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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. Assessment of infrared spectroscopy and multivariate techniques for monitoring the service condition of diesel-engine lubricating oils.

    PubMed

    Caneca, Arnobio Roberto; Pimentel, M Fernanda; Galvão, Roberto Kawakami Harrop; da Matta, Cláudia Eliane; de Carvalho, Florival Rodrigues; Raimundo, Ivo M; Pasquini, Celio; Rohwedder, Jarbas J R

    2006-09-15

    This paper presents two methodologies for monitoring the service condition of diesel-engine lubricating oils on the basis of infrared spectra. In the first approach, oils samples are discriminated into three groups, each one associated to a given wear stage. An algorithm is proposed to select spectral variables with good discriminant power and small collinearity for the purpose of discriminant analysis classification. As a result, a classification accuracy of 93% was obtained both in the middle (MIR) and near-infrared (NIR) ranges. The second approach employs multivariate calibration methods to predict the viscosity of the lubricant. In this case, the use of absorbance measurements in the NIR spectral range was not successful, because of experimental difficulties associated to the presence of particulate matter. Such a problem was circumvented by the use of attenuated total reflectance (ATR) measurements in the MIR spectral range, in which an RMSEP of 3.8cSt and a relative average error of 3.2% were attained.

  3. Monitoring of technical oils in supercritical CO(2) under continuous flow conditions by NIR spectroscopy and multivariate calibration.

    PubMed

    Bürck, J; Wiegand, G; Roth, S; Mathieu, H; Krämer, K

    2006-02-28

    Metal parts and residues from machining processes are usually polluted with cutting or grinding oil and have to be cleaned before further use. Supercritical carbon dioxide can be used for extraction processes and precision cleaning of metal parts, as developed at Forschungszentrum Karlsruhe. For optimizing and efficiently conducting the extraction process, in-line analysis of oil concentration is desirable. Therefore, a monitoring method using fiber-optic NIR spectroscopy in combination with PLS calibration has been developed. In an earlier paper we have described the instrumental set-up and a calibration model using the model compound squalane in the spectral range of the CH combination bands from 4900 to 4200cm(-1). With this model only poor prediction results were obtained if applied to technical oil samples in supercritical CO(2). In this paper we describe a new calibration model, which was set up for the squalane/carbon dioxide system covering the 323-353K temperature and the 16-35.6MPa pressure range. Here, calibration data in the spectral range from 6100 to 5030cm(-1) have been used. This range includes the 5100cm(-1) CO(2) band of the Fermi triad as well as the hydrocarbon 1st overtone CH stretching bands, where spectral features of oil compounds and squalane are more similar to each other. The root mean-squared error of prediction obtained with this model is 4mgcm(-3) for carbon dioxide and 0.4mgcm(-3) for squalane, respectively. The utilizability of the newly developed PLS calibration model for predicting the oil concentration and CO(2) density of solutions of technical oils in supercritical carbon dioxide has been tested. Three types of "real world" cutting and grinding oil formulations were used in these experiments. The calibration proved to be suitable for determining the technical oil concentration with an error of 1.1mgcm(-3) and the CO(2) density with an error of 6mgcm(-3). Therefore, it seems possible to apply this in-line analytical approach on

  4. 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

  5. Multivariate statistical monitoring and diagnosis with applications in semiconductor processes

    NASA Astrophysics Data System (ADS)

    Yue, Hongyu

    Modern chemical processes generate a tremendous amount of measurement data that could be used for process monitoring. Deviation of the process measurements from the specifications could indicate an abnormal condition. It is important to have an effective technique to detect, identify and correct the fault. Because of the correlation of the sensor data, multivariate statistical methods are preferred for process monitoring. In the semiconductor manufacturing industry, many processes have been monitored in a univariate and off-line fashion. Due to the increasing complexity and shrinking feature size of integrated circuits, real-time monitoring by analysis of tool measurements is required to detect and classify faults. This dissertation focuses on developing process monitoring techniques and applications in plasma etching and rapid thermal annealing processes. While principal component analysis (PCA) has found wide application in process monitoring, slow and normal changes often occur in real processes, which lead to false alarms for a fixed-model approach. Recursive PCA is proposed for adaptive process monitoring. Two algorithms are developed to update the model efficiently. Although it is relatively easy to detect a fault, fault identification is a more complicated task. A combined index is first proposed for fault detection and identification. It is shown that the identification result is more accurate than other existing methods. The methods are applied in monitoring a rapid thermal annealing process. Plasma etching is one of the most important processes. It is considered one of the yield limiter because of the occurrence of frequent faults. Tight process monitoring is therefore required to detect the process endpoint and faults. This research uses optical emission spectroscopy sensors to collect high-resolution spectra data. PCA is used to analyze the data for the purpose of low-open area endpoint detection and fault detection. New methods are developed for

  6. An intelligent system for multivariate statistical process monitoring and diagnosis.

    PubMed

    Tatara, Eric; Cinar, Ali

    2002-04-01

    A knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real-time KBS consists of a supervisory system using G2 KBS development software linked with external statistical modules for system identification and sensor fault diagnosis. The various statistical techniques were prototyped in MATLAB, converted to ANSI C code, and linked with the G2 Standard Interface. The KBS automatically performs all operations of data collection, identification, monitoring, and sensor fault diagnosis with little or no input from the user. Navigation throughout the KBS is via menu buttons on each user-accessible screen. Selected process variables are displayed on charts showing the history of the variables over a period of time. Multivariate statistical tests and contribution plots are also shown graphically. The KBS was evaluated using simulation studies with a polymerization reactor through a nonlinear dynamic model. Both normal operation conditions as well as conditions of process disturbances were observed to evaluate the KBS performance. Specific user-defined disturbances were added to the simulation, and the KBS correctly diagnosed both process and sensor faults when present.

  7. An extended multivariate framework for drought monitoring in Mexico

    NASA Astrophysics Data System (ADS)

    Real-Rangel, Roberto; Pedrozo-Acuña, Adrián; Breña-Naranjo, Agustín; Alcocer-Yamanaka, Víctor

    2017-04-01

    Around the world, monitoring natural hazards, such as droughts, represents a critical task in risk assessment and management plans. A reliable drought monitoring system allows to identify regions affected by these phenomena so that early response measures can be implemented. In Mexico, this activity is performed using Mexico's Drought Monitor, which is based on a similar methodology as the United States Drought Monitor and the North American Drought Monitor. The main feature of these monitoring systems is the combination of ground-based and remote sensing observations that is ultimately validated by local experts. However, in Mexico in situ records of variables such as precipitation and streamflow are often scarce, or even null, in many regions of the country. Another issue that adds uncertainty in drought monitoring is the arbitrary weight given to each analyzed variable. This study aims at providing an operational framework for drought monitoring in Mexico, based on univariate and multivariate nonparametric standardized indexes proposed in recent studies. Furthermore, the framework has been extended by taking into account the Enhanced Vegetation Index (EVI) for the drought severity assessment. The analyzed variables used for computing the drought indexes are mainly derived from remote sensing (MODIS) and land surface models datasets (NASA MERRA-2). A qualitative evaluation of the results shows that the indexes used are capable of adequately describes the intensity and spatial distribution of past drought documented events.

  8. Multivariate Drought Characterization in India for Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Sreekumaran Unnithan, P.; Mondal, A.

    2016-12-01

    Droughts are one of the most important natural hazards that affect the society significantly in terms of mortality and productivity. The metric that is most widely used by the India Meteorological Department (IMD) to monitor and predict the occurrence, spread, intensification and termination of drought is based on the univariate Standardized Precipitation Index (SPI). However, droughts may be caused by the influence and interaction of many variables (such as precipitation, soil moisture, runoff, etc.), emphasizing the need for a multivariate approach for drought characterization. This study advocates and illustrates use of the recently proposed multivariate standardized drought index (MSDI) in monitoring and prediction of drought and assessing its concerned risk in the Indian region. MSDI combines information from multiple sources: precipitation and soil moisture, and has been deemed to be a more reliable drought index. All-India monthly rainfall and soil moisture data sets are analysed for the period 1980 to 2014 to characterize historical droughts using both the univariate indices, the precipitation-based SPI and the standardized soil moisture index (SSI), as well as the multivariate MSDI using parametric and non-parametric approaches. We confirm that MSDI can capture droughts of 1986 and 1990 that aren't detected by using SPI alone. Moreover, in 1987, MSDI indicated a higher severity of drought when a deficiency in both soil moisture and precipitation was encountered. Further, this study also explores the use of MSDI for drought forecasts and assesses its performance vis-à-vis existing predictions from the IMD. Future research efforts will be directed towards formulating a more robust standardized drought indicator that can take into account socio-economic aspects that also play a key role for water-stressed regions such as India.

  9. 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.

  10. Multivariate image analysis for process monitoring and control

    NASA Astrophysics Data System (ADS)

    MacGregor, John F.; Bharati, Manish H.; Yu, Honglu

    2001-02-01

    Information from on-line imaging sensors has great potential for the monitoring and control of quality in spatially distributed systems. The major difficulty lies in the efficient extraction of information from the images, information such as the frequencies of occurrence of specific and often subtle features, and their locations in the product or process space. This paper presents an overview of multivariate image analysis methods based on Principal Component Analysis and Partial Least Squares for decomposing the highly correlated data present in multi-spectral images. The frequencies of occurrence of certain features in the image, regardless of their spatial locations, can be easily monitored in the space of the principal components. The spatial locations of these features can then be obtained by transposing highlighted pixels from the PC score space into the original image space. In this manner it is possible to easily detect and locate even very subtle features from on-line imaging sensors for the purpose of statistical process control or feedback control of spatial processes. The concepts and potential of the approach are illustrated using a sequence of LANDSAT satellite multispectral images, depicting a pass over a certain region of the earth's surface. Potential applications in industrial process monitoring using these methods will be discussed from a variety of areas such as pulp and paper sheet products, lumber and polymer films.

  11. 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.

  12. 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.

  13. SUGGESTIONS FOR OPTIMIZED PLANNING OF MULTIVARIATE MONITORING OF ATMOSPHERIC POLLUTION

    EPA Science Inventory

    Recent work in factor analysis of multivariate data sets has shown that variables with little signal should not be included in the factor analysis. Work also shows that rotational ambiguity is reduced if sources impacting a receptor have both large and small contributions. Thes...

  14. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. 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…

  16. 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.

  17. 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.

  18. Advanced optical condition monitoring. [of rocket engines

    NASA Technical Reports Server (NTRS)

    Cross, G.; Barkhoudarian, S.

    1991-01-01

    The application of Advanced Optical Condition Monitoring to optical leak detection and plume spectrometry is discussed. The development of these selected sensors for propulsion system monitoring is addressed.

  19. 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.

  20. 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.

  1. Modeling and monitoring of a high pressure polymerization process using multivariate statistical techniques

    NASA Astrophysics Data System (ADS)

    Sharmin, Rumana

    This thesis explores the use of multivariate statistical techniques in developing tools for property modeling and monitoring of a high pressure ethylene polymerization process. In polymer industry, many researchers have shown, mainly in simulation studies, the potential of multivariate statistical methods in identification and control of polymerization process. However, very few, if any, of these strategies have been implemented. This work was done using data collected from a commercial high pressure LDPE/EVA reactor located at AT Plastics, Edmonton. The models or methods developed in the course of this research have been validated with real data and in most cases, implemented in real time. One main objective of this PhD project was to develop and implement a data based inferential sensor to estimate the melt flow index of LDPE and EVA resins using regularly measured process variables. Steady state PLS method was used to develop the soft sensor model. A detailed description of the data preprocessing steps are given that should be followed in the analysis of industrial data. Models developed for two of the most frequently produced polymer grades at AT Plastics have been implemented. The models were tested for many sets of data and showed acceptable performance when applied with an online bias updating scheme. One observation from many validation exercises was that the model prediction becomes poorer with time as operators use new process conditions in the plant to produce the same resin with the same specification. During the implementation of the soft sensors, we suggested a simple bias update scheme as a remedy to this problem. An alternative and more rigorous approach is to recursively update the model with new data, which is also more suitable to handle grade transition. Two existing recursive PLS methods, one based on NIPALS algorithm and the other based on kernel algorithm were reviewed. In addition, we proposed a novel RPLS algorithm which is based on the

  2. 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. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Dynamic molecular monitoring of retina inflammation by in vivo Raman spectroscopy coupled with multivariate analysis.

    PubMed

    Marro, Monica; Taubes, Alice; Abernathy, Alice; Balint, Stephan; Moreno, Beatriz; Sanchez-Dalmau, Bernardo; Martínez-Lapiscina, Elena H; Amat-Roldan, Ivan; Petrov, Dmitri; Villoslada, Pablo

    2014-09-01

    Retinal tissue is damaged during inflammation in Multiple Sclerosis. We assessed molecular changes in inflamed murine retinal cultures by Raman spectroscopy. Partial Least Squares-Discriminant analysis (PLS-DA) was able to classify retina cultures as inflamed with high accuracy. Using Multivariate Curve Resolution (MCR) analysis, we deconvolved 6 molecular components suffering dynamic changes along inflammatory process. Those include the increase of immune mediators (Lipoxygenase, iNOS and TNFα), changes in molecules involved in energy production (Cytochrome C, phenylalanine and NADH/NAD+) and decrease of Phosphatidylcholine. Raman spectroscopy combined with multivariate analysis allows monitoring the evolution of retina inflammation.

  4. A multivariate probabilistic graphical model for real-time volcano monitoring on Mount Etna

    NASA Astrophysics Data System (ADS)

    Cannavò, Flavio; Cannata, Andrea; Cassisi, Carmelo; Di Grazia, Giuseppe; Montalto, Placido; Prestifilippo, Michele; Privitera, Eugenio; Coltelli, Mauro; Gambino, Salvatore

    2017-05-01

    Real-time assessment of the state of a volcano plays a key role for civil protection purposes. Unfortunately, because of the coupling of highly nonlinear and partially known complex volcanic processes, and the intrinsic uncertainties in measured parameters, the state of a volcano needs to be expressed in probabilistic terms, thus making any rapid assessment sometimes impractical. With the aim of aiding on-duty personnel in volcano-monitoring roles, we present an expert system approach to automatically estimate the ongoing state of a volcano from all available measurements. The system consists of a probabilistic model that encodes the conditional dependencies between measurements and volcanic states in a directed acyclic graph and renders an estimation of the probability distribution of the feasible volcanic states. We test the model with Mount Etna (Italy) as a case study by considering a long record of multivariate data. Results indicate that the proposed model is effective for early warning and has considerable potential for decision-making purposes.

  5. Coupling GIS and multivariate approaches to reference site selection for wadeable stream monitoring.

    PubMed

    Collier, Kevin J; Haigh, Andy; Kelly, Johlene

    2007-04-01

    Geographic Information System (GIS) was used to identify potential reference sites for wadeable stream monitoring, and multivariate analyses were applied to test whether invertebrate communities reflected a priori spatial and stream type classifications. We identified potential reference sites in segments with unmodified vegetation cover adjacent to the stream and in >85% of the upstream catchment. We then used various landcover, amenity and environmental impact databases to eliminate sites that had potential anthropogenic influences upstream and that fell into a range of access classes. Each site identified by this process was coded by four dominant stream classes and seven zones, and 119 candidate sites were randomly selected for follow-up assessment. This process yielded 16 sites conforming to reference site criteria using a conditional-probabilistic design, and these were augmented by an additional 14 existing or special interest reference sites. Non-metric multidimensional scaling (NMS) analysis of percent abundance invertebrate data indicated significant differences in community composition among some of the zones and stream classes identified a priori providing qualified support for this framework in reference site selection. NMS analysis of a range standardised condition and diversity metrics derived from the invertebrate data indicated a core set of 26 closely related sites, and four outliers that were considered atypical of reference site conditions and subsequently dropped from the network. Use of GIS linked to stream typology, available spatial databases and aerial photography greatly enhanced the objectivity and efficiency of reference site selection. The multi-metric ordination approach reduced variability among stream types and bias associated with non-random site selection, and provided an effective way to identify representative reference sites.

  6. 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.

  7. Integrated environmental monitoring and multivariate data analysis-A case study.

    PubMed

    Eide, Ingvar; Westad, Frank; Nilssen, Ingunn; de Freitas, Felipe Sales; Dos Santos, Natalia Gomes; Dos Santos, Francisco; Cabral, Marcelo Montenegro; Bicego, Marcia Caruso; Figueira, Rubens; Johnsen, Ståle

    2017-03-01

    The present article describes integration of environmental monitoring and discharge data and interpretation using multivariate statistics, principal component analysis (PCA), and partial least squares (PLS) regression. The monitoring was carried out at the Peregrino oil field off the coast of Brazil. One sensor platform and 3 sediment traps were placed on the seabed. The sensors measured current speed and direction, turbidity, temperature, and conductivity. The sediment trap samples were used to determine suspended particulate matter that was characterized with respect to a number of chemical parameters (26 alkanes, 16 PAHs, N, C, calcium carbonate, and Ba). Data on discharges of drill cuttings and water-based drilling fluid were provided on a daily basis. The monitoring was carried out during 7 campaigns from June 2010 to October 2012, each lasting 2 to 3 months due to the capacity of the sediment traps. The data from the campaigns were preprocessed, combined, and interpreted using multivariate statistics. No systematic difference could be observed between campaigns or traps despite the fact that the first campaign was carried out before drilling, and 1 of 3 sediment traps was located in an area not expected to be influenced by the discharges. There was a strong covariation between suspended particulate matter and total N and organic C suggesting that the majority of the sediment samples had a natural and biogenic origin. Furthermore, the multivariate regression showed no correlation between discharges of drill cuttings and sediment trap or turbidity data taking current speed and direction into consideration. Because of this lack of correlation with discharges from the drilling location, a more detailed evaluation of chemical indicators providing information about origin was carried out in addition to numerical modeling of dispersion and deposition. The chemical indicators and the modeling of dispersion and deposition support the conclusions from the multivariate

  8. 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.

  9. OTVE combustor wall condition monitoring

    NASA Technical Reports Server (NTRS)

    Szemenyei, Brian; Nelson, Robert S.; Barkhoudarian, S.

    1989-01-01

    Conventional ultrasonics, eddy current, and electromagnetic acoustic transduction (EMAT) technologies were evaluated to determine their capability of measuring wall thickness/wear of individual cooling channels in test specimens simulating conditions in the throat region of an OTVE combustion chamber liner. Quantitative results are presented for the eddy current technology, which was shown to measure up to the optimum 20-mil wall thickness with near single channel resolution. Additional results demonstrate the capability of the conventional ultrasonics and EMAT technologies to detect a thinning or cracked wall. Recommendations for additional eddy current and EMAT development tests are presented.

  10. Survey of Condition Indicators for Condition Monitoring Systems (Open Access)

    DTIC Science & Technology

    2014-09-29

    algorithm was applied to stabilize the shaft speed before the extraction of bearing condition indicators. Several case studies of real world wind turbine ...monitoring techniques are very capable of detecting component fault signatures at high speed or intermediate sections of the wind turbine while acoustic...Renewable Energy Laboratory (NREL) published a document named ‘ Wind Turbine Gearbox Condition Monitoring Round Robin Study – Vibration Analysis’ in 2012

  11. An advanced condition monitoring system for turbopumps

    NASA Technical Reports Server (NTRS)

    Cross, George S.; Barkhoudarian, Sarkis

    1991-01-01

    Advanced condition monitoring (ACM) technologies developed for in situ turbomachinery applications are reviewed. The ACM concepts are based on direct in situ hardware monitoring and between-flight inspections, using novel real-time, automated, noncontacting, and nonintrusive sensor and associated electronic technologies.

  12. 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.

  13. Combining multivariate statistics and analysis of variance to redesign a water quality monitoring network.

    PubMed

    Guigues, Nathalie; Desenfant, Michèle; Hance, Emmanuel

    2013-09-01

    The objective of this paper was to demonstrate how multivariate statistics combined with the analysis of variance could support decision-making during the process of redesigning a water quality monitoring network with highly heterogeneous datasets in terms of time and space. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were selected to optimise the selection of water quality parameters to be monitored as well as the number and location of monitoring stations. Sampling frequency was specifically investigated through the analysis of variance. The data used were obtained between 2007 and 2010 at the Long-term Environmental Research Monitoring and Testing System (OPE) located in the north-eastern part of France in relation with a geological disposal of radioactive waste project. PCA results showed that no substantial reduction among the parameters was possible as strong correlation only exists between electrical conductivity, calcium or bicarbonates. HCA results were geospatially represented for each field campaign and compared to one another in terms of similarities and differences allowing us to group the monitoring stations into 12 categories. This approach enabled us to take into account not only the spatial variability of water quality but also its temporal variability. Finally, the analysis of variances showed that three very different behaviours occurred: parameters with high temporal variability and low spatial variability (e.g. suspended matter), parameters with high spatial variability and average temporal variability (e.g. calcium) and finally parameters with both high temporal and spatial variability (e.g. nitrate).

  14. Application of in-line near infrared spectroscopy and multivariate batch modeling for process monitoring in fluid bed granulation.

    PubMed

    Kona, Ravikanth; Qu, Haibin; Mattes, Robert; Jancsik, Bela; Fahmy, Raafat M; Hoag, Stephen W

    2013-08-16

    Fluid bed is an important unit operation in pharmaceutical industry for granulation and drying. To improve our understanding of fluid bed granulation, in-line near infrared spectroscopy (NIRS) and novel environmental temperature and RH data logger called a PyroButton(®) were used in conjunction with partial least square (PLS) and principal component analysis (PCA) to develop multivariate statistical process control charts (MSPC). These control charts were constructed using real-time moisture, temperature and humidity data obtained from batch experiments. To demonstrate their application, statistical control charts such as Scores, Distance to model (DModX), and Hotelling's T(2) were used to monitor the batch evolution process during the granulation and subsequent drying phase; moisture levels were predicted using a validated PLS model. Two data loggers were placed one near the bottom of the granulator bowl plenum where air enters the granulator and another inside the granulator in contact with the product in the fluid bed helped to monitor the humidity and temperature levels during the granulation and drying phase. The control charts were used for real time fault analysis, and were tested on normal batches and on three batches which deviated from normal processing conditions. This study demonstrated the use of NIRS and the use of humidity and temperature data loggers in conjunction with multivariate batch modeling as an effective tool in process understanding and fault determining method to effective process control in fluid bed granulation.

  15. 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.

  16. 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.

  17. Monitoring, fault detection and operation prediction of MSW incinerators using multivariate statistical methods.

    PubMed

    Tavares, Gilberto; Zsigraiová, Zdena; Semiao, Viriato; Carvalho, Maria da Graca

    2011-07-01

    This work proposes the application of two multivariate statistical methods, principal component analysis (PCA) and partial least square (PLS), to a continuous process of a municipal solid waste (MSW) moving grate-type incinerator for process control--monitoring, fault detection and diagnosis--through the extraction of information from historical data. PCA model is built for process monitoring capable of detecting abnormal situations and the original 16-variable process dimension is reduced to eight, the first 4 being able to capture together 86% of the total process variation. PLS model is constructed to predict the generated superheated steam flow rate allowing for control of its set points. The model retained six of the original 13 variables, explaining together 90% of the input variation and almost 98% of the output variation. The proposed methodology is demonstrated by applying those multivariate statistical methods to process data continuously measured in an actual incinerator. Both models exhibited very good performance in fault detection and isolation. In predicting the generated superheated steam flow rate for its set point control the PLS model performed very well with low prediction errors (RMSE of 3.1 and 4.1).

  18. Multivariate statistical process control (MSPC) using Raman spectroscopy for in-line culture cell monitoring considering time-varying batches synchronized with correlation optimized warping (COW).

    PubMed

    Liu, Ya-Juan; André, Silvère; Saint Cristau, Lydia; Lagresle, Sylvain; Hannas, Zahia; Calvosa, Éric; Devos, Olivier; Duponchel, Ludovic

    2017-02-01

    Multivariate statistical process control (MSPC) is increasingly popular as the challenge provided by large multivariate datasets from analytical instruments such as Raman spectroscopy for the monitoring of complex cell cultures in the biopharmaceutical industry. However, Raman spectroscopy for in-line monitoring often produces unsynchronized data sets, resulting in time-varying batches. Moreover, unsynchronized data sets are common for cell culture monitoring because spectroscopic measurements are generally recorded in an alternate way, with more than one optical probe parallelly connecting to the same spectrometer. Synchronized batches are prerequisite for the application of multivariate analysis such as multi-way principal component analysis (MPCA) for the MSPC monitoring. Correlation optimized warping (COW) is a popular method for data alignment with satisfactory performance; however, it has never been applied to synchronize acquisition time of spectroscopic datasets in MSPC application before. In this paper we propose, for the first time, to use the method of COW to synchronize batches with varying durations analyzed with Raman spectroscopy. In a second step, we developed MPCA models at different time intervals based on the normal operation condition (NOC) batches synchronized by COW. New batches are finally projected considering the corresponding MPCA model. We monitored the evolution of the batches using two multivariate control charts based on Hotelling's T(2) and Q. As illustrated with results, the MSPC model was able to identify abnormal operation condition including contaminated batches which is of prime importance in cell culture monitoring We proved that Raman-based MSPC monitoring can be used to diagnose batches deviating from the normal condition, with higher efficacy than traditional diagnosis, which would save time and money in the biopharmaceutical industry. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Minimizing maintenance with oil condition monitoring

    SciTech Connect

    2005-09-01

    Oil condition monitoring (OCM) involves the analysis of oil samples taken at specific points in the equipment at regular intervals. The condition of the oil, its pace of deterioration and the presence of contaminants provide important indicators of component wear or equipment failure. Shell Lubricants has developed a number of bespoke tests to meet equipment and operative requirements. 1 fig.

  20. Machine condition monitoring using principal component representations

    NASA Astrophysics Data System (ADS)

    He, Qingbo; Yan, Ruqiang; Kong, Fanrang; Du, Ruxu

    2009-02-01

    The purpose of this paper is to find the low-dimensional principal component (PC) representations from the statistical features of the measured signals to characterize and hence, monitor machine conditions. The PC representations can be automatically extracted using the principal component analysis (PCA) technique from the time- and frequency-domains statistical features of the measured signals. First, a mean correlation rule is proposed to evaluate the capability of each of the PCs in characterizing machine conditions and to select the most representative PCs to classify machine fault patterns. Then a procedure that uses the low-dimensional PC representations for machine condition monitoring is proposed. The experimental results from an internal-combustion engine sound analysis and an automobile gearbox vibration analysis show that the proposed method is effective for machine condition monitoring.

  1. Integrated condition monitoring of space information network

    NASA Astrophysics Data System (ADS)

    Wang, Zhilin; Li, Xinming; Li, Yachen; Yu, Shaolin

    2015-11-01

    In order to solve the integrated condition monitoring problem in space information network, there are three works finished including analyzing the characteristics of tasks process and system health monitoring, adopting the automata modeling method, and respectively establishing the models for state inference and state determination. The state inference model is a logic automaton and is gotten by concluding engineering experiences. The state determination model is a double-layer automaton, the lower automaton is responsible for parameter judge and the upper automaton is responsible for state diagnosis. At last, the system state monitoring algorithm has been proposed, which realizes the integrated condition monitoring for task process and system health, and can avoid the false alarm.

  2. Reusable rocket engine turbopump condition monitoring

    NASA Technical Reports Server (NTRS)

    Hampson, M. E.

    1984-01-01

    Significant improvements in engine readiness with reductions in maintenance costs and turn-around times can be achieved with an engine condition monitoring systems (CMS). The CMS provides health status of critical engine components, without disassembly, through monitoring with advanced sensors. Engine failure reports over 35 years were categorized into 20 different modes of failure. Rotor bearings and turbine blades were determined to be the most critical in limiting turbopump life. Measurement technologies were matched to each of the failure modes identified. Three were selected to monitor the rotor bearings and turbine blades: the isotope wear detector and fiberoptic deflectometer (bearings), and the fiberoptic pyrometer (blades). Signal processing algorithms were evaluated for their ability to provide useful health data to maintenance personnel. Design modifications to the Space Shuttle Main Engine (SSME) high pressure turbopumps were developed to incorporate the sensors. Laboratory test fixtures have been designed for monitoring the rotor bearings and turbine blades in simulated turbopump operating conditions.

  3. Implementation of multivariate cumulative sum control charts in mastitis and lameness monitoring.

    PubMed

    Miekley, Bettina; Stamer, Eckhard; Traulsen, Imke; Krieter, Joachim

    2013-09-01

    This study analyzed the methodology and applicability of multivariate cumulative sum (MCUSUM) charts for early mastitis and lameness detection. Data used were recorded on the Karkendamm dairy research farm, Germany, between August 2008 and December 2010. Data of 328 and 315 cows in their first 200 d in milk were analyzed for mastitis and lameness detection, respectively. Mastitis as well as lameness was specified according to veterinary treatments. Both diseases were defined as disease blocks. Different disease definitions for mastitis and lameness (2 for mastitis and 3 for lameness) varied solely in the sequence length of the blocks. Only the days before the treatment were included in the disease blocks. Milk electrical conductivity, milk yield, and feeding patterns (feed intake, number of trough visits, and feeding time) were used for the recognition of mastitis. Pedometer activity and feeding patterns were used for lameness detection. To exclude biological trends and obtain independent observations, the values of each input variable were either preprocessed by wavelet filters or a multivariate vector autoregressive model. The residuals generated between the observed and filtered or observed and forecast values, respectively, were then transferred to a classic or self-starting MCUSUM chart. The combination of the 2 preprocessing methods with each of the 2 MCUSUM sum charts resulted in 4 combined monitoring systems. For mastitis as well as lameness detection requiring a block sensitivity of at least 70%, all 4 of the combined monitoring systems used revealed similar results within each of the disease definitions. Specificities of 73 to 80% and error rates of 99.6% were achieved for mastitis. The results for lameness showed that the definitions used obtained specificities of up to 81% and error rates of 99.1%. The results indicate that the monitoring systems with these study characteristics have appealing features for mastitis and lameness detection. However, they

  4. Linking multimetric and multivariate approaches to assess the ecological condition of streams.

    PubMed

    Collier, Kevin J

    2009-10-01

    Few attempts have been made to combine multimetric and multivariate analyses for bioassessment despite recognition that an integrated method could yield powerful tools for bioassessment. An approach is described that integrates eight macroinvertebrate community metrics into a Principal Components Analysis to develop a Multivariate Condition Score (MCS) from a calibration dataset of 511 samples. The MCS is compared to an Index of Biotic Integrity (IBI) derived using the same metrics based on the ratio to the reference site mean. Both approaches were highly correlated although the MCS appeared to offer greater potential for discriminating a wider range of impaired conditions. Both the MCS and IBI displayed low temporal variability within reference sites, and were able to distinguish between reference conditions and low levels of catchment modification and local habitat degradation, although neither discriminated among three levels of low impact. Pseudosamples developed to test the response of the metric aggregation approaches to organic enrichment, urban, mining, pastoral and logging stressor scenarios ranked pressures in the same order, but the MCS provided a lower score for the urban scenario and a higher score for the pastoral scenario. The MCS was calculated for an independent test dataset of urban and reference sites, and yielded similar results to the IBI. Although both methods performed comparably, the MCS approach may have some advantages because it removes the subjectivity of assigning thresholds for scoring biological condition, and it appears to discriminate a wider range of degraded conditions.

  5. Multivariate DPOAE metrics for identifying changes in hearing: Perspectives from ototoxicity monitoring

    PubMed Central

    Konrad-Martin, Dawn; Reavis, Kelly M.; McMillan, Garnett P.; Dille, Marilyn F.

    2017-01-01

    Distortion-product otoacoustic emissions (DPOAEs) provide a window into real-time cochlear mechanical function. Yet, relationships between the changes in DPOAE metrics and auditory sensitivity are still poorly understood. Explicating these relationships might support the use of DPOAEs in hearing conservation programs (HCPs) for detecting early damage leading to noise-induced hearing loss (NIHL) so that mitigating steps might be taken to limit any lasting damage. This report describes the development of DPOAE-based statistical models to assess the risk of hearing loss from cisplatin treatment among cancer patients. Ototoxicity risk assessment (ORA) models were constructed using a machine learning paradigm in which partial least squares and leave-one-out cross-validation were applied, yielding optimal screening algorithms from a set of known risk factors for ototoxicity and DPOAE changes from pre-exposure baseline measures. Single DPOAE metrics alone were poorer indicators of the risk of ototoxic hearing shifts than the best performing multivariate models. This finding suggests that multivariate approaches applied to the use of DPOAEs in a HCP, will improve the ability of DPOAE measures to identify ears with noise-induced mechanical damage and/or hearing loss at each monitoring interval. This prediction must be empirically assessed in noise-exposed subjects. PMID:22264063

  6. 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.

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

    PubMed

    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.

  8. 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.

  9. 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

  10. Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data.

    PubMed

    Chen, Yonghong; Bressler, Steven L; Ding, Mingzhou

    2006-01-30

    It is often useful in multivariate time series analysis to determine statistical causal relations between different time series. Granger causality is a fundamental measure for this purpose. Yet the traditional pairwise approach to Granger causality analysis may not clearly distinguish between direct causal influences from one time series to another and indirect ones acting through a third time series. In order to differentiate direct from indirect Granger causality, a conditional Granger causality measure in the frequency domain is derived based on a partition matrix technique. Simulations and an application to neural field potential time series are demonstrated to validate the method.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. Online Condition Monitoring mit der Stresswellenanalyse

    NASA Astrophysics Data System (ADS)

    Bruderreck, Frank

    Die Anforderungen des heutigen Energiemarkts und damit einhergehende veränderte Einsatzbedingungen für ältere Kraftwerksblöcke haben unvorhergesehene Produktionsausfälle in den letzten Jahren erheblich verteuert. Nach der Optimierung der Kraftwerksprozesse und der Steigerung der Wirkungsgrade richten die Energieversorger ihren Blick daher nun verstärkt auch auf die Verfügbarkeit ihrer Anlagen. Zur Verbesserung der Anlagenverfügbarkeit und der Minimierung der Instandhaltungskosten bietet sich der Einsatz von Condition Monitoring Systemen an. Nach der Erprobung eines Systems zur Vibrationsanalyse setzt die Evonik Steag GmbH jetzt in einem Pilotprojekt die Stresswellenanalyse ein, ein Online Condition Monitoring System auf der Basis von Ultraschallsensoren. Dieser Beitrag erläutert an einem Beispiel die Methode und grenzt sie gegen den De-facto-Standard Vibrationsanalyse ab.

  18. 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.

  19. Reusable rocket engine optical condition monitoring

    NASA Technical Reports Server (NTRS)

    Wyett, L.; Maram, J.; Barkhoudarian, S.; Reinert, J.

    1987-01-01

    Plume emission spectrometry and optical leak detection are described as two new applications of optical techniques to reusable rocket engine condition monitoring. Plume spectrometry has been used with laboratory flames and reusable rocket engines to characterize both the nominal combustion spectra and anomalous spectra of contaminants burning in these plumes. Holographic interferometry has been used to identify leaks and quantify leak rates from reusable rocket engine joints and welds.

  20. Electrical condition monitoring method for polymers

    DOEpatents

    Watkins, Jr., Kenneth S.; Morris, Shelby J [Hampton, VA; Masakowski, Daniel D [Worcester, MA; Wong, Ching Ping [Duluth, GA; Luo, Shijian [Boise, ID

    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.

  1. Bayesian inference of genetic parameters based on conditional decompositions of multivariate normal distributions.

    PubMed

    Hallander, Jon; Waldmann, Patrik; Wang, Chunkao; Sillanpää, Mikko J

    2010-06-01

    It is widely recognized that the mixed linear model is an important tool for parameter estimation in the analysis of complex pedigrees, which includes both pedigree and genomic information, and where mutually dependent genetic factors are often assumed to follow multivariate normal distributions of high dimension. We have developed a Bayesian statistical method based on the decomposition of the multivariate normal prior distribution into products of conditional univariate distributions. This procedure permits computationally demanding genetic evaluations of complex pedigrees, within the user-friendly computer package WinBUGS. To demonstrate and evaluate the flexibility of the method, we analyzed two example pedigrees: a large noninbred pedigree of Scots pine (Pinus sylvestris L.) that includes additive and dominance polygenic relationships and a simulated pedigree where genomic relationships have been calculated on the basis of a dense marker map. The analysis showed that our method was fast and provided accurate estimates and that it should therefore be a helpful tool for estimating genetic parameters of complex pedigrees quickly and reliably.

  2. 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

  3. Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India).

    PubMed

    Mavukkandy, Musthafa Odayooth; Karmakar, Subhankar; Harikumar, P S

    2014-09-01

    The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented. Significant multivariate statistical techniques like principal component analysis (PCA) and principal factor analysis (PFA) have been employed to evaluate the efficiency of the surface water quality monitoring network with monitoring stations as the evaluated variables for the interpretation of complex data matrix of the river basin. The main objective is to identify significant monitoring stations that must essentially be included in assessing annual and seasonal variations of river water quality. Moreover, the significance of seasonal redesign of the monitoring network was also investigated to capture valuable information on water quality from the network. Results identified few monitoring stations as insignificant in explaining the annual variance of the dataset. Moreover, the seasonal redesign of the monitoring network through a multivariate statistical framework was found to capture valuable information from the system, thus making the network more efficient. Cluster analysis (CA) classified the sampling sites into different groups based on similarity in water quality characteristics. The PCA/PFA identified significant latent factors standing for different pollution sources such as organic pollution, industrial pollution, diffuse pollution and faecal contamination. Thus, the present study illustrates that various multivariate statistical techniques can be effectively employed in sustainable management of water resources. The effectiveness of existing river water quality monitoring

  4. Monitoring batch-to-batch reproducibility of liquid-liquid extraction process using in-line near-infrared spectroscopy combined with multivariate analysis.

    PubMed

    Xiong, Haoshu; Gong, Xingchu; Qu, Haibin

    2012-11-01

    Traditional Chinese medicine (TCM) products are usually manufactured through batch processes. To improve batch-to-batch reproducibility, the feasible approaches for real-time monitoring of batch evolution need to be developed. In-line near-infrared (NIR) spectroscopy combined with multivariate data analysis as an efficient process analytical technology (PAT) tool, is presented in this study for real-time batch process monitoring. Liquid-liquid extraction is a widely used purification technology in the TCM manufacture, and selected as the example to demonstrate the effectiveness of this PAT tool. Multi-way partial least squares (MPLS) model was developed based on in-line measured NIR spectral data of ten normal operation condition (NOC) batches. Three kinds of multivariate control charts (scores, Hotelling T(2) and DModX) were used to monitor the evolution of six test batches with artificial batch variations, including the change of starting material quality attributes and abnormal operation conditions. The approach was found very effective for real-time monitoring of process deviations from NOC batches. It is an alternative promising tool for monitoring batch reproducibility of the unit operations during the manufacture of TCM. Copyright © 2012 Elsevier B.V. All rights reserved.

  5. [Near infrared spectroscopy and multivariate statistical process analysis for real-time monitoring of production process].

    PubMed

    Wang, Yi; Ma, Xiang; Wen, Ya-Dong; Zou, Quan; Wang, Jun; Tu, Jia-Run; Cai, Wen-Sheng; Shao, Xue-Guang

    2013-05-01

    Near infrared diffusive reflectance spectroscopy has been applied in on-site or on-line analysis due to its characteristics of fastness, non-destruction and the feasibility for real complex sample analysis. The present work reported a real-time monitoring method for industrial production by using near infrared spectroscopic technique and multivariate statistical process analysis. In the method, the real-time near infrared spectra of the materials are collected on the production line, and then the evaluation of the production process can be achieved by a statistic Hotelling T2 calculated with the established model. In this work, principal component analysis (PCA) is adopted for building the model, and the statistic is calculated by projecting the real-time spectra onto the PCA model. With an application of the method in a practical production, it was demonstrated that a real-time evaluation of the variations in the production can be realized by investigating the changes in the statistic, and the comparison of the products in different batches can be achieved by further statistics of the statistic. Therefore, the proposed method may provide a practical way for quality insurance of production processes.

  6. Condition monitoring of rotary blood pumps.

    PubMed

    Jammu, V B; Malanoski, S; Walter, T; Smith, W

    1997-01-01

    Long-term, trouble-free operation of ventricular assist devices (VADs) is critical to the patient. A catastrophic failure of the VAD could cost the patient's life, thus defeating the purpose of the device. The targeted 90% 5 year reliability also implies that the average device life would exceed the 5 year limit. Time based explantation of the device after the fifth year will replace many devices with significant additional life, subject the patient to unnecessary surgical risk, and increase costs. To preclude the need for time based replacements and prevent catastrophic failures, a condition monitor is proposed in this article for early detection of faults in VADs. To develop this monitor, the effectiveness of various sensing and monitoring methods for determining the VAD condition is investigated. A Hemadyne pump was instrumented with a set of eight sensors, and a series of experiments were performed to record and analyze signals from the normal and abnormal pumps with five different faults. Statistical, spectral, envelope, and ensemble averaging analyses were performed to characterize changes in sensor signals due to faults. Experimental results indicate that statistical and frequency information from the acceleration and dynamic pressure signals can clearly detect and identify various VAD faults.

  7. 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.

  8. 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.

  9. Condition monitoring of multistage printing presses

    NASA Astrophysics Data System (ADS)

    Wang, W.; Golnaraghi, F.; Ismail, F.

    2004-03-01

    The main concern in printing quality in multistage presses is doubling. Doubling is caused by imperfections either within stages (units) or in links connecting different stages, mainly resulting from machine vibration, gear damage, and excessive run-out. In this paper, we propose new means for printing quality control via geared system health condition monitoring. The diagnosis is based on the signals acquired from inexpensive magnetic pickups. A new technique is developed to monitor the gear rotation synchronization among different stages in order to isolate possible sources of the doubling problem. A new approach is proposed to determine the gear run-out. Moreover, gear tooth damage detection is conducted using the beta kurtosis and the continuous wavelet transform based on the overall residual signal. The beta kurtosis of original signal average is also shown here to be useful in detecting excessive gear run-out. Test results from printing presses demonstrated the viability of the proposed methods.

  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. Assessment of metals bioavailability to vegetables under field conditions using DGT, single extractions and multivariate statistics.

    PubMed

    Senila, Marin; Levei, Erika Andrea; Senila, Lacrimioara Ramona

    2012-10-18

    The metals bioavailability in soils is commonly assessed by chemical extractions; however a generally accepted method is not yet established. In this study, the effectiveness of Diffusive Gradients in Thin-films (DGT) technique and single extractions in the assessment of metals bioaccumulation in vegetables, and the influence of soil parameters on phytoavailability were evaluated using multivariate statistics. Soil and plants grown in vegetable gardens from mining-affected rural areas, NW Romania, were collected and analysed. Pseudo-total metal content of Cu, Zn and Cd in soil ranged between 17.3-146 mg kg-1, 141-833 mg kg-1 and 0.15-2.05 mg kg-1, respectively, showing enriched contents of these elements. High degrees of metals extractability in 1M HCl and even in 1M NH4Cl were observed. Despite the relatively high total metal concentrations in soil, those found in vegetables were comparable to values typically reported for agricultural crops, probably due to the low concentrations of metals in soil solution (Csoln) and low effective concentrations (CE), assessed by DGT technique. Among the analysed vegetables, the highest metal concentrations were found in carrots roots. By applying multivariate statistics, it was found that CE, Csoln and extraction in 1M NH4Cl, were better predictors for metals bioavailability than the acid extractions applied in this study. Copper transfer to vegetables was strongly influenced by soil organic carbon (OC) and cation exchange capacity (CEC), while pH had a higher influence on Cd transfer from soil to plants. The results showed that DGT can be used for general evaluation of the risks associated to soil contamination with Cu, Zn and Cd in field conditions. Although quantitative information on metals transfer from soil to vegetables was not observed.

  12. Assessment of metals bioavailability to vegetables under field conditions using DGT, single extractions and multivariate statistics

    PubMed Central

    2012-01-01

    Background The metals bioavailability in soils is commonly assessed by chemical extractions; however a generally accepted method is not yet established. In this study, the effectiveness of Diffusive Gradients in Thin-films (DGT) technique and single extractions in the assessment of metals bioaccumulation in vegetables, and the influence of soil parameters on phytoavailability were evaluated using multivariate statistics. Soil and plants grown in vegetable gardens from mining-affected rural areas, NW Romania, were collected and analysed. Results Pseudo-total metal content of Cu, Zn and Cd in soil ranged between 17.3-146 mg kg-1, 141–833 mg kg-1 and 0.15-2.05 mg kg-1, respectively, showing enriched contents of these elements. High degrees of metals extractability in 1M HCl and even in 1M NH4Cl were observed. Despite the relatively high total metal concentrations in soil, those found in vegetables were comparable to values typically reported for agricultural crops, probably due to the low concentrations of metals in soil solution (Csoln) and low effective concentrations (CE), assessed by DGT technique. Among the analysed vegetables, the highest metal concentrations were found in carrots roots. By applying multivariate statistics, it was found that CE, Csoln and extraction in 1M NH4Cl, were better predictors for metals bioavailability than the acid extractions applied in this study. Copper transfer to vegetables was strongly influenced by soil organic carbon (OC) and cation exchange capacity (CEC), while pH had a higher influence on Cd transfer from soil to plants. Conclusions The results showed that DGT can be used for general evaluation of the risks associated to soil contamination with Cu, Zn and Cd in field conditions. Although quantitative information on metals transfer from soil to vegetables was not observed. PMID:23079133

  13. 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.

  14. 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…

  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. 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

  17. Transcriptome and Multivariable Data Analysis of Corynebacterium glutamicum under Different Dissolved Oxygen Conditions in Bioreactors

    PubMed Central

    Sun, Yang; Guo, Wenwen; Wang, Fen; Peng, Feng; Yang, Yankun; Dai, Xiaofeng; Liu, Xiuxia; Bai, Zhonghu

    2016-01-01

    Dissolved oxygen (DO) is an important factor in the fermentation process of Corynebacterium glutamicum, which is a widely used aerobic microbe in bio-industry. Herein, we described RNA-seq for C. glutamicum under different DO levels (50%, 30% and 0%) in 5 L bioreactors. Multivariate data analysis (MVDA) models were used to analyze the RNA-seq and metabolism data to investigate the global effect of DO on the transcriptional distinction of the substance and energy metabolism of C. glutamicum. The results showed that there were 39 and 236 differentially expressed genes (DEGs) under the 50% and 0% DO conditions, respectively, compared to the 30% DO condition. Key genes and pathways affected by DO were analyzed, and the result of the MVDA and RNA-seq revealed that different DO levels in the fermenter had large effects on the substance and energy metabolism and cellular redox balance of C. glutamicum. At low DO, the glycolysis pathway was up-regulated, and TCA was shunted by the up-regulation of the glyoxylate pathway and over-production of amino acids, including valine, cysteine and arginine. Due to the lack of electron-acceptor oxygen, 7 genes related to the electron transfer chain were changed, causing changes in the intracellular ATP content at 0% and 30% DO. The metabolic flux was changed to rebalance the cellular redox. This study applied deep sequencing to identify a wealth of genes and pathways that changed under different DO conditions and provided an overall comprehensive view of the metabolism of C. glutamicum. The results provide potential ways to improve the oxygen tolerance of C. glutamicum and to modify the metabolic flux for amino acid production and heterologous protein expression. PMID:27907077

  18. Transcriptome and Multivariable Data Analysis of Corynebacterium glutamicum under Different Dissolved Oxygen Conditions in Bioreactors.

    PubMed

    Sun, Yang; Guo, Wenwen; Wang, Fen; Peng, Feng; Yang, Yankun; Dai, Xiaofeng; Liu, Xiuxia; Bai, Zhonghu

    2016-01-01

    Dissolved oxygen (DO) is an important factor in the fermentation process of Corynebacterium glutamicum, which is a widely used aerobic microbe in bio-industry. Herein, we described RNA-seq for C. glutamicum under different DO levels (50%, 30% and 0%) in 5 L bioreactors. Multivariate data analysis (MVDA) models were used to analyze the RNA-seq and metabolism data to investigate the global effect of DO on the transcriptional distinction of the substance and energy metabolism of C. glutamicum. The results showed that there were 39 and 236 differentially expressed genes (DEGs) under the 50% and 0% DO conditions, respectively, compared to the 30% DO condition. Key genes and pathways affected by DO were analyzed, and the result of the MVDA and RNA-seq revealed that different DO levels in the fermenter had large effects on the substance and energy metabolism and cellular redox balance of C. glutamicum. At low DO, the glycolysis pathway was up-regulated, and TCA was shunted by the up-regulation of the glyoxylate pathway and over-production of amino acids, including valine, cysteine and arginine. Due to the lack of electron-acceptor oxygen, 7 genes related to the electron transfer chain were changed, causing changes in the intracellular ATP content at 0% and 30% DO. The metabolic flux was changed to rebalance the cellular redox. This study applied deep sequencing to identify a wealth of genes and pathways that changed under different DO conditions and provided an overall comprehensive view of the metabolism of C. glutamicum. The results provide potential ways to improve the oxygen tolerance of C. glutamicum and to modify the metabolic flux for amino acid production and heterologous protein expression.

  19. EDF experiences in maintenance and condition monitoring

    SciTech Connect

    Zwingelstein, G.; Godin, R. )

    1989-01-01

    Maintenance is one of the key elements in a reliable, economic and flexible electricity generation program. Electricite de France, operating more than 100 units (fossil and nuclear), defined several years ago and applies a policy for its maintenance activities. The development of new maintenance concepts such as preventive,condition-directed or predictive maintenance has led EDF to undertake a research program in these areas. This paper presents the current status of the maintenance policy, the research and development program for valves, rotating machines, instrumentation and control systems. In conclusion, comments are made on the trends and the future organization of the maintenance activities taking into account the integrated diagnostic and on-line monitoring center.

  20. Functioning condition monitoring of industrial equipment

    NASA Astrophysics Data System (ADS)

    Ungureanu, N. S.; Petrovan, A.; Ungureanu, M.; Alexandrescu, M.

    2017-02-01

    The paper analyses the theoretical aspects related to monitoring industrial equipment. Are treated issues that concern the choosing of industrial equipment to be monitored, the parameters to be monitored, monitoring mode (local or remote) and the mode of collection and transmission of data.

  1. Multivariate Analysis of Mixed Lipid Aggregate Phase Transitions Monitored Using Raman Spectroscopy.

    PubMed

    Neal, Sharon L

    2017-01-01

    The phase behavior of aqueous 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC)/1,2-dihexanoyl-sn-glycero-3-phosphocholine (DHPC) mixtures between 8.0 ℃ and 41.0 ℃ were monitored using Raman spectroscopy. Temperature-dependent Raman matrices were assembled from series of spectra and subjected to multivariate analysis. The consensus of pseudo-rank estimation results is that seven to eight components account for the temperature-dependent changes observed in the spectra. The spectra and temperature response profiles of the mixture components were resolved by applying a variant of the non-negative matrix factorization (NMF) algorithm described by Lee and Seung (1999). The rotational ambiguity of the data matrix was reduced by augmenting the original temperature-dependent spectral matrix with its cumulative counterpart, i.e., the matrix formed by successive integration of the spectra across the temperature index (columns). Successive rounds of constrained NMF were used to isolate component spectra from a significant fluorescence background. Five major components exhibiting varying degrees of gel and liquid crystalline lipid character were resolved. Hydrogen-bonded water networks exhibiting varying degrees of organization are associated with the lipid components. Spectral parameters were computed to compare the chain conformation, packing, and hydration indicated by the resolved spectra. Based on spectral features and relative amounts of the components observed, four components reflect long chain lipid response. The fifth component could reflect the response of the short chain lipid, DHPC, but there were no definitive spectral features confirming this assignment. A minor component of uncertain assignment that exhibits a striking response to the DMPC pre-transition and chain melting transition also was recovered. While none of the spectra resolved exhibit features unequivocally attributable to a specific aggregate morphology or step in the gelation process

  2. Multivariable Sensors for Ubiquitous Monitoring of Gases in the Era of Internet of Things and Industrial Internet.

    PubMed

    Potyrailo, Radislav A

    2016-10-12

    Modern gas monitoring scenarios for medical diagnostics, environmental surveillance, industrial safety, and other applications demand new sensing capabilities. This Review provides analysis of development of new generation of gas sensors based on the multivariable response principles. Design criteria of these individual sensors involve a sensing material with multiresponse mechanisms to different gases and a multivariable transducer with independent outputs to recognize these different gas responses. These new sensors quantify individual components in mixtures, reject interferences, and offer more stable response over sensor arrays. Such performance is attractive when selectivity advantages of classic gas chromatography, ion mobility, and mass spectrometry instruments are canceled by requirements for no consumables, low power, low cost, and unobtrusive form factors for Internet of Things, Industrial Internet, and other applications. This Review is concluded with a perspective for future needs in fundamental and applied aspects of gas sensing and with the 2025 roadmap for ubiquitous gas monitoring.

  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. 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.

  5. 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.

  6. 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.

  7. Multivariate geomorphic analysis of forest streams: Implications for assessment of land use impacts on channel condition

    Treesearch

    Richard. D. Wood-Smith; John M. Buffington

    1996-01-01

    Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10...

  8. FT-IR/ATR univariate and multivariate calibration models for in situ monitoring of sugars in complex microalgal culture media.

    PubMed

    Girard, Jean-Michel; Deschênes, Jean-Sébastien; Tremblay, Réjean; Gagnon, Jonathan

    2013-09-01

    The objective of this work is to develop a quick and simple method for the in situ monitoring of sugars in biological cultures. A new technology based on Attenuated Total Reflectance-Fourier Transform Infrared (FT-IR/ATR) spectroscopy in combination with an external light guiding fiber probe was tested, first to build predictive models from solutions of pure sugars, and secondly to use those models to monitor the sugars in the complex culture medium of mixotrophic microalgae. Quantification results from the univariate model were correlated with the total dissolved solids content (R(2)=0.74). A vector normalized multivariate model was used to proportionally quantify the different sugars present in the complex culture medium and showed a predictive accuracy of >90% for sugars representing >20% of the total. This method offers an alternative to conventional sugar monitoring assays and could be used at-line or on-line in commercial scale production systems.

  9. 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.

  10. New insight into monitoring degradation products during the TiO2-photocatalysis process by multivariate molecular spectroscopy.

    PubMed

    Stets, Sandra; do Amaral, Bianca; Bach, Larissa; Nagata, Noemi; Peralta-Zamora, Patricio G

    2017-03-01

    This study focuses on the feasibility of a spectroscopic multivariate method for monitoring the concentration of phenol and its main degradation products during heterogeneous photocatalysis. Phenolic compounds were chosen as model to evaluate the degradation process due to their toxicity and persistence in the environment and also their well-known degradation pathway. The predictive capability of the multivariate method developed by partial least squares regression (PLSR) over the spectral range of 200-350 nm was satisfactory, allowing mean predicted errors below 5.0 % in the simultaneous determination of the target compounds using six latent variables and smoothing spectra. Suitable results were reported for the simultaneous determination of hydroquinone, resorcinol, pyrocatechol, and p-benzoquinone in accordance to the chromatographic method. Characteristics such as simplicity, low cost, and fast data acquisition are remarkable in this procedure, which makes it appropriate for this type of analytical control.

  11. Application of Multivariate Statistical Methods to Optimize Water Quality Monitoring Network with Emphasis on the Pollution Caused by Fish Farms.

    PubMed

    Tavakol, Mitra; Arjmandi, Reza; Shayeghi, Mansoureh; Monavari, Seyed Masoud; Karbassi, Abdolreza

    2017-01-01

    One of the key issues in determining the quality of water in rivers is to create a water quality control network with a suitable performance. The measured qualitative variables at stations should be representative of all the changes in water quality in water systems. Since the increase in water quality monitoring stations increases annual monitoring costs, recognition of the stations with higher importance as well as main parameters can be effective in future decisions to improve the existing monitoring network. Sampling was carried out on 12 physical and chemical parameters measured at 15 stations during 2013-2014 in Haraz River, northern Iran. The results of the measurements were analyzed using multivariate statistical analysis methods including cluster analysis (CA), principal component analysis (PCA), factor analysis (FA), and discriminant analysis (DA). According to the CA, PCA, and FA, the stations were divided into three groups of high pollution, medium pollution, and low pollution. The research findings confirm applicability of multivariate statistical techniques in the interpretation of large data sets, water quality assessment, and source apportionment of different pollution sources.

  12. Multivariate control charts based on net analyte signal and near infrared spectroscopy for quality monitoring of Nimesulide in pharmaceutical formulations

    NASA Astrophysics Data System (ADS)

    Fortunato de Carvalho Rocha, Wérickson; Luis Rosa, André; Antônio Martins, José; Poppi, Ronei Jesus

    2010-10-01

    Multivariate control charts based on the net analytical signal, in conjunction with near infrared spectroscopy, were developed to monitor the quality of a pharmaceutical formulation containing Nimesulide. Three control charts were developed: the NAS chart that corresponds to the analyte of interest (Nimesulide in this case), the interference chart that corresponds to the contribution of other compounds in the sample and the residual chart that corresponds to nonsystematic variation. From the limits estimated for each chart using samples inside the quality specifications, it was possible to identify the samples that were outside the specifications concerning Nimesulide concentration and to identify the presence of different constituents in the standard formulation.

  13. Application of near infrared spectroscopy and multivariate control charts for monitoring biodiesel blends.

    PubMed

    de Oliveira, Ingrid Komorizono; Rocha, Wérickson F de Carvalho; Poppi, Ronei J

    2009-05-29

    Multivariate control charts in conjunction with near infrared spectroscopy were developed to verify the quality of biodiesel blends (2% of biodiesel and 98% of diesel). The control charts were built using the net analyte signal method, generating three charts: the NAS chart that corresponds to the analyte of interest (biodiesel in this case), the interference chart that corresponds to the contribution of other compounds in the sample (diesel in this case) and the residual chart that corresponds to nonsystematic variations. For each chart, statistical limits were developed using samples inside the quality specifications. It was possible to identify biodiesel blend samples that were out of specifications relative to biodiesel content, biodiesel contaminated with vegetable oil and diesel contaminated with naphtha.

  14. Monitoring of the surface of paper samples exposed to UV light by ATR-FT-IR spectroscopy and use of multivariate control charts.

    PubMed

    Robotti, Elisa; Bobba, Marco; Panepinto, Andrea; Marengo, Emilio

    2007-07-01

    The effect of exposure of paper samples to UV light was monitored by use of ATR-FT-IR spectroscopy and multivariate statistical tools. Three types of paper were tested: common laser-printer paper, news print, and thermal fax paper. The samples were first characterised by ATR-FT-IR spectroscopy to determine natural experimental variability. They were then exposed to UV light for 30 h and the effects of the exposure were monitored by use of the same spectroscopic technique. Finally, multivariate statistical tools were applied to the final dataset, coupled with construction of multivariate control charts, to identify the effects of UV light on the sample surfaces.

  15. Noncontacting measurement technologies for space propulsion condition monitoring

    NASA Technical Reports Server (NTRS)

    Randall, M. R.; Barkhoudarian, S.; Collins, J. J.; Schwartzbart, A.

    1987-01-01

    This paper describes four noncontacting measurement technologies that can be used in a turbopump condition monitoring system. The isotope wear analyzer, fiberoptic deflectometer, brushless torque-meter, and fiberoptic pyrometer can be used to monitor component wear, bearing degradation, instantaneous shaft torque, and turbine blade cracking, respectively. A complete turbopump condition monitoring system including these four technologies could predict remaining component life, thus reducing engine operating costs and increasing reliability.

  16. Noncontacting measurement technologies for space propulsion condition monitoring

    NASA Technical Reports Server (NTRS)

    Randall, M. R.; Barkhoudarian, S.; Collins, J. J.; Schwartzbart, A.

    1987-01-01

    This paper describes four noncontacting measurement technologies that can be used in a turbopump condition monitoring system. The isotope wear analyzer, fiberoptic deflectometer, brushless torque-meter, and fiberoptic pyrometer can be used to monitor component wear, bearing degradation, instantaneous shaft torque, and turbine blade cracking, respectively. A complete turbopump condition monitoring system including these four technologies could predict remaining component life, thus reducing engine operating costs and increasing reliability.

  17. Multivariate or Multivariable Regression?

    PubMed Central

    Goodman, Melody

    2013-01-01

    The terms multivariate and multivariable are often used interchangeably in the public health literature. However, these terms actually represent 2 very distinct types of analyses. We define the 2 types of analysis and assess the prevalence of use of the statistical term multivariate in a 1-year span of articles published in the American Journal of Public Health. Our goal is to make a clear distinction and to identify the nuances that make these types of analyses so distinct from one another. PMID:23153131

  18. Modern techniques for condition monitoring of railway vehicle dynamics

    NASA Astrophysics Data System (ADS)

    Ngigi, R. W.; Pislaru, C.; Ball, A.; Gu, F.

    2012-05-01

    A modern railway system relies on sophisticated monitoring systems for maintenance and renewal activities. Some of the existing conditions monitoring techniques perform fault detection using advanced filtering, system identification and signal analysis methods. These theoretical approaches do not require complex mathematical models of the system and can overcome potential difficulties associated with nonlinearities and parameter variations in the system. Practical applications of condition monitoring tools use sensors which are mounted either on the track or rolling stock. For instance, monitoring wheelset dynamics could be done through the use of track-mounted sensors, while vehicle-based sensors are preferred for monitoring the train infrastructure. This paper attempts to collate and critically appraise the modern techniques used for condition monitoring of railway vehicle dynamics by analysing the advantages and shortcomings of these methods.

  19. Ultrasonic corrosion condition monitoring - A systematised approach

    SciTech Connect

    Yates, A.

    1985-01-01

    The technique of taking ultrasonic thickness readings as a basis for assessing corrosion and erosion damage on structures and pipework systems is an established means of obtaining condition data. To ensure that surveys carried out in this way are relevant and useful, several conditions must be met: 1. Individual readings must be accurate and the measuring system must be capable of ignoring paints and coatings at the test point; 2. Test points must be appropriately positioned; 3. Sufficient points must be taken to give a representative sample; 4. Reporting must be in a format which is readable, flexible and capable of highlighting anomalies. Following extensive experience in onshore and offshore corrosion condition surveys, systems have been evolved which have improved the efficiency of this approach in all the above areas.

  20. Monitoring Car Drivers' Condition Using Image Processing

    NASA Astrophysics Data System (ADS)

    Adachi, Kazumasa; Yamamto, Nozomi; Yamamoto, Osami; Nakano, Tomoaki; Yamamoto, Shin

    We have developed a car driver monitoring system for measuring drivers' consciousness, with which we aim to reduce car accidents caused by drowsiness of drivers. The system consists of the following three subsystems: an image capturing system with a pulsed infrared CCD camera, a system for detecting blinking waveform by the images using a neural network with which we can extract images of face and eye areas, and a system for measuring drivers' consciousness analyzing the waveform with a fuzzy inference technique and others. The third subsystem extracts three factors from the waveform first, and analyzed them with a statistical method, while our previous system used only one factor. Our experiments showed that the three-factor method we used this time was more effective to measure drivers' consciousness than the one-factor method we described in the previous paper. Moreover, the method is more suitable for fitting parameters of the system to each individual driver.

  1. 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.

  2. Monitoring breath markers under controlled conditions.

    PubMed

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

    2015-10-15

    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.

  3. 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.

  4. 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.

  5. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Monitoring of water quality from roof runoff: Interpretation using multivariate analysis.

    PubMed

    Vialle, C; Sablayrolles, C; Lovera, M; Jacob, S; Huau, M-C; Montrejaud-Vignoles, M

    2011-06-01

    The quality of harvested rainwater used for toilet flushing in a private house in the south-west of France was assessed over a one-year period. Temperature, pH, conductivity, colour, turbidity, anions, cations, alkalinity, total hardness and total organic carbon were screened using standard analytical techniques. Total flora at 22 °C and 36 °C, total coliforms, Escherichia coli and enterococci were analysed. Overall, the collected rainwater had good physicochemical quality but did not meet the requirements for drinking water. The stored rainwater is characterised by low conductivity, hardness and alkalinity compared to mains water. Three widely used bacterial indicators - total coliforms, E. coli and enterococci - were detected in the majority of samples, indicating microbiological contamination of the water. To elucidate factors affecting the rainwater composition, principal component analysis and cluster analysis were applied to the complete data set of 50 observations. Chemical and microbiological parameters fluctuated during the course of the study, with the highest levels of microbiological contamination observed in roof runoffs collected during the summer. E. coli and enterococci occurred simultaneously, and their presence was linked to precipitation. Runoff quality is also unpredictable because it is sensitive to the weather. Cluster analysis differentiated three clusters: ionic composition, parameters linked with the microbiological load and indicators of faecal contamination. In future surveys, parameters from these three groups will be simultaneously monitored to more accurately characterise roof-collected rainwater. Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. 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.

  8. Technical guide for monitoring selected conditions related to wilderness character

    Treesearch

    Peter Landres; Steve Boutcher; Liese Dean; Troy Hall; Tamara Blett; Terry Carlson; Ann Mebane; Carol Hardy; Susan Rinehart; Linda Merigliano; David N. Cole; Andy Leach; Pam Wright; Deb Bumpus

    2009-01-01

    The purpose of monitoring wilderness character is to improve wilderness stewardship by providing managers a tool to assess how selected actions and conditions related to wilderness character are changing over time. Wilderness character monitoring provides information to help answer two key questions about wilderness character and wilderness stewardship: 1. How is...

  9. 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...

  10. 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...

  11. 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.

  12. 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.

  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. 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.

  15. 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.

  16. Spatial and temporal information fusion for crop condition monitoring

    USDA-ARS?s Scientific Manuscript database

    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...

  17. 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.

  18. A hybrid framework for downscaling time-dependent multivariate coastal boundary conditions

    NASA Astrophysics Data System (ADS)

    Alvarez Antolinez, J. A.; Murray, A. B.; Moore, L. J.; Wood, J.; Mendez, F. J.

    2016-12-01

    response and to attribute particular local forcing conditions to synoptic-scale atmospheric patterns, for both extratropical and tropical cyclone activity.

  19. Bayesian estimation of multivariate normal mixtures with covariate-dependent mixing weights, with an application in antimicrobial resistance monitoring.

    PubMed

    Jaspers, Stijn; Komárek, Arnošt; Aerts, Marc

    2017-09-12

    Bacteria with a reduced susceptibility against antimicrobials pose a major threat to public health. Therefore, large programs have been set up to collect minimum inhibition concentration (MIC) values. These values can be used to monitor the distribution of the nonsusceptible isolates in the general population. Data are collected within several countries and over a number of years. In addition, the sampled bacterial isolates were not tested for susceptibility against one antimicrobial, but rather against an entire range of substances. Interest is therefore in the analysis of the joint distribution of MIC data on two or more antimicrobials, while accounting for a possible effect of covariates. In this regard, we present a Bayesian semiparametric density estimation routine, based on multivariate Gaussian mixtures. The mixing weights are allowed to depend on certain covariates, thereby allowing the user to detect certain changes over, for example, time. The new approach was applied to data collected in Europe in 2010, 2012, and 2013. We investigated the susceptibility of Escherichia coli isolates against ampicillin and trimethoprim, where we found that there seems to be a significant increase in the proportion of nonsusceptible isolates. In addition, a simulation study was carried out, showing the promising behavior of the proposed method in the field of antimicrobial resistance. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. 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.

  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. 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.

  3. 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.

  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.

  5. 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.

  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. 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.

  8. 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.

  9. 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.

  10. Vibration-based structural health monitoring using adaptive statistical method under varying environmental condition

    NASA Astrophysics Data System (ADS)

    Jin, Seung-Seop; Jung, Hyung-Jo

    2014-03-01

    It is well known that the dynamic properties of a structure such as natural frequencies depend not only on damage but also on environmental condition (e.g., temperature). The variation in dynamic characteristics of a structure due to environmental condition may mask damage of the structure. Without taking the change of environmental condition into account, false-positive or false-negative damage diagnosis may occur so that structural health monitoring becomes unreliable. In order to address this problem, an approach to construct a regression model based on structural responses considering environmental factors has been usually used by many researchers. The key to success of this approach is the formulation between the input and output variables of the regression model to take into account the environmental variations. However, it is quite challenging to determine proper environmental variables and measurement locations in advance for fully representing the relationship between the structural responses and the environmental variations. One alternative (i.e., novelty detection) is to remove the variations caused by environmental factors from the structural responses by using multivariate statistical analysis (e.g., principal component analysis (PCA), factor analysis, etc.). The success of this method is deeply depending on the accuracy of the description of normal condition. Generally, there is no prior information on normal condition during data acquisition, so that the normal condition is determined by subjective perspective with human-intervention. The proposed method is a novel adaptive multivariate statistical analysis for monitoring of structural damage detection under environmental change. One advantage of this method is the ability of a generative learning to capture the intrinsic characteristics of the normal condition. The proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation. A comparative

  11. Condition monitoring helps make the Space Shuttle Main Engine reusable

    NASA Technical Reports Server (NTRS)

    Lacroix, W. P.

    1973-01-01

    The Space Shuttle Main Engine (SSME) is a reusable, high-performance liquid-propellant rocket engine being developed for the Space Shuttle Orbiter Vehicle. The SSME has been designed for long life, rapid postflight maintenance, and a fast vehicle turnaround cycle of 160 hours. To meet the unique reusability requirements, the SSME considers maintainability and condition monitoring much as airlines do today. The condition monitoring capabilities designed into this engine are discussed with major emphasis on internal inspection and techniques which ensure the reusability of the SSME.

  12. A systems approach to the quantitative condition monitoring of pipelines

    SciTech Connect

    Shannon, R.W.; Argent, C.J.

    1988-01-01

    In Service deterioration is a problem on all pipelines. British Gas operates procedures for in-service inspection and surveillance, corrosion control and condition monitoring from which remedial maintenance action is initiated. These procedures include helicopter patrols, foot patrols, landowner liaison, cathodic protection monitoring, hydrostatic testing, on-line inspection by intelligent pig and above ground survey. All fault data is logged and the reasons for particular faults investigated. The experience gained through this process has permitted a quantitative re-assessment of pipeline behaviour - real rather than perceived behaviour - and has enabled the contribution of each monitoring technique to be established. Using this information, soundly based monitoring and preventative maintenance strategies have been derived for British Gas high-pressure pipelines. By integrating the different procedures into a co-ordinated policy, the basis for a technically acceptable, cost effective approach to pipeline preventative maintenance has been achieved.

  13. 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.

  14. Temperature Based Condition Monitoring of Rail and Structural Mill

    NASA Astrophysics Data System (ADS)

    Patidar, Lakhan; Chitransh, Chitragupt Swaroop; Rao, K. U.

    2012-06-01

    today in this competitive market it is necessary to reduce shutdowns and to increase our production rate. For this purpose we apply Condition Monitoring Methods. SAIL is the world?s largest producer of rails with an installed capacity to produce 500 000 tons of rails and 250 000 tons of structural?s. Bhilai is also the sole supplier of the country's longest rail tracks of 260 meters. Infrared Thermography is the latest Condition Monitoring technique that is adopted in Bhilai Steel Plant. Predictive Maintenance schemes are being practiced in Bhilai Steel Plant to monitor the health of the equipment and identify potential problems well in advance and plan remedial measures, thereby avoiding unwanted failures.

  15. 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.

  16. A selection of forest condition indicators for monitoring

    Treesearch

    Kurt H. Riitters; B.E. Law; R.C. Kucera; A.L. Gallant; R.L. DeVelice; C.J. Palmer

    1992-01-01

    Regional monitoring and assessments of the health of forested ecosystems require indicators of forest conditions and environmental stresses. Indicator selections depend on objectives and the strategy for data collection and analysis. This paper recommends a set of indicators to signal changes in forest ecosystem distribution, productivity, and disturbance. Additional...

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

    ERIC Educational Resources Information Center

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

    2016-01-01

    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…

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

    ERIC Educational Resources Information Center

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

    2016-01-01

    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…

  19. 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.

  20. Cable condition monitoring research activities at Sandia National Laboratories

    SciTech Connect

    Jacobus, M.J.; Zigler, G.L.; Bustard, L.D.

    1988-01-01

    Sandia National Laboratories is currently conducting long-term aging research on representative samples of nuclear power plant cables. The objectives of the program are to determine the suitability of these cables for extended life (beyond 40 year design basis) and to assess various cable condition monitoring techniques for predicting remaining cable life. The cables are being aged for long times at relatively mild exposure conditions with various condition monitoring techniques to be employed during the aging process. Following the aging process, the cables will be exposed to a sequential accident profile consisting of high dose rate irradiation followed by a simulated design basis loss-of-coolant accident (LOCA) steam exposure. 12 refs., 1 fig., 1 tab.

  1. 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.

  2. 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.

  3. Condition monitoring of a subsea pump using fibre optic sensing

    NASA Astrophysics Data System (ADS)

    Jones, Kevin; Staveley, Chris; Vialla, Jean-Francois

    2014-05-01

    With the growth in deep-water oil and gas production, condition monitoring of high-value subsea assets to give early warning of developing problems is vital. Offshore operators can then transport and deploy spare parts before a failure occurs thus minimizing equipment down- time. Results are presented from a suite of tests in which multiple elements of a subsea twin-screw pump were monitored using a single fibre optic sensing system that simultaneously measured dynamic strain on the main rotor bearings, pressure and temperature of the lube oil, distributed temperature through the motor stator windings and vibration of the motor housing.

  4. Monitoring of adherent live cells morphology using the undecimated wavelet transform multivariate image analysis (UWT-MIA).

    PubMed

    Juneau, Pierre-Marc; Garnier, Alain; Duchesne, Carl

    2017-01-01

    Cell morphology is an important macroscopic indicator of cellular physiology and is increasingly used as a mean of probing culture state in vitro. Phase contrast microscopy (PCM) is a valuable tool for observing live cells morphology over long periods of time with minimal culture artifact. Two general approaches are commonly used to analyze images: individual object segmentation and characterization by pattern recognition. Single-cell segmentation is difficult to achieve in PCM images of adherent cells since their contour is often irregular and blurry, and the cells bundle together when the culture reaches confluence. Alternatively, pattern recognition approaches such as the undecimated wavelet transform multivariate image analysis (UWT-MIA), allow extracting textural features from PCM images that are correlated with cellular morphology. A partial least squares (PLS) regression model built using textural features from a set of 200 ground truth images was shown to predict the distribution of cellular morphological features (major and minor axes length, orientation, and roundness) with good accuracy for most images. The PLS models were then applied on a large dataset of 631,136 images collected from live myoblast cell cultures acquired under different conditions and grown in two different culture media. The method was found sensitive to morphological changes due to cell growth (culture time) and those introduced by the use of different culture media, and was able to distinguish both sources of variations. The proposed approach is promising for application on large datasets of PCM live-cell images to assess cellular morphology and growth kinetics in real-time which could be beneficial for high-throughput screening as well as automated cell culture kinetics assessment and control applications. Biotechnol. Bioeng. 2017;114: 141-153. © 2016 Wiley Periodicals, Inc.

  5. 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.

  6. 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.

  7. Some aspects of AE application in tool condition monitoring

    PubMed

    Jemielniak

    2000-03-01

    Acoustic emission (AE) is rather a well-known form of non-destructive testing. In the last few years the technology of the AE measurement has been expanded to cover the area of tool condition monitoring. The paper presents some experience of Warsaw University of Technology (WUT) in such applications of AE. It provides an interpretation of common AE signal distortions and possible solutions to avoid them. Furthermore, a characteristic study of several different AE and ultrasonic sensors being used in WUT is furnished. Evaluation of the applicability of some basic measures of acoustic emission for tool condition monitoring is also presented in the paper. Finally paper presents a method of the catastrophic tool failure detection in turning, which uses symptoms other than the direct magnitude AERMS signal. The method is based on the statistical analysis of the distributions of the AERMS signal.

  8. Why is it important to monitor social conditions in wilderness?

    Treesearch

    Alan E. Watson

    1990-01-01

    “Social conditions in wilderness” refers to all aspects of human use of the wilderness that pose the possibility of impact to the resource and visitor experiences. The reasons for monitoring (1) use levels and use trends (including characteristics of use and users) and (2) the quality of the recreation experiences provided (ability to provide naturalness, privacy, and...

  9. 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.

  10. 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.

  11. Case studies aid choice among quantitative condition-monitoring strategies

    SciTech Connect

    Shannon, R.W.E.; Argent, C.J.

    1989-02-20

    Operational pipelines differ in age, condition, and location. All of these factors may influence the best option. From the operator's point of view, the expected working life of the pipeline is also important. Despite these complexities, a technical and financial appraisal of the options is desirable. To this end the pipeline-corrosion model has been constructed. Sample appraisals for a 40-year, condition-monitoring package on a new pipeline, and an ''on-off'' exercise on a 50-year-old line will be presented. The model pipeline in this instance consists of 100 km of 600-mm diameter pipe with an 8-mm W.T.

  12. 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

    2015-05-21

    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.

  13. 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

  14. [Feasibility of monitoring karst standing conditions with vegetation spectra].

    PubMed

    Yue, Yue-Min; Wang, Ke-Lin; Xiong, Ying

    2012-07-01

    Karst regions are typically ecological fragile zones constrained by geological setting, which resulted in high heterogeneity of vegetation standing conditions. The karst vegetation was featured with stone, dry and high calcium carbonate content growth conditions. Based on vegetation spectral analysis and canonical correspondence analysis (CCA), the present study aimed to examine the feasibility of using vegetation spectra to monitor the heterogeneous karst standing conditions. The results showed that there were significant differences between karst vegetation and non-karst vegetation within the spectral range of 1 300-2 500 nm reflectance and 400 - 680 nm first-derivative spectra. It was found that soil moisture and calcium carbonate contents had the most significant effects on vegetation spectral features in karst regions. Ordination diagrams of CCA could distinguish the differences of karst vegetation and non-karst vegetation. Our study demonstrates that vegetation spectra are highly related to karst standing conditions and it is feasible to monitor karst standing conditions with vegetation spectral features.

  15. 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

  16. An application of smart dust for pavement condition monitoring

    NASA Astrophysics Data System (ADS)

    Ferzli, Nadim A.; Ivey, Richard A.; King, Timothy; Sandburg, Colby J.; Pei, Jin-Song; Zaman, Musharraf M.; Refai, Hazem H.; Lin, Hung, Jr.; Landrum, Aaron; Victor, Rory

    2006-03-01

    Pavement maintenance is vital for travel safety; detecting road weather conditions using a wireless sensing network poses many challenges due to the harsh environment. This paper presents some preliminary results of an ongoing effort of applying "Smart Dust" sensor network for monitoring pavement temperature and moisture condition to detect icy road condition. Careful considerations yield effective solutions to various hardware and software development issues including the selection of sensors and antenna, design of casing, interfacing motes with alien sensors and programming of motes. A series of experiments is carried out to study traffic interference to packet delivery performance of a small-scale sensor network in a pseudo-field environment. In addition, several overnight tests are conducted to study the performance of motes operated under a power efficient condition. The results are analyzed and challenges are identified in this smart sensing application. The aforementioned research activities would benefit robust real-world implementations of off-the-shelf sensor network products.

  17. Induction machine condition monitoring using notch-filtered motor current

    NASA Astrophysics Data System (ADS)

    Günal, Serkan; Gökhan Ece, Dog˜an; Nezih Gerek, Ömer

    2009-11-01

    This paper presents a new approach to induction motor condition monitoring using notch-filtered motor current signature analysis (NFMCSA). Unlike most of the previous work utilizing motor current signature analysis (MCSA) using spectral methods to extract required features for detecting motor fault conditions, here NFMCSA is performed in time-domain to extract features of energy, sample extrema, and third and fourth cumulants evaluated from data within sliding time window. Six identical three-phase induction motors were used for the experimental verification of the proposed method. One healthy machine was used as a reference, while other five with different synthetic faults were used for condition detection and classification. Extracted features obtained from NFMCSA of all motors were employed in three different and popular classifiers. The proposed motor current analysis and the performance of the features used for fault detection and classification are examined at various motor load levels and it is shown that a successful induction motor condition monitoring system is developed. Developed system is also able to indicate the load level and the type of a fault in multi-dimensional feature space representation. In order to test the generality and applicability of the developed method to other induction motors, data acquired from another healthy induction motor with different number of poles and rated power is also incorporated into the system. In spite of the above difference, the proposed feature set successfully locates the healthy motor within the classification cluster of "healthy motors" on the feature space.

  18. ASSESSMENT OF CABLE AGING USING CONDITION MONITORING TECHNIQUES

    SciTech Connect

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

    2000-04-06

    Electric cables in nuclear power plants suffer degradation during service as a result of the thermal and radiation environments in which they are installed. Instrumentation and control cables are one type of cable that provide an important role in reactor safety. Should the polymeric cable insulation material become embrittled and cracked during service, or during a loss-of-coolant-accident (LOCA) and when steam and high radiation conditions are anticipated, failure could occur and prevent the cables from fulfilling their intended safety function(s). A research program is being conducted at Brookhaven National Laboratory to evaluate condition monitoring (CM) techniques for estimating the amount of cable degradation experienced during in-plant service. The objectives of this program are to assess the ability of the cables to perform under a simulated LOCA without losing their ability to function effectively, and to identify CM techniques which may be used to determine the effective lifetime of cables. The cable insulation materials tested include ethylene propylene rubber (EPR) and cross-linked polyethylene (XLPE). Accelerated aging (thermal and radiation) to the equivalent of 40 years of service was performed, followed by exposure to simulated LOCA conditions. The effectiveness of chemical, electrical, and mechanical condition monitoring techniques are being evaluated. Results indicate that several of these methods can detect changes in material parameters with increasing age. However, each has its limitations, and a combination of methods may provide an effective means for trending cable degradation in order to assess the remaining life of cables.

  19. Factorial switching linear dynamical systems applied to physiological condition monitoring.

    PubMed

    Quinn, John A; Williams, Christopher K I; McIntosh, Neil

    2009-09-01

    Condition monitoring often involves the analysis of systems with hidden factors that switch between different modes of operation in some way. Given a sequence of observations, the task is to infer the filtering distribution of the switch setting at each time step. In this paper, we present factorial switching linear dynamical systems as a general framework for handling such problems. We show how domain knowledge and learning can be successfully combined in this framework, and introduce a new factor (the "X-factor") for dealing with unmodeled variation. We demonstrate the flexibility of this type of model by applying it to the problem of monitoring the condition of a premature baby receiving intensive care. The state of health of a baby cannot be observed directly, but different underlying factors are associated with particular patterns of physiological measurements and artifacts. We have explicit knowledge of common factors and use the X-factor to model novel patterns which are clinically significant but have unknown cause. Experimental results are given which show the developed methods to be effective on typical intensive care unit monitoring data.

  20. In-situ oil condition monitoring in passenger cars

    SciTech Connect

    Lee, H.; Wang, S.S.; Smolenski, D.J.

    1994-08-01

    Oil condition sensors which had a two-electrode structure with an interdigitated pattern and roughened electrodes were fabricated using micromachining techniques. With an AC sawtooth waveform voltage source applied to the sensor electrodes, a current dependent on the oil condition can be measured and converted to a DC voltage output. The sensors were mounted on the dipsticks of test cars and were used for in-situ engine oil degradation monitoring over 20320 km (12700 miles). The duration of the testing was from winter to summer, and both normal and short distance driving were tested. Measured sensor outputs were also compared with oil analysis results. There was a strong correlation between the sensor output and the condition of the oil as confirmed by the oil analysis. 12 refs., 3 figs., 3 tabs.

  1. Non-Dispersive Infrared Sensor for Online Condition Monitoring of Gearbox Oil.

    PubMed

    Rauscher, Markus S; Tremmel, Anton J; Schardt, Michael; Koch, Alexander W

    2017-02-18

    The condition of lubricating oil used in automotive and industrial gearboxes must be controlled in order to guarantee optimum performance and prevent damage to machinery parts. In normal practice, this is done by regular oil change intervals and routine laboratory analysis, both of which involve considerable operating costs. In this paper, we present a compact and robust optical sensor that can be installed in the lubrication circuit to provide quasi-continuous information about the condition of the oil. The measuring principle is based on non-dispersive infrared spectroscopy. The implemented sensor setup consists of an optical measurement cell, two thin-film infrared emitters, and two four-channel pyroelectric detectors equipped with optical bandpass filters. We present a method based on multivariate partial least squares regression to select appropriate optical bandpass filters for monitoring the oxidation, water content, and acid number of the oil. We perform a ray tracing analysis to analyze and correct the influence of the light path in the optical setup on the optical parameters of the bandpass filters. The measurement values acquired with the sensor for three different gearbox oil types show high correlation with laboratory reference data for the oxidation, water content, and acid number. The presented sensor can thus be a useful supplementary tool for the online condition monitoring of lubricants when integrated into a gearbox oil circuit.

  2. Non-Dispersive Infrared Sensor for Online Condition Monitoring of Gearbox Oil

    PubMed Central

    Rauscher, Markus S.; Tremmel, Anton J.; Schardt, Michael; Koch, Alexander W.

    2017-01-01

    The condition of lubricating oil used in automotive and industrial gearboxes must be controlled in order to guarantee optimum performance and prevent damage to machinery parts. In normal practice, this is done by regular oil change intervals and routine laboratory analysis, both of which involve considerable operating costs. In this paper, we present a compact and robust optical sensor that can be installed in the lubrication circuit to provide quasi-continuous information about the condition of the oil. The measuring principle is based on non-dispersive infrared spectroscopy. The implemented sensor setup consists of an optical measurement cell, two thin-film infrared emitters, and two four-channel pyroelectric detectors equipped with optical bandpass filters. We present a method based on multivariate partial least squares regression to select appropriate optical bandpass filters for monitoring the oxidation, water content, and acid number of the oil. We perform a ray tracing analysis to analyze and correct the influence of the light path in the optical setup on the optical parameters of the bandpass filters. The measurement values acquired with the sensor for three different gearbox oil types show high correlation with laboratory reference data for the oxidation, water content, and acid number. The presented sensor can thus be a useful supplementary tool for the online condition monitoring of lubricants when integrated into a gearbox oil circuit. PMID:28218701

  3. Adaptive parameter blind source separation technique for wheel condition monitoring

    NASA Astrophysics Data System (ADS)

    Zhang, Jie; Gao, Hongli; Liu, Qiyue; Farzadpour, F.; Grebe, C.; Tian, Ying

    2017-06-01

    Wheel condition monitoring has played a key role in the safe operation of railway vehicles. Blind source separation (BSS) is an attractive tool due to its excellent performance in separating source signals from their mixtures when no detailed knowledge of defective sources and the mixing process is assumed. In this paper, we propose an adaptive parameter BSS approach based on the adaptive time-frequency distributions theory in order to deal with the non-stationary blind separation problem and apply it to wheel defect monitoring. Some classical time-frequency signal analysis and BSS methods are applied in comparison with the proposed approach through frequency-varying non-stationary and time-varying non-stationary simulations. Experiments of single and multi-fault wheels have been conducted using the wheel/rail simulation facility to illustrate the effectiveness of the proposed method in processing the non-stationary signals with varying fault complexity.

  4. Condition Monitoring of Wind Turbines Using Intelligent Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Morshedizadeh, Majid

    Wind Turbine condition monitoring can detect anomalies in turbine performance which have the potential to result in unexpected failure and financial loss. This study examines common Supervisory Control And Data Acquisition (SCADA) data over a period of 20 months for 21 pitch regulated 2.3 MW turbines and is presented in three manuscripts. First, power curve monitoring is targeted applying various types of Artificial Neural Networks to increase modeling accuracy. It is shown how the proposed method can significantly improve network reliability compared with existing models. Then, an advance technique is utilized to create a smoother dataset for network training followed by establishing dynamic ANFIS network. At this stage, designed network aims to predict power generation in future hours. Finally, a recursive principal component analysis is performed to extract significant features to be used as input parameters of the network. A novel fusion technique is then employed to build an advanced model to make predictions of turbines performance with favorably low errors.

  5. Research on Land Ecological Condition Investigation and Monitoring Technology

    NASA Astrophysics Data System (ADS)

    Lv, Chunyan; Guo, Xudong; Chen, Yuqi

    2017-04-01

    The ecological status of land reflects the relationship between land use and environmental factors. At present, land ecological situation in China is worrying. According to the second national land survey data, there are about 149 million acres of arable land located in forests and grasslands area in Northeast and Northwest of China, Within the limits of the highest flood level, at steep slope above 25 degrees; about 50 million acres of arable land has been in heavy pollution; grassland degradation is still serious. Protected natural forests accounted for only 6% of the land area, and forest quality is low. Overall, the ecological problem has been eased, but the local ecological destruction intensified, natural ecosystem in degradation. It is urgent to find out the situation of land ecology in the whole country and key regions as soon as possible. The government attaches great importance to ecological environment investigation and monitoring. Various industries and departments from different angles carry out related work, most of it about a single ecological problem, the lack of a comprehensive surveying and assessment of land ecological status of the region. This paper established the monitoring index system of land ecological condition, including Land use type area and distribution, quality of cultivated land, vegetation status and ecological service, arable land potential and risk, a total of 21 indicators. Based on the second national land use survey data, annual land use change data and high resolution remote sensing data, using the methods of sample monitoring, field investigation and statistical analysis to obtain the information of each index, this paper established the land ecological condition investigation and monitoring technology and method system. It has been improved, through the application to Beijing-Tianjin-Hebei Urban Agglomeration, the northern agro-pastoral ecological fragile zone, and 6 counties (cities).

  6. Condition monitoring of machinery using motor current signature analysis

    SciTech Connect

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

    1989-01-01

    Motor current signature analysis (MCSA) is a powerful monitoring tool for motor-driven equipment that provides a nonintrusive means for detecting changes in process conditions or the presence of mechanical abnormalities. It was recently developed at the Oak Ridge National Laboratory (ORNL) as a means for determining the effects of service wear on motor-operated valves used in nuclear power plant safety systems. 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, sensing both large and small, long-term and rapid, mechanical load variation and converting them into variations in the induced current generated in the motor windings. The motor current signature, which is carried by the motor power cables, can be extracted at a convenient location and processed as needed to obtain time- and frequency-domain (spectral) characteristics which provide equipment condition indicators for trending over time. MCSA technology (patent applied for) has already been applied successfully to motor-operated valves, vacuum pumps, water pumps, air blowers and air conditioning systems, and examples of such application will be presented. The applicability of MCSA to a broader range of equipment monitoring and production line testing is also discussed. 1 ref., 8 figs.

  7. 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.

  8. 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

  9. Guaranteeing robustness of structural condition monitoring to environmental variability

    NASA Astrophysics Data System (ADS)

    Van Buren, Kendra; Reilly, Jack; Neal, Kyle; Edwards, Harry; Hemez, François

    2017-01-01

    Advances in sensor deployment and computational modeling have allowed significant strides to be recently made in the field of Structural Health Monitoring (SHM). One widely used SHM strategy is to perform a vibration analysis where a model of the structure's pristine (undamaged) condition is compared with vibration response data collected from the physical structure. Discrepancies between model predictions and monitoring data can be interpreted as structural damage. Unfortunately, multiple sources of uncertainty must also be considered in the analysis, including environmental variability, unknown model functional forms, and unknown values of model parameters. Not accounting for these sources of uncertainty can lead to false-positives or false-negatives in the structural condition assessment. To manage the uncertainty, we propose a robust SHM methodology that combines three technologies. A time series algorithm is trained using "baseline" data to predict the vibration response, compare predictions to actual measurements collected on a potentially damaged structure, and calculate a user-defined damage indicator. The second technology handles the uncertainty present in the problem. An analysis of robustness is performed to propagate this uncertainty through the time series algorithm and obtain the corresponding bounds of variation of the damage indicator. The uncertainty description and robustness analysis are both inspired by the theory of info-gap decision-making. Lastly, an appropriate "size" of the uncertainty space is determined through physical experiments performed in laboratory conditions. Our hypothesis is that examining how the uncertainty space changes throughout time might lead to superior diagnostics of structural damage as compared to only monitoring the damage indicator. This methodology is applied to a portal frame structure to assess if the strategy holds promise for robust SHM. (Publication approved for unlimited, public release on October-28

  10. 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. PMID:27879734

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

    PubMed

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

    2008-02-06

    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. Integrated Multivariate Health Monitoring System for Helicopters Main Rotor Drives: Development and Validation with In-Service Data

    DTIC Science & Technology

    2014-10-02

    distribution of the ordinary regime of the process. In a population characterised by a multidimensional Gauss distribution, the Mahalanobis distances...The extent to which the filtered healthy operational states of each component of the power drive fit with a multidimen- sional Gauss distribution...automotive and aerospace applications. John Wiley and Sons, Ltd. Publications. Rencher, A. C. (2002). Methods of multivariate analysis. Wi- ley

  13. 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.

  14. 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.

  15. Condition Monitoring of Railway Track Using In-service Vehicle

    NASA Astrophysics Data System (ADS)

    Mori, Hirotaka; Tsunashima, Hitoshi; Kojima, Takashi; Matsumoto, Akira; Mizuma, Takeshi

    This paper summarizes the development of a portable track-condition-monitoring system for easy installation on in-service vehicles. In this system, rail irregularities are estimated from the vertical and lateral acceleration of the car body. The roll angle of the car body, calculated using a rate gyroscope, is used to distinguish line irregularities from level irregularities. Rail corrugation is detected from cabin noise with spectral peak calculation. A GPS system and a map-matching algorithm are used to pinpoint the location of faults on tracks. Field test using in-service vehicle was carried out to evaluate the developed system. The results show that the condition of rail irregularity and rail corrugation can be estimated effectively.

  16. Thermographic monitoring of materials under simulated reentry conditions

    NASA Technical Reports Server (NTRS)

    White, Susan M.; Burleigh, Douglas

    1991-01-01

    Thermography can be used to measure surface temperature gradients graphically, and can be used under conditions where the direct measurement of temperature at all desired points, using thermocouples or resistance temperature detectors (RTDs), is either difficult or impossible. The use of thermographic monitoring during a series of arc-jet tests is described. Described in this work are the issues that influence interpretation of the thermographic measurements under these conditions, including the calculation of effective emittance and window transmittance from the spectral properties of the materials in order to calculate the temperature distribution of a surface directly from the measured radiance. Comparison of the surface temperatures measured using thermocouples and the temperatures derived from thermographic measurements show good agreement. The data gathered will be used to evaluate important test parameters such as the heating distribution across the surface of a heat shield test model and at steps on the model surface.

  17. 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

  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. 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.

  20. Condition monitoring of machinery using motor current signature analysis

    NASA Astrophysics Data System (ADS)

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

    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. Real time video analysis to monitor neonatal medical condition

    NASA Astrophysics Data System (ADS)

    Shirvaikar, Mukul; Paydarfar, David; Indic, Premananda

    2017-05-01

    One in eight live births in the United States is premature and these infants have complications leading to life threatening events such as apnea (pauses in breathing), bradycardia (slowness of heart) and hypoxia (oxygen desaturation). Infant movement pattern has been hypothesized as an important predictive marker for these life threatening events. Thus estimation of movement along with behavioral states, as a precursor of life threatening events, can be useful for risk stratification of infants as well as for effective management of disease state. However, more important and challenging is the determination of the behavioral state of the infant. This information includes important cues such as sleep position and the status of the eyes, which are important markers for neonatal neurodevelopment state. This paper explores the feasibility of using real time video analysis to monitor the condition of premature infants. The image of the infant can be segmented into regions to localize and focus on specific areas of interest. Analysis of the segmented regions can be performed to identify different parts of the body including the face, arms, legs and torso. This is necessary due to real-time processing speed considerations. Such a monitoring system would be of great benefit as an aide to medical staff in neonatal hospital settings requiring constant surveillance. Any such system would have to satisfy extremely stringent reliability and accuracy requirements, before it can be deployed in a hospital care unit, due to obvious reasons. The effect of lighting conditions and interference will have to be mitigated to achieve such performance.

  2. Structural health condition monitoring of rails using acoustic emission techniques

    NASA Astrophysics Data System (ADS)

    Yilmazer, Pinar

    In-service rails can develop several types of structural defects due to fatigue and wear caused by rolling stock passing over them. Most rail defects will develop gradually over time thus permitting inspection engineers to detect them in time before final failure occurs. In the UK, certain types of severe rail defects such as tache ovales, require the fitting of emergency clamps and the imposing of an Emergency Speed Restriction (ESR) until the defects are removed. Acoustic emission (AE) techniques can be applied for the detection and continuous monitoring of defect growth therefore removing the need of imposing strict ESRs. The work reported herewith aims to develop a sound methodology for the application of AE in order to detect and subsequently monitor damage evolution in rails. To validate the potential of the AE technique, tests have been carried out under laboratory conditions on three and four-point bending samples manufactured from 260 grade rail steel. Further tests, simulating the background noise conditions caused by passing rolling stock have been carried out using special experimental setups. The crack growth events have been simulated using a pencil tip break..

  3. 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

  4. Wireless Condition Monitoring and Maintenance for Rooftop Packaged Heating, Ventilation, and Air-Conditioning

    SciTech Connect

    Katipamula, Srinivas; Brambley, Michael R.

    2004-06-01

    Rooftop package air-conditioning and heat pumps, while representing over half of U.S. commercial-building cooling energy consumption, are some of the most neglected of building systems. They are often found with inoperable dampers, dirty/clogged filters and coils, incorrect refrigerant charges, failing compressors, failed fans, missing enclosure panels, un-calibrated controls, failed sensors, and other problems. Frequently, actual operating hours deviate considerably from intended (and assumed) schedules. Although there are no reliable estimates on what fraction of the units operate under degraded conditions and the energy inefficiencies associated with such operations, a range of savings from 10 to 30% are generally believed to be achievable by enhancing operation of these units. Potential national energy savings from proper operation range from 23 to 70 trillion Btus annually in the U.S. Since the cost associated with conventional monitoring and servicing is quite high, conventional monitoring is seldom done. Combinations of wireless sensing and data acquisition, monitoring tools, automated diagnostics and prognostics show considerable promise to help remedy this maintenance problem for package HVAC units and the underserved small commercial building sector in which they are predominantly installed. This paper characterizes the current problem with maintenance of packaged air conditioners and heat pumps, provides estimates of the total energy impacts of the problem, and describes a generic system in which these developing technologies are used to provide real-time condition monitoring for package HVAC units and their components. Costs with today's technology are provided and future costs are estimated, showing that benefits will greatly exceed costs in many cases particularly if low-cost wireless monitoring is used.

  5. 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.

  6. 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.

  7. 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.

  8. 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

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

    PubMed

    Schotzko, Timo; Lang, Walter

    2014-07-10

    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.

  10. Design and realization of high voltage disconnector condition monitoring system

    NASA Astrophysics Data System (ADS)

    Shi, Jinrui; Xu, Tianyang; Yang, Shuixian; Li, Buoyang

    2017-08-01

    The operation status of the high voltage disconnector directly affects the safe and stable operation of the power system. This article uses the wireless frequency hopping communication technology of the communication module to achieve the temperature acquisition of the switch contacts and high voltage bus, to introduce the current value of the loop in ECS, and judge the operation status of the disconnector by considering the ambient temperature, calculating the temperature rise; And through the acquisition of the current of drive motor in the process of switch closing and opening, and fault diagnosis of the disconnector by analyzing the change rule of the drive motor current, the condition monitoring of the high voltage disconnector is realized.

  11. 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.

  12. 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

  13. 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.

  14. Physical working conditions as covered in European monitoring questionnaires.

    PubMed

    Tynes, Tore; Aagestad, Cecilie; Thorsen, Sannie Vester; Andersen, Lars Louis; Perkio-Makela, Merja; García, Francisco Javier Pinilla; Blanco, Luz Galiana; Vermeylen, Greet; Parent-Thirion, Agnes; Hooftman, Wendela; Houtman, Irene; Liebers, Falk; Burr, Hermann; Formazin, Maren

    2017-06-05

    The prevalence of workers with demanding physical working conditions in the European work force remains high, and occupational physical exposures are considered important risk factors for musculoskeletal disorders (MSD), a major burden for both workers and society. Exposures to physical workloads are therefore part of the European nationwide surveys to monitor working conditions and health. An interesting question is to what extent the same domains, dimensions and items referring to the physical workloads are covered in the surveys. The purpose of this paper is to determine 1) which domains and dimensions of the physical workloads are monitored in surveys at the national level and the EU level and 2) the degree of European consensus among these surveys regarding coverage of individual domains and dimensions. Items on physical workloads used in one European wide/Spanish and five other European nationwide work environment surveys were classified into the domains and dimensions they cover, using a taxonomy agreed upon among all participating partners. The taxonomy reveals that there is a modest overlap between the domains covered in the surveys, but when considering dimensions, the results indicate a lower agreement. The phrasing of items and answering categories differs between the surveys. Among the domains, the three domains covered by all surveys are "lifting, holding & carrying of loads/pushing & pulling of loads", "awkward body postures" and "vibrations". The three domains covered less well, that is only by three surveys or less, are "physical work effort", "working sitting", and "mixed exposure". This is the fırst thorough overview to evaluate the coverage of domains and dimensions of self-reported physical workloads in a selection of European nationwide surveys. We hope the overview will provide input to the revisions and updates of the individual countries' surveys in order to enhance coverage of relevant domains and dimensions in all surveys and to increase

  15. Multivariate analysis of the spatial patterns of 8 trace elements using the French soil monitoring network data.

    PubMed

    Saby, N P A; Thioulouse, J; Jolivet, C C; Ratié, C; Boulonne, L; Bispo, A; Arrouays, D

    2009-10-15

    Geostatistical and spatially constrained multivariate analysis methods (MULTISPATI-PCA) have been applied at the scale of France to differentiate the influence of natural background from the pollution due to human activities on the content of 8 trace elements in the topsoil. The results of MULTISPATI-PCA evidence strong spatial structures attributed to different natural and artificial processes. The first axis can be interpreted as an axis of global richness in trace elements. Axis 2 reflects geochemical anomalies in Tl and Pb. Axis 3 exhibits on one hand natural pedogeogenic anomalies and on the other hand, it shows high values attributable to anthropogenic contamination. Finally, axis 4 is driven by anthropogenic copper contamination. At the French territory scale, we show that the main factors controlling trace elements distribution in the topsoil are soil texture, variations in parent material geology and weathering, and various anthropogenic sources.

  16. Linear variable filter based oil condition monitoring systems for offshore windturbines

    NASA Astrophysics Data System (ADS)

    Wiesent, Benjamin R.; Dorigo, Daniel G.; Şimşek, Özlem; Koch, Alexander W.

    2011-10-01

    A major part of future renewable energy will be generated in offshore wind farms. The used turbines of the 5 MW class and beyond, often feature a planetary gear with 1000 liters lubricating oil or even more. Monitoring the oil aging process provides early indication of necessary maintenance and oil change. Thus maintenance is no longer time-scheduled but becomes wear dependent providing ecological and economical benefits. This paper describes two approaches based on a linear variable filter (LVF) as dispersive element in a setup of a cost effective infrared miniature spectrometer for oil condition monitoring purposes. Spectra and design criteria of a static multi-element detector and a scanning single element detector system are compared and rated. Both LVF miniature spectrometers are appropriately designed for the suggested measurements but have certain restrictions. LVF multi-channel sensors combined with sophisticated multivariate data processing offer the possibility to use the sensor for a broad range of lubricants just by a software update of the calibration set. An all-purpose oil sensor may be obtained.

  17. 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.

  18. Noninvasive health condition monitoring device for workers at high altitudes conditions.

    PubMed

    Aqueveque, Pablo; Gutierrez, Cristopher; Saavedra, Francisco; Pino, Esteban J

    2016-08-01

    This work presents the design and implementation of a continuous monitoring device to control the health state of workers, for instance miners, at high altitudes. The extreme ambient conditions are harmful for peoples' health; therefore a continuous control of the workers' vital signs is necessary. The developed system includes physiological variables: electrocardiogram (ECG), respiratory activity and body temperature (BT), and ambient variables: ambient temperature (AT) and relative humidity (RH). The noninvasive sensors are incorporated in a t-shirt to deliver a functional device, and maximum comfort to the users. The device is able to continuously calculate heart rate (HR) and respiration rate (RR), and establish a wireless data transmission to a central monitoring station.

  19. Time-varying associations of suicide with deployments, mental health conditions, and stressful life events among current and former US military personnel: a retrospective multivariate analysis.

    PubMed

    Shen, Yu-Chu; Cunha, Jesse M; Williams, Thomas V

    2016-11-01

    US military suicides have increased substantially over the past decade and currently account for almost 20% of all military deaths. We investigated the associations of a comprehensive set of time-varying risk factors with suicides among current and former military service members. We did a retrospective multivariate analysis of all US military personnel between 2001 and 2011 (n=110 035 573 person-quarter-years, representing 3 795 823 service members). Outcome was death by suicide, either during service or post-separation. We used Cox proportional hazard models at the person-quarter level to examine associations of deployment, mental disorders, history of unlawful activity, stressful life events, and other demographic and service factors with death by suicide. The strongest predictors of death by suicide were current and past diagnoses of self-inflicted injuries, major depression, bipolar disorder, substance use disorder, and other mental health conditions (compared with service members with no history of diagnoses, the hazard ratio [HR] ranged from 1·4 [95% CI 1·14-1·72] to 8·34 [6·71-10·37]). Compared with service members who were never deployed, hazard rates of suicide (which represent the probability of death by suicide in a specific quarter given that the individual was alive in the previous quarter) were lower among the currently deployed (HR 0·50, 95% CI 0·40-0·61) but significantly higher in the quarters following first deployment (HR 1·51 [1·17-1·96] if deployed in the previous three quarters; 1·14 [1·06-1·23] if deployed four or more quarters ago). The hazard rate of suicide increased within the first year of separation from the military (HR 2·49, 95% CI 2·12-2·91), and remained high for those who had separated from the military 6 or more years ago (HR 1·63, 1·45-1·82). The increased hazard rate of death by suicide for military personnel varies by time since exposure to deployment, mental health diagnoses, and other stressful

  20. Second campaign of microclimate monitoring in the carcer tullianum: temporal and spatial correlation and gradients evidenced by multivariate analysis

    PubMed Central

    2012-01-01

    Background This paper discusses results obtained in the second monitoring campaign of the Carcer Tullianum, a particular hypogeum environment located in the historical centre of Rome (Italy). In the first paper we stressed the need to apply chemometric tools to this kind of studies in order to obtain full and significant information; really information on sampling design, sensors (type, number, position) and instrument validation seems to be not easy to find in literature for researches dealing with monitoring of indoor environments. Also in this case three main parameters (temperature, humidity, illuminance) were monitored in the complex construction by an inexpensive self-assembled system along some horizontal and vertical vectors together with some measurements of oxygen, carbon dioxide and barometric pressure. With respect to the first campaign, we used a higher number of sensors to cover a new excavated zone; for the same reason, as well as to take into account the presence of visitors, a different experimental design was adopted. Results Different data treatments were applied to data coming from all the used sensors. A good view of the microclimate was obtained that also resulted coherent with the different position of the three rooms constituting the monitored site (Carcer, Tullianum, Convent). Classical time plots resulted useful to evidence the correlation of the main monitored parameters (T, RH% and illuminance) with macroclimate, as well as their delay in following macroclimate. Box-Whisker and Gain-Loss graphs evidenced at the best the microclimate differences between the three rooms; an almost hypogean microclimate was evidenced for the lower room (Tullianum) where humidity values range between 90 and 100% while lower values, but anyway higher than the external, and spread more widely were measured passing to Convent and Carcer with minimum values around 50% for the last. A scarce or very scarce correlation with macroclimate was evidenced for all the

  1. Effects of monitoring condition and frequency-altered feedback on stuttering frequency.

    PubMed

    Kalinowski, J; Stuart, A; Wamsley, L; Rastatter, M P

    1999-12-01

    The purpose of the study was to examine stuttering frequency during speaking conditions that are believed to mitigate stuttering frequency both with normal nonaltered auditory feedback (NAF) and a known fluency-enhancing feedback. Specifically, stuttering frequency was examined as a function of three monitoring conditions under NAF and frequency-altered feedback (FAF): no monitoring (i.e., speaking alone, in the absence of audio and visual recording), audiovisual monitoring (i.e., speaking alone with audiovisual recording), and audiovisual monitoring with observers (i.e., speaking with audiovisual recording in the presence of two observers). Seven adults and one adolescent who stutter served as participants. Stuttering frequency was differentially affected across monitoring conditions under each auditory feedback condition (p = .027). Post hoc analyses revealed no significant difference in stuttering frequency between the two conditions in the absence of the observers (i.e., no monitoring vs. audiovisual monitoring) under NAF (p = .45). There was, however, a significant difference in stuttering frequency for the no-monitoring and audiovisual-monitoring conditions relative to the audiovisual-monitoring-with-observers condition (p = .0002). There was no statistically significant difference in stuttering frequency across monitoring conditions under FAF (p > .05). The findings are consistent with the notion that during NAF stuttering frequency varies as a function of hierarchical socio-environmental conditions in which inanimate monitoring conditions constitute one entity. Such a relationship does not exist during FAF.

  2. Surface monitoring measurements of materials on environmental change conditions

    NASA Astrophysics Data System (ADS)

    Tornari, Vivi; Bernikola, Eirini; Bellendorf, Paul; Bertolin, Chiara; Camuffo, Dario; Kotova, Lola; Jacobs, Daniela; Zarnic, Roko; Rajcic, Vlatka; Leissner, Johanna

    2013-05-01

    Climate Change is one of the most critical global challenges of our time and the burdened cultural heritage of Europe is particularly vulnerable to be left unprotected. Climate for Culture2 project exploits the damage impact of climate change on cultural heritage at regional scale. In this paper the progress of the study with in situ measurements and investigations at cultural heritage sites throughout Europe combined with laboratory simulations is described. Cultural works of art are susceptible to deterioration with environmental changes causing imperceptibly slow but steady accumulation of damaging effects directly impacted on structural integrity. Laser holographic interference method is employed to provide remote non destructive field-wise detection of the structural differences occurred as climate responses. The first results from climate simulation of South East Europe (Crete) are presented. A full study in regards to the four climate regions of Europe is foreseen to provide values for development of a precise and integrated model of thermographic building simulations for evaluation of impact of climate change. Development of a third generation user interface software optimised portable metrology system (DHSPI II) is designed to record in custom intervals the surface of materials witnessing reactions under simulated climatic conditions both onfield and in laboratory. The climate conditions refer to real data-loggers readings representing characteristic historical building in selected climate zones. New generation impact sensors termed Glass Sensors and Free Water Sensors are employed in the monitoring procedure to cross-correlate climate data with deformation data. In this paper results from the combined methodology are additionally presented.

  3. Fetal breathing movements: antepartum monitoring of fetal condition.

    PubMed

    Manning, F A; Platt, L D

    1979-08-01

    Until recently, the relative inaccessibility of the human fetus to physical assessment has made antepartum assessment of its condition difficult. The development of methods for accurate antepartum fetal heart rate monitoring and the subsequent study of heart rate responses to various stimuli have resulted in a significant improvement in accuracy of antepartum fetal surveillance. The development of real time B-mode ultrasound enables the clinician to assess many additional fetal biophysical variables including fetal breathing movements. In our observations, the combination of heart rate and fetal breathing assessment has produced a significant improvement in differentiating the normal from the compromised fetus. The addition of other biophysical variables (tone, movements and amniotic fluid volume) have further refined the ability to identify the fetus at risk. At this point, we have evaluated only a few of many possible variables. It seems probable that, as other fetal biophysical variables are included with the overall assessment, for example fetal reflexes or fetal biophysical response to exogenous stimuli, the identification of the fetus at risk and the quantitation of the magnitude of risk will become increasingly more precise.

  4. Diamond pixel modules and the ATLAS beam conditions monitor

    NASA Astrophysics Data System (ADS)

    Dobos, D.; Pernegger, Heinz; RD42 Collaboration; ATLAS Diamond Pixel Upgrade Collaboration; ATLAS Beam Conditions Monitor Collaborations

    2011-02-01

    Chemical vapor deposition diamonds are considered among possible sensor materials for the next pixel upgrade in ATLAS. Full size diamond pixel modules have been constructed to the specification of the ATLAS Pixel Detector using poly-crystalline CVD diamond sensors to develop the production techniques required for industrial production. Those modules were tested in the lab and testbeam. Additionally we will present results of diamond pixel modules using single-crystal diamonds and results of proton irradiations up to 1.8 ×10 16 protons/cm 2. The ATLAS Beam Conditions Monitors (BCM) main purpose is to protect the experiments silicon tracker from beam incidents. In total 16 1×1 cm2 500 μm thick diamond pCVD sensors are used in eight positions around the LHC interaction point. They perform time difference measurements with sub nanosecond resolution to distinguish between particles from a collision and spray particles from a beam incident; an abundance of the latter can lead the BCM to provoke an abort of LHC beam. The BCM diamond detector modules, their readout system and the algorithms used to detect beam incidents are described. Results of the BCM operation with circulating LHC beams and its commissioning with first LHC collisions are reported.

  5. 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.

  6. Monitoring the condition of the slag crust in blast furnaces

    SciTech Connect

    Chernov, N.N.; Marder, B.F.; Demidenko, T.V.; Riznitskii, I.G.; Safina, L.A.; Dyshlevich, I.I.; Tkach, A.Ya.

    1988-05-01

    Studies conducted at the Krivorozhstal' combine blast furnaces have shown that fusion of the crust can be established from the change in the total content of alkali metals in the slag. After the furnaces were blown out for repairs the remaining lining and crust were inspected. It was found that the lining of the uncooled part of the stock remained in relatively good shape with the greatest amount of lining wear seen between the second row of stack coolers and bosh coolers. The composition and structure of the slag crust for different regions of the furnaces were analyzed and various physicochemical properties leading to crust formation and behavior were assessed. It was concluded that the systematic determination of the fraction of K/sub 2/O in the alkali compounds in the furnace slag will permit monitoring of the conditions of the slag crust in the furnace and, in the event of the onset of its collapse, will enable measures to be taken to stabilize the heating of the furnace.

  7. Development of a kind of multi-variable wireless sensor for structural health monitoring in civil engineering

    NASA Astrophysics Data System (ADS)

    Yu, Yan; Ou, Jinping

    2005-05-01

    In recent years, structural health monitoring (SHM) has been an important research area for designing and evaluating reliability of civil engineering structures. With the development of the technologies in sensing, wireless communication, and micro electro mechanical systems (MEMS), wireless sensing technique has been caused much more attentions and used gradually in the SHM. The wireless sensors and network has low capital and installation costs as well as ensures more reliability in the communication of sensor measurements, but there exists a key problem of the finite energy and this is a primary design constraint. Therefore, some measures must be adopted to make wireless sensor work more effectively. In this paper, a kind of wireless sensor with 3 variables, temperature- acceleration- strain, is proposed. Such several modules as sensing unit, micro-processing unit, power unit and wireless transceiver are constructed using commercially available parts, and integrated into a complete wireless sensor. The fusion arithmetic of the temperature-acceleration is embedded in the wireless sensor so that the measured acceleration values are more accurate. Measures are also adopted to reduce the energy consumption. Experimental results show that, the wireless sensor can monitor the temperature-acceleration-strain of the structures at real time and precisely, and pre-process and pack the measured data to reduce the data volume to be transmitted and save energy.

  8. 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

  9. 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.

  10. 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. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Impact of digenean parasite infection on metallothionein synthesis by the cockle (Cerastoderma edule): a multivariate field monitoring.

    PubMed

    Baudrimont, Magalie; de Montaudouin, Xavier; Palvadeau, Audrey

    2006-05-01

    Metallothioneins (MT) are proteins that play an important role in metabolism of essential metals and detoxification of trace metals from living organisms. Their synthesis is induced by metal pollution but can also be exacerbated by other factors such as reproduction processes. In this context, we monitored MT concentrations in a cockle Cerastoderma edule (marine bivalve) population and highlighted the effect of a castrating digenean parasite, Labratrema minimus. In spent cockles, MT levels were low (ca. 5 nmol sites g(-1), fresh weight) but slightly higher in parasitized individuals. During gametogenesis, MT synthesis increased in all cockles, but concentrations were lower in parasitized individuals (18 against 27 nmol sites g(-1), fw in unparasitized cockles) in relation with gonad damage by parasites. Therefore, it is suggested that parasite infection in cockles can modulate MT synthesis that could consequently interfere with the response of these protective proteins in case of metal contamination.

  12. 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.

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

    PubMed

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

    2013-05-15

    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. 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.

  15. 10 CFR 20.1502 - Conditions requiring individual monitoring of external and internal occupational dose.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 1 2010-01-01 2010-01-01 false Conditions requiring individual monitoring of external and internal occupational dose. 20.1502 Section 20.1502 Energy NUCLEAR REGULATORY COMMISSION STANDARDS FOR PROTECTION AGAINST RADIATION Surveys and Monitoring § 20.1502 Conditions requiring individual monitoring of external and internal...

  16. 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...

  17. 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...

  18. 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

  19. The use of acoustic emission for bearing condition monitoring

    NASA Astrophysics Data System (ADS)

    Lees, A. W.; Quiney, Z.; Ganji, A.; Murray, B.

    2011-07-01

    This paper reports research currently in progress at Swansea University in collaboration with SKF Engineering & Research Centre as part of a continuing investigation into high frequency Acoustic Emission. The primary concerns are experimentally producing subsurface cracks, the type of which would occur in a service failure of a ball bearing, within a steel ball and to closely monitor the properties of this AE from crack initiation to the formation of a ball on the ball surface. It is worth noting that there is evidence that the frequency content of the AE changes during this period, although this has yet to be proved consistent or even fully explained. Conclusive evidence could lead to a system which detects such cracks in a bearing operating in real life conditions, advantageous for many reasons including safety, downtime and maintenance and associated costs. The results from two experimental procedures are presented, one of which loads a single ball held stationary in a test rig to induce subsurface cracks, which are in turn detected by a pair of broadband AE sensors and recorded via a Labview based software system. This approach not only allows detailed analysis of the AE waveforms but also approximate AE source location from the time difference between two sensors. The second experimental procedure details an adaptation of a four-ball lubricant tester in an attempt to produce naturally occurring subsurface cracks from rolling contact whilst minimising the AE arising from surface wear. This thought behind this experiment is reinforced with 3D computational modelling of the rotating system.

  20. 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.

  1. 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.

  2. 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...

  3. 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...

  4. Near infrared spectroscopy combined with multivariate analysis for monitoring the ethanol precipitation process of fraction I + II + III supernatant in human albumin separation

    NASA Astrophysics Data System (ADS)

    Li, Can; Wang, Fei; Zang, Lixuan; Zang, Hengchang; Alcalà, Manel; Nie, Lei; Wang, Mingyu; Li, Lian

    2017-03-01

    Nowadays, as a powerful process analytical tool, near infrared spectroscopy (NIRS) has been widely applied in process monitoring. In present work, NIRS combined with multivariate analysis was used to monitor the ethanol precipitation process of fraction I + II + III (FI + II + III) supernatant in human albumin (HA) separation to achieve qualitative and quantitative monitoring at the same time and assure the product's quality. First, a qualitative model was established by using principal component analysis (PCA) with 6 of 8 normal batches samples, and evaluated by the remaining 2 normal batches and 3 abnormal batches. The results showed that the first principal component (PC1) score chart could be successfully used for fault detection and diagnosis. Then, two quantitative models were built with 6 of 8 normal batches to determine the content of the total protein (TP) and HA separately by using partial least squares regression (PLS-R) strategy, and the models were validated by 2 remaining normal batches. The determination coefficient of validation (Rp2), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and ratio of performance deviation (RPD) were 0.975, 0.501 g/L, 0.465 g/L and 5.57 for TP, and 0.969, 0.530 g/L, 0.341 g/L and 5.47 for HA, respectively. The results showed that the established models could give a rapid and accurate measurement of the content of TP and HA. The results of this study indicated that NIRS is an effective tool and could be successfully used for qualitative and quantitative monitoring the ethanol precipitation process of FI + II + III supernatant simultaneously. This research has significant reference value for assuring the quality and improving the recovery ratio of HA in industrialization scale by using NIRS.

  5. Near infrared spectroscopy combined with multivariate analysis for monitoring the ethanol precipitation process of fraction I+II+III supernatant in human albumin separation.

    PubMed

    Li, Can; Wang, Fei; Zang, Lixuan; Zang, Hengchang; Alcalà, Manel; Nie, Lei; Wang, Mingyu; Li, Lian

    2017-03-15

    Nowadays, as a powerful process analytical tool, near infrared spectroscopy (NIRS) has been widely applied in process monitoring. In present work, NIRS combined with multivariate analysis was used to monitor the ethanol precipitation process of fraction I+II+III (FI+II+III) supernatant in human albumin (HA) separation to achieve qualitative and quantitative monitoring at the same time and assure the product's quality. First, a qualitative model was established by using principal component analysis (PCA) with 6 of 8 normal batches samples, and evaluated by the remaining 2 normal batches and 3 abnormal batches. The results showed that the first principal component (PC1) score chart could be successfully used for fault detection and diagnosis. Then, two quantitative models were built with 6 of 8 normal batches to determine the content of the total protein (TP) and HA separately by using partial least squares regression (PLS-R) strategy, and the models were validated by 2 remaining normal batches. The determination coefficient of validation (Rp(2)), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP) and ratio of performance deviation (RPD) were 0.975, 0.501g/L, 0.465g/L and 5.57 for TP, and 0.969, 0.530g/L, 0.341g/L and 5.47 for HA, respectively. The results showed that the established models could give a rapid and accurate measurement of the content of TP and HA. The results of this study indicated that NIRS is an effective tool and could be successfully used for qualitative and quantitative monitoring the ethanol precipitation process of FI+II+III supernatant simultaneously. This research has significant reference value for assuring the quality and improving the recovery ratio of HA in industrialization scale by using NIRS.

  6. Foreign Exchange Value-at-Risk with Multiple Currency Exposure: A Multivariate and Copula Generalized Autoregressive Conditional Heteroskedasticity Approach

    DTIC Science & Technology

    2014-11-01

    à un risque financier lié aux varia- tions du taux de change, et les responsables de la gestion interne se voient donc pressés de trouver des...Jondeau, E. and Rockinger, M. (2006), The Copula-GARCH model of conditional dependencies: An international stock market application, Journal of

  7. 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…

  8. 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…

  9. Monitoring the condition of natural resources in US national parks.

    PubMed

    Fancy, S G; Gross, J E; Carter, S L

    2009-04-01

    The National Park Service has developed a long-term ecological monitoring program for 32 ecoregional networks containing more than 270 parks with significant natural resources. The monitoring program assists park managers in developing a broad-based understanding of the status and trends of park resources as a basis for making decisions and working with other agencies and the public for the long-term protection of park ecosystems. We found that the basic steps involved in planning and designing a long-term ecological monitoring program were the same for a range of ecological systems including coral reefs, deserts, arctic tundra, prairie grasslands, caves, and tropical rainforests. These steps involve (1) clearly defining goals and objectives, (2) compiling and summarizing existing information, (3) developing conceptual models, (4) prioritizing and selecting indicators, (5) developing an overall sampling design, (6) developing monitoring protocols, and (7) establishing data management, analysis, and reporting procedures. The broad-based, scientifically sound information obtained through this systems-based monitoring program will have multiple applications for management decision-making, research, education, and promoting public understanding of park resources. When combined with an effective education program, monitoring results can contribute not only to park issues, but also to larger quality-of-life issues that affect surrounding communities and can contribute significantly to the environmental health of the nation.

  10. A multivariate approach for a comparison of big data matrices. Case study: thermo-hygrometric monitoring inside the Carcer Tullianum (Rome) in the absence and in the presence of visitors.

    PubMed

    Visco, Giovanni; Plattner, Susanne H; Fortini, Patrizia; Sammartino, Mariapia

    2017-06-01

    In the last decades, the very fast improvement of the analytical instrumentation has led to the possibility of quickly and easily getting a lot of data; in turn, the need of advanced statistical methods suitable to extract the full information furnished by instruments has increased. Such kind of data treatments is particularly important in any case of continuous monitoring of one or more parameters, so the microclimate monitoring is a typical example for this application. Microclimate control is essential in the conservation of Cultural Heritage (CH), but decisions on optimal conservation parameters cannot base only on existing norms that do not take into account the environment's history. Often CH has survived for many centuries in conditions that must be considered risky but also a stable state (equilibrium) resulting from a long adaptation process during which a more or less heavy damage occurred to the materials. Any successive change of microclimate parameters has interrupted this equilibrium conditions and has induced further damage to material until a new equilibrium is reached; dimension and frequency of changes are proportional to the expected damage. This thermodynamic consideration provides the background for a CH conservation project based on microclimate control and highlights the importance of environmental monitoring for the identification of equilibrium parameters to be maintained. In 2010, we monitored the microclimate of an important historical building in Rome, the Mamertino Carcer, before its opening to visitors. One year later, we repeated the monitoring in the presence of visitors, and here, we present a careful choice of multivariate data treatments adopted for an enough, simple and immediate evaluation of the microclimatic changes; this allows an easier understanding also for persons with not too deep scientific background, such as Superintendents and, in turn, really useful information to provide suggestions for a conservation project

  11. [Monitoring and conditioning in plastic and reconstructive ENT-surgery].

    PubMed

    Dacho, A; Dietz, A

    2006-11-01

    Plastic and reconstructive ENT surgery serves for reconstruction of form and function. Frequent indications in ENT surgery are the covering of large tissue defects after tumor operations, firing and/or explosion injuries, accidents, burns or massive infections. A high revision rate of up to 20 % in selective patient groups show that more knowledge of both monitoring and ischemia-/reperfusion mechanisms is necessary. Besides improved monitor proceedings biochemical cell procedures in pedicled and free flaps are getting more focused. In the last years certain physical and medical factors appear, which have influence on the long-term surviving of a pedicled or free flap, e. g. pre- and/or postconditioning. The increasing knowledge of changes in perfusion and oxygenation, which prevail in the flap, as well as different options of physical and pharmacological therapies permit a promising view into the future, in order to achieve an improved surviving of a pedicled or free flap in combination with improved monitor proceedings.

  12. 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.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  14. Continuous adaptive monitoring of status and trends in ecosystem conditions

    Treesearch

    R. L. Czaplewski

    1996-01-01

    Adaptive management uses an experimental approach in the stewardship of our natural resources. This paper advocates the complementary concept of "adaptive monitoring" to observe and evaluate the outcomes of these experiments. Adaptive management acknowledges that decisions must be made in spite of imperfect understanding of their consequences;...

  15. 40 CFR 141.625 - Conditions requiring increased monitoring.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ....080 mg/L or a HAA5 sample is >0.060 mg/L at any location. (b) You are in violation of the MCL when the... least four consecutive quarters and the LRAA for every monitoring location is ≤0.060 mg/L for TTHM and ≤0.045 mg/L for HAA5....

  16. 40 CFR 141.625 - Conditions requiring increased monitoring.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....080 mg/L or a HAA5 sample is >0.060 mg/L at any location. (b) You are in violation of the MCL when the... least four consecutive quarters and the LRAA for every monitoring location is ≤0.060 mg/L for TTHM and ≤0.045 mg/L for HAA5....

  17. 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.

  18. Determination of ethyl glucuronide in human hair samples: A multivariate analysis of the impact of extraction conditions on quantitative results.

    PubMed

    Mueller, Alexander; Jungen, Hilke; Iwersen-Bergmann, Stefanie; Raduenz, Lars; Lezius, Susanne; Andresen-Streichert, Hilke

    2017-02-01

    Ethyl glucuronide (EtG), a minor metabolite of ethanol, is used as a direct alcohol biomarker for the prolonged detection of ethanol consumption. Hair testing for EtG offers retrospective, long-term detection of ethanol exposition for several months and has gained practical importance in forensic and clinical toxicology. Since quantitative results of EtG hair testings are included in interpretations, a rugged quantitation of EtG in hair matrix is important. As generally known, sample preparation is critical in hair testing, and the scope of this study was on extraction of EtG from hair matrix. The influence of extraction solvent, ultrasonication, incubation temperature, incubation time, solvent amount and hair particle size on quantitative results was investigated by a multifactorial experimental design using a validated analytical method and twelve different batches of authentic human hair material. Eight series of extraction experiments in a Plackett-Burman setup were carried out on each hair material with the studied factors at high or low levels. The effect of pulverization was further studied by two additional experimental series. Five independent samplings were performed for each run, resulting in a total number of 600 determinations. Considerable differences in quantitative EtG results were observed, concentrations above and below interpretative cut-offs were obtained from the same hair materials using different extraction conditions. Statistical analysis revealed extraction solvent and temperature as the most important experimental factors with significant influence on quantitative results. The impact of pulverization depended on other experimental factors and the different hair matrices themselves proved to be important predictors of extraction efficiency. A standardization of extraction procedures should be discussed, since it will probably reduce interlaboratory variabilities and improve the quality and acceptance of hair EtG analysis. Copyright © 2016

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. Instantaneous angular speed monitoring of gearboxes under non-cyclic stationary load conditions

    NASA Astrophysics Data System (ADS)

    Stander, C. J.; Heyns, P. S.

    2005-07-01

    Recent developments in the condition monitoring and asset management market have led to the commercialisation of online vibration-monitoring systems. These systems are primarily utilised to monitor large mineral mining equipment such as draglines, continuous miners and hydraulic shovels. Online monitoring systems make diagnostic information continuously available for asset management, production outsourcing and maintenance alliances with equipment manufacturers. However, most online vibration-monitoring systems are based on conventional vibration-monitoring technologies, which are prone to giving false equipment deterioration warnings on gears that operate under fluctuating load conditions. A simplified mathematical model of a gear system was developed to illustrate the feasibility of monitoring the instantaneous angular speed (IAS) as a means of monitoring the condition of gears that are subjected to fluctuating load conditions. A distinction is made between cyclic stationary load modulation and non-cyclic stationary load modulation. It is shown that rotation domain averaging will suppress the modulation caused by non-cyclic stationary load conditions but will not suppress the modulation caused by cyclic stationary load conditions. An experimental investigation on a test rig indicated that the IAS of a gear shaft could be monitored with a conventional shaft encoder to indicate a deteriorating gear fault condition.

  4. Low power sensor network for wireless condition monitoring

    NASA Astrophysics Data System (ADS)

    Richter, Ch.; Frankenstein, B.; Schubert, L.; Weihnacht, B.; Friedmann, H.; Ebert, C.

    2009-03-01

    For comprehensive fatigue tests and surveillance of large scale structures, a vibration monitoring system working in the Hz and sub Hz frequency range was realized and tested. The system is based on a wireless sensor network and focuses especially on the realization of a low power measurement, signal processing and communication. Regarding the development, we met the challenge of synchronizing the wireless connected sensor nodes with sufficient accuracy. The sensor nodes ware realized by compact, sensor near signal processing structures containing components for analog preprocessing of acoustic signals, their digitization, algorithms for data reduction and network communication. The core component is a digital micro controller which performs the basic algorithms necessary for the data acquisition synchronization and the filtering. As a first application, the system was installed in a rotor blade of a wind power turbine in order to monitor the Eigen modes over a longer period of time. Currently the sensor nodes are battery powered.

  5. 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.

  6. Anomaly Detection Techniques for the Condition Monitoring of Tidal Turbines

    DTIC Science & Technology

    2014-09-29

    Figure 1. The Andritz Hydro Hammerfest HS1000 tidal turbine The turbine has an open- blade horizontal axis design, fixed to the seabed. Similar to...exceeding 1000 RPM within the generator. The turbine has no yaw, with blades rotating in opposite directions in response to upstream and downstream...application of wavelet based monitoring (Duhaney, Khoshgaftaar, Sloan, Alhalibi & Beaujean, 2011).  Fatigue analysis of tidal turbine blades (Mahfuz

  7. Converting Tribology Based Condition Monitoring into Measurable Maintenance Results

    DTIC Science & Technology

    1998-01-01

    34* precision alignment and balance requirements, "* after installation startup and inspection, and "* cleanliness monitoring and removal of break-in...acceptable or excessive, depending on machine operation, balance, shaft alignment , etc. Surface chemistry for oil wetted surfaces can be benign or under...0.1 0.2 0.3 0.4 0.5 PERCEN T VVWATFER The SKF Bearing Company report that if contaminants larger than the clearances between bearing

  8. Transient multivariable sensor evaluation

    DOEpatents

    Vilim, Richard B.; Heifetz, Alexander

    2017-02-21

    A method and system for performing transient multivariable sensor evaluation. The method and system includes a computer system for identifying a model form, providing training measurement data, generating a basis vector, monitoring system data from sensor, loading the system data in a non-transient memory, performing an estimation to provide desired data and comparing the system data to the desired data and outputting an alarm for a defective sensor.

  9. Multivariate Quantitative Chemical Analysis

    NASA Technical Reports Server (NTRS)

    Kinchen, David G.; Capezza, Mary

    1995-01-01

    Technique of multivariate quantitative chemical analysis devised for use in determining relative proportions of two components mixed and sprayed together onto object to form thermally insulating foam. Potentially adaptable to other materials, especially in process-monitoring applications in which necessary to know and control critical properties of products via quantitative chemical analyses of products. In addition to chemical composition, also used to determine such physical properties as densities and strengths.

  10. 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

  11. Improving crop condition monitoring at field scale by using optimal Landsat and MODIS images

    USDA-ARS?s Scientific Manuscript database

    Satellite remote sensing data at coarse resolution (kilometers) have been widely used in monitoring crop condition for decades. However, crop condition monitoring at field scale requires high resolution data in both time and space. Although a large number of remote sensing instruments with different...

  12. Monitoring the Financial Condition of Colleges and Universities. AAHE-ERIC Higher Education Research Currents.

    ERIC Educational Resources Information Center

    Taylor, Barbara

    1984-01-01

    Efforts to monitor the financial condition of colleges and universities have arisen from concerns about the effects of economic and demographic pressures. Researchers have attempted to monitor financial condition through two types of research: subjective studies and objective financial indicator studies. Subjective analyses can be useful for…

  13. Monitoring Forest Condition in Europe: Impacts of Nitrogen and Sulfur Depositions on Forest Ecosystems

    Treesearch

    M. Lorenz; G. Becher; V. Mues; E. Ulrich

    2006-01-01

    Forest condition in Europe has been monitored over 19 years jointly by the United Nations Economic Commission for Europe (UNECE) and the European Union (EU). Large-scale variations of forest condition over space and time in relation to natural and anthropogenic factors are assessed on about 6,000 plots systematically spread across Europe. This large-scale monitoring...

  14. 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 plants...

  15. Optoelectronic methods in potential application in monitoring of environmental conditions

    NASA Astrophysics Data System (ADS)

    Mularczyk-Oliwa, Monika; Bombalska, Aneta; Kwaśny, Mirosław; Kopczyński, Krzysztof; Włodarski, Maksymilian; Kaliszewski, Miron; Kostecki, Jerzy

    2016-12-01

    Allergic rhinitis, also known as hay fever is a type of inflammation which occurs when the immune system overreacts to allergens in the air. It became the most common disease among people. It became important to monitor air content for the presence of a particular type of allergen. For the purposes of environmental monitoring there is a need to widen the group of traditional methods of identification of pollen for faster and more accurate research systems. The aim of the work was the characterization and classification of certain types of plant pollens by using laser optical methods, which were supported by the chemmometrics. Several species of pollen were examined, for which a database of spectral characteristics was created, using LIF, Raman scattering and FTIR methods. Spectral database contains characteristics of both common allergens and pollen of minor importance. Based on registered spectra, statistical analysis was made, which allows the classification of the tested pollen species. For the study of the emission spectra Nd:YAG laser was used with the fourth harmonic generation (266 nm) and GaN diode laser (375 nm). For Raman scattering spectra spectrometer Nicolet IS-50 with a excitation wavelength of 1064 nm was used. The FTIR spectra, recorded in the mid infrared1 range (4000-650 cm-1) were collected with use of transmission mode (KBr pellet), ATR and DRIFT.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Electrical techniques for monitoring the condition of lubrication oil

    NASA Astrophysics Data System (ADS)

    Turner, J. D.; Austin, L.

    2003-10-01

    The lubricating oil used in engines for vehicle and other applications is renewed according to a schedule specified by the manufacturer. This timetable is, naturally, very conservative, and makes no allowance for the way in which the engine is operated. Constant-speed operation (such as motorway use) is much less harmful to the lubricant than variable-speed operation, such as urban driving, during which the oil experiences extreme variations of temperature and engine speed. The net result of the conservative lubricant replacement schedule is that most engine oil is discarded well before it has reached the end of its useful life. This paper reports a study in which changes to the dielectric and magnetic properties of the oil are assessed as methods of measuring the degradation of lubricating oil. The relationship between oil use (measured by the distance a vehicle has travelled) and oil viscosity is also measured. The conclusions from this work are that simple distance travelled (miles/kilometres) is not a good indicator of the state of an oil, as estimated by measuring its viscosity. The magnetic characteristics of lubricating oil (i.e. its magnetic permeability) do change as the oil degrades, but the measurements were poorly correlated with viscosity and do not seem to offer much promise as the basis of an oil monitoring system. The dielectric properties of lubricating oil are reasonably well correlated with viscosity, and it is proposed that this could form the basis of a useful sensing technique.

  1. Alternative luciferase for monitoring bacterial cells under adverse conditions.

    PubMed

    Wiles, Siouxsie; Ferguson, Kathryn; Stefanidou, Martha; Young, Douglas B; Robertson, Brian D

    2005-07-01

    The availability of cloned luciferase genes from fireflies (luc) and from bacteria (luxAB) has led to the widespread use of bioluminescence as a reporter to measure cell viability and gene expression. The most commonly occurring bioluminescence system in nature is the deep-sea imidazolopyrazine bioluminescence system. Coelenterazine is an imidazolopyrazine derivative which, when oxidized by an appropriate luciferase enzyme, produces carbon dioxide, coelenteramide, and light. The luciferase from the marine copepod Gaussia princeps (Gluc) has recently been cloned. We expressed the Gluc gene in Mycobacterium smegmatis using a shuttle vector and compared its performance with that of an existing luxAB reporter. In contrast to luxAB, the Gluc luciferase retained its luminescence output in the stationary phase of growth and exhibited enhanced stability during exposure to low pH, hydrogen peroxide, and high temperature. The work presented here demonstrated the utility of the copepod luciferase bioluminescent reporter as an alternative to bacterial luciferase, particularly for monitoring responses to environmental stress stimuli.

  2. Disposable indicators for monitoring lighting conditions in museums.

    PubMed

    Bacci, Mauro; Cucci, Costanza; Dupont, Anne-Laurence; Lavédrine, Bertrand; Picollo, Marcello; Porcinai, Simone

    2003-12-15

    Photoinduced alterations of light-sensitive artifacts represent one of the main problems that conservators and curators have to face for environmental control in museums and galleries. Therefore, increasing attention has been recently devoted to developing strategies of indoor light monitoring, especially aimed at minimizing the cumulated light exposure for the objects on exhibit. In this work a prototype of a light dosimeter, constituted by a photosensitive dyes/polymer mixture applied on a paper substrate, is presented. This indicator, specially designed for a preventive assessment of the risk of damage for highly light-sensitive objects, undergoes a progressive color variation as its exposure to the light increases. Different, easily distinguishable color steps are exhibited depending on the light dose received, so that the dosimeter can be used straightforwardly to have a first, instrumentation-free estimation of the total light exposure. A reflectance spectroscopy study in the 350-860 nm range was carried out on prototype dosimeters exposed to light emitted from a tungsten-halogen lamp to investigate the response of the dosimeter to the light and to study the fading mechanism. Two different approaches were evaluated for the calibration of the prototype: colorimetry and principal component analysis of the reflectance spectra. The usefulness of the two methods in providing a quantitative indication of the light dose received was evaluated.

  3. 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.

  4. Diagnostic and Condition Monitoring System Assessment for Army Helicopter Modular Turboshaft Engines.

    DTIC Science & Technology

    1980-10-01

    and Condition Monitoring METS Modular Engine Test System MPFI Modular Performance F-4ult Isolation MTBF Mean Time Between Failures MTTR Mean Time to...AO-ACO? 31b GENERAL ELECTRIC CO LYNN MA AIRCRAFT ENGINE GROUP F/G 91/5 DIASNObIC AND CONDITION MONITORING SYSTEM ASSESSMENT FOR ARMY -ETCIU) OCT 80 H...1AIN)Il.A AD A-oft LEV t DIAGNOSTIC £ CONDITION MONITORING SYSTEM ASSESSMENT FOR ARMY HELICOPTER MODULAR TURBOSHAFT ENGINES. Harold J. Jord n General

  5. Condition monitoring of industrial infrastructures using distributed fibre optic acoustic sensors

    NASA Astrophysics Data System (ADS)

    Hicke, Konstantin; Hussels, Maria-Teresa; Eisermann, René; Chruscicki, Sebastian; Krebber, Katerina

    2017-04-01

    Distributed fibre optic acoustic sensing (DAS) can serve as an excellent tool for real-time condition monitoring of a variety of industrial and civil infrastructures. In this paper, we portray a subset of our current research activities investigating the usability of DAS based on coherent optical time-domain reflectometry (C-OTDR) for innovative and demanding condition monitoring applications. Specifically, our application-oriented research presented here aims at acoustic and vibrational condition monitoring of pipelines and piping systems, of rollers in industrial heavy-duty conveyor belt systems and of extensive submarine power cable installations, respectively.

  6. AN EVALUATION OF CONDITION MONITORING TECHNIQUES FOR LOW-VOLTAGE ELECTRIC CABLES

    SciTech Connect

    LOFARO,R.J.; GROVE,E.; SOO,P.

    2000-07-23

    Aging of systems and components in nuclear power plants is a well known occurrence that must be managed to ensure the continued safe operation of these plants. Much of the degradation due to aging is controlled through periodic maintenance and/or component replacement. However, there are components that do not receive periodic maintenance or monitoring once they are installed; electric cables are such a component. To provide a means of monitoring the condition of electric cables, research is ongoing to evaluate promising condition monitoring (CM) techniques that can be used in situ to monitor cable condition and predict remaining life. While several techniques are promising, each has limitations that must be considered in its application. This paper discusses the theory behind several of the promising cable CM techniques being studied, along with their effectiveness for monitoring aging degradation in typical cable insulation materials, such as cross-linked polyethylene and ethylene propylene rubber. Successes and limitations of each technique are also presented.

  7. 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...

  8. 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 WETLANDS RESERVE PROGRAM § 623.16 Monitoring and...

  9. GEOGRAPHIC-SPECIFIC WATER QUALITY CRITERIA DEVELOPMENT WITH MONITORING DATA USING CONDITIONAL PROBABILITIES - A PROPOSED APPROACH

    EPA Science Inventory

    A conditional probability approach using monitoring data to develop geographic-specific water quality criteria for protection of aquatic life is presented. Typical methods to develop criteria using existing monitoring data are limited by two issues: (1) how to extrapolate to an...

  10. 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...

  11. GEOGRAPHIC-SPECIFIC WATER QUALITY CRITERIA DEVELOPMENT WITH MONITORING DATA USING CONDITIONAL PROBABILITIES - A PROPOSED APPROACH

    EPA Science Inventory

    A conditional probability approach using monitoring data to develop geographic-specific water quality criteria for protection of aquatic life is presented. Typical methods to develop criteria using existing monitoring data are limited by two issues: (1) how to extrapolate to an...

  12. Experimental FSO network availability estimation using interactive fog condition monitoring

    NASA Astrophysics Data System (ADS)

    Turán, Ján.; Ovseník, Łuboš

    2016-12-01

    Free Space Optics (FSO) is a license free Line of Sight (LOS) telecommunication technology which offers full duplex connectivity. FSO uses infrared beams of light to provide optical broadband connection and it can be installed literally in a few hours. Data rates go through from several hundreds of Mb/s to several Gb/s and range is from several 100 m up to several km. FSO link advantages: Easy connection establishment, License free communication, No excavation are needed, Highly secure and safe, Allows through window connectivity and single customer service and Compliments fiber by accelerating the first and last mile. FSO link disadvantages: Transmission media is air, Weather and climate dependence, Attenuation due to rain, snow and fog, Scattering of laser beam, Absorption of laser beam, Building motion and Air pollution. In this paper FSO availability evaluation is based on long term measured data from Fog sensor developed and installed at TUKE experimental FSO network in TUKE campus, Košice, Slovakia. Our FSO experimental network has three links with different physical distances between each FSO heads. Weather conditions have a tremendous impact on FSO operation in terms of FSO availability. FSO link availability is the percentage of time over a year that the FSO link will be operational. It is necessary to evaluate the climate and weather at the actual geographical location where FSO link is going to be mounted. It is important to determine the impact of a light scattering, absorption, turbulence and receiving optical power at the particular FSO link. Visibility has one of the most critical influences on the quality of an FSO optical transmission channel. FSO link availability is usually estimated using visibility information collected from nearby airport weather stations. Raw data from fog sensor (Fog Density, Relative Humidity, Temperature measured at each ms) are collected and processed by FSO Simulator software package developed at our Department. Based

  13. Complex data management for landslide monitoring in emergency conditions

    NASA Astrophysics Data System (ADS)

    Intrieri, Emanuele; Bardi, Federica; Fanti, Riccardo; Gigli, Giovanni; Fidolini, Francesco; Casagli, Nicola; Costanzo, Sandra; Raffo, Antonio; Di Massa, Giuseppe; Versace, Pasquale

    2017-04-01

    Urbanization, especially in mountain areas, can be considered a major cause for high landslide risk because of the increased exposure of elements at risk. Among the elements at risk, important communication routes such as highways, can be classified as critical infrastructures, since their rupture can cause deaths and chain effects with catastrophic damages on society. The resiliency policy involves prevention activities but also, and more importantly, those activities needed to maintain functionality after disruption and promptly alert incoming catastrophes. To tackle these issues, early warning systems are increasingly employed. However, a gap exists between the ever more technologically advanced instruments and the actual capability of exploiting their full potential. This is due to several factors such as the limited internet connectivity with respect to big data transfers, or the impossibility for operators to check a continuous flow of real time information. A ground-based interferometric synthetic aperture radar was installed along the A16 highway (Campania Region, Southern Italy) to monitor an unstable slope threatening this infrastructure. The installation was in an area where the only internet connection available was 3G, with a limit of 2 gigabyte data transfer per month. On the other hand interferometric data are complex numbers organized in a matrix where each pixel contains both phase and amplitude information of the backscattered signal. The radar employed produced a 1001x1001 complex matrix (corresponding to 7 megabytes) every 5 minutes. Therefore there was the need to reduce the massive data flow produced by the radar. For this reason data were locally and automatically elaborated in order to produce, from a complex matrix, a simple ASCII grid containing only the pixel by pixel displacement value, which is derived from the phase information. Then, since interferometry only measures the displacement component projected along the radar line of sight

  14. Monitoring pasture damage in subarid conditions in south of Spain.

    NASA Astrophysics Data System (ADS)

    Díaz, Felix; Saa-Requejo, Antonio; Martín-Sotoca, Juan J.; Dalezios, Nicolas; Tarquis, Ana M.

    2016-04-01

    This work analyzes four areas in Murcia region (Spain) to study the application of the indexed pastures insurances in arid and subarid conditions. For this purpose four zones of 2,5 km have been selected, all of them close to meteorological stations, with records covering the period since 2001 to 2012 and with compound MODIS images of 500 m x 500 m from eight days intervals on that period. In addition to obtain historical series of the Normalized Difference Vegetation Index (NDVI), other indices (NDWI, NDDI and NDWU) have been computed. The results of this study show that NDWU provides additional information to that in the NDVI. In fact, according to our results, NDDI does not provide accurate information for the regions analyzed in this particular case study. In an attempt to relate precipitancy indices and drought situations in the four areas selected, we have showed that Standardized Precipitation Index (SPI) cannot be used accurately for drought intensity assessment. Then new indices have been formulated based on Markov chains: PI5mm and PI10mm.These indices can assess on isolated droughts which are missed by using indexed insurances. Nonetheless, it has also been observed that abnormal droppings in the NDWI index often coincide with drought lapses well established by indexed insurances. Acknowledgements First author acknowledges the Research Grant obtained from CEIGRAM in 2015

  15. Monitoring pavement condition using Smart Dust under surge time synchronization

    NASA Astrophysics Data System (ADS)

    Pei, Jin-Song; Ivey, Richard A.; Lin, Hungjr; Landrum, Aaron; Sandburg, Colby J.; King, Timothy; Zaman, Musharraf M.; Refai, Hazem H.; Mai, Eric C.; Oshlake, Olatunda; Heriba, Adam; Hurt, Erin

    2007-04-01

    This paper is a continuation of the authors' previous effort (presented at SPIE 2006) of developing a "Smart Dust" (Mica2 Motes)-based wireless sensor network to detect hazardous roadway surface conditions. New developments reported herein focus on a series of investigations into the performance of "Smart Dust" wireless network. A series of pseudo-outdoor and road tests are conducted in this study. The network is fairly small with a large transmitting range between each Mote, compared with the published work on applying the same product. Surge Time Synchronization is explored in the specific application to allow each Mote to "wake up" periodically at a predefined time interval. In addition, a fairly simplistic pattern classification algorithm is embedded into the Motes to create the smart wireless sensing application. Many performance metrics of the adopted "Smart Dust" wireless sensor network with a small size and large transmitting range are revealed in this study through a series of data processing efforts. Results are presented to examine (1) network connectivity, (2) packet delivery performance, (3) initial connection time, (4) error rate, (5) battery life, and (6) other network routing properties such as the parent time histories for each Mote. These results and analysis form a database for future efforts to better understand the performance of and the collected results from "Smart Dust".

  16. 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...

  17. 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...

  18. On-line Monitoring for Cutting Tool Wear Condition Based on the Parameters

    NASA Astrophysics Data System (ADS)

    Han, Fenghua; Xie, Feng

    2017-07-01

    In the process of cutting tools, it is very important to monitor the working state of the tools. On the basis of acceleration signal acquisition under the constant speed, time domain and frequency domain analysis of relevant indicators monitor the online of tool wear condition. The analysis results show that the method can effectively judge the tool wear condition in the process of machining. It has certain application value.

  19. 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.

  20. Effect of calibration and environmental condition on the performance of direct-reading organic vapor monitors.

    PubMed

    Coffey, Christopher; LeBouf, Ryan; Lee, Larry; Slaven, James; Martin, Stephen

    2012-01-01

    The performance of three MIRAN SapphIRe Portable Infrared Ambient Air Analyzers and three Century Portable Toxic Vapor Analyzers equipped with photoionization (PID) and flame ionization (FID) detectors was compared with charcoal tube sampling. Relationships were investigated using two different calibration methods at four cyclohexane concentrations, three temperatures, and four relative humidities. For the first method, the TVA monitors were calibrated with a single concentration of methane for the FID, and isobutylene for the PID. The SapphIRe monitors were zeroed and the monitor's manufacturer-supplied library was used. For the second method, a five-point cyclohexane calibration curve was created for each monitor. Comparison of the monitor results of each calibration method (pooled data) indicated a significant difference between methods (t-test, p < 0.001), The SapphIRe group had results closer to the charcoal tubes with the second calibration method, while the PID and FID monitor groups performed better using the first calibration method. The PID monitor group's performance was affected only at the 90% relative humidity (RH) condition. Using the first method, the monitor readings were compared with the charcoal tube average using mixed linear model analyses of variance (ANOVAs) and regression. The ANOVA results showed there was a statistically significant difference among readings from all monitor types (p <0.0001). The regression results demonstrated that the SapphIRe (r² = 0.97) and FID (r² = 0.92) monitor groups correlated well with the charcoal tubes. The PID monitor group had a similar correlation when 90% RH was excluded (r² = 0.94) but had a weaker correlation when it was included (r² = 0.58). The operator should take care when using these monitors at high concentrations and the PID monitors at high humidities, consider the variability between units of the same monitor, and conduct performance verification of the monitor being used.

  1. 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.

  2. 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.

  3. 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.

  4. Condition monitoring of distributed systems using two-stage Bayesian inference data fusion

    NASA Astrophysics Data System (ADS)

    Jaramillo, Víctor H.; Ottewill, James R.; Dudek, Rafał; Lepiarczyk, Dariusz; Pawlik, Paweł

    2017-03-01

    In industrial practice, condition monitoring is typically applied to critical machinery. A particular piece of machinery may have its own condition monitoring system that allows the health condition of said piece of equipment to be assessed independently of any connected assets. However, industrial machines are typically complex sets of components that continuously interact with one another. In some cases, dynamics resulting from the inception and development of a fault can propagate between individual components. For example, a fault in one component may lead to an increased vibration level in both the faulty component, as well as in connected healthy components. In such cases, a condition monitoring system focusing on a specific element in a connected set of components may either incorrectly indicate a fault, or conversely, a fault might be missed or masked due to the interaction of a piece of equipment with neighboring machines. In such cases, a more holistic condition monitoring approach that can not only account for such interactions, but utilize them to provide a more complete and definitive diagnostic picture of the health of the machinery is highly desirable. In this paper, a Two-Stage Bayesian Inference approach allowing data from separate condition monitoring systems to be combined is presented. Data from distributed condition monitoring systems are combined in two stages, the first data fusion occurring at a local, or component, level, and the second fusion combining data at a global level. Data obtained from an experimental rig consisting of an electric motor, two gearboxes, and a load, operating under a range of different fault conditions is used to illustrate the efficacy of the method at pinpointing the root cause of a problem. The obtained results suggest that the approach is adept at refining the diagnostic information obtained from each of the different machine components monitored, therefore improving the reliability of the health assessment of

  5. 14 CFR 414.31 - Monitoring compliance with the terms and conditions of a safety approval.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... conditions of a safety approval. 414.31 Section 414.31 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION LICENSING SAFETY APPROVALS Safety Approval Review and Issuance § 414.31 Monitoring compliance with the terms and conditions of a safety approval...

  6. Unraveling fabrication and calibration of wearable gas monitor for use under free-living conditions.

    PubMed

    Yue Deng; Cheng Chen; Tsow, Francis; Xiaojun Xian; Forzani, Erica

    2016-08-01

    Volatile organic compounds (VOC) are organic chemicals that have high vapor pressure at regular conditions. Some VOC could be dangerous to human health, therefore it is important to determine real-time indoor and outdoor personal exposures to VOC. To achieve this goal, our group has developed a wearable gas monitor with a complete sensor fabrication and calibration protocol for free-living conditions. Correction factors for calibrating the sensors, including sensitivity, aging effect, and temperature effect are implemented into a Quick Response Code (QR code), so that the pre-calibrated quartz tuning fork (QTF) sensor can be used with the wearable monitor under free-living conditions.

  7. 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.

  8. Vibration Condition Monitoring Techniques for Fault Diagnosis of Electromotor with 1.5 Kw Power

    NASA Astrophysics Data System (ADS)

    Mohamadi Monavar, H.; Ahmadi, H.; Mohtasebi, S. S.; Hasani, S.

    Vibration analysis is the main conditions monitoring techniques for machinery maintenance and fault diagnosis. This technique has its unique advantages and disadvantages associated with the monitoring and fault diagnosis of machinery. When this technique is conducted independently, only a portion of machine faults are typically diagnosed. However, practical experience has shown that this technique in a machine condition monitoring program provides useful reliable information, bringing significant cost benefits to industry. The objective of this research is to investigate the correlation between vibration analysis and fault diagnosis. This was achieved by vibration analysis and investigating different operating conditions of an experimental electromotor. The electromotor was initially run under normal operating conditions as a comparative test. A series of tests were then conducted corresponding to different operating condition. Our varieties were speed of electromotor at three levels, respectively 500, 1000 and 1500 rpm. We did three faults in our electromotor; there were misalignment, looseness and bad bearing. We coupled our electromotor to the variable blade fan and applied several load on that by changing the number of blade of fan. We have chosen 2, 6 and 10 blades fan to apply three different loads on our electromotor. Vibration data was regularly collected. Numerical data produced by vibration analysis were compared with vibration spectra in normal condition of healthy machine, in order to quantify the effectiveness of the vibration condition monitoring technique. The results from this paper have given more understanding on the dependent roles of vibration analysis in predicting and diagnosing machine faults.

  9. 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.

  10. Image edge detection based tool condition monitoring with morphological component analysis.

    PubMed

    Yu, Xiaolong; Lin, Xin; Dai, Yiquan; Zhu, Kunpeng

    2017-07-01

    The measurement and monitoring of tool condition are keys to the product precision in the automated manufacturing. To meet the need, this study proposes a novel tool wear monitoring approach based on the monitored image edge detection. Image edge detection has been a fundamental tool to obtain features of images. This approach extracts the tool edge with morphological component analysis. Through the decomposition of original tool wear image, the approach reduces the influence of texture and noise for edge measurement. Based on the target image sparse representation and edge detection, the approach could accurately extract the tool wear edge with continuous and complete contour, and is convenient in charactering tool conditions. Compared to the celebrated algorithms developed in the literature, this approach improves the integrity and connectivity of edges, and the results have shown that it achieves better geometry accuracy and lower error rate in the estimation of tool conditions. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  11. 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.

  12. An integrated condition-monitoring method for a milling process using reduced decomposition features

    NASA Astrophysics Data System (ADS)

    Liu, Jie; Wu, Bo; Wang, Yan; Hu, Youmin

    2017-08-01

    Complex and non-stationary cutting chatter affects productivity and quality in the milling process. Developing an effective condition-monitoring approach is critical to accurately identify cutting chatter. In this paper, an integrated condition-monitoring method is proposed, where reduced features are used to efficiently recognize and classify machine states in the milling process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition, and Shannon power spectral entropy is calculated to extract features from the decomposed signals. Principal component analysis is adopted to reduce feature size and computational cost. With the extracted feature information, the probabilistic neural network model is used to recognize and classify the machine states, including stable, transition, and chatter states. Experimental studies are conducted, and results show that the proposed method can effectively detect cutting chatter during different milling operation conditions. This monitoring method is also efficient enough to satisfy fast machine state recognition and classification.

  13. Multistage gearbox condition monitoring using motor current signature analysis and Kolmogorov Smirnov test

    NASA Astrophysics Data System (ADS)

    Kar, Chinmaya; Mohanty, A. R.

    2006-02-01

    Even though there are a number of condition monitoring and analysis techniques, researchers are in search of a simple and easy way to monitor vibration of a gearbox, which is an omnipresent and an important power transmission component in any machinery. Motor current signature analysis (MCSA) has been the most recent addition as a non-intrusive and easy to measure condition monitoring technique. The objective of this paper is to detect artificially introduced defects in gears of a multistage automotive transmission gearbox at different gear operations using MCSA as a condition monitoring technique and Kolmogorov-Smirnov (KS) test as an analysis technique assuming that any defect or load has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. Steady as well as fluctuating load conditions on the gearbox are tested for both vibration and current signatures during different gear operations. It is concluded that combined MCSA and KS test can be an effective way to monitor and detect faults in gears.

  14. 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.

  15. A hybrid fiber-optic sensor system for condition monitoring of large scale wind turbine blades

    NASA Astrophysics Data System (ADS)

    Kim, Dae-gil; Kim, Hyunjin; Sampath, Umesh; Song, Minho

    2015-07-01

    A hybrid fiber-optic sensor system which combines fiber Bragg grating (FBG) sensors and a Michelson interferometer is suggested for condition monitoring uses of large scale wind turbine blades. The system uses single broadband light source to address both sensors, which simplifies the optical setup and enhances the cost-effectiveness of condition monitoring system. An athermal-packaged FBG is used to supply quasi-coherent light for the Michelson interferometer demodulation. For the feasibility test, different profiles of test strain, temperature and vibration have been applied to test structures, and successfully reconstructed with the proposed sensor system.

  16. Progress toward an advanced condition monitoring system for reusable rocket engines

    NASA Technical Reports Server (NTRS)

    Maram, J.; Barkhoudarian, S.

    1987-01-01

    A new generation of advanced sensor technologies will allow the direct measurement of critical/degradable rocket engine components' health and the detection of degraded conditions before component deterioration affects engine performance, leading to substantial improvements in reusable engines' operation and maintenance. When combined with a computer-based engine condition-monitoring system, these sensors can furnish a continuously updated data base for the prediction of engine availability and advanced warning of emergent maintenance requirements. Attention is given to the case of a practical turbopump and combustion device diagnostic/prognostic health-monitoring system.

  17. 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.

  18. [Research on the inner wall condition monitoring method of ring forgings based on infrared spectra].

    PubMed

    Fu, Xian-bin; Liu, Bin; Wei, Bin; Zhang, Yu-cun; Liu, Zhao-lun

    2015-01-01

    In order to grasp the inner wall condition of ring forgings, an inner wall condition monitoring method based on infrared spectra for ring forgings is proposed in the present paper. Firstly, using infrared spectroscopy the forgings temperature measurement system was built based on the three-level FP-cavity LCTF. The two single radiation spectra from the forgings' surface were got using the three-level FP-cavity LCTF. And the temperature measuring of the surface forgings was achieved according to the infrared double-color temperature measuring principle. The measuring accuracy can be greatly improved by this temperature measurement method. Secondly, on the basis of the Laplace heat conduction differential equation the inner wall condition monitoring model was established by the method of separating variables. The inner wall condition monitoring of ring forgings was realized via combining the temperature data and the forgings own parameter information. Finally, this method is feasible according to the simulation experiment. The inner wall condition monitoring method can provide the theoretical basis for the normal operating of the ring forgings.

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

    PubMed

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

    2014-01-27

    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.

  20. 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

  1. New Fast Beam Conditions Monitoring (BCM1F) system for CMS

    NASA Astrophysics Data System (ADS)

    Zagozdzinska, A. A.; Bell, A. J.; Dabrowski, A. E.; Hempel, M.; Henschel, H. M.; Karacheban, O.; Przyborowski, D.; Leonard, J. L.; Penno, M.; Pozniak, K. T.; Miraglia, M.; Lange, W.; Lohmann, W.; Ryjov, V.; Lokhovitskiy, A.; Stickland, D.; Walsh, R.

    2016-01-01

    The CMS Beam Radiation Instrumentation and Luminosity (BRIL) project is composed of several systems providing the experiment protection from adverse beam conditions while also measuring the online luminosity and beam background. Although the readout bandwidth of the Fast Beam Conditions Monitoring system (BCM1F—one of the faster monitoring systems of the CMS BRIL), was sufficient for the initial LHC conditions, the foreseen enhancement of the beams parameters after the LHC Long Shutdown-1 (LS1) imposed the upgrade of the system. This paper presents the new BCM1F, which is designed to provide real-time fast diagnosis of beam conditions and instantaneous luminosity with readout able to resolve the 25 ns bunch structure.

  2. The role of sample surveys for monitoring the condition of the nation's lakes.

    PubMed

    Larsen, D P; Thornton, K W; Urquhart, N S; Paulsen, S G

    1994-09-01

    In order to meet a growing need to determine the condition of the nation's ecosystems and how their condition is changing, the U.S. Environmental Protection Agency (EPA) developed EMAP, the Environmental Monitoring and Assessment Program. A common survey design serves as the foundation on which to base monitoring of status and trends among diverse ecosystem types. In this paper, we describe the need for a statistically based survey design, briefly summarize the basic EMAP design, describe how that design is tailored for the selection of a probability sample of lakes on which to make measurements of lake condition, and illustrate the process for selecting a sample of lakes in the northeastern United States. Finally, we illustrate how measurements taken on the sample of lakes can be summarized, with known uncertainty, to describe the condition of a population of lakes.

  3. Aspects of model-based rocket engine condition monitoring and control

    NASA Technical Reports Server (NTRS)

    Karr, Gerald R.; Helmicki, Arthur J.

    1994-01-01

    A rigorous propulsion system modelling method suitable for control and condition monitoring purposes is developed. Previously developed control oriented methods yielding nominal models for gaseous medium propulsion systems are extended to include both nominal and anomalous models for liquid mediums in the following two ways. First, thermodynamic and fluid dynamic properties for liquids such as liquid hydrogen are incorporated into the governing equations. Second, anomalous conditions are captured in ways compatible with existing system theoretic design tools so that anomalous models can be constructed. Control and condition monitoring based methods are seen as an improvement over some existing modelling methods because such methods typically do not rigorously lead to low order models nor do they provide a means for capturing anomalous conditions. Applications to the nominal SSME HPFP and degraded HPFP serve to illustrate the approach.

  4. Model-based condition monitoring of PEM fuel cell using Hotelling T 2 control limit

    NASA Astrophysics Data System (ADS)

    Xue, X.; Tang, J.; Sammes, N.; Ding, Y.

    Although a variety of design and control strategies have been proposed to improve the performance of polymer electrolyte membrane (PEM) fuel cell systems, temporary faults in such systems still might occur during operations due to the complexity of the physical process and the functional limitations of some components. The development of an effective condition monitoring system that can detect these faults in a timely manner is complicated by the operating condition variation, the significant variability/uncertainty of the fuel cell system, and the measurement noise. In this research, we propose a model-based condition monitoring scheme that employs the Hotelling T 2 statistical analysis for fault detection of PEM fuel cells. Under a given operating condition, the instantaneous load current, the temperature and fuel/gas source pressures of the fuel cell are measured. These measurements are then fed into a lumped parameter dynamic fuel cell model for the establishment of the baseline under the same operating condition for comparison. The fuel cell operation is simulated under statistical sampling of parametric uncertainties with specified statistics (mean and variance) that account for the system variability/uncertainty and measurement noise. This yields a group of output voltages (under the same operating condition but with uncertainties) as the baseline. Fault detection is facilitated by comparing the real-time measurement of the fuel cell output voltage with the baseline voltages by employing the Hotelling T 2 statistical analysis. The baseline voltages are used to evaluate the output T 2 statistics under normal operating condition. Then, with a given confidence level the upper control limit can be specified. Fault condition will be declared if the T 2 statistics of real-time voltage measurement exceeds the upper control limit. This model-based robust condition monitoring scheme can deal with the operating condition variation, various uncertainties in a fuel cell

  5. 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

  6. 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.

  7. 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.

  8. Structural condition assessment of long-span suspension bridges using long-term monitoring data

    NASA Astrophysics Data System (ADS)

    Yang, Deng; Youliang, Ding; Aiqun, Li

    2010-03-01

    This paper focuses on developing an online structural condition assessment technique using long-term monitoring data measured by a structural health monitoring system. The seasonal correlations of frequency-temperature and beam-end displacement-temperature for the Runyang Suspension Bridge are performed, first. Then, a statistical modeling technique using a six-order polynomial is further applied to formulate the correlations of frequency-temperature and displacement-temperature, from which abnormal changes of measured frequencies and displacements are detected using the mean value control chart. Analysis results show that modal frequencies of higher vibration modes and displacements have remarkable seasonal correlations with the environmental temperature and the proposed method exhibits a good capability for detecting the micro damage-induced changes of modal frequencies and displacements. The results demonstrate that the proposed method can effectively eliminate temperature complications from frequency and displacement time series and is well suited for online condition monitoring of long-span suspension bridges.

  9. 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.

  10. Principles for the monitoring and evaluation of wetland extent, condition and function in Australia.

    PubMed

    Saintilan, Neil; Imgraben, Sarah

    2012-01-01

    The monitoring of resource condition is receiving renewed attention across several levels of government in Australia. This interest is linked to substantial investment in environmental remediation and aquatic ecosystem restoration in particular. In this context, it is timely to consider principles which ought to guide the development and implementation of monitoring programmes for wetland ecosystems. A framework is established which places monitoring in the context of the strategic adaptive management of wetlands. This framework requires there has to be clear goals for the extent and condition of the resource, with these goals being defined within thresholds of acceptable variability. Qualitative and, where possible, quantitative conceptual models linking management interventions to management goals should be the basis of indicator selection and assessment. The intensity of sampling ought to be informed by pilot surveys of statistical power in relation to the thresholds of acceptable variability identified within the management plan.

  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. 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…

  13. 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.

  14. 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…

  15. 14 CFR 414.31 - Monitoring compliance with the terms and conditions of a safety approval.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Monitoring compliance with the terms and conditions of a safety approval. 414.31 Section 414.31 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION LICENSING SAFETY APPROVALS Safety Approval Review and Issuance §...

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

    USDA-ARS?s Scientific Manuscript database

    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...

  17. Monitoring Global Crop Condition Indicators Using a Web-Based Visualization Tool

    Treesearch

    Bob Tetrault; Bob Baldwin

    2006-01-01

    Global crop condition information for major agricultural regions in the world can be monitored using the web-based application called Crop Explorer. With this application, U.S. and international producers, traders, researchers, and the public can access remote sensing information used by agricultural economists and scientists who predict crop production worldwide. For...

  18. Development of a Decision Support System for Monitoring, Reporting, Forecasting Ecological Conditions of the Appalachian Trail

    Treesearch

    Y. Wang; R. Nemani; F. Dieffenbach; K. Stolte; G. Holcomb

    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 decision-making on management of the A.T. by providing a coherent framework for data integration,...

  19. An approach to effectiveness monitoring of floodplain channel aquatic habitat: channel condition assessment.

    Treesearch

    Richard D. Woodsmith; James R. Noel; Michael L. Dilger

    2005-01-01

    The condition of aquatic habitat and the health of species dependent on that habitat are issues of significant concern to land management agencies, other organizations, and the public at large in southeastern Alaska, as well as along much of the Pacific coastal region of North America. We develop and test a set of effectiveness monitoring procedures for measuring...

  20. 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.

  1. 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.

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

    USDA-ARS?s Scientific Manuscript database

    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 ...

  3. Smartphone ownership and interest in mobile applications to monitor symptoms of mental health conditions.

    PubMed

    Torous, John; Friedman, Rohn; Keshavan, Matcheri

    2014-01-21

    Patient retrospective recollection is a mainstay of assessing symptoms in mental health and psychiatry. However, evidence suggests that these retrospective recollections may not be as accurate as data collection though the experience sampling method (ESM), which captures patient data in "real time" and "real life." However, the difficulties in practical implementation of ESM data collection have limited its impact in psychiatry and mental health. Smartphones with the capability to run mobile applications may offer a novel method of collecting ESM data that may represent a practical and feasible tool for mental health and psychiatry. This paper aims to provide data on psychiatric patients' prevalence of smartphone ownership, patterns of use, and interest in utilizing mobile applications to monitor their mental health conditions. One hundred psychiatric outpatients at a large urban teaching hospital completed a paper-and-pencil survey regarding smartphone ownership, use, and interest in utilizing mobile applications to monitor their mental health condition. Ninety-seven percent of patients reported owning a phone and 72% reported that their phone was a smartphone. Patients in all age groups indicated greater than 50% interest in using a mobile application on a daily basis to monitor their mental health condition. Smartphone and mobile applications represent a practical opportunity to explore new modalities of monitoring, treatment, and research of psychiatric and mental health conditions.

  4. 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.

  5. 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.

  6. 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

  7. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings

    PubMed Central

    Liu, Jie; Hu, Youmin; Wu, Bo; Wang, Yan; Xie, Fengyun

    2017-01-01

    The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD). Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features’ information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components. PMID:28524088

  8. 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.

  9. Condition Monitoring of a Motor-Operated Valve Using Estimated Motor Torque

    NASA Astrophysics Data System (ADS)

    Chai, Jangbom; Kang, Shinchul; Park, Sungkeun; Hong, Sungyull; Lim, Chanwoo

    This paper is concerned with the development of data analysis methods to be used in on-line monitoring and diagnosis of Motor-Operated Valves (MOVs) effectively and accurately. The technique to be utilized includes the electrical measurements and signal processing to estimate electric torque of induction motors, which are attached to most of MOV systems. The estimated torque of an induction motor is compared with the directly measured torque using a torque cell in various loading conditions including the degraded voltage conditions to validate the estimating scheme. The accuracy of the estimating scheme is presented. The advantages of the estimated torque signatures are reviewed over the currently used ones such as the current signature and the power signature in several respects: accuracy, sensitivity, resolution and so on. Additionally, the estimated torque methods are suggested as a good way to monitor the conditions of MOVs with higher accuracy.

  10. Monitoring strategies for re-establishment of ecological reference conditions: possibilities and limitations.

    PubMed

    Alve, Elisabeth; Lepland, Aivo; Magnusson, Jan; Backer-Owe, Kristian

    2009-01-01

    The ecological status of an environment should be evaluated by comparison with local "reference conditions", here defined as the pre-industrial ecological status of the 19th century. This pilot study illustrates how micropalaeontological monitoring, using benthic foraminifera (protists) and associated geochemical parameters preserved in inner Oslofjord (Norway) sediments, characterise local reference conditions. In order to optimise the usefulness of the ecological information held by foraminifera and enable characterisation of temporal changes in environmental quality beyond time intervals covered by biological time-series, the Norwegian governmental macrofauna-based classification system is applied on fossil benthic foraminiferal assemblages. Quantitative comparisons demonstrate deteriorating ecological status in response to increased anthropogenic forcing (eutrophication, micropollutants), including a 73% loss in number of foraminiferal species. Despite reduced pollution during the past decades and, at one site, capping of polluted sediments with clean clay, the reference conditions are far from re-established. Micropalaeontological monitoring requires net sediment accumulation basins and careful considerations of taphonomic processes.

  11. 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.

  12. 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.

  13. Automated System Of Monitoring Of The Physical Condition Of The Staff Of The Enterprise

    NASA Astrophysics Data System (ADS)

    Pilipenko, A.

    2017-01-01

    In the work the author solves an important applied problem of increasing of safety of engineering procedures and production using technologies of monitoring of a condition of employees. The author offers a work algorithm, structural and basic electric schemes of system of collection of data of employee’s condition of the enterprise and some parameters of the surrounding environment. In the article the author offers an approach to increasing of efficiency of acceptance of management decisions at the enterprise at the expense of the prompt analysis of information about employee’s condition and productivity of his work and also about various parameters influencing these factors.

  14. 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.

  15. Thick-film acoustic emission sensors for use in structurally integrated condition-monitoring applications.

    PubMed

    Pickwell, Andrew J; Dorey, Robert A; Mba, David

    2011-09-01

    Monitoring the condition of complex engineering structures is an important aspect of modern engineering, eliminating unnecessary work and enabling planned maintenance, preventing failure. Acoustic emissions (AE) testing is one method of implementing continuous nondestructive structural health monitoring. A novel thick-film (17.6 μm) AE sensor is presented. Lead zirconate titanate thick films were fabricated using a powder/sol composite ink deposition technique and mechanically patterned to form a discrete thick-film piezoelectric AE sensor. The thick-film sensor was benchmarked against a commercial AE device and was found to exhibit comparable responses to simulated acoustic emissions.

  16. Remote monitoring as a tool in condition assessment of a highway bridge

    NASA Astrophysics Data System (ADS)

    Tantele, Elia A.; Votsis, Renos A.; Onoufriou, Toula; Milis, Marios; Kareklas, George

    2016-08-01

    The deterioration of civil infrastructure and their subsequent maintenance is a significant problem for the responsible managing authorities. The ideal scenario is to detect deterioration and/or structural problems at early stages so that the maintenance cost is kept low and the safety of the infrastructure remains undisputed. The current inspection regimes implemented mostly via visual inspection are planned at specific intervals but are not always executed on time due to shortcomings in expert personnel and finance. However the introduction of technological advances in the assessment of infrastructures provides the tools to alleviate this problem. This study describes the assessment of a highway RC bridge's structural condition using remote structural health monitoring. A monitoring plan is implemented focusing on strain measurements; as strain is a parameter influenced by the environmental conditions supplementary data are provided from temperature and wind sensors. The data are acquired using wired sensors (deployed at specific locations) which are connected to a wireless sensor unit installed at the bridge. This WSN application enables the transmission of the raw data from the field to the office for processing and evaluation. The processed data are then used to assess the condition of the bridge. This case study, which is part of an undergoing RPF research project, illustrates that remote monitoring can alleviate the problem of missing structural inspections. Additionally, shows its potential to be the main part of a fully automated smart procedure of obtaining structural data, processed them and trigger an alarm when certain undesirable conditions are met.

  17. Reduction of Doppler effect for the needs of wayside condition monitoring system of railway vehicles

    NASA Astrophysics Data System (ADS)

    Dybała, Jacek; Radkowski, Stanisław

    2013-07-01

    Technology of acoustic condition monitoring of vehicles in motion is based on the assumption that diagnostically relevant information is stored in the acoustic signal generated by a passing vehicle. Analyzing the possibilities of increasing the effectiveness of condition monitoring of a passing vehicle with stationary microphones, it should be noted that the acoustic signal recorded in these conditions is disturbed with the disturbance resulting from the Doppler effect. Reduction of signal's frequential structure disturbance resulting from the Doppler effect allows efficient analysis of changes in frequential structure of recorded signals and as a result extraction of relevant diagnostic information related with technical condition of running gear of vehicle. This article presents a method for removal of signal's frequential structure disturbances related with relative move of vehicles and stationary monitoring station. For elimination of the frequential non-stationary of signals disturbance-oriented dynamic signal resampling method was used. The paper provides a test of two methods for defining the time course of local disturbance of signal's frequential structure: the method based on the Hilbert transform and the method of analytical description of signal's disturbance based on the knowledge of a phenomenon that causes frequential non-stationarity of signals. As an example, the results of the processing and analysis of acoustic signals recorded by wayside measuring station, during the passage of WM-15A railway vehicle on an experimental track of Polish Railway Institute, are presented.

  18. Monitoring working conditions and health of older workers in Dutch construction industry.

    PubMed

    Hoonakker, Peter; van Duivenbooden, Cor

    2010-06-01

    Accurate reporting of work-related conditions is necessary to monitor workplace health and safety and to identify the interventions that are most needed. In the Netherlands, working conditions and health are monitored on an aggregated level in the construction industry. One of the purposes of monitoring is to identify specific risk factors and risk groups. The objectives of this study was to examine (1) whether older workers (> or =55 years) in the construction industry are a special group at risk and (2) whether there are specific risk factors for older workers in the construction industry. Every 2 years, more than 70,000 construction workers in the Netherlands fill out a questionnaire as part of their periodic health checkup. In a repeated cross-sectional (trend) design, we compared working conditions (physical and psychological demands), musculoskeletal disorders (symptoms and conditions), and injuries of older workers with other age categories. Older construction workers have fewer complaints about physically demanding work and psychosocial workload, but have more complaints about working in awkward postures. Older workers have more complaints about their health than workers in other age categories. Older construction workers have fewer injuries than younger workers. Older construction workers are a risk group for musculoskeletal disorders. Working in awkward postures can be considered a risk factor for older workers in construction industry. 2010 Wiley-Liss, Inc.

  19. Measuring various sizes of H-reflex while monitoring the stimulus condition.

    PubMed

    Hiraoka, Koichi

    2002-11-01

    The purpose of this study was to assess the usefulness of a new technique that measured various sizes of the soleus H-reflex, while monitoring the stimulus condition. Eight healthy volunteers participated in this experiment. In the new technique, an above-motor-threshold conditioning stimulus was given to the tibial nerve 10-12 ms after a below-motor-threshold test stimulus. The conditioning stimulus evoked a direct M-wave, which was followed by a test-stimulus-evoked H-reflex. This reflex was followed by a conditioning stimulus-evoked H-reflex. The amount of the voluntary-contraction-induced facilitation of the H-reflex was similar for both the new technique and conventional technique, in which an above-motor-threshold test stimulus was given without a conditioning stimulus. Using the new technique, we found that the amount of facilitation increased linearly with the size of the test H-reflex. This technique allows us to evoke various sizes of H-reflex while monitoring a stimulus condition, and is useful for measuring H-reflexes during voluntary movement.

  20. Remote sensing of Northern mines: supporting operation and environmental monitoring in cold conditions

    NASA Astrophysics Data System (ADS)

    Tuomela, Anne; Davids, Corine; Knutsson, Sven; Knutsson, Roger; Rauhala, Anssi; Rossi, Pekka M.; Rouyet, Line

    2017-04-01

    Northern areas of Finland, Sweden and Norway have mineral-rich deposits. There are several active mines in the area but also closed ones and deposits with plans for future mining. With increasing demand for environmental protection in the sensitive Northern conditions, there is a need for more comprehensive monitoring of the mining environment. In our study, we aim to develop new opportunities to use remote sensing data from satellites and unmanned aerial vehicles (UAVs) in improving mining safety and monitoring, for example in the case of mine waste storage facilities. Remote sensing methods have evolved fast, and could in many cases enable precise, reliable, and cost-efficient data collection over large areas. The study has focused on four mining areas in Northern Fennoscandia. Freely available medium-resolution (e.g. Sentinel-1), commercial high-resolution (e.g. TerraSAR-X) and Synthetic Aperture Radar (SAR) data has been collected during 2015-2016 to study how satellite remote sensing could be used e.g. for displacement monitoring using SAR Interferometry (InSAR). Furthermore, UAVs have been utilized in similar data collection in a local scale, and also in collection of thermal infrared data for hydrological monitoring of the areas. The development and efficient use of the methods in mining areas requires experts from several fields. In addition, the Northern conditions with four distinct seasons bring their own challenges for the efficient use of remote sensing, and further complicate their integration as standardised monitoring methods for mine environments. Based on the initial results, remote sensing could especially enhance the monitoring of large-scale structures in mine areas such as tailings impoundments.

  1. 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

  2. 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.

  3. 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

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

    PubMed

    Zhang, Cunji; Yao, Xifan; Zhang, Jianming

    2015-12-03

    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.

  5. Construction Condition and Damage Monitoring of Post-Tensioned PSC Girders Using Embedded Sensors

    PubMed Central

    Shin, Kyung-Joon; Lee, Seong-Cheol; Kim, Yun Yong; Kim, Jae-Min; Park, Seunghee; Lee, Hwanwoo

    2017-01-01

    The potential for monitoring the construction of post-tensioned concrete beams and detecting damage to the beams under loading conditions was investigated through an experimental program. First, embedded sensors were investigated that could measure pre-stress from the fabrication process to a failure condition. Four types of sensors were installed on a steel frame, and the applicability and the accuracy of these sensors were tested while pre-stress was applied to a tendon in the steel frame. As a result, a tri-sensor loading plate and a Fiber Bragg Grating (FBG) sensor were selected as possible candidates. With those sensors, two pre-stressed concrete flexural beams were fabricated and tested. The pre-stress of the tendons was monitored during the construction and loading processes. Through the test, it was proven that the variation in thepre-stress had been successfully monitored throughout the construction process. The losses of pre-stress that occurred during a jacking and storage process, even those which occurred inside the concrete, were measured successfully. The results of the loading test showed that tendon stress and strain within the pure span significantly increased, while the stress in areas near the anchors was almost constant. These results prove that FBG sensors installed in a middle section can be used to monitor the strain within, and the damage to pre-stressed concrete beams. PMID:28796156

  6. 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.

  7. 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.

  8. Monitoring psychosocial stress at work: development of the Psychosocial Working Conditions Questionnaire.

    PubMed

    Widerszal-Bazyl, M; Cieślak, R

    2000-01-01

    Many studies on the impact of psychosocial working conditions on health prove that psychosocial stress at work is an important risk factor endangering workers' health. Thus it should be constantly monitored like other work hazards. The paper presents a newly developed instrument for stress monitoring called the Psychosocial Working Conditions Questionnaire (PWC). Its structure is based on Robert Karasek's model of job stress (Karasek, 1979; Karasek & Theorell, 1990). It consists of 3 main scales Job Demands, Job Control, Social Support and 2 additional scales adapted from the Occupational Stress Questionnaire (Elo, Leppanen, Lindstrom, & Ropponen, 1992), Well-Being and Desired Changes. The study of 8 occupational groups (bank and insurance specialists, middle medical personnel, construction workers, shop assistants, government and self-government administration officers, computer scientists, public transport drivers, teachers, N = 3,669) indicates that PWC has satisfactory psychometrics parameters. Norms for the 8 groups were developed.

  9. Wireless acceleration sensor of moving elements for condition monitoring of mechanisms

    NASA Astrophysics Data System (ADS)

    Sinitsin, Vladimir V.; Shestakov, Aleksandr L.

    2017-09-01

    Comprehensive analysis of the angular and linear accelerations of moving elements (shafts, gears) allows an increase in the quality of the condition monitoring of mechanisms. However, existing tools and methods measure either linear or angular acceleration with postprocessing. This paper suggests a new construction design of an angular acceleration sensor for moving elements. The sensor is mounted on a moving element and, among other things, the data transfer and electric power supply are carried out wirelessly. In addition, the authors introduce a method for processing the received information which makes it possible to divide the measured acceleration into the angular and linear components. The design has been validated by the results of laboratory tests of an experimental model of the sensor. The study has shown that this method provides a definite separation of the measured acceleration into linear and angular components, even in noise. This research contributes an advance in the range of methods and tools for condition monitoring of mechanisms.

  10. Using Johnson Distribution for Automatic Threshold Setting in Wind Turbine Condition Monitoring System

    DTIC Science & Technology

    2014-12-23

    Using Johnson Distribution for Automatic Threshold Setting in Wind Turbine Condition Monitoring System Kun S. Marhadi1 and Georgios Alexandros...distribution could result in sub-optimal thresholds. Moreover, in wind turbine applications the collected data available may not rep- resent the whole...investigated. 1. INTRODUCTION Wind turbines are generally subject to aleatory uncertainty due to stochastic nature of the weather and the wind itself

  11. Dynamic Data-Driven Prognostics and Condition Monitoring of On-board Electronics

    DTIC Science & Technology

    2012-08-27

    STSA, Data Driven Prognostics, Time Series Sudipto Ghoshal, Mohammad Azam , Sunil Dixit Qualtech Systems Inc Putnam Park, Suite 501 100 Great Meadow...components, and condition monitoring of KN-4073 INS/GPS (used on Army’s MQ-8 Fire Scout UAV). (a) Papers published in peer-reviewed journals ( N /A for none...papers, including journal references, in the following categories: PaperReceived TOTAL: (b) Papers published in non-peer-reviewed journals ( N /A for none

  12. Lubricant oil condition monitoring using a scattering-free single-wavelength optical scheme

    NASA Astrophysics Data System (ADS)

    Mignani, A. G.; Ciaccheri, L.; Mencaglia, Andrea A.; Adriani, G.; Paccagnini, A.; Campatelli, M.; Ottevaere, H.; Thienpont, H.

    2014-05-01

    A simple and low-cost optical setup can be used for monitoring online the condition of lubricant oil in big machineries, as an action of preventive maintenance. The total acid number and the water content, as indicators of the lubricant oil quality, can be assessed by means of an integrating sphere for achieving scattering-free absorption measurements. For each indicator, spectroscopy showed that a peculiar wavelength is enough for predicting with good accuracy the value of the indicator.

  13. 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

  14. [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.

  15. 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.

  16. Informal and formal trail monitoring protocols and baseline conditions: Acadia National Park

    USGS Publications Warehouse

    Marion, Jeffrey L.; Wimpey, Jeremy F.; Park, L.

    2011-01-01

    At Acadia National Park, changing visitor use levels and patterns have contributed to an increasing degree of visitor use impacts to natural and cultural resources. To better understand the extent and severity of these resource impacts and identify effective management techniques, the park sponsored this research to develop monitoring protocols, collect baseline data, and identify suggestions for management strategies. Formal and informal trails were surveyed and their resource conditions were assessed and characterized to support park planning and management decision-making.

  17. 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

  18. 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.

  19. 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

  20. Semi-supervised vibration-based classification and condition monitoring of compressors

    NASA Astrophysics Data System (ADS)

    Potočnik, Primož; Govekar, Edvard

    2017-09-01

    Semi-supervised vibration-based classification and condition monitoring of the reciprocating compressors installed in refrigeration appliances is proposed in this paper. The method addresses the problem of industrial condition monitoring where prior class definitions are often not available or difficult to obtain from local experts. The proposed method combines feature extraction, principal component analysis, and statistical analysis for the extraction of initial class representatives, and compares the capability of various classification methods, including discriminant analysis (DA), neural networks (NN), support vector machines (SVM), and extreme learning machines (ELM). The use of the method is demonstrated on a case study which was based on industrially acquired vibration measurements of reciprocating compressors during the production of refrigeration appliances. The paper presents a comparative qualitative analysis of the applied classifiers, confirming the good performance of several nonlinear classifiers. If the model parameters are properly selected, then very good classification performance can be obtained from NN trained by Bayesian regularization, SVM and ELM classifiers. The method can be effectively applied for the industrial condition monitoring of compressors.

  1. Compressed-Sensing Reconstruction Based on Block Sparse Bayesian Learning in Bearing-Condition Monitoring

    PubMed Central

    Sun, Jiedi; Yu, Yang; Wen, Jiangtao

    2017-01-01

    Remote monitoring of bearing conditions, using wireless sensor network (WSN), is a developing trend in the industrial field. In complicated industrial environments, WSN face three main constraints: low energy, less memory, and low operational capability. Conventional data-compression methods, which concentrate on data compression only, cannot overcome these limitations. Aiming at these problems, this paper proposed a compressed data acquisition and reconstruction scheme based on Compressed Sensing (CS) which is a novel signal-processing technique and applied it for bearing conditions monitoring via WSN. The compressed data acquisition is realized by projection transformation and can greatly reduce the data volume, which needs the nodes to process and transmit. The reconstruction of original signals is achieved in the host computer by complicated algorithms. The bearing vibration signals not only exhibit the sparsity property, but also have specific structures. This paper introduced the block sparse Bayesian learning (BSBL) algorithm which works by utilizing the block property and inherent structures of signals to reconstruct CS sparsity coefficients of transform domains and further recover the original signals. By using the BSBL, CS reconstruction can be improved remarkably. Experiments and analyses showed that BSBL method has good performance and is suitable for practical bearing-condition monitoring. PMID:28635623

  2. Compressed-Sensing Reconstruction Based on Block Sparse Bayesian Learning in Bearing-Condition Monitoring.

    PubMed

    Sun, Jiedi; Yu, Yang; Wen, Jiangtao

    2017-06-21

    Remote monitoring of bearing conditions, using wireless sensor network (WSN), is a developing trend in the industrial field. In complicated industrial environments, WSN face three main constraints: low energy, less memory, and low operational capability. Conventional data-compression methods, which concentrate on data compression only, cannot overcome these limitations. Aiming at these problems, this paper proposed a compressed data acquisition and reconstruction scheme based on Compressed Sensing (CS) which is a novel signal-processing technique and applied it for bearing conditions monitoring via WSN. The compressed data acquisition is realized by projection transformation and can greatly reduce the data volume, which needs the nodes to process and transmit. The reconstruction of original signals is achieved in the host computer by complicated algorithms. The bearing vibration signals not only exhibit the sparsity property, but also have specific structures. This paper introduced the block sparse Bayesian learning (BSBL) algorithm which works by utilizing the block property and inherent structures of signals to reconstruct CS sparsity coefficients of transform domains and further recover the original signals. By using the BSBL, CS reconstruction can be improved remarkably. Experiments and analyses showed that BSBL method has good performance and is suitable for practical bearing-condition monitoring.

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

    PubMed

    Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

    2014-11-14

    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.

  4. THE MULTI-ISOTOPE PROCESS (MIP) MONITOR: A NEAR-REAL-TIME, NON-DESTRUCTIVE, INDICATOR OF SPENT NUCLEAR FUEL REPROCESSING CONDITIONS

    SciTech Connect

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

    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, non-destructively, 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 validation is currently under way and significant results are available. The latest experimental results, along with an overview of the method will be presented.

  5. 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

  6. 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.

  7. Psycho-physiological monitoring in real and simulated space flight conditions.

    PubMed

    Larina, I M; Bystritzkaya, A F; Smirnova, T M

    1997-07-01

    Earlier in simulating experiments from long isolation of small group in hermetic cabin we were found out the significant interrelation between changes physiological parameters and subjective appraisal of a condition, activity regulating systems of organism, individual variability of a colour choice, and also quality of operator's activity. On the basis of these results we develop a method of psychophysiological monitoring. The important component of a method is study of the variational characteristics of registered parameters, with the purpose of reception of the information about character of transients in organism. The present research is carried out in conditions of 135-daily isolation in a breadboard model MIR station (experiment HUBES). Its PURPOSE was study of dynamic psycho-emotional condition, simultaneously with study physiological and biochemical parameters, describing process of adaptation to complex conditions of ability to live. Besides were analyzed the results of circadian rhythm's researches during space flights of 6 Russian cosmonauts (duration from 70 till 182 days) on orbital MIR station.

  8. 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.

  9. 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.)

  10. A novel multivariate approach using science-based calibration for direct coating thickness determination in real-time NIR process monitoring.

    PubMed

    Möltgen, C-V; Herdling, T; Reich, G

    2013-11-01

    This study demonstrates an approach, using science-based calibration (SBC), for direct coating thickness determination on heart-shaped tablets in real-time. Near-Infrared (NIR) spectra were collected during four full industrial pan coating operations. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film up to a film thickness of 28 μm. The application of SBC permits the calibration of the NIR spectral data without using costly determined reference values. This is due to the fact that SBC combines classical methods to estimate the coating signal and statistical methods for the noise estimation. The approach enabled the use of NIR for the measurement of the film thickness increase from around 8 to 28 μm of four independent batches in real-time. The developed model provided a spectroscopic limit of detection for the coating thickness of 0.64 ± 0.03 μm root-mean square (RMS). In the commonly used statistical methods for calibration, such as Partial Least Squares (PLS), sufficiently varying reference values are needed for calibration. For thin non-functional coatings this is a challenge because the quality of the model depends on the accuracy of the selected calibration standards. The obvious and simple approach of SBC eliminates many of the problems associated with the conventional statistical methods and offers an alternative for multivariate calibration.

  11. Using Vibration Monitoring for Local Fault Detection on Gears Operating Under Fluctuating Load Conditions

    NASA Astrophysics Data System (ADS)

    Stander, C. J.; Heyns, P. S.; Schoombie, W.

    2002-11-01

    Gearboxes often operate under fluctuating load conditions during service. Conventional techniques for monitoring vibration are based on the assumption that changes in the measured structural response are caused by deterioration in the condition of the gearbox. However, this assumption is not valid for fluctuating load conditions. To find a methodology that could deal with such conditions, experiments were conducted on a gearbox test rig with different levels of tooth damage severity and the capability of applying fluctuating loads to the gear system. Different levels of fluctuation in constant loads as well as in sinusoidal, step and chirp loads were considered. The test data were order tracked and time synchronously averaged with the rotation of the shaft in order to compensate for the variation in rotational speed induced by the fluctuating loads. A pseudo-Wigner-Ville distribution was then applied to the test data, in order to identify the influence of the fluctuating load conditions. In this work, a vibration waveform normalisation approach is presented, which enables the use of the pseudo-Wigner-Ville distribution to indicate deteriorating fault conditions under fluctuating load conditions. Statistical parameters and various other features were extracted from the distribution in order to indicate the linear separation of the values for various fault conditions, after applying the vibration waveform normalisation approach. Feature vectors were compiled for the various fault and load conditions. Mahalanobis distances were calculated between the various feature vectors and an average feature vector was compiled from data measured on the undamaged gearbox. It was proved that the Mahalanobis distance could be used as a single parameter, which can readily be monotonically trended to indicate the progression of a fault condition under fluctuating load conditions. It was shown that a single layer perceptron network could be trained with the perceptron learning rule

  12. 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.

  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

    2016-04-15

    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.

  15. Breath acetone to monitor life style interventions in field conditions: an exploratory study.

    PubMed

    Samudrala, Devasena; Lammers, Gerwen; Mandon, Julien; Blanchet, Lionel; Schreuder, Tim H A; Hopman, Maria T; Harren, Frans J M; Tappy, Luc; Cristescu, Simona M

    2014-04-01

    To assess whether breath acetone concentration can be used to monitor the effects of a prolonged physical activity on whole body lipolysis and hepatic ketogenesis in field conditions. Twenty-three non-diabetic, 11 type 1 diabetic, and 17 type 2 diabetic subjects provided breath and blood samples for this study. Samples were collected during the International Four Days Marches, in the Netherlands. For each participant, breath acetone concentration was measured using proton transfer reaction ion trap mass spectrometry, before and after a 30-50 km walk on four consecutive days. Blood non-esterified free fatty acid (NEFA), beta-hydroxybutyrate (BOHB), and glucose concentrations were measured after walking. Breath acetone concentration was significantly higher after than before walking, and was positively correlated with blood NEFA and BOHB concentrations. The effect of walking on breath acetone concentration was repeatedly observed on all four consecutive days. Breath acetone concentrations were higher in type 1 diabetic subjects and lower in type 2 diabetic subjects than in control subjects. Breath acetone can be used to monitor hepatic ketogenesis during walking under field conditions. It may, therefore, provide real-time information on fat burning, which may be of use for monitoring the lifestyle interventions. Copyright © 2014 The Obesity Society.

  16. Design and realization of online monitoring system for blade condition of mixture machine based on Bluetooth

    NASA Astrophysics Data System (ADS)

    Qian, Zheng; Teng, Shufen

    2006-11-01

    It is very important for mixture machine to make real-time pressure monitor of blade condition in order to ensure the quality of product and the safety of producing course. However, it is difficult to measure this pressure by using wire-method. Thus it is urgently required to develop the wireless monitoring system. In this paper, an on-line monitoring system by using the Bluetooth wireless transmission technology is designed and realized. According to the structure of mixture machine, several pressure sensors are fixed on the two blades which are the solid blade and the hollow blade respectively. The multi-channel switch, instrument amplifier and A/D converter are used to process the output signals of all pressure sensors. These signals could be acquired and transmitted by the Bluetooth acquisition module. Moreover, the Bluetooth module on the wall of mixture machine is utilized to receive these signals and to transmit them to the outside main controller. The real-time data acquisition of the blade condition is implemented by using the communication mode of one master and two slaves. This system has been tested successfully in the lad, the rationality and the feasibility is verified simultaneously.

  17. An effective neuro-fuzzy paradigm for machinery condition health monitoring.

    PubMed

    Yen, G G; Meesad, P

    2001-01-01

    An innovative neuro-fuzzy network appropriate for fault detection and classification in a machinery condition health monitoring environment is proposed. The network, called an incremental learning fuzzy neural (ILFN) network, uses localized neurons to represent the distributions of the input space and is trained using a one-pass, on-line, and incremental learning algorithm that is fast and can operate in real time. The ILFN network employs a hybrid supervised and unsupervised learning scheme to generate its prototypes. The network is a self-organized structure with the ability to adaptively learn new classes of failure modes and update its parameters continuously while monitoring a system. To demonstrate the feasibility and effectiveness of the proposed network, numerical simulations have been performed using some well-known benchmark data sets, such as the Fisher's Iris data and the Deterding vowel data set. Comparison studies with other well-known classifiers were performed and the ILFN network was found competitive with or even superior to many existing classifiers. The ILFN network was applied on the vibration data known as Westland data set collected from a U.S. Navy CH-46E helicopter test stand, in order to assess its efficiency in machinery condition health monitoring. Using a simple fast Fourier transform (FFT) technique for feature extraction, the ILFN network has shown promising results. With various torque levels for training the network, 100% correct classification was achieved for the same torque Levels of the test data.

  18. Aging and condition monitoring of electric cables in nuclear power plants

    SciTech Connect

    Lofaro, R.J.; Grove, E.; Soo, P.

    1998-05-01

    There are a variety of environmental stressors in nuclear power plants that can influence the aging rate of components; these include elevated temperatures, high radiation fields, and humid conditions. Exposure to these stressors over long periods of time can cause degradation of components that may go undetected unless the aging mechanisms are identified and monitored. In some cases the degradation may be mitigated by maintenance or replacement. However, some components receive neither and are thus more susceptible to aging degradation, which might lead to failure. One class of components that falls in this category is electric cables. Cables are very often overlooked in aging analyses since they are passive components that require no maintenance. However, they are very important components since they provide power to safety related equipment and transmit signals to and from instruments and controls. This paper will look at the various aging mechanisms and failure modes associated with electric cables. Condition monitoring techniques that may be useful for monitoring degradation of cables will also be discussed.

  19. 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.

  20. Monitoring compared with paleolimnology: implications for the definition of reference condition in limed lakes in Sweden.

    PubMed

    Norberg, Matilda; Bigler, Christian; Renberg, Ingemar

    2008-11-01

    Surface water acidification was identified as a major environmental problem in the 1960s. Consequently, a liming program was launched in Sweden in the 1970s. The primary purpose of liming is to restore conditions that existed prior to acidification. To reach this goal, as well as achieve 'good status' (i.e. low levels of distortion resulting from human activity) in European freshwaters until 2016 under the European Union Water Framework Directive, lake data are required to define reference conditions. Here, we compare data from chemical/biological monitoring of 12 limed lakes with results of paleolimnological investigations, to address questions of reference conditions, acidification, and restoration by liming. Using diatom-based lake-water pH inferences, we found clear evidence of acidification in only five of the 12 lakes, which had all originally been classified as acidified according to monitoring data. After liming, measured and diatom-inferred pH agree well in seven lakes. The sediment record of three of the five remaining lakes gave ambiguous results, presumably due to sediment mixing or low sediment accumulation rates. It is difficult to determine whether liming restored the lakes to a good status, especially as some of the lakes were not acidified during the twentieth century. In addition to acid deposition, other factors, such as natural lake and catchment ontogeny or human impact through agricultural activity, influence lake acidity. This study shows that monitoring series are usually too short to define reference conditions for lakes, and that paleolimnological studies are useful to set appropriate goals for restoration and for evaluation of counter measures.

  1. The diagnostic line: A novel criterion for condition monitoring of rotating machinery.

    PubMed

    Lin, Jinshan; Dou, Chunhong

    2015-11-01

    This study examined scaling properties of an increment series from rotating machinery. Moreover, two fluctuation parameters for the smallest and largest time scales of a scaling range served as a pair of fluctuation parameters to describe system conditions. Therefore, an interesting phenomenon is observed: the data points, each representing a pair of fluctuation parameters, for fault conditions almost form a straight line, while those for normal clearly depart from the straight line. To describe the phenomenon, a novel concept termed the diagnostic line was introduced. Subsequently, properties of the diagnostic line were carefully investigated theoretically and numerically. Consequently, a decisive role of noise in forming the diagnostic line was determined. Accordingly, this study develops a novel criterion for condition monitoring of rotating machinery.

  2. 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.

  3. [Bioimpedance means of skin condition monitoring during therapeutic and cosmetic procedures].

    PubMed

    Alekseenko, V A; Kus'min, A A; Filist, S A

    2008-01-01

    Engineering and technological problems of bioimpedance skin surface mapping are considered. A typical design of a device based on a PIC 16F microcontroller is suggested. It includes a keyboard, LCD indicator, probing current generator with programmed frequency tuning, and units for probing current monitoring and bioimpedance measurement. The electrode matrix of the device is constructed using nanotechnology. A microcontroller-controlled multiplexor provides scanning of interelectrode impedance, which makes it possible to obtain the impedance image of the skin surface under the electrode matrix. The microcontroller controls the probing signal generator frequency and allows layer-by-layer images of skin under the electrode matrix to be obtained. This makes it possible to use reconstruction tomography methods for analysis and monitoring of the skin condition during therapeutic and cosmetic procedures.

  4. 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.

  5. Fiber optic sensor for simultaneous strain and temperature monitoring in composite materials at cryogenic condition

    NASA Astrophysics Data System (ADS)

    Sampath, Umesh; Kim, Dae-gil; Kim, Hyunjin; Song, Minho

    2017-04-01

    Low thermal sensitivity and cross sensitivity of Fiber Bragg Grating (FBG) towards the applied strain, temperature make FBG implementation complicated in composite materials at cryogenic conditions. In order to alleviate this problem, our work focuses on simultaneous strain and temperature monitoring inside the composite material at cryogenic temperatures. The temperature sensitive polymer coating on an FBG sensor makes it a suitable candidate for cryogenic temperature measurement. The average temperature sensitivity of 48 pm °C-1 was obtained in -180 25 °C. In addition, the cross sensitivity problem has been adjusted by introducing a glass capillary tube to encapsulate the FBG. The thermal expansion of capillary material was compensated by cleaving the one end of FBG free and the other end with the temperature resistant epoxy resins. Experiments results validate that the proposed method can successfully monitor the strain and temperature factors that can be applied to composite material at cryogenic temperatures.

  6. 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.

  7. 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.

  8. Real-time monitoring of process parameters in rice wine fermentation by a portable spectral analytical system combined with multivariate analysis.

    PubMed

    Ouyang, Qin; Zhao, Jiewen; Pan, Wenxiu; Chen, Quansheng

    2016-01-01

    A portable and low-cost spectral analytical system was developed and used to monitor real-time process parameters, i.e. total sugar content (TSC), alcohol content (AC) and pH during rice wine fermentation. Various partial least square (PLS) algorithms were implemented to construct models. The performance of a model was evaluated by the correlation coefficient (Rp) and the root mean square error (RMSEP) in the prediction set. Among the models used, the synergy interval PLS (Si-PLS) was found to be superior. The optimal performance by the Si-PLS model for the TSC was Rp = 0.8694, RMSEP = 0.438; the AC was Rp = 0.8097, RMSEP = 0.617; and the pH was Rp = 0.9039, RMSEP = 0.0805. The stability and reliability of the system, as well as the optimal models, were verified using coefficients of variation, most of which were found to be less than 5%. The results suggest this portable system is a promising tool that could be used as an alternative method for rapid monitoring of process parameters during rice wine fermentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. 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.

  10. Clinical monitoring and high-risk conditions among patients with SUD newly prescribed opioids and benzodiazepines.

    PubMed

    Grossbard, Joel R; Malte, Carol A; Saxon, Andrew J; Hawkins, Eric J

    2014-09-01

    Opioid therapy alone or in combination with benzodiazepines poses safety concerns among patients with substance use disorders (SUD). Guidelines for opioid therapy recommend SUD treatment and enhanced monitoring, especially in patients with additional risk factors, but information on monitoring practices is sparse. This study estimated high-risk conditions - psychiatric comorbidity, suicide risk, and age <35 and ≥65 - and described clinical monitoring among patients with SUD who were newly prescribed opioids alone and concurrent with benzodiazepines long-term. This study included VA Northwest Veterans Network patients with SUD who started opioids only (n=980) or benzodiazepines and opioids concurrently (n=353) long-term (≥90 days) in 2009-2010. Clinical characteristics, outpatient visits and urine drug screens (UDS) documented within 7-months after starting medications were extracted from VA data. Approximately 67% (95% CI: 64-70) of opioids only and 94% (92-97) of concurrent medications groups had ≥1 psychiatric diagnoses. Prevalences of suicide risk and age <35 and ≥65 were 7% (5-8), 6% (5-8) and 18% (15-20) among the opioids only group, and 20% (16-24), 8% (5-11) and 13% (9-16) among the concurrent medications group. Among patients prescribed opioids only and medications concurrently, 87% and 91% attended primary care, whereas 28% and 26% attended SUD specialty-care. Overall, 30% and 48% of opioids only and concurrent medications groups engaged in mental health or SUD care, and 35% and 39% completed UDS. Improvements in clinical monitoring are needed as many VA patients with SUD and comorbid risks who initiate opioid therapy do not receive sufficient mental health/SUD care or UDS monitoring. Published by Elsevier Ireland Ltd.

  11. 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.

  12. Fluorescence spectroscopy: a promising tool for gear-oil condition monitoring

    NASA Astrophysics Data System (ADS)

    Dorigo, Daniel D.; Wiesent, Benjamin R.; Simsek, Özlem; Pérez Grassi, A.; Koch, Alexander W.

    2012-04-01

    Wind power is one of the most promising green energy sources, especially when produced in offshore power plants. Corrective operations in wind turbines cause a considerable part of the maintenance costs of such plants. One preventive action for reducing such operations is the periodic off-line control of oil samples from the wind turbines. The time delay between sampling and availability of the results is a major disadvantage of this kind of controlling. In-situ condition monitoring is a solution to this problem. In-situ monitoring allows real time detection of random, time discrete events, thus enabling a better scheduling of preventive actions and reducing costs and downtime. Fluorescence spectroscopy is a complementary technique to absorption spectroscopy. Due to absorption of UV or visible light, the electrons of specific molecules are excited from a ground electronic state to a vibrational state of higher energy. By collision with other molecules, the excited electron looses a part of the acquired energy and relaxes to a lower vibrational state. The remaining acquired energy is emitted during the electron's transition to the ground state. The resulting frequency shift between excitation and emission energy, known as Stokes shift, is unique and characteristic for each active molecule. In this paper gear-oil condition monitoring based on fluorescence spectroscopy is proposed. Three typical commercial gear-oils for wind turbines were studied. The spectra gained by UV excitation of the samples were analyzed by means of partial least square (PLS) regression. Good prediction results were obtained for the total acid number (TAN). The latter is a measure for the oil acidity and is considered to be a proxy variable for oil age. Other parameters delivering information about gear-oil additive depletion and the related oil aging condition, like phosphor, sulfur and molybdenum concentration, were also analyzed.

  13. Condition Monitoring System Designing of GIS Based on Trip/close Coil Current

    NASA Astrophysics Data System (ADS)

    Wei, Dongliang; Wang, Zhi; Xue, Feng; Li, Haitao

    2017-05-01

    In this article, the types and characteristics of the faults from GIS were analyzed that the major failures were caused by its operating mechanism and auxiliary control circuits. While a useful parameter to effectively diagnose the mechanical failures of GIS is the trip/close coil current which is accessible and easy-to-measure. A portable system has been design to monitor the condition of GIS by detecting the coil current. This system was fulfilled with functions like signal sampling, processing, transmitting and performing. DSP and ARM11 carrying WINCE 6.0 have been used to construct the system. The feasibility and reliability were validated through several repeated experiments.

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

    SciTech Connect

    Billinge S. J.; Redmond, E.L.; Setzler, B.P.; Juhas, P.; Fullera, T.F.

    2012-05-01

    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.

  15. 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.

  16. 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.

  17. Monitoring of conditions inside gas aggregation cluster source during production of Ti/TiOx nanoparticles

    NASA Astrophysics Data System (ADS)

    Kousal, J.; Kolpaková, A.; Shelemin, A.; Kudrna, P.; Tichý, M.; Kylián, O.; Hanuš, J.; Choukourov, A.; Biederman, H.

    2017-10-01

    Gas aggregation sources are nowadays rather widely used in the research community for producing nanoparticles. However, the direct diagnostics of conditions inside the source are relatively scarce. In this work, we focused on monitoring the plasma parameters and the composition of the gas during the production of the TiOx nanoparticles. We studied the role of oxygen in the aggregation process and the influence of the presence of the particles on the plasma. The construction of the source allowed us to make a 2D map of the plasma parameters inside the source.

  18. Remote sensing of vegetation pattern and condition to monitor changes in everglades biogeochemistry

    USGS Publications Warehouse

    Jones, J.W.

    2011-01-01

    Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management. Copyright ?? 2011 Taylor & Francis Group, LLC.

  19. Remote sensing of vegetation pattern and condition to monitor changes in Everglades biogeochemistry

    USGS Publications Warehouse

    Jones, John W.

    2011-01-01

    Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management.

  20. Low cost digester monitoring under realistic conditions: Rural use of biogas and digestate quality.

    PubMed

    Castro, L; Escalante, H; Jaimes-Estévez, J; Díaz, L J; Vecino, K; Rojas, G; Mantilla, L

    2017-09-01

    The purpose of this work was to assess the behaviour of anaerobic digestion of cattle manure in a rural digester under realistic conditions, and estimate the quality and properties of the digestate. The data obtained during monitoring indicated that the digester operation was stable without risk of inhibition. It produced an average of 0.85Nm(3)biogas/d at 65.6% methane, providing an energy savings of 76%. In addition, the digestate contained high nutrient concentrations, which is an important feature of fertilizers. However, this method requires post-treatment due to the presence of pathogens. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. 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.

  2. System monitoring feedback in cinemas and harvesting energy of the air conditioning condenser

    NASA Astrophysics Data System (ADS)

    Pop, P. P.; Pop-Vadean, A.; Barz, C.; Latinovic, T.; Chiver, O.

    2017-05-01

    Our article monitors the degree of emotional involvement of the audience in the action film in theaters by measuring the concentration of CO2. The software performs data processing obtained dispersion sensors and displays data during the film. The software will also trigger the start of the air conditioning condenser where we can get harvesting energy by installing a piezoelectric device. Useful energy can be recovered from various waste produced in cinema. The time lag between actions and changes in environmental systems determines that decisions made now will affect subsequent generations and the future of our environment.

  3. Integrated condition monitoring of a fleet of offshore wind turbines with focus on acceleration streaming processing

    NASA Astrophysics Data System (ADS)

    Helsen, Jan; Gioia, Nicoletta; Peeters, Cédric; Jordaens, Pieter-Jan

    2017-05-01

    Particularly offshore there is a trend to cluster wind turbines in large wind farms, and in the near future to operate such a farm as an integrated power production plant. Predictability of individual turbine behavior across the entire fleet is key in such a strategy. Failure of turbine subcomponents should be detected well in advance to allow early planning of all necessary maintenance actions; Such that they can be performed during low wind and low electricity demand periods. In order to obtain the insights to predict component failure, it is necessary to have an integrated clean dataset spanning all turbines of the fleet for a sufficiently long period of time. This paper illustrates our big-data approach to do this. In addition, advanced failure detection algorithms are necessary to detect failures in this dataset. This paper discusses a multi-level monitoring approach that consists of a combination of machine learning and advanced physics based signal-processing techniques. The advantage of combining different data sources to detect system degradation is in the higher certainty due to multivariable criteria. In order to able to perform long-term acceleration data signal processing at high frequency a streaming processing approach is necessary. This allows the data to be analysed as the sensors generate it. This paper illustrates this streaming concept on 5kHz acceleration data. A continuous spectrogram is generated from the data-stream. Real-life offshore wind turbine data is used. Using this streaming approach for calculating bearing failure features on continuous acceleration data will support failure propagation detection.

  4. 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.

  5. 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.

  6. 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

  7. Using an infrasonic method to monitor the destruction of glaciers in Arctic conditions

    NASA Astrophysics Data System (ADS)

    Asming, V. E.; Baranov, S. V.; Vinogradov, A. N.; Vinogradov, Yu. A.; Fedorov, A. V.

    2016-09-01

    We study the application of an infrasonic method to detect infrasonic acoustic emission caused by the destruction of glaciers in the Arctic. We consider the main approaches and methods for automatic signal detection from the data of infrasonic microarrays from the viewpoint of their practical use in conditions of frequent and significant variations in the noise level characteristics of the Arctic coast. We propose a novel method for the automatic detection of infrasonic events based on representation of a plane wave signal and adaptive estimation of the noise level. The method makes it possible to detect signals with a small number of sensors (up to three) in the specific conditions of the Arctic coast. We present the results of infrasonic monitoring of the destruction of Icefjord outlet glaciers (Spitsbergen archipelago) carried out by the Kola Branch of the RAS Geophysical Survey in 2011-2012.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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].

  17. 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).

  18. The effect of different holding conditions for environmental monitoring with caged rainbow trout (Oncorhynchus mykiss).

    PubMed

    Hanson, Niklas; Guttman, Elin; Larsson, Ake

    2006-10-01

    Biomarkers in fish can be a useful tool for environmental monitoring of aquatic ecosystems when diffuse pollution is becoming more important and new chemicals are being created continuously. There are, however, a number of drawbacks with this method. Because of environmental variability, health status of wild fish populations may differ between years, leading to unrepresentative results in long term studies. Furthermore, genetic or adaptive differences between populations complicate the interpretation of studies on different sites. The use of farmed fish, placed in cages, can reduce these problems. However, experimental conditions are likely to differ between sites. For practical reasons it may, e.g., be neccesary to use different types of caging. Here, the use of net cages and flow through tanks has been compared for a number of biomarkers. Rainbow trout (Oncorhynchus mykiss) were placed in net cages and flow through tanks in the river Göta Alv, in western Sweden, during three different periods in 2004 and 2005. No differences between types of caging were found for any biomarker. Therefore, the results suggest that net cages and flow through tanks can be used and compared in environmental monitoring using biomarkers in caged rainbow trout. However, efforts should be taken to reduce differences in experimental conditions, e.g., light intensity and feeding levels.

  19. Application-ready expedited MODIS data for operational land surface monitoring of vegetation condition

    USGS Publications Warehouse

    Brown, Jesslyn; Howard, Daniel M.; Wylie, Bruce K.; Frieze, Aaron; Ji, Lei; Gacke, Carolyn

    2015-01-01

    Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) system. Because of near-daily global coverage, MODIS data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clear benefits for monitoring vegetation, especially when information can be delivered as fast as changing surface conditions. An “expedited” processing system called “eMODIS” operated by the U.S. Geological Survey provides rapid MODIS surface reflectance data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard MODIS products. We assessed eMODIS quality and consistency by comparing to standard MODIS data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard MODIS (MOD/MYD09Q1), the eMODIS Normalized Difference Vegetation Index (NDVI) maintained a strong, significant relationship to standard MODIS NDVI, whether from morning (Terra) or afternoon (Aqua) orbits. The Aqua eMODIS data were more prone to noise than the Terra data, likely due to differences in the internal cloud mask used in MOD/MYD09Q1 or compositing rules. Post-processing temporal smoothing decreased noise in eMODIS data.

  20. 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.

  1. 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.

  2. Conditional extraction of air-pollutant source signals from air-quality monitoring

    NASA Astrophysics Data System (ADS)

    Malby, Andrew R.; Whyatt, J. Duncan; Timmis, Roger J.

    2013-08-01

    Ambient air-quality data contain information about air-pollution sources that is currently under-exploited. This information could be used to assess trends in the emissions performance of specific sources, and to check at an early stage if policies or controls to reduce air-quality impacts from particular sources are working. Previous techniques for extracting such information have tended to adopt complex analyses and to rely on data from monitoring networks with many sites, thus limiting their applicability to non-specialist users and to networks with few sites. This paper describes simple techniques for 'conditionally' selecting data from one or two monitors, and for analysing and interpreting concentrations in terms of source performance or policy progress. Our techniques minimise the effects of variations in meteorology and source activity, so that the selected data give a more consistent indication of individual source performance. We demonstrate our techniques with a case study, in which we track the source performance of road traffic on the M4 motorway in London and show how impacts per vehicle have changed over time under different conditions of traffic flow and fleet composition.

  3. 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.

  4. 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.

  5. Real-time ischemic condition monitoring in normoglycemic and hyperglycemic rats.

    PubMed

    Choi, Samjin; Kang, Sung Wook; Lee, Gi-Ja; Choi, Seok Keun; Chae, Su-Jin; Park, Hun-Kuk; Chung, Joo-Ho

    2010-03-01

    An increase in excitotoxic amino acid glutamate (GLU) concentration associated with neuronal damage might be the cause of the ischemic damage observed in stroke patients suffering from hyperglycemia. However, the effect has never been investigated by real-time in vivo monitoring. Therefore, this study examined the effects of the functional responses of ischemia-evoked electroencephalography (EEG), cerebral blood flow (%CBF) and DeltaGLU in hyperglycemia through real-time in vivo monitoring. Five Sprague-Dawley rats were treated with streptozocin (hyperglycemia) and five normal rats were used as the controls. Global ischemia was induced using an 11-vessel occlusion model. The experimental protocols consisting of 10 min pre-ischemic, 10 min ischemic and 40 min reperfusion periods were applied to both groups. Under these conditions, the responses of the ischemia-evoked EEG, %CBF and DeltaGLU were monitored in real time. The EEG showed flat patterns during ischemia followed by poor recovery during reperfusion. The peak reperfusion %CBF was decreased significantly in the hyperglycemia group compared to the control group (p < 0.05, n = 5). The extracellular DeltaGLU releases increased significantly during ischemia (p < 0.0001, n = 5) and reperfusion (p < 0.001, n = 5) in the hyperglycemia group compared to the control group. The decrease in reperfusion %CBF during short-term hyperglycemia might be related to the increased plasma osmolality, decreased adenosine levels and swollen endothelial cells with decreased vascular luminal diameters under hyperglycemic conditions. And, the increase in DeltaGLU during short-term hyperglycemia might be related to the neurotoxic effects of the high extracellular concentrations of DeltaGLU and the inhibition of GLU uptake.

  6. 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

  7. Development of a Tool Condition Monitoring System for Impregnated Diamond Bits in Rock Drilling Applications

    NASA Astrophysics Data System (ADS)

    Perez, Santiago; Karakus, Murat; Pellet, Frederic

    2017-05-01

    The great success and widespread use of impregnated diamond (ID) bits are due to their self-sharpening mechanism, which consists of a constant renewal of diamonds acting at the cutting face as the bit wears out. It is therefore important to keep this mechanism acting throughout the lifespan of the bit. Nonetheless, such a mechanism can be altered by the blunting of the bit that ultimately leads to a less than optimal drilling performance. For this reason, this paper aims at investigating the applicability of artificial intelligence-based techniques in order to monitor tool condition of ID bits, i.e. sharp or blunt, under laboratory conditions. Accordingly, topologically invariant tests are carried out with sharp and blunt bits conditions while recording acoustic emissions (AE) and measuring-while-drilling variables. The combined output of acoustic emission root-mean-square value (AErms), depth of cut ( d), torque (tob) and weight-on-bit (wob) is then utilized to create two approaches in order to predict the wear state condition of the bits. One approach is based on the combination of the aforementioned variables and another on the specific energy of drilling. The two different approaches are assessed for classification performance with various pattern recognition algorithms, such as simple trees, support vector machines, k-nearest neighbour, boosted trees and artificial neural networks. In general, Acceptable pattern recognition rates were obtained, although the subset composed by AErms and tob excels due to the high classification performances rates and fewer input variables.

  8. Skeletal anomaly monitoring in rainbow trout (Oncorhynchus mykiss, Walbaum 1792) reared under different conditions.

    PubMed

    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.

  9. 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

  10. [Hardware-software system for monitoring parameters and characteristics of X-ray computer tomographs under operation conditions].

    PubMed

    Blinov, N N; Zelikman, M I; Kruchinin, S A

    2007-01-01

    The results of testing of hardware and software for monitoring parameters (mean number of CT units, noise, field uniformity, high-contrast spatial resolution, layer width, dose) and characteristics (modulation transfer function) of X-ray computer tomographs are presented. The developed hardware and software are used to monitor the stability of X-ray computer tomograph parameters under operation conditions.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. Monitoring and modeling conditions for regional shallow landslide initiation in the San Francisco Bay area, California

    NASA Astrophysics Data System (ADS)

    Collins, B. D.; Stock, J. D.; Godt, J. W.

    2012-12-01

    Intense winter storms in the San Francisco Bay area (SFBA) of California often trigger widespread landsliding, including debris flows that originate as shallow (<3 m) landslides. The strongest storms result in the loss of lives and millions of dollars in damage. Whereas precipitation-based rainfall intensity-duration landslide initiation thresholds are available for the SFBA, antecedent soil moisture conditions also play a major role in determining the likelihood for landslide generation from a given storm. Previous research has demonstrated that antecedent triggering conditions can be obtained using pre-storm precipitation thresholds (e.g., 250-400 mm of seasonal pre-storm rainfall). However, these types of thresholds do not account for the often cyclic pattern of wetting and drying that can occur early in the winter storm season (i.e. October - December), and which may skew the applicability of precipitation-only based thresholds. To account for these cyclic and constantly evolving soil moisture conditions, we have pursued methods to measure soil moisture directly and integrate these measurements into predictive analyses. During the past three years, the USGS installed a series of four subsurface hydrology monitoring stations in shallow landslide-prone locations of the SFBA to establish a soil-moisture-based antecedent threshold. In addition to soil moisture sensors, the monitoring stations are each equipped with piezometers to record positive pore water pressure that is likely required for shallow landslide initiation and a rain gauge to compare storm intensities with existing precipitation-based thresholds. Each monitoring station is located on a natural, grassy hillslope typically composed of silty sands, underlain by sandstone, sloping at approximately 30°, and with a depth to bedrock of approximately 1 meter - conditions typical of debris flow generation in the SFBA. Our observations reveal that various locations respond differently to seasonal

  19. 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.

  20. 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.

  1. 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.

  2. USDA Foreign Agricultural Service overview for operational monitoring of current crop conditions and production forecasts.

    NASA Astrophysics Data System (ADS)

    Crutchfield, J.

    2016-12-01

    The presentation will discuss the current status of the International Production Assessment Division of the USDA ForeignAgricultural Service for operational monitoring and forecasting of current crop conditions, and anticipated productionchanges to produce monthly, multi-source consensus reports on global crop conditions including the use of Earthobservations (EO) from satellite and in situ sources.United States Department of Agriculture (USDA) Foreign Agricultural Service (FAS) International Production AssessmentDivision (IPAD) deals exclusively with global crop production forecasting and agricultural analysis in support of the USDAWorld Agricultural Outlook Board (WAOB) lockup process and contributions to the World Agricultural Supply DemandEstimates (WASE) report. Analysts are responsible for discrete regions or countries and conduct in-depth long-termresearch into national agricultural statistics, farming systems, climatic, environmental, and economic factors affectingcrop production. IPAD analysts become highly valued cross-commodity specialists over time, and are routinely soughtout for specialized analyses to support governmental studies. IPAD is responsible for grain, oilseed, and cotton analysison a global basis. IPAD is unique in the tools it uses to analyze crop conditions around the world, including customweather analysis software and databases, satellite imagery and value-added image interpretation products. It alsoincorporates all traditional agricultural intelligence resources into its forecasting program, to make the fullest use ofavailable information in its operational commodity forecasts and analysis. International travel and training play animportant role in learning about foreign agricultural production systems and in developing analyst knowledge andcapabilities.

  3. 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.

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

    PubMed

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

    2016-04-29

    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.

  5. 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.

  6. The monitoring of micro milling tool wear conditions by wear area estimation

    NASA Astrophysics Data System (ADS)

    Zhu, Kunpeng; Yu, Xiaolong

    2017-09-01

    In micro milling, the tool wear condition is key to the geometrical and surface integrity of the product. This study proposes a novel tool wear surface area monitoring approach based on the full tool wear image, which can reflect the tool conditions better than the traditional tool wear width criteria. To meet the challenges of heavy noise, blur boundary, and mis-alignment of the captured tool wear images, this paper develops a region growing algorithm based on morphological component analysis (MCA) to solve the problems. It decomposes the original micro milling tool image into target tool images, background image and noise image. Then, the region growing algorithm is used to detect the defect and extract the wear region of the target tool image. In addition, rotation invariant features are extracted from wear region to overcome the inconsistency of wear image orientation. The experiment results show that region growing based on MCA algorithm can extract the wear region of the target tool image effectively and the extracted wear region also has good indication of tool wear conditions. It also demonstrates that the estimation of wear area can generalize the tool wear width estimation approach, and yield more accurate results than the traditional approaches.

  7. 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.

  8. 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

  9. 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.

  10. Monitoring present day climatic conditions in tropical caves using an Environmental Data Acquisition System (EDAS)

    NASA Astrophysics Data System (ADS)

    Sondag, Francis; van Ruymbeke, Michel; Soubiès, François; Santos, Roberto; Somerhausen, André; Seidel, Alexandre; Boggiani, Paulo

    2003-03-01

    This paper presents data from automatic stations which have been installed for monitoring climatic parameters in caves in two areas of Brazil. These devices, initially developed at the Royal Observatory of Belgium to monitor environmental parameters in geophysical observatories, were adapted in our study to operate under tropical cave conditions and to measure temperature, atmospheric pressure and drip rate of stalactites. Similar devices were installed at the surface near to the caves to measure air temperature, atmospheric pressure and rainfall. The results reveal that the drip rate at the tip of stalactites is related to the effective rainfall (water excess). The stable drip regime observed during the dry season seems to be reproducible from one year to the other and could be related to the infiltration of water which has a long residence time in the aquifer. Regular pressure oscillations, with amplitude ranging between 1 and 2 mb, are observed in both of the monitored caves. Spectral analysis of the data suggests that these oscillations are linked to the diurnal and semi-diurnal solar tides (S1 and S2). In one cave, very small temperature variations (0.02-0.05 °C) are also observed with a similar diurnal and semi-diurnal pattern, and we argue that the generating process of the thermal components of the S1 and S2 frequencies is a mixture of thermal convection produced by the surface meteorological variations and of an adiabatic induction of the S2 atmospheric pressure modulation. A very large annual thermal amplitude (13 °C) is observed in the other cave; this is a great motivation to study the stable isotope geochemistry of its speleothems as they probably have recorded past temperature fluctuations linked to paleoclimate variations in this area of south-western Brazil.

  11. 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.

  12. Using Continuous Glucose Monitoring Data and Detrended Fluctuation Analysis to Determine Patient Condition

    PubMed Central

    Thomas, Felicity; Signal, Matthew; Chase, J. Geoffrey

    2015-01-01

    Patients admitted to critical care often experience dysglycemia and high levels of insulin resistance, various intensive insulin therapy protocols and methods have attempted to safely normalize blood glucose (BG) levels. Continuous glucose monitoring (CGM) devices allow glycemic dynamics to be captured much more frequently (every 2-5 minutes) than traditional measures of blood glucose and have begun to be used in critical care patients and neonates to help monitor dysglycemia. In an attempt to obtain a better insight relating biomedical signals and patient status, some researchers have turned toward advanced time series analysis methods. In particular, Detrended Fluctuation Analysis (DFA) has been a topic of many recent studies in to glycemic dynamics. DFA investigates the “complexity” of a signal, how one point in time changes relative to its neighboring points, and DFA has been applied to signals like the inter-beat-interval of human heartbeat to differentiate healthy and pathological conditions. Analyzing the glucose metabolic system with such signal processing tools as DFA has been enabled by the emergence of high quality CGM devices. However, there are several inconsistencies within the published work applying DFA to CGM signals. Therefore, this article presents a review and a “how-to” tutorial of DFA, and in particular its application to CGM signals to ensure the methods used to determine complexity are used correctly and so that any relationship between complexity and patient outcome is robust. PMID:26134835

  13. 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.

  14. Using Continuous Glucose Monitoring Data and Detrended Fluctuation Analysis to Determine Patient Condition: A Review.

    PubMed

    Thomas, Felicity; Signal, Matthew; Chase, J Geoffrey

    2015-06-30

    Patients admitted to critical care often experience dysglycemia and high levels of insulin resistance, various intensive insulin therapy protocols and methods have attempted to safely normalize blood glucose (BG) levels. Continuous glucose monitoring (CGM) devices allow glycemic dynamics to be captured much more frequently (every 2-5 minutes) than traditional measures of blood glucose and have begun to be used in critical care patients and neonates to help monitor dysglycemia. In an attempt to obtain a better insight relating biomedical signals and patient status, some researchers have turned toward advanced time series analysis methods. In particular, Detrended Fluctuation Analysis (DFA) has been a topic of many recent studies in to glycemic dynamics. DFA investigates the "complexity" of a signal, how one point in time changes relative to its neighboring points, and DFA has been applied to signals like the inter-beat-interval of human heartbeat to differentiate healthy and pathological conditions. Analyzing the glucose metabolic system with such signal processing tools as DFA has been enabled by the emergence of high quality CGM devices. However, there are several inconsistencies within the published work applying DFA to CGM signals. Therefore, this article presents a review and a "how-to" tutorial of DFA, and in particular its application to CGM signals to ensure the methods used to determine complexity are used correctly and so that any relationship between complexity and patient outcome is robust.

  15. 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.

  16. Condition monitoring of major turbomachinery cuts costs over 4-year period

    SciTech Connect

    Dodd, V.R.

    1984-03-12

    Using a turbomachinery protection system, Chevron, U.S.A. has cut its machinery maintenance costs by 34% in 4 years. This article describes Chevron U.S.A.'s philosophy on condition and protection monitoring of critical turbomachinery trains. It presents background and present status of approximately 200 major machines. Additionally, the justification for instrumenting this type of equipment with machinery protection systems is reviewed. Chevron U.S.A.'s six major refineries operate approximately 26,000 machines with a total of 1.7 million hp. Approximately 200 of these are single-train (unspared) machines vital to plant operation. We have never experienced a catastrophic failure on a machine instrumented with an API 670 Vibration, Axial Position, and Bearing Temperature Monitoring System and armed in the shutdown mode. However, in the last decade we have experienced 16 catastrophic failures on unprotected critical machines, resulting in repair costs ranging from $100,000 to over $3 million. In early 1981, Chevron U.S.A. developed a plan to protect all of the major machines with an API 670 system, with a goal of completion in 3 years. At this writing, 80% are instrumented and operating in the shutdown mode. The remaining 20% are in operating plants scheduled to be shutdown after June 1984. These machines will be instrumented with protection systems as they become available during the scheduled shutdowns.

  17. Corrosion Sensor for Monitoring the Service Condition of Chloride-Contaminated Cement Mortar

    PubMed Central

    Lu, Shuang; Ba, Heng-Jing

    2010-01-01

    A corrosion sensor for monitoring the corrosion state of cover mortar was developed. The sensor was tested in cement mortar, with and without the addition of chloride to simulate the adverse effects of chloride-contaminated environmental conditions on concrete structures. In brief, a linear polarization resistance method combined with an embeddable reference electrode was utilized to measure the polarization resistance (Rp) using built-in sensor electrodes. Subsequently, electrochemical impedance spectroscopy in the frequency range of 1 kHz to 50 kHz was used to obtain the cement mortar resistance (Rs). The results show that the polarization resistance is related to the chloride content and Rs; ln (Rp) is linearly related to the Rs values in mortar without added chloride. The relationships observed between the Rp of the steel anodes and the resistance of the surrounding cement mortar measured by the corrosion sensor confirms that Rs can indicate the corrosion state of concrete structures. PMID:22319347

  18. Non-Linear Dynamics Tools for the Motion Analysis and Condition Monitoring of Robot Joints

    NASA Astrophysics Data System (ADS)

    Trendafilova, I.; van Brussel, H.

    2001-11-01

    Time series from non-damaged and three types of damaged robot joints are considered and analysed from the viewpoint of non-linear dynamics. The embedding spaces for the four types of signals are recovered. The application of surrogate data tests is used to prove the presence of non-linearities in the joints. The results suggest a rise in unstable behaviour due to the introduction of backlash in robot joints. The chaotic behaviour gets stronger with the increase of the backlash extent. This is confirmed by the increase of the embedding dimension as well as by the increase of the Lyapunov exponents and the correlation dimension with the backlash increase. A straightforward method for condition monitoring using non-linear dynamics characteristics, based on a classification procedure, is suggested.

  19. Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis

    NASA Astrophysics Data System (ADS)

    Zhang, Wan; Jia, Min-Ping; Zhu, Lin; Yan, Xiao-An

    2017-07-01

    Computational intelligence is one of the most powerful data processing tools to solve complex nonlinear problems, and thus plays a significant role in intelligent fault diagnosis and prediction. However, only few comprehensive reviews have summarized the ongoing efforts of computational intelligence in machinery condition monitoring and fault diagnosis. The recent research and development of computational intelligence techniques in fault diagnosis, prediction and optimal sensor placement are reviewed. The advantages and limitations of computational intelligence techniques in practical applications are discussed. The characteristics of different algorithms are compared, and application situations of these methods are summarized. Computational intelligence methods need to be further studied in deep understanding algorithm mechanism, improving algorithm efficiency and enhancing engineering application. This review may be considered as a useful guidance for researchers in selecting a suitable method for a specific situation and pointing out potential research directions.

  20. Transmission path phase compensation for gear monitoring under fluctuating load conditions

    NASA Astrophysics Data System (ADS)

    Stander, C. J.; Heyns, P. S.

    2006-10-01

    Vibration can be monitored under fluctuating load conditions if provision is made for taking into account the fluctuation in machine speed, the response amplitude modulation caused by the change in input force, and the amplitude and phase effects on the measured response from the transmission path. Methodologies have been developed to compensate for the effects of fluctuating speed and amplitude modulation. However, this article investigates the effect of the transmission path phase. This is discussed in terms of the effect this phase has on synchronous averaging. A new approach is presented to resolve the influence that the transmission path phase has on synchronous averaging. The approach is used for the experimental data measured on a helical gear test rig. A significant improvement in the rate of convergence was obtained by adopting the new approach which compensates for the phase shifting in the measured structural response. This contrasts with conventional synchronous averaging with order tracking which does not compensate for structural response phase shifting.

  1. 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.

  2. 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.

  3. Corrosion sensor for monitoring the service condition of chloride-contaminated cement mortar.

    PubMed

    Lu, Shuang; Ba, Heng-Jing

    2010-01-01

    A corrosion sensor for monitoring the corrosion state of cover mortar was developed. The sensor was tested in cement mortar, with and without the addition of chloride to simulate the adverse effects of chloride-contaminated environmental conditions on concrete structures. In brief, a linear polarization resistance method combined with an embeddable reference electrode was utilized to measure the polarization resistance (Rp) using built-in sensor electrodes. Subsequently, electrochemical impedance spectroscopy in the frequency range of 1 kHz to 50 kHz was used to obtain the cement mortar resistance (Rs). The results show that the polarization resistance is related to the chloride content and Rs; ln (Rp) is linearly related to the Rs values in mortar without added chloride. The relationships observed between the Rp of the steel anodes and the resistance of the surrounding cement mortar measured by the corrosion sensor confirms that Rs can indicate the corrosion state of concrete structures.

  4. Combating Curse of Dimensionality in Resilient Monitoring Systems: Conditions for Lossless Decomposition.

    PubMed

    Meerkov, Semyon M; Ravichandran, Maruthi T

    2017-05-01

    Resilient monitoring systems (RMSs) are sensor networks that degrade gracefully under cyber-attacks on their sensors. The recently developed RMSs, while being effective in the attacked sensors identification and isolation, exhibited a drawback in their operation-an exponentially increasing assessment time as a function of the number of sensors in the network. To combat this curse of dimensionality, a decomposition approach has been proposed, which led to a dramatic reduction of the assessment time, irrespective of the sensor network dimensionality. However, information losses and, thus, reductions in the level of resiliency due to the decomposition, have not been investigated. This paper is intended to carry out such an investigation. Specifically, it derives conditions for lossless decomposition in terms of the Renyi-2 entropy. The development is based on the analysis of matrices, which characterize coupling of process variables and on a monotonicity property of the Dempster-Shafer combination rule on a class of functions, which arise within the RMS operation.

  5. Using reflection seismics to identify and monitor the basal conditions of Russell Glacier South West Greenland.

    NASA Astrophysics Data System (ADS)

    Hofstede, Coen; Kleiner, Thomas; Bondzio, Johannes; Eisen, Olaf; Wilhelms, Frank; Bohleber, Pascal; Fritzsche, Diedrich; Hubbard, Alun

    2015-04-01

    Russell Glacier is a land terminating glacier in South West Greenland. Survey site SHR lies at several kilometers from the terminus and is closely monitored. In recent years in Summer months, site SHR has seen unusual high ice velocities of up to 400m/a which have been linked to increased Summer melt. To capture the probably changing basal conditions of Russell Glacier at SHR we carried out two seismic surveys at site SHR, one in September 2013 at the end of the melt season and one in May 2014 at the start of the melt season. The seismic data were recorded using a 300m snow streamer and explosives. The data reveal an ice thickness of about 550m and 30 to 40m thick accreted subglacial sediments with varying degrees of water saturation in both ice and sediment. We speculate the increased ice velocity is caused by sediments that become temporarily liquefied in the Summer months.

  6. Experimental Validation of Condition Monitoring for Electrically Activated Shape Memory Alloys for an Unlocking Device

    NASA Astrophysics Data System (ADS)

    Rathmann, Christian; Theren, Benedict; Fleczok, Benjamin; Kuhlenkötter, Bernd

    2017-06-01

    Shape memory alloys (SMA) belong to the group functional materials which can be activated thermally. Along with a phase transformation, they can remember a previously imprinted shape and have a special resistance behavior. Therefore, they can also be used as a sensor and may be capable of detecting various system states in technical systems. This paper makes a contribution by evaluating the measurability of measured variables by SMA elements. Furthermore, it investigates the technically relevant states of “blockade” and “activation” of electrically activated shape memory actuators. It develops and validates an algorithm which is able to detect a possible “blockade”. Moreover, this work presents a hardware concept for a condition monitoring system of shape memory actuators.

  7. 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.

  8. Multivariable Control Systems

    DTIC Science & Technology

    1968-01-01

    one). Examples abound of systems with numerous controlled variables, and the modern tendency is toward ever greater utilization of systems and plants of this kind. We call them multivariable control systems (MCS).

  9. Application of FBG sensing technique for monitoring and early warning system of high-speed railway track conditions

    NASA Astrophysics Data System (ADS)

    Zhang, Yongjia; Liu, Fang; Jing, Yuhai; Li, Weilai

    2017-04-01

    High-speed railway has achieved remarkable development in China, and safety monitoring of high-speed railway is becoming an important research. Fiber bragg grating (FBG) sensing technology is applied for monitoring and early warning system of high-speed railway track condition in this paper. The sensor network is built by putting FBG sensors on the high-speed rail tracks, which is necessary for real-time online monitoring of railway track temperature, displacement and strain. These different variables are collected, processed and analyzed by FBG demodulator. In addition, the railway track temperature prediction model are established based on relevance vector regression algorithm, which further improves the prediction accuracy and generalization performance. The system has been applied in the realtime online monitoring and early warning system of Guangzhou-Shenzhen-Hong Kong high-speed railway track condition. The system is running in good condition and playing an important role in early warning.

  10. 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)

  11. Multivariate Optimization of Conditions for Digestion of Wet Feeds for Dogs and Cats Using a Closed Digester Block and Multielement Determination by ICP-OES.

    PubMed

    Ávila, Dayara Virgínia Lino; Souza, Sidnei Oliveira; Costa, Silvânio Silvério Lopes; Garcia, Carlos Alexandre Borges; Alves, José do Patrocínio Hora; Araujo, Rennan Geovanny Oliveira; Passos, Elisangela Andrade

    2017-09-01

    A full 24 factorial design was applied to find the best combination of diluted reagents (HNO3 and H2O2), time, and temperature for the digestion of samples of wet feed for dogs and cats using a closed digestion block. The residual carbon concentration (RCC) was used as the response in the factorial design. All variables and their interactions significantly influenced the digestion of the feed samples, as indicated by the RCC. The conditions established for the digestion of 0.05 g (dry mass) wet feed samples were the addition of 3.0 mol/L HNO3 and 5.0% m/m H2O2 in a final volume of 10 mL, followed by heating in a closed digestion block at a temperature of 170°C for 120 min. Analyses were performed by inductively coupled plasma (ICP) optical emission spectrometry (OES). LOQs ranged from 0.2 μg/g (Mg and Sr) to 51 μg/g (P). Accuracy of the analytical method was confirmed through the analysis of the Standard Reference Materials Tomato Leaves (NIST 1573), Apple Leaves (NIST 1515), and Peach Leaves (NIST 1547). The agreement values achieved ranged from 80.2 ± 0.3% for Ba to 113.8 ± 7.1% for Zn (n = 3). Addition and recovery tests were carried out by adding the analytes to a feed sample at two concentration levels, and the recoveries were between 84 ± 6 and 114 ± 10% for macroelements (Ca, K, Mg, and P; n = 3) and between 88 ± 3 and 113 ± 7% for microelements and trace elements (B, Cu, Fe, Sr, and Zn; n = 3). The precision values achieved for the different elements, expressed as RSDs, were better than 7.3% (Zn; n = 3) except for Cu determination, that was 14.6% (n=3). The optimized analytical method was applied to 10 commercial samples of wet feed for cats and dogs, with the concentrations of Al, B, Ba, Ca, Cu, Fe, K, Mg, Mn, P, Sr, and Zn determined by ICP-OES.

  12. Condition monitoring of 3G cellular networks through competitive neural models.

    PubMed

    Barreto, Guilherme A; Mota, João C M; Souza, Luis G M; Frota, Rewbenio A; Aguayo, Leonardo

    2005-09-01

    We develop an unsupervised approach to condition monitoring of cellular networks using competitive neural algorithms. Training is carried out with state vectors representing the normal functioning of a simulated CDMA2000 network. Once training is completed, global and local normality profiles (NPs) are built from the distribution of quantization errors of the training state vectors and their components, respectively. The global NP is used to evaluate the overall condition of the cellular system. If abnormal behavior is detected, local NPs are used in a component-wise fashion to find abnormal state variables. Anomaly detection tests are performed via percentile-based confidence intervals computed over the global and local NPs. We compared the performance of four competitive algorithms [winner-take-all (WTA), frequency-sensitive competitive learning (FSCL), self-organizing map (SOM), and neural-gas algorithm (NGA)] and the results suggest that the joint use of global and local NPs is more efficient and more robust than current single-threshold methods.

  13. 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

  14. 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

    2012-09-25

    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.

  15. Tool wear condition monitoring using a sensor fusion model based on fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Aliustaoglu, Cuneyt; Ertunc, H. Metin; Ocak, Hasan

    2009-02-01

    One of the biggest problems in manufacturing is the failure of machine tools due to loss of surface material in cutting operations like drilling and milling. Carrying on the process with a dull tool may damage the workpiece material fabricated. On the other hand, it is unnecessary to change the cutting tool if it is still able to continue cutting operation. Therefore, an effective diagnosis mechanism is necessary for the automation of machining processes so that production loss and downtime can be avoided. This study concerns with the development of a tool wear condition-monitoring technique based on a two-stage fuzzy logic scheme. For this, signals acquired from various sensors were processed to make a decision about the status of the tool. In the first stage of the proposed scheme, statistical parameters derived from thrust force, machine sound (acquired via a very sensitive microphone) and vibration signals were used as inputs to fuzzy process; and the crisp output values of this process were then taken as the input parameters of the second stage. Conclusively, outputs of this stage were taken into a threshold function, the output of which is used to assess the condition of the tool.

  16. 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.

  17. 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.

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

    PubMed

    Yocum, George D; Rinehart, Joseph P; Larson, Marnie L

    2011-05-01

    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 32 possible expression profiles, eight could be arranged in chronological order of diapause development. These eight profiles account for over 92% of the beetles surveyed. Intra-population variation in diapause phenotypes was observed in the field. Some beetles were already in the diapause initiation phase in June when the day length was greater than 17 h. Inter-seasonal variation in the timing of diapause development was also noted. The greatest differences were before the day length decreased to less than 15 h. Anomalies in the results, e.g., the presence of the diapause maintenance phase profiles in beetles collected on the potato plants, argue that laboratory results are not always equivalent with what is observed under field conditions.

  19. 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.

  20. 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

  1. Monitoring of transcriptional regulation in Pichia pastoris under protein production conditions

    PubMed Central

    Gasser, Brigitte; Maurer, Michael; Rautio, Jari; Sauer, Michael; Bhattacharyya, Anamitra; Saloheimo, Markku; Penttilä, Merja; Mattanovich, Diethard

    2007-01-01

    Background It has become evident that host cells react to recombinant protein production with a variety of metabolic and intrinsic stresses such as the unfolded protein response (UPR) pathway. Additionally, environmental conditions such as growth temperature may have a strong impact on cell physiology and specific productivity. However, there is little information about the molecular reactions of the host cells on a genomic level, especially in context to recombinant protein secretion. For the first time, we monitored transcriptional regulation of a subset of marker genes in the common production host Pichia pastoris to gain insights into the general physiological status of the cells under protein production conditions, with the main focus on secretion stress related genes. Results Overexpression of the UPR activating transcription factor Hac1p was employed to identify UPR target genes in P. pastoris and the responses were compared to those known for Saccharomyces cerevisiae. Most of the folding/secretion related genes showed similar regulation patterns in both yeasts, whereas genes associated with the general stress response were differentially regulated. Secretion of an antibody Fab fragment led to induction of UPR target genes in P. pastoris, however not to the same magnitude as Hac1p overproduction. Overexpression of S. cerevisiae protein disulfide isomerase (PDI1) enhances Fab secretion rates 1.9 fold, but did not relief UPR stress. Reduction of cultivation temperature from 25°C to 20°C led to a 1.4-fold increase of specific product secretion rate in chemostat cultivations, although the transcriptional levels of the product genes (Fab light and heavy chain) were significantly reduced at the lower temperature. A subset of folding related genes appeared to be down-regulated at the reduced temperature, whereas transcription of components of the ER associated degradation and the secretory transport was enhanced. Conclusion Monitoring of genomic regulation of

  2. A new thermographic NDT for condition monitoring of electrical components using ANN with confidence level analysis.

    PubMed

    Huda, A S N; Taib, S; Ghazali, K H; Jadin, M S

    2014-05-01

    Infrared thermography technology is one of the most effective non-destructive testing techniques for predictive faults diagnosis of electrical components. Faults in electrical system show overheating of components which is a common indicator of poor connection, overloading, load imbalance or any defect. Thermographic inspection is employed for finding such heat related problems before eventual failure of the system. However, an automatic diagnostic system based on artificial neural network reduces operating time, human efforts and also increases the reliability of system. In the present study, statistical features and artificial neural network (ANN) with confidence level analysis are utilized for inspection of electrical components and their thermal conditions are classified into two classes namely normal and overheated. All the features extracted from images do not produce good performance. Features having low performance reduce the diagnostic performance. The study reveals the performance of each feature individually for selecting the suitable feature set. In order to find the individual feature performance, each feature of thermal image was used as input for neural network and the classification of condition types were used as output target. The multilayered perceptron network using Levenberg-Marquardt training algorithm was used as classifier. The performances were determined in terms of percentage of accuracy, specificity, sensitivity, false positive and false negative. After selecting the suitable features, the study introduces the intelligent diagnosis system using suitable features as inputs of neural network. Finally, confidence percentage and confidence level were used to find out the strength of the network outputs for condition monitoring. The experimental result shows that multilayered perceptron network produced 79.4% of testing accuracy with 43.60%, 12.60%, 21.40, 9.20% and 13.40% highest, high, moderate, low and lowest confidence level respectively

  3. MONITORING AND ASSESSING THE CONDITION OF AQUATIC RESOURCES: ROLE OF COMPLEX SURVEY DESIGN AND ANALYSIS

    EPA Science Inventory

    The National Water Quality Monitoring Council (NWQMC) developed a common framework for aquatic resource monitoring. The framework is described in a series of articles published in Water Resources IMPACT, September, 2003. One objective of the framework is to encourage consistenc...

  4. Reliability of differing densities of sample grids used for the monitoring of forest condition in Europe.

    PubMed

    Köhl, M; Innes, J L; Kaufmann, E

    1994-02-01

    Concern about the possible deterioration of forest health led to the establishment in the 1980s of inventories of forest condition throughout Europe. International standardisation of the programmes was sought and a number of recommendations were made concerning sampling and assessment procedures. One of the most important rulings was that the assessment should be made on a systematic grid, the minimum density of which was 16×16 km. However, many countries adopted denser sampling grids, with 4×4 km being used in several countries and 1×1 km being used in the Netherlands. With five or more years of monitoring completed, there is a growing belief that a rapid and irreversible decline in forest health is not occurring. Consequently, some countries/regions are seeking to reduce their annual investment in forest health monitoring.The precision of national/regional estimates of forest health can be directly related to the sample size. As the sample size decreases, so also does the precision of the estimates. This is illustrated using data collected in Switzerland in 1992 and using grid densities of 4×4 km, 8×8 km, 12×12 km and 16×16 km. The value of the data is dependent on the sample size and the degree to which it is broken down (by region or species). The loss of precision associated with most subdivisions at the 8×8 km grid level remains acceptable, but a sharp deterioration in the precision occurs at the 12×12 km and 16×16 km grid levels. This has considerable implications for the interpretation of the inventories from those countries using a 16×16 km grid. In Switzerland, a reduction from the current 4×4 km grid to an 8×8 km grid (i.e. 75% reduction in sample size) would have relatively little impact on the overall results from the annual inventories of forest health.

  5. Worker selection of safe speed and idle condition in simulated monitoring of two industrial robots.

    PubMed

    Karwowski, W; Rahimi, M

    1991-05-01

    Industrial robots often operate at high speed, with unpredictable motion patterns and erratic idle times. Serious injuries and deaths have occurred due to operator misperception of these robot design and performance characteristics. The main objective of the research project was to study human perceptual aspects of hazardous robotics workstations. Two laboratory experiments were designed to investigate workers' perceptions of two industrial robots with different physical configurations and performance capabilities. Twenty-four subjects participated in the study. All subjects were chosen from local industries, and had had considerable exposure to robots and other automated equipment in their working experience. Experiment 1 investigated the maximum speed of robot arm motions that workers, who were experienced with operation of industrial robots, judged to be 'safe' for monitoring tasks. It was found that the selection of safe speed depends on the size of the robot and the speed with which the robot begins its operation. Speeds of less than 51 cm/s and 63 cm/s for large and small robots, respectively, were perceived as safe, i.e., ones that did not result in workers feeling uneasy or endangered when working in close proximity to the robot and monitoring its actions. Experiment 2 investigated the minimum value of robot idle time (inactivity) perceived by industrial workers as system malfunction, and an indication of the 'safe-to-approach' condition. It was found that idle times of 41 s and 28 s or less for the small and large robots, respectively, were perceived by workers to be a result of system malfunction. About 20% of the workers waited only 10 s or less before deciding that the robot had stopped because of system malfunction. The idle times were affected by the subjects' prior exposure to a simulated robot accident. Further interpretations of the results and suggestions for operational limitations of robot systems are discussed.

  6. Stability and long term continuity of satellite data for rapid land surface monitoring of vegetation condition

    NASA Astrophysics Data System (ADS)

    Brown, J. F.; Howard, D. M.

    2014-12-01

    Satellite-based normalized difference vegetation index, or NDVI, is a commonly used index in applications that require consistent and timely data, including monitoring drought, tracking vegetation phenological transitions, and assessing crop progress and condition. Although many other indices have been developed, the NDVI remains popular in the monitoring community. One reason is the value of NDVI for use in long-term studies necessitating multiple sensor data sources. It is calculated using a standard formula, red minus near-infrared divided by red plus near-infrared. But, this does not mean that all NDVI data are the same. Many factors, ranging from sensor design and raw satellite data ingest to initial data manipulation and post-processing, influence end-product quality and consistency. The purpose of this study was to perform a statistical scientific comparison between multiple NDVI data sources. The NDVI data analyzed in this study were derived from 8-day 250 meter (m) standard Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua surface reflectance composites (Collection 5, MOD09Q1), 7-day 250 m expedited MODIS (eMODIS) Terra and Aqua NDVI products, and 14-day 1000 m Advanced Very High Resolution Radiometer (AVHRR) NDVI products of central U.S. over the 2003 - 2012 timeframe. Only composites falling within the growing season (between April and October) and temporally coincident were included. All composites were consistently post-processed using standard MODIS quality assurance data and evaluated to calculate spatial statistics (e.g. means and standard deviations) for 160 uniform 150 kilometer2 tiles. The results for seasonal, period-specific and overall correlations indicated the highest agreement was between standard MODIS Terra and Aqua composites, with a Pearson's coefficient of determination of R2 = 0.98, and the lowest agreement was between eMODIS Terra and AVHRR, with a R2 value of 0.84. There was evidence of slight Terra sensor

  7. Fundus autofluorescence imaging: systematic review of test accuracy for the diagnosis and monitoring of retinal conditions.

    PubMed

    Frampton, G K; Kalita, N; Payne, L; Colquitt, J L; Loveman, E; Downes, S M; Lotery, A J

    2017-03-10

    We conducted a systematic review of the accuracy of fundus autofluorescence (FAF) imaging for diagnosing and monitoring retinal conditions. Searches in November 2014 identified English language references. Sources included MEDLINE, EMBASE, the Cochrane Library, Web of Science, and MEDION databases; reference lists of retrieved studies; and internet pages of relevant organisations, meetings, and trial registries. For inclusion, studies had to report FAF imaging accuracy quantitatively. Studies were critically appraised using QUADAS risk of bias criteria. Two reviewers conducted all review steps. From 2240 unique references identified, eight primary research studies met the inclusion criteria. These investigated diagnostic accuracy of FAF imaging for choroidal neovascularisation (one study), reticular pseudodrusen (three studies), cystoid macular oedema (two studies), and diabetic macular oedema (two studies). Diagnostic sensitivity of FAF imaging ranged from 32 to 100% and specificity from 34 to 100%. However, owing to methodological limitations, including high and/or unclear risks of bias, none of these studies provides conclusive evidence of the diagnostic accuracy of FAF imaging. Study heterogeneity precluded meta-analysis. In most studies, the patient spectrum was not reflective of those who would present in clinical practice and no studies adequately reported whether FAF images were interpreted consistently. No studies of monitoring accuracy were identified. An update in October 2016, based on MEDLINE and internet searches, identified four new studies but did not alter our conclusions. Robust quantitative evidence on the accuracy of FAF imaging and how FAF images are interpreted is lacking. We provide recommendations to address this.Eye advance online publication, 10 March 2017; doi:10.1038/eye.2017.19.

  8. 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

  9. Dimensional comparability of psychosocial working conditions as covered in European monitoring questionnaires.

    PubMed

    Formazin, Maren; Burr, Hermann; Aagestad, Cecilie; Tynes, Tore; Thorsen, Sannie Vester; Perkio-Makela, Merja; Díaz Aramburu, Clara Isabel; Pinilla García, Francisco Javier; Galiana Blanco, Luz; Vermeylen, Greet; Parent-Thirion, Agnes; Hooftman, Wendela; Houtman, Irene

    2014-12-09

    In most countries in the EU, national surveys are used to monitor working conditions and health. Since the development processes behind the various surveys are not necessarily theoretical, but certainly practical and political, the extent of similarity among the dimensions covered in these surveys has been unclear. Another interesting question is whether prominent models from scientific research on work and health are present in the surveys--bearing in mind that the primary focus of these surveys is on monitoring status and trends, not on mapping scientific models. Moreover, it is relevant to know which other scales and concepts not stemming from these models have been included in the surveys. The purpose of this paper is to determine (1) the similarity of dimensions covered in the surveys included and (2) the congruence of dimensions of scientific research and of dimensions present in the monitoring systems. Items from surveys representing six European countries and one European wide survey were classified into the dimensions they cover, using a taxonomy agreed upon among all involved partners from the six countries. The classification reveals that there is a large overlap of dimensions, albeit not in the formulation of items, covered in the seven surveys. Among the available items, the two prominent work-stress-models--job-demand-control-support-model (DCS) and effort-reward-imbalance-model (ERI)--are covered in most surveys even though this has not been the primary aim in the compilation of these surveys. In addition, a large variety of items included in the surveillance systems are not part of these models and are--at least partly--used in nearly all surveys. These additional items reflect concepts such as "restructuring", "meaning of work", "emotional demands" and "offensive behaviour/violence & harassment". The overlap of the dimensions being covered in the various questionnaires indicates that the interests of the parties deciding on the questionnaires in

  10. Validation of the concentration profiles obtained from the near infrared/multivariate curve resolution monitoring of reactions of epoxy resins using high performance liquid chromatography as a reference method.

    PubMed

    Garrido, M; Larrechi, M S; Rius, F X

    2007-03-07

    This paper reports the validation of the results obtained by combining near infrared spectroscopy and multivariate curve resolution-alternating least squares (MCR-ALS) and using high performance liquid chromatography as a reference method, for the model reaction of phenylglycidylether (PGE) and aniline. The results are obtained as concentration profiles over the reaction time. The trueness of the proposed method has been evaluated in terms of lack of bias. The joint test for the intercept and the slope showed that there were no significant differences between the profiles calculated spectroscopically and the ones obtained experimentally by means of the chromatographic reference method at an overall level of confidence of 5%. The uncertainty of the results was estimated by using information derived from the process of assessment of trueness. Such operational aspects as the cost and availability of instrumentation and the length and cost of the analysis were evaluated. The method proposed is a good way of monitoring the reactions of epoxy resins, and it adequately shows how the species concentration varies over time.

  11. Monitoring the prevalence of chronic conditions: which data should we use?

    PubMed Central

    2012-01-01

    Background Chronic diseases are an increasing threat to people’s health and to the sustainability of health organisations. Despite the need for routine monitoring systems to assess the impact of chronicity in the population and its evolution over time, currently no single source of information has been identified as suitable for this purpose. Our objective was to describe the prevalence of various chronic conditions estimated using routine data recorded by health professionals: diagnoses on hospital discharge abstracts, and primary care prescriptions and diagnoses. Methods The ICD-9-CM codes for diagnoses and Anatomical Therapeutic Chemical (ATC) codes for prescriptions were collected for all patients in the Basque Country over 14 years of age (n=1,964,337) for a 12-month period. We employed a range of different inputs: hospital diagnoses, primary care diagnoses, primary care prescriptions and combinations thereof. Data were collapsed into the morbidity groups specified by the Johns Hopkins Adjusted Clinical Groups (ACGs) Case-Mix System. We estimated the prevalence of 12 chronic conditions, comparing the results obtained using the different data sources with each other and also with those of the Basque Health Interview Survey (ESCAV). Using the different combinations of inputs, Standardized Morbidity Ratios (SMRs) for the considered diseases were calculated for the list of patients of each general practitioner. The variances of the SMRs were used as a measure of the dispersion of the data and were compared using the Brown-Forsythe test. Results The prevalences calculated using prescription data were higher than those obtained from diagnoses and those from the ESCAV, with two exceptions: malignant neoplasm and migraine. The variances of the SMRs obtained from the combination of all the data sources (hospital diagnoses, and primary care prescriptions and diagnoses) were significantly lower than those using only diagnoses. Conclusions The estimated prevalence of

  12. The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery

    NASA Astrophysics Data System (ADS)

    Loutas, T. H.; Roulias, D.; Pauly, E.; Kostopoulos, V.

    2011-05-01

    The monitoring of progressive wear in gears using various non-destructive technologies as well as the use of advanced signal processing techniques upon the acquired recordings to the direction of more effective diagnostic schemes, is the scope of the present work. For this reason multi-hour tests were performed in healthy gears in a single-stage lab scale gearbox until they were seriously damaged. Three on-line monitoring techniques are implemented in the tests. Vibration and acoustic emission recordings in combination with data coming from oil debris monitoring (ODM) of the lubricating oil are utilized in order to assess the condition of the gears. A plethora of parameters/features were extracted from the acquired waveforms via conventional (in time and frequency domain) and non-conventional (wavelet-based) signal processing techniques. Data fusion was accomplished in the level of integration of the most representative among the extracted features from all three measurement technologies in a single data matrix. Principal component analysis (PCA) was utilized to reduce the dimensionality of the data matrix whereas independent component analysis (ICA) was further applied to identify the independent components among the data and correlate them to different damage modes of the gearbox. Finally heuristic rules based on characteristic values of the resulted independent components were set, realizing thus a health monitoring scheme for gearboxes. The integration of vibration, AE and ODM data increases the diagnostic capacity and reliability of the condition monitoring scheme concluding to very interesting results. The present work summarizes the joint efforts of two research groups towards a more reliable condition monitoring of rotating machinery and gearboxes specifically.

  13. Structural health monitoring and condition based fatigue damage prognosis of complex metallic structures

    NASA Astrophysics Data System (ADS)

    Mohanty, Subhasish

    Current practice in fatigue life prediction is based on assumed initial structural flaws regardless of whether these assumed flaws actually occur in service. Furthermore, the model parameters are often estimated empirically based on previous coupon test results. Small deviations of the initial conditions and model parameters may generate large errors in the expected dynamical behavior of fatigue damage growth. Consequently, a large degree of conservatism is incorporated into structural designs due to these expected uncertainties. The current research in the area of Structural Health Monitoring (SHM) and probabilistic fatigue modeling can help in improved fatigue damage modeling and remaining useful life estimation (RULE) techniques. This thesis discusses an integrated approach of SHM and adaptive prognosis model that not only estimates the current health, but can also forecast the future health and calculate RULE of an aerospace structural component with high level of confidence. The approach does not assume any fixed initial condition and model parameters. This dissertation include the following novel contributions. 1) A Bayesian based off-line Gaussian Process (GP) model is developed, which is the core of the present condition based prognosis approach. 2) Different passive and active SHM approaches are used for on-line damage state estimation. Applications of passive sensing are shown to estimate the time-series fatigue damage states both under constant and random fatigue loading. It is found that there is a good correlation between estimated damage states and optically measured damage states. In addition, applications for both narrow and broadband active sensing approaches are presented to estimate smaller incipient damage. It is demonstrated that the active sensing techniques not only can identify smaller incipient damage but also can quantify fatigue damage during all the three stages (stages I, II, and III) of fatigue life. 3) An integrated on-line SHM and

  14. 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.

  15. Multivariate bubbles and antibubbles

    NASA Astrophysics Data System (ADS)

    Fry, John

    2014-08-01

    In this paper we develop models for multivariate financial bubbles and antibubbles based on statistical physics. In particular, we extend a rich set of univariate models to higher dimensions. Changes in market regime can be explicitly shown to represent a phase transition from random to deterministic behaviour in prices. Moreover, our multivariate models are able to capture some of the contagious effects that occur during such episodes. We are able to show that declining lending quality helped fuel a bubble in the US stock market prior to 2008. Further, our approach offers interesting insights into the spatial development of UK house prices.

  16. 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.

  17. Online condition monitoring of axial-flow turbomachinery blades using rotor-axial Eulerian laser Doppler vibrometry

    NASA Astrophysics Data System (ADS)

    Oberholster, A. J.; Heyns, P. S.

    2009-07-01

    The ability to monitor the vibration of blades online is of great importance to the structural health of turbomachinery.