM) in terms of TRIZ language and set of inventive principles possible to apply, on the way to IFR. This means we should present the machine CM problem by means of contradiction and contradiction matrix. When specifying the problem parameters and inventive principles, one should use analogy and metaphorical thinking, which by definition is not exact but fuzzy, and leads sometimes to unexpected results and outcomes. The paper undertakes this important problem again and brings some new insight into system and machine CM problems. This may mean for example the minimal dimensionality of TRIZ engineering parameter set for the description of machine CM problems, and the set of most useful inventive principles applied to given engineering parameter and contradictions of TRIZ.

  18. Condition monitoring of machinery using motor current signature analysis

    SciTech Connect

    Kryter, R.C.; Haynes, H.D.

    1989-01-01

    Motor current signature analysis (MCSA) is a powerful monitoring tool for motor-driven equipment that provides a nonintrusive means for detecting the presence of mechanical and electrical abnormalities in the motor and the driven equipment, including altered conditions in the process ''downstream'' of the motor-driven equipment. It was developed at the Oak Ridge National Laboratory as a means for determining the effects of aging and service wear systems, but it is applicable to a broad range of machinery. MCSA is based on the recognition that an electric motor (ac or dc) driving a mechanical load acts as an efficient and permanently available transducer by sensing mechanical load variations, large and small, long-term and rapid, and converting them into variations in the induced current generated in the motor windings. These motor current variations are carried by the electrical cables processes as desired. Motor current signatures, obtained in both time and over time to provide early indication of degradation. Successful applications of MCSA technology (patent applied for) include not only motor-operated valves but also pumps of various designs, blowers, and air conditioning systems. Examples are presented briefly, and speculation regarding the applicability of MCSA to a broader range of equipment monitoring and production line testing is also given. 1 ref., 13 figs.

  19. SSME Condition Monitoring Using Neural Networks and Plume Spectral Signatures

    NASA Technical Reports Server (NTRS)

    Hopkins, Randall; Benzing, Daniel

    1996-01-01

    For a variety of reasons, condition monitoring of the Space Shuttle Main Engine (SSME) has become an important concern for both ground tests and in-flight operation. The complexities of the SSME suggest that active, real-time condition monitoring should be performed to avoid large-scale or catastrophic failure of the engine. In 1986, the SSME became the subject of a plume emission spectroscopy project at NASA's Marshall Space Flight Center (MSFC). Since then, plume emission spectroscopy has recorded many nominal tests and the qualitative spectral features of the SSME plume are now well established. Significant discoveries made with both wide-band and narrow-band plume emission spectroscopy systems led MSFC to develop the Optical Plume Anomaly Detection (OPAD) system. The OPAD system is designed to provide condition monitoring of the SSME during ground-level testing. The operational health of the engine is achieved through the acquisition of spectrally resolved plume emissions and the subsequent identification of abnormal emission levels in the plume indicative of engine erosion or component failure. Eventually, OPAD, or a derivative of the technology, could find its way on to an actual space vehicle and provide in-flight engine condition monitoring. This technology step, however, will require miniaturized hardware capable of processing plume spectral data in real-time. An objective of OPAD condition monitoring is to determine how much of an element is present in the SSME plume. The basic premise is that by knowing the element and its concentration, this could be related back to the health of components within the engine. For example, an abnormal amount of silver in the plume might signify increased wear or deterioration of a particular bearing in the engine. Once an anomaly is identified, the engine could be shut down before catastrophic failure occurs. Currently, element concentrations in the plume are determined iteratively with the help of a non-linear computer

  20. Diagnosis of abnormal patterns in multivariate microclimate monitoring: a case study of an open-air archaeological site in Pompeii (Italy).

    PubMed

    Merello, Paloma; García-Diego, Fernando-Juan; Zarzo, Manuel

    2014-08-01

    Chemometrics has been applied successfully since the 1990s for the multivariate statistical control of industrial processes. A new area of interest for these tools is the microclimatic monitoring of cultural heritage. Sensors record climatic parameters over time and statistical data analysis is performed to obtain valuable information for preventive conservation. A case study of an open-air archaeological site is presented here. A set of 26 temperature and relative humidity data-loggers was installed in four rooms of Ariadne's house (Pompeii). If climatic values are recorded versus time at different positions, the resulting data structure is equivalent to records of physical parameters registered at several points of a continuous chemical process. However, there is an important difference in this case: continuous processes are controlled to reach a steady state, whilst open-air sites undergo tremendous fluctuations. Although data from continuous processes are usually column-centred prior to applying principal components analysis, it turned out that another pre-treatment (row-centred data) was more convenient for the interpretation of components and to identify abnormal patterns. The detection of typical trajectories was more straightforward by dividing the whole monitored period into several sub-periods, because the marked climatic fluctuations throughout the year affect the correlation structures. The proposed statistical methodology is of interest for the microclimatic monitoring of cultural heritage, particularly in the case of open-air or semi-confined archaeological sites. PMID:24814033

  1. Multivariate statistical monitoring as applied to clean-in-place (CIP) and steam-in-place (SIP) operations in biopharmaceutical manufacturing.

    PubMed

    Roy, Kevin; Undey, Cenk; Mistretta, Thomas; Naugle, Gregory; Sodhi, Manbir

    2014-01-01

    Multivariate statistical process monitoring (MSPM) is becoming increasingly utilized to further enhance process monitoring in the biopharmaceutical industry. MSPM can play a critical role when there are many measurements and these measurements are highly correlated, as is typical for many biopharmaceutical operations. Specifically, for processes such as cleaning-in-place (CIP) and steaming-in-place (SIP, also known as sterilization-in-place), control systems typically oversee the execution of the cycles, and verification of the outcome is based on offline assays. These offline assays add to delays and corrective actions may require additional setup times. Moreover, this conventional approach does not take interactive effects of process variables into account and cycle optimization opportunities as well as salient trends in the process may be missed. Therefore, more proactive and holistic online continued verification approaches are desirable. This article demonstrates the application of real-time MSPM to processes such as CIP and SIP with industrial examples. The proposed approach has significant potential for facilitating enhanced continuous verification, improved process understanding, abnormal situation detection, and predictive monitoring, as applied to CIP and SIP operations. PMID:24532460

  2. Condition Based Monitoring of Gas Turbine Combustion Components

    SciTech Connect

    Ulerich, Nancy; Kidane, Getnet; Spiegelberg, Christine; Tevs, Nikolai

    2012-09-30

    The objective of this program is to develop sensors that allow condition based monitoring of critical combustion parts of gas turbines. Siemens teamed with innovative, small companies that were developing sensor concepts that could monitor wearing and cracking of hot turbine parts. A magnetic crack monitoring sensor concept developed by JENTEK Sensors, Inc. was evaluated in laboratory tests. Designs for engine application were evaluated. The inability to develop a robust lead wire to transmit the signal long distances resulted in a discontinuation of this concept. An optical wear sensor concept proposed by K Sciences GP, LLC was tested in proof-of concept testing. The sensor concept depended, however, on optical fiber tips wearing with the loaded part. The fiber tip wear resulted in too much optical input variability; the sensor could not provide adequate stability for measurement. Siemens developed an alternative optical wear sensor approach that used a commercial PHILTEC, Inc. optical gap sensor with an optical spacer to remove fibers from the wearing surface. The gap sensor measured the length of the wearing spacer to follow loaded part wear. This optical wear sensor was developed to a Technology Readiness Level (TRL) of 5. It was validated in lab tests and installed on a floating transition seal in an F-Class gas turbine. Laboratory tests indicate that the concept can measure wear on loaded parts at temperatures up to 800{degrees}C with uncertainty of < 0.3 mm. Testing in an F-Class engine installation showed that the optical spacer wore with the wearing part. The electro-optics box located outside the engine enclosure survived the engine enclosure environment. The fiber optic cable and the optical spacer, however, both degraded after about 100 operating hours, impacting the signal analysis.

  3. A simplified scheme for induction motor condition monitoring

    NASA Astrophysics Data System (ADS)

    Rodríguez, Pedro Vicente Jover; Negrea, Marian; Arkkio, Antero

    2008-07-01

    This work proposes a general scheme to detect induction motor fault by monitoring the motor current. The scheme is based on signal processing (predictive filters) and soft computing technique (fuzzy logic). The predictive filter is used in order to separate the fundamental component from the harmonic components. Fuzzy logic is used to identify the motor state. Finite element method (FEM) is utilised to generate virtual data that allows to test the proposed technique and foresee the change in the current under different motor conditions. A simple and reliable method for the detection of stator winding failures based on the phase current amplitudes is implemented and tested. The layout has been proved in MATLAB/SIMULINK, with both data from FEM motor simulation program and real measurements. The proposed method has the ability to work with variable speed drives and avoids the detailed spectral analysis of the motor current. This work shows the feasibility of spotting broken rotor bars, eccentricities and inter-turn short-circuit by monitoring the motor currents.

  4. Embedded strain gauges for condition monitoring of silicone gaskets.

    PubMed

    Schotzko, Timo; Lang, Walter

    2014-01-01

    A miniaturized strain gauge with a thickness of 5 µm is molded into a silicone O-ring. This is a first step toward embedding sensors in gaskets for structural health monitoring. The signal of the integrated sensor exhibits a linear correlation with the contact pressure of the O-ring. This affords the opportunity to monitor the gasket condition during installation. Thus, damages caused by faulty assembly can be detected instantly, and early failures, with their associated consequences, can be prevented. Through the embedded strain gauge, the contact pressure applied to the gasket can be directly measured. Excessive pressure and incorrect positioning of the gasket can cause structural damage to the material of the gasket, which can lead to an early outage. A platinum strain gauge is fabricated on a thin polyimide layer and is contacted through gold connections. The measured resistance pressure response exhibits hysteresis for the first few strain cycles, followed by a linear behavior. The short-term impact of the embedded sensor on the stability of the gasket is investigated. Pull-tests with O-rings and test specimens have indicated that the integration of the miniaturized sensors has no negative impact on the stability in the short term. PMID:25014099

  5. Embedded Strain Gauges for Condition Monitoring of Silicone Gaskets

    PubMed Central

    Schotzko, Timo; Lang, Walter

    2014-01-01

    A miniaturized strain gauge with a thickness of 5 µm is molded into a silicone O-ring. This is a first step toward embedding sensors in gaskets for structural health monitoring. The signal of the integrated sensor exhibits a linear correlation with the contact pressure of the O-ring. This affords the opportunity to monitor the gasket condition during installation. Thus, damages caused by faulty assembly can be detected instantly, and early failures, with their associated consequences, can be prevented. Through the embedded strain gauge, the contact pressure applied to the gasket can be directly measured. Excessive pressure and incorrect positioning of the gasket can cause structural damage to the material of the gasket, which can lead to an early outage. A platinum strain gauge is fabricated on a thin polyimide layer and is contacted through gold connections. The measured resistance pressure response exhibits hysteresis for the first few strain cycles, followed by a linear behavior. The short-term impact of the embedded sensor on the stability of the gasket is investigated. Pull-tests with O-rings and test specimens have indicated that the integration of the miniaturized sensors has no negative impact on the stability in the short term. PMID:25014099

  6. Distributed acoustic fibre optic sensors for condition monitoring of pipelines

    NASA Astrophysics Data System (ADS)

    Hussels, Maria-Teresa; Chruscicki, Sebastian; Habib, Abdelkarim; Krebber, Katerina

    2016-05-01

    Industrial piping systems are particularly relevant to public safety and the continuous availability of infrastructure. However, condition monitoring systems based on many discrete sensors are generally not well-suited for widespread piping systems due to considerable installation effort, while use of distributed fibre-optic sensors would reduce this effort to a minimum. Specifically distributed acoustic sensing (DAS) is employed for detection of third-party threats and leaks in oil and gas pipelines in recent years and can in principle also be applied to industrial plants. Further possible detection routes amenable by DAS that could identify damage prior to emission of medium are subject of a current project at BAM, which aims at qualifying distributed fibre optic methods such as DAS as a means for spatially continuous monitoring of industrial piping systems. Here, first tests on a short pipe are presented, where optical fibres were applied directly to the surface. An artificial signal was used to define suitable parameters of the measurement system and compare different ways of applying the sensor.

  7. Diagnostic device for monitoring the technical condition of mechanical assemblies

    NASA Technical Reports Server (NTRS)

    Osovskiy, V. I.; Shergin, V. V.; Shumilin, V. I.

    1973-01-01

    An automatic diagnostic device for monitoring the condition of tractor transmission gears is described. The structural noise spectrum of the gearshift box and rear axle of the tractor were analyzed in a digital computer, by an algorithm based on the multiple correlation method. The optimum assembly of operating frequencies, by use of which the errors in measurement were minimized, was selected from the entire frequency spectrum. Selected frequencies are necessary for choosing the measurement range of the diagnostic device. It turned out that, to obtain a relative error of no more than 2%, it was sufficient to use two filters, vibrating only at the frequencies carrying the maximum data of the mechanical parameter being investigated. The measurement system consists of frequency-selection filters, amplifiers and quadratic detectors, at the outlets of which constant voltages are created, which are proportional to the signal level at the frequencies selected.

  8. New methods for the condition monitoring of level crossings

    NASA Astrophysics Data System (ADS)

    García Márquez, Fausto Pedro; Pedregal, Diego J.; Roberts, Clive

    2015-04-01

    Level crossings represent a high risk for railway systems. This paper demonstrates the potential to improve maintenance management through the use of intelligent condition monitoring coupled with reliability centred maintenance (RCM). RCM combines advanced electronics, control, computing and communication technologies to address the multiple objectives of cost effectiveness, improved quality, reliability and services. RCM collects digital and analogue signals utilising distributed transducers connected to either point-to-point or digital bus communication links. Assets in many industries use data logging capable of providing post-failure diagnostic support, but to date little use has been made of combined qualitative and quantitative fault detection techniques. The research takes the hydraulic railway level crossing barrier (LCB) system as a case study and develops a generic strategy for failure analysis, data acquisition and incipient fault detection. For each barrier the hydraulic characteristics, the motor's current and voltage, hydraulic pressure and the barrier's position are acquired. In order to acquire the data at a central point efficiently, without errors, a distributed single-cable Fieldbus is utilised. This allows the connection of all sensors through the project's proprietary communication nodes to a high-speed bus. The system developed in this paper for the condition monitoring described above detects faults by means of comparing what can be considered a 'normal' or 'expected' shape of a signal with respect to the actual shape observed as new data become available. ARIMA (autoregressive integrated moving average) models were employed for detecting faults. The statistical tests known as Jarque-Bera and Ljung-Box have been considered for testing the model.

  9. Condition monitoring of gearboxes using synchronously averaged electric motor signals

    NASA Astrophysics Data System (ADS)

    Ottewill, J. R.; Orkisz, M.

    2013-07-01

    Due to their prevalence in rotating machinery, the condition monitoring of gearboxes is extremely important in the minimization of potentially dangerous and expensive failures. Traditionally, gearbox condition monitoring has been conducted using measurements obtained from casing-mounted vibration transducers such as accelerometers. A well-established technique for analyzing such signals is the synchronous signal average, where vibration signals are synchronized to a measured angular position and then averaged from rotation to rotation. Driven, in part, by improvements in control methodologies based upon methods of estimating rotor speed and torque, induction machines are used increasingly in industry to drive rotating machinery. As a result, attempts have been made to diagnose defects using measured terminal currents and voltages. In this paper, the application of the synchronous signal averaging methodology to electric drive signals, by synchronizing stator current signals with a shaft position estimated from current and voltage measurements is proposed. Initially, a test-rig is introduced based on an induction motor driving a two-stage reduction gearbox which is loaded by a DC motor. It is shown that a defect seeded into the gearbox may be located using signals acquired from casing-mounted accelerometers and shaft mounted encoders. Using simple models of an induction motor and a gearbox, it is shown that it should be possible to observe gearbox defects in the measured stator current signal. A robust method of extracting the average speed of a machine from the current frequency spectrum, based on the location of sidebands of the power supply frequency due to rotor eccentricity, is presented. The synchronous signal averaging method is applied to the resulting estimations of rotor position and torsional vibration. Experimental results show that the method is extremely adept at locating gear tooth defects. Further results, considering different loads and different

  10. Microclimate monitoring in the Carcer Tullianum: temporal and spatial correlation and gradients evidenced by multivariate analysis; first campaign

    PubMed Central

    2012-01-01

    Too often microclimate studies in the field of cultural heritage are published without any or scarce information on sampling design, sensors (type, number, position) and instrument validation. Lacking of this fundamental information does not allow an open discussion in the scientific community. This work aims to be an invitation for a different approach. Three main parameters (temperature, humidity, luminance) were monitored in a selected part of a complex construction by an inexpensive self-assembled system along some horizontal and vertical vectors. All data was then processed and analyse by chemometric methods. Some measurements of oxygen, carbon monoxide and dioxide and pressure were also performed. Correlation of some indoor and outdoor data was shown for temperature and humidity. In case of outdoor changes the indoor environment reacted with a certain delay which is position-dependent and more evident for humidity data. The two observed rooms (Carcer and Tullianum) behave differently and the hypogean one is less influenced by the outdoor environment. Instrument validation before and after the campaign, allows to consider detected variations as significant. The fundamental importance of Sampling Design and of instrument validation before and after the monitoring campaign was enhanced. The choice of two main and two minor vectors allowed detection of different behaviour for the two rooms, also permitting to detect for both rooms a trend towards a spontaneous microclimate necessary for a conservation project. In the next campaign we will focus on the choice of the best sampling frequency to use more sophisticated statistical methods. PMID:22594436

  11. The Performance of Cross-Validation Indices Used to Select among Competing Covariance Structure Models under Multivariate Nonnormality Conditions

    ERIC Educational Resources Information Center

    Whittaker, Tiffany A.; Stapleton, Laura M.

    2006-01-01

    Cudeck and Browne (1983) proposed using cross-validation as a model selection technique in structural equation modeling. The purpose of this study is to examine the performance of eight cross-validation indices under conditions not yet examined in the relevant literature, such as nonnormality and cross-validation design. The performance of each…

  12. A modern diagnostic approach for automobile systems condition monitoring

    NASA Astrophysics Data System (ADS)

    Selig, M.; Shi, Z.; Ball, A.; Schmidt, K.

    2012-05-01

    An important topic in automotive research and development is the area of active and passive safety systems. In general, it is grouped in active safety systems to prevent accidents and passive systems to reduce the impact of a crash. An example for an active system is ABS while a seat belt tensioner represents the group of passive systems. Current developments in the automotive industry try to link active with passive system components to enable a complete event sequence, beginning with the warning of the driver about a critical situation till the automatic emergency call after an accident. The cross-linking has an impact on the current diagnostic approach, which is described in this paper. Therefore, this contribution introduces a new diagnostic approach for automotive mechatronic systems. The concept is based on monitoring the messages which are exchanged via the automotive communication systems, e.g. the CAN bus. According to the authors' assumption, the messages on the bus are changing between faultless and faulty vehicle condition. The transmitted messages of the sensors and control units are different depending on the condition of the car. First experiments are carried and in addition, the hardware design of a suitable diagnostic interface is presented. Finally, first results will be presented and discussed.

  13. Application of near-infrared spectroscopy combined with multivariate analysis in monitoring of crude heparin purification process

    NASA Astrophysics Data System (ADS)

    Zang, Hengchang; Wang, Jinfeng; Li, Lian; Zhang, Hui; Jiang, Wei; Wang, Fengshan

    2013-05-01

    Ion-exchange chromatography is a widely used purification technology in the heparin manufacturing process. To improve the efficiency and understand the process directly, a rapid and equally precise method needs to be developed to measure heparin concentration in chromatography process. Here, two robust partial least squares regression (PLS-R) models were established for quantification of heparin based on the near-infrared (NIR) spectroscopy with 80 samples of adsorption process and 76 samples of elution process. Several variables selection algorithms, including correlation coefficient method, successive projection algorithm (SPA) and interval partial least squares (iPLSs), were performed to remove non-informative variables. The results showed that the correlation coefficient of validation (Rp) and the residual predictive deviation (RPD) corresponded to 0.957 and 3.4472 for adsorption process, 0.968 and 3.9849 for elution process, respectively. The approach was found considerable potential for real-time monitoring the heparin concentration of chromatography process.

  14. MONITORING SPENT NUCLEAR FUEL REPROCESSING CONDITIONS NON-DESTRUCTIVELY AND IN NEAR-REAL-TIME USING THE MULTI-ISOTOPE PROCESS (MIP) MONITOR

    SciTech Connect

    Orton, Christopher R.; Fraga, Carlos G.; Douglas, Matthew; Christensen, Richard; Schwantes, Jon M.

    2010-05-07

    Researchers from Pacific Northwest National Laboratory and The Ohio State University are working to develop a system for monitoring spent nuclear fuel reprocessing facilities on-line, nondestructively, and in near-real-time. This method, known as the Multi-Isotope Process (MIP) Monitor, is based upon the measurement of distribution patterns of a suite of indicator (radioactive) isotopes present within product and waste streams of a nuclear reprocessing facility. Signatures from these indicator isotopes are monitored on-line by gamma spectrometry and compared, in near-real-time, to patterns representing "normal" process conditions using multivariate pattern recognition software. By targeting gamma-emitting indicator isotopes, the MIP Monitor approach is compatible with the use of small, portable, high-resolution gamma detectors that may be easily deployed throughout an existing facility. In addition, utilization of a suite of radio-elements, including ones with multiple oxidation states, increases the likelihood that attempts to divert material via process manipulation would be detected. Proof-of-principle modeling exercises simulating changes in acid strength have been completed and the results are promising. Laboratory testing is currently under way and significant results are available. Recent experimental results, along with an overview of the method are presented.

  15. Increasing Potlife of Hall-Héroult Reduction Cells Through Multivariate On-Line Monitoring of Preheating, Start-Up, and Early Operation

    NASA Astrophysics Data System (ADS)

    Tessier, Jayson; Duchesne, Carl; Tarcy, Gary P.; Gauthier, Claude; Dufour, Gilles

    2010-06-01

    Aluminum is produced inside metallurgical reactors known as pots that are replaced at the end of their service life. New pots are preheated, started, and then enter a period known as early operation in which different control strategies are used before entering regular operation. It is known that how preheating, start-up, and early operation are performed can damage a well-designed pot and lead to a shorter service life. However, the impact of these phases with respect to potlife is not well documented quantitatively. In this article, multivariate statistical analysis techniques are used to investigate the impact of pot-to-pot variations during the three phases. A partial least squares regression model is first proposed for predicting potlife, within an error of 90 days, using process data gathered until the end of early operation. This model is also used to identify those variables having the greatest influence on potlife. Finally, multivariate statistical process control charts are proposed to monitor the three steps efficiently. These charts have a low false-alarm rate and can help find the root cause of abnormal operation occurring during the early phases. A few examples are used to illustrate how operators and engineers could use the charts to maintain consistent early operation and help improve mean potlife. Nomenclature: In this article, bold characters are used to identify vectors (bold lowercase), matrices (bold capital), and three-dimensional arrays (bold, underlined capital). Lowercase italics letters are used to define indices. Al—Aluminium; Al2O3—Alumina; C—Carbon; CO2—Carbon dioxide; kA—kilo-Amperes; Na—Sodium; Na3AlF6—Cryolite; V—Volt.

  16. Multivariate Principal Component Analysis and Case-Based Reasoning for monitoring, fault detection and diagnosis in a WWTP.

    PubMed

    Ruiz, Magda; Sin, Gürkan; Berjaga, Xavier; Colprim, Jesús; Puig, Sebastià; Colomer, Joan

    2011-01-01

    The main idea of this paper is to develop a methodology for process monitoring, fault detection and predictive diagnosis of a WasteWater Treatment Plant (WWTP). To achieve this goal, a combination of Multiway Principal Component Analysis (MPCA) and Case-Based Reasoning (CBR) is proposed. First, MPCA is used to reduce the multi-dimensional nature of online process data, which summarises most of the variance of the process data in a few (new) variables. Next, the outputs of MPCA (t-scores, Q-statistic) are provided as inputs (descriptors) to the CBR method, which is employed to identify problems and propose appropriate solutions (hence diagnosis) based on previously stored cases. The methodology is evaluated on a pilot-scale SBR performing nitrogen, phosphorus and COD removal and to help to diagnose abnormal situations in the process operation. Finally, it is believed that the methodology is a promising tool for automatic diagnosis and real-time warning, which can be used for daily management of plant operation. PMID:22335109

  17. Stability conditions of the Vistula Valley attained by a multivariate approach - a case study from the Warsaw Southern Ring Road

    NASA Astrophysics Data System (ADS)

    Kaczmarek, Łukasz; Dobak, Paweł

    2015-12-01

    Localised landslide activity has been observed in the area of the plateau slope analysed, in the vicinity of the planned Warsaw Southern Ring Road. Using calculation models quantitative and qualitative evaluations of the impact of natural and anthropogenic load factors on slope stability (and hence, safety) are made. The present paper defines six stages of slope stability analysis, leading to an indication of optimum slope design in relation to the development planned. The proposed procedure produces a ranking of factors that affect slope stability. In the engineering geological conditions under consideration, the greatest factors impacting degradation and failure of slope stability are changes in soil strength due to local, periodic yielding and the presence of dynamic loads generated by intensification of road traffic. Calculation models were used to assess the impact of destabilisation factors and to obtain mutual equivalence with 3D-visualisation relations. Based on this methodology, various scenarios dedicated to specific engineering geological conditions can be developed and rapid stability evaluations of changing slope loads can be performed.

  18. Monitoring the quality consistency of Weibizhi tablets by micellar electrokinetic chromatography fingerprints combined with multivariate statistical analyses, the simple quantified ratio fingerprint method, and the fingerprint-efficacy relationship.

    PubMed

    Liu, Yingchun; Sun, Guoxiang; Wang, Yan; Yang, Lanping; Yang, Fangliang

    2015-06-01

    Micellar electrokinetic chromatography fingerprinting combined with quantification was successfully developed and applied to monitor the quality consistency of Weibizhi tablets, which is a classical compound preparation used to treat gastric ulcers. A background electrolyte composed of 57 mmol/L sodium borate, 21 mmol/L sodium dodecylsulfate and 100 mmol/L sodium hydroxide was used to separate compounds. To optimize capillary electrophoresis conditions, multivariate statistical analyses were applied. First, the most important factors influencing sample electrophoretic behavior were identified as background electrolyte concentrations. Then, a Box-Benhnken design response surface strategy using resolution index RF as an integrated response was set up to correlate factors with response. RF reflects the effective signal amount, resolution, and signal homogenization in an electropherogram, thus, it was regarded as an excellent indicator. In fingerprint assessments, simple quantified ratio fingerprint method was established for comprehensive quality discrimination of traditional Chinese medicines/herbal medicines from qualitative and quantitative perspectives, by which the quality of 27 samples from the same manufacturer were well differentiated. In addition, the fingerprint-efficacy relationship between fingerprints and antioxidant activities was established using partial least squares regression, which provided important medicinal efficacy information for quality control. The present study offered an efficient means for monitoring Weibizhi tablet quality consistency. PMID:25867134

  19. A knowledge based expert system for condition monitoring

    SciTech Connect

    Selkirk, C.G.; Roberge, P.R.; Fisher, G.F.; Yeung, K.K.

    1994-12-31

    Condition monitoring (CM) is the focus of many maintenance philosophies around the world today. In the Canadian Forces (CF), CM has played an important role in the maintenance of aircraft systems since the introduction of spectrometric oil analysis (SOAP) over twenty years ago. Other techniques in use in the CF today include vibration analysis (VA), ferrography, and filter debris analysis (FDA). To improve the usefulness and utility gained from these CM techniques, work is currently underway to incorporate expert systems into them. An expert system for FDA is being developed which will aid filter debris analysts in identifying wear debris and wear level trends, and which will provide the analyst with reference examples in an attempt to standardize results. Once completed, this knowledge based expert system will provide a blueprint from which other CM expert systems can be created. Amalgamating these specific systems into a broad based global system will provide the CM analyst with a tool that will be able to correlate data and results from each of the techniques, thereby increasing the utility of each individual method of analysis. This paper will introduce FDA and then outline the development of the FDA expert system and future applications.

  20. Structural health monitoring methodology for aircraft condition-based maintenance

    NASA Astrophysics Data System (ADS)

    Saniger, Jordi; Reithler, Livier; Guedra-Degeorges, Didier; Takeda, Nobuo; Dupuis, Jean Pierre

    2001-06-01

    Reducing maintenance costs while keeping a constant level of safety is a major issue for Air Forces and airlines. The long term perspective is to implement condition based maintenance to guarantee a constant safety level while decreasing maintenance costs. On this purpose, the development of a generalized Structural Health Monitoring System (SHMS) is needed. The objective of such a system is to localize the damages and to assess their severity, with enough accuracy to allow low cost corrective actions. The present paper describes a SHMS based on acoustic emission technology. This choice was driven by its reliability and wide use in the aerospace industry. The described SHMS uses a new learning methodology which relies on the generation of artificial acoustic emission events on the structure and an acoustic emission sensor network. The calibrated acoustic emission events picked up by the sensors constitute the knowledge set that the system relies on. With this methodology, the anisotropy of composite structures is taken into account, thus avoiding the major cause of errors of classical localization methods. Moreover, it is adaptive to different structures as it does not rely on any particular model but on measured data. The acquired data is processed and the event's location and corrected amplitude are computed. The methodology has been demonstrated and experimental tests on elementary samples presented a degree of accuracy of 1cm.

  1. Comparison of a Multimetric Index and a Multivariate Predictive Model for Assessing the Biological Condition of Kentucky Streams

    NASA Astrophysics Data System (ADS)

    Pond, G. J.

    2005-05-01

    There is still debate on the strength of various data analysis tools for assessing biological condition in streams. This study compared two popular assessment approaches (multimetric index and RIVPACS-type O/E model) using macroinvertebrates from Kentucky streams. Data from 557 targeted and randomly selected sites (212 reference, 345 non-reference) sampled between 2000 and 2004 were used in this analysis. The Kentucky Macroinvertebrate Bioassessment Index (MBI) combines seven metrics (total generic richness, EPT generic richness, modified HBI, %Ephemeroptera, %EPT minus Cheumatopsyche, %midges+worms, and %clingers) that are scored by standardizing to the 95th or 5th percentile of the reference distribution and averaged. For comparison, three separate genus-level RIVPACS-type models were constructed (high-, low-, and mixed gradient streams) using four predictive variables (area, latitude, longitude, and week number) and taxa from reference sites. All 3 models preformed well but the low gradient model had the lowest precision. Assessments of non-reference sites based on MBI and O/E scores yielded similar results in terms of discrimination efficiency but the model based on mixed-gradient streams was the least sensitive. Using a subset of data from 84 headwater streams in the Appalachian region, MBI and O/E scores responded almost identically to stressors such as conductivity and habitat degradation.

  2. An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions Using Inaccurate or Scarce Information

    NASA Technical Reports Server (NTRS)

    Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.

    2013-01-01

    In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

  3. An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

    NASA Technical Reports Server (NTRS)

    Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.

    2013-01-01

    In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter. In order to increase overall robustness, the vehicle also has an alternate method of triggering the drogue parachute deployment based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this velocity-based trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers excellent performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

  4. An Alternative Flight Software Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

    NASA Technical Reports Server (NTRS)

    Smith, Kelly; Gay, Robert; Stachowiak, Susan

    2013-01-01

    In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles

  5. 10 CFR 20.1502 - Conditions requiring individual monitoring of external and internal occupational dose.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... PROTECTION AGAINST RADIATION Surveys and Monitoring § 20.1502 Conditions requiring individual monitoring of external and internal occupational dose. Each licensee shall monitor exposures to radiation and radioactive... a minimum— (a) Each licensee shall monitor occupational exposure to radiation from licensed...

  6. 10 CFR 20.1502 - Conditions requiring individual monitoring of external and internal occupational dose.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... PROTECTION AGAINST RADIATION Surveys and Monitoring § 20.1502 Conditions requiring individual monitoring of external and internal occupational dose. Each licensee shall monitor exposures to radiation and radioactive... a minimum— (a) Each licensee shall monitor occupational exposure to radiation from licensed...

  7. 10 CFR 20.1502 - Conditions requiring individual monitoring of external and internal occupational dose.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... PROTECTION AGAINST RADIATION Surveys and Monitoring § 20.1502 Conditions requiring individual monitoring of external and internal occupational dose. Each licensee shall monitor exposures to radiation and radioactive... a minimum— (a) Each licensee shall monitor occupational exposure to radiation from licensed...

  8. 10 CFR 20.1502 - Conditions requiring individual monitoring of external and internal occupational dose.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... PROTECTION AGAINST RADIATION Surveys and Monitoring § 20.1502 Conditions requiring individual monitoring of external and internal occupational dose. Each licensee shall monitor exposures to radiation and radioactive... a minimum— (a) Each licensee shall monitor occupational exposure to radiation from licensed...

  9. Investigation of Various Condition Monitoring Techniques Based on a Damaged Wind Turbine Gearbox

    SciTech Connect

    Sheng, S.

    2011-10-01

    This paper is a continuation of a 2009 paper presented at the 7th International Workshop on Structural Health Monitoring that described various wind turbine condition-monitoring techniques. This paper presents the results obtained by various condition- monitoring techniques from a damaged Gearbox Reliability Collaborative test gearbox.

  10. Multivariate normality

    NASA Technical Reports Server (NTRS)

    Crutcher, H. L.; Falls, L. W.

    1976-01-01

    Sets of experimentally determined or routinely observed data provide information about the past, present and, hopefully, future sets of similarly produced data. An infinite set of statistical models exists which may be used to describe the data sets. The normal distribution is one model. If it serves at all, it serves well. If a data set, or a transformation of the set, representative of a larger population can be described by the normal distribution, then valid statistical inferences can be drawn. There are several tests which may be applied to a data set to determine whether the univariate normal model adequately describes the set. The chi-square test based on Pearson's work in the late nineteenth and early twentieth centuries is often used. Like all tests, it has some weaknesses which are discussed in elementary texts. Extension of the chi-square test to the multivariate normal model is provided. Tables and graphs permit easier application of the test in the higher dimensions. Several examples, using recorded data, illustrate the procedures. Tests of maximum absolute differences, mean sum of squares of residuals, runs and changes of sign are included in these tests. Dimensions one through five with selected sample sizes 11 to 101 are used to illustrate the statistical tests developed.

  11. MONITORING STREAM CONDITION IN THE WESTERN UNITED STATES

    EPA Science Inventory


    The U.S. Environmental Protection Agency Environmental Monitoring and Assessment Program (EMAP) is a national research program to develop the tools necessary to monitor and assess the- status and trends of ecological resources. EMAP's goal is to develop the scientific underst...

  12. Monitoring and Reporting Hospital-Acquired Conditions: A Federalist Approach

    PubMed Central

    West, Nathan; Eng, Terry

    2015-01-01

    Background Serious adverse events that occur in hospitals rank as a leading cause of preventable death in the United States. Many states operate reporting systems to monitor and publicly report serious adverse events, a subset that falls under Medicare’s Hospital-Acquired Conditions (HACs). Purpose(s) Identify and describe state efforts, and the supporting role of federal initiatives, to track and report HACs and other serious adverse events. Data Sources Document review of state and federal reports, databases, and policies for HACs and other serious adverse events; conduct semi-structured telephone interviews with state health department officials and directors of patient safety organizations. Results Thirty-two states and the District of Columbia (D.C.) track at least one Medicare HAC. Five states collect nearly all ten Medicare HACs (9–10). Eighteen states and D.C. track events through both a state-based reporting system and the Centers for Disease Control National Healthcare Safety Network (NHSN) for health-care associated infections (HAI). For serious adverse events, most states either partially or fully adopted the National Quality Forum’s Serious Reportable Events. For HAIs, thirty states and D.C. mandate reporting through NHSN. States interviewed reported that Medicare’s choice of HACs for nonpayment had at least a partial influence on which serious adverse events required reporting. Conclusions Many states use the collected data on HACs and other events for quality improvement initiatives and to provide greater transparency through public reporting. More work and research is needed to develop a national reporting system template that has standard definitions, methodology, and reporting. PMID:25584196

  13. Raman and surface-enhanced Raman spectroscopy for renal condition monitoring

    NASA Astrophysics Data System (ADS)

    Li, Jingting; Li, Ming; Du, Yong; Santos, Greggy M.; Mohan, Chandra; Shih, Wei-Chuan

    2016-03-01

    Non- and minimally-invasive techniques can provide advantages in the monitoring and clinical diagnostics in renal diseases. Although renal biopsy may be useful in establishing diagnosis in several diseases, it is an invasive approach and impractical for longitudinal disease monitoring. To address this unmet need, we have developed two techniques based on Raman spectroscopy. First, we have investigated the potential of diagnosing and staging nephritis by analyzing kidney tissue Raman spectra using multivariate techniques. Secondly, we have developed a urine creatinine sensor based on surface-enhanced Raman spectroscopy with performance near commercial assays which require relatively laborious sample preparation and longer time.

  14. BIRD COMMUNITIES AND HABITAT AS ECOLOGICAL INDICATORS OF FOREST CONDITION IN REGIONAL MONITORING

    EPA Science Inventory

    Ecological indicators for long-term monitoring programs are needed to detect and assess changing environmental conditions, We developed and tested community-level environmental indicators for monitoring forest bird populations and associated habitat. We surveyed 197 sampling plo...

  15. Wetlands monitoring - hydrological conditions and water quality in selected transects of Biebrza National Park.

    NASA Astrophysics Data System (ADS)

    Stelmaszczyk, Mateusz; Okruszko, Tomasz

    2010-05-01

    . Studied locations were covered mainly by Magnocaricion vegetation (e.g. Caricetum gracilis and Caricetum elatae), Molinio-Arrhenatheretea vegetation (Molinietum caeruleae), and Scheuchzerio-Caricetea nigrae vegetation (e.g. Caricetum lasiocarpae). In presented work authors show results of water quality measurements and monitoring of hydrological conditions, characterized by changes of groundwater table, period and size of inundation. During six years long monitoring period (2004 - 2009 hydrological years) there were observed high diversification of groundwater and surface water levels among locations. They fluctuate in some places from very low groundwater levels, observed in late summer and in early autumn (over 1 m beneath the ground), to levels reaching surface of the ground or laying nearly below it, occurring in winter and spring. There are also places where quite high inundations in winter and spring are observed. Collected chemical and hydrological data were statistically analyzed using STATISTICA 8 software with a use of one of the multivariate analysis - Principal Component Analysis (PCA) method. Owing to the usage of PCA analysis it was possible to define most important parameters characterizing habitats were occurs selected vegetation. The impact of hydrological conditions (presented as a main factor) on forming particular wetland plant communities can be discussed. Authors determine that some other factors (e.g. management) can be more responsible for occurrence of particular plant communities and their sustaining in good status in specific locations.

  16. Low-cost micro condition monitoring system based on LabVIEW and SQL server

    NASA Astrophysics Data System (ADS)

    Jia, Zhizhou; Guo, Yu; Fan, Yajun

    2013-03-01

    Due to most of the existing condition monitoring systems have a rather complicated structure and the high cost makes even big companies can only afford on a few key equipments, a developing scheme of low-cost micro condition monitoring system based on LabVIEW and SQL Server is proposed in this paper. The low-cost micro condition monitoring system can realize the effective monitoring to general machinery by full taking the advantages of LabVIEW and SQL Server respectively. The system supplements the existing condition monitoring systems to some extent. It affords good applicability and expanding ability, which make it suitable for the equipment management of enterprises for general equipment condition monitoring and health maintenance.

  17. Machine condition monitoring using neural networks and the likelihood function

    SciTech Connect

    Vilim, R.B.; Garcia, H.E.; Chen, F.W.

    1997-09-01

    A model-based technique incorporating neural networks has been developed for process monitoring. The technique is intended for processes where the uncertainty in the reference model is larger than desired but where process measurements providing additional information about the behavior of the system are available. This data is used to reduce the uncertainty of the model. The technique has been implemented in a real-time system for monitoring operational changes of mechanical equipment for use in predictive maintenance applications. Tests on a peristaltic pump were conducted and demonstrate the advantages of the proposed technique.

  18. VARIOGRAPHY AND CONDITIONAL SEQUENTIAL SIMULATION: NEW TOOLS FOR ECOLOGICAL MONITORING

    EPA Science Inventory

    The Superfund reauthorization Act requires an ecological impact statement as part of each site assessment. his is difficult because of the hierarchical multiple dimensionality of ecosystems and becaus of the limited time and resources for the site's monitoring and evaluation. he ...

  19. 40 CFR 141.625 - Conditions requiring increased monitoring.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Stage 2 Disinfection Byproducts... monitoring to dual sample sets once per quarter (taken every 90 days) at all locations if a TTHM sample is >0.080 mg/L or a HAA5 sample is >0.060 mg/L at any location. (b) You are in violation of the MCL when...

  20. Wireless sensor network for monitoring soil moisture and weather conditions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A wireless sensor network (WSN) was developed and deployed in three fields to monitor soil water status and collect weather data for irrigation scheduling. The WSN consists of soil-water sensors, weather sensors, wireless data loggers, and a wireless modem. Soil-water sensors were installed at three...

  1. An online technique for condition monitoring the induction generators used in wind and marine turbines

    NASA Astrophysics Data System (ADS)

    Yang, Wenxian; Tavner, P. J.; Court, R.

    2013-07-01

    Induction generators have been successfully applied to a variety of industries. However, their operation and maintenance in renewable wind and marine energy industries still face challenges due to harsh environments, limited access to site and relevant reliability issues. Hence, further enhancing their condition monitoring is regarded as one of the essential measures for improving their availability. To date, much effort has been made to monitor induction motors, which can be equally applied to monitoring induction generators. However, the achieved techniques still have constrains in particular when dealing with the condition monitoring problems in wind and marine turbine generators. For example, physical measurements of partial discharge, noise and temperature have been widely applied to monitoring induction machinery. They are simple and cost-effective, but unable to be used for fault diagnosis. The spectral analysis of vibration and stator current signals is also a mature technique popularly used in motor/generator condition monitoring practice. However, it often requires sufficient expertise for data interpretation, and significant pre-knowledge about the machines and their components. In particular in renewable wind and marine industries, the condition monitoring results are usually coupled with load variations, which further increases the difficulty of obtaining a reliable condition monitoring result. In view of these issues, a new condition monitoring technique is developed in this paper dedicated for wind and marine turbine generators. It is simple, informative and less load-dependent thus more reliable to deal with the online motor/generator condition monitoring problems under varying loading conditions. The technique has been verified through both simulated and practical experiments. It has been shown that with the aid of the proposed technique, not only the electrical faults but also the shaft unbalance occurring in the generator become detectable

  2. Chiller condition monitoring using topological case-based modeling

    SciTech Connect

    Tsutsui, Hiroaki; Kamimura, Kazuyuki

    1996-11-01

    To increase energy efficiency and economy, commercial building projects now often utilize centralized, shared sources of heat such as district heating and cooling (DHC) systems. To maintain efficiency, precise monitoring and scheduling of maintenance for chillers and heat pumps is essential. Low-performance operation results in energy loss, while unnecessary maintenance is expensive and wasteful. Plant supervisors are responsible for scheduling and supervising maintenance. Modeling systems that assist in analyzing system deterioration are of great benefit for these tasks. Topological case-based modeling (TCBM) (Tsutsui et al. 1993; Tsutsui 1995) is an effective tool for chiller performance deterioration monitoring. This paper describes TCBM and its application to this task using recorded historical performance data.

  3. Monitor weather conditions for cloud seeding control. [Colorado River Basin

    NASA Technical Reports Server (NTRS)

    Kahan, A. M. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. The near real-time DCS platform data transfer to the time-share compare is a working reality. Six stations are now being automatically monitored and displayed with a system delay of 3 to 8 hours from time of data transmission to time of data accessibility on the computer. The DCS platform system has proven itself a valuable tool for near real-time monitoring of mountain precipitation. Data from Wolf Creek Pass were an important input in making the decision when to suspend seeding operations to avoid exceeding suspension criteria in that area. The DCS platforms, as deployed in this investigation, have proven themselves to be reliable weather resistant systems for winter mountain environments in the southern Colorado mountains.

  4. 77 FR 24228 - Condition Monitoring Techniques for Electric Cables Used in Nuclear Power Plants

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-23

    ... COMMISSION Condition Monitoring Techniques for Electric Cables Used in Nuclear Power Plants AGENCY: Nuclear... Techniques for Electric Cables Used in Nuclear Power Plants.'' This guide describes techniques that the staff of the NRC considers acceptable for condition monitoring of electric cables for nuclear power...

  5. Development of GUI Type On-Line Condition Monitoring Program for a Turboprop Engine Using Labview

    NASA Astrophysics Data System (ADS)

    Kong, Changduk; Kim, Keonwoo

    2011-12-01

    Recently, an aero gas turbine health monitoring system has been developed for precaution and maintenance action against faults or performance degradations of the advanced propulsion system which occurs in severe environments such as high altitude, foreign object damage particles, hot and heavy rain and snowy atmospheric conditions. However to establish this health monitoring system, the online condition monitoring program is firstly required, and the program must monitor the engine performance trend through comparison between measured engine performance data and base performance results calculated by base engine performance model. This work aims to develop a GUI type on-line condition monitoring program for the PT6A-67 turboprop engine of a high altitude and long endurance operation UAV using LabVIEW. The base engine performance of the on-line condition monitoring program is simulated using component maps inversely generated from the limited performance deck data provided by engine manufacturer. The base engine performance simulation program is evaluated because analysis results by this program agree well with the performance deck data. The proposed on-line condition program can monitor the real engine performance as well as the trend through precise comparison between clean engine performance results calculated by the base performance simulation program and measured engine performance signals. In the development phase of this monitoring system, a signal generation module is proposed to evaluate the proposed online monitoring system. For user friendly purpose, all monitoring program are coded by LabVIEW, and monitoring examples are demonstrated using the proposed GUI type on-condition monitoring program.

  6. Optical methods for hydrogen degassing monitoring in urban conditions

    NASA Astrophysics Data System (ADS)

    Timchenko, E. V.; Timchenko, P. E.; Zherdeva, L. A.; Tregub, N. V.; Selezneva, E. A.; Yakovlev, V. N.

    2015-12-01

    Results of a study of variations in optical parameters of bioindicators that grow in the regions of hydrogen degassing in Samara are presented. Raman spectroscopy and confocal fluorescence microscopy were used as the main methods of the study. Features of Raman spectra of plants that grow in zones with presence/ absence of deep hydrogen emissions have been ascertained. The main variations have been recorded at wavenumbers of 1380, 1522, 1547, and 1600 cm-1, which are responsible for stretching vibrations in lignin and β-carotene and chlorophyll a and cellulose in plant leaves. Confocal fluorescence microscopy showed an increase in the chloroplasts in leaves of plants which grow at hydrogen degassing territories. An optical coefficient was introduced, on the basis of which the Samara region was monitored.

  7. PROCESS OF SELECTING INDICATORS FOR MONITORING CONDITIONS OF RANGELAND HEALTH

    EPA Science Inventory

    This paper reports on a process for selecting a suite of indicators that, in combination, can be useful in assessing the ecological conditions of rangelands. onceptual models that depict the structural and functional properties of ecological processes were used to show the linkag...

  8. Planetary gearbox condition monitoring of ship-based satellite communication antennas using ensemble multiwavelet analysis method

    NASA Astrophysics Data System (ADS)

    Chen, Jinglong; Zhang, Chunlin; Zhang, Xiaoyan; Zi, Yanyang; He, Shuilong; Yang, Zhe

    2015-03-01

    Satellite communication antennas are key devices of a measurement ship to support voice, data, fax and video integration services. Condition monitoring of mechanical equipment from the vibration measurement data is significant for guaranteeing safe operation and avoiding the unscheduled breakdown. So, condition monitoring system for ship-based satellite communication antennas is designed and developed. Planetary gearboxes play an important role in the transmission train of satellite communication antenna. However, condition monitoring of planetary gearbox still faces challenges due to complexity and weak condition feature. This paper provides a possibility for planetary gearbox condition monitoring by proposing ensemble a multiwavelet analysis method. Benefit from the property on multi-resolution analysis and the multiple wavelet basis functions, multiwavelet has the advantage over characterizing the non-stationary signal. In order to realize the accurate detection of the condition feature and multi-resolution analysis in the whole frequency band, adaptive multiwavelet basis function is constructed via increasing multiplicity and then vibration signal is processed by the ensemble multiwavelet transform. Finally, normalized ensemble multiwavelet transform information entropy is computed to describe the condition of planetary gearbox. The effectiveness of proposed method is first validated through condition monitoring of experimental planetary gearbox. Then this method is used for planetary gearbox condition monitoring of ship-based satellite communication antennas and the results support its feasibility.

  9. A remote condition monitoring system for wind-turbine based DG systems

    NASA Astrophysics Data System (ADS)

    Ma, X.; Wang, G.; Cross, P.; Zhang, X.

    2012-05-01

    In this paper, a remote condition monitoring system is proposed, which fundamentally consists of real-time monitoring modules on the plant side, a remote support centre and the communications between them. The paper addresses some of the key issues related on the monitoring system, including i) the implementation and configuration of a VPN connection, ii) an effective database system to be able to handle huge amount of monitoring data, and iii) efficient data mining techniques to convert raw data into useful information for plant assessment. The preliminary results have demonstrated that the proposed system is practically feasible and can be deployed to monitor the emerging new energy generation systems.

  10. Health Monitoring and Management for Manufacturing Workers in Adverse Working Conditions.

    PubMed

    Xu, Xiaoya; Zhong, Miao; Wan, Jiafu; Yi, Minglun; Gao, Tiancheng

    2016-10-01

    In adverse working conditions, environmental parameters such as metallic dust, noise, and environmental temperature, directly affect the health condition of manufacturing workers. It is therefore important to implement health monitoring and management based on important physiological parameters (e.g., heart rate, blood pressure, and body temperature). In recent years, new technologies, such as body area networks, cloud computing, and smart clothing, have allowed the improvement of the quality of services. In this article, we first give five-layer architecture for health monitoring and management of manufacturing workers. Then, we analyze the system implementation process, including environmental data processing, physical condition monitoring and system services and management, and present the corresponding algorithms. Finally, we carry out an evaluation and analysis from the perspective of insurance and compensation for manufacturing workers in adverse working conditions. The proposed scheme will contribute to the improvement of workplace conditions, realize health monitoring and management, and protect the interests of manufacturing workers. PMID:27624491

  11. A NATIONAL PROGRAM FOR MONITORING STREAM CONDITION IN THE WESTERN UNITED STATES

    EPA Science Inventory


    The U.S. Environmental Protection Agency recently initiated a four-year survey of streams in the Western United States as a component of the Environmental Monitoring and Assessment Program (EMAP). EMAP is developing indicators to monitor and assess the condition of ecological...

  12. Monitoring network-design influence on assessment of ecological condition in wadeable streams

    EPA Science Inventory

    We investigated outcomes of three monitoring networks for assessing ecological character and condition of wadeable streams in the Waikato region, New Zealand. Sites were selected 1) based on a professional judgment network, 2) within categories of stream and watershed characteris...

  13. Operational-Condition-Independent Criteria Dedicated to Monitoring Wind Turbine Generators: Preprint

    SciTech Connect

    Yang, W.; Sheng, S.; Court, R.

    2012-08-01

    To date the existing wind turbine condition monitoring technologies and commercially available systems have not been fully accepted for improving wind turbine availability and reducing their operation and maintenance costs. One of the main reasons is that wind turbines are subject to constantly varying loads and operate at variable rotational speeds. As a consequence, the influences of turbine faults and the effects of varying load and speed are coupled together in wind turbine condition monitoring signals. So, there is an urgent need to either introduce some operational condition de-coupling procedures into the current wind turbine condition monitoring techniques or develop a new operational condition independent wind turbine condition monitoring technique to maintain high turbine availability and achieve the expected economic benefits from wind. The purpose of this paper is to develop such a technique. In the paper, three operational condition independent criteria are developed dedicated for monitoring the operation and health condition of wind turbine generators. All proposed criteria have been tested through both simulated and practical experiments. The experiments have shown that these criteria provide a solution for detecting both mechanical and electrical faults occurring in wind turbine generators.

  14. Combination of process and vibration data for improved condition monitoring of industrial systems working under variable operating conditions

    NASA Astrophysics Data System (ADS)

    Ruiz-Cárcel, C.; Jaramillo, V. H.; Mba, D.; Ottewill, J. R.; Cao, Y.

    2016-01-01

    The detection and diagnosis of faults in industrial processes is a very active field of research due to the reduction in maintenance costs achieved by the implementation of process monitoring algorithms such as Principal Component Analysis, Partial Least Squares or more recently Canonical Variate Analysis (CVA). Typically the condition of rotating machinery is monitored separately using vibration analysis or other specific techniques. Conventional vibration-based condition monitoring techniques are based on the tracking of key features observed in the measured signal. Typically steady-state loading conditions are required to ensure consistency between measurements. In this paper, a technique based on merging process and vibration data is proposed with the objective of improving the detection of mechanical faults in industrial systems working under variable operating conditions. The capabilities of CVA for detection and diagnosis of faults were tested using experimental data acquired from a compressor test rig where different process faults were introduced. Results suggest that the combination of process and vibration data can effectively improve the detectability of mechanical faults in systems working under variable operating conditions.

  15. Comparison of multispectral remote-sensing techniques for monitoring subsurface drain conditions. [Imperial Valley, California

    NASA Technical Reports Server (NTRS)

    Goettelman, R. C.; Grass, L. B.; Millard, J. P.; Nixon, P. R.

    1983-01-01

    The following multispectral remote-sensing techniques were compared to determine the most suitable method for routinely monitoring agricultural subsurface drain conditions: airborne scanning, covering the visible through thermal-infrared (IR) portions of the spectrum; color-IR photography; and natural-color photography. Color-IR photography was determined to be the best approach, from the standpoint of both cost and information content. Aerial monitoring of drain conditions for early warning of tile malfunction appears practical. With careful selection of season and rain-induced soil-moisture conditions, extensive regional surveys are possible. Certain locations, such as the Imperial Valley, Calif., are precluded from regional monitoring because of year-round crop rotations and soil stratification conditions. Here, farms with similar crops could time local coverage for bare-field and saturated-soil conditions.

  16. Application of Condition-Based Monitoring Techniques for Remote Monitoring of a Simulated Gas Centrifuge Enrichment Plant

    SciTech Connect

    Hooper, David A; Henkel, James J; Whitaker, Michael

    2012-01-01

    This paper presents research into the adaptation of monitoring techniques from maintainability and reliability (M&R) engineering for remote unattended monitoring of gas centrifuge enrichment plants (GCEPs) for international safeguards. Two categories of techniques are discussed: the sequential probability ratio test (SPRT) for diagnostic monitoring, and sequential Monte Carlo (SMC or, more commonly, particle filtering ) for prognostic monitoring. Development and testing of the application of condition-based monitoring (CBM) techniques was performed on the Oak Ridge Mock Feed and Withdrawal (F&W) facility as a proof of principle. CBM techniques have been extensively developed for M&R assessment of physical processes, such as manufacturing and power plants. These techniques are normally used to locate and diagnose the effects of mechanical degradation of equipment to aid in planning of maintenance and repair cycles. In a safeguards environment, however, the goal is not to identify mechanical deterioration, but to detect and diagnose (and potentially predict) attempts to circumvent normal, declared facility operations, such as through protracted diversion of enriched material. The CBM techniques are first explained from the traditional perspective of maintenance and reliability engineering. The adaptation of CBM techniques to inspector monitoring is then discussed, focusing on the unique challenges of decision-based effects rather than equipment degradation effects. These techniques are then applied to the Oak Ridge Mock F&W facility a water-based physical simulation of a material feed and withdrawal process used at enrichment plants that is used to develop and test online monitoring techniques for fully information-driven safeguards of GCEPs. Advantages and limitations of the CBM approach to online monitoring are discussed, as well as the potential challenges of adapting CBM concepts to safeguards applications.

  17. A New Experimental Method for in Situ Corrosion Monitoring Under Alternate Wet-Dry Conditions

    PubMed Central

    Fu, Xinxin; Dong, Junhua; Han, Enhou; Ke, Wei

    2009-01-01

    A new experimental method was applied in in situ corrosion monitoring of mild steel Q235 under alternate wet-dry conditions. The thickness of the electrolyte film during the wet cycle was monitored by a high-precision balance with a sensibility of 0.1 mg. At the same time, an electrochemical impedance technique was employed to study the effect of film thickness on corrosion rates. Experimental results showed that there was a critical electrolyte film condition for which the corrosion rate reached a maximum during wet-dry cycles. For the substrate, the critical condition could be described by a film thickness of about 17 μm. For the rusted specimen, the critical condition could be described by an electrolyte amount of about 0.038 g, which is equivalent to a film thickness of 38 μm. This monitoring system was very useful for studying atmospheric corrosion of metals covered by corrosion products. PMID:22303180

  18. A new experimental method for in situ corrosion monitoring under alternate wet-dry conditions.

    PubMed

    Fu, Xinxin; Dong, Junhua; Han, Enhou; Ke, Wei

    2009-01-01

    A new experimental method was applied in in situ corrosion monitoring of mild steel Q235 under alternate wet-dry conditions. The thickness of the electrolyte film during the wet cycle was monitored by a high-precision balance with a sensibility of 0.1 mg. At the same time, an electrochemical impedance technique was employed to study the effect of film thickness on corrosion rates. Experimental results showed that there was a critical electrolyte film condition for which the corrosion rate reached a maximum during wet-dry cycles. For the substrate, the critical condition could be described by a film thickness of about 17 μm. For the rusted specimen, the critical condition could be described by an electrolyte amount of about 0.038 g, which is equivalent to a film thickness of 38 μm. This monitoring system was very useful for studying atmospheric corrosion of metals covered by corrosion products. PMID:22303180

  19. Monitoring cutting tool operation and condition with a magnetoelastic rate of change of torque sensor

    SciTech Connect

    Garshelis, Ivan J.; Kari, Ryan J.; Tollens, Stijn P. L.; Cuseo, James M.

    2008-04-01

    Application of a magnetoelastic rate of change of torque sensor to monitor the condition of milling cutters and operating parameters is described. Cutting tools naturally degrade with use by wear, chipping, or fracture, and the efficiency and quality of the product are highly dependent on the tool condition. The theoretical analysis is compared to experimental data in detecting changes in torque during each cutting event, and the rate of change of torque signal is investigated for a variety of cutting tool conditions.

  20. Chemometric methods applied to the calibration of a Vis-NIR sensor for gas engine's condition monitoring.

    PubMed

    Villar, Alberto; Gorritxategi, Eneko; Otaduy, Deitze; Ciria, Jose I; Fernandez, Luis A

    2011-10-31

    This paper describes the calibration process of a Visible-Near Infrared sensor for the condition monitoring of a gas engine's lubricating oil correlating transmittance oil spectra with the degradation of a gas engine's oil via a regression model. Chemometric techniques were applied to determine different parameters: Base Number (BN), Acid Number (AN), insolubles in pentane and viscosity at 40 °C. A Visible-Near Infrared (400-1100 nm) sensor developed in Tekniker research center was used to obtain the spectra of artificial and real gas engine oils. In order to improve sensor's data, different preprocessing methods such as smoothing by Saviztky-Golay, moving average with Multivariate Scatter Correction or Standard Normal Variate to eliminate the scatter effect were applied. A combination of these preprocessing methods was applied to each parameter. The regression models were developed by Partial Least Squares Regression (PLSR). In the end, it was shown that only some models were valid, fulfilling a set of quality requirements. The paper shows which models achieved the established validation requirements and which preprocessing methods perform better. A discussion follows regarding the potential improvement in the robustness of the models. PMID:21962360

  1. Development of a real time monitor and multivariate method for long term diagnostics of atmospheric pressure dielectric barrier discharges: application to He, He/N2, and He/O2 discharges.

    PubMed

    O'Connor, N; Milosavljević, V; Daniels, S

    2011-08-01

    In this paper we present the development and application of a real time atmospheric pressure discharge monitoring diagnostic. The software based diagnostic is designed to extract latent electrical and optical information associated with the operation of an atmospheric pressure dielectric barrier discharge (APDBD) over long time scales. Given that little is known about long term temporal effects in such discharges, the diagnostic methodology is applied to the monitoring of an APDBD in helium and helium with both 0.1% nitrogen and 0.1% oxygen gas admixtures over periods of tens of minutes. Given the large datasets associated with the experiments, it is shown that this process is much expedited through the novel application of multivariate correlations between the electrical and optical parameters of the corresponding chemistries which, in turn, facilitates comparisons between each individual chemistry also. The results of these studies show that the electrical and optical parameters of the discharge in helium and upon the addition of gas admixtures evolve over time scales far longer than the gas residence time and have been compared to current modelling works. It is envisaged that the diagnostic together with the application of multivariate correlations will be applied to rapid system identification and prototyping in both experimental and industrial APDBD systems in the future. PMID:21895242

  2. Condition Monitoring and Fault Diagnosis of Wet-Shift Clutch Transmission Based on Multi-technology

    NASA Astrophysics Data System (ADS)

    Chen, Man; Wang, Liyong; Ma, Biao

    Based on the construction feature and operating principle of the wet-shift clutch transmission, the condition monitoring and fault diagnosis for the transmission of the tracklayer with wet-shift clutch were implemented with using the oil analysis technology, function parameter test method and vibration analysis technology. The new fault diagnosis methods were proposed, which are to build the gray modeling with the oil analysis data, and to test the function parameter of the clutch press, the rotate speed of each gear, the oil press of the steer system and lubrication system and the hydraulic torque converter. It's validated that the representative function signals were chosen to execute the condition monitoring analysis, when the fault symptoms were found, and the oil analysis data were used to apply the gray modeling to forecast the fault occurs time can satisfy the demand of the condition monitoring and fault diagnosis for the transmission regular work.

  3. A time-frequency analysis approach for condition monitoring of a wind turbine gearbox under varying load conditions

    NASA Astrophysics Data System (ADS)

    Antoniadou, I.; Manson, G.; Staszewski, W. J.; Barszcz, T.; Worden, K.

    2015-12-01

    This paper deals with the condition monitoring of wind turbine gearboxes under varying operating conditions. Generally, gearbox systems include nonlinearities so a simplified nonlinear gear model is developed, on which the time-frequency analysis method proposed is first applied for the easiest understanding of the challenges faced. The effect of varying loads is examined in the simulations and later on in real wind turbine gearbox experimental data. The Empirical Mode Decomposition (EMD) method is used to decompose the vibration signals into meaningful signal components associated with specific frequency bands of the signal. The mode mixing problem of the EMD is examined in the simulation part and the results in that part of the paper suggest that further research might be of interest in condition monitoring terms. For the amplitude-frequency demodulation of the signal components produced, the Hilbert Transform (HT) is used as a standard method. In addition, the Teager-Kaiser energy operator (TKEO), combined with an energy separation algorithm, is a recent alternative method, the performance of which is tested in the paper too. The results show that the TKEO approach is a promising alternative to the HT, since it can improve the estimation of the instantaneous spectral characteristics of the vibration data under certain conditions.

  4. Monitoring lining and hearth conditions at Inland`s No. 7 blast furnace

    SciTech Connect

    Quisenberry, P.; Grant, M.; Carter, W.

    1997-12-31

    The paper describes: furnace statistics; mini-reline undertaken in November, 1993; the stack condition; throat gunning; stabilizing the graphite bricks; the hearth condition; reactions to temperature excursions; future instrumentation; and hot blast system areas of concern. The present data from monitoring systems and inspections indicate that the furnace should be able to operate well beyond the expectation for the 1993 mini-reline (3--5 years) with: (1) consistent, high quality raw materials; (2) instrumentation, diagnostic, remedial, and preventative techniques developed; and (3) stopping quickly any water leaks into the furnace. The longevity of this campaign has undoubtedly been a result of this monitoring program.

  5. A Wavelet Bicoherence-Based Quadratic Nonlinearity Feature for Translational Axis Condition Monitoring

    PubMed Central

    Li, Yong; Wang, Xiufeng; Lin, Jing; Shi, Shengyu

    2014-01-01

    The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM) has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features. PMID:24473281

  6. A wavelet bicoherence-based quadratic nonlinearity feature for translational axis condition monitoring.

    PubMed

    Li, Yong; Wang, Xiufeng; Lin, Jing; Shi, Shengyu

    2014-01-01

    The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM) has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features. PMID:24473281

  7. A New Application of Support Vector Machine Method: Condition Monitoring and Analysis of Reactor Coolant Pump

    NASA Astrophysics Data System (ADS)

    Meng, Qinghu; Meng, Qingfeng; Feng, Wuwei

    2012-05-01

    Fukushima nuclear power plant accident caused huge losses and pollution and it showed that the reactor coolant pump is very important in a nuclear power plant. Therefore, to keep the safety and reliability, the condition of the coolant pump needs to be online condition monitored and fault analyzed. In this paper, condition monitoring and analysis based on support vector machine (SVM) is proposed. This method is just to aim at the small sample studies such as reactor coolant pump. Both experiment data and field data are analyzed. In order to eliminate the noise and useless frequency, these data are disposed through a multi-band FIR filter. After that, a fault feature selection method based on principal component analysis is proposed. The related variable quantity is changed into unrelated variable quantity, and the dimension is descended. Then the SVM method is used to separate different fault characteristics. Firstly, this method is used as a two-kind classifier to separate each two different running conditions. Then the SVM is used as a multiple classifier to separate all of the different condition types. The SVM could separate these conditions successfully. After that, software based on SVM was designed for reactor coolant pump condition analysis. This software is installed on the reactor plant control system of Qinshan nuclear power plant in China. It could monitor the online data and find the pump mechanical fault automatically.

  8. Recommendations for strengthening the infrared technology component of any condition monitoring program

    NASA Astrophysics Data System (ADS)

    Nicholas, Jack R., Jr.; Young, R. K.

    1999-03-01

    This presentation provides insights of a long term 'champion' of many condition monitoring technologies and a Level III infra red thermographer. The co-authors present recommendations based on their observations of infra red and other components of predictive, condition monitoring programs in manufacturing, utility and government defense and energy activities. As predictive maintenance service providers, trainers, informal observers and formal auditors of such programs, the co-authors provide a unique perspective that can be useful to practitioners, managers and customers of advanced programs. Each has over 30 years experience in the field of machinery operation, maintenance, and support the origins of which can be traced to and through the demanding requirements of the U.S. Navy nuclear submarine forces. They have over 10 years each of experience with programs in many different countries on 3 continents. Recommendations are provided on the following: (1) Leadership and Management Support (For survival); (2) Life Cycle View (For establishment of a firm and stable foundation for a program); (3) Training and Orientation (For thermographers as well as operators, managers and others); (4) Analyst Flexibility (To innovate, explore and develop their understanding of machinery condition); (5) Reports and Program Justification (For program visibility and continued expansion); (6) Commitment to Continuous Improvement of Capability and Productivity (Through application of updated hardware and software); (7) Mutual Support by Analysts (By those inside and outside of the immediate organization); (8) Use of Multiple Technologies and System Experts to Help Define Problems (Through the use of correlation analysis of data from up to 15 technologies. An example correlation analysis table for AC and DC motors is provided.); (9) Root Cause Analysis (Allows a shift from reactive to proactive stance for a program); (10) Master Equipment Identification and Technology Application (To

  9. Railway track component condition monitoring using optical fibre Bragg grating sensors

    NASA Astrophysics Data System (ADS)

    Buggy, S. J.; James, S. W.; Staines, S.; Carroll, R.; Kitson, P.; Farrington, D.; Drewett, L.; Jaiswal, J.; Tatam, R. P.

    2016-05-01

    The use of optical fibre Bragg grating (FBG) strain sensors to monitor the condition of safety critical rail components is investigated. Fishplates, switchblades and stretcher bars on the Stagecoach Supertram tramway in Sheffield in the UK have been instrumented with arrays of FBG sensors. The dynamic strain signatures induced by the passage of a tram over the instrumented components have been analysed to identify features indicative of changes in the condition of the components.

  10. Monitoring of WUT grand hall roof in conditions of high temperature changes

    NASA Astrophysics Data System (ADS)

    Wozniak, M.

    2009-04-01

    The geodetic control measurements of changes in object's geometry should satisfy high accuracy and reliability. New tacheometers equipped with Automatic Target Recognition automatically moves the telescope to the center of the prism and supports control points measurements. The accuracy of using ATR system and stability of instrument in precise measurements were controlled in laboratory and field conditions. This paper will present the results of monitoring measurements using Leica TDA 5005 during investigations of roof geometry in conditions of high temperature changes.

  11. A Recursive Multiscale Correlation-Averaging Algorithm for an Automated Distributed Road Condition Monitoring System

    SciTech Connect

    Ndoye, Mandoye; Barker, Alan M; Krogmeier, James; Bullock, Darcy

    2011-01-01

    A signal processing approach is proposed to jointly filter and fuse spatially indexed measurements captured from many vehicles. It is assumed that these measurements are influenced by both sensor noise and measurement indexing uncertainties. Measurements from low-cost vehicle-mounted sensors (e.g., accelerometers and Global Positioning System (GPS) receivers) are properly combined to produce higher quality road roughness data for cost-effective road surface condition monitoring. The proposed algorithms are recursively implemented and thus require only moderate computational power and memory space. These algorithms are important for future road management systems, which will use on-road vehicles as a distributed network of sensing probes gathering spatially indexed measurements for condition monitoring, in addition to other applications, such as environmental sensing and/or traffic monitoring. Our method and the related signal processing algorithms have been successfully tested using field data.

  12. Rotor fault condition monitoring techniques for squirrel-cage induction machine—A review

    NASA Astrophysics Data System (ADS)

    Mehrjou, Mohammad Rezazadeh; Mariun, Norman; Hamiruce Marhaban, Mohammad; Misron, Norhisam

    2011-11-01

    Nowadays, manufacturing companies are making great efforts to implement an effective machinery maintenance program, which provides incipient fault detection. The machine problem and its irregularity can be detected at an early stage by employing a suitable condition monitoring accompanied with powerful signal processing technique. Among various defects occurred in machines, rotor faults are of significant importance as they cause secondary failures that lead to a serious motor malfunction. Diagnosis of rotor failures has long been an important but complicated task in the area of motor faults detection. This paper intends to review and summarize the recent researches and developments performed in condition monitoring of the induction machine with the purpose of rotor faults detection. The aim of this article is to provide a broad outlook on rotor fault monitoring techniques for the researchers and engineers.

  13. Monitoring diapause development in the Colorado potato beetle, Leptinotarsa decemlineata, under field conditions using molecular biomarkers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A multiplex PCR protocol was developed using five diapause-regulated genes to monitor diapause development of the Colorado potato beetle under field conditions. A total of 870 beetles from the Red River Valley of North Dakota and Minnesota, USA, were screened for three consecutive years. Out of the ...

  14. Online Condition Monitoring to Enable Extended Operation of Nuclear Power Plants

    SciTech Connect

    Meyer, Ryan M.; Bond, Leonard J.; Ramuhalli, Pradeep

    2012-03-31

    Safe, secure, and economic operation of nuclear power plants will remain of strategic significance. New and improved monitoring will likely have increased significance in the post-Fukushima world. Prior to Fukushima, many activities were already underway globally to facilitate operation of nuclear power plants beyond their initial licensing periods. Decisions to shut down a nuclear power plant are mostly driven by economic considerations. Online condition monitoring is a means to improve both the safety and economics of extending the operating lifetimes of nuclear power plants, enabling adoption of proactive aging management. With regard to active components (e.g., pumps, valves, motors, etc.), significant experience in other industries has been leveraged to build the science base to support adoption for online condition-based maintenance and proactive aging management in the nuclear industry. Many of the research needs are associated with enabling proactive management of aging in passive components (e.g., pipes, vessels, cables, containment structures, etc.). This paper provides an overview of online condition monitoring for the nuclear power industry with an emphasis on passive components. Following the overview, several technology/knowledge gaps are identified, which require addressing to facilitate widespread online condition monitoring of passive components.

  15. Implementation of an Integrated, Portable Transformer Condition Monitoring Instrument in the Classroom and On-Site

    ERIC Educational Resources Information Center

    Chatterjee, B.; Dey, D.; Chakravorti, S.

    2010-01-01

    The development of integrated, portable, transformer condition monitoring (TCM) equipment for classroom demonstrations as well as for student exercises conducted in the field is discussed. Demonstrations include experimentation with real-world transformers to illustrate concepts such as polarization and depolarization current through oil-paper…

  16. Wind Turbine Drivetrain Condition Monitoring During GRC Phase 1 and Phase 2 Testing

    SciTech Connect

    Sheng, S.; Link, H.; LaCava, W.; van Dam, J.; McNiff, B.; Veers, P.; Keller, J.; Butterfield, S.; Oyague, F.

    2011-10-01

    This report will present the wind turbine drivetrain condition monitoring (CM) research conducted under the phase 1 and phase 2 Gearbox Reliability Collaborative (GRC) tests. The rationale and approach for this drivetrain CM research, investigated CM systems, test configuration and results, and a discussion on challenges in wind turbine drivetrain CM and future research and development areas, will be presented.

  17. 7 CFR 623.16 - Monitoring and enforcement of easement terms and conditions.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Monitoring and enforcement of easement terms and conditions. 623.16 Section 623.16 Agriculture Regulations of the Department of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE WATER RESOURCES EMERGENCY...

  18. The Role of Sample Surveys for Monitoring the Condition of the Nation's Lakes.

    ERIC Educational Resources Information Center

    Larsen, D. P.; And Others

    1994-01-01

    This paper describes the need for statistically based survey design. It briefly summarizes the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) and demonstrates how its design is tailored for the selection of a probability sample of lakes on which to make measurements of lake conditions. (LZ)

  19. Introducing passive acoustic filter in acoustic based condition monitoring: Motor bike piston-bore fault identification

    NASA Astrophysics Data System (ADS)

    Jena, D. P.; Panigrahi, S. N.

    2016-03-01

    Requirement of designing a sophisticated digital band-pass filter in acoustic based condition monitoring has been eliminated by introducing a passive acoustic filter in the present work. So far, no one has attempted to explore the possibility of implementing passive acoustic filters in acoustic based condition monitoring as a pre-conditioner. In order to enhance the acoustic based condition monitoring, a passive acoustic band-pass filter has been designed and deployed. Towards achieving an efficient band-pass acoustic filter, a generalized design methodology has been proposed to design and optimize the desired acoustic filter using multiple filter components in series. An appropriate objective function has been identified for genetic algorithm (GA) based optimization technique with multiple design constraints. In addition, the sturdiness of the proposed method has been demonstrated in designing a band-pass filter by using an n-branch Quincke tube, a high pass filter and multiple Helmholtz resonators. The performance of the designed acoustic band-pass filter has been shown by investigating the piston-bore defect of a motor-bike using engine noise signature. On the introducing a passive acoustic filter in acoustic based condition monitoring reveals the enhancement in machine learning based fault identification practice significantly. This is also a first attempt of its own kind.

  20. Integrating remote sensing data from multiple optical sensors for ecological and crop condition monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ecological and crop condition monitoring requires high temporal and spatial resolution remote sensing data. Due to technical limitations and budget constraints, remote sensing instruments trade spatial resolution for swath width. As a result, it is difficult to acquire remotely sensed data with both...

  1. Fluorescent and Luminescent Probes for Monitoring Hydroxyl Radical under Biological Conditions.

    PubMed

    Żamojć, Krzysztof; Zdrowowicz, Magdalena; Jacewicz, Dagmara; Wyrzykowski, Dariusz; Chmurzyński, Lech

    2016-01-01

    Detection and quantitative determination in biological media of the hydroxyl radical are of great importance due to the role this radical plays in many physiological and pathological processes. This review focuses on the progress that has been made in recent years in the development of fluorescent and luminescent probes employed to monitor hydroxyl radical concentrations under biological conditions. PMID:26042844

  2. Assessing the ecological condition of streams in a southeastern Brazilian basin using a probabilistic monitoring design.

    PubMed

    Jiménez-Valencia, Juliana; Kaufmann, Philip R; Sattamini, Ana; Mugnai, Riccardo; Baptista, Darcilio Fernandes

    2014-08-01

    Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodiversity and habitat. We assessed the ecological condition of streams in a southeastern Brazilian basin. We quantified the percentage of stream length in good, fair, and poor ecological condition according to benthic macroinvertebrate assemblage. We assessed the risk of finding degraded ecological condition associated with degraded aquatic riparian physical habitat condition, watershed condition, and water quality. We describe field sampling and implementation issues encountered in our survey and discuss design options to remedy them. Survey sample sites were selected using a spatially balanced, stratified random design, which enabled us to put confidence bounds on the ecological condition estimates derived from the stream survey. The benthic condition index indicated that 62 % of stream length in the basin was in poor ecological condition, and 13 % of stream length was in fair condition. The risk of finding degraded biological condition when the riparian vegetation and forests in upstream catchments were degraded was 2.5 and 4 times higher, compared to streams rated as good for the same stressors. We demonstrated that the GRTS statistical sampling method can be used routinely in Brazilian rain forests and other South American regions with similar conditions. This survey establishes an initial baseline for monitoring the condition and trends of streams in the region. PMID:24829159

  3. Multivariate optimization and supplementation strategies for the simultaneous production of amylases, cellulases, xylanases, and proteases by Aspergillus awamori under solid-state fermentation conditions.

    PubMed

    de Castro, Aline Machado; Castilho, Leda R; Freire, Denise Maria Guimarães

    2015-02-01

    The production of extracts containing a pool of enzymes for extensive biomass deconstruction can lead to significant advantages in biorefinery applications. In this work, a strain of Aspergillus awamori IOC-3914 was used for the simultaneous production of five groups of hydrolases by solid-state fermentation of babassu cake. Sequential experimental design strategies and multivariate optimization using the desirability function were first used to study temperature, moisture content, and granulometry. After that, further improvements in product yields were achieved by supplementation with other agro-industrial materials. At the end of the study, the production of enzymes was up to 3.3-fold increased, and brewer's spent grains and babassu flour showed to be the best supplements. Maximum activities for endoamylases, exoamylases, cellulases (CMCases), xylanases, and proteases achieved were 197, 106, 20, 835, and 57 U g(-1), respectively. The strain was also able to produce β-glucosidases and debranching amylases (up to 35 and 43 U g(-1), respectively), indicating the potential of its enzyme pool for cellulose and starch degradation. PMID:25413792

  4. Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

    SciTech Connect

    Kumar, Rajeeva; Kumar, Aditya; Dai, Dan; Seenumani, Gayathri; Down, John; Lopez, Rodrigo

    2012-12-31

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve

  5. The Piston Compressor: The Methodology of the Real-Time Condition Monitoring

    NASA Astrophysics Data System (ADS)

    Naumenko, A. P.; Kostyukov, V. N.

    2012-05-01

    The methodology of a diagnostic signal processing, a function chart of the monitoring system are considered in the article. The methodology of monitoring and diagnosing is based on measurement of indirect processes' parameters (vibroacoustic oscillations) therefore no more than five sensors is established on the cylinder, measurement of direct structural and thermodynamic parameters is envisioned as well. The structure and principle of expert system's functioning of decision-making is given. Algorithm of automatic expert system includes the calculation diagnostic attributes values based on their normative values, formation sets of diagnostic attributes that correspond to individual classes to malfunction, formation of expert system messages. The scheme of a real-time condition monitoring system for piston compressors is considered. The system have consistently-parallel structure of information-measuring equipment, which allows to measure the vibroacoustic signal for condition monitoring of reciprocating compressors and modes of its work. Besides, the system allows to measure parameters of other physical processes, for example, system can measure and use for monitoring and statements of the diagnosis the pressure in decreasing spaces (the indicator diagram), the inlet pressure and flowing pressure of each cylinder, inlet and delivery temperature of gas, valves temperature, position of a rod, leakage through compression packing and others.

  6. Monitoring Surface Condition of Plasma Grid of a Negative Hydrogen Ion Source

    SciTech Connect

    Wada, M.; Kasuya, T.; Tokushige, S.; Kenmotsu, T.

    2011-09-26

    Surface condition of a plasma grid in a negative hydrogen ion source is controlled so as to maximize the beam current under a discharge operation with introducing Cs into the ion source. Photoelectric current induced by laser beams incident on the plasma grid can produce a signal to monitor the surface condition, but the signal detection can be easily hindered by plasma noise. Reduction in size of a detection electrode embedded in the plasma grid can improve signal-to-noise ratio of the photoelectric current from the electrode. To evaluate the feasibility of monitoring surface condition of a plasma gird by utilizing photoelectric effect, a small experimental setup capable of determining quantum yields of a surface in a cesiated plasma environment is being assembled. Some preliminary test results of the apparatus utilizing oxide cathodes are reported.

  7. Grinding Wheel Condition Monitoring with Hidden Markov Model-Based Clustering Methods

    SciTech Connect

    Liao, T. W.; Hua, G; Qu, Jun; Blau, Peter Julian

    2006-01-01

    Hidden Markov model (HMM) is well known for sequence modeling and has been used for condition monitoring. However, HMM-based clustering methods are developed only recently. This article proposes a HMM-based clustering method for monitoring the condition of grinding wheel used in grinding operations. The proposed method first extract features from signals based on discrete wavelet decomposition using a moving window approach. It then generates a distance (dissimilarity) matrix using HMM. Based on this distance matrix several hierarchical and partitioning-based clustering algorithms are applied to obtain clustering results. The proposed methodology was tested with feature sequences extracted from acoustic emission signals. The results show that clustering accuracy is dependent upon cutting condition. Higher material removal rate seems to produce more discriminatory signals/features than lower material removal rate. The effect of window size, wavelet decomposition level, wavelet basis, clustering algorithm, and data normalization were also studied.

  8. Unified Multi-speed analysis (UMA) for the condition monitoring of aero-engines

    NASA Astrophysics Data System (ADS)

    Nembhard, Adrian D.; Sinha, Jyoti K.

    2015-12-01

    For rotating machinery in which speeds and dynamics constantly change, performing vibration-based condition monitoring can be challenging. Thus, an effort is made here to develop a Unified Multi-speed fault diagnosis technique that can exploit useful vibration information available at various speeds from a rotating machine in a single analysis. Commonly applied indicators are computed from data collected from a rig at different speeds for a baseline case and different faults. Four separate analyses are performed: single speed at a single bearing, integrated features from multiple speeds at a single bearing, single speed for integrated features from multiple bearings and the proposed Unified Multi-speed analysis. The Unified Multi-speed approach produces the most conspicuous separation and isolation among the conditions tested. Observations made here suggest integration of more dynamic features available at different speeds improves the learning process of the tool which could prove useful for aero-engine condition monitoring.

  9. Multivariable PID control by decoupling

    NASA Astrophysics Data System (ADS)

    Garrido, Juan; Vázquez, Francisco; Morilla, Fernando

    2016-04-01

    This paper presents a new methodology to design multivariable proportional-integral-derivative (PID) controllers based on decoupling control. The method is presented for general n × n processes. In the design procedure, an ideal decoupling control with integral action is designed to minimise interactions. It depends on the desired open-loop processes that are specified according to realisability conditions and desired closed-loop performance specifications. These realisability conditions are stated and three common cases to define the open-loop processes are studied and proposed. Then, controller elements are approximated to PID structure. From a practical point of view, the wind-up problem is also considered and a new anti-wind-up scheme for multivariable PID controller is proposed. Comparisons with other works demonstrate the effectiveness of the methodology through the use of several simulation examples and an experimental lab process.

  10. Research of on-line monitoring method for insulation condition of power transformer bushing

    NASA Astrophysics Data System (ADS)

    Xia, Jiuyun; Qian, Zheng; Yu, Hao; Yao, Junda

    2016-01-01

    The power transformer is the key equipment of the power system; its insulation condition will directly influence the security and reliability of the power system. Thus, the on-line monitoring of power transformer is urgently required in order to guarantee the normal operation of the power system. Moreover, the dielectric loss factor is a significant parameter reflecting the condition of transformer bushing, so the on-line measurement of dielectric loss factor is really important. In this paper, the phase-to-phase comparison method is selected as the on-line monitoring method based on the overall analysis and discussion of the existing on-line monitoring methods. At first, the harmonic analysis method is utilized to calculate the dielectric loss of each phase of the three-phase transformer bushing, and then the differences of dielectric loss between every two phases are calculated and analyzed. So the insulation condition of each bushing could be achieved based on the careful analysis of different phase-to-phase dielectric loss. The simulation results of phase-to-phase comparison method are carried out in this paper, and the validity is verified. At last, this method is utilized in an actual equipment of on-line monitoring.

  11. Problems with Multivariate Normality: Can the Multivariate Bootstrap Help?

    ERIC Educational Resources Information Center

    Thompson, Bruce

    Multivariate normality is required for some statistical tests. This paper explores the implications of violating the assumption of multivariate normality and illustrates a graphical procedure for evaluating multivariate normality. The logic for using the multivariate bootstrap is presented. The multivariate bootstrap can be used when distribution…

  12. An Updated Methodology for Enhancing Risk Monitors with Integrated Equipment Condition Assessment

    SciTech Connect

    Ramuhalli, Pradeep; Hirt, Evelyn H.; Coles, Garill A.; Bonebrake, Christopher A.; Ivans, William J.; Wootan, David W.; Mitchell, Mark R.

    2014-07-18

    Small modular reactors (SMRs) generally include reactors with electric output of ~350 MWe or less (this cutoff varies somewhat but is substantially less than full-size plant output of 700 MWe or more). Advanced SMRs (AdvSMRs) refer to a specific class of SMRs and are based on modularization of advanced reactor concepts. Enhancing affordability of AdvSMRs will be critical to ensuring wider deployment, as AdvSMRs suffer from loss of economies of scale inherent in small reactors when compared to large (~greater than 600 MWe output) reactors and the controllable day-to-day costs of AdvSMRs will be dominated by operation and maintenance (O&M) costs. Technologies that help characterize real-time risk are important for controlling O&M costs. Risk monitors are used in current nuclear power plants to provide a point-in-time estimate of the system risk given the current plant configuration (e.g., equipment availability, operational regime, and environmental conditions). However, current risk monitors are unable to support the capability requirements listed above as they do not take into account plant-specific normal, abnormal, and deteriorating states of active components and systems. This report documents technology developments towards enhancing risk monitors that, if integrated with supervisory plant control systems, can provide the capability requirements listed and meet the goals of controlling O&M costs. The report describes research results on augmenting an initial methodology for enhanced risk monitors that integrate real-time information about equipment condition and POF into risk monitors. Methods to propagate uncertainty through the enhanced risk monitor are evaluated. Available data to quantify the level of uncertainty and the POF of key components are examined for their relevance, and a status update of this data evaluation is described. Finally, we describe potential targets for developing new risk metrics that may be useful for studying trade-offs for economic

  13. A multivariate CAR model for mismatched lattices.

    PubMed

    Porter, Aaron T; Oleson, Jacob J

    2014-10-01

    In this paper, we develop a multivariate Gaussian conditional autoregressive model for use on mismatched lattices. Most current multivariate CAR models are designed for each multivariate outcome to utilize the same lattice structure. In many applications, a change of basis will allow different lattices to be utilized, but this is not always the case, because a change of basis is not always desirable or even possible. Our multivariate CAR model allows each outcome to have a different neighborhood structure which can utilize different lattices for each structure. The model is applied in two real data analysis. The first is a Bayesian learning example in mapping the 2006 Iowa Mumps epidemic, which demonstrates the importance of utilizing multiple channels of infection flow in mapping infectious diseases. The second is a multivariate analysis of poverty levels and educational attainment in the American Community Survey. PMID:25457598

  14. Perspectives on railway track geometry condition monitoring from in-service railway vehicles

    NASA Astrophysics Data System (ADS)

    Weston, P.; Roberts, C.; Yeo, G.; Stewart, E.

    2015-07-01

    This paper presents a view of the current state of monitoring track geometry condition from in-service vehicles. It considers technology used to provide condition monitoring; some issues of processing and the determination of location; how things have evolved over the past decade; and what is being, or could/should be done in future research. Monitoring railway track geometry from an in-service vehicle is an attractive proposition that has become a reality in the past decade. However, this is only the beginning. Seeing the same track over and over again provides an opportunity for observing track geometry degradation that can potentially be used to inform maintenance decisions. Furthermore, it is possible to extend the use of track condition information to identify if maintenance is effective, and to monitor the degradation of individual faults such as dipped joints. There are full unattended track geometry measurement systems running on in-service vehicles in the UK and elsewhere around the world, feeding their geometry measurements into large databases. These data can be retrieved, but little is currently done with the data other than the generation of reports of track geometry that exceeds predefined thresholds. There are examples of simpler systems that measure some track geometry parameters more or less directly and accurately, but forego parameters such as gauge. Additionally, there are experimental systems that use mathematics and models to infer track geometry using data from sensors placed on an in-service vehicle. Finally, there are systems that do not claim to measure track geometry, but monitor some other quantity such as ride quality or bogie acceleration to infer poor track geometry without explicitly measuring it.

  15. Abnormal Condition Monitoring of Workpieces Based on RFID for Wisdom Manufacturing Workshops

    PubMed Central

    Zhang, Cunji; Yao, Xifan; Zhang, Jianming

    2015-01-01

    Radio Frequency Identification (RFID) technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP) technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi® Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops. PMID:26633418

  16. Abnormal Condition Monitoring of Workpieces Based on RFID for Wisdom Manufacturing Workshops.

    PubMed

    Zhang, Cunji; Yao, Xifan; Zhang, Jianming

    2015-01-01

    Radio Frequency Identification (RFID) technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP) technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi(®) Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops. PMID:26633418

  17. An Uncertainty Quantification Framework for Prognostics and Condition-Based Monitoring

    NASA Technical Reports Server (NTRS)

    Sankararaman, Shankar; Goebel, Kai

    2014-01-01

    This paper presents a computational framework for uncertainty quantification in prognostics in the context of condition-based monitoring of aerospace systems. The different sources of uncertainty and the various uncertainty quantification activities in condition-based prognostics are outlined in detail, and it is demonstrated that the Bayesian subjective approach is suitable for interpreting uncertainty in online monitoring. A state-space model-based framework for prognostics, that can rigorously account for the various sources of uncertainty, is presented. Prognostics consists of two important steps. First, the state of the system is estimated using Bayesian tracking, and then, the future states of the system are predicted until failure, thereby computing the remaining useful life of the system. The proposed framework is illustrated using the power system of a planetary rover test-bed, which is being developed and studied at NASA Ames Research Center.

  18. Fusing human knowledge with neural networks in machine condition monitoring systems

    NASA Astrophysics Data System (ADS)

    Melvin, David G.; Penman, J.

    1995-04-01

    There is currently much interest in the application of artificial neural network (ANN) technology to the field of on-line machine condition monitoring (CM) for complex electro- mechanical systems. In this paper the authors discuss, with the help of an industrial case study, a few of the difficulties inherent in the application of neural network based condition monitoring. A method of overcoming these difficulties by utilizing a combination of human knowledge, encoded using techniques borrowed from fuzzy logic, Kohonen neural networks, and statistical K-means clustering has been constructed. The methodology is discussed in the paper by means of a direct comparison between this new approach and a purely neural approach. An analysis of other situations where this approach would be applicable is also presented and the paper discusses other current research work in the area of hybrid AI technologies which should assist further with the alleviation of the problems under consideration.

  19. DEVELOPMENT OF A SENSOR NETWORK TEST BED FOR ISD MATERIALS AND STRUCUTRAL CONDITION MONITORING

    SciTech Connect

    Zeigler, K.; Ferguson, B.; Karapatakis, D.; Herbst, C.; Stripling, C.

    2011-07-06

    The P Reactor at the Savannah River Site is one of the first reactor facilities in the US DOE complex that has been placed in its end state through in situ decommissioning (ISD). The ISD end state consists of a grout-filled concrete civil structure within the concrete frame of the original building. To evaluate the feasibility and utility of remote sensors to provide verification of ISD system conditions and performance characteristics, an ISD Sensor Network Test Bed has been designed and deployed at the Savannah River National Laboratory. The test bed addresses the DOE-EM Technology Need to develop a remote monitoring system to determine and verify ISD system performance. Commercial off-the-shelf sensors have been installed on concrete blocks taken from walls of the P Reactor Building. Deployment of this low-cost structural monitoring system provides hands-on experience with sensor networks. The initial sensor system consists of: (1) Groutable thermistors for temperature and moisture monitoring; (2) Strain gauges for crack growth monitoring; (3) Tiltmeters for settlement monitoring; and (4) A communication system for data collection. Preliminary baseline data and lessons learned from system design and installation and initial field testing will be utilized for future ISD sensor network development and deployment.

  20. Development of a wireless bridge monitoring system for condition assessment using hybrid techniques

    NASA Astrophysics Data System (ADS)

    Whelan, Matthew J.; Fuchs, Michael P.; Gangone, Michael V.; Janoyan, Kerop D.

    2007-04-01

    The introduction and development of wireless sensor network technology has resulted in rapid growth within the field of structural health monitoring (SHM), as the dramatic cable costs associated with instrumentation of large civil structures is potentially alleviated. Traditionally, condition assessment of bridge structures is accomplished through the use of either vibration measurements or strain sensing. One approach is through quantifying dynamic characteristics and mode shapes developed through the use of relatively dense arrays of accelerometers. Another widely utilized method of condition assessment is bridge load rating, which is enabled through the use of strain sensors. The Wireless Sensor Solution (WSS) developed specifically for diagnostic bridge monitoring provides a hybrid system that interfaces with both accelerometers and strain sensors to facilitate vibration-based bridge evaluation as well as load rating and static analysis on a universal platform. This paper presents the development and testing of a wireless bridge monitoring system designed within the Laboratory for Intelligent Infrastructure and Transportation Technologies (LIITT) at Clarkson University. The system interfaces with low-cost MEMS accelerometers using custom signal conditioning for amplification and filtering tailored to the spectrum of typical bridge vibrations, specifically from ambient excitation. Additionally, a signal conditioning and high resolution ADC interface is provided for strain gauge sensors. To permit compensation for the influence of temperature, thermistor-based temperature sensing is also enabled. In addition to the hardware description, this paper presents features of the software applications and host interface developed for flexible, user-friendly in-network control of and acquisition from the sensor nodes. The architecture of the software radio protocol is also discussed along with results of field deployments including relatively large-scale networks and

  1. [Fundamentals of socio-hygienic monitoring of environmental conditions for students of higher education schools].

    PubMed

    Blinova, E G; Kuchma, V R

    2012-01-01

    Socioeconomic transformations and the poor environment of an industrial megalopolis negatively affected quality of life and morbidity rates in students (n = 2160). Academic intensity contributed to an increase in overall morbidity and morbidity from nervous system involvement. The regional sociohygienic monitoring of high-school training conditions within the framework of the surveillance system substantiates programs to prevent worse health and life quality in high school students. PMID:22712322

  2. Monitoring of Double-Stud Wall Moisture Conditions in the Northeast

    SciTech Connect

    Ueno, K.

    2015-03-01

    Double-stud walls insulated with cellulose or low-density spray foam can have R-values of 40 or higher. However, double-stud walls have a higher risk of interior-sourced condensation moisture damage when compared with high-R approaches using exterior insulating sheathing. Moisture conditions in double-stud walls were monitored in Zone 5A (Massachusetts); three double-stud assemblies were compared.

  3. Development of an In-Situ Decommissioning Sensor Network Test Bed for Structural Condition Monitoring - 12156

    SciTech Connect

    Zeigler, Kristine E.; Ferguson, Blythe A.

    2012-07-01

    The Savannah River National Laboratory (SRNL) has established an In Situ Decommissioning (ISD) Sensor Network Test Bed, a unique, small scale, configurable environment, for the assessment of prospective sensors on actual ISD system material, at minimal cost. The Department of Energy (DOE) is presently implementing permanent entombment of contaminated, large nuclear structures via ISD. The ISD end state consists of a grout-filled concrete civil structure within the concrete frame of the original building. Validation of ISD system performance models and verification of actual system conditions can be achieved through the development a system of sensors to monitor the materials and condition of the structure. The ISD Sensor Network Test Bed has been designed and deployed to addresses the DOE-Environmental Management Technology Need to develop a remote monitoring system to determine and verify ISD system performance. Commercial off-the-shelf sensors have been installed on concrete blocks taken from walls of the P Reactor Building at the Savannah River Site. Deployment of this low-cost structural monitoring system provides hands-on experience with sensor networks. The initial sensor system consists of groutable thermistors for temperature and moisture monitoring, strain gauges for crack growth monitoring, tilt-meters for settlement monitoring, and a communication system for data collection. Baseline data and lessons learned from system design and installation and initial field testing will be utilized for future ISD sensor network development and deployment. The Sensor Network Test Bed at SRNL uses COTS sensors on concrete blocks from the outer wall of the P Reactor Building to measure conditions expected to occur in ISD structures. Knowledge and lessons learned gained from installation, testing, and monitoring of the equipment will be applied to sensor installation in a meso-scale test bed at FIU and in future ISD structures. The initial data collected from the sensors

  4. An efficient recursive least square-based condition monitoring approach for a rail vehicle suspension system

    NASA Astrophysics Data System (ADS)

    Liu, X. Y.; Alfi, S.; Bruni, S.

    2016-06-01

    A model-based condition monitoring strategy for the railway vehicle suspension is proposed in this paper. This approach is based on recursive least square (RLS) algorithm focusing on the deterministic 'input-output' model. RLS has Kalman filtering feature and is able to identify the unknown parameters from a noisy dynamic system by memorising the correlation properties of variables. The identification of suspension parameter is achieved by machine learning of the relationship between excitation and response in a vehicle dynamic system. A fault detection method for the vertical primary suspension is illustrated as an instance of this condition monitoring scheme. Simulation results from the rail vehicle dynamics software 'ADTreS' are utilised as 'virtual measurements' considering a trailer car of Italian ETR500 high-speed train. The field test data from an E464 locomotive are also employed to validate the feasibility of this strategy for the real application. Results of the parameter identification performed indicate that estimated suspension parameters are consistent or approximate with the reference values. These results provide the supporting evidence that this fault diagnosis technique is capable of paving the way for the future vehicle condition monitoring system.

  5. Force sensor based tool condition monitoring using a heterogeneous ensemble learning model.

    PubMed

    Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

    2014-01-01

    Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability. PMID:25405514

  6. Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

    PubMed Central

    Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

    2014-01-01

    Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability. PMID:25405514

  7. Suitable features selection for monitoring thermal condition of electrical equipment using infrared thermography

    NASA Astrophysics Data System (ADS)

    Huda, A. S. N.; Taib, S.

    2013-11-01

    Monitoring the thermal condition of electrical equipment is necessary for maintaining the reliability of electrical system. The degradation of electrical equipment can cause excessive overheating, which can lead to the eventual failure of the equipment. Additionally, failure of equipment requires a lot of maintenance cost, manpower and can also be catastrophic- causing injuries or even deaths. Therefore, the recognition processof equipment conditions as normal and defective is an essential step towards maintaining reliability and stability of the system. The study introduces infrared thermography based condition monitoring of electrical equipment. Manual analysis of thermal image for detecting defects and classifying the status of equipment take a lot of time, efforts and can also lead to incorrect diagnosis results. An intelligent system that can separate the equipment automatically could help to overcome these problems. This paper discusses an intelligent classification system for the conditions of equipment using neural networks. Three sets of features namely first order histogram based statistical, grey level co-occurrence matrix and component based intensity features are extracted by image analysis, which are used as input data for the neural networks. The multilayered perceptron networks are trained using four different training algorithms namely Resilient back propagation, Bayesian Regulazation, Levenberg-Marquardt and Scale conjugate gradient. The experimental results show that the component based intensity features perform better compared to other two sets of features. Finally, after selecting the best features, multilayered perceptron network trained using Levenberg-Marquardt algorithm achieved the best results to classify the conditions of electrical equipment.

  8. Nonlinearity detection for condition monitoring utilizing higher-order spectral analysis diagnostics

    NASA Astrophysics Data System (ADS)

    Park, Hyeonsu

    In this dissertation, we investigate the theory and application of higher-order spectral analysis techniques to condition monitoring in shipboard electrical power systems. Monitoring and early detection of faults in rotating machines, such as induction motors, are essential for both preventive maintenance and to avoid potentially severe damage. As machines degrade, they often tend to become more nonlinear. This increased nonlinearity results in the introduction of new frequencies which satisfy particular frequency selection rules; the exact selection rule depends on the order of the nonlinearity. In addition, the phases of the newly generated frequencies satisfy a similar phase selection rule. This results in a phase coherence, or phase coupling, between the "original" interacting frequencies and the "new" frequencies. This phase coupling is a true signature of nonlinearity. Since the classical auto-power spectrum contains no phase information, the phase coupling signature associated with nonlinear interactions is not available. However, various higher-order spectra (HOS) are capable of detecting such nonlinear-induced phase coupling. The efficacy of the various proposed HOS-based methodologies is investigated using real-world vibration time-series data from a faulted induction motor driving a dc generator. The fault is controlled by varying a resistor placed in one phase of the three-phase line to the induction motor. First, we propose a novel method using a bispectral change detection (BCD) for condition monitoring. Even though the bicoherence is dominant and powerful in the detection of phase coupling of nonlinearly interacting frequencies, it has some difficulties in its application to machine condition monitoring. Basically, the bicoherence may not be able to distinguish between intrinsic nonlinearities associated with healthy machines and fault-induced nonlinearities. Therefore, the ability to discriminate the fault-only nonlinearities from the intrinsic

  9. Usefulness of LANDSAT data for monitoring plant development and range conditions in California's annual grassland

    NASA Technical Reports Server (NTRS)

    Carneggie, D. M.; Degloria, S. D.; Colwell, R. N.

    1975-01-01

    A network of sampling sites throughout the annual grassland region of California was established to correlate plant growth stages and forage production to climatic and other environmental factors. Plant growth and range conditions were further related to geographic location and seasonal variations. A sequence of LANDSAT data was obtained covering critical periods in the growth cycle. This was analyzed by both photointerpretation and computer aided techniques. Image characteristics and spectral reflectance data were then related to forage production, range condition, range site and changing growth conditions. It was determined that repeat sequences with LANDSAT color composite images do provide a means for monitoring changes in range condition. Spectral radiance data obtained from magnetic tape can be used to determine quantitatively the critical stages in the forage growth cycle. A computer ratioing technique provided a sensitive indicator of changes in growth stages and an indication of the relative differences in forage production between range sites.

  10. Technical Report on Preliminary Methodology for Enhancing Risk Monitors with Integrated Equipment Condition Assessment

    SciTech Connect

    Ramuhalli, Pradeep; Coles, Garill A.; Coble, Jamie B.; Hirt, Evelyn H.

    2013-09-17

    Small modular reactors (SMRs) generally include reactors with electric output of ~350 MWe or less (this cutoff varies somewhat but is substantially less than full-size plant output of 700 MWe or more). Advanced SMRs (AdvSMRs) refer to a specific class of SMRs and are based on modularization of advanced reactor concepts. AdvSMRs may provide a longer-term alternative to traditional light-water reactors (LWRs) and SMRs based on integral pressurized water reactor concepts currently being considered. Enhancing affordability of AdvSMRs will be critical to ensuring wider deployment. AdvSMRs suffer from loss of economies of scale inherent in small reactors when compared to large (~greater than 600 MWe output) reactors. Some of this loss can be recovered through reduced capital costs through smaller size, fewer components, modular fabrication processes, and the opportunity for modular construction. However, the controllable day-to-day costs of AdvSMRs will be dominated by operation and maintenance (O&M) costs. Technologies that help characterize real-time risk are important for controlling O&M costs. Risk monitors are used in current nuclear power plants to provide a point-in-time estimate of the system risk given the current plant configuration (e.g., equipment availability, operational regime, and environmental conditions). However, current risk monitors are unable to support the capability requirements listed above as they do not take into account plant-specific normal, abnormal, and deteriorating states of active components and systems. This report documents technology developments that are a step towards enhancing risk monitors that, if integrated with supervisory plant control systems, can provide the capability requirements listed and meet the goals of controlling O&M costs. The report describes research results from an initial methodology for enhanced risk monitors by integrating real-time information about equipment condition and POF into risk monitors.

  11. Detection and classification of alarm threshold violations in condition monitoring systems working in highly varying operational conditions

    NASA Astrophysics Data System (ADS)

    Strączkiewicz, M.; Barszcz, T.; Jabłoński, A.

    2015-07-01

    All commonly used condition monitoring systems (CMS) enable defining alarm thresholds that enhance efficient surveillance and maintenance of dynamic state of machinery. The thresholds are imposed on the measured values such as vibration-based indicators, temperature, pressure, etc. For complex machinery such as wind turbine (WT) the total number of thresholds might be counted in hundreds multiplied by the number of operational states. All the parameters vary not only due to possible machinery malfunctions, but also due to changes in operating conditions and these changes are typically much stronger than the former ones. Very often, such a behavior may lead to hundreds of false alarms. Therefore, authors propose a novel approach based on parameterized description of the threshold violation. For this purpose the novelty and severity factors are introduced. The first parameter refers to the time of violation occurrence while the second one describes the impact of the indicator-increase to the entire machine. Such approach increases reliability of the CMS by providing the operator with the most useful information of the system events. The idea of the procedure is presented on a simulated data similar to those from a wind turbine.

  12. Field monitoring of condition of large electric generators. (Latest citations from the EI Compendex plus database). Published Search

    SciTech Connect

    Not Available

    1993-08-01

    The bibliography contains citations concerning monitoring techniques to determine the condition of large electric generators. Electric generators are limited to turbine generators, variously called hydroturbines, turbogenerators and turbosets. Wind turbines and magnetohydrodynamics are not included in this bibliography. Techniques for condition monitoring include noise analysis and acoustic monitoring, vibration and misalignment measurements, bearing oil analyses, and transient torsional changes affecting shafts and rotors. (Contains a minimum of 178 citations and includes a subject term index and title list.)

  13. Graphite Based Electrode for ECG Monitoring: Evaluation under Freshwater and Saltwater Conditions

    PubMed Central

    Thap, Tharoeun; Yoon, Kwon-Ha; Lee, Jinseok

    2016-01-01

    We proposed new electrodes that are applicable for electrocardiogram (ECG) monitoring under freshwater- and saltwater-immersion conditions. Our proposed electrodes are made of graphite pencil lead (GPL), a general-purpose writing pencil. We have fabricated two types of electrode: a pencil lead solid type (PLS) electrode and a pencil lead powder type (PLP) electrode. In order to assess the qualities of the PLS and PLP electrodes, we compared their performance with that of a commercial Ag/AgCl electrode, under a total of seven different conditions: dry, freshwater immersion with/without movement, post-freshwater wet condition, saltwater immersion with/without movement, and post-saltwater wet condition. In both dry and post-freshwater wet conditions, all ECG-recorded PQRST waves were clearly discernible, with all types of electrodes, Ag/AgCl, PLS, and PLP. On the other hand, under the freshwater- and saltwater-immersion conditions with/without movement, as well as post-saltwater wet conditions, we found that the proposed PLS and PLP electrodes provided better ECG waveform quality, with significant statistical differences compared with the quality provided by Ag/AgCl electrodes. PMID:27092502

  14. Graphite Based Electrode for ECG Monitoring: Evaluation under Freshwater and Saltwater Conditions.

    PubMed

    Thap, Tharoeun; Yoon, Kwon-Ha; Lee, Jinseok

    2016-01-01

    We proposed new electrodes that are applicable for electrocardiogram (ECG) monitoring under freshwater- and saltwater-immersion conditions. Our proposed electrodes are made of graphite pencil lead (GPL), a general-purpose writing pencil. We have fabricated two types of electrode: a pencil lead solid type (PLS) electrode and a pencil lead powder type (PLP) electrode. In order to assess the qualities of the PLS and PLP electrodes, we compared their performance with that of a commercial Ag/AgCl electrode, under a total of seven different conditions: dry, freshwater immersion with/without movement, post-freshwater wet condition, saltwater immersion with/without movement, and post-saltwater wet condition. In both dry and post-freshwater wet conditions, all ECG-recorded PQRST waves were clearly discernible, with all types of electrodes, Ag/AgCl, PLS, and PLP. On the other hand, under the freshwater- and saltwater-immersion conditions with/without movement, as well as post-saltwater wet conditions, we found that the proposed PLS and PLP electrodes provided better ECG waveform quality, with significant statistical differences compared with the quality provided by Ag/AgCl electrodes. PMID:27092502

  15. Condition health monitoring of composite wound pressure vessels using fiber Bragg gratings

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaojing; Zhang, Boming; Wu, Zhanjun

    2007-07-01

    Structure health monitoring refers to a real time and in situ monitoring system. It can diagnose the condition status of composite structure in time and effectively estimate the safety, increasing the reliability, extending the service life, at the same time, reducing the maintenance cost. In this paper, the sensing technology based on FBG sensors is employed to monitor the health of composite wound pressure vessel in service. Strain monitoring of the vessel in fatigue tests is carried out with the surface mounted FBG sensors. The experiment result shows that FBG sensors have several excellent performances: it has anti-fatigue capability to accurately measure the cycle strain; it is linear with the inner pressure and can be used as pressure sensor; the wavelength is diverged in the high stress gradient field, so the FBG can be used to measure the non-homogeneous strain field. Based on the fatigue damage mechanism of composite laminates and stiffness degradation model, the variation regularity of cycle strain of composite pressure vessel is studied and the residual stiffness during damage is obtained.

  16. Optimizing groundwater monitoring systems for landfills with random leaks under heterogeneous subsurface conditions

    NASA Astrophysics Data System (ADS)

    Yenigül, N. B.; Elfeki, A. M. M.; van den Akker, C.; Dekking, F. M.

    2013-12-01

    Landfills are one of the most common human activities threatening the natural groundwater quality. The landfill may leak, and the corresponding plumes may contaminate an area, entailing costly remediation measures. The objective of the installation of monitoring systems at landfill sites is to detect the contaminant plumes before they reach the regulatory compliance boundary in order to enable cost-effective counter measures. In this study, a classical decision analysis approach is linked to a stochastic simulation model to determine the optimal groundwater monitoring system given uncertainties due to the hydrogeological conditions and contaminant source characteristics. A Monte Carlo approach is used to incorporate uncertainties. Hydraulic conductivity and the leak location are the random inputs of the simulation model. The design objectives are to: (1) maximize the detection probability, (2) minimize the area of contamination at the time of detection, and (3) minimize the total cost of the monitoring system. A synthetic test case based on a real-world case in the Netherlands is analyzed. The results show that monitoring systems located close to the source are optimal except for the cases with very high unit installation and sampling cost and/or very cheap unit remediation.

  17. Wireless monitoring of the longitudinal displacement of the Tamar Suspension Bridge deck under changing environmental conditions

    NASA Astrophysics Data System (ADS)

    de Battista, Nicky; Westgate, Robert; Koo, Ki Young; Brownjohn, James

    2011-04-01

    In order to be able to monitor the performance and health of a civil structure it is essential to understand how it behaves under different environmental conditions. It is a well documented fact that the structural performance of bridges can be altered considerably when they are subjected to changes in environmental conditions. This paper presents a study investigating the longitudinal movement of the road deck on Tamar Suspension Bridge in Plymouth in the UK over six months. The expansion joint of the bridge deck was instrumented with pull-wire type extensometers. The data were transmitted wirelessly using commercial wireless sensor nodes and collected at a data acquisition laptop computer, which was accessible online for remote monitoring. In addition, position data of various locations on the bridge deck were collected using a Robotic Total Station (RTS). Environmental data, such as the temperature, and structural data, such as cable tension, were acquired from other monitoring systems. Conclusions drawn from a fusion of the bridge deck's longitudinal displacement with other structural and environmental data are discussed in this paper.

  18. Condition monitoring through advanced sensor and computational technology : final report (January 2002 to May 2005).

    SciTech Connect

    Kim, Jung-Taek; Luk, Vincent K.

    2005-05-01

    The overall goal of this joint research project was to develop and demonstrate advanced sensors and computational technology for continuous monitoring of the condition of components, structures, and systems in advanced and next-generation nuclear power plants (NPPs). This project included investigating and adapting several advanced sensor technologies from Korean and US national laboratory research communities, some of which were developed and applied in non-nuclear industries. The project team investigated and developed sophisticated signal processing, noise reduction, and pattern recognition techniques and algorithms. The researchers installed sensors and conducted condition monitoring tests on two test loops, a check valve (an active component) and a piping elbow (a passive component), to demonstrate the feasibility of using advanced sensors and computational technology to achieve the project goal. Acoustic emission (AE) devices, optical fiber sensors, accelerometers, and ultrasonic transducers (UTs) were used to detect mechanical vibratory response of check valve and piping elbow in normal and degraded configurations. Chemical sensors were also installed to monitor the water chemistry in the piping elbow test loop. Analysis results of processed sensor data indicate that it is feasible to differentiate between the normal and degraded (with selected degradation mechanisms) configurations of these two components from the acquired sensor signals, but it is questionable that these methods can reliably identify the level and type of degradation. Additional research and development efforts are needed to refine the differentiation techniques and to reduce the level of uncertainties.

  19. Bedload monitoring under conditions of ultra-high suspended sediment concentrations

    NASA Astrophysics Data System (ADS)

    Liébault, F.; Jantzi, H.; Klotz, S.; Laronne, J. B.; Recking, A.

    2016-09-01

    The bedload response of the Moulin Ravine, a small alluvial system draining a very active Mediterranean badlands landscape entrenched into Jurassic black marls of the Southern French Prealps, has been investigated using an automatic Reid bedload slot sampler. This site is known for its exceptional sediment transport conditions thanks to a long-term monitoring program that started in the late 1980s, revealing a mean annual bedload yield of 2810 t km-2 yr-1, and suspended sediment concentrations (SSCs) during flow events commonly reaching 100 g L-1. With the deployment of the slot sampler, it has been possible to record instantaneous bedload fluxes during 10 s time increments and to investigate bedload response under flow conditions with ultra-high SSCs. Bedload records cover 4 flashy summer flow events induced by heavy convective storms including a 20-yr return period event. Due to the very high SSC conditions these events challenge bedload monitoring. Even if slot sampling has been recognized as insensitive to fine sediments (silts and clays), it has never been tested in such exceptional muddy flow conditions. The bedload slot sampler performed well in such conditions. A flow-invariant proportion of fines (∼15-20%) was captured in the slot sampler during flows. This proportion is equivalent to its content in the active bedload layer during summer flows, suggesting that fines enter the slot embedded with coarse particles. Instantaneous bedload fluxes recorded in the Moulin are amongst the highest hitherto reported values worldwide, providing evidence of the exceptional sediment transport conditions of marly alpine badlands. The dimensionless entrainment threshold is one order of magnitude higher than commonly reported for gravel-bed rivers, likely reflecting the cohesion effect of fines intruded in the channel surface and subsurface.

  20. OTVE turbopump condition monitoring, task E. 5. Final report, October 1988-September 1989

    SciTech Connect

    Coleman, P.T.; Collins, J.J.

    1989-08-01

    Recent work has been carried out on development of isotope wear analysis and optical and eddy current technologies to provide bearing wear measurements and real time monitoring of shaft speed, shaft axial displacement and shaft orbit of the Orbit Transfer Vehicle hydrostatic bearing tester. Results show shaft axial displacement can be optically measured (at the same time as shaft orbital motion and speed) to within 0.3 mils by two fiberoptic deflectometers. Evaluation of eddy current probes showed that, in addition to measuring shaft orbital motion, they can be used to measure shaft speed without having to machine grooves on the shaft surface as is the usual practice for turbomachinery. The interim results of this condition monitoring effort are presented.

  1. Photopyroelectric Monitoring of Olive's Ripening Conditions and Olive Oil Quality Using Pulsed Wideband IR Thermal Source

    NASA Astrophysics Data System (ADS)

    Abu-Taha, M. I.; Sarahneh, Y.; Saleh, A. M.

    The present study is based on band absorption of radiation from pulsed wideband infrared (IR) thermal source (PWBS) in conjunction with polyvinylidene fluoride film (PVDF). It is the first time to be employed to monitor the ripening state of olive fruit. Olive's characteristics vary at different stages of ripening, and hence, cultivation of olives at the right time is important in ensuring the best oil quality and maximizes the harvest yield. The photopyroelectric (PPE) signal resulting from absorption of wideband infrared (IR) radiation by fresh olive juice indicates the ripening stage of olives, i.e., allows an estimate of the suitable harvest time. The technique was found to be very useful in discriminating between olive oil samples according to geographical region, shelf life, some storage conditions, and deliberate adulteration. Our results for monitoring oil accumulation in olives during the ripening season agree well with the complicated analytical studies carried out by other researchers.

  2. Condition monitoring and life-cycle cost design of stay cable by embedded OFBG sensors

    NASA Astrophysics Data System (ADS)

    Lan, C. M.; Ju, Y.; Li, H.

    2011-04-01

    Stay cables are one of the most critical structural components of a cable-stayed bridge. However, stay cables readily suffer from fatigue damage, corrosion damage and their coupled effect. Thus, condition monitoring of stay cables is important to ensure the integrity and safety of a bridge. Glass Fibre Reinforced Polymer Optical Fibre Bragg Grating (GFRP-OFBG) cable, a kind of fibre Bragg grating optical sensing technology-based smart stay cables is used in this study. The application of the smart stay cables on the Tianjin Yonghe Bridge was demonstrated and the vehicle live load effect and fatigue effect of smart stay cables were evaluated based on field monitoring data. Furthermore, the life-cycle cost analysis method of the stay cables is established. Finally, based on the nonlinear reliability index deterioration model, the optimal design of stay cable with different reference period is evaluated.

  3. Multivariate Regression with Calibration*

    PubMed Central

    Liu, Han; Wang, Lie; Zhao, Tuo

    2014-01-01

    We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional multivariate regression models. Compared to existing methods, CMR calibrates the regularization for each regression task with respect to its noise level so that it is simultaneously tuning insensitive and achieves an improved finite-sample performance. Computationally, we develop an efficient smoothed proximal gradient algorithm which has a worst-case iteration complexity O(1/ε), where ε is a pre-specified numerical accuracy. Theoretically, we prove that CMR achieves the optimal rate of convergence in parameter estimation. We illustrate the usefulness of CMR by thorough numerical simulations and show that CMR consistently outperforms other high dimensional multivariate regression methods. We also apply CMR on a brain activity prediction problem and find that CMR is as competitive as the handcrafted model created by human experts. PMID:25620861

  4. Innovative monitoring campaign of the environmental conditions of the Stibbert museum in Florence

    NASA Astrophysics Data System (ADS)

    Angelini, E.; Civita, F.; Corbellini, S.; Fulginiti, D.; Giovagnoli, A.; Grassini, S.; Parvis, M.

    2016-02-01

    Conservation of ancient metallic artefact displayed inside museums is a complex problem due to the large number of constraints mainly related to the artefacts fruition by people. The development of a simple procedure for monitoring the artefact conservation state promptly highlighting risky conditions without impacting on the normal museum operations could be of interest in the cultural heritage world. This paper describes the interesting results obtained by using a highly sensitive and innovative methodology for evaluating the safety level of the museum indoor areas, and more specifically of the interior of the showcases, with respect to the metallic artefacts. The methodology is based on the use of an innovative smart sensors network and of copper reference samples. The smart sensors network was employed for the continuous monitoring of temperature and relative humidity close to the artefacts, i.e. inside the display showcases. The reference specimens were Cu coated with a 100 nm Cu nanostructured layer put for 1 year in the exhibition rooms inside and outside the showcases and characterised by means of normal imaging, colorimetric and FESEM techniques at regular intervals. The results of the monitoring activity evidenced the higher reactivity to the environmental aggressivity of the nanocoated copper specimen with respect to bulk artefacts and therefore the possibility to use them as alerts to possible corrosion phenomena that may occur to the real artefacts. A proper temperature and relative humidity monitoring inside the showcases and close to each group of artefacts is a powerful though economic and non-invasive way to highlight most of the possible critical display conditions.

  5. Multivariate Data EXplorer (MDX)

    SciTech Connect

    Steed, Chad Allen

    2012-08-01

    The MDX toolkit facilitates exploratory data analysis and visualization of multivariate datasets. MDX provides and interactive graphical user interface to load, explore, and modify multivariate datasets stored in tabular forms. MDX uses an extended version of the parallel coordinates plot and scatterplots to represent the data. The user can perform rapid visual queries using mouse gestures in the visualization panels to select rows or columns of interest. The visualization panel provides coordinated multiple views whereby selections made in one plot are propagated to the other plots. Users can also export selected data or reconfigure the visualization panel to explore relationships between columns and rows in the data.

  6. Approach towards sensor placement, selection and fusion for real-time condition monitoring of precision machines

    NASA Astrophysics Data System (ADS)

    Er, Poi Voon; Teo, Chek Sing; Tan, Kok Kiong

    2016-02-01

    Moving mechanical parts in a machine will inevitably generate vibration profiles reflecting its operating conditions. Vibration profile analysis is a useful tool for real-time condition monitoring to avoid loss of performance and unwanted machine downtime. In this paper, we propose and validate an approach for sensor placement, selection and fusion for continuous machine condition monitoring. The main idea is to use a minimal series of sensors mounted at key locations of a machine to measure and infer the actual vibration spectrum at a critical point where it is not suitable to mount a sensor. The locations for sensors' mountings which are subsequently used for vibration inference are identified based on sensitivity calibration at these locations moderated with normalized Fisher Information (NFI) associated with the measurement quality of the sensor at that location. Each of the identified sensor placement location is associated with one or more sensitive frequencies for which it ranks top in terms of the moderated sensitivities calibrated. A set of Radial Basis Function (RBF), each of them associated with a range of sensitive frequencies, is used to infer the vibration at the critical point for that frequency. The overall vibration spectrum of the critical point is then fused from these components. A comprehensive set of experimental results for validation of the proposed approach is provided in the paper.

  7. In-Situ Monitoring of Particle Growth at PEMFC Cathode under Accelerated Cycling Conditions

    SciTech Connect

    Redmond, Erin L.; Setzler, Brian P.; Juhas, Pavol; Billinge, Simon J.L.; Fuller, Thomas F.

    2012-10-25

    An in-situ method to measure changes in catalyst particle size at the cathode of a proton exchange membrane fuel cell is demonstrated. Synchrotron X-rays, 58 keV, were used to measure the pair distribution function on an operating fuel cell and observe the growth of catalyst particles under accelerated degradation conditions. The stability of Pt/C and PtCo/C with different initial particle sizes was monitored over 3000 potential cycles. The increase in particle size was fit to a linear trend as a function of cycles. The most stable electrocatalyst was found to be the alloyed PtCo with the larger initial particle size.

  8. An approach to monitoring HVAC (heating ventilating and air conditioning) technology developments in Japan

    SciTech Connect

    Lewis, P.M.; Ashton, W.B.; McDonald, S.C.

    1987-12-01

    This paper presents a discussion of methods for periodicaly monitoring Japanese advanced technology developments for equipment and components in the heating ventilating and air conditioning (HVAC) industry. The emphasis in the approach recommended is on evaluation of foreign literature - both technical and trade publications - because of both the increasing availability of these materials and the usefulness of information they present. Although not a comprehensive nor completely detailed source of information, HVAC technology literature is an important component of ''scanning the business/technical environmental'' for many purposes. Moreover, despite obstacles in obtaining and translating some important literature, useful knowledge can be obtained from many foreign literature sources for relatively modest costs.

  9. A ground test program to support condition monitoring of a spacecraft attitude control propulsion system

    NASA Technical Reports Server (NTRS)

    Clark, Douglas J.; Lester, Robert W.; Baroth, Edmund C.; Coleman, Arthur L.

    1991-01-01

    The Comet Rendezvous Asteroid Flyby (CRAF) mission involves seven years of flight from 0.6 to 4.57 Astronomical Units (AU), followed by about 915 days of maneuvering around a comet. Ground testing will characterize the very critical attitude control system thrusters' fuel consumption and performance for all anticipated fuel temperatures over thruster life. The ground test program characterization will support flight condition monitoring. A commercial software application hosted on a commercial microcomputer will control ground test operations and data acquisition using a newly designed thrust stand. The data acquisition and control system uses a graphics-based language and features a visual interface to integrate data acquisition and control.

  10. Monitoring of forest condition in the Finnish-Russian border region

    SciTech Connect

    Maelkoenen, E.; Lumme, I. ); Tikkanen, E. )

    1994-12-01

    Large industrial and population centers of NW Russia and Estonia are great sources of air pollutants, which is regarded as a threat to the vitality of forests also in Finland. Therefore, the monitoring of forest condition has been set as a central goal of the Finnish-Russian cooperation in the field of environmental protection in near-border districts. Except in the vicinity of emissions sources it has been difficult to distinguish in a scientifically reliable way antropogenic symptoms from natural disturbances and epidemics.

  11. Validity of activity monitors worn at multiple nontraditional locations under controlled and free-living conditions in young adult women.

    PubMed

    Kumahara, Hideaki; Ayabe, Makoto; Ichibakase, Misato; Tashima, Akari; Chiwata, Maiko; Takashi, Tomomi

    2015-05-01

    The purpose of this study was to examine the validity of counting steps and computing indices of moderate-to-vigorous physical activity (MVPA) using miniature activity monitors with 3-D technology worn at various locations under controlled (CON) and free-living conditions (FL). Kenz e-style2, Tanita Calorism Smart, and Omron Calori Scan HJA-306 activity monitors were assessed. Nine and 31 young adult women were assigned to the CON and FL studies, respectively. While walking or jogging on a treadmill at 5 different speeds, the subjects simultaneously carried the 3 different monitors in a pants pocket (PP), a chest shirt pocket, and a shoulder bag (B). Under the FL condition, the 3 monitors were placed only at the PP and B locations for practical reasons. Significant effects of monitor location and walking/jogging speed on the step count measured by the 3 monitors were evaluated under the CON condition. Monitors placed at both PP and B tended to underestimate the number of steps; however, there were no significant differences between the values obtained with the Kenz monitor and those obtained with a criterion accelerometer under the FL condition. Moreover, strong correlations were observed between steps measured by monitors placed at PP and steps measured by the criterion accelerometer. The amount of MVPA for the PP location and the non-carrying duration of the bag for the B location were considered to be important determinants of the accuracy of step counting under the FL condition. In conclusion, monitors placed at the PP location, especially the Kenz monitor, showed acceptable accuracy for young adult women in real-life settings. In contrast, MVPA indices assessed using these monitors showed limited validity. PMID:25832964

  12. Simultaneous multicomponent spectrophotometric monitoring of methyl and propyl parabens using multivariate statistical methods after their preconcentration by robust ionic liquid-based dispersive liquid-liquid microextraction

    NASA Astrophysics Data System (ADS)

    Khani, Rouhollah; Ghasemi, Jahan B.; Shemirani, Farzaneh

    2014-03-01

    A powerful and efficient signal-preprocessing technique that combines local and multiscale properties of the wavelet prism with the global filtering capability of orthogonal signal correction (OSC) is applied for pretreatment of spectroscopic data of parabens as model compounds after their preconcentration by robust ionic liquid-based dispersive liquid-liquid microextraction method (IL-DLLME). In the proposed technique, a mixture of a water-immiscible ionic liquid (as extraction solvent) [Hmim][PF6] and disperser solvent is injected into an aqueous sample solution containing one of the IL's ions, NaPF6, as extraction solvent and common ion source. After preconcentration, the absorbance of the extracted compounds was measured in the wavelength range of 200-700 nm. The wavelet orthogonal signal correction with partial least squares (WOSC-PLS) method was then applied for simultaneous determination of each individual compound. Effective parameters, such as amount of IL, volume of the disperser solvent and amount of NaPF6, were inspected by central composite design to identify the most important parameters and their interactions. The effect of pH on the sensitivity and selectivity was studied according to the net analyte signal (NAS) for each component. Under optimum conditions, enrichment factors of the studied compounds were 75 for methyl paraben (MP) and 71 for propyl paraben (PP). Limits of detection for MP and PP were 4.2 and 4.8 ng mL-1, respectively. The root mean square errors of prediction for MP and PP were 0.1046 and 0.1275 μg mL-1, respectively. The practical applicability of the developed method was examined using hygienic, cosmetic, pharmaceutical and natural water samples.

  13. Simultaneous multicomponent spectrophotometric monitoring of methyl and propyl parabens using multivariate statistical methods after their preconcentration by robust ionic liquid-based dispersive liquid-liquid microextraction.

    PubMed

    Khani, Rouhollah; Ghasemi, Jahan B; Shemirani, Farzaneh

    2014-03-25

    A powerful and efficient signal-preprocessing technique that combines local and multiscale properties of the wavelet prism with the global filtering capability of orthogonal signal correction (OSC) is applied for pretreatment of spectroscopic data of parabens as model compounds after their preconcentration by robust ionic liquid-based dispersive liquid-liquid microextraction method (IL-DLLME). In the proposed technique, a mixture of a water-immiscible ionic liquid (as extraction solvent) [Hmim][PF6] and disperser solvent is injected into an aqueous sample solution containing one of the IL's ions, NaPF6, as extraction solvent and common ion source. After preconcentration, the absorbance of the extracted compounds was measured in the wavelength range of 200-700 nm. The wavelet orthogonal signal correction with partial least squares (WOSC-PLS) method was then applied for simultaneous determination of each individual compound. Effective parameters, such as amount of IL, volume of the disperser solvent and amount of NaPF6, were inspected by central composite design to identify the most important parameters and their interactions. The effect of pH on the sensitivity and selectivity was studied according to the net analyte signal (NAS) for each component. Under optimum conditions, enrichment factors of the studied compounds were 75 for methyl paraben (MP) and 71 for propyl paraben (PP). Limits of detection for MP and PP were 4.2 and 4.8 ng mL(-)(1), respectively. The root mean square errors of prediction for MP and PP were 0.1046 and 0.1275 μg mL(-)(1), respectively. The practical applicability of the developed method was examined using hygienic, cosmetic, pharmaceutical and natural water samples. PMID:24317257

  14. Multivariate Intraclass Correlation.

    ERIC Educational Resources Information Center

    Wiley, David E.; Hawkes, Thomas H.

    This paper is an explication of a statistical model which will permit an interpretable intraclass correlation coefficient that is negative, and a generalized extension of that model to cover a multivariate problem. The methodological problem has its practical roots in an attempt to find a statistic which could indicate the degree of similarity or…

  15. Monitoring the mechanical behaviour of electrically conductive polymer nanocomposites under ramp and creep conditions.

    PubMed

    Pedrazzoli, D; Dorigato, A; Pegoretti, A

    2012-05-01

    Various amounts of carbon black (CB) and carbon nanofibres (CNF) were dispersed in an epoxy resin to prepare nanocomposites whose mechanical behaviour, under ramp and creep conditions, was monitored by electrical measurements. The electrical resistivity of the epoxy resin was dramatically reduced by both nanofillers after the percolation threshold (1 wt% for CB and 0.5 wt% for CNF), reaching values in the range of 10(3)-10(4) omega . cm for filler loadings higher than 2 wt%. Due to the synergistic effects between the nanofillers, an epoxy system containing a total nanofiller amount of 2 wt%, with a relative CB/CNF ratio of 90/10 was selected for the specific applications. A direct correlation between the tensile strain and the increase of the electrical resistance was observed over the whole experimental range, and also the final failure of the samples was clearly detected. Creep tests confirmed the possibility to monitor the various deformational stages under constant loads, with a strong dependency from the temperature and the applied stress. The obtained results are encouraging for a possible application of nanomodified epoxy resin as a matrix for the preparation of structural composites with sensing (i.e., damage-monitoring) capabilities. PMID:22852352

  16. Aspects of structural health and condition monitoring of offshore wind turbines

    PubMed Central

    Antoniadou, I.; Dervilis, N.; Papatheou, E.; Maguire, A. E.; Worden, K.

    2015-01-01

    Wind power has expanded significantly over the past years, although reliability of wind turbine systems, especially of offshore wind turbines, has been many times unsatisfactory in the past. Wind turbine failures are equivalent to crucial financial losses. Therefore, creating and applying strategies that improve the reliability of their components is important for a successful implementation of such systems. Structural health monitoring (SHM) addresses these problems through the monitoring of parameters indicative of the state of the structure examined. Condition monitoring (CM), on the other hand, can be seen as a specialized area of the SHM community that aims at damage detection of, particularly, rotating machinery. The paper is divided into two parts: in the first part, advanced signal processing and machine learning methods are discussed for SHM and CM on wind turbine gearbox and blade damage detection examples. In the second part, an initial exploration of supervisor control and data acquisition systems data of an offshore wind farm is presented, and data-driven approaches are proposed for detecting abnormal behaviour of wind turbines. It is shown that the advanced signal processing methods discussed are effective and that it is important to adopt these SHM strategies in the wind energy sector. PMID:25583864

  17. Aspects of structural health and condition monitoring of offshore wind turbines.

    PubMed

    Antoniadou, I; Dervilis, N; Papatheou, E; Maguire, A E; Worden, K

    2015-02-28

    Wind power has expanded significantly over the past years, although reliability of wind turbine systems, especially of offshore wind turbines, has been many times unsatisfactory in the past. Wind turbine failures are equivalent to crucial financial losses. Therefore, creating and applying strategies that improve the reliability of their components is important for a successful implementation of such systems. Structural health monitoring (SHM) addresses these problems through the monitoring of parameters indicative of the state of the structure examined. Condition monitoring (CM), on the other hand, can be seen as a specialized area of the SHM community that aims at damage detection of, particularly, rotating machinery. The paper is divided into two parts: in the first part, advanced signal processing and machine learning methods are discussed for SHM and CM on wind turbine gearbox and blade damage detection examples. In the second part, an initial exploration of supervisor control and data acquisition systems data of an offshore wind farm is presented, and data-driven approaches are proposed for detecting abnormal behaviour of wind turbines. It is shown that the advanced signal processing methods discussed are effective and that it is important to adopt these SHM strategies in the wind energy sector. PMID:25583864

  18. Condition monitoring methods applied to degradation of chlorosulfonated polyethylene cable jacketing materials.

    SciTech Connect

    Assink, Roger Alan; Gillen, Kenneth Todd; Bernstein, Robert; Celina, Mathias Christopher

    2005-05-01

    Three promising polymer material condition monitoring (CM) methods were applied to eight commercial chlorosulfonated polyethylene cable jacket materials aged under both elevated temperature and high-energy radiation conditions. The CM methods examined, cross-sectional modulus profiling, solvent uptake and NMR T{sub 2} relaxation time measurements of solvent-swelled samples, are closely related since they are all strongly influenced by the changes in overall crosslink density of the materials. Each approach was found to correlate well with ultimate tensile elongation measurements, the most widely used method for following degradation of elastomeric materials. In addition approximately universal failure criteria were found to be applicable for the modulus profiling and solvent uptake measurements, independent of the CSPE material examined and its degradation environment. For an arbitrarily assumed elongation 'failure' criterion of 50% absolute, the CSPE materials typically reached 'failure' when the modulus increased to {approx}35 MPa and the uptake factor in p-xylene decreased to {approx}1.6.

  19. A dynamical model for condition monitoring and fault diagnostics of spur gears

    SciTech Connect

    Paya, B.; Esat, I.; Badi, M.N.M.

    1996-12-31

    The symptoms of condition monitoring and fault diagnostics of machinery based on the dynamic modelling of spur gears are discussed in this paper. The mathematical model presented in the earlier work, assumes two degree of freedom for each gear and the rotor, and also incorporates a varying gear tooth stiffness. This system is assumed to be in good condition (i.e. no fault present). The results obtained from this analytical model are compared with the ones obtained from an experimental model gearbox. This experimental gearbox consists of two meshing spur gears driven by an electric motor. The comparison of the results are encouraging as fundamental (dominant) frequencies of the analytical results correlates very closely to the experimental ones. It is shown that certain vibration frequency of a real gearbox such as the tooth meshing frequencies can be achieved from its mathematical model.

  20. Technical Needs for Enhancing Risk Monitors with Equipment Condition Assessment for Advanced Small Modular Reactors

    SciTech Connect

    Coble, Jamie B.; Coles, Garill A.; Ramuhalli, Pradeep; Meyer, Ryan M.; Berglin, Eric J.; Wootan, David W.; Mitchell, Mark R.

    2013-04-04

    Advanced small modular reactors (aSMRs) can provide the United States with a safe, sustainable, and carbon-neutral energy source. The controllable day-to-day costs of aSMRs are expected to be dominated by operation and maintenance costs. Health and condition assessment coupled with online risk monitors can potentially enhance affordability of aSMRs through optimized operational planning and maintenance scheduling. Currently deployed risk monitors are an extension of probabilistic risk assessment (PRA). For complex engineered systems like nuclear power plants, PRA systematically combines event likelihoods and the probability of failure (POF) of key components, so that when combined with the magnitude of possible adverse consequences to determine risk. Traditional PRA uses population-based POF information to estimate the average plant risk over time. Currently, most nuclear power plants have a PRA that reflects the as-operated, as-modified plant; this model is updated periodically, typically once a year. Risk monitors expand on living PRA by incorporating changes in the day-by-day plant operation and configuration (e.g., changes in equipment availability, operating regime, environmental conditions). However, population-based POF (or population- and time-based POF) is still used to populate fault trees. Health monitoring techniques can be used to establish condition indicators and monitoring capabilities that indicate the component-specific POF at a desired point in time (or over a desired period), which can then be incorporated in the risk monitor to provide a more accurate estimate of the plant risk in different configurations. This is particularly important for active systems, structures, and components (SSCs) proposed for use in aSMR designs. These SSCs may differ significantly from those used in the operating fleet of light-water reactors (or even in LWR-based SMR designs). Additionally, the operating characteristics of aSMRs can present significantly different

  1. The use of the motor as a transducer to monitor pump conditions

    SciTech Connect

    Casada, D.A.; Bunch, S.L.

    1995-12-31

    Motor current and power analysis methods have been developed to assist in the condition monitoring of a variety of motor-driven devices. The successful implementation of motor current signature analysis (MCSA) as a diagnostic for valves led to its application to other devices and to refinements in the methodologies used. A variety of pump applications, ranging from 5 to over 1200 horsepower have been analyzed, including low and high specific speed and suction specific speed pumps. For some of the pumps, the full range of flow conditions from shutoff to runout has been studied. Motor current and power analysis have been found to provide information that is complementary to that available from conventional diagnostics, such as vibration and pressure pulsation analysis. Inherent signal filtering associated with rotor to stator magnetic field coupling does limit the high frequency response capability of the motor as a transducer; as a result certain phenomena, such as vane pass energy, is not readily apparent in the motor electrical signals. On the other hand, the motor-monitored parameters have often been found to be much more sensitive than vibration transducers in detecting the effects of unsteady flow conditions resulting from both system and pump specific sources such as suction cavitation. By combining motor equivalent circuit models with pump performance characteristics, shaft power and torque fluctuation estimates have been assessed. The usefulness of motor data in assessing some common sources of pump problems, such as mechanical and hydraulic imbalance, misalignment, and unstable flow conditions is shown. The results of testing several motor-driven pumps, including comparisons with vibration and pressure pulsation analysis are discussed. The development of a single figure of merit for pump load stability (as a function of pump flow rate and type) is presented.

  2. Ecological Indicators and Monitoring Systems are Needed to Track Changing Ecosystem Condition in the United States

    NASA Astrophysics Data System (ADS)

    Negra, C.; O'Malley, R.; Cavender-Bares, K.

    2007-12-01

    Well-designed ecological indicators are important tools for tracking the cumulative effects of land management, disturbance patterns and climate on the biogeochemical condition of ecosystems. Indicators can be used to identify direct and indirect ecological responses to major stressors, to evaluate the effectiveness of management strategies and to understand potential changes in provision of ecological services. To contextualize the magnitude of contemporary ecological changes, long-term data sources are needed for indicator metrics. In the absence of ongoing, objective monitoring programs, public and private environmental decisions will not be adequately supported by scientifically sound baseline or trend information. In the State of the Nation's Ecosystems, the Heinz Center reports on 108 indicators selected to represent the most important components of major terrestrial and aquatic ecosystem types in the U.S. A central finding of this effort is the large number of gaps in available datasets to populate key ecological indicators. The 2008 edition of the report will have complete data for 42 indicators, partial data for 27 indicators and data gaps for 28 indicators (11 indicators require further development). The U.S. Government Accountability Office (GAO) and the Heinz Center have produced major assessments of the status of environmental monitoring systems. The GAO report highlights eroding data-gathering capacity in the face of funding constraints and expanding information demands. The Heinz Center report maps out specific technical challenges in filling high-priority, national-scale data gaps and addresses barriers to integration and efficiency in the nation's overall monitoring system. This presentation will focus on crucial environmental monitoring needs for reporting on U.S. ecological indicators. Key concepts for effective monitoring systems will be presented including: (1) design to capture essential dynamics of ecosystems and to establish credible

  3. Incorporating Equipment Condition Assessment in Risk Monitors for Advanced Small Modular Reactors

    SciTech Connect

    Coble, Jamie B.; Coles, Garill A.; Meyer, Ryan M.; Ramuhalli, Pradeep

    2013-10-01

    Advanced small modular reactors (aSMRs) can complement the current fleet of large light-water reactors in the USA for baseload and peak demand power production and process heat applications (e.g., water desalination, shale oil extraction, hydrogen production). The day-to-day costs of aSMRs are expected to be dominated by operations and maintenance (O&M); however, the effect of diverse operating missions and unit modularity on O&M is not fully understood. These costs could potentially be reduced by optimized scheduling, with risk-informed scheduling of maintenance, repair, and replacement of equipment. Currently, most nuclear power plants have a “living” probabilistic risk assessment (PRA), which reflects the as-operated, as-modified plant and combine event probabilities with population-based probability of failure (POF) for key components. “Risk monitors” extend the PRA by incorporating the actual and dynamic plant configuration (equipment availability, operating regime, environmental conditions, etc.) into risk assessment. In fact, PRAs are more integrated into plant management in today’s nuclear power plants than at any other time in the history of nuclear power. However, population-based POF curves are still used to populate fault trees; this approach neglects the time-varying condition of equipment that is relied on during standard and non-standard configurations. Equipment condition monitoring techniques can be used to estimate the component POF. Incorporating this unit-specific estimate of POF in the risk monitor can provide a more accurate estimate of risk in different operating and maintenance configurations. This enhanced risk assessment will be especially important for aSMRs that have advanced component designs, which don’t have an available operating history to draw from, and often use passive design features, which present challenges to PRA. This paper presents the requirements and technical gaps for developing a framework to integrate unit

  4. Design and Realization of Rotating Machinery Conditions Monitoring System Based on Labview

    NASA Astrophysics Data System (ADS)

    Fan, Qiyuan

    Nonlinear dynamic analysis of rotating machinery system has always been the hot spot of the rotational dynamics research. This article sets up a rotating machinery condition monitoring system to realize the measurement of system dynamic characteristic parameters based on NI(National Instruments) virtual instruments technology. The measurement of vibration signal of rotating machinery system is achieved by using NI company general data acquisition module of NI company. Meanwhile, by analyzing and processing the acquired data using Labview 2012, the dynamic characteristics, such as .the speed of the rotating machinery system, the axis trajectory, spectrum parameters, are attained. The measurement results show that the rotating machinery condition monitoring system based on Labview is easy to operate, easy to realize the function extension and maintenance, and that it can be used in the industrial engineering projects with rotation characteristics. Labview as the development tools used by virtual instrument function, is very powerful data acquisition software products support is one of the features of it, so using Labview programming and data acquisition is simple and convenient [1].

  5. Testing ZigBee Motes for Monitoring Refrigerated Vegetable Transportation under Real Conditions

    PubMed Central

    Ruiz-Garcia, Luis; Barreiro, Pilar; Robla, Jose Ignacio; Lunadei, Loredana

    2010-01-01

    Quality control and monitoring of perishable goods during transportation and delivery services is an increasing concern for producers, suppliers, transport decision makers and consumers. The major challenge is to ensure a continuous ‘cold chain’ from producer to consumer in order to guaranty prime condition of goods. In this framework, the suitability of ZigBee protocol for monitoring refrigerated transportation has been proposed by several authors. However, up to date there was not any experimental work performed under real conditions. Thus, the main objective of our experiment was to test wireless sensor motes based in the ZigBee/IEEE 802.15.4 protocol during a real shipment. The experiment was conducted in a refrigerated truck traveling through two countries (Spain and France) which means a journey of 1,051 kilometers. The paper illustrates the great potential of this type of motes, providing information about several parameters such as temperature, relative humidity, door openings and truck stops. Psychrometric charts have also been developed for improving the knowledge about water loss and condensation on the product during shipments. PMID:22399917

  6. Condition monitoring requirements for the development of a space nuclear propulsion module

    NASA Technical Reports Server (NTRS)

    Wagner, Robert C.

    1993-01-01

    To facilitate the development of a space nuclear propulsion module for manned flights to Mars, requirements must be established early in the technology cycle. The long lead times for the acquisition of the engine system and nuclear test facilities demands that the engine system, size, performance, safety goals and condition monitoring philosophy be defined at the earliest possible time. These systems are highly complex and require a large multi-disciplinary systems engineering team to develop and track the requirements and to ensure that the as-built system reflects the intent of the mission. An effective methodology has been devised coupled with sophisticated computer tools to effectivly develop and interpret the functional requirements. These requirements can then be decomposed down to the specification level for implementation. This paper discusses the application of the methodology and the analyses to develop condition monitoring requirements under a contract with the National Aeronautics and Space Administration (NASA) Lewis Research Center (LeRC) Nuclear Propulsion Office (NPO).

  7. The use of the motor as a transducer to monitor system conditions

    SciTech Connect

    Casada, D.A.; Bunch, S.L.

    1996-01-26

    Motor current and power analysis methods have been developed to assist in the condition monitoring of a variety of motor-driven devices. The early work in this area was conducted at Oak Ridge National Laboratory (ORNL) on motor-operated valves in the mid-to-late 1980`s in support of the US Nuclear Regulatory Commission`s Nuclear Plant Aging Research Program. The successful implementation of motor current signature analysis (MCSA) as a diagnostic for valves led to its application to other devices and to refinements in the methodologies used. Motor current and power analysis have been found to provide information that is complementary to that available from conventional diagnostics, such as vibration and pressure pulsation analysis. Inherent signal filtering associated with rotor to stator magnetic field coupling does limit the high frequency response capability of the motor as a transducer; as a result, certain phenomena, such as pump or fan vane pass energy, is not readily apparent in the motor electrical signals. On the other hand, the motor-monitored parameters have often been found to be much more sensitive than vibration transducers in detecting the effects of unsteady process conditions resulting from both system and process specific sources.

  8. Interactive graphics on large datasets drives remote condition monitoring on a cloud

    NASA Astrophysics Data System (ADS)

    Hickinbotham, Simon; Austin, James; McAvoy, John

    2012-05-01

    We demonstrate a new system for condition monitoring using the cloud. The system combines state of the art pattern search capability with youShare, a platform that allows people to run compute-intensive research in an ordered manner over the internet. Data from sensors distributed across one or more assets at one or more sites are uploaded to the cloud compute resource. The uploading triggers the deployment of a range of pattern search services, and is capable of rapidly detecting novel patterns in the data. The outputs of these processes are archived as a matter of course, but are also sent to a further service which processes the data for remote visualisation on a web browser. The system is built in Java, using GWT and RaphaelGWT for graphics rendering. The design of these systems must satisfy conflicting requirements of data currency and data throughput. We present an evaluation of our system that involves processing data at a range of frequencies and bandwidths that are commensurate with commercial requirements. We show that our system has the potential to satisfy a range of processing requirements with minimal latency, and that the user experience is easily sufficient for rapid interpretation of complex condition monitoring data.

  9. Remote monitoring of parental incubation conditions in the greater sandhill crane

    USGS Publications Warehouse

    Gee, G.F.; Hatfield, J.; Howey, P.J.

    1995-01-01

    To monitor incubation conditions in nests of greater sandhill cranes, a radiotransmitting egg was built using six temperature sensors, a position sensor, and a light sensor. Sensor readings were received, along with time of observations, and stored in a computer. The egg was used to monitor incubation in nests of six pairs of cranes during 1987 and 1988. Ambient temperature was also measured. Analysis of covariance (ANCOVA) was used to relate highest egg temperature, core egg temperature, and lowest egg temperature to ambient temperature, time since the egg was last turned, and time since the beginning of incubation. Ambient temperature had the greatest effect on egg temperature (P 0.0001), followed by the time since the beginning of incubation and time since the egg was last turned. Pair effect, the class variable in the ANCOVA. was also very significant (P < 0.0001). A nine-term Fourier series was used to estimate the average core egg temperature versus time of day and was found to fit the data well (r2 = 0.94). The Fourier series will be used to run a mechanical incubator to simulate natural incubation conditions for cranes.

  10. Personal sampler for monitoring of viable viruses; modelling of outdoor sampling conditions

    NASA Astrophysics Data System (ADS)

    Borodulin, A. I.; Desyatkov, B. M.; Lapteva, N. A.; Sergeev, A. N.; Agranovski, I. E.

    A new personal bioaerosol sampler has recently been developed and verified to be very efficient for monitoring of viable airborne bacteria, fungi and viruses. The device is capable of providing high recovery rates even for microorganisms which are rather sensitive to physical and biological stresses. However, some mathematical procedure is required for realistic calculation of an actual concentration of viable bioaerosols in the air taking into account a rate of inactivation of targeted microorganisms, sampling parameters, and results of microbial analysis of collecting liquid from the sampler. In this paper, we develop such procedure along with the model of aerosol propagation for outdoor conditions. Combining these procedures allows one to determine the optimal sampling locations for the best possible coverage of the area to be monitored. A hypothetical episode concerned with terrorists' attack during music concert in the central square of Novosibirsk, Russia was considered to evaluate possible coverage of the area by sampling equipment to detect bioaerosols at various locations within the square. It was found that, for chosen bioaerosol generation parameters and weather conditions, the new personal sampler would be capable to reliably detect pathogens at all locations occupied by crowd, even at distances of up to 600 m from the source.

  11. Adaptive responses of the cardiovascular system to prolonged spaceflight conditions: assessment with Holter monitoring

    NASA Technical Reports Server (NTRS)

    Baevsky, R. M.; Bennett, B. S.; Bungo, M. W.; Charles, J. B.; Goldberger, A. L.; Nikulina, G. A.

    1997-01-01

    This article presents selected findings obtained with Holter monitoring from two crew members of the expedition, performed during a 175-day space mission on board orbital space station "MIR." Using mathematical processing of daily cardiointervals files, 5-minute sections of records were analyzed consecutively. Then, the average daily values of indices, the average-per-every-eight-hours values (morning, evening, night) and mean values per hour were computed. The results of analysis showed that prolonged exposure of man to microgravity conditions leads to important functional alteration in human neuroautonomic regulatory mechanisms. Both crew members had significant increase of heart rate, the rise of stress index, the decrease in power of the spectrum in the range of respiratory sinus arrhythmia. These marked signs of activation of the sympathetic section of the vegetative nervous system showed individual variations. The analysis of the daily collection of cardiointervals with Holter monitoring allows us to understand and forecast the functional feasibilities of the human organism under a variety of stress conditions associated with acute and chronic microgravity exposure.

  12. Condition monitoring and optimization for a 1000 MW combined-cycle plant

    SciTech Connect

    1995-10-01

    Barking Power Ltd., an independent power producer in the southeast of England, appointed Boyce Engineering International to supply a performance condition monitoring and optimization package. The Barking Power combined-cycle plant operates five Frame 9E gas turbines manufactured by EGT in Belfort, France, and two steam turbines supplied by GEC Alsthom. The Boyce Engineering system selected by Power Ltd., is the DATM4 fully integrated condition monitoring system, which offers full diagnosis and optimization for the electrical, mechanical and thermal performance of the plant. The transient electrical analysis system will enable operating and maintenance engineers to diagnose and reduce problems caused by transient electrical impulses which may occur. All four modules will be handled on a single hardware platform using an OS/2 PC network. The Boyce system offers a number of distinct benefits to the customer, particularly in terms of maximizing profitability. Additional benefits of the system include a `what if` module, allowing engineers to troubleshoot aspects of the plant, evaluate the cost of any inefficiencies in relation to the plant`s bottom line and schedule maintenance efficiently, and the ability to ensure safe and clean operation meeting and exceeding current environmental legislative requirements.

  13. Phenomenological models of vibration signals for condition monitoring and fault diagnosis of epicyclic gearboxes

    NASA Astrophysics Data System (ADS)

    Lei, Yaguo; Liu, Zongyao; Lin, Jing; Lu, Fanbo

    2016-05-01

    Condition monitoring and fault diagnosis of epicyclic gearboxes using vibration signals are not as straightforward as that of fixed-axis gearboxes since epicyclic gearboxes behave quite differently from fixed-axis gearboxes in many aspects, like spectral structures. Aiming to present the spectral structures of vibration signals of epicyclic gearboxes, phenomenological models of vibration signals of epicyclic gearboxes are developed by algebraic equations and spectral structures of these models are deduced using Fourier series analysis. In the phenomenological models, all the possible vibration transfer paths from gear meshing points to a fixed transducer and the effects of angular shifts of planet gears on the spectral structures are considered. Accordingly, time-varying vibration transfer paths from sun-planet/ring-planet gear meshing points to the fixed transducer due to carrier rotation are given by window functions with different amplitudes. And an angular shift in one planet gear position is introduced in the process of modeling. After the theoretical derivations, three experiments are conducted on an epicyclic gearbox test rig and the spectral structures of collected vibration signals are analyzed. As a result, the effects of angular shifts of planet gears are verified, and the phenomenological models of vibration signals when a local fault occurs on the sun gear and the planet gear are validated, respectively. The experiment results demonstrate that the established phenomenological models in this paper are helpful to the condition monitoring and fault diagnosis of epicyclic gearboxes.

  14. Testing ZigBee motes for monitoring refrigerated vegetable transportation under real conditions.

    PubMed

    Ruiz-Garcia, Luis; Barreiro, Pilar; Robla, Jose Ignacio; Lunadei, Loredana

    2010-01-01

    Quality control and monitoring of perishable goods during transportation and delivery services is an increasing concern for producers, suppliers, transport decision makers and consumers. The major challenge is to ensure a continuous 'cold chain' from producer to consumer in order to guaranty prime condition of goods. In this framework, the suitability of ZigBee protocol for monitoring refrigerated transportation has been proposed by several authors. However, up to date there was not any experimental work performed under real conditions. Thus, the main objective of our experiment was to test wireless sensor motes based in the ZigBee/IEEE 802.15.4 protocol during a real shipment. The experiment was conducted in a refrigerated truck traveling through two countries (Spain and France) which means a journey of 1,051 kilometers. The paper illustrates the great potential of this type of motes, providing information about several parameters such as temperature, relative humidity, door openings and truck stops. Psychrometric charts have also been developed for improving the knowledge about water loss and condensation on the product during shipments. PMID:22399917

  15. Adaptive responses of the cardiovascular system to prolonged spaceflight conditions: assessment with Holter monitoring.

    PubMed

    Baevsky, R M; Bennett, B S; Bungo, M W; Charles, J B; Goldberger, A L; Nikulina, G A

    1997-01-01

    This article presents selected findings obtained with Holter monitoring from two crew members of the expedition, performed during a 175-day space mission on board orbital space station "MIR." Using mathematical processing of daily cardiointervals files, 5-minute sections of records were analyzed consecutively. Then, the average daily values of indices, the average-per-every-eight-hours values (morning, evening, night) and mean values per hour were computed. The results of analysis showed that prolonged exposure of man to microgravity conditions leads to important functional alteration in human neuroautonomic regulatory mechanisms. Both crew members had significant increase of heart rate, the rise of stress index, the decrease in power of the spectrum in the range of respiratory sinus arrhythmia. These marked signs of activation of the sympathetic section of the vegetative nervous system showed individual variations. The analysis of the daily collection of cardiointervals with Holter monitoring allows us to understand and forecast the functional feasibilities of the human organism under a variety of stress conditions associated with acute and chronic microgravity exposure. PMID:11539935

  16. Circular domain features based condition monitoring for low speed slewing bearing

    NASA Astrophysics Data System (ADS)

    Caesarendra, Wahyu; Kosasih, Buyung; Tieu, Anh Kiet; Moodie, Craig A. S.

    2014-03-01

    This paper presents a novel application of circular domain features calculation based condition monitoring method for low rotational speed slewing bearing. The method employs data reduction process using piecewise aggregate approximation (PAA) to detect frequency alteration in the bearing signal when the fault occurs. From the processed data, circular domain features such as circular mean, circular variance, circular skewness and circular kurtosis are calculated and monitored. It is shown that the slight changes of bearing condition during operation can be identified more clearly in circular domain analysis compared to time domain analysis and other advanced signal processing methods such as wavelet decomposition and empirical mode decomposition (EMD) allowing the engineer to better schedule the maintenance work. Four circular domain features were shown to consistently and clearly identify the onset (initiation) of fault from the peak feature value which is not clearly observable in time domain features. The application of the method is demonstrated with simulated data, laboratory slewing bearing data and industrial bearing data from Coal Bridge Reclaimer used in a local steel mill.

  17. PREFACE: 25th International Congress on Condition Monitoring and Diagnostic Engineering (COMADEM 2012)

    NASA Astrophysics Data System (ADS)

    Ball, Andrew; Mishra, Rakesh; Gu, Fengshou; Rao, Raj B. K. N.

    2012-05-01

    The proactive multidisciplinary conceptual philosophy of Condition Monitoring and Diagnostic Engineering Management (COMADEM) was conceived and has been nurtured, developed and sustained since 1988. Since then, it is gratifying to note that the condition monitoring, diagnostic and prognostic community worldwide (representing industrialists, academics, research and development organizations, professional/private establishments and many hardware/software vending organizations) has warmly welcomed and supported this venture. As is evidenced, many have reaped (and are reaping) the benefits of COMADEM interdiscipline through continuous knowledge discovery, generation and dissemination. We are now proud to celebrate the 25th Annual Event (Silver Jubilee) in Huddersfield, the most beautiful part of the United Kingdom. The theme of this Congress is 'Sustained Prosperity through Proactive Monitoring, Diagnosis, Prognosis and Management'. This proceedings is enriched by contributions from many keynote experts representing many industry and academic establishments worldwide. Authors from more than 30 different countries have pooled their rich multidisciplinary up-to-date knowledge, in order to share their invaluable experience with the COMADEM community. In this proceedings, the readers will find more than 120 refereed papers encompassing a number of topical areas of interest relating to the theme of the congress. The proceedings of COMADEM 2012 will appear in the Open Access Journal of Physics: Conference Series (JPCS), which is part of the IOP Conference Series. All papers published in the IOP Conference Series are fully citable and upon publication will be free to download. We would like to express our deep gratitude to all the keynote speakers, authors, referees, exhibitors, Technical Co-Sponsoring Organizations, Gold Sponsors, IOP Publishers, COMADEM 2012 organizing committee members, delegates and many others on whom the success of this prestigious event depends

  18. Skeletal Anomaly Monitoring in Rainbow Trout (Oncorhynchus mykiss, Walbaum 1792) Reared under Different Conditions

    PubMed Central

    Boglione, Clara; Pulcini, Domitilla; Scardi, Michele; Palamara, Elisa; Russo, Tommaso; Cataudella, Stefano

    2014-01-01

    The incidence of skeletal anomalies could be used as an indicator of the “quality” of rearing conditions as these anomalies are thought to result from the inability of homeostatic mechanisms to compensate for environmentally-induced stress and/or altered genetic factors. Identification of rearing conditions that lower the rate of anomalies can be an important step toward profitable aquaculture as malformed market-size fish have to be discarded, thus reducing fish farmers’ profits. In this study, the occurrence of skeletal anomalies in adult rainbow trout grown under intensive and organic conditions was monitored. As organic aquaculture animal production is in its early stages, organic broodstock is not available in sufficient quantities. Non-organic juveniles could, therefore, be used for on-growing purposes in organic aquaculture production cycle. Thus, the adult fish analysed in this study experienced intensive conditions during juvenile rearing. Significant differences in the pattern of anomalies were detected between organically and intensively-ongrown specimens, although the occurrence of severe, commercially important anomalies, affecting 2–12.5% of individuals, was comparable in the two systems. Thus, organic aquaculture needs to be improved in order to significantly reduce the incidence of severe anomalies in rainbow trout. PMID:24809347

  19. Condition index monitoring supports conservation priorities for the protection of threatened grass-finch populations

    PubMed Central

    Maute, Kimberly; French, Kristine; Legge, Sarah; Astheimer, Lee; Garnett, Stephen

    2015-01-01

    Conservation agencies are often faced with the difficult task of prioritizing what recovery actions receive support. With the number of species under threat of decline growing globally, research that informs conservation priorities is greatly needed. The relative vulnerability of cryptic or nomadic species is often uncertain, because populations are difficult to monitor and local populations often seem stable in the short term. This uncertainty can lead to inaction when populations are in need of protection. We tested the feasibility of using differences in condition indices as an indication of population vulnerability to decline for related threatened Australian finch sub-species. The Gouldian finch represents a relatively well-studied endangered species, which has a seasonal and site-specific pattern of condition index variation that differs from the closely related non-declining long-tailed finch. We used Gouldian and long-tailed finch condition variation as a model to compare with lesser studied, threatened star and black-throated finches. We compared body condition (fat and muscle scores), haematocrit and stress levels (corticosterone) among populations, seasons and years to determine whether lesser studied finch populations matched the model of an endangered species or a non-declining species. While vulnerable finch populations often had lower muscle and higher fat and corticosterone concentrations during moult (seasonal pattern similar to Gouldian finches), haematocrit values did not differ among populations in a predictable way. Star and black-throated finch populations, which were predicted to be vulnerable to decline, showed evidence of poor condition during moult, supporting their status as vulnerable. Our findings highlight how measures of condition can provide insight into the relative vulnerability of animal and plant populations to decline and will allow the prioritization of efforts towards the populations most likely to be in jeopardy of extinction

  20. Condition index monitoring supports conservation priorities for the protection of threatened grass-finch populations.

    PubMed

    Maute, Kimberly; French, Kristine; Legge, Sarah; Astheimer, Lee; Garnett, Stephen

    2015-01-01

    Conservation agencies are often faced with the difficult task of prioritizing what recovery actions receive support. With the number of species under threat of decline growing globally, research that informs conservation priorities is greatly needed. The relative vulnerability of cryptic or nomadic species is often uncertain, because populations are difficult to monitor and local populations often seem stable in the short term. This uncertainty can lead to inaction when populations are in need of protection. We tested the feasibility of using differences in condition indices as an indication of population vulnerability to decline for related threatened Australian finch sub-species. The Gouldian finch represents a relatively well-studied endangered species, which has a seasonal and site-specific pattern of condition index variation that differs from the closely related non-declining long-tailed finch. We used Gouldian and long-tailed finch condition variation as a model to compare with lesser studied, threatened star and black-throated finches. We compared body condition (fat and muscle scores), haematocrit and stress levels (corticosterone) among populations, seasons and years to determine whether lesser studied finch populations matched the model of an endangered species or a non-declining species. While vulnerable finch populations often had lower muscle and higher fat and corticosterone concentrations during moult (seasonal pattern similar to Gouldian finches), haematocrit values did not differ among populations in a predictable way. Star and black-throated finch populations, which were predicted to be vulnerable to decline, showed evidence of poor condition during moult, supporting their status as vulnerable. Our findings highlight how measures of condition can provide insight into the relative vulnerability of animal and plant populations to decline and will allow the prioritization of efforts towards the populations most likely to be in jeopardy of extinction

  1. Monitoring electron donor metabolism under variable electron acceptor conditions using 13C-labeled lactate

    NASA Astrophysics Data System (ADS)

    Bill, M.; Conrad, M. E.; Yang, L.; Beller, H. R.; Brodie, E. L.

    2010-12-01

    Three sets of flow-through columns constructed with aquifer sediment from Hanford (WA) were used to study reduction of Cr(VI) to poorly soluble Cr(III) under denitrifying, sulfate-reducing/fermentative, and iron-reducing conditions with lactate as the electron donor. In order to understand the relationship between electron donors and biomarkers, and to determine the differences in carbon isotope fractionation resulting from different microbial metabolic processes, we monitored the variation in carbon isotopes in dissolved inorganic carbon (DIC), in total organic carbon (TOC), and in lactate, acetate and propionate. The greatest enrichment in 13C in columns was observed under denitrifying conditions. The δ13C of DIC increased by ~1750 to ~2000‰ fifteen days after supplementation of natural abundance lactate with a 13C-labeled lactate tracer (for an influent δ13C of ~2250‰ for the lactate) indicating almost complete oxidation of the electron donor. The denitrifying columns were among the most active columns and had the highest cell counts and the denitrification rate was highly correlated with Cr(VI) reduction rate. δ13C values of DIC ranged from ~540 to ~1170‰ for iron-reducing conditions. The lower enrichment in iron columns was related to the lower biological activity observed with lower yields of RNA and cell numbers in the column effluents. The carbon isotope shift in the sulfate-reducing ~198 to ~1960‰ for sulfate-reducing conditions reflecting the lower levels of the lactate in these columns. Additionally, in two of the sulfate columns, almost complete fermentation of the lactate occurred, producing acetate and propionate with the labeled carbon signature, but relatively smaller amounts of inorganic carbon. For all electron-accepting conditions, TOC yielded similar δ13C values as lactate stock solutions. Differences in C use efficiency, metabolic rate or metabolic pathway contributed to the differing TOC δ13C to DIC δ13C ratios between treatments

  2. Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production

    NASA Astrophysics Data System (ADS)

    Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.

    2014-12-01

    The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key indicators pay more attention to crops and include Vegetation health index (VHI), Vegetation condition index (VCI), Cropped arable land fraction (CALF) as well as Cropping intensity (CI). Together, they characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are

  3. Developing RCM Strategy for Hydrogen Fuel Cells Utilizing On Line E-Condition Monitoring

    NASA Astrophysics Data System (ADS)

    Baglee, D.; Knowles, M. J.

    2012-05-01

    Fuel cell vehicles are considered to be a viable solution to problems such as carbon emissions and fuel shortages for road transport. Proton Exchange Membrane (PEM) Fuel Cells are mainly used in this purpose because they can run at low temperatures and have a simple structure. Yet high maintenance costs and the inherent dangers of maintaining equipment using hydrogen are two main issues which need to be addressed. The development of appropriate and efficient strategies is currently lacking with regard to fuel cell maintenance. A Reliability Centered Maintenance (RCM) approach offers considerable benefit to the management of fuel cell maintenance since it includes an identification and consideration of the impact of critical components. Technological developments in e-maintenance systems, radio-frequency identification (RFID) and personal digital assistants (PDAs) have proven to satisfy the increasing demand for improved reliability, efficiency and safety. RFID technology is used to store and remotely retrieve electronic maintenance data in order to provide instant access to up-to-date, accurate and detailed information. The aim is to support fuel cell maintenance decisions by developing and applying a blend of leading-edge communications and sensor technology including RFID. The purpose of this paper is to review and present the state of the art in fuel cell condition monitoring and maintenance utilizing RCM and RFID technologies. Using an RCM analysis critical components and fault modes are identified. RFID tags are used to store the critical information, possible faults and their cause and effect. The relationship between causes, faults, symptoms and long term implications of fault conditions are summarized. Finally conclusions are drawn regarding suggested maintenance strategies and the optimal structure for an integrated, cost effective condition monitoring and maintenance management system.

  4. Monitoring the condition of the Canadian forest environment: The relevance of the concept of 'ecological indicators'.

    PubMed

    Kimmins, J P

    1990-11-01

    The Canadian forest environment is characterized by high spatial and temporal variability, especially in the west. Our forests vary according to climate, landform, and surficial geology, and according to the type, intensity, extent of, and the time since the last disturbance. Most Canadian forests have had a history of repeated acute, episodic disturbance from fire, insects, wind, diseases and/or logging, with a frequency of disturbance varying from a few decades to many centuries. These sources of variability have resulted in a complex and continually changing mosaic of forest conditions and stages of successional development.Monitoring the 'quality' of this dynamic forested landscape mosaic is extremely difficult, and in most cases the concept of a relatively simple index of forest ecosystem quality or condition (i.e. an 'ecological indicator') is probably inappropriate. Such ecological indicators are better suited for monitoring chronic anthropogenically induced disturbances that are continuous in their effect (e.g. 'acid rain', heavy metal pollution, air pollution, and the 'greenhouse effect') in ecosystems that, in the absence of such chronic disturbance, exhibit very slow directional change (e.g. lakes, higher order streams and rivers). Monitoring the effects of a chronic anthropogenic disturbance to forest ecosystems to determine if it is resulting in a sustained, directional alteration of environmental 'quality' will require a definition of the expected pattern of episodic disturbance and recovery therefrom (i.e. patterns of secondary succession in the absence of the chronic disturbance). Only when we have such a 'temporal fingerprint' of forest ecosystem condition for 'normal' patterns of disturbance and recovery can we determine if the ecosystem condition is being degraded by chronic human-induced alteration of the environment. Thus, degradation is assessed in terms of deviations from the expected temporal pattern of conditions rather than in terms of an

  5. Multivariate Analysis in Metabolomics

    PubMed Central

    Worley, Bradley; Powers, Robert

    2015-01-01

    Metabolomics aims to provide a global snapshot of all small-molecule metabolites in cells and biological fluids, free of observational biases inherent to more focused studies of metabolism. However, the staggeringly high information content of such global analyses introduces a challenge of its own; efficiently forming biologically relevant conclusions from any given metabolomics dataset indeed requires specialized forms of data analysis. One approach to finding meaning in metabolomics datasets involves multivariate analysis (MVA) methods such as principal component analysis (PCA) and partial least squares projection to latent structures (PLS), where spectral features contributing most to variation or separation are identified for further analysis. However, as with any mathematical treatment, these methods are not a panacea; this review discusses the use of multivariate analysis for metabolomics, as well as common pitfalls and misconceptions. PMID:26078916

  6. Multivariate Data EXplorer (MDX)

    Energy Science and Technology Software Center (ESTSC)

    2012-08-01

    The MDX toolkit facilitates exploratory data analysis and visualization of multivariate datasets. MDX provides and interactive graphical user interface to load, explore, and modify multivariate datasets stored in tabular forms. MDX uses an extended version of the parallel coordinates plot and scatterplots to represent the data. The user can perform rapid visual queries using mouse gestures in the visualization panels to select rows or columns of interest. The visualization panel provides coordinated multiple views wherebymore » selections made in one plot are propagated to the other plots. Users can also export selected data or reconfigure the visualization panel to explore relationships between columns and rows in the data.« less

  7. An Updated Decision Support Interface: A Tool for Remote Monitoring of Crop Growing Conditions

    NASA Astrophysics Data System (ADS)

    Husak, G. J.; Budde, M. E.; Rowland, J.; Verdin, J. P.; Funk, C. C.; Landsfeld, M. F.

    2014-12-01

    Remote sensing of agroclimatological variables to monitor food production conditions is a critical component of the Famine Early Warning Systems Network portfolio of tools for assessing food security in the developing world. The Decision Support Interface (DSI) seeks to integrate a number of remotely sensed and modeled variables to create a single, simplified portal for analysis of crop growing conditions. The DSI has been reformulated to incorporate more variables and give the user more freedom in exploring the available data. This refinement seeks to transition the DSI from a "first glance" agroclimatic indicator to one better suited for the differentiation of drought events. The DSI performs analysis of variables over primary agricultural zones at the first sub-national administrative level. It uses the spatially averaged rainfall, normalized difference vegetation index (NDVI), water requirement satisfaction index (WRSI), and actual evapotranspiration (ETa) to identify potential hazards to food security. Presenting this information in a web-based client gives food security analysts and decision makers a lightweight portal for information on crop growing conditions in the region. The crop zones used for the aggregation contain timing information which is critical to the DSI presentation. Rainfall and ETa are accumulated from different points in the crop phenology to identify season-long deficits in rainfall or transpiration that adversely affect the crop-growing conditions. Furthermore, the NDVI and WRSI serve as their own seasonal accumulated measures of growing conditions by capturing vegetation vigor or actual evapotranspiration deficits. The DSI is currently active for major growing regions of sub-Saharan Africa, with intention of expanding to other areas over the coming years.

  8. A methodology for hard/soft information fusion in the condition monitoring of aircraft

    NASA Astrophysics Data System (ADS)

    Bernardo, Joseph T.

    2013-05-01

    Condition-based maintenance (CBM) refers to the philosophy of performing maintenance when the need arises, based upon indicators of deterioration in the condition of the machinery. Traditionally, CBM involves equipping machinery with electronic sensors that continuously monitor components and collect data for analysis. The addition of the multisensory capability of human cognitive functions (i.e., sensemaking, problem detection, planning, adaptation, coordination, naturalistic decision making) to traditional CBM may create a fuller picture of machinery condition. Cognitive systems engineering techniques provide an opportunity to utilize a dynamic resource—people acting as soft sensors. The literature is extensive on techniques to fuse data from electronic sensors, but little work exists on fusing data from humans with that from electronic sensors (i.e., hard/soft fusion). The purpose of my research is to explore, observe, investigate, analyze, and evaluate the fusion of pilot and maintainer knowledge, experiences, and sensory perceptions with digital maintenance resources. Hard/soft information fusion has the potential to increase problem detection capability, improve flight safety, and increase mission readiness. This proposed project consists the creation of a methodology that is based upon the Living Laboratories framework, a research methodology that is built upon cognitive engineering principles1. This study performs a critical assessment of concept, which will support development of activities to demonstrate hard/soft information fusion in operationally relevant scenarios of aircraft maintenance. It consists of fieldwork, knowledge elicitation to inform a simulation and a prototype.

  9. Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines.

    PubMed

    Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

    2016-01-01

    In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved. PMID:27136561

  10. Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines

    PubMed Central

    Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

    2016-01-01

    In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved. PMID:27136561

  11. Nonlinear model for condition monitoring of non-stationary vibration signals in ship driveline application

    NASA Astrophysics Data System (ADS)

    Cardona-Morales, O.; Avendaño, L. D.; Castellanos-Domínguez, G.

    2014-02-01

    Condition monitoring of mechanical systems is an important topic for industry since it improves machine maintenance and reduce the total associated operational cost. In this sense, vibration analysis is a useful tool for failure prevention in rotating machines, and its main challenge is to perform on-line estimation of dynamic behavior, due to non-stationary operating conditions. To this, estimation of both, amplitude and instantaneous frequency, holding most of process information should be carried out. Nevertheless, approaches for estimating those parameters require to have the shaft speed reference signal, which is not always provided in several industrial applications. In this paper, a novel Order Tracking (OT) scheme of estimation is proposed that is based on the state space model that avoids the shaft speed reference signal. The nonlinear oscillatory model designed as frequency tracker is adapted for estimating the phase and the amplitude of each particular harmonic component. Specifically, nonlinear filtering (namely, the Square-Root Cubature Kalman Filter) is used to estimate the spectral components from the vibration signal. The proposed approach is tested and compared with baseline Vold-Kalman Filtering over four different datasets. The obtained results show that proposed approach is robust and it performs with high accuracy estimation of the order component and the instantaneous frequency under different operating conditions; both allow capturing machine dynamic behavior.

  12. System accuracy of blood glucose monitoring systems: impact of use by patients and ambient conditions.

    PubMed

    Schmid, Christina; Haug, Cornelia; Heinemann, Lutz; Freckmann, Guido

    2013-10-01

    For self-monitoring of blood glucose by people with diabetes, the reliability of the measured blood glucose values is a prerequisite in order to ensure correct therapeutic decisions. Requirements for system accuracy are defined by the International Organization for Standardization (ISO) in the standard EN ISO 15197:2003. However, even a system with high analytical quality is not a guarantee for accurate and reliable measurement results. Under routine life conditions, blood glucose measurement results are affected by several factors. First, the act of performing measurements as well as the handling of the system may entail numerous possible error sources, such as traces of glucose-containing products on the fingertips, the use of deteriorated test strips, or the incorrect storage of test strips. Second, ambient and sampling conditions such as high altitude, partial pressure of oxygen, ambient temperature, and the use of alternate test sites can have an influence on measurement results. Therefore, the user-friendliness of a system and the quality of the manufacturer's labeling to reduce the risk of handling errors are also important aspects in ensuring reliable and accurate measurement results. In addition, the analytical performance of systems should be less prone to user errors and ambient conditions. Finally, people with diabetes must be aware of the information and instructions in the manufacturer's labeling and must be able to measure and interpret blood glucose results correctly. PMID:23883407

  13. Rapid evaluation of mechanical boundary conditions using impedance based structural health monitoring

    NASA Astrophysics Data System (ADS)

    Kettle, Ryan A.; Anton, Steven R.

    2016-04-01

    Conventionally, structural health monitoring (SHM) has been primarily concerned with sensing, identifying, locating, and determining the severity of damage present in a structure that is in a static state. Instead, this study will investigate adapting the impedance SHM method to rapidly evaluate a mechanical system during a dynamic event. Also in contrast to conventional SHM, the objective is not to detect damage but instead to detect changes in the boundary conditions as they occur during a dynamic event. Rapid detection of changes in boundary conditions in highly dynamic environments has the potential to be used in a wide variety of applications, including the aerospace, civil, and mining industries. A key feature of this work will be the use of frequency ranges higher than what is typically used for SHM impedance measurements, in the range of several MHz. Using such high frequencies will allow for faster measurements of impedance, thus enabling the capture of variations in boundary conditions as they change during a dynamic event. An existing analytical model from the literature for electromechanical impedance based SHM will be utilized for this study.

  14. Estimation of critical conditions of polymers based on monitoring the polymer recovery.

    PubMed

    Bhati, S S; Macko, T; Brüll, R

    2016-06-17

    Liquid chromatography at critical conditions (LCCC) is a very attractive chromatographic technique on the border between the size exclusion and liquid adsorption mode of the liquid chromatography. The strong interest in LCCC arises from the fact that it is well suited to analyze the block lengths in segmented copolymers or the heterogeneities with regard to end groups present, for example, in functionalized polymers e.g., telechelics. In this paper a new method for identification of the critical conditions of synthetic polymers is proposed, which requires only one polymer sample with higher molar mass. The method is based on monitoring the recovery of the polymer sample from a column. The composition of the mobile phase is modified until the polymer sample is fully recovered from the column. The corresponding composition of the mobile phase is composition corresponding to LCCC. This new method was applied for the determination of critical conditions for polyethylene, syndiotactic polypropylene and isotactic polypropylene. The results of the new method will be compared to those of classical approaches and advantages will be pointed out. PMID:27208990

  15. Numerical simulation and experimental study of a two-stage reciprocating compressor for condition monitoring

    NASA Astrophysics Data System (ADS)

    Elhaj, M.; Gu, F.; Ball, A. D.; Albarbar, A.; Al-Qattan, M.; Naid, A.

    2008-02-01

    A numerical simulation of a two-stage reciprocating compressor has replicated the operations of the compressor under various conditions for the development of diagnostic features for predictive condition monitoring. The simulation involves the development of a mathematical model of five different physical processes: speed-torque characteristics of an induction motor, cylinder pressure variation, crankshaft rotational motion, flow characteristics through valves and vibration of the valve plates. Modelling both valve leakage and valve spring deterioration has also been achieved. The simulation was implemented in a MATLAB environment for an efficient numerical solution and ease of result presentation. For normal operating conditions, the simulated results are in good agreement with the test results for cylinder pressure waveforms and crankshaft instantaneous angular speed (IAS). It has been found that both the IAS fluctuation and pressure waveform are sensitive detection features for compressor faults such as valve leakage and valve spring deterioration. However, IAS is preferred because of its non-intrusive measurement nature. Further studies using the model and experiments are being undertaken in order to develop fault detection features for compressor driving motors and transmission systems.

  16. Use of fuzzy inference system for condition monitoring of induction motor

    NASA Astrophysics Data System (ADS)

    Janier, Josefina B.; Zaim Zaharia, M. F.; Karim, Samsul Ariffin Abd.

    2012-09-01

    Three phase induction motors are commonly used in industry due to its robustness, simplicity of its construction and high reliability. The tasks performed by these motors grow increasingly complex because of modern industries hence there is a need to determine the faults. Early detection of faults will reduce an unscheduled machine downtime that can upset production deadlines and may cause heavy financial losses. This paper is focused in developing a computer based system using Fuzzy Inference system's membership function. An unusual increase in vibration of the motor could be an indicator of faulty condition hence the vibration of the motor of an induction motor was used as an input, whereas the output is the motor condition. An inference system of the Fuzzy Logic was created to classify the vibration characteristics of the motor which is called vibration analysis. The system classified the motor of the gas distribution pump condition as from 'acceptable' to 'monitor closely'. The early detection of unusual increase in vibration of the induction motor is an important part of a predictive maintenance for motor driven machinery.

  17. Vibration-based machine condition monitoring with attention to the use of time-frequency methods

    NASA Astrophysics Data System (ADS)

    Rehorn, Adam G. J.; Orban, Peter E.; Jiang, Jin

    2004-03-01

    To enable lightly staffed or fully autonomous machining operations, it is essential that both the condition of the cutter and the health of the machine tool system be known. In this paper, the health of the spindle positioning drive (Z axis) on a Proteo D/94 precision machining center is investigated using time, frequency and time-frequency techniques. Investigated is a cogging phenomenon produced as a result of the DC servomotor brushes sticking due to poor design. This incipient fault reduces the accuracy and controllability of the machine tool, and always leads to total drive failure. Thus, it is important to determine the fault signature of the drive so that corrective action may be taken before failure can occur, permanently damaging both the motor and the workpiece. The vibratory signatures of both a healthy and a faulty spindle during translation are analyzed. It is shown that a spindle under fault conditions behaves differently from a healthy one, and that time and time-frequency domain methods provide useful information on the status of the system. This paper lays the groundwork for the development of a future machine condition monitoring system, which can be easily retrofitted to any machine tool system.

  18. A distributed on-line HV transmission condition monitoring information system

    SciTech Connect

    Chan, W.L.; Pang, S.L.; Chan, T.M.; So, A.T.P.

    1997-04-01

    China Light and Power Company Ltd. (CLP) is responsible for supplying electricity to the whole of Hong Kong except Hong Kong Island and Lamma Island. In CLP`s Castle Peak power plant, 19 kV and 23 kV electric supplies are generated. The voltage is then stepped up to 400 kV for transmission. The intermediate control between those transformers and the major 400 kV overhead transmission system lies with a standard One and a half Breaker Configuration switch substations. The substation houses single phase encapsulated SF{sub 6} circuit breakers. In the urban centers, 400 kV substations are installed to step down 400 kV to 132 kV or further to 11 kV for distribution. This paper describes the development of a on-line distributed information system for monitoring the conditions of the whole HV transmission system. The system continuously monitors status of each circuit breaker (CB) together with important operational parameters, such as duration during making and breaking, operations of hydraulic pumps and SF{sub 6} gas pressure etc. Each group of CBs is monitored by a standalone microcontroller using a local area network with a baud rate of 9,600. The information can be recorded on the harddisk of an on-site microcomputer and further transmitted back to a remote computer for alarm generation and multi-station supervision. The CLP 400 kV substation and the Tsz Wan Shan 400 kV substation are among the first targets for development.

  19. Structural Health Monitoring of Composite Plates Under Ambient and Cryogenic Conditions

    NASA Technical Reports Server (NTRS)

    Engberg, Robert C.

    2005-01-01

    Methods for structural health monitoring are now being assessed, especially in high-performance, extreme environment, safety-critical applications. One such application is for composite cryogenic fuel tanks. The work presented here attempts to characterize and investigate the feasibility of using imbedded piezoelectric sensors to detect cracks and delaminations under cryogenic and ambient conditions. Different types of excitation and response signals and different sensors are employed in composite plate samples to aid in determining an optimal algorithm, sensor placement strategy, and type of imbedded sensor to use. Variations of frequency and high frequency chirps of the sensors are employed and compared. Statistical and analytic techniques are then used to determine which method is most desirable for a specific type of damage and operating environment. These results are furthermore compared with previous work using externally mounted sensors. More work is needed to accurately account for changes in temperature seen in these environments and be statistically significant. Sensor development and placement strategy are other areas of further work to make structural health monitoring more robust. Results from this and other work might then be incorporated into a larger composite structure to validate and assess its structural health. This could prove to be important in the development and qualification of any 2nd generation reusable launch vehicle using composites as a structural element.

  20. Acoustic emission-based condition monitoring methods: Review and application for low speed slew bearing

    NASA Astrophysics Data System (ADS)

    Caesarendra, Wahyu; Kosasih, Buyung; Tieu, Anh Kiet; Zhu, Hongtao; Moodie, Craig A. S.; Zhu, Qiang

    2016-05-01

    This paper presents an acoustic emission-based method for the condition monitoring of low speed reversible slew bearings. Several acoustic emission (AE) hit parameters as the monitoring parameters for the detection of impending failure of slew bearings are reviewed first. The review focuses on: (1) the application of AE in typical rolling element bearings running at different speed classifications, i.e. high speed (>600 rpm), low speed (10-600 rpm) and very low speed (<10 rpm); (2) the commonly used AE hit parameters in rolling element bearings and (3) AE signal processing, feature extraction and pattern recognition methods. In the experiment, impending failure of the slew bearing was detected by the AE hit parameters after the new bearing had run continuously for approximately 15 months. The slew bearing was then dismantled and the evidence of the early defect was analysed. Based on the result, we propose a feature extraction method of the AE waveform signal using the largest Lyapunov exponent (LLE) algorithm and demonstrate that the LLE feature can detect the sign of failure earlier than the AE hit parameters with improved prediction of the progressive trend of the defect.

  1. Monitoring Technical Conditions of Engineering Structures Using the Non-Linear Approach

    NASA Astrophysics Data System (ADS)

    Volkova, V. E.

    2015-11-01

    Conventional methods of monitoring technical condition are based on detection of damage in the structures of buildings or facilities during the entire period of their operation. In spite of considerable interest displayed to this issue and a significant number of publications, there is no unity of opinions. These methods differ from each other in the sets of values fixed for investigations, the techniques of their recording, transfer and further processing. Today's rules and regulations for structural designs expand the scope of application of the structures operating in the elastic-plastic stage. These damage-free structures originally display the nonlinear properties and can be adequately described only by the non-linear models. This paper presents a method for determining the type and level of non-linearity from the structural oscillations data for monitoring the change in the health of structures. It is shown that a plot of acceleration against the magnitude of the displacement represents the restoring force of a structure. If the structure is damaged during a new striking motion, the phase trajectories in plane “acceleration-displacement” will deviate from its healthy signature.

  2. Using Fuzzy Linguistics to Select Optimum Maintenance and Condition Monitoring Strategies

    NASA Astrophysics Data System (ADS)

    Mechefske, Chris K.; Wang, Zheng

    2003-03-01

    Continued pressure on companies to reduce costs and improve customer satisfaction has resulted in increasingly detailed examinations of maintenance practices and strategies. The justification of any given maintenance strategy or practice within an organisation must consider multiple criteria. It should also be based on the overall objectives of the organisation, many of which are 'intangible' or 'non-monetary'. A fuzzy linguistic approach to achieve the inclusion of somewhat subjective assessments of maintenance strategies and practices in an objective manner is outlined in this paper. This approach is also demonstrated with two examples. Implementation of this approach will assist decision makers in the evaluation and selection of maintenance strategies and particular condition-monitoring techniques.

  3. Using Fuzzy Linguistics to Select Optimum Maintenance and Condition Monitoring Strategies

    NASA Astrophysics Data System (ADS)

    Mechefske, Chris K.; Wang, Zheng

    2001-11-01

    Continued pressure on companies to reduce costs and improve customer satisfaction has resulted in increasingly detailed examinations of maintenance practices and strategies. The justification of any given maintenance strategy or practice within an organisation must consider multiple criteria. It should also be based on the overall objectives of the organisation, many of which are 'intangible' or 'non-monetary'. A fuzzy linguistic approach to achieve the inclusion of somewhat subjective assessments of maintenance strategies and practices in an objective manner is outlined in this paper. This approach is also demonstrated with two examples. Implementation of this approach will assist decision makers in the evaluation and selection of maintenance strategies and particular condition-monitoring techniques.

  4. Long-term monitoring of the Sedlec Ossuary - Analysis of hygrothermal conditions

    NASA Astrophysics Data System (ADS)

    Pavlík, Zbyšek; Balík, Lukáš; Maděra, Jiří; Černý, Robert

    2016-07-01

    The Sedlec Ossuary is one of the twelve UNESCO World Heritage Sites in the Czech Republic. Although the ossuary is listed among the most visited Czech tourist attractions, its technical state is almost critical and a radical renovation is necessary. On this account, hygrothermal performance of the ossuary is experimentally researched in the presented paper in order to get information on moisture sources and to get necessary data for optimized design of renovation treatments and reconstruction solutions that will allow preserve the historical significance of this attractive heritage site. Within the performed experimental analysis, the interior and exterior climatic conditions are monitored over an almost three year period together with relative humidity and temperature profiles measured in the most damage parts of the ossuary chapel. On the basis of measured data, the long-term hygrothermal state of the ossuary building is accessed and the periods of possible surface condensation are identified.

  5. Diamond pad detector telescope for beam conditions and luminosity monitoring in ATLAS

    NASA Astrophysics Data System (ADS)

    Mikuž, M.; Cindro, V.; Dolenc, I.; Frais-Kölbl, H.; Gorišek, A.; Griesmayer, E.; Kagan, H.; Kramberger, G.; Mandić, I.; Niegl, M.; Pernegger, H.; Trischuk, W.; Weilhammer, P.; Zavrtanik, M.

    2007-09-01

    Beam conditions and the potential detector damage resulting from their anomalies have pushed the LHC experiments to plan their own monitoring devices in addition to those provided by the machine. ATLAS decided to build a telescope composed of two stations with four diamond pad detector modules each, placed symmetrically around the interaction point at z=±183.8cm and r˜55mm (η˜4.2). Equipped with fast electronics it allows time-of-flight separation of events resulting from beam anomalies from normally occurring p p interactions. In addition it will provide a coarse measurement of the LHC luminosity in ATLAS. Ten detector modules have been assembled and subjected to tests, from characterization of bare diamonds to source and beam tests. Preliminary results of beam test in the CERN PS indicate a signal-to-noise ratio of 14±2.

  6. Monitoring temperature conditions in recently drilled nonproductive industry boreholes in Oklahoma

    SciTech Connect

    Harrison, W.E.; Luza, K.V.

    1985-06-01

    Temperature conditions were monitored in seven industry petroleum-test wells (called holes-of-opportunity in this report) that were drilled in central and eastern Oklahoma. Five of these wells provided useful temperature information, and two wells were used to determine the length of time needed for the borehole-fluid temperature to achieve thermal equilibrium with the formation rocks. Four wells were used to verify the validity of a geothermal-gradient map of Oklahoma. Temperature surveys in two wells indicated a gradient lower than the predicted gradients on the geothermal-gradient map. When deep temperature data, between 5000 and 13,000 feet, are adjusted for mud-circulation effects, the adjusted gradients approximate the gradients on the geothermal-gradient map. The temperature-confirmation program appears to substantiate the geographic distribution of the high- and low-thermal-gradient regimes in Oklahoma. 13 refs., 18 figs., 7 tabs.

  7. Performance in real condition of photonic crystal sensor based NO2 gas monitoring system

    NASA Astrophysics Data System (ADS)

    Rahmat, M.; Maulina, W.; Rustami, E.; Azis, M.; Budiarti, D. R.; Seminar, K. B.; Yuwono, A. S.; Alatas, H.

    2013-11-01

    In this report we discuss the performance in real condition of an optical based real-time NO2 gas monitoring system. For detecting the gas concentration in the ambient air we have developed an optical sensor based on one-dimensional photonic crystal with two defects that allows the existence of photonic pass band inside the associated photonic band gap. To measure the gas concentration, we dissolve the corresponding NO2 gas into a specific Griess Saltzman reagent solution. The change of gas concentration in the related dissolved-solution can be inspected by the photonic pass band peak variation. It is observed that the wavelength of the photonic pass band peak of the fabricated photonic crystal is nearly coincide with the wavelength of the associated solution highest absorbance. The laboratory test shows that the device works properly, whereas the field measurement test demonstrates accurate results with validation error of 1.56%.

  8. High-sensitivity chemical derivatization NMR analysis for condition monitoring of aged elastomers.

    SciTech Connect

    Assink, Roger Alan; Celina, Mathias Christopher; Skutnik, Julie Michelle

    2004-06-01

    An aged polybutadiene-based elastomer was reacted with trifluoroacetic anhydride (TFAA) and subsequently analyzed via 19F NMR spectroscopy. Derivatization between the TFAA and hydroxyl functionalities produced during thermo-oxidative aging was achieved, resulting in the formation of trifluoroester groups on the polymer. Primary and secondary alcohols were confirmed to be the main oxidation products of this material, and the total percent oxidation correlated with data obtained from oxidation rate measurements. The chemical derivatization appears to be highly sensitive and can be used to establish the presence and identity of oxidation products in aged polymeric materials. This methodology represents a novel condition monitoring approach for the detection of chemical changes that are otherwise difficult to analyze.

  9. Laser surface inspections: fundamentals and applications to monitor inner surface conditions of nuclear fusion reactor chambers

    NASA Astrophysics Data System (ADS)

    Kasuya, Koichi; Ozawa, S.; Norimatsu, T.; Azechi, H.; Mima, K.; Nakai, S.; Suzuki, S.; Budner, B.; Mroz, W.; Kasuya, N.; Kasuya, W.; Kasuya, Kei.; Izawa, Y.; Furukawa, H.; Shimada, Y.; Yamanaka, T.; Nakai, M.; Nagai, K.; Yokoyama, K.; Ezato, K.; Enoeda, M.; Akiba, M.; Prokopiuk, A.

    2010-09-01

    The most recent fundamental research results to investigate surface erosions of nuclear fusion candidate chamber materials are described in short. We used a commercial surface profiler with a red semiconductor laser. Various material surfaces ablated and eroded by a rather short pulse electron beam and a short pulse ArF laser light were measured with this surface profiler and the associated three-dimensional analysis software. Threshold input levels for various sample surface erosions with electron and laser beams were clearly decided for the first time with our new method in this article. After the above fundamental results were gathered, the methods to inspect inner surface conditions of nuclear fusion reactor chambers were newly proposed with various kinds of laser displacement sensors. The first one is the erosion monitor with the above profiler, and the second one is the laser induced ultrasonic wave detection method to inspect deeper surface layers than the first one.

  10. Monitoring Sea Ice Conditions and Use in Arctic Alaska to Enhance Community Adaptation to Change

    NASA Astrophysics Data System (ADS)

    Druckenmiller, M. L.; Eicken, H.

    2010-12-01

    Sea ice changes in the coastal zone, while less conspicuous in relation to the dramatic thinning and retreat of perennial Arctic sea ice, can be more readily linked to local impacts. Shorefast ice is a unique area for interdisciplinary research aimed at improving community adaptation to climate through local-scale environmental observations. Here, geophysical monitoring, local Iñupiat knowledge, and the documented use of ice by the Native hunting community of Barrow, Alaska are combined to relate coastal ice processes and morphologies in the Chukchi Sea to ice stability and community adaption strategies for travel, hunting, and risk assessment. A multi-year effort to map and survey the community’s seasonal ice trails, alongside a detailed record of shorefast ice conditions, provides insight into how hunters evaluate the evolution of ice throughout winter and spring. Various data sets are integrated to relate the annual accretion history of the local ice cover to both measurements of ice thickness and topography and hunter observations of ice types and hazards. By relating changes in the timing of shorefast ice stabilization, offshore ice conditions, and winter wind patterns to ice characteristics in locations where spring bowhead whaling occurs, we are working toward an integrated scientific product compatible with the perspective of local ice experts. A baseline for assessing future change and community climate-related vulnerabilities may not be characterized by single variables, such as ice thickness, but rather by how changes in observable variables manifest in impacts to human activities. This research matches geophysical data to ice-use to establish such a baseline. Documenting human-environment interactions will allow future monitoring to illustrate how strategies for continued community ice-use are indicative of or responsive to change, and potentially capable of incorporating science products as additional sources of useable information.

  11. Application of the JDL data fusion process model to hard/soft information fusion in the condition monitoring of aircraft

    NASA Astrophysics Data System (ADS)

    Bernardo, Joseph T.

    2014-05-01

    Hard/soft information fusion has been proposed as a way to enhance diagnostic capability for the condition monitoring of machinery. However, there is a limited understanding of where hard/soft information fusion could and should be applied in the condition monitoring of aircraft. Condition-based maintenance refers to the philosophy of performing maintenance when the need arises, based upon indicators of deterioration in the condition of the machinery. The addition of the multisensory capability of human cognition to electronic sensors may create a fuller picture of machinery condition. Since 1988, the Joint Directors of Laboratories (JDL) data fusion process model has served as a framework for information fusion research. Advances are described in the application of hard/soft information fusion in condition monitoring using terms that condition-based maintenance professionals in aviation will recognize. Emerging literature on hard/soft information fusion in condition monitoring is organized into the levels of the JDL data fusion process model. Gaps in the literature are identified, and the author's ongoing research is discussed. Future efforts will focus on building domain-specific frameworks and experimental design, which may provide a foundation for improving flight safety, increasing mission readiness, and reducing the cost of maintenance operations.

  12. Multivariate respiratory motion prediction

    NASA Astrophysics Data System (ADS)

    Dürichen, R.; Wissel, T.; Ernst, F.; Schlaefer, A.; Schweikard, A.

    2014-10-01

    In extracranial robotic radiotherapy, tumour motion is compensated by tracking external and internal surrogates. To compensate system specific time delays, time series prediction of the external optical surrogates is used. We investigate whether the prediction accuracy can be increased by expanding the current clinical setup by an accelerometer, a strain belt and a flow sensor. Four previously published prediction algorithms are adapted to multivariate inputs—normalized least mean squares (nLMS), wavelet-based least mean squares (wLMS), support vector regression (SVR) and relevance vector machines (RVM)—and evaluated for three different prediction horizons. The measurement involves 18 subjects and consists of two phases, focusing on long term trends (M1) and breathing artefacts (M2). To select the most relevant and least redundant sensors, a sequential forward selection (SFS) method is proposed. Using a multivariate setting, the results show that the clinically used nLMS algorithm is susceptible to large outliers. In the case of irregular breathing (M2), the mean root mean square error (RMSE) of a univariate nLMS algorithm is 0.66 mm and can be decreased to 0.46 mm by a multivariate RVM model (best algorithm on average). To investigate the full potential of this approach, the optimal sensor combination was also estimated on the complete test set. The results indicate that a further decrease in RMSE is possible for RVM (to 0.42 mm). This motivates further research about sensor selection methods. Besides the optical surrogates, the sensors most frequently selected by the algorithms are the accelerometer and the strain belt. These sensors could be easily integrated in the current clinical setup and would allow a more precise motion compensation.

  13. Introduction to multivariate discrimination

    NASA Astrophysics Data System (ADS)

    Kégl, Balázs

    2013-07-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  14. Multivariate volume rendering

    SciTech Connect

    Crawfis, R.A.

    1996-03-01

    This paper presents a new technique for representing multivalued data sets defined on an integer lattice. It extends the state-of-the-art in volume rendering to include nonhomogeneous volume representations. That is, volume rendering of materials with very fine detail (e.g. translucent granite) within a voxel. Multivariate volume rendering is achieved by introducing controlled amounts of noise within the volume representation. Varying the local amount of noise within the volume is used to represent a separate scalar variable. The technique can also be used in image synthesis to create more realistic clouds and fog.

  15. Chemiluminescence as a condition monitoring method for thermal aging and lifetime prediction of an HTPB elastomer.

    SciTech Connect

    Gillen, Kenneth Todd; Minier, Leanna M. G.; Celina, Mathias Christopher; Trujillo, Ana B.

    2007-03-01

    Chemiluminescence (CL) has been applied as a condition monitoring technique to assess aging related changes in a hydroxyl-terminated-polybutadiene based polyurethane elastomer. Initial thermal aging of this polymer was conducted between 110 and 50 C. Two CL methods were applied to examine the degradative changes that had occurred in these aged samples: isothermal 'wear-out' experiments under oxygen yielding initial CL intensity and 'wear-out' time data, and temperature ramp experiments under inert conditions as a measure of previously accumulated hydroperoxides or other reactive species. The sensitivities of these CL features to prior aging exposure of the polymer were evaluated on the basis of qualifying this method as a quick screening technique for quantification of degradation levels. Both the techniques yielded data representing the aging trends in this material via correlation with mechanical property changes. Initial CL rates from the isothermal experiments are the most sensitive and suitable approach for documenting material changes during the early part of thermal aging.

  16. Operational control of radiation conditions in Space Monitoring Data Center of Moscow State University

    NASA Astrophysics Data System (ADS)

    Kalegaev, Vladimir; Shugay, Yulia; Bobrovnikov, Sergey; Kuznetsov, Nikolay; Barinova, Vera; Myagkova, Irina; Panasyuk, Mikhail

    2016-07-01

    Space Monitoring Data Center (SMDC) of Moscow State University provides mission support for Russian satellites and give operational analysis of radiation conditions in space. SMDC Web-sites (http://smdc.sinp.msu.ru/ and http://swx.sinp.msu.ru/) give access to current data on the level of solar activity, geomagnetic and radiation state of Earth's magnetosphere and heliosphere in near-real time. For data analysis the models of space environment factors working online have been implemented. Interactive services allow one to retrieve and analyze data at a given time moment. Forecasting applications including solar wind parameters, geomagnetic and radiation condition forecasts have been developed. Radiation dose and SEE rate control are of particular importance in practical satellite operation. Satellites are always under the influence of high-energy particle fluxes during their orbital flight. The three main sources of particle fluxes: the Earth's radiation belts, the galactic cosmic rays, and the solar energetic particles (SEP), are taken into account by SMDC operational services to estimate the radiation dose caused by high-energy particles to a satellite at LEO orbits. ISO 15039 and AP8/AE8 physical models are used to estimate effects of galactic cosmic rays and radiation belt particle fluxes. Data of geosynchronous satellites (GOES or Electro-L1) allow to reconstruct the SEP fluxes spectra at a given low Earth orbit taking into account the geomagnetic cut-off depending on geomagnetic activity level.

  17. Operation reliability assessment for cutting tools by applying a proportional covariate model to condition monitoring information.

    PubMed

    Cai, Gaigai; Chen, Xuefeng; Li, Bing; Chen, Baojia; He, Zhengjia

    2012-01-01

    The reliability of cutting tools is critical to machining precision and production efficiency. The conventional statistic-based reliability assessment method aims at providing a general and overall estimation of reliability for a large population of identical units under given and fixed conditions. However, it has limited effectiveness in depicting the operational characteristics of a cutting tool. To overcome this limitation, this paper proposes an approach to assess the operation reliability of cutting tools. A proportional covariate model is introduced to construct the relationship between operation reliability and condition monitoring information. The wavelet packet transform and an improved distance evaluation technique are used to extract sensitive features from vibration signals, and a covariate function is constructed based on the proportional covariate model. Ultimately, the failure rate function of the cutting tool being assessed is calculated using the baseline covariate function obtained from a small sample of historical data. Experimental results and a comparative study show that the proposed method is effective for assessing the operation reliability of cutting tools. PMID:23201980

  18. Operation Reliability Assessment for Cutting Tools by Applying a Proportional Covariate Model to Condition Monitoring Information

    PubMed Central

    Cai, Gaigai; Chen, Xuefeng; Li, Bing; Chen, Baojia; He, Zhengjia

    2012-01-01

    The reliability of cutting tools is critical to machining precision and production efficiency. The conventional statistic-based reliability assessment method aims at providing a general and overall estimation of reliability for a large population of identical units under given and fixed conditions. However, it has limited effectiveness in depicting the operational characteristics of a cutting tool. To overcome this limitation, this paper proposes an approach to assess the operation reliability of cutting tools. A proportional covariate model is introduced to construct the relationship between operation reliability and condition monitoring information. The wavelet packet transform and an improved distance evaluation technique are used to extract sensitive features from vibration signals, and a covariate function is constructed based on the proportional covariate model. Ultimately, the failure rate function of the cutting tool being assessed is calculated using the baseline covariate function obtained from a small sample of historical data. Experimental results and a comparative study show that the proposed method is effective for assessing the operation reliability of cutting tools. PMID:23201980

  19. Measurement capability of field portable organic vapor monitoring instruments under different experimental conditions.

    PubMed

    Coffey, Christopher C; Pearce, Terri A; Lawrence, Robert B; Hudnall, Judith B; Slaven, James E; Martin, Stephen B

    2009-01-01

    The performance of field portable direct-reading organic vapor monitors (DROVMs) was evaluated under a variety of experimental conditions. Four of the DROVMs had photoionization detectors (ppbRAE, IAQRAE, MultiRAE, and Century Toxic Vapor Analyzer), one had a flame ionization detector (Century Toxic Vapor Analyzer), and one was a single-beam infrared spectrophotometer (SapphIRe). Four of each DROVM (two Century Toxic Vapor Analyzers and SapphIRes) were tested. The DROVMs were evaluated at three temperatures (4 degrees C, 21 degrees C, and 38 degrees C), three relative humidities (30%, 60%, and 90%), and two hexane concentrations (5 ppm and 100 ppm). These conditions were selected to provide a range within the operational parameters of all the instruments. At least four replicate trials were performed across the 18 experimental conditions (3 temperatures x 3 relative humidities x 2 concentrations). To evaluate performance, the 4-hr time-weighted average readings from the DROVMs in a given trial were compared with the average of two charcoal tube concentrations using pairwise comparison. The pairwise comparison criterion was +/-25% measurement agreement between each individual DROVM and the DROVMs as a group and the average charcoal tube concentration. The ppbRAE group performed the best with 40% of all readings meeting the comparison criterion followed by the SapphIRe group at 39%. Among individual DROVMs, the best performer was a SapphIRe, with 57% of its readings meeting the criterion. The data was further analyzed by temperature, humidity, and concentration. The results indicated the performance of some DROVMs may be affected by temperature, humidity, and/or concentration. The ppbRAE group performed best at 21 degrees C with the percentage of readings meeting the criterion increasing to 63%. At the 5 ppm concentration, 44% of the ppbRAE group readings met the criterion, while at 100 ppm, only 35% did. The results indicate that monitors can be used as survey tools

  20. Final Technical Report Recovery Act: Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines

    SciTech Connect

    Wei Qiao

    2012-05-29

    The penetration of wind power has increased greatly over the last decade in the United States and across the world. The U.S. wind power industry installed 1,118 MW of new capacity in the first quarter of 2011 alone and entered the second quarter with another 5,600 MW under construction. By 2030, wind energy is expected to provide 20% of the U.S. electricity needs. As the number of wind turbines continues to grow, the need for effective condition monitoring and fault detection (CMFD) systems becomes increasingly important [3]. Online CMFD is an effective means of not only improving the reliability, capacity factor, and lifetime, but it also reduces the downtime, energy loss, and operation and maintenance (O&M) of wind turbines. The goal of this project is to develop novel online nonintrusive CMFD technologies for wind turbines. The proposed technologies use only the current measurements that have been used by the control and protection system of a wind turbine generator (WTG); no additional sensors or data acquisition devices are needed. Current signals are reliable and easily accessible from the ground without intruding on the wind turbine generators (WTGs) that are situated on high towers and installed in remote areas. Therefore, current-based CMFD techniques have great economic benefits and the potential to be adopted by the wind energy industry. Specifically, the following objectives and results have been achieved in this project: (1) Analyzed the effects of faults in a WTG on the generator currents of the WTG operating at variable rotating speed conditions from the perspective of amplitude and frequency modulations of the current measurements; (2) Developed effective amplitude and frequency demodulation methods for appropriate signal conditioning of the current measurements to improve the accuracy and reliability of wind turbine CMFD; (3) Developed a 1P-invariant power spectrum density (PSD) method for effective signature extraction of wind turbine faults with

  1. Evaluating GIS for establishing and monitoring environmental conditions of oil fields

    SciTech Connect

    Pfeil, R.W.; Ellis, J.W.

    1995-04-01

    Good management of an oil field and compliance with ever-increasing environmental regulations is enhanced by technologies that improve a company`s understanding of field/production facilities and environmental conditions that have occurred to both through time. In Nigeria, Kazakhstan, Indonesia, and offshore Cabinda, remote sensing, computer-aided drafting (CAD) and Global Positioning System (GPF) technologies have effectively been used by Chevron to provide accurate maps of facilities and to better understand environmental conditions. Together these proven technologies have provided a solid and cost-effective base for planning field operation, verifying well and seismic locations, and locating sampling sites. The end product of these technologies is often locations, and locating sampling sites. The end product of these technologies is often cartographic-quality hardcopy images and maps for use in the office and field. Chevron has been evaluating the capability of Geographical Information System (GIS) technology to integrate images, maps, and tabular data into a useful database that can help managers and workers better evaluate conditions in an oil field, plan new facilities, and monitor/predict trends (for example, of air emissions, groundwater, soil chemistry, subsidence, etc.). Remote sensing, CAD (if formatted properly), and GPS data can be integrated to establish the spatial or cartographic base of the GIS. A major obstacle to establishing a sophisticated GIS for an overseas operation is the initial cost of data collection and conversion from legacy data base management systems and hardcopy to appropriate digital format. However, Chevron routinely uses GIS for oil spill modeling and is now using GIS in the field for integrating GPS data with field observations and programs.

  2. Primer on multivariate calibration

    SciTech Connect

    Thomas, E.V. )

    1994-08-01

    In analytical chemistry, calibration is the procedure that relates instrumental measurements to an analyte of interest. Typically, instrumental measurements are obtained from specimens in which the amount (or level) of the analyte has been determined by some independent and inherently accurate assay (e.g., wet chemistry). Together, the instrumental measurements and results from the independent assays are used to construct a model that relates the analyte level to the instrumental measurements. The advent of high-speed digital computers has greatly increased data acquisition and analysis capabilities and has provided the analytical chemist with opportunities to use many measurements - perhaps hundreds - for calibrating an instrument (e.g., absorbances at multiple wave-lengths). To take advantage of this technology, however, new methods (i.e., multivariate calibration methods) were needed for analyzing and modeling the experimental data. The purpose of this report is to introduce several evolving multivariate calibration methods and to present some important issues regarding their use. 30 refs., 7 figs.

  3. Monitoring of suspended sediments, sediment conditions and aquatic biota during the functional check of bottom outlets

    NASA Astrophysics Data System (ADS)

    Haun, Stefan; Seitz, Lydia; Stockinger, Wolfram; Riedl, Martin; Schletterer, Martin

    2016-04-01

    Reservoirs are used to store water for multiple purposes and are therefore of great importance for our society. Regularly inspections of the dam structure and the bottom outlets are necessary to ensure a safe operation of these structures. The release of water from the reservoirs for this procedure often results in high suspended sediment concentrations downstream by the remobilization of deposited sediments, which may result further in negative effects on the downstream located habitats. Due to a careful elaborated monitoring concept, e.g. regarding the opening procedure of the bottom outlets, it is possible to change the management strategy and to avoid or to minimize ecological impacts. Within this study a monitoring concept is developed and implemented to observe occurring suspended sediment concentrations during the opening of the bottom outlets of a small reservoir in the alpine region. The measurement concept includes suspended sediment concentration and discharge measurements at the two upstream located tributaries as well as suspended sediment concentration measurements downstream. Two stations are selected downstream with a distance of 750 m and 2,000 m from the dam. To ensure a complete series of concentrations over time bottom samples, Imhoff-cones as well as turbidity meters are implemented. Whereas the turbidity meters ensure a permanent observation of the conditions (will be calibrated with laboratory results from the bottle samples), the Imhoff-cones make it possible to intervene right away into the process of releasing water. A second focus lies on the downstream located river bed, which is monitored before and after the opening of the bottom outlets in order to assess morphodynamical changes such as river bed clogging occurs. Therefore sediment samples with the so called freeze-panel technique are collected before and after the opening of the bottom outlets to quantify possible changes of the bed material. The results show that downstream habitats

  4. System identification for multivariable control

    NASA Astrophysics Data System (ADS)

    Vanzee, G. A.

    1981-05-01

    System identification methods and modern control theory are applied to industrial processes. These processes must often be controlled in order to meet certain requirements with respect to the product quality, safety, energy consumption, and environmental load. Modern control system design methods which take the occurring interaction phenomena and stochastic disturbances into account are used. An accurate dynamic mathematical model of the process, by theoretical modelling and/or by system identification is obtained. The computational aspects of two important types of identifications methods, i.e., stochastic realization and prediction error based parameter estimation are studied. The studied computational aspects are the robustness, the accuracy, and the computational costs of the methods. Theoretical analyses and applications to a multivariable pilot scale process, operating under closed loop conditions are investigated.

  5. Monitors.

    ERIC Educational Resources Information Center

    Powell, David

    1984-01-01

    Provides guidelines for selecting a monitor to suit specific applications, explains the process by which graphics images are produced on a CRT monitor, and describes four types of flat-panel displays being used in the newest lap-sized portable computers. A comparison chart provides prices and specifications for over 80 monitors. (MBR)

  6. Use of Landsat-Series Data in National Geographic Condition Monitoring in China

    NASA Astrophysics Data System (ADS)

    Bai, J.; Zhao, Y.; Sheng, L.; Li, Y.; Lv, G.

    2015-04-01

    To fully grasp the nature and human geography situation information, solve the problem of ecological environment, economic and social development of the country, monitoring the state of geographic condition by uniform index system has great significance. By collecting the existing standard documents, our paper established a suit of index system considering the characteristics of long time series remote sensing data. The index system includes basic, subject, composite statistical indexes, and statistical indexes based on basic geographic element. The spatial and temporal distribution of geographic condition with Landsat TM image in Haidian district of Beijing from 1983 to 2013 are studies. Results show that farmland decreases by 28.60%, build-up land increases by 38.95% in this period. The amount of land resources in different elevation/slope shows that, with the increase of elevation/slope, farmland and build-up land is gradually reduced, while grassland area is gradually increasing. In plains areas of elevation less than 50m and within the scope of the 0 to 3° slope, farmland and build-up land are the main land cover types, and both show the characteristic of tradeoffs. Urban area extended to the west and the north, meanwhile mass center of Haidian also moves to the northwest. The urban compactness decreases and the fractal index increased gradually, reflecting the city saturation degree become reduced, the city boundary becomes complicated gradually. The comprehensive land cover dynamic degree after the first decrease and then increases. Finally, based on the above statistic results, the spatial distribution of land cover in 2015 is predicted.

  7. Feature selection by merging sequential bidirectional search into relevance vector machine in condition monitoring

    NASA Astrophysics Data System (ADS)

    Zhang, Kui; Dong, Yu; Ball, Andrew

    2015-11-01

    For more accurate fault detection and diagnosis, there is an increasing trend to use a large number of sensors and to collect data at high frequency. This inevitably produces large-scale data and causes difficulties in fault classification. Actually, the classification methods are simply intractable when applied to high-dimensional condition monitoring data. In order to solve the problem, engineers have to resort to complicated feature extraction methods to reduce the dimensionality of data. However, the features transformed by the methods cannot be understood by the engineers due to a loss of the original engineering meaning. In this paper, other forms of dimensionality reduction technique(feature selection methods) are employed to identify machinery condition, based only on frequency spectrum data. Feature selection methods are usually divided into three main types: filter, wrapper and embedded methods. Most studies are mainly focused on the first two types, whilst the development and application of the embedded feature selection methods are very limited. This paper attempts to explore a novel embedded method. The method is formed by merging a sequential bidirectional search algorithm into scale parameters tuning within a kernel function in the relevance vector machine. To demonstrate the potential for applying the method to machinery fault diagnosis, the method is implemented to rolling bearing experimental data. The results obtained by using the method are consistent with the theoretical interpretation, proving that this algorithm has important engineering significance in revealing the correlation between the faults and relevant frequency features. The proposed method is a theoretical extension of relevance vector machine, and provides an effective solution to detect the fault-related frequency components with high efficiency.

  8. Multivariate Hypergeometric Similarity Measure

    PubMed Central

    Kaddi, Chanchala D.; Parry, R. Mitchell; Wang, May D.

    2016-01-01

    We propose a similarity measure based on the multivariate hypergeometric distribution for the pairwise comparison of images and data vectors. The formulation and performance of the proposed measure are compared with other similarity measures using synthetic data. A method of piecewise approximation is also implemented to facilitate application of the proposed measure to large samples. Example applications of the proposed similarity measure are presented using mass spectrometry imaging data and gene expression microarray data. Results from synthetic and biological data indicate that the proposed measure is capable of providing meaningful discrimination between samples, and that it can be a useful tool for identifying potentially related samples in large-scale biological data sets. PMID:24407308

  9. Monitoring Microbe-Induced Sulfide Precipitation Under Dynamic Flow Conditions Using Multiple Geophysical Techniques

    NASA Astrophysics Data System (ADS)

    Williams, K. H.; Hubbard, S.; Ntarlagiannis, D.; Banfield, J.

    2004-05-01

    A laboratory study was undertaken to investigate the feasibility of using minimally invasive geophysical techniques to monitor microbe-induced sulfide precipitation in saturated sand-packed columns under dynamic flow conditions. Specifically, the effect of zinc and iron sulfide precipitation on geophysical signatures was evaluated during stimulated sulfate-reduction by Desulfovibrio vulgaris. Four inoculated columns and one non-inoculated control were operated under a continuous upward flow velocity of 50cm/day with the following measurements made: multi-port fluid sampling, cross-column acoustic wave propagation, induced polarization, time domain reflectometry and saturated hydraulic conductivity. Over a period of seven weeks, the onset and progression of sulfate reduction within the columns was confirmed through decreasing substrate and aqueous metals concentrations, increased biomass, and visible regions of sulfide accumulation. Decreases in initial lactate and sulfate concentrations (2.8mM and 4.0mM, respectively) followed predicted stoichiometric relationships and soluble Zn(II) and Fe(II) concentrations (0.31mM and 0.36mM, respectively) were reduced to levels below detection through sequestration as insoluble sulfide phases. The areas where sulfide precipitation and accumulation occurred resulted in significant changes in two of the three geophysical measurements. High frequency (400-600kHz) acoustic wave amplitudes were reduced by nearly an order of magnitude over the course of the experiment with no significant accompanying change in wave velocity. Neither the wave amplitudes nor the velocities changed significantly in the downgradient portions of the column where microbial activity and sulfide precipitation were depressed due to depleted substrate and metals concentrations. The frequency content of the transmitted waves remained unchanged throughout the course of the experiment. Over the frequency range of the induced polarization measurements (0.1-1000Hz

  10. Use of fuzzy logic for condition monitoring of motor driven machineries

    NASA Astrophysics Data System (ADS)

    Janier, Josefina Barnachea; Zaim Zaharia, M. Fazrin

    2012-06-01

    An intelligent system called Fuzzy Logic is one of the current technologies that allow a description of the desired system behavior using common language. It generalizes the yes-no Boolean logic into numerical value of 1 and 0 but also permits the in between values. This paper presents the use of Fuzzy Logic to determine the unusual increase of vibrations of an induction motor called vibration analysis. Sudden increase of vibrations could be a good indicator of faulty condition of the motor. Based on the vibration characteristics of the motor, a Fuzzy Inference System (FIS) was created. The system classified the motor of the gas distribution pump as `acceptable' of the vibration ranges from 1.8mm/s to 4.5mm/s or `monitor closely' of the vibration ranges from 4.5mm/s to 7.1mm/s respectively. The system enabled an early detection of faults which is very important in maintenance management.

  11. Technology Solutions Case Study: Monitoring of Double Stud Wall Moisture Conditions in the Northeast, Devens, Massachusetts

    SciTech Connect

    2015-03-01

    Double stud walls have a higher risk of interior-sourced condensation moisture damage when compared with high-R approaches using exterior insulating sheathing. In this project, Building Science Corporation monitored moisture conditions in double-stud walls from 2011 through 2014 at a new production house located in Devens, Massachusetts. The builder, Transformations, Inc., has been using double-stud walls insulated with 12 in. of open cell polyurethane spray foam (ocSPF); however, the company has been considering a change to netted and blown cellulose insulation for cost reasons. Cellulose is a common choice for double-stud walls because of its lower cost (in most markets). However, cellulose is an air-permeable insulation, unlike spray foams, which increases interior moisture risks. The team compared three double-stud assemblies: 12 in. of ocSPF, 12 in. of cellulose, and 5-½ in. of ocSPF at the exterior of a double-stud wall (to approximate conventional 2 × 6 wall construction and insulation levels, acting as a control wall). These assemblies were repeated on the north and south orientations, for a total of six assemblies.

  12. Possibility of ozone depletion monitoring in conditions of opaque atmosphere using D-dosimeter

    NASA Astrophysics Data System (ADS)

    Terenetskaya, Irina P.

    2002-01-01

    Variations of solar ultraviolet (UV) radiation by clouds and aerosols that have a comparable effect on UVB (280-315 nm) caused by variations in stratospheric ozone hinder accurate detecting mid-latitude UVB trends. In this connection it is desirable to use a UVB dosimeter that has at least two independent parameters, namely, a parameter responding to the integral intensity of UVB radiation and an additional one exclusively sensitive to the short wavelength variations in solar UV spectrum related to ozone depletion. The desired spectral selectivity is intrinsic in D-dosimeter that was recently introduced for an in situ monitoring of vitamin D synthetic capacity of solar UVB radiation. D-dosimeter is based on an in vitro model of vitamin D synthesis. The photoreaction rate (decay of provitamin D and formation of previtamin D) depends upon the integral UV intensity whereas maximum achievable concentration of previtamin D is solely dictated by the spectral position of the short-wave edge of solar spectrum. This makes it possible to reveal ozone depletion under conditions of opaque atmosphere when clouds and aerosols attenuate solar UV flux like a gray filter.

  13. Autocorrelation-based time synchronous averaging for condition monitoring of planetary gearboxes in wind turbines

    NASA Astrophysics Data System (ADS)

    Ha, Jong M.; Youn, Byeng D.; Oh, Hyunseok; Han, Bongtae; Jung, Yoongho; Park, Jungho

    2016-03-01

    We propose autocorrelation-based time synchronous averaging (ATSA) to cope with the challenges associated with the current practice of time synchronous averaging (TSA) for planet gears in planetary gearboxes of wind turbine (WT). An autocorrelation function that represents physical interactions between the ring, sun, and planet gears in the gearbox is utilized to define the optimal shape and range of the window function for TSA using actual kinetic responses. The proposed ATSA offers two distinctive features: (1) data-efficient TSA processing and (2) prevention of signal distortion during the TSA process. It is thus expected that an order analysis with the ATSA signals significantly improves the efficiency and accuracy in fault diagnostics of planet gears in planetary gearboxes. Two case studies are presented to demonstrate the effectiveness of the proposed method: an analytical signal from a simulation and a signal measured from a 2 kW WT testbed. It can be concluded from the results that the proposed method outperforms conventional TSA methods in condition monitoring of the planetary gearbox when the amount of available stationary data is limited.

  14. Containerless protein crystallization in floating drops: application to crystal growth monitoring under reduced nucleation conditions

    NASA Astrophysics Data System (ADS)

    Lorber, Bernard; Giegé, Richard

    1996-10-01

    A micromethod was developed for the batch crystallization of proteins under conditions were the solution has no contact with the container walls. Drops of crystallization solutions (5 to 100 μl) are placed at the interface between two layers of inert and non-miscible silicone fluids contained in square glass or plastic cuvettes. The densities of the fluids are either lower or higher than those of the major precipitating agents of macromolecules, including aqueous solutions containing salts, polyethylene glycols or alcohols. Several proteins and a spherical plant virus were crystallized in the temperature range 4°C-20°C using this set-up. A thermostated device was built for the dynamic control of the temperature of crystallization drops and the monitoring of crystal growth by video-microscopy. In all cases, the habit of the crystals grown in floating drops are identical to those of controls grown in sealed glass tubes without silicone fluid. The comparison of the number of crystals in drops kept under one layer of fluid and in floating drops of the same volume indicates that heterogeneous nucleation is minimized when protein crystallization is performed in floating drops. The advantages and limitations of this novel containerless crystallization method are discussed.

  15. Vibration based condition monitoring of a multistage epicyclic gearbox in lifting cranes

    NASA Astrophysics Data System (ADS)

    Assaad, Bassel; Eltabach, Mario; Antoni, Jérôme

    2014-01-01

    This paper proposes a model-based technique for detecting wear in a multistage planetary gearbox used by lifting cranes. The proposed method establishes a vibration signal model which deals with cyclostationary and autoregressive models. First-order cyclostationarity is addressed by the analysis of the time synchronous average (TSA) of the angular resampled vibration signal. Then an autoregressive model (AR) is applied to the TSA part in order to extract a residual signal containing pertinent fault signatures. The paper also explores a number of methods commonly used in vibration monitoring of planetary gearboxes, in order to make comparisons. In the experimental part of this study, these techniques are applied to accelerated lifetime test bench data for the lifting winch. After processing raw signals recorded with an accelerometer mounted on the outside of the gearbox, a number of condition indicators (CIs) are derived from the TSA signal, the residual autoregressive signal and other signals derived using standard signal processing methods. The goal is to check the evolution of the CIs during the accelerated lifetime test (ALT). Clarity and fluctuation level of the historical trends are finally considered as a criteria for comparing between the extracted CIs.

  16. Monitoring photo-induced transformations in crystals of 2,6-difluorocinnamic acid under ambient conditions.

    PubMed

    Galica, Tomasz; Bąkowicz, Julia; Broda, Piotr; Turowska-Tyrk, Ilona

    2016-07-01

    Several conditions need to be fulfilled for a photochemical reaction to proceed in crystals. Some of these conditions, for example, geometrical conditions, depend on the particular type of photochemical reaction, but the rest are common for all reactions. The mutual directionality of two neighbouring molecules determines the kind of product obtained. The influence of temperature on the probability of a photochemical reaction occurring varies for different types of photochemical reaction and different compounds. High pressure imposed on crystals also has a big influence on the free space and the reaction cavity. The wavelength of the applied UV light is another factor which can initiate a reaction and sometimes determine the structure of a product. It is possible, to a certain degree, to control the packing of molecules in stacks by using fluoro substituents on benzene rings. The crystal and molecular structure of 2,6-difluorocinnamic acid [systematic name: 3-(2,6-difluorophenyl)prop-2-enoic acid], C9H6F2O2, (I), was determined and analysed in terms of a photochemical [2 + 2] dimerization. The molecules are arranged in stacks along the a axis and the values of the intermolecular geometrical parameters indicate that they may undergo this photochemical reaction. The reaction was carried out in situ and the changes of the unit-cell parameters during crystal irradiation by a UV beam were monitored. The values of the unit-cell parameters change in a different manner, viz. cell length a after an initial increase starts to decrease, b after a decrease starts to increase, c increases and the unit-cell volume V after a certain increase starts to decrease. The structure of a partially reacted crystal, i.e. containing both the reactant and the product, namely 2,6-difluorocinnamic acid-3,4-bis(2,6-difluorophenyl)cyclobutane-1,2-dicarboxylic acid (0.858/0.071), 0.858C9H6F2O2·0.071C18H12F4O4, obtained in situ, is also presented. The powder of compound (I) was irradiated with

  17. Linear models of coregionalization for multivariate lattice data: a general framework for coregionalized multivariate CAR models.

    PubMed

    MacNab, Ying C

    2016-09-20

    We present a general coregionalization framework for developing coregionalized multivariate Gaussian conditional autoregressive (cMCAR) models for Bayesian analysis of multivariate lattice data in general and multivariate disease mapping data in particular. This framework is inclusive of cMCARs that facilitate flexible modelling of spatially structured symmetric or asymmetric cross-variable local interactions, allowing a wide range of separable or non-separable covariance structures, and symmetric or asymmetric cross-covariances, to be modelled. We present a brief overview of established univariate Gaussian conditional autoregressive (CAR) models for univariate lattice data and develop coregionalized multivariate extensions. Classes of cMCARs are presented by formulating precision structures. The resulting conditional properties of the multivariate spatial models are established, which cast new light on cMCARs with richly structured covariances and cross-covariances of different spatial ranges. The related methods are illustrated via an in-depth Bayesian analysis of a Minnesota county-level cancer data set. We also bring a new dimension to the traditional enterprize of Bayesian disease mapping: estimating and mapping covariances and cross-covariances of the underlying disease risks. Maps of covariances and cross-covariances bring to light spatial characterizations of the cMCARs and inform on spatial risk associations between areas and diseases. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27091685

  18. Integrated Approach Using Condition Monitoring and Modeling to Investigate Wind Turbine Gearbox Design: Preprint

    SciTech Connect

    Sheng, S.; Guo, Y.

    2015-03-01

    Vibration-based condition monitoring (CM) of geared utility-scale turbine drivetrains has been used by the wind industry to help improve operation and maintenance (O&M) practices, increase turbine availability, and reduce O&M cost. This study is a new endeavor that integrates the vibration-based CM technique with wind turbine gearbox modeling to investigate various gearbox design options. A teamof researchers performed vibration-based CM measurements on a damaged wind turbine gearbox with a classic configuration, (i.e., one planetary stage and two parallel stages). We observed that the acceleration amplitudes around the first-order sidebands of the intermediate stage gear set meshing frequency were much lower than that measured at the high-speed gear set, and similar difference wasalso observed in a healthy gearbox. One factor for a reduction at the intermediate stage gear set is hypothesized to be the soft sun-spline configuration in the test gearbox. To evaluate this hypothesis, a multibody dynamic model of the healthy test gearbox was first developed and validated. Relative percent difference of the first-order sidebands--of the high-speed and intermediate stagegear-meshing frequencies--in the soft and the rigid sun spline configurations were compared. The results verified that the soft sun-spline configuration can reduce the sidebands of the intermediate stage gear set and also the locating bearing loads. The study demonstrates that combining vibration-based CM with appropriate modeling can provide insights for evaluating different wind turbinegearbox design options.

  19. Cable aging and condition monitoring of radiation resistant nano-dielectrics in advanced reactor applications

    SciTech Connect

    Duckworth, Robert C; Aytug, Tolga; Paranthaman, Mariappan Parans; Kidder, Michelle; Polyzos, Georgios; Leonard, Keith J

    2015-01-01

    Cross-linked polyethylene (XLPE) nanocomposites have been developed in an effort to improve cable insulation lifetime to serve in both instrument cables and auxiliary power systems in advanced reactor applications as well as to provide an alternative for new or retro-fit cable insulation installations. Nano-dielectrics composed of different weight percentages of MgO & SiO2 have been subjected to radiation at accumulated doses approaching 20 MRad and thermal aging temperatures exceeding 100 C. Depending on the composition, the performance of the nanodielectric insulation was influenced, both positively and negatively, when quantified with respect to its electrical and mechanical properties. For virgin unradiated or thermally aged samples, XLPE nanocomposites with 1wt.% SiO2 showed improvement in breakdown strength and reduction in its dissipation factor when compared to pure undoped XLPE, while XLPE 3wt.% SiO2 resulted in lower breakdown strength. When aged in air at 120 C, retention of electrical breakdown strength and dissipation factor was observed for XLPE 3wt.% MgO nanocomposites. Irrespective of the nanoparticle species, XLPE nanocomposites that were gamma irradiated up to the accumulated dose of 18 MRad showed a significant drop in breakdown strength especially for particle concentrations greater than 3 wt.%. Additional attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy measurements suggest changes in the structure of the XLPE SiO2 nanocomposites associated with the interaction of silicon and oxygen. Discussion on the relevance of property changes with respect to cable aging and condition monitoring is presented.

  20. Telemedical systems for home monitoring of patients with chronic conditions in rural environment.

    PubMed

    Maciejewski, Marcin; Surtel, Wojciech; Wójcik, Waldemar; Masiak, Jolanta; Dzida, Grzegorz; Horoch, Andrzej

    2014-01-01

    This paper describes the requirements and possible implementations of a telemedical system. The idea of remote patient monitoring is a point of interest for researchers in Poland, and is also in high demand in fields such as diabetology, cardiology, and geriatrics, among others. Aging society, medical care costs and many other factors make remote patient care a promising idea for the future. For each and every condition, a specialized type of sensor must be used to allow specific measurements to be performed. Moreover, a local data storage and communication device must be provided for the sensor to be able to relay data to the station. A smart phone can be used perform such tasks. By implementing such remote diagnostic systems it is possible to collect, process, store and present vital medical data that can be used immediately to perform diagnosis, or later as reference for expert systems. The 'Borboleta' and 'SaguiSaúde' systems already implemented can serve as a base for system analysis. The systems provide necessary functions and can be used as reference. Many factors contribute to the success of the telemedical system, such as ease of access, scalability, safety, platform independence, and many others. For easier implementation and clarity, the system should be divided into independent layers, which will also make it easier to modify and integrate into other medical systems. Making the system easy to use for patients, medical staff, administrators and data managers makes the task of system design especially challenging. One must decide which information is necessary for each type of user and provide them clearly and in an orderly fashion. PMID:24738518

  1. Summary report: Working Group 4 on 'Beam Monitoring, Conditioning, and Control at High Frequencies and Ultrafast Timescales'

    SciTech Connect

    Smith, Todd I.

    1999-07-12

    Working Group 4 at the 8th Advanced Accelerator Concepts Workshop (ACC'98), held July 5-11, 1998 in Baltimore, Maryland hosted more than fifteen scheduled or impromptu talks (all punctuated with lively discussion) on the general topic of 'Beam Monitoring, Conditioning, and Control at High Frequencies and Ultrafast Timescales'. This report is a summary of these talks and discussions.

  2. A practical signal processing approach for condition monitoring of low speed machinery using Peak-Hold-Down-Sample algorithm

    NASA Astrophysics Data System (ADS)

    Lin, Tian Ran; Kim, Eric; Tan, Andy C. C.

    2013-04-01

    A simple and effective down-sample algorithm, Peak-Hold-Down-Sample (PHDS) algorithm is developed in this paper to enable a rapid and efficient data transfer in remote condition monitoring applications. The algorithm is particularly useful for high frequency Condition Monitoring (CM) techniques, and for low speed machine applications since the combination of the high sampling frequency and low rotating speed will generally lead to large unwieldy data size. The effectiveness of the algorithm was evaluated and tested on four sets of data in the study. One set of the data was extracted from the condition monitoring signal of a practical industry application. Another set of data was acquired from a low speed machine test rig in the laboratory. The other two sets of data were computer simulated bearing defect signals having either a single or multiple bearing defects. The results disclose that the PHDS algorithm can substantially reduce the size of data while preserving the critical bearing defect information for all the data sets used in this work even when a large down-sample ratio was used (i.e., 500 times down-sampled). In contrast, the down-sample process using the existing normal down-sample technique in signal processing eliminates the useful and critical information such as bearing defect frequencies in a signal when the same down-sample ratio was employed. Noise and artificial frequency components were also induced by the normal down-sample technique, thus limits its usefulness for machine condition monitoring applications.

  3. Real time monitoring of slope condition for transmission tower safety in Kenyir, Malaysia

    NASA Astrophysics Data System (ADS)

    Omar, R. C.; Ismail, A.; Khalid, N. H. N.; Din, N. M.; Hussain, H.; Jamaludin, M. Z.; Abdullah, F.; Arazad, A. Z.; Yusop, H.

    2013-06-01

    The Malaysia national electricity grid traverses throughout the nation over urban and rural areas including mountainous terrain. A major number of the transmission towers have been in existence for over 40 years and some traversed through very remote and high altitude areas like the Titiwangsa range that forms the backbone of the Malay Peninsula. This paper describes the instrumentation and real time monitoring in a transmission tower site in Kenyir, a hilly terrain in the East Coast of Malaysia. The site itself which is between 300-500m above sea level is deep in the rainforest area of Kenyir. The site and surrounding areas has been identified with signs of slope failure. A design concern is the real time slope monitoring sensors reliability and data integrity from the remote area with potential interference to the electronics equipment from the power line. The monitoring system comprised of an automated system for collecting and reporting field monitoring data. The instruments collect readings and transmit real time through GSM to the monitoring office over designated intervals. This initiative is a part of a project on developing an early warning system for monitoring landslide hazards at selected transmission towers. This paper reviews the various instrumentation used and challenges faced and the output received for slope movement warnings.

  4. Network challenges for cyber physical systems with tiny wireless devices: a case study on reliable pipeline condition monitoring.

    PubMed

    Ali, Salman; Qaisar, Saad Bin; Saeed, Husnain; Khan, Muhammad Farhan; Naeem, Muhammad; Anpalagan, Alagan

    2015-01-01

    The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs). CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed. PMID:25815444

  5. Network Challenges for Cyber Physical Systems with Tiny Wireless Devices: A Case Study on Reliable Pipeline Condition Monitoring

    PubMed Central

    Ali, Salman; Qaisar, Saad Bin; Saeed, Husnain; Farhan Khan, Muhammad; Naeem, Muhammad; Anpalagan, Alagan

    2015-01-01

    The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs). CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed. PMID:25815444

  6. Modeling of ultrasonic and terahertz radiations in defective tiles for condition monitoring of thermal protection systems

    NASA Astrophysics Data System (ADS)

    Kabiri Rahani, Ehsan

    Condition based monitoring of Thermal Protection Systems (TPS) is necessary for safe operations of space shuttles when quick turn-around time is desired. In the current research Terahertz radiation (T-ray) has been used to detect mechanical and heat induced damages in TPS tiles. Voids and cracks inside the foam tile are denoted as mechanical damage while property changes due to long and short term exposures of tiles to high heat are denoted as heat induced damage. Ultrasonic waves cannot detect cracks and voids inside the tile because the tile material (silica foam) has high attenuation for ultrasonic energy. Instead, electromagnetic terahertz radiation can easily penetrate into the foam material and detect the internal voids although this electromagnetic radiation finds it difficult to detect delaminations between the foam tile and the substrate plate. Thus these two technologies are complementary to each other for TPS inspection. Ultrasonic and T-ray field modeling in free and mounted tiles with different types of mechanical and thermal damages has been the focus of this research. Shortcomings and limitations of FEM method in modeling 3D problems especially at high-frequencies has been discussed and a newly developed semi-analytical technique called Distributed Point Source Method (DPSM) has been used for this purpose. A FORTRAN code called DPSM3D has been developed to model both ultrasonic and electromagnetic problems using the conventional DPSM method. This code is designed in a general form capable of modeling a variety of geometries. DPSM has been extended from ultrasonic applications to electromagnetic to model THz Gaussian beams, multilayered dielectrics and Gaussian beam-scatterer interaction problems. Since the conventional DPSM has some drawbacks, to overcome it two modification methods called G-DPSM and ESM have been proposed. The conventional DPSM in the past was only capable of solving time harmonic (frequency domain) problems. Time history was

  7. Extended step-out length fiber Bragg grating interrogation system for condition monitoring of electrical submersible pumps

    NASA Astrophysics Data System (ADS)

    Fusiek, G.; Niewczas, Pawel; McDonald, James R.

    2005-03-01

    We present details of the design and laboratory evaluation of the fiber Bragg grating (FBG) interrogation system developed specifically for condition monitoring of electrical submersible pumps (ESPs). The system, based on the microelectromechanical systems (MEMS) Fabry-Pérot tunable filter, is capable of interrogating several FBG sensors placed around an ESP unit and configured to measure static and dynamic parameters, e.g., temperature, vibration signature and/or instantaneous voltage, and current. Sensor interrogation over the extended step-out length distance of 24 km is demonstrated in the laboratory in a simple experiment of multipoint dynamic strain monitoring in a vibrated cantilever beam.

  8. Autonomous monitoring of control hardware to predict off-normal conditions using NIF automatic Alignment Systems

    SciTech Connect

    Awwal, A; Wilhelmsen, K; Leach, R; Kamm, V M; Burkhart, S; Lowe-Webb, R; Cohen, S

    2011-07-20

    The National Ignition Facility (NIF) is a high power laser system capable of supporting high-energy-density experimentation as a user facility for the next 30 years. In order to maximize the facility availability, preventive maintenance enhancements are being introduced into the system. An example of such an enhancement is a camera-based health monitoring system, integrated into the automated alignment system, which provides an opportunity to monitor trends in measurements such as average beam intensity, size of the beam, and pixel saturation. The monitoring system will generate alerts based on observed trends in measurements to allow scheduled pro-active maintenance before routine off-normal detection stops system operations requiring unscheduled intervention.

  9. An Improved Gaussian Mixture Model for Damage Propagation Monitoring of an Aircraft Wing Spar under Changing Structural Boundary Conditions

    PubMed Central

    Qiu, Lei; Yuan, Shenfang; Mei, Hanfei; Fang, Fang

    2016-01-01

    Structural Health Monitoring (SHM) technology is considered to be a key technology to reduce the maintenance cost and meanwhile ensure the operational safety of aircraft structures. It has gradually developed from theoretic and fundamental research to real-world engineering applications in recent decades. The problem of reliable damage monitoring under time-varying conditions is a main issue for the aerospace engineering applications of SHM technology. Among the existing SHM methods, Guided Wave (GW) and piezoelectric sensor-based SHM technique is a promising method due to its high damage sensitivity and long monitoring range. Nevertheless the reliability problem should be addressed. Several methods including environmental parameter compensation, baseline signal dependency reduction and data normalization, have been well studied but limitations remain. This paper proposes a damage propagation monitoring method based on an improved Gaussian Mixture Model (GMM). It can be used on-line without any structural mechanical model and a priori knowledge of damage and time-varying conditions. With this method, a baseline GMM is constructed first based on the GW features obtained under time-varying conditions when the structure under monitoring is in the healthy state. When a new GW feature is obtained during the on-line damage monitoring process, the GMM can be updated by an adaptive migration mechanism including dynamic learning and Gaussian components split-merge. The mixture probability distribution structure of the GMM and the number of Gaussian components can be optimized adaptively. Then an on-line GMM can be obtained. Finally, a best match based Kullback-Leibler (KL) divergence is studied to measure the migration degree between the baseline GMM and the on-line GMM to reveal the weak cumulative changes of the damage propagation mixed in the time-varying influence. A wing spar of an aircraft is used to validate the proposed method. The results indicate that the crack

  10. An Improved Gaussian Mixture Model for Damage Propagation Monitoring of an Aircraft Wing Spar under Changing Structural Boundary Conditions.

    PubMed

    Qiu, Lei; Yuan, Shenfang; Mei, Hanfei; Fang, Fang

    2016-01-01

    Structural Health Monitoring (SHM) technology is considered to be a key technology to reduce the maintenance cost and meanwhile ensure the operational safety of aircraft structures. It has gradually developed from theoretic and fundamental research to real-world engineering applications in recent decades. The problem of reliable damage monitoring under time-varying conditions is a main issue for the aerospace engineering applications of SHM technology. Among the existing SHM methods, Guided Wave (GW) and piezoelectric sensor-based SHM technique is a promising method due to its high damage sensitivity and long monitoring range. Nevertheless the reliability problem should be addressed. Several methods including environmental parameter compensation, baseline signal dependency reduction and data normalization, have been well studied but limitations remain. This paper proposes a damage propagation monitoring method based on an improved Gaussian Mixture Model (GMM). It can be used on-line without any structural mechanical model and a priori knowledge of damage and time-varying conditions. With this method, a baseline GMM is constructed first based on the GW features obtained under time-varying conditions when the structure under monitoring is in the healthy state. When a new GW feature is obtained during the on-line damage monitoring process, the GMM can be updated by an adaptive migration mechanism including dynamic learning and Gaussian components split-merge. The mixture probability distribution structure of the GMM and the number of Gaussian components can be optimized adaptively. Then an on-line GMM can be obtained. Finally, a best match based Kullback-Leibler (KL) divergence is studied to measure the migration degree between the baseline GMM and the on-line GMM to reveal the weak cumulative changes of the damage propagation mixed in the time-varying influence. A wing spar of an aircraft is used to validate the proposed method. The results indicate that the crack

  11. Technologies of Physical Monitoring and Mathematical Modeling for Estimation of Ground Forest Fuel Fire Condition

    NASA Astrophysics Data System (ADS)

    Baranovskiy, Nikolay V.; Bazarov, Alexandr V.

    2016-02-01

    Description of new experimental installations for the control of parameters of environment with a view of monitoring of forest fires presented in article. Stationary and mobile variants developed. Typical results of operation of installations during a fire-dangerous season of 2015 in vicinities of Ulan-Ude (Republic Buryatiya, Russia) presented. One-dimensional mathematical model of forest fuel drying which can be used for monitoring of forest fire danger with attraction of environmental parameters data during fire-dangerous season offered. Verification of mathematical model with use of known experimental data spent.

  12. Monitoring crop condition at field scale using multiple remote sensing data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop growth condition is affected by both environmental variables (climate, weather and soil condition etc.) and anthropogenic activities (fertilization and irrigation etc.). Crop condition varies by year and location and is critical for crop management and yield estimation. In the United States, cr...

  13. A general framework for multivariate multi-index drought prediction based on Multivariate Ensemble Streamflow Prediction (MESP)

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.

    2016-08-01

    Drought is among the costliest natural hazards worldwide and extreme drought events in recent years have caused huge losses to various sectors. Drought prediction is therefore critically important for providing early warning information to aid decision making to cope with drought. Due to the complicated nature of drought, it has been recognized that the univariate drought indicator may not be sufficient for drought characterization and hence multivariate drought indices have been developed for drought monitoring. Alongside the substantial effort in drought monitoring with multivariate drought indices, it is of equal importance to develop a drought prediction method with multivariate drought indices to integrate drought information from various sources. This study proposes a general framework for multivariate multi-index drought prediction that is capable of integrating complementary prediction skills from multiple drought indices. The Multivariate Ensemble Streamflow Prediction (MESP) is employed to sample from historical records for obtaining statistical prediction of multiple variables, which is then used as inputs to achieve multivariate prediction. The framework is illustrated with a linearly combined drought index (LDI), which is a commonly used multivariate drought index, based on climate division data in California and New York in the United States with different seasonality of precipitation. The predictive skill of LDI (represented with persistence) is assessed by comparison with the univariate drought index and results show that the LDI prediction skill is less affected by seasonality than the meteorological drought prediction based on SPI. Prediction results from the case study show that the proposed multivariate drought prediction outperforms the persistence prediction, implying a satisfactory performance of multivariate drought prediction. The proposed method would be useful for drought prediction to integrate drought information from various sources

  14. Cable Polymer Aging and Condition Monitoring Research at Sandia National Laboratores Under the Nuclear Energy Plant Optimization (NEPO) Program

    SciTech Connect

    K. Gillen; R. Assink; R. Bernstein

    2005-12-23

    This report describes cable polymer aging and condition monitoring research performed at Sandia National Laboratories under the Nuclear Energy Plant Optimization (NEPO) Program from 2000 to 2005. The research results apply to low-voltage cable insulation and Program from 2000 to 2005. The research results apply to low-voltage cable insulation and jacket materials that are commonly used in U.S. nuclear power plants. The research builds upon and is liked to research performed at Sandia from 1977 through 1986, sponsored by the U.S. Nuclear Regulatory Commission. Aged and unaged specimens from that research remained available and were subjected to further testing under the NEPO research effort.The documented results from the earlier research were complemented by subjecting the specimens to new condition monitoring tests. Additional aging regimens were applied to additional specimens to develop aging models for key cable jacket and insulation materials

  15. Application of the largest Lyapunov exponent algorithm for feature extraction in low speed slew bearing condition monitoring

    NASA Astrophysics Data System (ADS)

    Caesarendra, Wahyu; Kosasih, Buyung; Tieu, Anh Kiet; Moodie, Craig A. S.

    2015-01-01

    This paper presents a new application of the largest Lyapunov exponent (LLE) algorithm for feature extraction method in low speed slew bearing condition monitoring. The LLE algorithm is employed to measure the degree of non-linearity of the vibration signal which is not easily monitored by existing methods. The method is able to detect changes in the condition of the bearing and demonstrates better tracking of the progressive deterioration of the bearing during the 139 measurement days than comparable methods such as the time domain feature methods based on root mean square (RMS), skewness and kurtosis extraction from the raw vibration signal and also better than extracting similar features from selected intrinsic mode functions (IMFs) of the empirical mode decomposition (EMD) result. The application of the method is demonstrated with laboratory slew bearing vibration data and industrial bearing data from a coal bridge reclaimer used in a local steel mill.

  16. Monitoring Drought Conditions in the Navajo Nation Using NASA Earth Observations

    NASA Technical Reports Server (NTRS)

    Ly, Vickie; Gao, Michael; Cary, Cheryl; Turnbull-Appell, Sophie; Surunis, Anton

    2016-01-01

    The Navajo Nation, a 65,700 sq km Native American territory located in the southwestern United States, has been increasingly impacted by severe drought events and changes in climate. These events are coupled with a lack of domestic water infrastructure and economic resources, leaving approximately one-third of the population without access to potable water in their homes. Current methods of monitoring drought are dependent on state-based monthly Standardized Precipitation Index value maps calculated by the Western Regional Climate Center. However, these maps do not provide the spatial resolution needed to illustrate differences in drought severity across the vast Nation. To better understand and monitor drought events and drought regime changes in the Navajo Nation, this project created a geodatabase of historical climate information specific to the area, and a decision support tool to calculate average Standardized Precipitation Index values for user-specified areas. The tool and geodatabase use Tropical Rainfall Monitoring Mission (TRMM) and Global Precipitation Monitor (GPM) observed precipitation data and Parameter-elevation Relationships on Independent Slopes Model modeled historical precipitation data, as well as NASA's modeled Land Data Assimilation Systems deep soil moisture, evaporation, and transpiration data products. The geodatabase and decision support tool will allow resource managers in the Navajo Nation to utilize current and future NASA Earth observation data for increased decision-making capacity regarding future climate change impact on water resources.

  17. Monitoring crop and vegetation condition using the fused dense time-series landsat-like imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Since the launch of the first Landsat satellite in the early 1970s, Landsat has been widely used in many applications such as land cover and land use change monitoring, crop yield estimation, forest fire detection, and global ecosystem carbon cycle studies. Medium resolution sensors like Landsat hav...

  18. Monitoring

    DOEpatents

    Orr, Christopher Henry; Luff, Craig Janson; Dockray, Thomas; Macarthur, Duncan Whittemore

    2004-11-23

    The invention provides apparatus and methods which facilitate movement of an instrument relative to an item or location being monitored and/or the item or location relative to the instrument, whilst successfully excluding extraneous ions from the detection location. Thus, ions generated by emissions from the item or location can successfully be monitored during movement. The technique employs sealing to exclude such ions, for instance, through an electro-field which attracts and discharges the ions prior to their entering the detecting location and/or using a magnetic field configured to repel the ions away from the detecting location.

  19. Building America Case Study: Monitoring of Double Stud Wall Moisture Conditions in the Northeast, Devens, Massachusetts (Fact Sheet)

    SciTech Connect

    Not Available

    2015-03-01

    Double-stud walls insulated with cellulose or low-density spray foam can have R-values of 40 or higher. However, double stud walls have a higher risk of interior-sourced condensation moisture damage, when compared with high-R approaches using exterior insulating sheathing. Moisture conditions in double stud walls were monitored in Zone 5A (Massachusetts); three double stud assemblies were compared.

  20. Condition monitoring of concrete structures using wireless sensor networks and MEMS

    NASA Astrophysics Data System (ADS)

    Grosse, Christian U.; Glaser, Steven D.; Krüger, Markus

    2006-03-01

    The inspection of building structures, especially bridges, is currently made by visual inspection. The few non-visual methodologies make use of wired sensor networks, which are relatively expensive, vulnerable to damage, and time consuming to install. Systems based on wireless sensor networks should be both cost efficient and easy to install, scalable and adaptive to different type of structures. Acoustic emission techniques are an additional monitoring method to investigate the status of a bridge or some of its components. It has the potential to detect defects in terms of cracks propagating during the routine use of structures. However, acoustic emissions recording and analysis techniques need powerful algorithms to handle and reduce the immense amount of data generated. These algorithms are developed on the basis of neural network techniques and - regarding localization of defects - by array techniques. Sensors with low price are essential for such monitoring systems to be accepted. Although the development costs of such a system are relatively high, the target price for the entire monitoring system will be several thousands Euro, depending on the size of the structure and the number of sensors necessary to cover the most important parts of the structure. Micro-Electro-Mechanical-Systems and hybrid sensors form the heart of Motes (network nodes). The network combined multi-hop data transmission techniques with efficient data pre-processing in the nodes. Using this technique, monitoring of large structures in civil engineering becomes very efficient including the sensing of temperature, moisture, strain and other data continuously. In this paper, the basic principles of a wireless monitoring system equipped with MEMS sensors is presented along with a first prototype. The authors work on details of network configuration, power consumption, data acquisition and data aggregation, signal analysis and data reduction is presented.

  1. Feasibility study of monitoring of plasma etching chamber conditions using superimposed high-frequency signals on rf power transmission line.

    PubMed

    Kasashima, Y; Uesugi, F

    2015-10-01

    An in situ monitoring system that can detect changes in the conditions of a plasma etching chamber has been developed. In the system, low-intensity high-frequency signals are superimposed on the rf power transmission line used for generating plasma. The system measures reflected high-frequency signals and detects the change in their frequency characteristics. The results indicate that the system detects the changes in the conditions in etching chambers caused by the changes in the electrode gap and the inner wall condition and demonstrate the effectiveness of the system. The system can easily be retrofitted to mass-production equipment and it can be used with or without plasma discharge. Therefore, our system is suitable for in situ monitoring of mass-production plasma etching chambers. The system is expected to contribute to development of predictive maintenance, which monitors films deposited on the inner wall of the chamber and prevents equipment faults caused by misalignment of chamber parts in mass-production equipment. PMID:26520984

  2. Joint use of soil moisture and vegetation growth condition by remote sensing on the agricultural drought monitoring

    NASA Astrophysics Data System (ADS)

    Liu, Ming; Yang, Siquan; Huang, He; He, Haixia; Li, Suju; Cui, Yan

    2015-12-01

    Remote sensing is one of important methods on the agricultural drought monitoring for its long-term and wide-area observations. The detection of soil moisture and vegetation growth condition are two widely used remote sensing methods on that. However, because of the time lag in the impact of water deficit on the crop growth, it is difficulty to indicate the severity of drought by once monitoring. It also cannot distinguish other negative impact on crop growth such as low temperature or solar radiation. In this paper, the joint use of soil moisture and vegetation growth condition detections was applied on the drought management during the summer of 2013 in Liaoning province, China, in which 84 counties were affected by agricultural drought. MODIS vegetation indices and land surface temperature (LST) were used to extract the drought index. Vegetation Condition Index (VCI), which only contain the change in vegetation index, and Vegetation Supply Water Index (VSWI), which combined the information of vegetation index and land surface temperature, were selected to compare the monitoring ability on drought during the drought period in Liaoning, China in 2014. It was found that VCI could be a good method on the loss assessment. VSWI has the information on the change in LST, which can indicate the spatial pattern of drought and can also be used as the early warning method in the study.

  3. Integrating Condition Indicators and Usage Parameters for Improved Spiral Bevel Gear Health Monitoring

    NASA Technical Reports Server (NTRS)

    Dempsey, Paula J.; Handschuh, Robert F.; Delgado, Irebert R.

    2013-01-01

    The objective of this study was to illustrate the importance of combining Health Usage Monitoring Systems (HUMS) data with usage monitoring system data when detecting rotorcraft transmission health. Six gear sets were tested in the NASA Glenn Spiral Bevel Gear Fatigue Rig. Damage was initiated and progressed on the gear and pinion teeth. Damage progression was measured by debris generation and documented with inspection photos at varying torque values. A contact fatigue analysis was applied to the gear design indicating the effect temperature, load and reliability had on gear life. Results of this study illustrated the benefits of combining HUMS data and actual usage data to indicate progression of damage for spiral bevel gears.

  4. Wide band fiber Bragg grating accelerometer for rotating AC machinery condition monitoring

    NASA Astrophysics Data System (ADS)

    Vilchis-Rodriguez, Damian S.; Djurovic, Sinisa; Kung, Peter; Comanici, Maria I.; Scepanovic, S.; Tshiloz, Kavul; Smith, Alexander C.

    2014-09-01

    This paper investigates the use of fiber Bragg grating (FBG) accelerometers for wide band vibration monitoring in a wound rotor induction generator. The sensor performance is assessed in a series of experiments on a laboratory test rig comprising a 30kW induction machine operating under steady state and variable speed regimes. Vibration measurements are investigated in the frequency domain for generator fault specific electromagnetically induced vibration components. The fiber optic sensor effectiveness in detection of wide band spectral effects (<1kHz) in the vibration signal is compared with that of a commercial piezoelectric based solution. The potential and limitations of the prototype wide band FBG accelerometer are evaluated for use in vibration monitoring applications.

  5. Monitoring of environmental conditions in the Alaskan forests using ERS-1 SAR data

    NASA Technical Reports Server (NTRS)

    Rignot, Eric; Way, Jobea; Mcdonald, Kyle; Viereck, Leslie; Adams, Phyllis

    1992-01-01

    Preliminary results from an analysis of the multitemporal radar backscatter signatures of tree species acquired by European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data are presented. Significant changes in radar backscatter are detected. Correlation of these differences with ground truth observations indicate that these are due to changes in soil and liquid water content as a result of freeze/thaw events. C-band observations acquired by the NASA/Jet Propulsion Laboratory Airborne SAR (JPL AIRSAR) instrument demonstrate the potential of a C-band radar instrument to monitor drought/flood events. The potential of ERS-1 for monitoring phenologic changes in the forest and for classifying tree species is less promising.

  6. Integrating Condition Indicators and Usage Parameters for Improved Spiral Bevel Gear Health Monitoring

    NASA Technical Reports Server (NTRS)

    Dempsey, Paula J.; Handschuh, Robert F.; Delgado, Irebert, R.

    2013-01-01

    The objective of this study was to illustrate the importance of combining Health Usage Monitoring Systems (HUMS) data with usage monitoring system data when detecting rotorcraft transmission health. Three gear sets were tested in the NASA Glenn Spiral Bevel Gear Fatigue Rig. Damage was initiated and progressed on the gear and pinion teeth. Damage progression was measured by debris generation and documented with inspection photos at varying torque values. A contact fatigue analysis was applied to the gear design indicating the effect temperature, load and reliability had on gear life. Results of this study illustrated the benefits of combining HUMS data and actual usage data to indicate progression of damage for spiral bevel gears.

  7. Real-Time Condition Monitoring and Fault Diagnosis of Gear Train Systems Using Instantaneous Angular Speed (IAS) Analysis

    NASA Astrophysics Data System (ADS)

    Sait, Abdulrahman S.

    This dissertation presents a reliable technique for monitoring the condition of rotating machinery by applying instantaneous angular speed (IAS) analysis. A new analysis of the effects of changes in the orientation of the line of action and the pressure angle of the resultant force acting on gear tooth profile of spur gear under different levels of tooth damage is utilized. The analysis and experimental work discussed in this dissertation provide a clear understating of the effects of damage on the IAS by analyzing the digital signals output of rotary incremental optical encoder. A comprehensive literature review of state of the knowledge in condition monitoring and fault diagnostics of rotating machinery, including gearbox system is presented. Progress and new developments over the past 30 years in failure detection techniques of rotating machinery including engines, bearings and gearboxes are thoroughly reviewed. This work is limited to the analysis of a gear train system with gear tooth surface faults utilizing angular motion analysis technique. Angular motion data were acquired using an incremental optical encoder. Results are compared to a vibration-based technique. The vibration data were acquired using an accelerometer. The signals were obtained and analyzed in the phase domains using signal averaging to determine the existence and position of faults on the gear train system. Forces between the mating teeth surfaces are analyzed and simulated to validate the influence of the presence of damage on the pressure angle and the IAS. National Instruments hardware is used and NI LabVIEW software code is developed for real-time, online condition monitoring systems and fault detection techniques. The sensitivity of optical encoders to gear fault detection techniques is experimentally investigated by applying IAS analysis under different gear damage levels and different operating conditions. A reliable methodology is developed for selecting appropriate testing

  8. Refinement of current monitoring methodology for electroosmotic flow assessment under low ionic strength conditions.

    PubMed

    Saucedo-Espinosa, Mario A; Lapizco-Encinas, Blanca H

    2016-05-01

    Current monitoring is a well-established technique for the characterization of electroosmotic (EO) flow in microfluidic devices. This method relies on monitoring the time response of the electric current when a test buffer solution is displaced by an auxiliary solution using EO flow. In this scheme, each solution has a different ionic concentration (and electric conductivity). The difference in the ionic concentration of the two solutions defines the dynamic time response of the electric current and, hence, the current signal to be measured: larger concentration differences result in larger measurable signals. A small concentration difference is needed, however, to avoid dispersion at the interface between the two solutions, which can result in undesired pressure-driven flow that conflicts with the EO flow. Additional challenges arise as the conductivity of the test solution decreases, leading to a reduced electric current signal that may be masked by noise during the measuring process, making for a difficult estimation of an accurate EO mobility. This contribution presents a new scheme for current monitoring that employs multiple channels arranged in parallel, producing an increase in the signal-to-noise ratio of the electric current to be measured and increasing the estimation accuracy. The use of this parallel approach is particularly useful in the estimation of the EO mobility in systems where low conductivity mediums are required, such as insulator based dielectrophoresis devices. PMID:27375813

  9. REGIONAL SCALE TREND MONITORING OF INDICATORS OF TROPHIC CONDITION OF LAKES

    EPA Science Inventory

    Society increasingly faces a need to determine whether the condition of its aquatic resources is improving, degrading, or remaining the same on statewide, regional, and national scales. he U.S.EPA has proposed a sample survey design to answer questions about the ecological condit...

  10. Systems and methods of monitoring acoustic pressure to detect a flame condition in a gas turbine

    SciTech Connect

    Ziminsky, Willy Steve; Krull, Anthony Wayne; Healy, Timothy Andrew , Yilmaz, Ertan

    2011-05-17

    A method may detect a flashback condition in a fuel nozzle of a combustor. The method may include obtaining a current acoustic pressure signal from the combustor, analyzing the current acoustic pressure signal to determine current operating frequency information for the combustor, and indicating that the flashback condition exists based at least in part on the current operating frequency information.

  11. Usefulness of LANDSAT data for monitoring plant development and range conditions in California's annual grassland

    NASA Technical Reports Server (NTRS)

    Carneggie, D. M.; Degloria, S. D.; Colwell, R. N.

    1977-01-01

    A network of sampling sites throughout the annual grassland region was established to correlate plant growth in stages and forage production to climatic and other environmental factors. Plant growth and range conditions were further related to geographic location and seasonal variations. A sequence of LANDSAT data was obtained covering critical periods in the growth cycle. Data were analyzed by both photointerpretation and computer aided techniques. Image characteristics and spectral reflectance data were then related to forage production, range condition, range site, and changing growth conditions.

  12. (Anti)symmetric multivariate trigonometric functions and corresponding Fourier transforms

    NASA Astrophysics Data System (ADS)

    Klimyk, A.; Patera, J.

    2007-09-01

    Four families of special functions, depending on n variables, are studied. We call them symmetric and antisymmetric multivariate sine and cosine functions. They are given as determinants or antideterminants of matrices, whose matrix elements are sine or cosine functions of one variable each. These functions are eigenfunctions of the Laplace operator, satisfying specific conditions at the boundary of a certain domain F of the n-dimensional Euclidean space. Discrete and continuous orthogonality on F of the functions within each family allows one to introduce symmetrized and antisymmetrized multivariate Fourier-like transforms involving the symmetric and antisymmetric multivariate sine and cosine functions.

  13. Normalization and source separation of acoustic emission signals for condition monitoring and fault detection of multi-cylinder diesel engines

    NASA Astrophysics Data System (ADS)

    Wu, Weiliang; Lin, Tian Ran; Tan, Andy C. C.

    2015-12-01

    A signal processing technique is presented in this paper to normalize and separate the source of non-linear acoustic emission (AE) signals of a multi-cylinder diesel engine for condition monitoring applications and fault detection. The normalization technique presented in the paper overcomes the long-existing non-linearity problem of AE sensors so that responses measured by different AE sensors can be quantitatively analysed and compared. A source separation algorithm is also developed in the paper to separate the mixture of the normalized AE signals produced by a multi-cylinder diesel engine by utilising the system parameters (i.e., wave attenuation constant and the arrival time delay) of AE wave propagation determined by a standard pencil lead break test on the engine cylinder head. It is shown that the source separation algorithm is able to separate the signal interference of adjacent cylinders from the monitored cylinder once the wave attenuation constant and the arrival time delay along the propagation path are known. The algorithm is particularly useful in the application of AE technique for condition monitoring of small-size diesel engines where signal interference from the neighbouring cylinders is strong.

  14. Cost-effective sampling network design for contaminant plume monitoring under general hydrogeological conditions.

    PubMed

    Wu, Jianfeng; Zheng, Chunmiao; Chien, Calvin C

    2005-03-01

    A new simulation-optimization methodology is developed for cost-effective sampling network design associated with long-term monitoring of large-scale contaminant plumes. The new methodology is similar in concept to the one presented by Reed et al. (Reed, P.M., Minsker, B.S., Valocchi, A.J., 2000a. Cost-effective long-term groundwater monitoring design using a genetic algorithm and global mass interpolation. Water Resour. Res. 36 (12), 3731-3741) in that an optimization model based on a genetic algorithm is coupled with a flow and transport simulator and a global mass estimator to search for optimal sampling strategies. However, this study introduces the first and second moments of a three-dimensional contaminant plume as new constraints in the optimization formulation, and demonstrates the proposed methodology through a real-world application. The new moment constraints significantly increase the accuracy of the plume interpolated from the sampled data relative to the plume simulated by the transport model. The plume interpolation approaches employed in this study are ordinary kriging (OK) and inverse distance weighting (IDW). The proposed methodology is applied to the monitoring of plume evolution during a pump-and-treat operation at a large field site. It is shown that potential cost savings up to 65.6% may be achieved without any significant loss of accuracy in mass and moment estimations. The IDW-based interpolation method is computationally more efficient than the OK-based method and results in more potential cost savings. However, the OK-based method leads to more accurate mass and moment estimations. A comparison of the sampling designs obtained with and without the moment constraints points to their importance in ensuring a robust long-term monitoring design that is both cost-effective and accurate in mass and moment estimations. Additional analysis demonstrates the sensitivity of the optimal sampling design to the various coefficients included in the

  15. Monitoring the Heliospheric Conditions at Mars Using MSL/RAD Measurements

    NASA Astrophysics Data System (ADS)

    Guo, J.; Wimmer-Schweingruber, R. F.; Zeitlin, C. J.; Rafkin, S. C.; Hassler, D.; Posner, A.

    2015-12-01

    The Radiation Assessment Detector (RAD), on board Mars Science Laboratory's (MSL) rover Curiosity, measures the radiation dose rate as well as the energy spectra of energetic charged and neutral particles at the surface of Mars. With these first-ever measurements of GCR fluxes on the Martian surface, RAD can be used as a monitor for heliospheric modulation at Mars location, similar to neutron monitors at Earth. We do this by first correlating the GCR dose rate measurements at Mars and solar modulations at Earth when there is a good magnetic connection between the two planets. With the thus obtained correlation we obtain an empirical function for the dependence of the modulation parameter at Mars on RAD dose rate. This function can in turn help to calibrate the heliospheric modulation at Mars throughout the MSL/RAD mission period. The resulting solar modulation at Mars and at Earth over three years (>1000 sols) is then compared. In order to verify our 'prediction' method, we use the local modulation parameter at Mars as an input for Badhwar O'Neil model providing the primary spectra for PLANETOCOSMIC simulations which eventually model the surface particle spectra that can be compared with RAD measurements of the spectra.

  16. Internet-based monitoring and prediction system of coal stockpile behaviors under atmospheric conditions.

    PubMed

    Yilmaz, Nihat; Ozdeniz, A Hadi

    2010-03-01

    Spontaneous combustion on industrial-scale stockpiles causes environmental problems and economic losses for the companies consuming large amounts of coal. In this study, an effective monitoring and prediction system based on internet was developed and implemented to prevent losses and environmental problems. The system was performed in a coal stockpile with 5 m width, 10 m length, 3 m height, and having 120 t of weight. The inner temperature data of the stockpile was recorded by 17 temperature sensors placed inside the stockpile at certain points. Additionally, the data relating to the air temperature, air humidity, atmospheric pressure, wind velocity, and wind direction that are the parameters affecting the coal stockpile were also recorded. The recorded values were analyzed with artificial neural network and Statistical modeling methods for prediction of spontaneous combustion. Real-time measurement values and model outputs were published with a web page on internet. The internet-based system can also provide real-time monitoring (combustion alarms, system status) and tele-controlling (Parameter adjusting, system control) through internet exclusively with a standard web browser without the need of any additional software. PMID:19238568

  17. An investigation of the orthogonal outputs from an on-rotor MEMS accelerometer for reciprocating compressor condition monitoring

    NASA Astrophysics Data System (ADS)

    Feng, G.; Hu, N.; Mones, Z.; Gu, F.; Ball, A. D.

    2016-08-01

    With rapid development in electronics and microelectromechanical systems (MEMS) technology, it becomes possible and attractive to monitor rotor dynamics by directly installing MEMS accelerometers on rotors. This paper studies the mathematical modelling of the orthogonal outputs from an on-rotor MEMS accelerometer and proposes a method to eliminate the gravitational acceleration projected on the measurement axes. This is achieved by shifting the output in the normal direction by π / 2 using a Hilbert transform and then combining it with the output of the tangential direction. With further compensation of the combined signal in the frequency domain, the tangential acceleration of the rotor is reconstructed to a high degree of accuracy. Experimental results show that the crankshaft tangential acceleration of a reciprocating compressor, obtained by the proposed method, can discriminate clearly between different discharge pressures and hence can allow common leakage faults to be detected, located and diagnosed for online condition monitoring purposes.

  18. Monitoring a 5 MW offshore wind energy converter—Condition parameters and triangulation based extraction of modal parameters

    NASA Astrophysics Data System (ADS)

    Häckell, Moritz W.; Rolfes, Raimund

    2013-10-01

    The test field alpha ventus is the first operating German offshore parks for wind energy. Twelve Wind Energy Converters (WECs) of the 5 MW-class are installed, both, for commercial and research reasons. Due to upcoming mass production and uncertainties in loads and behaviour, monitoring the foundation of these structures was desired. Two goals addressed are the extraction of modal parameters for model validation and the estimation of condition parameters to allow a hypothesis of the system's state. In a first step the largedatabase is classified by Environmental and Operational Conditions (EOCs) through affinity propagation which is a new approach for Structural Health Monitoring (SHM) on wind turbines. Further, system identification through data driven stochastic subspace identification (SSI) is performed. A new, automated approach called triangulation-based extraction of modal parapeters (TEMP), using stability diagrams, is a key focus of the presented research. Finally, extraction of condition parameters for tower accelerations classified by EOCs, based on covariance driven SSI and Vector Auto-Regressive (VAR) Models, is performed for several observation periods from one to 16 weeks. These parameters and their distributions provide a base line for long term observations.

  19. Investigation of Techniques to Improve Continuous Air Monitors Under Conditions of High Dust Loading in Environmental Settings

    SciTech Connect

    Suilou Huang; Stephen D. Schery; John C. Rodgers

    2002-07-23

    A number of DOE facilities, such as the Los Alamos National Laboratory (LANL) and the Waste Isolation Pilot Plant (WIPP), use alpha-particle environmental continuous air monitors (ECAMs) to monitor air for unwanted releases of radioactive aerosols containing such materials as plutonium and uranium. High sensitivity, ease of operation, and lack of false alarms are all important for ECAMs. The object of the project was to conduct investigations to improve operation of ECAMs, particularly under conditions where a lot of nonradioactive dust may be deposited on the filters (conditions of high dust loading). The presence of such dust may increase the frequency with which filters must be changed and can lead to an increased incidence of false alarms due to deteriorated energy resolution and response specificity to the radionuclides of interest. A major finding of the investigation, not previously documented, was that under many conditions thick layers of underlying nonradioactive dust do not decrease energy resolution and specificity for target radionuclides if the radioactive aerosol arrives as a sudden thin burst deposit, as commonly occurs in the early-warning alarm mode. As a result, operators of ECAMs may not need to change filters as often as previously thought and have data upon which to base more reliable operating procedures.

  20. A low-level activation technique for monitoring thermonuclear fusion plasma conditions.

    PubMed

    Gasparro, Joël; Hult, Mikael; Bonheure, Georges; Johnston, Peter N

    2006-01-01

    Optimisation of the confinement and sustainability of a thermonuclear plasma requires methods to monitor processes in the plasma. In this work three materials were used as activation targets (Ti, MgF2 and a TiVAl compound). They were placed inside the joint European Torus (JET) vacuum chamber. Certain gamma-ray emitting radionuclides (7Be, 54Mn, 56Co, 57Co, 58Co and 46Sc) were measured using ultra low-level gamma-ray spectrometry in an underground laboratory 1-2 months after activation. They were found to arise from neutron activation of bulk sample material and surface contaminants sputtered from other Tokamak parts. Decision thresholds for some activation products were determined in order to aid in giving upper bounds for the flux of charged particles. PMID:16580838

  1. Thermal monitoring of transport infrastructures by infrared thermography coupled with inline local atmospheric conditions survey

    NASA Astrophysics Data System (ADS)

    Dumoulin, J.

    2013-09-01

    An infrared system architecture (software and hardware) has been studied and developed to allow long term monitoring of transport infrastructures in a standalone configuration. It is based on the implementation of low cost infrared thermal cameras (equipped with uncooled microbolometer focal plane array) available on the market coupled with other measurement systems. All data collected feed simplified radiative models running on GPU available on small PC to produce corrected thermal map of the surveyed structure at selected time step. Furthermore, added Web-enabled capabilities of this new infrared measurement system are also presented and discussed. A prototype of this system was tested and evaluated on real infrastructure opened to traffic. Results obtained by image and signal processing are presented. Finally, conclusions and perspectives for new implementation and new functionalities are presented and discussed.

  2. Noninvasive Oxygen Monitoring in Three-Dimensional Tissue Cultures Under Static and Dynamic Culture Conditions

    PubMed Central

    Weyand, Birgit; Nöhre, Mariel; Schmälzlin, Elmar; Stolz, Marvin; Israelowitz, Meir; Gille, Christoph; von Schroeder, Herb P.; Reimers, Kerstin; Vogt, Peter M.

    2015-01-01

    Abstract We present a new method for noninvasive real-time oxygen measurement inside three-dimensional tissue-engineered cell constructs in static and dynamic culture settings in a laminar flow bioreactor. The OPAL system (optical oxygen measurement system) determines the oxygen-dependent phosphorescence lifetime of spherical microprobes and uses a two-frequency phase-modulation technique, which fades out the interference of background fluorescence from the cell carrier and culture medium. Higher cell densities in the centrum of the scaffolds correlated with lower values of oxygen concentration obtained with the OPAL system. When scaffolds were placed in the bioreactor, higher oxygen values were measured compared to statically cultured scaffolds in a Petri dish, which were significantly different at day 1–3 of culture. This technique allows the use of signal-weak microprobes in biological environments and monitors the culture process inside a bioreactor. PMID:26309802

  3. Pasture monitoring at a farm scale with the USDA-NRCS pasture condition score system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Pasture Condition Score (PCS) system, developed by the USDA-Natural Resources Conservation Service (NRCS), is an assessment tool for pastureland enrolled in conservation programs. Ten indicators of vegetation and soils status are rated on a 1 to 5 scale and summed to give an aggregate score, whi...

  4. Assessing the Ecological Condition of Streams in a Southeastern Brazilian Basin using a Probabilistic Monitoring Design

    EPA Science Inventory

    Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodi...

  5. Building Partnerships to Monitor the Conditions of Streams and Rivers on Public Lands

    EPA Science Inventory

    The Bureau of Land Management (BLM), in collaboration with the U.S. Environmental Protection Agency (EPA), will conduct its first Western Rivers and Streams Assessment (WRSA), a survey of the condition of BLM streams and rivers throughout the contiguous western U.S. The objective...

  6. SELECTING THE DEVELOPING INDICATORS FOR MONITORING CONDITION: THE NATION COASTAL ASSESSMENT EXPERIENCE

    EPA Science Inventory

    The purpose of the National Coastal Assessment (NCA) is to estimate the status and trends of the condition of the nation's coastal resources on a state, regional and national basis. From 1999-2003, 100% of the nation's estuarine waters (at over 4500 locations) were representative...

  7. Engine condition monitoring: CF6 family 60's through the 80's

    NASA Technical Reports Server (NTRS)

    Kent, H. J.; Dienger, G.

    1981-01-01

    The on condition program is described in terms of its effectiveness as a maintenance tool both at the line station as well as at home base by the early detection of engine faults, erroneous instrumentation signals and by verification of engine health. The system encompasses all known methods from manual procedures to the fully automated airborne integrated data system.

  8. Aero/aeroderivative engines - Internal transducers offer potential for enhanced condition monitoring and vibration diagnostics

    NASA Astrophysics Data System (ADS)

    Werner, Malcolm J.

    1990-06-01

    Gas turbine aero engines and their ground based derivatives can benefit greatly from the enhanced condition and diagnostic data available from internal vibration transducers. This paper discusses transducer selection, illustrates typical transducer locations and mounting, and describes some of the rotor malfunctions that can be diagnosed from the vibrations data.

  9. THE USE OF MICROBIAL INDICATORS FOR MONITORING STREAM SANITARY AND ECOLOGICAL CONDITION

    EPA Science Inventory

    We measured traditional public health indicators of sanitary condition, including heterotrophic plate counts, total coliforms, fecal coliforms, and E. coli using membrane filtration from several sites in the John Day watershed of eastern Oregon and from Oak Creek and Thomas Creek...

  10. Monitoring of Microbial Metabolites and Bacterial Diversity in Beef Stored under Different Packaging Conditions ▿ †

    PubMed Central

    Ercolini, Danilo; Ferrocino, Ilario; Nasi, Antonella; Ndagijimana, Maurice; Vernocchi, Pamela; La Storia, Antonietta; Laghi, Luca; Mauriello, Gianluigi; Guerzoni, M. Elisabetta; Villani, Francesco

    2011-01-01

    Beef chops were stored at 4°C under different conditions: in air (A), modified-atmosphere packaging (MAP), vacuum packaging (V), or bacteriocin-activated antimicrobial packaging (AV). After 0 to 45 days of storage, analyses were performed to determine loads of spoilage microorganisms, microbial metabolites (by solid-phase microextraction [SPME]-gas chromatography [GC]-mass spectrometry [MS] and proton nuclear magnetic resonance [1H NMR]), and microbial diversity (by PCR–denaturing gradient gel electrophoresis [DGGE] and pyrosequencing). The microbiological shelf life of meat increased with increasing selectivity of storage conditions. Culture-independent analysis by pyrosequencing of DNA extracted directly from meat showed that Brochothrix thermosphacta dominated during the early stages of storage in A and MAP, while Pseudomonas spp. took over during further storage in A. Many different bacteria, several of which are usually associated with soil rather than meat, were identified in V and AV; however, lactic acid bacteria (LAB) dominated during the late phases of storage, and Carnobacterium divergens was the most frequent microorganism in AV. Among the volatile metabolites, butanoic acid was associated with the growth of LAB under V and AV storage conditions, while acetoin was related to the other spoilage microbial groups and storage conditions. 1H NMR analysis showed that storage in air was associated with decreases in lactate, glycogen, IMP, and ADP levels and with selective increases in levels of 3-methylindole, betaine, creatine, and other amino acids. The meat microbiota is significantly affected by storage conditions, and its changes during storage determine complex shifts in the metabolites produced, with a potential impact on meat quality. PMID:21803905

  11. 1-3 connectivity composite material made from lithium niobate and cement for ultrasonic condition monitoring at elevated temperatures.

    PubMed

    Shepherd, G; Cochran, A; Kirk, K J; McNab, A

    2002-05-01

    We have designed, manufactured and tested a piezoelectric composite material to operate at temperatures above 400 degrees C. The material is a 1-3 connectivity composite with pillars of Z-cut lithium niobate in a matrix of alumina cement. The composite material produced shorter pulses than a monolithic plate of lithium niobate and remained intact upon cooling. Results are presented from room temperature and high temperature testing. This material could be bonded permanently to a test object, making it possible to carry out condition monitoring over an extended period. A new excitation method was also developed to enable remote switching between array elements. PMID:12159936

  12. Conditioned quantum motion of an atom in a continuously monitored one-dimensional lattice

    NASA Astrophysics Data System (ADS)

    Blattmann, Ralf; Mølmer, Klaus

    2016-05-01

    We consider a quantum particle on a one-dimensional lattice subject to weak local measurements and study its stochastic dynamics conditioned on the measurement outcomes. Depending on the measurement strength our analysis of the quantum trajectories reveals dynamical regimes ranging from quasicoherent wave-packet oscillations to a Zeno-type dynamics. We analyze how these dynamical regimes are directly reflected in the spectral properties of the noisy measurement records.

  13. Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation

    PubMed Central

    Kilpatrick, Adam D.; Lewis, Megan M.; Ostendorf, Bertram

    2015-01-01

    A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672km2 area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural spatio

  14. Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.

    PubMed

    Kilpatrick, Adam D; Lewis, Megan M; Ostendorf, Bertram

    2015-01-01

    A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2) area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural

  15. Can faecal glucocorticoid metabolites be used to monitor body condition in wild Upland geese Chloephaga picta leucoptera?

    PubMed

    Gladbach, Anja; Gladbach, David Joachim; Koch, Martina; Kuchar, Alexandra; Möstl, Erich; Quillfeldt, Petra

    2011-07-01

    The measurement of faecal glucocorticoid metabolites is used as a non-invasive technique to study stress in animal populations. They have been used most widely in mammals, and mammalian studies have also treated issues such as sample stability and storage methods. In birds, faecal corticosterone metabolite (CM) assays have been validated for a small number of species, and adequate storage under field conditions has not been addressed explicitly in previous studies. Furthermore, while it is well-established that baseline plasma corticosterone levels in birds rise with declining body condition, no study so far investigated if this relationship is also reflected in faecal samples. We here present data of a field study in wild Upland geese Chloephaga picta leucoptera on the Falkland Islands, testing different storage methods and investigating the relationship of faecal CM concentrations to body condition and reproductive parameters. We found that faecal CM measures are significantly repeatable within individuals, higher in individuals with lower body condition in both male and female wild Upland geese and higher in later breeding females with smaller broods. These results suggest that measuring faecal CM values may be a valuable non-invasive tool to monitor the relative condition or health of individuals and populations, especially in areas where there still is intense hunting practice. PMID:21765584

  16. Multi-functional surface acoustic wave sensor for monitoring enviromental and structural condition

    NASA Astrophysics Data System (ADS)

    Furuya, Y.; Kon, T.; Okazaki, T.; Saigusa, Y.; Nomura, T.

    2006-03-01

    As a first step to develop a health monitoring system with active and embedded nondestructive evaluation devices for the machineries and structures, multi-functional SAW (surface acoustic wave) device was developed. A piezoelectric LiNbO3(x-y cut) materials were used as a SAW substrate on which IDT(20μm pitch) was produced by lithography. On the surface of a path of SAW between IDTs, environmentally active material films of shape memory Ti50Ni41Cu(at%) with non-linear hysteresis and superelastic Ti48Ni43Cu(at%) with linear deformation behavior were formed by magnetron-sputtering technique. In this study, these two kinds of shape memory alloys SMA) system were used to measure 1) loading level, 2) phase transformation and 3)stress-strain hysteresis under cyclic loading by utilizing their linearity and non-linearity deformation behaviors. Temperature and stress dependencies of SAW signal were also investigated in the non-sputtered film state. Signal amplitude and phase change of SAW were chosen to measure as the sensing parameters. As a result, temperature, stress level, phase transformation in SMA depending on temperature and mechanical damage accumulation could be measured by the proposed multi-functional SAW sensor. Moreover, the wireless SAW sensing system which has a unique feature of no supplying electric battery was constructed, and the same characteristic evaluation is confirmed in comparison with wired case.

  17. Web application for detailed real-time database transaction monitoring for CMS condition data

    NASA Astrophysics Data System (ADS)

    de Gruttola, Michele; Di Guida, Salvatore; Innocente, Vincenzo; Pierro, Antonio

    2012-12-01

    In the upcoming LHC era, database have become an essential part for the experiments collecting data from LHC, in order to safely store, and consistently retrieve, a wide amount of data, which are produced by different sources. In the CMS experiment at CERN, all this information is stored in ORACLE databases, allocated in several servers, both inside and outside the CERN network. In this scenario, the task of monitoring different databases is a crucial database administration issue, since different information may be required depending on different users' tasks such as data transfer, inspection, planning and security issues. We present here a web application based on Python web framework and Python modules for data mining purposes. To customize the GUI we record traces of user interactions that are used to build use case models. In addition the application detects errors in database transactions (for example identify any mistake made by user, application failure, unexpected network shutdown or Structured Query Language (SQL) statement error) and provides warning messages from the different users' perspectives. Finally, in order to fullfill the requirements of the CMS experiment community, and to meet the new development in many Web client tools, our application was further developed, and new features were deployed.

  18. Condition Monitoring of a Thermally Aged HTPB/IPDI Elastomer by NMR CP Recovery Times

    SciTech Connect

    ASSINK,ROGER A.; LANG,DAVID; CELINA,MATHIAS C.

    2000-07-24

    A hydroxy-terminated polybutadiene (HTPB)/isophorone diisocyanate (IPDI) elastomer is commonly used as propellant binder material. The thermal degradation of the binder is believed to be an important parameter governing the performance of the propellant. The aging of these binders can be monitored by mechanical property measurements such as modulus or tensile elongation. These techniques, however, are not easily adapted to binder agents that are dispersed throughout a propellant. In this paper the authors investigated solid state NMR relaxation times as a means to predict the mechanical properties of the binder as a function of aging time. {sup 1}H spin-lattice and spin-spin relaxation times were found to be insensitive to the degree of thermal degradation of the elastomer. Apparently these relaxation times depend on localized motions that are only weakly correlated with mechanical properties. A strong correlation was found between the {sup 13}C cross-polarization (CP) NMR time constant, T{sub cp}, and the tensile elongation at break of the elastomer as a function of aging time. A ramped-amplitude CP experiment was shown to be less sensitive to imperfections in setting critical instrumental parameters for this mobile material.

  19. Parameter Sensitivity in Multivariate Methods

    ERIC Educational Resources Information Center

    Green, Bert F., Jr.

    1977-01-01

    Interpretation of multivariate models requires knowing how much the fit of the model is impaired by changes in the parameters. The relation of parameter change to loss of goodness of fit can be called parameter sensitivity. Formulas are presented for assessing the sensitivity of multiple regression and principal component weights. (Author/JKS)

  20. Multivariate Model of Infant Competence.

    ERIC Educational Resources Information Center

    Kierscht, Marcia Selland; Vietze, Peter M.

    This paper describes a multivariate model of early infant competence formulated from variables representing infant-environment transaction including: birthweight, habituation index, personality ratings of infant social orientation and task orientation, ratings of maternal responsiveness to infant distress and social signals, and observational…

  1. A "Model" Multivariable Calculus Course.

    ERIC Educational Resources Information Center

    Beckmann, Charlene E.; Schlicker, Steven J.

    1999-01-01

    Describes a rich, investigative approach to multivariable calculus. Introduces a project in which students construct physical models of surfaces that represent real-life applications of their choice. The models, along with student-selected datasets, serve as vehicles to study most of the concepts of the course from both continuous and discrete…

  2. A radioactive waste transportation package monitoring system for normal transport and accident emergency response conditions

    SciTech Connect

    Brown, G. S.; Cashwell, J. W.; Apple, M. L.

    1991-01-01

    Shipments of radioactive material (RAM) constitute but a small fraction of the total hazardous materials shipped in the United States each year. Public perception, however, of the potential consequences of a release from a transportation package containing RAM has resulted in significant regulation of transport operations, both to ensure the integrity of a package in accident conditions and to place operational constraints on the shipper. Much of this attention has focused on shipments of spent nuclear fuel and high level wastes which, although comprising a very small number of total shipments, constitute a majority of the total curies transported on an annual basis. This report discusses the shipment of these highly radioactive materials.

  3. Real-time condition monitoring of thermal power plants feed-pumps by rolling bearings supports vibration

    NASA Astrophysics Data System (ADS)

    Kostyukov, V. N.; Tarasov, E. V.

    2012-05-01

    The report addresses the real-time condition monitoring of technical state and automatic diagnosis of auxiliary equipment for bearings supports vibration, for example, control of the feed-pump operating modes of thermal power stations. The causes that lead to premature birth and development of defects in rolling bearings are identified and the development of activities ensuring safe and continuous operation of the auxiliary equipment of thermal power stations is carried out. Collection and analysis of vibration parameters of pumping units during their operation at the operating modes of the technological process are realized by means of real-time technical condition monitoring. Spectral analysis of vibration parameters of one of the pumps showed the presence of frequency components, which mark violations in the operating practices of the pump, the imbalance development and, as a consequence, the development of defects in the bearings by long-term operation of the unit. Timely warning of the personnel on the operation of the unit with the "INTOLERABLE" technical state and automatic warning issuance of the need to change the technological process allowed to recover the estimated pump operation mode in due time and prevent further development of defects in equipment.

  4. A Data Filter for Identifying Steady-State Operating Points in Engine Flight Data for Condition Monitoring Applications

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Litt, Jonathan S.

    2010-01-01

    This paper presents an algorithm that automatically identifies and extracts steady-state engine operating points from engine flight data. It calculates the mean and standard deviation of select parameters contained in the incoming flight data stream. If the standard deviation of the data falls below defined constraints, the engine is assumed to be at a steady-state operating point, and the mean measurement data at that point are archived for subsequent condition monitoring purposes. The fundamental design of the steady-state data filter is completely generic and applicable for any dynamic system. Additional domain-specific logic constraints are applied to reduce data outliers and variance within the collected steady-state data. The filter is designed for on-line real-time processing of streaming data as opposed to post-processing of the data in batch mode. Results of applying the steady-state data filter to recorded helicopter engine flight data are shown, demonstrating its utility for engine condition monitoring applications.

  5. The CMS fast beams condition monitor back-end electronics based on MicroTCA technology: status and development

    NASA Astrophysics Data System (ADS)

    Zagozdzinska, Agnieszka A.; Dabrowski, Anne E.; Pozniak, Krzysztof T.

    2015-09-01

    The Fast Beams Condition Monitor (BCM1F), upgraded for LHC Run II, is used to measure the online luminosity and machine induced background for the CMS experiment. The detector consists of 24 single-crystal CVD diamond sensors that are read out with a custom fast front-end chip fabricated in 130 nm CMOS technology. Since the signals from the sensors are used for real time monitoring of the LHC conditions they are processed by dedicated back-end electronics to measure separately rates corresponding to LHC collision products, machine induced background and residual activation exploiting different arrival times. The system is built in MicroTCA technology and uses high speed analog-to-digital converters. In operational modes of high rates, consecutive events, spaced in time by less than 12.5 ns, may cause partially overlapping events. Hence, novel signal processing techniques are deployed to resolve overlapping peaks. The high accuracy qualification of the signals is crucial to determine the luminosity and the machine induced background rates for the CMS experiment and the LHC.

  6. Monitoring of environmental conditions in taiga forests using ERS-1 SAR

    SciTech Connect

    Rignot, E.; Way, J.B.; McDonald, K. ); Viereck, L.; Williams, C.; Adams, P.; Payne, C.; Wood, W. ); Shi, J. )

    1994-08-01

    Synthetic-aperture radar images of forest site near Manley Hot Springs (64[degree]N, 151[degree]W), Alaska, were collected between August 1991 and December 1991, day and night, every 3 days, at C-band frequency ([lambda] = 5.7 cm), vertical receive and transmit polarization, by the European Space Agency First Remote Sensing Satellite, ERS-1. During the same period, air and soil temperatures and dielectric and gravimetric moisture properties of the forest canopy and forest floor were monitored in three forest stands dominated, respectively, by black spruce (Picea mariana), white spruce (Picea glauca), and balsam poplar (Populus balsamifera). The calibrated ERS-1 radar backscatter values, [sigma][degree], of the forest stands are shown to exhibit a pronounced temporal pattern, with little separability between tree species. The largest change in [sigma][degree], a 3-dB decrease almost independent of tree species, is observed in early winter when the soil and vegetation freeze. In the summer, temporal fluctuations in [sigma][degree] are about 1--2 dB in magnitude, depending on tree species. Diurnal variations in [sigma][degree] are as large as 2 dB during fall freeze-up, and less than 1 dB in summer and winter. These temporal variations in radar backscatter from the forest are interpreted using the MIMICS radar backscatter model and the in situ surface observations as due to changes in the dielectric properties of the forest floor and forest canopy induced by precipitation (summer), drought (fall), and freezing (fall-winter) events. In winter, [sigma][degree] increases across the entire landscape, probably because of volume scattering from large depth hoar ice crystals forming in the snow pack.

  7. ANN based Performance Evaluation of BDI for Condition Monitoring of Induction Motor Bearings

    NASA Astrophysics Data System (ADS)

    Patel, Raj Kumar; Giri, V. K.

    2016-07-01

    One of the critical parts in rotating machines is bearings and most of the failure arises from the defective bearings. Bearing failure leads to failure of a machine and the unpredicted productivity loss in the performance. Therefore, bearing fault detection and prognosis is an integral part of the preventive maintenance procedures. In this paper vibration signal for four conditions of a deep groove ball bearing; normal (N), inner race defect (IRD), ball defect (BD) and outer race defect (ORD) were acquired from a customized bearing test rig, under four different conditions and three different fault sizes. Two approaches have been opted for statistical feature extraction from the vibration signal. In the first approach, raw signal is used for statistical feature extraction and in the second approach statistical features extracted are based on bearing damage index (BDI). The proposed BDI technique uses wavelet packet node energy coefficients analysis method. Both the features are used as inputs to an ANN classifier to evaluate its performance. A comparison of ANN performance is made based on raw vibration data and data chosen by using BDI. The ANN performance has been found to be fairly higher when BDI based signals were used as inputs to the classifier.

  8. Diagnostic approach for monitoring hydroclimatic conditions related to emergence of west nile virus in west virginia.

    PubMed

    Jutla, Antarpreet; Huq, Anwar; Colwell, Rita R

    2015-01-01

    West Nile virus (WNV), mosquito-borne and water-based disease, is increasingly a global threat to public health. Since its appearance in the northeastern United States in 1999, WNV has since been reported in several states in the continental United States. The objective of this study is to highlight role of hydroclimatic processes estimated through satellite sensors in capturing conditions for emergence of the vectors in historically disease free regions. We tested the hypothesis that an increase in surface temperature, in combination with intensification of vegetation, and enhanced precipitation, lead to conditions favorable for vector (mosquito) growth. Analysis of land surface temperature (LST) pattern shows that temperature values >16°C, with heavy precipitation, may lead to abundance of the mosquito population. This hypothesis was tested in West Virginia where a sudden epidemic of WNV infection was reported in 2012. Our results emphasize the value of hydroclimatic processes estimated by satellite remote sensing, as well as continued environmental surveillance of mosquitoes, because when a vector-borne infection like WNV is discovered in contiguous regions, the risk of spread of WNV mosquitoes increase at points where appropriate hydroclimatic processes intersect with the vector niche. PMID:25729746

  9. Multifunctional ultrasonic sensor for on-line tool condition monitoring in turning operations

    SciTech Connect

    Nayfeh, T.H.; Abu-Zahra, N.H.

    1998-03-01

    Machining operations in automated manufacturing centers are, in general, under-performing by 20--80 percent. Optimizing these machining operations requires on-line knowledge of the cutting tool`s condition and the process state. Currently, this information is either not reliable or not available in a timely manner. This in part is due to the lack of suitable sensors which are able to measure on-line directly and accurately one or more of the relevant tool and process variables. A direct, active, ultrasonic method for on-line sensing of the tool condition and the process state in turning operations was developed in this work. Sensing is achieved by using an ultrasonic transducer operating at 10 MHz in a pulse-echo mode to send pulses through the cutting tool. The amplitude and propagation time of the reflected pulses are modulated by the tool nose, flank, temperature, and by the material in contact with the tools. This method has the potential to measure on-line several relevant process and cutting tool parameters directly and accurately through the use of a single sensor. These parameters are tool-workpiece contact, tool gradual wear, tool chipping and tool chatter.

  10. CargoCBM - Feature Generation and Classification for a Condition Monitoring System for Freight Wagons

    NASA Astrophysics Data System (ADS)

    Gericke, C.; Hecht, M.

    2012-05-01

    Despite the fact that rail freight transport is one of the most environmentally friendly matters of transport, its growth has been far behind the growth of freight transport in general. Studies showed that a competitive disadvantage is caused by a low availability of rolling stock, especially freight wagons. Changing from a time based to a condition based maintenance strategy is believed to decrease down times by at least one third. To make condition based maintenance for freight wagons possible the TU Berlin and five industry partners started the research project CargoCBM. One task in this project is to develop algorithms for the automatic on-board diagnosis of wheel flats. The focus of the work is on the process of feature generation and feature selection as well as the application of different classifiers to automatically evaluate the data. Based on the results of measured data, features were selected and tested with different classifiers. Thought advanced classifiers such as neural networks have been analysed in accordance to their classification accuracy. It can be shown that with carefully constructed and selected features comparatively simple classifiers can lead to excellent results.

  11. A spectroscopy-based detector to monitor tomato growth condition in greenhouse

    NASA Astrophysics Data System (ADS)

    Yang, Ce; Li, Minzan; Cui, Di

    2008-12-01

    A spectroscopy-based detector is developed to measure the nitrogen and chlorophyll content of tomato leaves and then to predict the growth condition of tomato plants in greenhouse. The detector uses two wavebands, 527 nm and 762 nm, since it is proved that these wavebands are sensitive to nitrogen and chlorophyll content in plant leaves by previous field test. The detector contains: A Y-type optic fiber, two silicon photocells, a signal processing unit, and a MCU. Light reflection from tomato leaves is transmitted by the Y-type optic fiber to the surface of the silicon photo cells, which transfer optical signal into electrical signal. Then the analog signal is amplified to conform to the TTL level signal standard and finally converted to digital signal by MAX186. After that, the MCU carries on a series of actions, including data calculating, displaying and storage. Using the measured data, the Normalized Difference Vegetation Index (NDVI) is calculated to estimate the nitrogen and chlorophyll content in plant leaves. The result is directly displayed on an LCD screen. Users have an option in saving data, either into a USB-memory stick or into a database over the PC serial port. The detector is portable, inexpensive, and convenient, which make it meet farmers' need in China. The performance test shows that the growth model works very well, and the device has high accuracy in predicting the growth condition of tomato plants in greenhouse.

  12. Diagnostic Approach for Monitoring Hydroclimatic Conditions Related to Emergence of West Nile Virus in West Virginia

    PubMed Central

    Jutla, Antarpreet; Huq, Anwar; Colwell, Rita R.

    2015-01-01

    West Nile virus (WNV), mosquito-borne and water-based disease, is increasingly a global threat to public health. Since its appearance in the northeastern United States in 1999, WNV has since been reported in several states in the continental United States. The objective of this study is to highlight role of hydroclimatic processes estimated through satellite sensors in capturing conditions for emergence of the vectors in historically disease free regions. We tested the hypothesis that an increase in surface temperature, in combination with intensification of vegetation, and enhanced precipitation, lead to conditions favorable for vector (mosquito) growth. Analysis of land surface temperature (LST) pattern shows that temperature values >16°C, with heavy precipitation, may lead to abundance of the mosquito population. This hypothesis was tested in West Virginia where a sudden epidemic of WNV infection was reported in 2012. Our results emphasize the value of hydroclimatic processes estimated by satellite remote sensing, as well as continued environmental surveillance of mosquitoes, because when a vector-borne infection like WNV is discovered in contiguous regions, the risk of spread of WNV mosquitoes increase at points where appropriate hydroclimatic processes intersect with the vector niche. PMID:25729746

  13. Fast Multivariate Search on Large Aviation Datasets

    NASA Technical Reports Server (NTRS)

    Bhaduri, Kanishka; Zhu, Qiang; Oza, Nikunj C.; Srivastava, Ashok N.

    2010-01-01

    Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which can contain up to several gigabytes of data. Surprisingly, research on MTS search is very limited. Most existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two provably correct algorithms to solve this problem (1) an R-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences, and (2) a List Based Search (LBS) algorithm which uses sorted lists for indexing. We demonstrate the performance of these algorithms using two large MTS databases from the aviation domain, each containing several millions of observations Both these tests show that our algorithms have very high prune rates (>95%) thus needing actual

  14. Integrated monitoring of hydrogeomorphic, vegetative, and edaphic conditions in riparian ecosystems of Great Basin National Park, Nevada

    USGS Publications Warehouse

    Beever, Erik A.; Pyke, D.A.

    2004-01-01

    In contrast to the more incised riparian channels of central Nevada, we observed knickzones, downcutting, and incision only rarely and usually with limited extent in the walking surveys. Downcutting occurred most frequently and extensively in Strawberry and Snake creeks, due in part to their more erodible soils. According to a hydrogeomorphologist with extensive experience in Great Basin riparian systems, the sediment-delivery and hydrologic systems appeared relatively undisturbed in most reaches, with respect to grazing animals and other types of anthropogenic alteration. Site elevation of the 31 transects ranged from 1,950-2,987 m, and stream slope (i.e., gradient) was relatively steep (mean = 9.3%, range 3-16%). Strawberry Creek averaged the lowest maximum water depth, and correspondingly had greatest width/depth ratios. Baker Creek sites averaged the smallest amount of tree-canopy gaps, whereas Snake Creek sites on average had the largest proportion of gaps in understory vegetation. Sites in terrace-bound valley types averaged the lowest slope in the channel as well as the least cover of trees, litter, and vegetation overall, whereas alluviated, boulder-bed canyon sites averaged the greatest widths of the active channel. Sites in Lehman Creek averaged nearly twice as much coarse woody debris as sites from any other creek, whereas Baker Creek sites averaged greatest tree cover (mean = 67%, range 40 – 96%) and species richness (mean = 17.3 species). Multivariate ordinations suggested that sites in leveed outwash valleys and alluvial-fan-influenced valleys had the greatest inter-site heterogeneity in plant composition, whereas sites in incised moraine-filled valleys appeared most homogeneous. Differences among homogeneity of sites within vegetation types were less pronounced, but sites dominated by either aspen and Woodsʼ rose or narrow-leaved cottonwood had the most similar plant communities among sites of the same vegetation type. A number of species were

  15. Methods for improved forewarning of condition changes in monitoring physical processes

    DOEpatents

    Hively, Lee M.

    2013-04-09

    This invention teaches further improvements in methods for forewarning of critical events via phase-space dissimilarity analysis of data from biomedical equipment, mechanical devices, and other physical processes. One improvement involves objective determination of a forewarning threshold (U.sub.FW), together with a failure-onset threshold (U.sub.FAIL) corresponding to a normalized value of a composite measure (C) of dissimilarity; and providing a visual or audible indication to a human observer of failure forewarning and/or failure onset. Another improvement relates to symbolization of the data according the binary numbers representing the slope between adjacent data points. Another improvement relates to adding measures of dissimilarity based on state-to-state dynamical changes of the system. And still another improvement relates to using a Shannon entropy as the measure of condition change in lieu of a connected or unconnected phase space.

  16. Monitoring and ANN modeling of coal stockpile behavior under different atmospheric conditions

    SciTech Connect

    Ozdeniz, A.H.; Ozbay, Y.; Yilmaz, N.; Sensogut, C.

    2008-07-01

    In this study, an industrial-sized stockpile of 5 m width, 4 m height, and 10 m length was built in a coal stock area to investigate coal stockpile behavior under different atmospheric conditions. The effective parameters on the coal stockpile that were time, weather temperature, atmospheric pressure, air humidity, velocity, and direction of wind values were automatically measured by means of a computer-aided measurement system to obtain Artificial Neural Network (ANN) input data. The coal stockpiles, which should be continuously observed, are capable of spontaneous combustion and then causing serious economical losses due to the mentioned parameters. Afterwards, these measurement values were used for training and testing of the ANN model. Comparison of the experimental and ANN results, accuracy rates of training, and testing were found as 98.6% and 98.7%, respectively. It is shown that possible coal stockpile behavior with this ANN model is powerfully estimated.

  17. Elastic wave velocity and acoustic emission monitoring during Gypsum dehydration under triaxial stress conditions

    NASA Astrophysics Data System (ADS)

    Brantut, N.; David, E. C.; Héripré, E.; Schubnel, A. J.; Zimmerman, R. W.; Gueguen, Y.

    2010-12-01

    Dehydration experiments were performed on natural Gypsum polycrystal samples coming from Volterra, Italy in order to study contemporaneously the evolution of P and S elastic wave velocities and acoustic emission (AE) triggering. During these experiments, temperature was slowly raised at 0.15 degrees C per minute under constant stress conditions. Two experiments were realized under quasi-hydrostatic stress (15 and 55 MPa respectively). The third experiment was realized under constant triaxial stress (σ3=45MPa, σ1=75MPa). All three were drained (10MPa constant pore pressure). In each experiments, both P and S wave velocities reduced drastically (as much as approx. 50% in the low confining pressure case) at the onset of dehydration. Importantly, the Vp/Vs ratio also decreased. Shortly after the onset of decrease in P and S wave velocities, the dehydration reaction was also accompanied by bursts of AEs. Time serie locations of the AEs show that they initiated from the pore pressure port, ie from where the pore fluid could easily be drained, and then slowly migrated within the sample. In each experiments, the AE rate could be positively correlated to the reaction rate, inferred from pore volumetry. In such a way, the AE rate reached a peak when the reaction was the fastest. Focal mechanism analysis of the largest AEs showed they had a large volumetric component in compaction, confirming that AEs were indeed related to pore closure and/or collapse. In addition, the AE rate also increased with confinement, ie when a larger amount of compaction was observed. Interestingly, when under differential stress conditions, AE focal mechanisms were mainly in shear. Additional dehydration experiments performed within an environmental scanning electron microscope under low vacuum highlight that, in drained conditions at least, the reaction seems to take place in two phases. First, cracks are being opened along cleavage planes within a single gypsum crystal, which allows for the

  18. Modelling and mapping spatio-temporal trends of heavy metal accumulation in moss and natural surface soil monitored 1990-2010 throughout Norway by multivariate generalized linear models and geostatistics

    NASA Astrophysics Data System (ADS)

    Nickel, Stefan; Hertel, Anne; Pesch, Roland; Schröder, Winfried; Steinnes, Eiliv; Uggerud, Hilde Thelle

    2014-12-01

    Objective. This study explores the statistical relations between the accumulation of heavy metals in moss and natural surface soil and potential influencing factors such as atmospheric deposition by use of multivariate regression-kriging and generalized linear models. Based on data collected in 1995, 2000, 2005 and 2010 throughout Norway the statistical correlation of a set of potential predictors (elevation, precipitation, density of different land uses, population density, physical properties of soil) with concentrations of cadmium (Cd), mercury and lead in moss and natural surface soil (response variables), respectively, were evaluated. Spatio-temporal trends were estimated by applying generalized linear models and geostatistics on spatial data covering Norway. The resulting maps were used to investigate to what extent the HM concentrations in moss and natural surface soil are correlated. Results. From a set of ten potential predictor variables the modelled atmospheric deposition showed the highest correlation with heavy metals concentrations in moss and natural surface soil. Density of various land uses in a 5 km radius reveal significant correlations with lead and cadmium concentration in moss and mercury concentration in natural surface soil. Elevation also appeared as a relevant factor for accumulation of lead and mercury in moss and cadmium in natural surface soil respectively. Precipitation was found to be a significant factor for cadmium in moss and mercury in natural surface soil. The integrated use of multivariate generalized linear models and kriging interpolation enabled creating heavy metals maps at a high level of spatial resolution. The spatial patterns of cadmium and lead concentrations in moss and natural surface soil in 1995 and 2005 are similar. The heavy metals concentrations in moss and natural surface soil are correlated significantly with high coefficients for lead, medium for cadmium and moderate for mercury. From 1995 up to 2010 the

  19. The use of check valve performance data to support new concepts (probabilistic risk assessment, condition monitoring) for check valve program

    SciTech Connect

    Hart, K.A.; Gower, D.

    1996-12-01

    The concept of developing an integrated check valve database based on the Nuclear Power Reliability Data System (NPRDS) data was presented at the last Symposium. The Nuclear Industry Check Valve Group (NIC), working in cooperation with the Oak Ridge National Laboratory (ORNL), has completed an operational database of check valve performance from 1984 to the present. NIC has committed to the nuclear industry to periodically update the data and maintain this information accessible. As the new concepts of probabilistic risk analysis and condition monitoring are integrated into the American Society of Mechanical Engineers (ASME) Code, a critical element will be performance data. From check valve performance data, feasible failure modes and rates can be established. When a failure rate or frequency of failures can be established based on a significant enough population (sampling), a more solid foundation for focusing resources and determining appropriate frequencies and testing can be determined. The presentation will give the updated status of the NIC Check Valve Performance Database covering (1) methodology used to combine the original ORNL data; (2) process/controls established for continuing update and refinement of the data; (3) discussion of how this data is being utilized by (a) OM-22 for condition monitoring, and (b) risk-based inservice testing work of Westinghouse Owners` Group; and (4) results/trends of data evaluations. At the 1994 Symposium, ORNL provided an update as of 1991 to their original work of 1984 -1990 which they had performed to characterize check valve degradations and failures in the nuclear industry. These characterizations will be updated to 1995 and additional reviews provided to give insight into the current condition and trends of check valve performance.

  20. Characterizing redox conditions and monitoring attenuation of selected pharmaceuticals during artificial recharge through a reactive layer.

    PubMed

    Valhondo, Cristina; Carrera, Jesús; Ayora, Carlos; Tubau, Isabel; Martinez-Landa, Lurdes; Nödler, Karsten; Licha, Tobias

    2015-04-15

    A permeable reactive layer was installed at the floor of an infiltration basin. The reactive layer comprised 1) vegetable compost to provide a sorption surface for neutral organic compounds and to release easily degradable organic matter, thus generating a sequence of redox states, and 2) minor amounts of clay and iron oxide to increase sorption of cationic and anionic species, respectively. Field application of this design was successful in generating denitrification, and manganese-, and iron-reducing conditions beneath the basin. This, together with the increase in types of sorption sites, may explain the improved removal of three of the four selected pharmaceuticals compared with their behavior prior to installation of the layer. After installation of the reactive layer, atenolol concentrations were below the detection limits in the vadose zone. Moreover, concentrations of gemfibrozil and cetirizine were reduced to 20% and 40% of their initial concentrations, respectively, after 200 h of residence time. In contrast, prior to installation of the reactive layer, the concentrations of these three pharmaceuticals in both the vadose zone and the aquifer were more than 60% of the initial concentration. Carbamazepine exhibited recalcitrant behavior both prior to and after the reactive barrier installation. PMID:25625636

  1. Monitoring biological impacts of space shuttle launches from Vandenberg Air Force Base: Establishment of baseline conditions

    NASA Technical Reports Server (NTRS)

    Schmaizer, Paul A.; Hinkle, C. Ross

    1987-01-01

    Space shuttle launches produce environmental impacts resulting from the formation of an exhaust cloud containing hydrogen chloride aerosols and aluminum oxide particulates. Studies have shown that most impacts occur near-field (within 1.5 km) of the launch site while deposition from launches occurs far-field (as distant as 22 km). In order to establish baseline conditions of vegetation and soils in the areas likely to be impacted by shuttle launches from Vandenberg Air Force Base (VAFB), vegetation and soils in the vicinity of Space Launch Complex-6 (SLC-6) were sampled and a vegetation map prepared. The areas likely to be impacted by launches were determined considering the structure of the launch complex, the prevailing winds, the terrain, and predictions of the Rocket Exhaust Effluent Diffusion Model (REEDM). Fifty vegetation transects were established and sampled in March 1986 and resampled in September 1986. A vegetation map was prepared for six Master Planning maps surrounding SLC-6 using LANDSAT Thematic Mapper imagery as well as color and color infrared aerial photography. Soil samples were collected form the 0 to 7.5 cm layer at all transects in the wet season and at a subsample of the transects in the dry season and analyzed for pH, organic matter, conductivity, cation exchange capacity, exchangeable Ca, Mg, Na, K, and Al, available NH3-N, PO4-P, Cu, Fe, Mn, Zn, and TKN.

  2. Monitoring transitory profiles of leachate humic substances in landfill aeration reactors in mesophilic and thermophilic conditions.

    PubMed

    Tong, Huanhuan; Yin, Ke; Ge, Liya; Giannis, Apostolos; Chuan, Valerie W L; Wang, Jing-Yuan

    2015-04-28

    The presence of humic substances (HS) in landfill leachate is of great interest because of their structural stability and potential toxicity. This study examined the effects of temperature and waste age on the transformation of HS during in situ aeration of bioreactor landfills. By establishing aerobic conditions, dissolved organic carbon (DOC) rapidly accumulated in the bioreactor leachate. Fractional analysis showed that the elevated concentration of humic acids (HAs) was primarily responsible for the increment of leachate strength. Further structural characterization indicated that the molecular weight (MW) and aromacity of HS were enhanced by aeration in conjunction with thermophilic temperature. Interestingly, elevation of HAs concentration was not observed in the aeration reactor with a prolonged waste age, as the mobility of HAs was lowered by the high MW derived from extended waste age. Based on these results, aeration may be more favorable in aged landfills, since dissolution of HAs could be minimized by the evolution to larger MW compared to young landfills. Moreover, increased operation temperature during aeration likely offers benefits for the rapid maturation of HS. PMID:25682368

  3. Monitoring Local Strain in a Thermal Barrier Coating System Under Thermal Mechanical Gas Turbine Operating Conditions

    NASA Astrophysics Data System (ADS)

    Manero, Albert; Sofronsky, Stephen; Knipe, Kevin; Meid, Carla; Wischek, Janine; Okasinski, John; Almer, Jonathan; Karlsson, Anette M.; Raghavan, Seetha; Bartsch, Marion

    2015-07-01

    Advances in aircraft and land-based turbine engines have been increasing the extreme loading conditions on traditional engine components and have incited the need for improved performance with the use of protective coatings. These protective coatings shield the load-bearing super alloy blades from the high-temperature combustion gases by creating a thermal gradient over their thickness. This addition extends the life and performance of blades. A more complete understanding of the behavior, failure mechanics, and life expectancy for turbine blades and their coatings is needed to enhance and validate simulation models. As new thermal-barrier-coated materials and deposition methods are developed, strides to effectively test, evaluate, and prepare the technology for industry deployment are of paramount interest. Coupling the experience and expertise of researchers at the University of Central Florida, The German Aerospace Center, and Cleveland State University with the world-class synchrotron x-ray beam at the Advanced Photon Source in Argonne National Laboratory, the synergistic collaboration has yielded previously unseen measurements to look inside the coating layer system for in situ strain measurements during representative service loading. These findings quantify the in situ strain response on multilayer thermal barrier coatings and shed light on the elastic and nonelastic properties of the layers and the role of mechanical load and internal cooling variations on the response. The article discusses the experimental configuration and development of equipment to perform in situ strain measurements on multilayer thin coatings and provides an overview of the achievements thus far.

  4. Monitoring Thermal Performance of Hollow Bricks with Different Cavity Fillers in Difference Climate Conditions

    NASA Astrophysics Data System (ADS)

    Pavlík, Zbyšek; Jerman, Miloš; Fořt, Jan; Černý, Robert

    2015-03-01

    Hollow brick blocks have found widespread use in the building industry during the last decades. The increasing requirements to the thermal insulation properties of building envelopes given by the national standards in Europe led the brick producers to reduce the production of common solid bricks. Brick blocks with more or less complex systems of internal cavities replaced the traditional bricks and became dominant on the building ceramics market. However, contrary to the solid bricks where the thermal conductivity can easily be measured by standard methods, the complex geometry of hollow brick blocks makes the application of common techniques impossible. In this paper, a steady-state technique utilizing a system of two climatic chambers separated by a connecting tunnel for sample positioning is used for the determination of the thermal conductivity, thermal resistance, and thermal transmittance ( U value) of hollow bricks with the cavities filled by air, two different types of mineral wool, polystyrene balls, and foam polyurethane. The particular brick block is provided with the necessary temperature- and heat-flux sensors and thermally insulated in the tunnel. In the climatic chambers, different temperatures are set. After steady-state conditions are established in the measuring system, the effective thermal properties of the brick block are calculated using the measured data. Experimental results show that the best results are achieved with hydrophilic mineral wool as a cavity filler; the worst performance exhibits the brick block with air-filled cavities.

  5. Using the Boundary Conditions of Sunspots as a Technique for Monitoring Solar Luminosity Variations

    NASA Technical Reports Server (NTRS)

    Hoyt, Douglas V.

    1990-01-01

    Recent satellite observations of the solar total irradiance confirm that it is varying at least on the 11 year time scale. Both blocking by sunspots and re-emission by faculae are components in this variation, but changes in the temperature of the solar photosphere may also be a contributing component. The satellite observations are as yet of insufficient length to answer the question of whether the sun is varying in luminosity on time scales longer than the 11 year sunspot cycle. Examined here are proxy methods of re-constructing these longer term luminosity variations, with an examination of secular changes in sunspot structure as one tool. Solar rotation changes and solar diameter changes are other parameters which may reveal information about solar luminosity variations. All three variables give remarkably similar conclusions. Over the last century the Earth's surface temperatures and the structure of sunspots have varied in a parallel manner. It is hypothesized that sunspots have varied in a convective medium which itself is varying over long time periods. These variations in convective strength alter the boundary conditions on sunspots and hence cause their structure to vary. Simultaneous with the variations in convective strength, the solar luminosity will vary as well. This, in turn, leads to changes in the climate of the Earth. Variations in solar diameter and solar rotation support the hypothesis that solar luminosity has varied over the last century and reached a peak around 1925 to 1935. This evidence is reviewed along with a possible model of why sunspot structure may provide a good proxy measure of solar luminosity changes.

  6. Multichannel hierarchical image classification using multivariate copulas

    NASA Astrophysics Data System (ADS)

    Voisin, Aurélie; Krylov, Vladimir A.; Moser, Gabriele; Serpico, Sebastiano B.; Zerubia, Josiane

    2012-03-01

    This paper focuses on the classification of multichannel images. The proposed supervised Bayesian classification method applied to histological (medical) optical images and to remote sensing (optical and synthetic aperture radar) imagery consists of two steps. The first step introduces the joint statistical modeling of the coregistered input images. For each class and each input channel, the class-conditional marginal probability density functions are estimated by finite mixtures of well-chosen parametric families. For optical imagery, the normal distribution is a well-known model. For radar imagery, we have selected generalized gamma, log-normal, Nakagami and Weibull distributions. Next, the multivariate d-dimensional Clayton copula, where d can be interpreted as the number of input channels, is applied to estimate multivariate joint class-conditional statistics. As a second step, we plug the estimated joint probability density functions into a hierarchical Markovian model based on a quadtree structure. Multiscale features are extracted by discrete wavelet transforms, or by using input multiresolution data. To obtain the classification map, we integrate an exact estimator of the marginal posterior mode.

  7. Information extraction from multivariate images

    NASA Technical Reports Server (NTRS)

    Park, S. K.; Kegley, K. A.; Schiess, J. R.

    1986-01-01

    An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

  8. An Attachable Electromagnetic Energy Harvester Driven Wireless Sensing System Demonstrating Milling-Processes and Cutter-Wear/Breakage-Condition Monitoring

    PubMed Central

    Chung, Tien-Kan; Yeh, Po-Chen; Lee, Hao; Lin, Cheng-Mao; Tseng, Chia-Yung; Lo, Wen-Tuan; Wang, Chieh-Min; Wang, Wen-Chin; Tu, Chi-Jen; Tasi, Pei-Yuan; Chang, Jui-Wen

    2016-01-01

    An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies. PMID:26907297

  9. In-situ monitoring of drug release from therapeutic eluting polyelectrolyte multilayers under static and dynamic conditions

    NASA Astrophysics Data System (ADS)

    Tian, Fei; Min, Jouha; Kanka, Jiri; Hammond, Paula T.; Du, Henry

    2015-05-01

    The release profiles of gentamicin sulfate (GS) from [chitosan (CHI)/poly(acrylic acid) (PAA)/GS/PAA]n polyelectrolyte multilayers were investigated in situ using an innovative lab-on-fiber (LOF) optofluidic platform that mimics physiologically relevant fluid flow in a microenvironment. The LOF was constructed by enclosing in a flow-enabled and optically coupled glass capillary a long-period fiber grating both as a substrate for LbL growth of [CHI/PAA/GS/PAA]n and a measurement probe for GS release. We show that the LOF is very robust in monitoring the construction of the [CHI/PAA/GS/PAA]n multilayers at monolayer resolution as well as evaluating the rate of GS release with high sensitivity. The release processes in the LOF under static and a range of dynamic conditions are evaluated, showing a faster release under dynamic condition than that under static condition due to the varying circumstance of GS concentration gradient and the effect of flow-induced shear at the medium-multilayer interface. The LOF platform has the potential to be a powerful test bed to facilitate the design and evaluation of drug-eluting polyelectrolyte thin films for their clinical insertion as part of patient care strategy.

  10. An Attachable Electromagnetic Energy Harvester Driven Wireless Sensing System Demonstrating Milling-Processes and Cutter-Wear/Breakage-Condition Monitoring.

    PubMed

    Chung, Tien-Kan; Yeh, Po-Chen; Lee, Hao; Lin, Cheng-Mao; Tseng, Chia-Yung; Lo, Wen-Tuan; Wang, Chieh-Min; Wang, Wen-Chin; Tu, Chi-Jen; Tasi, Pei-Yuan; Chang, Jui-Wen

    2016-01-01

    An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies. PMID:26907297

  11. Real-Time Optical Monitoring of Flow Kinetics and Gas Phase Reactions Under High-Pressure OMCVD Conditions

    NASA Technical Reports Server (NTRS)

    Dietz, N.; McCall, S.; Bachmann, K. J.

    2001-01-01

    This contribution addresses the real-time optical characterization of gas flow and gas phase reactions as they play a crucial role for chemical vapor phase depositions utilizing elevated and high pressure chemical vapor deposition (HPCVD) conditions. The objectives of these experiments are to validate on the basis of results on real-time optical diagnostics process models simulation codes, and provide input parameter sets needed for analysis and control of chemical vapor deposition at elevated pressures. Access to microgravity is required to retain high pressure conditions of laminar flow, which is essential for successful acquisition and interpretation of the optical data. In this contribution, we describe the design and construction of the HPCVD system, which include access ports for various optical methods of real-time process monitoring and to analyze the initial stages of heteroepitaxy and steady-state growth in the different pressure ranges. To analyze the onset of turbulence, provisions are made for implementation of experimental methods for in-situ characterization of the nature of flow. This knowledge will be the basis for the design definition of experiments under microgravity, where gas flow conditions, gas phase and surface chemistry, might be analyzed by remote controlled real-time diagnostics tools, developed in this research project.

  12. Robust Vehicle Detection under Various Environmental Conditions Using an Infrared Thermal Camera and Its Application to Road Traffic Flow Monitoring

    PubMed Central

    Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

    2013-01-01

    We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as “our previous method”) using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as “our new method”). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal. PMID:23774988

  13. Health monitoring of Japanese payload specialist: Autonomic nervous and cardiovascular responses under reduced gravity condition (L-0)

    NASA Technical Reports Server (NTRS)

    Sekiguchi, Chiharu

    1993-01-01

    In addition to health monitoring of the Japanese Payload Specialists (PS) during the flight, this investigation also focuses on the changes of cardiovascular hemodynamics during flight which will be conducted under the science collaboration with the Lower Body Negative Pressure (LBNP) Experiment of NASA. For the Japanese, this is an opportunity to examine firsthand the effects of microgravity of human physiology. We are particularly interested in the adaption process and how it relates to space motion sickness and cardiovascular deconditioning. By comparing data from our own experiment to data collected by others, we hope to understand the processes involved and find ways to avoid these problems for future Japanese astronauts onboard Space Station Freedom and other Japanese space ventures. The primary objective of this experiment is to monitor the health condition of Japanese Payload Specialists to maintain a good health status during and after space flight. The second purpose is to investigate the autonomic nervous system's response to space motion sickness. To achieve this, the function of the autonomic nervous system will be monitored using non-invasive techniques. Data obtained will be employed to evaluate the role of autonomic nervous system in space motion sickness and to predict susceptibility to space motion sickness. The third objective is evaluation of the adaption process of the cardiovascular system to microgravity. By observation of the hemodynamics using an echocardiogram we will gain insight on cardiovascular deconditioning. The last objective is to create a data base for use in the health care of Japanese astronauts by obtaining control data in experiment L-O in the SL-J mission.

  14. Monitoring Inland Ice Cover under All-weather Conditions with the Combined Use of Microwave and GOES-R Observations

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Key, J. R.; Wang, X.

    2010-12-01

    The cryosphere exists at all latitudes and in about one hundred countries. Not only does the cryosphere play a significant role in climate, but also it has profound socio-economic value, especially over inland water, including lakes and rivers, due to its role in water resources and its impact on transportation, fisheries, hunting, herding, and agriculture. A number of ice characterization algorithms have been improved and/or developed for the next generation Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager (ABI), including ice identification, ice concentration, ice thickness and age, and ice motion. These products will play an important role in monitoring ice cover over inland water considering its high spatial, temporal, and spectral resolution. However, the effectiveness of such products is constrained by cloud cover. Lake ice products from microwave observations are less affected by clouds, but their quality is hindered by coarse spatial and temporal resolution as well as contamination by the land surface. Optimization of all-weather ice products from microwave observations, and ice products with higher spatial and temporal resolutions from GOES-R enables us to monitor the ice characteristics over the inland water surfaces, e.g., the Great Lakes, effectively in real time under all-weather conditions, and improves the products that are being developed for ABI. The combined used of both products provides accurate, timely information on ice characteristics over inland water surfaces to meet the needs of transportation and winter weather forecasting. An overview of the ice cover, concentration, and motion products for both GOES-R and microwave observation will be given, and case studies of combining both products for monitoring ice characteristics over inland water will be presented.

  15. Risk Assessment and Monitoring of Stored CO2 in Organic Rocks Under Non-Equilibrium Conditions

    SciTech Connect

    Malhotra, Vivak

    2014-06-30

    cores, which were pressurized with high pressure CO2, determine the fate of sequestered CO2 in these cores. Our results suggested that Illinois bituminous coal in its unperturbed state, i.e., when not pressurized with CO2, showed large variations in the mechanical properties. Modulus varied from 0.7 GPa to 3.4 GPa even though samples were extracted from a single large chunk of coal. We did not observe any glass transition for Illinois bituminous coal at - 100oC ≤ T ≤ 300oC, however, when the coal was pressurized with CO2 at ambient ≤ P ≤ 20.7 MPa, the viscosity of the coal decreased and inversely scaled with the CO2 pressure. The decrease in viscosity as a function of pressure could pose CO2 injection problems for coal as lower viscosity would allow the solid coal to flow to plug the fractures, fissures, and cleats. Our experiments also showed a very small fraction of CO2 was absorbed in coal; and when CO2 pressurized coals were exposed to atmospheric conditions, the loss of CO2 from coals was massive. Half of the sequestered gas from the coal cores was lost in less than 20 minutes. Our shockwave experiments on Illinois bituminous coal, New Albany shale (Illinois), Devonian shale (Ohio), and Utica shale (Ohio) presented clear evidence that the significant emission of the sequestered CO2 from these formations cannot be discounted during seismic activity, especially if caprock is compromised. It is argued that additional shockwave studies, both compressive and transverse, would be required for successfully mapping the risks associated with sequestering high pressure CO2 in coal and shale formations.

  16. Glider monitoring of shelf suspended particle dynamics and transport during storm and flooding conditions

    NASA Astrophysics Data System (ADS)

    Bourrin, François; Many, Gaël; Durrieu de Madron, Xavier; Martín, Jacobo; Puig, Pere; Houpert, Loic; Testor, Pierre; Kunesch, Stéphane; Mahiouz, Karim; Béguery, Laurent

    2015-10-01

    Transfers of particulate matter on continental margins primarily occur during energetic events. As part of the CASCADE (CAscading, Storm, Convection, Advection and Downwelling Events) experiment, a glider equipped with optical sensors was deployed in the coastal area of the Gulf of Lions, NW Mediterranean in March 2011 to assess the spatio-temporal variability of hydrology, suspended particles properties and fluxes during energetic conditions. This deployment complemented a larger observational effort, a part of the MOOSE (Mediterranean Ocean Observing System of the Environment) network, composed of a coastal benthic station, a surface buoy and moorings on the continental slope. This set of observations permitted to measure the impact of three consecutive storms and a flood event across the entire continental shelf. Glider data showed that the sediment resuspension and transport observed at the coastal station during the largest storm (Hs>4 m) was effective down to a water depth of 80 m. The mid-shelf mud belt, located between 40 and 90 m depth, appears as the zone where the along-shelf flux of suspended sediment is maximum. Besides, the across-shelf flux of suspended sediment converges towards the outer limit of the mid-shelf mud belt, where deposition of suspended particles probably occurs and contributes to the nourishment of this area. Hydrological structures, suspended particles transport and properties changed drastically during stormy periods and the following flood event. Prior to the storms, the shelf waters were weakly stratified due in particular to the presence of cold dense water on the inner- and mid-shelf. The storms rapidly swept away this dense water, as well as the resuspended sediments, along the shelf and towards a downstream submarine canyon. The buoyant river plumes that spread along the shelf after the flooding period provoked a restratification of the water column on the inner- and mid-shelf. The analysis of glider's optical data at

  17. A new method for on-line monitoring of brake fluid condition using an enclosed reference probe

    NASA Astrophysics Data System (ADS)

    Wang, Chuantong; Shida, Katsunori

    2007-11-01

    This paper presents a new method for on-line monitoring of the liquid level and water content of brake fluid using an enclosed reference probe as the capacitive sensing part. The probe has an enclosed cavity at the end which is designed to hold fresh brake fluid as an on-line reference. Three capacitances formed by four electrodes are used for the liquid level, water content and reference measurement and form the mutual calibrating output functions of the sensing probe. The liquid level measurement is calibrated to the permittivity changes by the capacitance for water content measurement. At the same time, the water content measurement is calibrated to temperature changes and variety of fluids by the capacitance of the reference measurement. Therefore, once the permittivity characteristics of brake fluids are experimentally modeled, the proposed method has a self-calibration ability to influence factors including temperature, water content (to liquid level measurement) and variety of brake fluids without an additional sensor supported by database as in conventional intelligent sensor systems. The design and implementation method are discussed with a prototype probe developed and tested. The permittivity characteristics of brake fluid samples are discussed. The calibration method and errors analysis are presented. The method presents a different way to construct a smart sensor which is useful in brake fluid condition monitoring and also other liquid measurement applications.

  18. Development of a decision support system for monitoring, reporting and forecasting ecological conditions of the Appalachian Trail

    USGS Publications Warehouse

    Wang, Yeqiao; Nemani, Ramakrishna; Dieffenbach, Fred; Stolte, Kenneth; Holcomb, Glenn B.; Robinson, Matt; Reese, Casey C.; McNiff, Marcia; Duhaime, Roland; Tierney, Geri; Mitchell, Brian; August, Peter; Paton, Peter; LaBash, Charles

    2010-01-01

    This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.

  19. On the derivation of the pre-lockup feature based condition monitoring method for automatic transmission clutches

    NASA Astrophysics Data System (ADS)

    Ompusunggu, Agusmian Partogi

    2014-05-01

    This paper discusses how a qualitative understanding on the physics of failure can lead to a theoretical derivation of effective features that are useful for condition monitoring of wet friction clutches. The physical relationships between the features and the mean coefficient of friction (COF) which can be seen as the representation of the degradation level of a wet friction clutch are theoretically derived. In order to assess the accuracy of the theoretical relationships, Pearson's correlation coefficient is applied to experimental data obtained from accelerated life tests on some commercial paper-based wet friction clutches using a fully instrumented SAE#2 setup. The analyses on the experimental data reveal that the theoretical predictions are plausible.

  20. Assessment and monitoring of recreation impacts and resource conditions on mountain summits: examples from the Northern Forest, USA

    USGS Publications Warehouse

    Monz, Christopher A.; Marion, Jeffrey L.; Goonan, Kelly A.; Manning, Robert E.; Wimpey, Jeremy; Carr, Christopher

    2010-01-01

    Mountain summits present a unique challenge to manage sustainably: they are ecologically important and, in many circumstances, under high demand for recreation and tourism activities. This article presents recent advances in the assessment of resource conditions and visitor disturbance in mountain summit environments, by drawing on examples from a multiyear, interdisciplinary study of summits in the northeastern United States. Primary impact issues as a consequence of visitor use, such as informal trail formation, vegetation disturbance, and soil loss, were addressed via the adaption of protocols from recreation ecology studies to summit environments. In addition, new methodologies were developed that provide measurement sensitivity to change previously unavailable through standard recreation monitoring protocols. Although currently limited in application to the northeastern US summit environments, the methods presented show promise for widespread application wherever summits are in demand for visitor activities.

  1. Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations.

    PubMed

    Zhang, Cunji; Yao, Xifan; Zhang, Jianming; Jin, Hong

    2016-01-01

    Tool breakage causes losses of surface polishing and dimensional accuracy for machined part, or possible damage to a workpiece or machine. Tool Condition Monitoring (TCM) is considerably vital in the manufacturing industry. In this paper, an indirect TCM approach is introduced with a wireless triaxial accelerometer. The vibrations in the three vertical directions (x, y and z) are acquired during milling operations, and the raw signals are de-noised by wavelet analysis. These features of de-noised signals are extracted in the time, frequency and time-frequency domains. The key features are selected based on Pearson's Correlation Coefficient (PCC). The Neuro-Fuzzy Network (NFN) is adopted to predict the tool wear and Remaining Useful Life (RUL). In comparison with Back Propagation Neural Network (BPNN) and Radial Basis Function Network (RBFN), the results show that the NFN has the best performance in the prediction of tool wear and RUL. PMID:27258277

  2. Rocket plume spectrometry: A system permitting engine condition monitoring, as applied to the technology test bed engine

    NASA Technical Reports Server (NTRS)

    Powers, W. T.

    1989-01-01

    The appearance of visible objects in the exhaust plume of space shuttle main engines (SSME) during test firings is discussed. A program was undertaken to attempt to identify anomalous material resulting from wear, normal or excessive, of internal parts, allowing time monitoring of engine condition or detection of failure precursors. Measurements were taken during test firings at Stennis Space Center and at the Santa Suzanna facility in California. The results indicated that a system having high spectral resolution, a fast time response, and a wide spectral range was required to meet all requirements, thus two special systems have been designed and built. One is the Optical Plume Anomaly Detector (OPAD). The other instrument, which is described in this report, is the superspectrometer, an optical multichannel analyzer having 8,192 channels covering the spectral band 250 to 1,000 nm.

  3. Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations

    PubMed Central

    Zhang, Cunji; Yao, Xifan; Zhang, Jianming; Jin, Hong

    2016-01-01

    Tool breakage causes losses of surface polishing and dimensional accuracy for machined part, or possible damage to a workpiece or machine. Tool Condition Monitoring (TCM) is considerably vital in the manufacturing industry. In this paper, an indirect TCM approach is introduced with a wireless triaxial accelerometer. The vibrations in the three vertical directions (x, y and z) are acquired during milling operations, and the raw signals are de-noised by wavelet analysis. These features of de-noised signals are extracted in the time, frequency and time–frequency domains. The key features are selected based on Pearson’s Correlation Coefficient (PCC). The Neuro-Fuzzy Network (NFN) is adopted to predict the tool wear and Remaining Useful Life (RUL). In comparison with Back Propagation Neural Network (BPNN) and Radial Basis Function Network (RBFN), the results show that the NFN has the best performance in the prediction of tool wear and RUL. PMID:27258277

  4. Multivariate calibration applied to the quantitative analysis of infrared spectra

    NASA Astrophysics Data System (ADS)

    Haaland, David M.

    1992-03-01

    Multivariate calibration methods are very useful for improving the precision, accuracy, and reliability of quantitative spectral analyses. Spectroscopists can more effectively use these sophisticated statistical tools if they have a qualitative understanding of the techniques involved. A qualitative picture of the factor analysis multivariate calibration methods of partial least squares (PLS) and principal component regression (PCR) is presented using infrared calibrations based upon spectra of phosphosilicate glass thin films on silicon wafers. Comparisons of the relative prediction abilities of four different multivariate calibration methods are given based on Monte Carlo simulations of spectral calibration and prediction data. The success of multivariate spectral calibrations is demonstrated for several quantitative infrared studies. The infrared absorption and emission spectra of thin-film dielectrics used in the manufacture of microelectronic devices demonstrate rapid, nondestructive at-line and in- situ analyses using PLS calibrations. Finally, the application of multivariate spectral calibrations to reagentless analysis of blood is presented. We have found that the determination of glucose in whole blood taken from diabetics can be precisely monitored from the PLS calibration of either mid- or near-infrared spectra of the blood. Progress toward the noninvasive determination of glucose levels in diabetics is an ultimate goal of this research.

  5. Multivariate calibration applied to the quantitative analysis of infrared spectra

    SciTech Connect

    Haaland, D.M.

    1991-01-01

    Multivariate calibration methods are very useful for improving the precision, accuracy, and reliability of quantitative spectral analyses. Spectroscopists can more effectively use these sophisticated statistical tools if they have a qualitative understanding of the techniques involved. A qualitative picture of the factor analysis multivariate calibration methods of partial least squares (PLS) and principal component regression (PCR) is presented using infrared calibrations based upon spectra of phosphosilicate glass thin films on silicon wafers. Comparisons of the relative prediction abilities of four different multivariate calibration methods are given based on Monte Carlo simulations of spectral calibration and prediction data. The success of multivariate spectral calibrations is demonstrated for several quantitative infrared studies. The infrared absorption and emission spectra of thin-film dielectrics used in the manufacture of microelectronic devices demonstrate rapid, nondestructive at-line and in-situ analyses using PLS calibrations. Finally, the application of multivariate spectral calibrations to reagentless analysis of blood is presented. We have found that the determination of glucose in whole blood taken from diabetics can be precisely monitored from the PLS calibration of either mind- or near-infrared spectra of the blood. Progress toward the non-invasive determination of glucose levels in diabetics is an ultimate goal of this research. 13 refs., 4 figs.

  6. Multivariate Strategies in Functional Magnetic Resonance Imaging

    ERIC Educational Resources Information Center

    Hansen, Lars Kai

    2007-01-01

    We discuss aspects of multivariate fMRI modeling, including the statistical evaluation of multivariate models and means for dimensional reduction. In a case study we analyze linear and non-linear dimensional reduction tools in the context of a "mind reading" predictive multivariate fMRI model.

  7. A method for monitoring hydrological conditions beneath herbaceous wetlands using multi-temporal ALOS PALSAR coherence data

    NASA Astrophysics Data System (ADS)

    Zhang, M.; Li, Z.; Tian, B.; Zhou, J.; Zeng, J.

    2015-06-01

    Reed marshes, the world's most widespread type of wetland vegetation, are undergoing major changes as a result of climate changes and human activities. The presence or absence of water in reed marshes has a significant impact on the whole ecosystem and remains a key indicator to identify the effective area of a wetland and help estimate the degree of degeneration. Past studies have demonstrated the use of interferometric synthetic aperture radar (InSAR) to map water-level changes for flooded reeds. However, the identification of the different hydrological states of reed marshes is often poorly understood. The analysis given in this paper shows that L-band interferometric coherence is very sensitive to the water surface conditions beneath reed marshes and so can be used as classifier. A method based on a statistical analysis of the coherence distributions for wet and dry reeds using InSAR pairs was, therefore, investigated in this study. The experimental results were validated by in-situ data and showed very good agreement. This is the first time that information about the water cover under herbaceous wetlands has been derived using interferometric coherence values. This method can also effectively and easily be applied to monitor the hydrological conditions beneath other herbaceous wetlands.

  8. How aggressive are coastal cliff environments? Monitoring micro-environmental conditions on an actively eroding rock cliff.

    NASA Astrophysics Data System (ADS)

    Lim, Michael; Rosser, Nicholas; Petley, David; Norman, Emma; Brain, Matthew; Barlow, John

    2010-05-01

    Despite their widespread occurrence, the behaviour of coastal rock cliffs, and in particular the balance between the marine and subaerial conditions that promote erosion, is poorly understood. This is mainly due to a lack of direct, quantitative data on process and response in this type of environment. This paper investigates how near-cliff environmental processes can be associated with the occurrence of rockfalls, which we argue contribute the majority of material lost from coastal cliffs. A detailed recent history of rockfall volumes, dating back to 2003, has been collected using repeat terrestrial laser scans of a 70 m high cliff section on the North Yorkshire coast, UK. This dataset is complimented with a bespoke environmental monitoring system installed upon the cliff face, which allows the influence of weathering and erosion processes on the magnitude and frequency of rockfalls to be analysed. This system is comprised of three instrument clusters at nodes that correspond to three main lithological units of the cliff, hard wired to a communications unit at the top of the cliff face. Data is collected on air temperature, humidity, irradiance, wind and precipitation. Within the near surface of the rock mass we also measure temperature, rock moisture, surface wetness and strain, to allow the direct physical response of the rock to be quantified. The cliff (local) environment monitoring system demonstrates that the rock undergoes significantly greater variability than can be identified from more generic regional weather and tide datasets, predominantly as a function of the angular geometry of the cliff face, resulting in rapid gradients of change. For example, daily variations in temperature and moisture can be seen to have a significant and direct effect on the strain responses of the rock. We seek to establish this as a long-term dataset, to provide a new quantitative assessment of the links between regional and hinterland weather conditions and those found on

  9. A semiparametric multivariate and multisite weather generator

    NASA Astrophysics Data System (ADS)

    Apipattanavis, Somkiat; Podestá, Guillermo; Rajagopalan, Balaji; Katz, Richard W.

    2007-11-01

    We propose a semiparametric multivariate weather generator with greater ability to reproduce the historical statistics, especially the wet and dry spells. The proposed approach has two steps: (1) a Markov Chain for generating the precipitation state (i.e., no rain, rain, or heavy rain), and (2) a k-nearest neighbor (k-NN) bootstrap resampler for generating the multivariate weather variables. The Markov Chain captures the spell statistics while the k-NN bootstrap captures the distributional and lag-dependence statistics of the weather variables. Traditional k-NN generators tend to under-simulate the wet and dry spells that are keys to watershed and agricultural modeling for water planning and management; hence the motivation for this research. We demonstrate the utility of the proposed approach and its improvement over the traditional k-NN approach through an application to daily weather data from Pergamino in the Pampas region of Argentina. We show the applicability of the proposed framework in simulating weather scenarios conditional on the seasonal climate forecast and also at multiple sites in the Pampas region.

  10. Software For Multivariate Bayesian Classification

    NASA Technical Reports Server (NTRS)

    Saul, Ronald; Laird, Philip; Shelton, Robert

    1996-01-01

    PHD general-purpose classifier computer program. Uses Bayesian methods to classify vectors of real numbers, based on combination of statistical techniques that include multivariate density estimation, Parzen density kernels, and EM (Expectation Maximization) algorithm. By means of simple graphical interface, user trains classifier to recognize two or more classes of data and then use it to identify new data. Written in ANSI C for Unix systems and optimized for online classification applications. Embedded in another program, or runs by itself using simple graphical-user-interface. Online help files makes program easy to use.

  11. Channel Efficiency with Security Enhancement for Remote Condition Monitoring of Multi Machine System Using Hybrid Huffman Coding

    NASA Astrophysics Data System (ADS)

    Datta, Jinia; Chowdhuri, Sumana; Bera, Jitendranath

    2015-07-01

    This paper presents a novel scheme of remote condition monitoring of multi machine system where a secured and coded data of induction machine with different parameters is communicated between a state-of-the-art dedicated hardware Units (DHU) installed at the machine terminal and a centralized PC based machine data management (MDM) software. The DHUs are built for acquisition of different parameters from the respective machines, and hence are placed at their nearby panels in order to acquire different parameters cost effectively during their running condition. The MDM software collects these data through a communication channel where all the DHUs are networked using RS485 protocol. Before transmitting, the parameter's related data is modified with the adoption of differential pulse coded modulation (DPCM) and Huffman coding technique. It is further encrypted with a private key where different keys are used for different DHUs. In this way a data security scheme is adopted during its passage through the communication channel in order to avoid any third party attack into the channel. The hybrid mode of DPCM and Huffman coding is chosen to reduce the data packet length. A MATLAB based simulation and its practical implementation using DHUs at three machine terminals (one healthy three phase, one healthy single phase and one faulty three phase machine) proves its efficacy and usefulness for condition based maintenance of multi machine system. The data at the central control room are decrypted and decoded using MDM software. In this work it is observed that Chanel efficiency with respect to different parameter measurements has been increased very much.

  12. Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

    PubMed

    MacNab, Ying C

    2016-08-01

    This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. PMID:27566769

  13. A Multimodel Global Drought Information System (GDIS) for Near Real-Time Monitoring of Surface Water Conditions (Invited)

    NASA Astrophysics Data System (ADS)

    Nijssen, B.

    2013-12-01

    While the absolute magnitude of economic losses associated with weather and climate disasters such as droughts is greatest in the developed world, the relative impact is much larger in the developing world, where agriculture typically constitutes a much larger percentage of the labor force and food insecurity is a major concern. Nonetheless, our ability to monitor and predict the development and occurrence of droughts at a global scale in near real-time is limited and long-term records of soil moisture are essentially non-existent globally The problem is particularly critical given that many of the most damaging droughts occur in parts of the world that are most deficient in terms of in situ precipitation observations. In recent years, a number of near real-time drought monitoring systems have been developed with regional or global extent. While direct observations of key variables such as moisture storage are missing, the evolution of land surface models that are globally applicable provides a means of reconstructing them. The implementation of a multi-model drought monitoring system is described, which provides near real-time estimates of surface moisture storage for the global land areas between 50S and 50N with a time lag of about one day. Near real-time forcings are derived from satellite-based precipitation estimates and modeled air temperatures. The system is distinguished from other operational systems in that it uses multiple land surface models to simulate surface moisture storage, which are then combined to derive a multi-model estimate of drought. Previous work has shown that while land surface models agree in broad context, particularly in terms of soil moisture percentiles, important differences remain, which motivates a multi-model ensemble approach. The system is an extension of similar systems developed by at the University of Washington for the Pacific Northwest and for the United States, but global application of the protocols used in the U

  14. Exploiting the Free Landsat Archive for Operational Monitoring of Ecosystem Condition and Change Across the Chesapeake Bay Watershed

    NASA Technical Reports Server (NTRS)

    BrowndeColstoun, Eric

    2010-01-01

    For the first time, all imagery acquired by the Landsat series of satellites is being made available by the USGS to users at no cost. This represents a key opportunity to use Landsat in a truly operational monitoring framework: large regions of the U.S. such as the Chesapeake Bay Watershed can now be analyzed using "wall-to-wall" imagery at timescales from approximately 1 month to several years. With the future launch of the Landsat Data Continuity Mission (LDCM) and Decadal Survey missions such as the hyperspectral HyspIRI, it is imperative to develop robust processing systems to perform annual ecosystem assessments over large regions such as the Chesapeake Bay. We have been working at NASA's Goddard Space Flight Center (GSFC) to develop an integrative framework for inserting 30m, annual, Landsat based data and derived products into the existing decision support system for the Bay, with a particular focus on ecosystem condition and changes over the entire watershed. The basic goal is to use a 'stack' of Landsat imagery with 40% or less cloud cover to produce multi-date (2005-2009 period), cloud/shadow/gap-free composited surface reflectance products that will support the creation of watershed scale land cover/ use products and the monitoring of ecosystem change across the Bay. Our scientific focus extends beyond the conventional definition of land cover (i.e. a classification of vegetation type) as we propose to monitor both changes in surface type (e.g. forest to urban), vegetation structure (e.g. forest disturbance due to logging or insect damage), as well as winter crop cover. These processes represent a continuum from large, interannual changes in land cover type, to subtler, intra-annual changes associated with short-term disturbance. The free Landsat data are being processed to surface reflectance and composited using the existing Landsat Ecosystem Disturbance Adaptive Processing System here at NASA/ GSFC, and land cover products (type, tree cover

  15. Geophysical Measurements for Real-time Monitoring of Biogeochemical Processes for Improvement of Soil Engineering Properties and Subsurface Environmental Conditions (Invited)

    NASA Astrophysics Data System (ADS)

    DeJong, J. T.

    2013-12-01

    A variety of biogeochemical processes, from inorganic mineral precipitation, to bio-film formation, to bio-gas generation, are being investigated as alternative methods to improve soil engineering properties and subsurface environmental conditions. Every process applied in a geotechnical or geoenvironmental application requires the ability to monitor the progression of treatment non-destructively and in real-time. Geophysical methods have been shown effective to monitor temporally and map spatially soil improvement. Results from seismic velocity (compression and shear wave) and resistivity measurements obtained on 1-D, 2-D, and 3-D experiments at scales ranging from bench-top to field scale will be presented. Shear wave velocity will be demonstrated to be most effective in monitoring microbially induced calcite precipitation (MICP) in sands while compression wave velocity will be used to monitor desaturation through bio-gas formation. Finally, the implications of these results for real-time monitoring during field-scale applications will be discussed.

  16. Statistical analysis of multivariate atmospheric variables. [cloud cover

    NASA Technical Reports Server (NTRS)

    Tubbs, J. D.

    1979-01-01

    Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

  17. Multivariate Feature Selection for Predicting Scour-Related Bridge Damage using a Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Anderson, I.

    2015-12-01

    Scour and hydraulic damage are the most common cause of bridge failure, reported to be responsible for over 60% of bridge failure nationwide. Scour is a complex process, and is likely an epistatic function of both bridge and stream conditions that are both stationary and in dynamic flux. Bridge inspections, conducted regularly on bridges nationwide, rate bridge health assuming a static stream condition, and typically do not include dynamically changing geomorphological adjustments. The Vermont Agency of Natural Resources stream geomorphic assessment data could add value into the current bridge inspection and scour design. The 2011 bridge damage from Tropical Storm Irene served as a case study for feature selection to improve bridge scour damage prediction in extreme events. The bridge inspection (with over 200 features on more than 300 damaged and 2,000 non-damaged bridges), and the stream geomorphic assessment (with over 300 features on more than 5000 stream reaches) constitute "Big Data", and together have the potential to generate large numbers of combined features ("epistatic relationships") that might better predict scour-related bridge damage. The potential combined features pose significant computational challenges for traditional statistical techniques (e.g., multivariate logistic regression). This study uses a genetic algorithm to perform a search of the multivariate feature space to identify epistatic relationships that are indicative of bridge scour damage. The combined features identified could be used to improve bridge scour design, and to better monitor and rate bridge scour vulnerability.

  18. Monitoring drought conditions and their uncertainties in areas with sparse precipitation data. Evaluation of different precipitation datasets in Africa.

    NASA Astrophysics Data System (ADS)

    Naumann, G.; Barbosa, P.; Carrao, H.; Singleton, A.; Vogt, J.

    2012-04-01

    Assessment of drought conditions requires understanding regional historical droughts as well as the impacts on human activities during their occurrences. Traditional methods for drought assessment are mainly based on water supply indices derived from precipitation time-series alone. Thus, the main limitation for developing effective real-time drought monitoring and early warning systems in Africa is the lack of reliable and up-to-date precipitation data in many regions of the continent. A sparse distribution of rain gauges and short or incomplete rainfall historical records pose further problems. This lack of information may lead to significant errors in the estimation of statistical parameters for deriving water supply indices from the precipitation time-series. Procedures for drought detection and assessment have a particular level of uncertainty associated to the data and models used. In order to better understand the extent, severity and impact of a drought in a region, it is first necessary to improve the quality of these procedures by using the best available data, theoretical assumptions and model formulations. The main objective of this study is to evaluate the uncertainties due to sample size associated with the estimation of the Standardized Precipitation Index (SPI) and their impact on the possible level of confidence in drought monitoring in Africa. In order to do this, four different rainfall datasets, each available on a monthly basis, were analysed over four river basins in Africa (Oum-er-Rbia, Limpopo, Niger, and Eastern Nile) as well as at continental level. The four precipitation datasets used were the Tropical Rainfall Measuring Mission (TRMM) satellite monthly rainfall product 3B43 (0.25°x0.25°), the Global Precipitation Climatology Centre (GPCC) gridded precipitation dataset V.5 (0.5°x0.5°), the Global Precipitation Climatology Project (GPCP) Global Monthly Merged Precipitation Analyses (2.5°x2.5°), and the Climate Prediction Center

  19. Ultraviolet sensor as integrity monitor for enhanced flight vision system (EFVS) approaches to Cat II RVR conditions

    NASA Astrophysics Data System (ADS)

    McKinley, John B.; Pierson, Roger; Ertem, M. C.; Krone, Norris J., Jr.; Cramer, James A.

    2008-04-01

    Flight tests were conducted at Greenbrier Valley Airport (KLWB) and Easton Municipal Airport / Newnam Field (KESN) in a Cessna 402B aircraft using a head-up display (HUD) and a Norris Electro Optical Systems Corporation (NEOC) developmental ultraviolet (UV) sensor. These flights were sponsored by NEOC under a Federal Aviation Administration program, and the ultraviolet concepts, technology, system mechanization, and hardware for landing during low visibility landing conditions have been patented by NEOC. Imagery from the UV sensor, HUD guidance cues, and out-the-window videos were separately recorded at the engineering workstation for each approach. Inertial flight path data were also recorded. Various configurations of portable UV emitters were positioned along the runway edge and threshold. The UV imagery of the runway outline was displayed on the HUD along with guidance generated from the mission computer. Enhanced Flight Vision System (EFVS) approaches with the UV sensor were conducted from the initial approach fix to the ILS decision height in both VMC and IMC. Although the availability of low visibility conditions during the flight test period was limited, results from previous fog range testing concluded that UV EFVS has the performance capability to penetrate CAT II runway visual range obscuration. Furthermore, independent analysis has shown that existing runway light emit sufficient UV radiation without the need for augmentation other than lens replacement with UV transmissive quartz lenses. Consequently, UV sensors should qualify as conforming to FAA requirements for EFVS approaches. Combined with Synthetic Vision System (SVS), UV EFVS would function as both a precision landing aid, as well as an integrity monitor for the GPS and SVS database.

  20. Monitoring Surface Moisture of Crater-fill Sediment in Extreme hydroclimatic conditions (Ubehebe Volcanic Field, Death Valley, California).

    NASA Astrophysics Data System (ADS)

    Bonaccorsi, R.; Zent, A.; McKay, C. P.

    2014-12-01

    The long term monitoring of soil surface moisture is key for constraining surface hydrology processes in extreme weather and climatic settings and their impact on biological and geological components of desert environments. We tested and applied the use of miniature data loggers to acquire novel Temperature (T) and water content (weight percent, wt%) of fine-grained sediments deposited during rain events at Ubehebe Crater (UC), the larger and deeper crater within a volcanic field in Death Valley. The Miniaturized in situ systems are compliant with Death Valley National Park's regulations to conduct scientific research in wilderness and sacred sites. About 130,000 hours of recorded soil moisture and temperature were acquired in relation to the hydroclimatic conditions (2009-current). Total annual rainfall in the area range from ~50mm to <250 mm/y in water years (WY) 2004-to date. These values are representative of the climatic context of the Mojave Region as they encompass the wettest (2005, 2011) and driest years (2002, 2007, 2012, 2013, 2014) of the last ~120 years (Western Regional Climate Center, www.wrcc.dri.edu). To date, surface (0.5 cm to 2 cm-depth) moisture of intra-crater deposits can vary from dry-very dry (1-3wt % to - 10 wt%) to wet-saturated (10-60 wt%). Over saturated conditions occur in ephemeral ponds, which appear to form once a year as a result of winter and summer rainstorms, and may last for one-two weeks (2009-2014 study years). Summer storms can yield ca. 40% to 60% of the total annual precipitation (WY 2011 thru 2014). The intensity and temporal distribution of annual storms together with ground temperature extremes (-16 to +67 ºC) influence moisture distribution and retention within the crater's floor.

  1. A resolution analysis of two geophysical imaging methods for characterizing and monitoring hydrologic conditions in the Vadose zone.

    SciTech Connect

    Brainard, James Robert; Hammond, Gary.; Alumbaugh, David L.; La Brecque, D.J.

    2007-06-01

    This research project analyzed the resolution of two geophysical imaging techniques, electrical resistivity tomography (ERT) and cross-borehole ground penetrating radar (XBGPR), for monitoring subsurface flow and transport processes within the vadose zone. The study was based on petrophysical conversion of moisture contents and solute distributions obtained from unsaturated flow forward modeling. This modeling incorporated boundary conditions from a potable water and a salt tracer infiltration experiment performed at the Sandia-Tech Vadose Zone (STVZ) facility, and high-resolution spatial grids (6.25-cm spacing over a 1700-m domain) and incorporated hydraulic properties measured on samples collected from the STVZ. The analysis process involved petrophysical conversion of moisture content and solute concentration fields to geophysical property fields, forward geophysical modeling using the geophysical property fields to obtain synthetic geophysical data, and finally, inversion of this synthetic data. These geophysical property models were then compared to those derived from the conversion of the hydrologic forward modeling to provide an understanding of the resolution and limitations of the geophysical techniques.

  2. A WebGIS platform to monitor environmental conditions in ports and their surroundings in South Eastern Europe.

    PubMed

    Kolios, Stavros; Stylios, Chrysostomos; Petunin, Aleksandr

    2015-09-01

    The scope of this work is to describe the design and development of a web-based Geographic Information System (GIS) application and highlight its usefulness regarding monitoring and evaluating environmental conditions in several ports and their surroundings in the greater South East Europe (SEE). The system receives inputs and handles two kinds of data that are processed and illustrated through maps and graphs at various temporal and spatial scales in this informational platform. The aforementioned data consists of point measurements from stations operating in the area of SEE ports as well as satellite date sets derived monthly for a period of 10 to 12 years, in terms of sea surface temperature, chlorophyll a, and colored dissolved organic matter (CDOM). The WebGIS platform is based on the client-server model and uses Google Maps API services for data plotting. Advanced designing and development tools and methodologies are used. The available valuable data render the application into a trustful and accurate provider of visual environmental interest information regarding the main ports of southeastern Europe and their surroundings that would operate as a guide for an environmentally sustainable future of ports and sea corridors in SEE. PMID:26275763

  3. Measurements of the performance of a beam condition monitor prototype in a 5 GeV electron beam

    NASA Astrophysics Data System (ADS)

    Hempel, M.; Afanaciev, K.; Burtowy, P.; Dabrowski, A.; Henschel, H.; Idzik, M.; Karacheban, O.; Lange, W.; Leonard, J.; Levy, I.; Lohmann, W.; Pollak, B.; Przyborowski, D.; Ryjov, V.; Schuwalow, S.; Stickland, D.; Walsh, R.; Zagozdzinska, A.

    2016-08-01

    The Fast Beam Conditions Monitor, BCM1F, in the Compact Muon Solenoid, CMS, experiment was operated since 2008 and delivered invaluable information on the machine induced background in the inner part of the CMS detector supporting a safe operation of the inner tracker and high quality data. Due to the shortening of the time between two bunch crossings from 50 ns to 25 ns and higher expected luminosity at the Large Hadron Collider, LHC, in 2015, BCM1F needed an upgrade to higher bandwidth. In addition, BCM1F is used as an on-line luminometer operated independently of CMS. To match these requirements, the number of single crystal diamond sensors was enhanced from 8 to 24. Each sensor is subdivided into two pads, leading to 48 readout channels. Dedicated fast front-end ASICs were developed in 130 nm technology, and the back-end electronics is completely upgraded. An assembled prototype BCM1F detector comprising sensors, a fast front-end ASIC and optical analog readout was studied in a 5 GeV electron beam at the DESY-II accelerator. Results on the performance are given.

  4. Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms

    NASA Astrophysics Data System (ADS)

    Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

    2013-03-01

    The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.

  5. Turbidity in the fluvial Gironde Estuary (S-W France) based on 10 year continuous monitoring: sensitivity to hydrological conditions

    NASA Astrophysics Data System (ADS)

    Jalón-Rojas, I.; Schmidt, S.; Sottolichio, A.

    2015-03-01

    Climate change and human activities impact the volume and timing of freshwater input to estuaries. These modifications in fluvial discharges are expected to influence estuarine suspended sediment dynamics, and in particular the turbidity maximum zone (TMZ). Located in the southwest France, the Gironde fluvial-estuarine systems has an ideal context to address this issue. It is characterized by a very pronounced TMZ, a decrease in mean annual runoff in the last decade, and it is quite unique in having a long-term and high-frequency monitoring of turbidity. The effect of tide and river flow on turbidity in the fluvial estuary is detailed, focusing on dynamics related to changes in hydrological conditions (river floods, periods of low-water, inter-annual changes). Turbidity shows hysteresis loops at different time scales: during river floods and over the transitional period between the installation and expulsion of the TMZ. These hysteresis patterns, that reveal the origin of sediment, locally resuspended or transported from the watershed, may be a tool to evaluate the presence of remained mud. Statistics on turbidity data bound the range of river flow that promotes the TMZ installation in the fluvial stations. Hydrological indicators of the persistence and turbidity level of the TMZ are also defined. The long-term evolution of these indicators confirms the influence of discharge decrease on the intensification of the TMZ in tidal rivers, and provides a tool to evaluate future scenarios.

  6. Customized maximal-overlap multiwavelet denoising with data-driven group threshold for condition monitoring of rolling mill drivetrain

    NASA Astrophysics Data System (ADS)

    Chen, Jinglong; Wan, Zhiguo; Pan, Jun; Zi, Yanyang; Wang, Yu; Chen, Binqiang; Sun, Hailiang; Yuan, Jing; He, Zhengjia

    2016-02-01

    Fault identification timely of rolling mill drivetrain is significant for guaranteeing product quality and realizing long-term safe operation. So, condition monitoring system of rolling mill drivetrain is designed and developed. However, because compound fault and weak fault feature information is usually sub-merged in heavy background noise, this task still faces challenge. This paper provides a possibility for fault identification of rolling mills drivetrain by proposing customized maximal-overlap multiwavelet denoising method. The effectiveness of wavelet denoising method mainly relies on the appropriate selections of wavelet base, transform strategy and threshold rule. First, in order to realize exact matching and accurate detection of fault feature, customized multiwavelet basis function is constructed via symmetric lifting scheme and then vibration signal is processed by maximal-overlap multiwavelet transform. Next, based on spatial dependency of multiwavelet transform coefficients, spatial neighboring coefficient data-driven group threshold shrinkage strategy is developed for denoising process by choosing the optimal group length and threshold via the minimum of Stein's Unbiased Risk Estimate. The effectiveness of proposed method is first demonstrated through compound fault identification of reduction gearbox on rolling mill. Then it is applied for weak fault identification of dedusting fan bearing on rolling mill and the results support its feasibility.

  7. Method of multivariate spectral analysis

    DOEpatents

    Keenan, Michael R.; Kotula, Paul G.

    2004-01-06

    A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

  8. Multivariable Burchnall-Chaundy theory.

    PubMed

    Previato, Emma

    2008-03-28

    Burchnall & Chaundy (Burchnall & Chaundy 1928 Proc. R. Soc. A 118, 557-583) classified the (rank 1) commutative subalgebras of the algebra of ordinary differential operators. To date, there is no such result for several variables. This paper presents the problem and the current state of the knowledge, together with an interpretation in differential Galois theory. It is known that the spectral variety of a multivariable commutative ring will not be associated to a KP-type hierarchy of deformations, but examples of related integrable equations were produced and are reviewed. Moreover, such an algebro-geometric interpretation is made to fit into A.N. Parshin's newer theory of commuting rings of partial pseudodifferential operators and KP-type hierarchies which uses higher local fields. PMID:17588865

  9. Satellite monitoring temperature conditions spawning area of the Northeast Arctic cod in the Norwegian Sea and assessment its abundance

    NASA Astrophysics Data System (ADS)

    Vanyushin, George; Bulatova, Tatiana; Klochkov, Dmitriy; Troshkov, Anatoliy; Kruzhalov, Michail

    2013-04-01

    favorable conditions for development of the cod larvae and fry and provide them with food stock, finally, direct influence on forming total stock biomass of cod and helping its population forecast. Key words: satellite monitoring of SST, Northeast Arctic cod, spawning area, maps of SST, prognosis.

  10. The Multi-Isotope Process (MIP) Monitor Project: FY12 Progress and Accomplishments

    SciTech Connect

    Coble, Jamie B.; Orton, Christopher R.; Jordan, David V.; Schwantes, Jon M.; Bender, Sarah; Dayman, Kenneth J.; Unlu, Kenan; Landsberger, Sheldon

    2012-09-27

    The Multi-Isotope Process (MIP) Monitor, being developed at Pacific Northwest National Laboratory (PNNL), provides an efficient approach to monitoring the process conditions in reprocessing facilities in support of the goal of "...(minimization of) the risks of nuclear proliferation and terrorism." The MIP Monitor measures distributions of a suite of indicator (radioactive) isotopes present within product and waste streams of a nuclear reprocessing facility. These indicator isotopes are monitored on-line by gamma spectrometry and compared, in near-real-time, to spectral patterns representing "normal" process conditions using multivariate pattern recognition software. The monitor utilizes this multivariate analysis and gamma spectroscopy of reprocessing streams to detect small changes in the gamma spectrum, which may indicate changes in process conditions. Multivariate analysis methods common in chemometrics, such as principal component analysis (PCA) and partial least squares regression (PLS), act as pattern recognition techniques, which can detect small deviations from the expected, nominal condition. By targeting multiple gamma-emitting indicator isotopes, the MIP Monitor approach is compatible with the use of small, portable, relatively high-resolution gamma detectors that may be easily deployed throughout an existing facility. The automated multivariate analysis can provide a level of data obscurity, giving a built-in information barrier to protect sensitive or proprietary operational data. Proof-of-concept simulations and experiments have been performed in previous years to demonstrate the validity of this tool in a laboratory setting. Development of the MIP Monitor approach continues to evaluate the efficacy of the monitor for automated, real-time or near-real-time application. This report details follow-on research and development efforts sponsored by the U.S. Department of Energy Fuel Cycle Research and Development related to the MIP Monitor for fiscal year

  11. A theoretical study of the fundamental torsional wave in buried pipes for pipeline condition assessment and monitoring

    NASA Astrophysics Data System (ADS)

    Muggleton, J. M.; Kalkowski, M.; Gao, Y.; Rustighi, E.

    2016-07-01

    Waves that propagate at low frequencies in buried pipes are of considerable interest in a variety of practical scenarios, for example leak detection, remote pipe detection, and pipeline condition assessment and monitoring. Whilst there has been considerable research and commercial attention on the accurate location of pipe leakage for many years, the various causes of pipe failures and their identification, have not been well documented; moreover, there are still a number of gaps in the existing knowledge. Previous work has focused on two of the three axisymmetric wavetypes that can propagate: the s=1, fluid-dominated wave; and the s=2, shell-dominated wave. In this paper, the third axisymmetric wavetype, the s=0 torsional wave, is investigated. The effects of the surrounding soil on the characteristics of wave propagation and attenuation are analysed for a compact pipe/soil interface for which there is no relative motion between the pipe wall and the surrounding soil. An analytical dispersion relationship is derived for the torsional wavenumber from which both the wavespeed and wave attenuation can be obtained. How torsional waves can subsequently radiate to the ground surface is then investigated. Analytical expressions are derived for the ground surface displacement above the pipe resulting from torsional wave motion within the pipe wall. A numerical model is also included, primarily in order to validate some of the assumptions made whilst developing the analytical solutions, but also so that some comparison in the results may be made. Example results are presented for both a cast iron pipe and an MDPE pipe buried in two typical soil types.

  12. Turbidity in the fluvial Gironde Estuary (southwest France) based on 10-year continuous monitoring: sensitivity to hydrological conditions

    NASA Astrophysics Data System (ADS)

    Jalón-Rojas, I.; Schmidt, S.; Sottolichio, A.

    2015-06-01

    Climate change and human activities impact the volume and timing of freshwater input to estuaries. These modifications in fluvial discharges are expected to influence estuarine suspended sediment dynamics, and in particular the turbidity maximum zone (TMZ). Located in southwest France, the Gironde fluvial-estuarine system has an ideal context to address this issue. It is characterized by a very pronounced TMZ, a decrease in mean annual runoff in the last decade, and it is quite unique in having a long-term and high-frequency monitoring of turbidity. The effect of tide and river flow on turbidity in the fluvial estuary is detailed, focusing on dynamics related to changes in hydrological conditions (river floods, periods of low discharge, interannual changes). Turbidity shows hysteresis loops at different timescales: during river floods and over the transitional period between the installation and expulsion of the TMZ. These hysteresis patterns, that reveal the origin of sediment, locally resuspended or transported from the watershed, may be a tool to evaluate the presence of remained mud. Statistics on turbidity data bound the range of river flow that promotes the upstream migration of TMZ in the fluvial stations. Whereas the duration of the low discharge period mainly determines the TMZ persistence, the freshwater volume during high discharge periods explains the TMZ concentration at the following dry period. The evolution of these two hydrological indicators of TMZ persistence and turbidity level since 1960 confirms the effect of discharge decrease on the intensification of the TMZ in tidal rivers; both provide a tool to evaluate future scenarios.

  13. Using daily field-scale evapotranspiration (ET) derived with multi-sensor data fusion for monitoring crop condition and yield in central Iowa, United States

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drought has significant impacts over broad spatial and temporal scales, and information about the timing and extent of such conditions is of critical importance to many end users in the agricultural and water resource management communities. The ability to accurately monitor effects on crops and pr...

  14. Influence of milk yeild stage of lactation, and body conditions on dairy cattle lying behavior measured using an automated activity monitoring sensor

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The lying times of lactating Holstein-Friesian cows of varying body condition scores (BCS) and milk yield were measured using IceTag™ animal activity monitors in the Barony College dairy herd. A three-week average BCS was calculated for each cow; and in total 84 cows were selected equally between 3...

  15. Multivariate Time Series Similarity Searching

    PubMed Central

    Wang, Jimin; Zhu, Yuelong; Li, Shijin; Wan, Dingsheng; Zhang, Pengcheng

    2014-01-01

    Multivariate time series (MTS) datasets are very common in various financial, multimedia, and hydrological fields. In this paper, a dimension-combination method is proposed to search similar sequences for MTS. Firstly, the similarity of single-dimension series is calculated; then the overall similarity of the MTS is obtained by synthesizing each of the single-dimension similarity based on weighted BORDA voting method. The dimension-combination method could use the existing similarity searching method. Several experiments, which used the classification accuracy as a measure, were performed on six datasets from the UCI KDD Archive to validate the method. The results show the advantage of the approach compared to the traditional similarity measures, such as Euclidean distance (ED), cynamic time warping (DTW), point distribution (PD), PCA similarity factor (SPCA), and extended Frobenius norm (Eros), for MTS datasets in some ways. Our experiments also demonstrate that no measure can fit all datasets, and the proposed measure is a choice for similarity searches. PMID:24895665

  16. Multivariate time series similarity searching.

    PubMed

    Wang, Jimin; Zhu, Yuelong; Li, Shijin; Wan, Dingsheng; Zhang, Pengcheng

    2014-01-01

    Multivariate time series (MTS) datasets are very common in various financial, multimedia, and hydrological fields. In this paper, a dimension-combination method is proposed to search similar sequences for MTS. Firstly, the similarity of single-dimension series is calculated; then the overall similarity of the MTS is obtained by synthesizing each of the single-dimension similarity based on weighted BORDA voting method. The dimension-combination method could use the existing similarity searching method. Several experiments, which used the classification accuracy as a measure, were performed on six datasets from the UCI KDD Archive to validate the method. The results show the advantage of the approach compared to the traditional similarity measures, such as Euclidean distance (ED), cynamic time warping (DTW), point distribution (PD), PCA similarity factor (SPCA), and extended Frobenius norm (Eros), for MTS datasets in some ways. Our experiments also demonstrate that no measure can fit all datasets, and the proposed measure is a choice for similarity searches. PMID:24895665

  17. Multivariate analysis of pathophysiological factors in reflux oesophagitis.

    PubMed Central

    Cadiot, G; Bruhat, A; Rigaud, D; Coste, T; Vuagnat, A; Benyedder, Y; Vallot, T; Le Guludec, D; Mignon, M

    1997-01-01

    BACKGROUND: Reflux oesophagitis is considered a multifactorial disease, but the respective roles of the main factors involved in its pathophysiology have not been clearly established. AIMS: To attempt to assign these roles by means of a multivariate logistic regression analysis of the main parameters associated with reflux oesophagitis. PATIENTS: Eighty seven patients with gastro-oesophageal reflux disease were studied: 41 without oesophagitis and 46 with reflux oesophagitis grade 1 to 3. METHODS: (1) Monovariate comparison of patients' characteristics and of parameters derived from in hospital 24 hour oesophageal pH monitoring, oesophageal manometry, double isotope gastric emptying studies, and basal and pentagastrin stimulated gastric acid and pepsin output determinations, between patients with and without oesophagitis. (2) Multivariate logistic regression analysis including the parameters significant in the monovariate analysis. RESULTS: Among the 16 significant parameters from monovariate analysis, three significant independent parameters were identified by multivariate logistic regression analysis: number of refluxes lasting more than five minutes, reflecting oesophageal acid clearance (p = 0.002); basal lower oesophageal sphincter pressure (p = 0.008); and peak acid output (p = 0.012). These three parameters were not correlated with each other. The multivariate model was highly discriminant (correct classification of 81.3% of the cases (95% confidence intervals 0.723, 0.903). Risk for oesophagitis increased as a function of the tercile threshold values of the three parameters. Odds ratios of the three parameters for oesophagitis risk were similar, regardless of whether they were calculated when the patients were compared as a function of oesophagitis grade or the presence or absence of oesophagitis. CONCLUSIONS: This multivariate approach adds evidence that impaired oesophageal acid clearance and hypotonic lower oesophageal sphincter are the two major

  18. Visual Data Mining of Large, Multivariate Space-Time Data

    NASA Astrophysics Data System (ADS)

    Cook, D.

    2001-12-01

    Interest in understanding global climate change is generating monitoring efforts that yield a huge amount of multivariate space-time data. While analytical methods for univariate space-time data may be mature and substantial, methods for multivariate space-time data analysis are still in their infancy. The urgency of understanding climate change on a global scale begs for input from data analysts, and to work effectively they need new tools to explore multivariate aspects of climate. This talk describes interactive and dynamic visual tools for mining information from multivariate space-time data. Methods for small amounts of data will be discussed, followed by approaches to scaling up methods for large quantities of data. We focus on the ``multiple views'' approach for viewing multivariate data, and how these extend to include space-time contextual information. We also will describe dynamic graphics methods such as tours in the space-time context. Data mining is the current terminology for exploratory analyses of data, typically associated with large databases. Exploratory analysis has a goal of finding anomalies, quirks and deviations from a trend, and basically extracting unexpected information from data. It oft-times emphasizes model-free methods, although model-based approaches are also integral components to the analysis process. Visual data mining concentrates on the use of visual tools in the exploratory process. As such it often involves highly interactive and dynamic graphics environments which facilitate quick queries and visual responses. Visual methods are especially important in exploratory analysis because they provide an interface for using the human eye to digest complex information. A good plot can convey far more information than a numerical summary. Visual tools enhance the chances of discovering the unexpected, and detecting the anomalous events.

  19. Feasibility Study on the Use of On-line Multivariate Statistical Process Control for Safeguards Applications in Natural Uranium Conversion Plants

    SciTech Connect

    Ladd-Lively, Jennifer L

    2014-01-01

    The objective of this work was to determine the feasibility of using on-line multivariate statistical process control (MSPC) for safeguards applications in natural uranium conversion plants. Multivariate statistical process control is commonly used throughout industry for the detection of faults. For safeguards applications in uranium conversion plants, faults could include the diversion of intermediate products such as uranium dioxide, uranium tetrafluoride, and uranium hexafluoride. This study was limited to a 100 metric ton of uranium (MTU) per year natural uranium conversion plant (NUCP) using the wet solvent extraction method for the purification of uranium ore concentrate. A key component in the multivariate statistical methodology is the Principal Component Analysis (PCA) approach for the analysis of data, development of the base case model, and evaluation of future operations. The PCA approach was implemented through the use of singular value decomposition of the data matrix where the data matrix represents normal operation of the plant. Component mole balances were used to model each of the process units in the NUCP. However, this approach could be applied to any data set. The monitoring framework developed in this research could be used to determine whether or not a diversion of material has occurred at an NUCP as part of an International Atomic Energy Agency (IAEA) safeguards system. This approach can be used to identify the key monitoring locations, as well as locations where monitoring is unimportant. Detection limits at the key monitoring locations can also be established using this technique. Several faulty scenarios were developed to test the monitoring framework after the base case or normal operating conditions of the PCA model were established. In all of the scenarios, the monitoring framework was able to detect the fault. Overall this study was successful at meeting the stated objective.

  20. Integrated biomarker response in catfish Hypostomus ancistroides by multivariate analysis in the Pirapó River, southern Brazil.

    PubMed

    Ghisi, Nédia C; Oliveira, Elton C; Mendonça Mota, Thais F; Vanzetto, Guilherme V; Roque, Aliciane A; Godinho, Jayson P; Bettim, Franciele Lima; Silva de Assis, Helena Cristina da; Prioli, Alberto J

    2016-10-01

    Aquatic pollutants produce multiple consequences in organisms, populations, communities and ecosystems, affecting the function of organs, reproductive state, population size, species survival and even biodiversity. In order to monitor the health of aquatic organisms, biomarkers have been used as effective tools in environmental risk assessment. The aim of this study is to evaluate, through a multivariate and integrative analysis, the response of the native species Hypostomus ancistroides over a pollution gradient in the main water supply body of northwestern Paraná state (Brazil). The condition factor, micronucleus test and erythrocyte nuclear abnormalities (ENA), comet assay, measurement of the cerebral and muscular enzyme acetylcholinesterase (AChE), and histopathological analysis of liver and gill were evaluated in fishes from three sites of the Pirapó River during the dry and rainy seasons. The multivariate general result showed that the interaction between the seasons and the sites was significant: there are variations in the rates of alterations in the biological parameters, depending on the time of year researched at each site. In general, the best results were observed for the site nearest the spring, and alterations in the parameters at the intermediate and downstream sites. In sum, the results of this study showed the necessity of a multivariate analysis, evaluating several biological parameters, to obtain an integrated response to the effects of the environmental pollutants on the organisms. PMID:27421103

  1. Smart Sensor System for Structural Condition Monitoring of Wind Turbines: 30 May 2002--30 April 2006

    SciTech Connect

    Schulz, M. J.; Sundaresan, M. J.

    2006-08-01

    This report describes the efforts of the University of Cincinnati, North Carolina A&T State University, and NREL to develop a structural neural system for structural health monitoring of wind turbine blades.

  2. High-intensity focused ultrasound monitoring using harmonic motion imaging for focused ultrasound (HMIFU) under boiling or slow denaturation conditions.

    PubMed

    Hou, Gary Y; Marquet, Fabrice; Wang, Shutao; Apostolakis, Iason-Zacharias; Konofagou, Elisa E

    2015-07-01

    Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method that utilizes an amplitude-modulated therapeutic ultrasound beam to induce an oscillatory radiation force at the HIFU focus and estimates the focal tissue displacement to monitor the HIFU thermal treatment. In this study, the performance of HMIFU under acoustic, thermal, and mechanical effects was investigated. The performance of HMIFU was assessed in ex vivo canine liver specimens (n = 13) under slow denaturation or boiling regimes. A passive cavitation detector (PCD) was used to assess the acoustic cavitation activity, and a bare-wire thermocouple was used to monitor the focal temperature change. During lesioning with slow denaturation, high quality displacements (correlation coefficient above 0.97) were observed under minimum cavitation noise, indicating the tissue initial-softening-then- stiffening property change. During HIFU with boiling, HMIFU monitored a consistent change in lesion-to-background displacement contrast (0.46 ± 0.37) despite the presence of strong cavitation noise due to boiling during lesion formation. Therefore, HMIFU effectively monitored softening-then-stiffening during lesioning under slow denaturation, and detected lesioning under boiling with a distinct change in displacement contrast under boiling in the presence of cavitation. In conclusion, HMIFU was shown under both boiling and slow denaturation regimes to be effective in HIFU monitoring and lesioning identification without being significantly affected by cavitation noise. PMID:26168177

  3. A clamping force measurement system for monitoring the condition of bolted joints on railway track joints and points

    NASA Astrophysics Data System (ADS)

    Tesfa, B.; Horler, G.; Thobiani, F. Al; Gu, F.; Ball, A. D.

    2012-05-01

    can be developed to monitor the condition of bolted joints as found on railway track and points.

  4. Nuclear Energy Plant Optimization (NEPO) final report on aging and condition monitoring of low-voltage cable materials.

    SciTech Connect

    Assink, Roger Alan; Gillen, Kenneth Todd; Bernstein, Robert

    2005-11-01

    This report summarizes results generated on a 5-year cable-aging program that constituted part of the Nuclear Energy Plant Optimization (NEPO) program, an effort cosponsored by the U. S. Department of Energy (DOE) and the Electric Power Research Institute (EPRI). The NEPO cable-aging effort concentrated on two important issues involving the development of better lifetime prediction methods as well as the development and testing of novel cable condition-monitoring (CM) techniques. To address improved life prediction methods, we first describe the use of time-temperature superposition principles, indicating how this approach improves the testing of the Arrhenius model by utilizing all of the experimentally generated data instead of a few selected and processed data points. Although reasonable superposition is often found, we show several cases where non-superposition is evident, a situation that violates the constant acceleration assumption normally used in accelerated aging studies. Long-term aging results over extended temperature ranges allow us to show that curvature in Arrhenius plots for elongation is a common occurrence. In all cases the curvature results in a lowering of the Arrhenius activation energy at lower temperatures implying that typical extrapolation of high temperature results over-estimates material lifetimes. The long-term results also allow us to test the significance of extrapolating through the crystalline melting point of semi-crystalline materials. By utilizing ultrasensitive oxygen consumption (UOC) measurements, we show that it is possible to probe the low temperature extrapolation region normally inaccessible to conventional accelerated aging studies. This allows the quantitative testing of the often-used Arrhenius extrapolation assumption. Such testing indicates that many materials again show evidence of ''downward'' curvature (E{sub a} values drop as the aging temperature is lowered) consistent with the limited elongation results and

  5. Multivariate pluvial flood damage models

    SciTech Connect

    Van Ootegem, Luc; Verhofstadt, Elsy; Van Herck, Kristine; Creten, Tom

    2015-09-15

    Depth–damage-functions, relating the monetary flood damage to the depth of the inundation, are commonly used in the case of fluvial floods (floods caused by a river overflowing). We construct four multivariate damage models for pluvial floods (caused by extreme rainfall) by differentiating on the one hand between ground floor floods and basement floods and on the other hand between damage to residential buildings and damage to housing contents. We do not only take into account the effect of flood-depth on damage, but also incorporate the effects of non-hazard indicators (building characteristics, behavioural indicators and socio-economic variables). By using a Tobit-estimation technique on identified victims of pluvial floods in Flanders (Belgium), we take into account the effect of cases of reported zero damage. Our results show that the flood depth is an important predictor of damage, but with a diverging impact between ground floor floods and basement floods. Also non-hazard indicators are important. For example being aware of the risk just before the water enters the building reduces content damage considerably, underlining the importance of warning systems and policy in this case of pluvial floods. - Highlights: • Prediction of damage of pluvial floods using also non-hazard information • We include ‘no damage cases’ using a Tobit model. • The damage of flood depth is stronger for ground floor than for basement floods. • Non-hazard indicators are especially important for content damage. • Potential gain of policies that increase awareness of flood risks.

  6. Application of time-domain reflectometry to monitoring conditions in crushed tuff test plots at Los Alamos, New Mexico: Interpretation and recommendations for landfill monitoring

    SciTech Connect

    Filippone, C.L.; Schofield, T.G.

    1994-08-01

    Horizontal and vertical measurements of moisture content were obtained daily using time domain reflectometry (TDR) at four sites in two crushed tuff experimental plots over a period of 287 days. Moisture contents were also measured weekly at the same locations and at two additional locations in the plots using the neutron probe method. Results are assessed to determine the influence of waveguide length and waveguide orientation on TDR moisture content measurements, the degree of spatial variability in measured moisture content in this engineered porous material, and the ability of TDR to resolve vertical moisture content gradients. Recommendations are made for TDR instrumentation of mixed waste landfill monitoring systems.

  7. MULTIVARIATE ANALYSIS ON LEVELS OF SELECTED METALS, PARTICULATE MATTER, VOC, AND HOUSEHOLD CHARACTERISTICS AND ACTIVITIES FROM THE MIDWESTERN STATES NHEXAS

    EPA Science Inventory

    Microenvironmental and biological/personal monitoring information were collected during the National Human Exposure Assessment Survey (NHEXAS), conducted in the six states comprising U.S. EPA Region Five. They have been analyzed by multivariate analysis techniques with general ...

  8. Inclusion of Dominance Effects in the Multivariate GBLUP Model

    PubMed Central

    Vasconcellos, Renato Coelho de Castro; Pires, Luiz Paulo Miranda; Von Pinho, Renzo Garcia

    2016-01-01

    New proposals for models and applications of prediction processes with data on molecular markers may help reduce the financial costs of and identify superior genotypes in maize breeding programs. Studies evaluating Genomic Best Linear Unbiased Prediction (GBLUP) models including dominance effects have not been performed in the univariate and multivariate context in the data analysis of this crop. A single cross hybrid construction procedure was performed in this study using phenotypic data and actual molecular markers of 4,091 maize lines from the public database Panzea. A total of 400 simple hybrids resulting from this process were analyzed using the univariate and multivariate GBLUP model considering only additive effects additive plus dominance effects. Historic heritability scenarios of five traits and other genetic architecture settings were used to compare models, evaluating the predictive ability and estimation of variance components. Marginal differences were detected between the multivariate and univariate models. The main explanation for the small discrepancy between models is the low- to moderate-magnitude correlations between the traits studied and moderate heritabilities. These conditions do not favor the advantages of multivariate analysis. The inclusion of dominance effects in the models was an efficient strategy to improve the predictive ability and estimation quality of variance components. PMID:27074056

  9. Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data

    PubMed Central

    Liu, Zitao; Hauskrecht, Milos

    2016-01-01

    Building accurate predictive models of clinical multivariate time series is crucial for understanding of the patient condition, the dynamics of a disease, and clinical decision making. A challenging aspect of this process is that the model should be flexible and adaptive to reflect well patient-specific temporal behaviors and this also in the case when the available patient-specific data are sparse and short span. To address this problem we propose and develop an adaptive two-stage forecasting approach for modeling multivariate, irregularly sampled clinical time series of varying lengths. The proposed model (1) learns the population trend from a collection of time series for past patients; (2) captures individual-specific short-term multivariate variability; and (3) adapts by automatically adjusting its predictions based on new observations. The proposed forecasting model is evaluated on a real-world clinical time series dataset. The results demonstrate the benefits of our approach on the prediction tasks for multivariate, irregularly sampled clinical time series, and show that it can outperform both the population based and patient-specific time series prediction models in terms of prediction accuracy. PMID:27525189

  10. Estimating the decomposition of predictive information in multivariate systems.

    PubMed

    Faes, Luca; Kugiumtzis, Dimitris; Nollo, Giandomenico; Jurysta, Fabrice; Marinazzo, Daniele

    2015-03-01

    In the study of complex systems from observed multivariate time series, insight into the evolution of one system may be under investigation, which can be explained by the information storage of the system and the information transfer from other interacting systems. We present a framework for the model-free estimation of information storage and information transfer computed as the terms composing the predictive information about the target of a multivariate dynamical process. The approach tackles the curse of dimensionality employing a nonuniform embedding scheme that selects progressively, among the past components of the multivariate process, only those that contribute most, in terms of conditional mutual information, to the present target process. Moreover, it computes all information-theoretic quantities using a nearest-neighbor technique designed to compensate the bias due to the different dimensionality of individual entropy terms. The resulting estimators of prediction entropy, storage entropy, transfer entropy, and partial transfer entropy are tested on simulations of coupled linear stochastic and nonlinear deterministic dynamic processes, demonstrating the superiority of the proposed approach over the traditional estimators based on uniform embedding. The framework is then applied to multivariate physiologic time series, resulting in physiologically well-interpretable information decompositions of cardiovascular and cardiorespiratory interactions during head-up tilt and of joint brain-heart dynamics during sleep. PMID:25871169

  11. Inclusion of Dominance Effects in the Multivariate GBLUP Model.

    PubMed

    Dos Santos, Jhonathan Pedroso Rigal; Vasconcellos, Renato Coelho de Castro; Pires, Luiz Paulo Miranda; Balestre, Marcio; Von Pinho, Renzo Garcia

    2016-01-01

    New proposals for models and applications of prediction processes with data on molecular markers may help reduce the financial costs of and identify superior genotypes in maize breeding programs. Studies evaluating Genomic Best Linear Unbiased Prediction (GBLUP) models including dominance effects have not been performed in the univariate and multivariate context in the data analysis of this crop. A single cross hybrid construction procedure was performed in this study using phenotypic data and actual molecular markers of 4,091 maize lines from the public database Panzea. A total of 400 simple hybrids resulting from this process were analyzed using the univariate and multivariate GBLUP model considering only additive effects additive plus dominance effects. Historic heritability scenarios of five traits and other genetic architecture settings were used to compare models, evaluating the predictive ability and estimation of variance components. Marginal differences were detected between the multivariate and univariate models. The main explanation for the small discrepancy between models is the low- to moderate-magnitude correlations between the traits studied and moderate heritabilities. These conditions do not favor the advantages of multivariate analysis. The inclusion of dominance effects in the models was an efficient strategy to improve the predictive ability and estimation quality of variance components. PMID:27074056

  12. Estimating the decomposition of predictive information in multivariate systems

    NASA Astrophysics Data System (ADS)

    Faes, Luca; Kugiumtzis, Dimitris; Nollo, Giandomenico; Jurysta, Fabrice; Marinazzo, Daniele

    2015-03-01

    In the study of complex systems from observed multivariate time series, insight into the evolution of one system may be under investigation, which can be explained by the information storage of the system and the information transfer from other interacting systems. We present a framework for the model-free estimation of information storage and information transfer computed as the terms composing the predictive information about the target of a multivariate dynamical process. The approach tackles the curse of dimensionality employing a nonuniform embedding scheme that selects progressively, among the past components of the multivariate process, only those that contribute most, in terms of conditional mutual information, to the present target process. Moreover, it computes all information-theoretic quantities using a nearest-neighbor technique designed to compensate the bias due to the different dimensionality of individual entropy terms. The resulting estimators of prediction entropy, storage entropy, transfer entropy, and partial transfer entropy are tested on simulations of coupled linear stochastic and nonlinear deterministic dynamic processes, demonstrating the superiority of the proposed approach over the traditional estimators based on uniform embedding. The framework is then applied to multivariate physiologic time series, resulting in physiologically well-interpretable information decompositions of cardiovascular and cardiorespiratory interactions during head-up tilt and of joint brain-heart dynamics during sleep.

  13. Multivariate Analysis of Ladle Vibration

    NASA Astrophysics Data System (ADS)

    Yenus, Jaefer; Brooks, Geoffrey; Dunn, Michelle

    2016-05-01

    The homogeneity of composition and uniformity of temperature of the steel melt before it is transferred to the tundish are crucial in making high-quality steel product. The homogenization process is performed by stirring the melt using inert gas in ladles. Continuous monitoring of this process is important to make sure the action of stirring is constant throughout the ladle. Currently, the stirring process is monitored by process operators who largely rely on visual and acoustic phenomena from the ladle. However, due to lack of measurable signals, the accuracy and suitability of this manual monitoring are problematic. The actual flow of argon gas to the ladle may not be same as the flow gage reading due to leakage along the gas line components. As a result, the actual degree of stirring may not be correctly known. Various researchers have used one-dimensional vibration, and sound and image signals measured from the ladle to predict the degree of stirring inside. They developed online sensors which are indeed to monitor the online stirring phenomena. In this investigation, triaxial vibration signals have been measured from a cold water model which is a model of an industrial ladle. Three flow rate ranges and varying bath heights were used to collect vibration signals. The Fast Fourier Transform was applied to the dataset before it has been analyzed using principal component analysis (PCA) and partial least squares (PLS). PCA was used to unveil the structure in the experimental data. PLS was mainly applied to predict the stirring from the vibration response. It was found that for each flow rate range considered in this study, the informative signals reside in different frequency ranges. The first latent variables in these frequency ranges explain more than 95 pct of the variation in the stirring process for the entire single layer and the double layer data collected from the cold model. PLS analysis in these identified frequency ranges demonstrated that the latent

  14. Multivariate Analysis of Ladle Vibration

    NASA Astrophysics Data System (ADS)

    Yenus, Jaefer; Brooks, Geoffrey; Dunn, Michelle

    2016-08-01

    The homogeneity of composition and uniformity of temperature of the steel melt before it is transferred to the tundish are crucial in making high-quality steel product. The homogenization process is performed by stirring the melt using inert gas in ladles. Continuous monitoring of this process is important to make sure the action of stirring is constant throughout the ladle. Currently, the stirring process is monitored by process operators who largely rely on visual and acoustic phenomena from the ladle. However, due to lack of measurable signals, the accuracy and suitability of this manual monitoring are problematic. The actual flow of argon gas to the ladle may not be same as the flow gage reading due to leakage along the gas line components. As a result, the actual degree of stirring may not be correctly known. Various researchers have used one-dimensional vibration, and sound and image signals measured from the ladle to predict the degree of stirring inside. They developed online sensors which are indeed to monitor the online stirring phenomena. In this investigation, triaxial vibration signals have been measured from a cold water model which is a model of an industrial ladle. Three flow rate ranges and varying bath heights were used to collect vibration signals. The Fast Fourier Transform was applied to the dataset before it has been analyzed using principal component analysis (PCA) and partial least squares (PLS). PCA was used to unveil the structure in the experimental data. PLS was mainly applied to predict the stirring from the vibration response. It was found that for each flow rate range considered in this study, the informative signals reside in different frequency ranges. The first latent variables in these frequency ranges explain more than 95 pct of the variation in the stirring process for the entire single layer and the double layer data collected from the cold model. PLS analysis in these identified frequency ranges demonstrated that the latent

  15. Advanced multivariate analysis to assess remediation of hydrocarbons in soils.

    PubMed

    Lin, Deborah S; Taylor, Peter; Tibbett, Mark

    2014-10-01

    Accurate monitoring of degradation levels in soils is essential in order to understand and achieve complete degradation of petroleum hydrocarbons in contaminated soils. We aimed to develop the use of multivariate methods for the monitoring of biodegradation of diesel in soils and to determine if diesel contaminated soils could be remediated to a chemical composition similar to that of an uncontaminated soil. An incubation experiment was set up with three contrasting soil types. Each soil was exposed to diesel at varying stages of degradation and then analysed for key hydrocarbons throughout 161 days of incubation. Hydrocarbon distributions were analysed by Principal Coordinate Analysis and similar samples grouped by cluster analysis. Variation and differences between samples were determined using permutational multivariate analysis of variance. It was found that all soils followed trajectories approaching the chemical composition of the unpolluted soil. Some contaminated soils were no longer significantly different to that of uncontaminated soil after 161 days of incubation. The use of cluster analysis allows the assignment of a percentage chemical similarity of a diesel contaminated soil to an uncontaminated soil sample. This will aid in the monitoring of hydrocarbon contaminated sites and the establishment of potential endpoints for successful remediation. PMID:25028320

  16. Multivariate analysis of the volumetric capnograph for PaCO2 estimation

    PubMed Central

    Belenkiy, Slava M; Baker, William L; Batchinsky, Andriy I; Mittal, Sumit; Watkins, Taylor; Salinas, Jose; Cancio, Leopoldo C

    2015-01-01

    Purpose: End-tidal CO2 (eTCO2) can be used to estimate the arterial CO2 (PaCO2) under steady-state conditions, but that relationship deteriorates during hemodynamic or respiratory instability. We developed a multivariate method to improve our ability to estimate the PaCO2, by using additional information contained in the volumetric capnograph (Vcap) waveform. We tested this approach using data from a porcine model of chest trauma/hemorrhage. Methods: This experiment consisted of 3 stages: pre-injury, injury/resuscitation, and post-injury. In stage I, anesthetized pigs (n=26) underwent ventilator maneuvers (tidal volume and respiratory rate) to induce hypo-or hyper-ventilation. In stage II, pigs underwent either (A) unilateral pulmonary contusion, hemorrhage, and resuscitation (n=13); or (B) bilateral pulmonary contusion (n=13) followed by 30 min of monitoring. In stage III, the ventilator maneuvers were repeated. The following Vcap features were measured: eTCO2, phase 2 slope (p2m), phase 3 slope (p3m), and inter-breath interval. The data were fit to 2 models: (1) multivariate linear regression and (2) a machine-learning model (M5P). Results: 1750 10-breath sets were analyzed. Univariate models employing eTCO2 alone were adequate during stages I and III. During stage II, mean error for the linear model was -8.44 mmHg (R2=0.14, P<0.001) and for M5P it was -5.98 mmHg (R2=0.13, P<0.01). By adding Vcap features, all models exhibited improvement. In stage II, the mean error of the linear model improved to -4.64 mmHg (R2=0.11, P<0.01), and that of the M5P model improved to -1.62 mmHg (R2=0.25, P<0.01). Conclusions: By incorporating Vcap waveform features, multivariate methods modestly improved PaCO2 estimation, especially during periods of hemodynamic and respiratory instability. Further work would be needed to produce a clinically useful CO2 monitoring system under these challenging conditions. PMID:26550531

  17. Multivariate models of adult Pacific salmon returns.

    PubMed

    Burke, Brian J; Peterson, William T; Beckman, Brian R; Morgan, Cheryl; Daly, Elizabeth A; Litz, Marisa

    2013-01-01

    Most modeling and statistical approaches encourage simplicity, yet ecological processes are often complex, as they are influenced by numerous dynamic environmental and biological factors. Pacific salmon abundance has been highly variable over the last few decades and most forecasting models have proven inadequate, primarily because of a lack of understanding of the processes affecting variability in survival. Better methods and data for predicting the abundance of returning adults are therefore required to effectively manage the species. We combined 31 distinct indicators of the marine environment collected over an 11-year period into a multivariate analysis to summarize and predict adult spring Chinook salmon returns to the Columbia River in 2012. In addition to forecasts, this tool quantifies the strength of the relationship between various ecological indicators and salmon returns, allowing interpretation of ecosystem processes. The relative importance of indicators varied, but a few trends emerged. Adult returns of spring Chinook salmon were best described using indicators of bottom-up ecological processes such as composition and abundance of zooplankton and fish prey as well as measures of individual fish, such as growth and condition. Local indicators of temperature or coastal upwelling did not contribute as much as large-scale indicators of temperature variability, matching the spatial scale over which salmon spend the majority of their ocean residence. Results suggest that effective management of Pacific salmon requires multiple types of data and that no single indicator can represent the complex early-ocean ecology of salmon. PMID:23326586

  18. Multivariate Models of Adult Pacific Salmon Returns

    PubMed Central

    Burke, Brian J.; Peterson, William T.; Beckman, Brian R.; Morgan, Cheryl; Daly, Elizabeth A.; Litz, Marisa

    2013-01-01

    Most modeling and statistical approaches encourage simplicity, yet ecological processes are often complex, as they are influenced by numerous dynamic environmental and biological factors. Pacific salmon abundance has been highly variable over the last few decades and most forecasting models have proven inadequate, primarily because of a lack of understanding of the processes affecting variability in survival. Better methods and data for predicting the abundance of returning adults are therefore required to effectively manage the species. We combined 31 distinct indicators of the marine environment collected over an 11-year period into a multivariate analysis to summarize and predict adult spring Chinook salmon returns to the Columbia River in 2012. In addition to forecasts, this tool quantifies the strength of the relationship between various ecological indicators and salmon returns, allowing interpretation of ecosystem processes. The relative importance of indicators varied, but a few trends emerged. Adult returns of spring Chinook salmon were best described using indicators of bottom-up ecological processes such as composition and abundance of zooplankton and fish prey as well as measures of individual fish, such as growth and condition. Local indicators of temperature or coastal upwelling did not contribute as much as large-scale indicators of temperature variability, matching the spatial scale over which salmon spend the majority of their ocean residence. Results suggest that effective management of Pacific salmon requires multiple types of data and that no single indicator can represent the complex early-ocean ecology of salmon. PMID:23326586

  19. Improving Ground Motion Simulation Capabilities for Underground Explosion Monitoring: Coupling Hydrodynamic-To Solvers and Studies of Emplacement Conditions

    NASA Astrophysics Data System (ADS)

    Xu, H.; Rodgers, A.; Lomov, I.; Petersson, A.; Sjogreen, B.; Vorobiev, O.; Chipman, V.

    2011-12-01

    We report research being performed to improve underground nuclear explosion (UNE) monitoring by developing capabilities for hydrodynamic modeling of ground motions. This effort involves work along two thrusts: 1) we are coupling hydrodynamic (non-linear shock) and seismic (linear anelastic) wave propagation codes; and 2) we are investigating the effect of source emplacement conditions on ground motions in the near field due to nonlinearity and comparing with the empirical models. For both thrusts we are modeling explosion motions using GEODYN, a fully three-dimensional Eulerian hydrodynamic code developed at LLNL. This code incorporates many important features for modeling shock waves in geologic materials, including non-linear response (e.g. porosity, tensile failure, yielding), topography, gravity, 3D material heterogeneities and adaptive mesh refinement. The calculation accuracy is well validated with the analytical solutions to the Lamb's problem and to the finite dilatational volume source at depth in a linear elastic medium. In order to propagate full waveform solutions from hydrodynamic simulations to distances where seismic measurements are made we are coupling GEODYN to WPP (LLNL's anelastic finite difference code for seismic wave simulation). Complex motions computed by GEODYN for explosions are recorded on a dense grid spanning the ranges where motions become linear (elastic). These wavefield records are processed and embedded into the WPP domain where they are introduced as a boundary driving source and continue to propagate as elastic waves at much lower numerical cost than with nonlinear GEODYN. The coupling scheme is validated by comparing the analytical, direct GEODYN solutions and WPP solutions to the finite dilatational volume source at depth in a linear elastic medium, and also by comparing the direct GEODYN solutions and WPP solutions to a complex 1kt chemical explosion in nonlinear granite at stations beyond the elastic radius. The excellent

  20. FINAL REPORT. INVESTIGATIONS OF TECHNIQUES TO IMPROVE CONTINUOUS AIR MONITORS UNDER CONDITIONS OF HIGH DUST LOADING IN ENVIRONMENTAL SETTINGS

    EPA Science Inventory

    The overall objective was to carry out studies to improve the detection of plutonium aerosols by environmental continuous air monitors (ECAMs), particularly in dusty environments. A number of alpha-particle ECAMs are used at DOE sites such as Los Alamos National Laboratory (LANL)...