Remote online monitoring and measuring system for civil engineering structures

NASA Astrophysics Data System (ADS)

Kujawińska, Malgorzata; Sitnik, Robert; Dymny, Grzegorz; Karaszewski, Maciej; Michoński, Kuba; Krzesłowski, Jakub; Mularczyk, Krzysztof; Bolewicki, Paweł

2009-06-01

In this paper a distributed intelligent system for civil engineering structures on-line measurement, remote monitoring, and data archiving is presented. The system consists of a set of optical, full-field displacement sensors connected to a controlling server. The server conducts measurements according to a list of scheduled tasks and stores the primary data or initial results in a remote centralized database. Simultaneously the server performs checks, ordered by the operator, which may in turn result with an alert or a specific action. The structure of whole system is analyzed along with the discussion on possible fields of application and the ways to provide a relevant security during data transport. Finally, a working implementation consisting of a fringe projection, geometrical moiré, digital image correlation and grating interferometry sensors and Oracle XE database is presented. The results from database utilized for on-line monitoring of a threshold value of strain for an exemplary area of interest at the engineering structure are presented and discussed.

OGUPSA sensor scheduling architecture and algorithm

NASA Astrophysics Data System (ADS)

Zhang, Zhixiong; Hintz, Kenneth J.

1996-06-01

This paper introduces a new architecture for a sensor measurement scheduler as well as a dynamic sensor scheduling algorithm called the on-line, greedy, urgency-driven, preemptive scheduling algorithm (OGUPSA). OGUPSA incorporates a preemptive mechanism which uses three policies, (1) most-urgent-first (MUF), (2) earliest- completed-first (ECF), and (3) least-versatile-first (LVF). The three policies are used successively to dynamically allocate and schedule and distribute a set of arriving tasks among a set of sensors. OGUPSA also can detect the failure of a task to meet a deadline as well as generate an optimal schedule in the sense of minimum makespan for a group of tasks with the same priorities. A side benefit is OGUPSA's ability to improve dynamic load balance among all sensors while being a polynomial time algorithm. Results of a simulation are presented for a simple sensor system.

On-Line Monitoring the Growth of E. coli or HeLa Cells Using an Annular Microelectrode Piezoelectric Biosensor.

PubMed

Tong, Feifei; Lian, Yan; Han, Junliang

2016-12-18

Biological information is obtained from the interaction between the series detection electrode and the organism or the physical field of biological cultures in the non-mass responsive piezoelectric biosensor. Therefore, electric parameter of the electrode will affect the biosensor signal. The electric field distribution of the microelectrode used in this study was simulated using the COMSOL Multiphysics analytical tool. This process showed that the electric field spatial distribution is affected by the width of the electrode finger or the space between the electrodes. In addition, the characteristic response of the piezoelectric sensor constructed serially with an annular microelectrode was tested and applied for the continuous detection of Escherichia coli culture or HeLa cell culture. Results indicated that the piezoelectric biosensor with an annular microelectrode meets the requirements for the real-time detection of E. coli or HeLa cells in culture. Moreover, this kind of piezoelectric biosensor is more sensitive than the sensor with an interdigital microelectrode. Thus, the piezoelectric biosensor acts as an effective analysis tool for acquiring online cell or microbial culture information.

Optical fiber sensors-based temperature distribution measurement in ex vivo radiofrequency ablation with submillimeter resolution.

PubMed

Macchi, Edoardo Gino; Tosi, Daniele; Braschi, Giovanni; Gallati, Mario; Cigada, Alfredo; Busca, Giorgio; Lewis, Elfed

2014-01-01

Radiofrequency thermal ablation (RFTA) induces a high-temperature field in a biological tissue having steep spatial (up to 6°C∕mm) and temporal (up to 1°C∕s) gradients. Applied in cancer care, RFTA produces a localized heating, cytotoxic for tumor cells, and is able to treat tumors with sizes up to 3 to 5 cm in diameter. The online measurement of temperature distribution at the RFTA point of care has been previously carried out with miniature thermocouples and optical fiber sensors, which exhibit problems of size, alteration of RFTA pattern, hysteresis, and sensor density worse than 1 sensor∕cm. In this work, we apply a distributed temperature sensor (DTS) with a submillimeter spatial resolution for the monitoring of RFTA in porcine liver tissue. The DTS demodulates the chaotic Rayleigh backscattering pattern with an interferometric setup to obtain the real-time temperature distribution. A measurement chamber has been set up with the fiber crossing the tissue along different diameters. Several experiments have been carried out measuring the space-time evolution of temperature during RFTA. The present work showcases the temperature monitoring in RFTA with an unprecedented spatial resolution and is exportable to in vivo measurement; the acquired data can be particularly useful for the validation of RFTA computational models.

3D Printing-Based Integrated Water Quality Sensing System

PubMed Central

Banna, Muinul; Bera, Kaustav; Sochol, Ryan; Lin, Liwei; Najjaran, Homayoun; Sadiq, Rehan; Hoorfar, Mina

2017-01-01

The online and accurate monitoring of drinking water supply networks is critically in demand to rapidly detect the accidental or deliberate contamination of drinking water. At present, miniaturized water quality monitoring sensors developed in the laboratories are usually tested under ambient pressure and steady-state flow conditions; however, in Water Distribution Systems (WDS), both the pressure and the flowrate fluctuate. In this paper, an interface is designed and fabricated using additive manufacturing or 3D printing technology—material extrusion (Trade Name: fused deposition modeling, FDM) and material jetting—to provide a conduit for miniaturized sensors for continuous online water quality monitoring. The interface is designed to meet two main criteria: low pressure at the inlet of the sensors and a low flowrate to minimize the water bled (i.e., leakage), despite varying pressure from WDS. To meet the above criteria, a two-dimensional computational fluid dynamics model was used to optimize the geometry of the channel. The 3D printed interface, with the embedded miniaturized pH and conductivity sensors, was then tested at different temperatures and flowrates. The results show that the response of the pH sensor is independent of the flowrate and temperature. As for the conductivity sensor, the flowrate and temperature affect only the readings at a very low conductivity (4 µS/cm) and high flowrates (30 mL/min), and a very high conductivity (460 µS/cm), respectively. PMID:28594387

Incremental Support Vector Machine Framework for Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Awad, Mariette; Jiang, Xianhua; Motai, Yuichi

2006-12-01

Motivated by the emerging requirements of surveillance networks, we present in this paper an incremental multiclassification support vector machine (SVM) technique as a new framework for action classification based on real-time multivideo collected by homogeneous sites. The technique is based on an adaptation of least square SVM (LS-SVM) formulation but extends beyond the static image-based learning of current SVM methodologies. In applying the technique, an initial supervised offline learning phase is followed by a visual behavior data acquisition and an online learning phase during which the cluster head performs an ensemble of model aggregations based on the sensor nodes inputs. The cluster head then selectively switches on designated sensor nodes for future incremental learning. Combining sensor data offers an improvement over single camera sensing especially when the latter has an occluded view of the target object. The optimization involved alleviates the burdens of power consumption and communication bandwidth requirements. The resulting misclassification error rate, the iterative error reduction rate of the proposed incremental learning, and the decision fusion technique prove its validity when applied to visual sensor networks. Furthermore, the enabled online learning allows an adaptive domain knowledge insertion and offers the advantage of reducing both the model training time and the information storage requirements of the overall system which makes it even more attractive for distributed sensor networks communication.

WikiSensing: An Online Collaborative Approach for Sensor Data Management

PubMed Central

Silva, Dilshan; Ghanem, Moustafa; Guo, Yike

2012-01-01

This paper presents a new methodology for collaborative sensor data management known as WikiSensing. It is a novel approach that incorporates online collaboration with sensor data management. We introduce the work on this research by describing the motivation and challenges of designing and developing an online collaborative sensor data management system. This is followed by a brief survey on popular sensor data management and online collaborative systems. We then present the architecture for WikiSensing highlighting its main components and features. Several example scenarios are described to present the functionality of the system. We evaluate the approach by investigating the performance of aggregate queries and the scalability of the system. PMID:23201997

Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

PubMed

Oliker, Nurit; Ostfeld, Avi

2015-09-01

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Service Oriented Architecture for Wireless Sensor Networks in Agriculture

NASA Astrophysics Data System (ADS)

Sawant, S. A.; Adinarayana, J.; Durbha, S. S.; Tripathy, A. K.; Sudharsan, D.

2012-08-01

Rapid advances in Wireless Sensor Network (WSN) for agricultural applications has provided a platform for better decision making for crop planning and management, particularly in precision agriculture aspects. Due to the ever-increasing spread of WSNs there is a need for standards, i.e. a set of specifications and encodings to bring multiple sensor networks on common platform. Distributed sensor systems when brought together can facilitate better decision making in agricultural domain. The Open Geospatial Consortium (OGC) through Sensor Web Enablement (SWE) provides guidelines for semantic and syntactic standardization of sensor networks. In this work two distributed sensing systems (Agrisens and FieldServer) were selected to implement OGC SWE standards through a Service Oriented Architecture (SOA) approach. Online interoperable data processing was developed through SWE components such as Sensor Model Language (SensorML) and Sensor Observation Service (SOS). An integrated web client was developed to visualize the sensor observations and measurements that enables the retrieval of crop water resources availability and requirements in a systematic manner for both the sensing devices. Further, the client has also the ability to operate in an interoperable manner with any other OGC standardized WSN systems. The study of WSN systems has shown that there is need to augment the operations / processing capabilities of SOS in order to understand about collected sensor data and implement the modelling services. Also, the very low cost availability of WSN systems in future, it is possible to implement the OGC standardized SWE framework for agricultural applications with open source software tools.

Multi-Sensor Distributive On-Line Processing, Visualization, and Analysis Infrastructure for an Agricultural Information System at the NASA Goddard Earth Sciences DAAC

NASA Technical Reports Server (NTRS)

Teng, William; Berrick, Steve; Leptuokh, Gregory; Liu, Zhong; Rui, Hualan; Pham, Long; Shen, Suhung; Zhu, Tong

2004-01-01

The Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC) Distributed Active Center (DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM On-line Visualization and Analysis System precipitation and other satellite data products and services. AIS outputs will be ,integrated into existing operational decision support system for global crop monitoring, such as that of the U.N. World Food Program. The ability to use the raw data stored in the GES DAAC archives is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. To gain this understanding is a time-consuming process and not a productive investment of the user's time. This is an especially difficult challenge when users need to deal with multi-sensor data that usually are of different structures and resolutions. The AIS has taken a major step towards meeting this challenge by incorporating an underlying infrastructure, called the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni," that integrates various components to support web interfaces that ,allow users to perform interactive analysis on-line without downloading any data. Several instances of the Giovanni-based interface have been or are being created to serve users of TRMM precipitation, MODIS aerosol, and SeaWiFS ocean color data, as well as agricultural applications users. Giovanni-based interfaces are simple to use but powerful. The user selects geophysical ,parameters, area of interest, and time period; and the system generates an output ,on screen in a matter of seconds.

A Distributed Fiber Optic Sensor Network for Online 3-D Temperature and Neutron Fluence Mapping in a VHTR Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsvetkov, Pavel; Dickerson, Bryan; French, Joseph

2014-04-30

Robust sensing technologies allowing for 3D in-core performance monitoring in real time are of paramount importance for already established LWRs to enhance their reliability and availability per year, and therefore, to further facilitate their economic competitiveness via predictive assessment of the in-core conditions.

Differential surface models for tactile perception of shape and on-line tracking of features

NASA Technical Reports Server (NTRS)

Hemami, H.

1987-01-01

Tactile perception of shape involves an on-line controller and a shape perceptor. The purpose of the on-line controller is to maintain gliding or rolling contact with the surface, and collect information, or track specific features of the surface such as edges of a certain sharpness. The shape perceptor uses the information to perceive, estimate the parameters of, or recognize the shape. The differential surface model depends on the information collected and on the a priori information known about the robot and its physical parameters. These differential models are certain functionals that are projections of the dynamics of the robot onto the surface gradient or onto the tangent plane. A number of differential properties may be directly measured from present day tactile sensors. Others may have to be indirectly computed from measurements. Others may constitute design objectives for distributed tactile sensors of the future. A parameterization of the surface leads to linear and nonlinear sequential parameter estimation techniques for identification of the surface. Many interesting compromises between measurement and computation are possible.

Online Soft Sensor of Humidity in PEM Fuel Cell Based on Dynamic Partial Least Squares

PubMed Central

Long, Rong; Chen, Qihong; Zhang, Liyan; Ma, Longhua; Quan, Shuhai

2013-01-01

Online monitoring humidity in the proton exchange membrane (PEM) fuel cell is an important issue in maintaining proper membrane humidity. The cost and size of existing sensors for monitoring humidity are prohibitive for online measurements. Online prediction of humidity using readily available measured data would be beneficial to water management. In this paper, a novel soft sensor method based on dynamic partial least squares (DPLS) regression is proposed and applied to humidity prediction in PEM fuel cell. In order to obtain data of humidity and test the feasibility of the proposed DPLS-based soft sensor a hardware-in-the-loop (HIL) test system is constructed. The time lag of the DPLS-based soft sensor is selected as 30 by comparing the root-mean-square error in different time lag. The performance of the proposed DPLS-based soft sensor is demonstrated by experimental results. PMID:24453923

A Fiber Bragg Grating-Based Dynamic Tension Detection System for Overhead Transmission Line Galloping.

PubMed

Ma, Guo-Ming; Li, Ya-Bo; Mao, Nai-Qiang; Shi, Cheng; Zhang, Bo; Li, Cheng-Rong

2018-01-26

Galloping of overhead transmission lines (OHTLs) may induce conductor breakage and tower collapse, and there is no effective method for long distance distribution on-line galloping monitoring. To overcome the drawbacks of the conventional galloping monitoring systems, such as sensitivity to electromagnetic interference, the need for onsite power, and short lifetimes, a novel optical remote passive measuring system is proposed in the paper. Firstly, to solve the hysteresis and eccentric load problem in tension sensing, and to extent the dynamic response range, an 'S' type elastic element structure with flanges was proposed. Then, a tension experiment was carried out to demonstrate the dynamic response characteristics. Moreover, the designed tension sensor was stretched continuously for 30 min to observe its long time stability. Last but not the least, the sensor was mounted on a 70 m conductor model, and the conductor was oscillated at different frequencies to investigate the dynamic performance of the sensor. The experimental results demonstrate the sensor is suitable for the OHTL galloping detection. Compared with the conventional sensors for OHTL monitoring, the system has many advantages, such as easy installation, no flashover risk, distribution monitoring, better bandwidth, improved accuracy and higher reliability.

Online Variational Bayesian Filtering-Based Mobile Target Tracking in Wireless Sensor Networks

PubMed Central

Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

2014-01-01

The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer–Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying. PMID:25393784

Joint Data Assimilation and Parameter Calibration in on-line groundwater modelling using Sequential Monte Carlo techniques

NASA Astrophysics Data System (ADS)

Ramgraber, M.; Schirmer, M.

2017-12-01

As computational power grows and wireless sensor networks find their way into common practice, it becomes increasingly feasible to pursue on-line numerical groundwater modelling. The reconciliation of model predictions with sensor measurements often necessitates the application of Sequential Monte Carlo (SMC) techniques, most prominently represented by the Ensemble Kalman Filter. In the pursuit of on-line predictions it seems advantageous to transcend the scope of pure data assimilation and incorporate on-line parameter calibration as well. Unfortunately, the interplay between shifting model parameters and transient states is non-trivial. Several recent publications (e.g. Chopin et al., 2013, Kantas et al., 2015) in the field of statistics discuss potential algorithms addressing this issue. However, most of these are computationally intractable for on-line application. In this study, we investigate to what extent compromises between mathematical rigour and computational restrictions can be made within the framework of on-line numerical modelling of groundwater. Preliminary studies are conducted in a synthetic setting, with the goal of transferring the conclusions drawn into application in a real-world setting. To this end, a wireless sensor network has been established in the valley aquifer around Fehraltorf, characterized by a highly dynamic groundwater system and located about 20 km to the East of Zürich, Switzerland. By providing continuous probabilistic estimates of the state and parameter distribution, a steady base for branched-off predictive scenario modelling could be established, providing water authorities with advanced tools for assessing the impact of groundwater management practices. Chopin, N., Jacob, P.E. and Papaspiliopoulos, O. (2013): SMC2: an efficient algorithm for sequential analysis of state space models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 75 (3), p. 397-426. Kantas, N., Doucet, A., Singh, S.S., Maciejowski, J., and Chopin, N. (2015): On Particle Methods for Parameter Estimation in State-Space Models. Statistical Science, 30 (3), p. 328.-351.

Online PH measurement technique in seawater desalination

NASA Astrophysics Data System (ADS)

Wang, Haibo; Wu, Kaihua; Hu, Shaopeng

2009-11-01

The measurement technology of pH is essential in seawater desalination. Glass electrode is the main pH sensor in seawater desalination. Because the internal impedance of glass electrode is high and the signal of pH sensor is easy to be disturbed, a signal processing circuit with high input impedance was designed. Because of high salinity of seawater and the characteristic of glass electrode, ultrasonic cleaning technology was used to online clean pH sensor. Temperature compensation was also designed to reduce the measurement error caused by variety of environment temperature. Additionally, the potential drift of pH sensor was analyzed and an automatic calibration method was proposed. In order to online monitor the variety of pH in seawater desalination, three operating modes were designed. The three modes are online monitoring mode, ultrasonic cleaning mode and auto-calibration mode. The current pH in seawater desalination was measured and displayed in online monitoring mode. The cleaning process of pH sensor was done in ultrasonic cleaning mode. The calibration of pH sensor was finished in auto-calibration mode. The result of experiments showed that the measurement technology of pH could meet the technical requirements for desalination. The glass electrode could be promptly and online cleaned and its service life was lengthened greatly.

On-line detection of Escherichia coli intrusion in a pilot-scale drinking water distribution system.

PubMed

Ikonen, Jenni; Pitkänen, Tarja; Kosse, Pascal; Ciszek, Robert; Kolehmainen, Mikko; Miettinen, Ilkka T

2017-08-01

Improvements in microbial drinking water quality monitoring are needed for the better control of drinking water distribution systems and for public health protection. Conventional water quality monitoring programmes are not always able to detect a microbial contamination of drinking water. In the drinking water production chain, in addition to the vulnerability of source waters, the distribution networks are prone to contamination. In this study, a pilot-scale drinking-water distribution network with an on-line monitoring system was utilized for detecting bacterial intrusion. During the experimental Escherichia coli intrusions, the contaminant was measured by applying a set of on-line sensors for electric conductivity (EC), pH, temperature (T), turbidity, UV-absorbance at 254 nm (UVAS SC) and with a device for particle counting. Monitored parameters were compared with the measured E. coli counts using the integral calculations of the detected peaks. EC measurement gave the strongest signal compared with the measured baseline during the E. coli intrusion. Integral calculations showed that the peaks in the EC, pH, T, turbidity and UVAS SC data were detected corresponding to the time predicted. However, the pH and temperature peaks detected were barely above the measured baseline and could easily be mixed with the background noise. The results indicate that on-line monitoring can be utilized for the rapid detection of microbial contaminants in the drinking water distribution system although the peak interpretation has to be performed carefully to avoid being mixed up with normal variations in the measurement data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimal Location through Distributed Algorithm to Avoid Energy Hole in Mobile Sink WSNs

PubMed Central

Qing-hua, Li; Wei-hua, Gui; Zhi-gang, Chen

2014-01-01

In multihop data collection sensor network, nodes near the sink need to relay on remote data and, thus, have much faster energy dissipation rate and suffer from premature death. This phenomenon causes energy hole near the sink, seriously damaging the network performance. In this paper, we first compute energy consumption of each node when sink is set at any point in the network through theoretical analysis; then we propose an online distributed algorithm, which can adjust sink position based on the actual energy consumption of each node adaptively to get the actual maximum lifetime. Theoretical analysis and experimental results show that the proposed algorithms significantly improve the lifetime of wireless sensor network. It lowers the network residual energy by more than 30% when it is dead. Moreover, the cost for moving the sink is relatively smaller. PMID:24895668

Just-in-Time Correntropy Soft Sensor with Noisy Data for Industrial Silicon Content Prediction.

PubMed

Chen, Kun; Liang, Yu; Gao, Zengliang; Liu, Yi

2017-08-08

Development of accurate data-driven quality prediction models for industrial blast furnaces encounters several challenges mainly because the collected data are nonlinear, non-Gaussian, and uneven distributed. A just-in-time correntropy-based local soft sensing approach is presented to predict the silicon content in this work. Without cumbersome efforts for outlier detection, a correntropy support vector regression (CSVR) modeling framework is proposed to deal with the soft sensor development and outlier detection simultaneously. Moreover, with a continuous updating database and a clustering strategy, a just-in-time CSVR (JCSVR) method is developed. Consequently, more accurate prediction and efficient implementations of JCSVR can be achieved. Better prediction performance of JCSVR is validated on the online silicon content prediction, compared with traditional soft sensors.

Just-in-Time Correntropy Soft Sensor with Noisy Data for Industrial Silicon Content Prediction

PubMed Central

Chen, Kun; Liang, Yu; Gao, Zengliang; Liu, Yi

2017-01-01

Development of accurate data-driven quality prediction models for industrial blast furnaces encounters several challenges mainly because the collected data are nonlinear, non-Gaussian, and uneven distributed. A just-in-time correntropy-based local soft sensing approach is presented to predict the silicon content in this work. Without cumbersome efforts for outlier detection, a correntropy support vector regression (CSVR) modeling framework is proposed to deal with the soft sensor development and outlier detection simultaneously. Moreover, with a continuous updating database and a clustering strategy, a just-in-time CSVR (JCSVR) method is developed. Consequently, more accurate prediction and efficient implementations of JCSVR can be achieved. Better prediction performance of JCSVR is validated on the online silicon content prediction, compared with traditional soft sensors. PMID:28786957

Development of realtime, handheld and portable flood distribution and water quality sensor based android smartphone

NASA Astrophysics Data System (ADS)

Rachmatika, Ratih; Adriyanto, Feri

2017-09-01

Current sensors to monitor water quality are made of manual sensors, which reported to have good performance. However, the major problems, which manual process to get the data. In addition, the data interpretation takes a long time. Due to these problems, a new approach needs to be introduced into the process to prevent a long data acquisition. Therefore, the SIAGA application was proposed. The application of SIAGA is divided into two main applications which are SIBA (Siaga Banjir) and SIAB (Siaga Air Bersih). We using WiFi system which is located at points along the flow of river.. The result can be monitored in the online application based on smartphone which is divided into the river water quality, potential sources of pollution and flood area. Each WiFi point is completed with the instruments which are divided into the sensors that can do the identification of parameters to determine the water quality such as temperature, pH, water level and turbidity. This instrument completed using GPS (Global Positioning System), Full Map menu. The instrument was succesfully monitoredthe flood distribution and water quality in Bengawan Solo river.

Evaluation of Object Detection Algorithms for Ship Detection in the Visible Spectrum

DTIC Science & Technology

2013-12-01

Kodak KAI-2093 was assumed throughout the model to be the image equitation sensor. The sensor was assumed to have taken all of the evaluation imagery...www.ShipPhotos.co.uk. [Online]. Available: http://www.shipphotos.co.uk/hull/ [42] Kodak (2007. March 19). Kodak KAI-2093 image sensor. [Online]. Available

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

PubMed

Ma, Junjie; Meng, Fansheng; Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-02-16

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks

PubMed Central

Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-01-01

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths. PMID:29462929

On-line soft sensing in upstream bioprocessing.

PubMed

Randek, Judit; Mandenius, Carl-Fredrik

2018-02-01

This review provides an overview and a critical discussion of novel possibilities of applying soft sensors for on-line monitoring and control of industrial bioprocesses. Focus is on bio-product formation in the upstream process but also the integration with other parts of the process is addressed. The term soft sensor is used for the combination of analytical hardware data (from sensors, analytical devices, instruments and actuators) with mathematical models that create new real-time information about the process. In particular, the review assesses these possibilities from an industrial perspective, including sensor performance, information value and production economy. The capabilities of existing analytical on-line techniques are scrutinized in view of their usefulness in soft sensor setups and in relation to typical needs in bioprocessing in general. The review concludes with specific recommendations for further development of soft sensors for the monitoring and control of upstream bioprocessing.

Stochastic modeling to identify requirements for centralized monitoring of distributed wastewater treatment.

PubMed

Hug, T; Maurer, M

2012-01-01

Distributed (decentralized) wastewater treatment can, in many situations, be a valuable alternative to a centralized sewer network and wastewater treatment plant. However, it is critical for its acceptance whether the same overall treatment performance can be achieved without on-site staff, and whether its performance can be measured. In this paper we argue and illustrate that the system performance depends not only on the design performance and reliability of the individual treatment units, but also significantly on the monitoring scheme, i.e. on the reliability of the process information. For this purpose, we present a simple model of a fleet of identical treatment units. Thereby, their performance depends on four stochastic variables: the reliability of the treatment unit, the respond time for the repair of failed units, the reliability of on-line sensors, and the frequency of routine inspections. The simulated scenarios show a significant difference between the true performance and the observations by the sensors and inspections. The results also illustrate the trade-off between investing in reactor and sensor technology and in human interventions in order to achieve a certain target performance. Modeling can quantify such effects and thereby support the identification of requirements for the centralized monitoring of distributed treatment units. The model approach is generic and can be extended and applied to various distributed wastewater treatment technologies and contexts.

Automated Water Quality Survey and Evaluation Using an IoT Platform with Mobile Sensor Nodes.

PubMed

Li, Teng; Xia, Min; Chen, Jiahong; Zhao, Yuanjie; de Silva, Clarence

2017-07-28

An Internet of Things (IoT) platform with capabilities of sensing, data processing, and wireless communication has been deployed to support remote aquatic environmental monitoring. In this paper, the design and development of an IoT platform with multiple Mobile Sensor Nodes (MSN) for the spatiotemporal quality evaluation of surface water is presented. A survey planner is proposed to distribute the Sampling Locations of Interest (SLoIs) over the study area and generate paths for MSNs to visit the SLoIs, given the limited energy and time budgets. The SLoIs are chosen based on a cellular decomposition that is composed of uniform hexagonal cells. They are visited by the MSNs along a path ring generated by a planning approach that uses a spanning tree. For quality evaluation, an Online Water Quality Index (OLWQI) is developed to interpret the large quantities of online measurements. The index formulations are modified by a state-of-the-art index, the CCME WQI, which has been developed by the Canadian Council of Ministers of Environment (CCME) for off-line indexing. The proposed index has demonstrated effective and reliable performance in online indexing a large volume of measurements of water quality parameters. The IoT platform is deployed in the field, and its performance is demonstrated and discussed in this paper.

Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine.

PubMed

Ma, Zhiyuan; Luo, Guangchun; Qin, Ke; Wang, Nan; Niu, Weina

2018-03-01

Sensor drift is a common issue in E-Nose systems and various drift compensation methods have received fruitful results in recent years. Although the accuracy for recognizing diverse gases under drift conditions has been largely enhanced, few of these methods considered online processing scenarios. In this paper, we focus on building online drift compensation model by transforming two domain adaptation based methods into their online learning versions, which allow the recognition models to adapt to the changes of sensor responses in a time-efficient manner without losing the high accuracy. Experimental results using three different settings confirm that the proposed methods save large processing time when compared with their offline versions, and outperform other drift compensation methods in recognition accuracy.

Partial Discharge Monitoring on Metal-Enclosed Switchgear with Distributed Non-Contact Sensors.

PubMed

Zhang, Chongxing; Dong, Ming; Ren, Ming; Huang, Wenguang; Zhou, Jierui; Gao, Xuze; Albarracín, Ricardo

2018-02-11

Metal-enclosed switchgear, which are widely used in the distribution of electrical energy, play an important role in power distribution networks. Their safe operation is directly related to the reliability of power system as well as the power quality on the consumer side. Partial discharge detection is an effective way to identify potential faults and can be utilized for insulation diagnosis of metal-enclosed switchgear. The transient earth voltage method, an effective non-intrusive method, has substantial engineering application value for estimating the insulation condition of switchgear. However, the practical application effectiveness of TEV detection is not satisfactory because of the lack of a TEV detection application method, i.e., a method with sufficient technical cognition and analysis. This paper proposes an innovative online PD detection system and a corresponding application strategy based on an intelligent feedback distributed TEV wireless sensor network, consisting of sensing, communication, and diagnosis layers. In the proposed system, the TEV signal or status data are wirelessly transmitted to the terminal following low-energy signal preprocessing and acquisition by TEV sensors. Then, a central server analyzes the correlation of the uploaded data and gives a fault warning level according to the quantity, trend, parallel analysis, and phase resolved partial discharge pattern recognition. In this way, a TEV detection system and strategy with distributed acquisition, unitized fault warning, and centralized diagnosis is realized. The proposed system has positive significance for reducing the fault rate of medium voltage switchgear and improving its operation and maintenance level.

Personalization algorithm for real-time activity recognition using PDA, wireless motion bands, and binary decision tree.

PubMed

Pärkkä, Juha; Cluitmans, Luc; Ermes, Miikka

2010-09-01

Inactive and sedentary lifestyle is a major problem in many industrialized countries today. Automatic recognition of type of physical activity can be used to show the user the distribution of his daily activities and to motivate him into more active lifestyle. In this study, an automatic activity-recognition system consisting of wireless motion bands and a PDA is evaluated. The system classifies raw sensor data into activity types online. It uses a decision tree classifier, which has low computational cost and low battery consumption. The classifier parameters can be personalized online by performing a short bout of an activity and by telling the system which activity is being performed. Data were collected with seven volunteers during five everyday activities: lying, sitting/standing, walking, running, and cycling. The online system can detect these activities with overall 86.6% accuracy and with 94.0% accuracy after classifier personalization.

Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles.

PubMed

Zhu, Qingyuan; Xiao, Chunsheng; Hu, Huosheng; Liu, Yuanhui; Wu, Jinjin

2018-01-13

Articulated wheel loaders used in the construction industry are heavy vehicles and have poor stability and a high rate of accidents because of the unpredictable changes of their body posture, mass and centroid position in complex operation environments. This paper presents a novel distributed multi-sensor system for real-time attitude estimation and stability measurement of articulated wheel loaders to improve their safety and stability. Four attitude and heading reference systems (AHRS) are constructed using micro-electro-mechanical system (MEMS) sensors, and installed on the front body, rear body, rear axis and boom of an articulated wheel loader to detect its attitude. A complementary filtering algorithm is deployed for sensor data fusion in the system so that steady state margin angle (SSMA) can be measured in real time and used as the judge index of rollover stability. Experiments are conducted on a prototype wheel loader, and results show that the proposed multi-sensor system is able to detect potential unstable states of an articulated wheel loader in real-time and with high accuracy.

Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles

PubMed Central

Xiao, Chunsheng; Liu, Yuanhui; Wu, Jinjin

2018-01-01

Articulated wheel loaders used in the construction industry are heavy vehicles and have poor stability and a high rate of accidents because of the unpredictable changes of their body posture, mass and centroid position in complex operation environments. This paper presents a novel distributed multi-sensor system for real-time attitude estimation and stability measurement of articulated wheel loaders to improve their safety and stability. Four attitude and heading reference systems (AHRS) are constructed using micro-electro-mechanical system (MEMS) sensors, and installed on the front body, rear body, rear axis and boom of an articulated wheel loader to detect its attitude. A complementary filtering algorithm is deployed for sensor data fusion in the system so that steady state margin angle (SSMA) can be measured in real time and used as the judge index of rollover stability. Experiments are conducted on a prototype wheel loader, and results show that the proposed multi-sensor system is able to detect potential unstable states of an articulated wheel loader in real-time and with high accuracy. PMID:29342850

Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine

PubMed Central

Luo, Guangchun; Qin, Ke; Wang, Nan; Niu, Weina

2018-01-01

Sensor drift is a common issue in E-Nose systems and various drift compensation methods have received fruitful results in recent years. Although the accuracy for recognizing diverse gases under drift conditions has been largely enhanced, few of these methods considered online processing scenarios. In this paper, we focus on building online drift compensation model by transforming two domain adaptation based methods into their online learning versions, which allow the recognition models to adapt to the changes of sensor responses in a time-efficient manner without losing the high accuracy. Experimental results using three different settings confirm that the proposed methods save large processing time when compared with their offline versions, and outperform other drift compensation methods in recognition accuracy. PMID:29494543

Advancing from offline to online activity recognition with wearable sensors.

PubMed

Ermes, Miikka; Parkka, Juha; Cluitmans, Luc

2008-01-01

Activity recognition with wearable sensors could motivate people to perform a variety of different sports and other physical exercises. We have earlier developed algorithms for offline analysis of activity data collected with wearable sensors. In this paper, we present our current progress in advancing the platform for the existing algorithms to an online version, onto a PDA. Acceleration data are obtained from wireless motion bands which send the 3D raw acceleration signals via a Bluetooth link to the PDA which then performs the data collection, feature extraction and activity classification. As a proof-of-concept, the online activity system was tested with three subjects. All of them performed at least 5 minutes of each of the following activities: lying, sitting, standing, walking, running and cycling with an exercise bike. The average second-by-second classification accuracies for the subjects were 99%, 97%, and 82 %. These results suggest that earlier developed offline analysis methods for the acceleration data obtained from wearable sensors can be successfully implemented in an online activity recognition application.

Multi-Sensor Distributive On-line Processing, Visualization, and Analysis Infrastructure for an Agricultural Information System at the NASA Goddard Earth Sciences DAAC

NASA Astrophysics Data System (ADS)

Teng, W.; Berrick, S.; Leptoukh, G.; Liu, Z.; Rui, H.; Pham, L.; Shen, S.; Zhu, T.

2004-12-01

The Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC) Distributed Active Archive Center (DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide precipitation and other satellite data products and services. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as that of the U.N. World Food Program. The ability to use the raw data stored in the GES DAAC archives is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. To gain this understanding is a time-consuming process and not a productive investment of the user's time. This is an especially difficult challenge when users need to deal with multi-sensor data that usually are of different structures and resolutions. The AIS has taken a major step towards meeting this challenge by incorporating an underlying infrastructure, called the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni," that integrates various components to support web interfaces that allow users to perform interactive analysis on-line without downloading any data. Several instances of the Giovanni-based interface have been or are being created to serve users of TRMM precipitation, MODIS aerosol, and SeaWiFS ocean color data, as well as agricultural applications users. Giovanni-based interfaces are simple to use but powerful. The user selects geophysical parameters, area of interest, and time period; and the system generates an output on screen in a matter of seconds. The currently available output options are (1) area plot - averaged or accumulated over any available data period for any rectangular area; (2) time plot - time series averaged over any rectangular area; (3) Hovmoller plots - longitude-time and latitude-time plots; (4) ASCII output - for all plot types; and (5) image animation - for area plot. Planned output options for the near-future include correlation plots and GIS-compatible outputs. The AIS will enable the remote, interoperable access to distributed data, because the current Giovanni implementation incorporates the GrADS-DODS Server (GDS), a stable, secure data server that provides subsetting and analysis services across the Internet, for any GrADS-readable data set. The subsetting capability allows users to retrieve a specified spatial region from a large data set, eliminating the need to first download the entire data set. The analysis capability allows users to retrieve the results of an operation applied to one or more data sets on the server. The Giovanni-GDS technology allows the serving of data, through convenient on-line analysis tools, from any location where GDS and a few GrADS scripts are installed. The GES-DISC implementation of this technology is unique in the way it enables multi-sensor processing and analysis.

A distributed fault-detection and diagnosis system using on-line parameter estimation

NASA Technical Reports Server (NTRS)

Guo, T.-H.; Merrill, W.; Duyar, A.

1991-01-01

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

Expert system for online surveillance of nuclear reactor coolant pumps

DOEpatents

Gross, Kenny C.; Singer, Ralph M.; Humenik, Keith E.

1993-01-01

An expert system for online surveillance of nuclear reactor coolant pumps. This system provides a means for early detection of pump or sensor degradation. Degradation is determined through the use of a statistical analysis technique, sequential probability ratio test, applied to information from several sensors which are responsive to differing physical parameters. The results of sequential testing of the data provide the operator with an early warning of possible sensor or pump failure.

Microfluidic electrochemical sensor for on-line monitoring of aerosol oxidative activity.

PubMed

Sameenoi, Yupaporn; Koehler, Kirsten; Shapiro, Jeff; Boonsong, Kanokporn; Sun, Yele; Collett, Jeffrey; Volckens, John; Henry, Charles S

2012-06-27

Particulate matter (PM) air pollution has a significant impact on human morbidity and mortality; however, the mechanisms of PM-induced toxicity are poorly defined. A leading hypothesis states that airborne PM induces harm by generating reactive oxygen species in and around human tissues, leading to oxidative stress. We report here a system employing a microfluidic electrochemical sensor coupled directly to a particle-into-liquid sampler (PILS) system to measure aerosol oxidative activity in an on-line format. The oxidative activity measurement is based on the dithiothreitol (DTT) assay, where, after being oxidized by PM, the remaining reduced DTT is analyzed by the microfluidic sensor. The sensor consists of an array of working, reference, and auxiliary electrodes fabricated in a poly(dimethylsiloxane)-based microfluidic device. Cobalt(II) phthalocyanine-modified carbon paste was used as the working electrode material, allowing selective detection of reduced DTT. The electrochemical sensor was validated off-line against the traditional DTT assay using filter samples taken from urban environments and biomass burning events. After off-line characterization, the sensor was coupled to a PILS to enable on-line sampling/analysis of aerosol oxidative activity. Urban dust and industrial incinerator ash samples were aerosolized in an aerosol chamber and analyzed for their oxidative activity. The on-line sensor reported DTT consumption rates (oxidative activity) in good correlation with aerosol concentration (R(2) from 0.86 to 0.97) with a time resolution of approximately 3 min.

Assessment of online monitoring strategies for measuring N2O emissions from full-scale wastewater treatment systems.

PubMed

Marques, Ricardo; Rodriguez-Caballero, A; Oehmen, Adrian; Pijuan, Maite

2016-08-01

Clark-Type nitrous oxide (N2O) sensors are routinely used to measure dissolved N2O concentrations in wastewater treatment plants (WWTPs), but have never before been applied to assess gas-phase N2O emissions in full-scale WWTPs. In this study, a full-scale N2O gas sensor was tested and validated for online gas measurements, and assessed with respect to its linearity, temperature dependence, signal saturation and drift prior to full-scale application. The sensor was linear at the concentrations tested (0-422.3, 0-50 and 0-10 ppmv N2O) and had a linear response up to 2750 ppmv N2O. An exponential correlation between temperature and sensor signal was described and predicted using a double exponential equation while the drift did not have a significant influence on the signal. The N2O gas sensor was used for online N2O monitoring in a full-scale sequencing batch reactor (SBR) treating domestic wastewater and results were compared with those obtained by a commercial online gas analyser. Emissions were successfully described by the sensor, being even more accurate than the values given by the commercial analyser at N2O concentrations above 500 ppmv. Data from this gas N2O sensor was also used to validate two models to predict N2O emissions from dissolved N2O measurements, one based on oxygen transfer rate and the other based on superficial velocity of the gas bubble. Using the first model, predictions for N2O emissions agreed by 98.7% with the measured by the gas sensor, while 87.0% similarity was obtained with the second model. This is the first study showing a reliable estimation of gas emissions based on dissolved N2O online data in a full-scale wastewater treatment facility. Copyright © 2016 Elsevier Ltd. All rights reserved.

Smart Sensor for Online Detection of Multiple-Combined Faults in VSD-Fed Induction Motors

PubMed Central

Garcia-Ramirez, Armando G.; Osornio-Rios, Roque A.; Granados-Lieberman, David; Garcia-Perez, Arturo; Romero-Troncoso, Rene J.

2012-01-01

Induction motors fed through variable speed drives (VSD) are widely used in different industrial processes. Nowadays, the industry demands the integration of smart sensors to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can be produce severe damages. The combined fault identification in induction motors is a demanding task, but it has been rarely considered in spite of being a common situation, because it is difficult to identify two or more faults simultaneously. This work presents a smart sensor for online detection of simple and multiple-combined faults in induction motors fed through a VSD in a wide frequency range covering low frequencies from 3 Hz and high frequencies up to 60 Hz based on a primary sensor being a commercially available current clamp or a hall-effect sensor. The proposed smart sensor implements a methodology based on the fast Fourier transform (FFT), RMS calculation and artificial neural networks (ANN), which are processed online using digital hardware signal processing based on field programmable gate array (FPGA).

A survey of online activity recognition using mobile phones.

PubMed

Shoaib, Muhammad; Bosch, Stephan; Incel, Ozlem Durmaz; Scholten, Hans; Havinga, Paul J M

2015-01-19

Physical activity recognition using embedded sensors has enabled many context-aware applications in different areas, such as healthcare. Initially, one or more dedicated wearable sensors were used for such applications. However, recently, many researchers started using mobile phones for this purpose, since these ubiquitous devices are equipped with various sensors, ranging from accelerometers to magnetic field sensors. In most of the current studies, sensor data collected for activity recognition are analyzed offline using machine learning tools. However, there is now a trend towards implementing activity recognition systems on these devices in an online manner, since modern mobile phones have become more powerful in terms of available resources, such as CPU, memory and battery. The research on offline activity recognition has been reviewed in several earlier studies in detail. However, work done on online activity recognition is still in its infancy and is yet to be reviewed. In this paper, we review the studies done so far that implement activity recognition systems on mobile phones and use only their on-board sensors. We discuss various aspects of these studies. Moreover, we discuss their limitations and present various recommendations for future research.

A high sensitivity wear debris sensor using ferrite cores for online oil condition monitoring

NASA Astrophysics Data System (ADS)

Zhu, Xiaoliang; Zhong, Chong; Zhe, Jiang

2017-07-01

Detecting wear debris and measuring the increasing number of wear debris in lubrication oil can indicate abnormal machine wear well ahead of machine failure, and thus are indispensable for online machine health monitoring. A portable wear debris sensor with ferrite cores for online monitoring is presented. The sensor detects wear debris by measuring the inductance change of two planar coils wound around a pair of ferrite cores that make the magnetic flux denser and more uniform in the sensing channel, thereby improving the sensitivity of the sensor. Static testing results showed this wear debris sensor is capable of detecting 11 µm and 50 µm ferrous debris in 1 mm and 7 mm diameter fluidic pipes, respectively; such a high sensitivity has not been achieved before. Furthermore, a synchronized sampling method was also applied to reduce the data size and realize real-time data processing. Dynamic testing results demonstrated that the sensor is capable of detecting wear debris in real time with a high throughput of 750 ml min-1 the measured debris concentration is in good agreement with the actual concentration.

On-line structural health and fire monitoring of a composite personal aircraft using an FBG sensing system

NASA Astrophysics Data System (ADS)

Chandler, K.; Ferguson, S.; Graver, T.; Csipkes, A.; Mendez, A.

2008-03-01

We report in this paper on the design and development of a novel on-line structural health monitoring and fire detection system based on an array of optical fiber Bragg grating (FBG) sensors and interrogation system installed on a new, precommercial compact aircraft. A combined total of 17 FBG sensors - strain, temperature and high-temperature - were installed at critical locations in an around the wings, fuselage and engine compartment of a prototype, Comp Air CA 12 all-composite, ten-passenger personal airplane powered by a 1,650 hp turbine engine. The sensors are interrogated online and in real time by a swept laser FBG interrogator (Micron Optics sm125-700) mounted on board the plane. Sensors readings are then combined with the plane's avionics system and displayed on the pilot's aviation control panel. This system represents the first of its kind in commercial, small frame, airplanes and a first for optical fiber sensors.

Automated Water Quality Survey and Evaluation Using an IoT Platform with Mobile Sensor Nodes

PubMed Central

Li, Teng; Xia, Min; Chen, Jiahong; Zhao, Yuanjie; de Silva, Clarence

2017-01-01

An Internet of Things (IoT) platform with capabilities of sensing, data processing, and wireless communication has been deployed to support remote aquatic environmental monitoring. In this paper, the design and development of an IoT platform with multiple Mobile Sensor Nodes (MSN) for the spatiotemporal quality evaluation of surface water is presented. A survey planner is proposed to distribute the Sampling Locations of Interest (SLoIs) over the study area and generate paths for MSNs to visit the SLoIs, given the limited energy and time budgets. The SLoIs are chosen based on a cellular decomposition that is composed of uniform hexagonal cells. They are visited by the MSNs along a path ring generated by a planning approach that uses a spanning tree. For quality evaluation, an Online Water Quality Index (OLWQI) is developed to interpret the large quantities of online measurements. The index formulations are modified by a state-of-the-art index, the CCME WQI, which has been developed by the Canadian Council of Ministers of Environment (CCME) for off-line indexing. The proposed index has demonstrated effective and reliable performance in online indexing a large volume of measurements of water quality parameters. The IoT platform is deployed in the field, and its performance is demonstrated and discussed in this paper. PMID:28788098

A novel, optical, on-line bacteria sensor for monitoring drinking water quality

PubMed Central

Højris, Bo; Christensen, Sarah Christine Boesgaard; Albrechtsen, Hans-Jørgen; Smith, Christian; Dahlqvist, Mathis

2016-01-01

Today, microbial drinking water quality is monitored through either time-consuming laboratory methods or indirect on-line measurements. Results are thus either delayed or insufficient to support proactive action. A novel, optical, on-line bacteria sensor with a 10-minute time resolution has been developed. The sensor is based on 3D image recognition, and the obtained pictures are analyzed with algorithms considering 59 quantified image parameters. The sensor counts individual suspended particles and classifies them as either bacteria or abiotic particles. The technology is capable of distinguishing and quantifying bacteria and particles in pure and mixed suspensions, and the quantification correlates with total bacterial counts. Several field applications have demonstrated that the technology can monitor changes in the concentration of bacteria, and is thus well suited for rapid detection of critical conditions such as pollution events in drinking water. PMID:27040142

A novel, optical, on-line bacteria sensor for monitoring drinking water quality.

PubMed

Højris, Bo; Christensen, Sarah Christine Boesgaard; Albrechtsen, Hans-Jørgen; Smith, Christian; Dahlqvist, Mathis

2016-04-04

Today, microbial drinking water quality is monitored through either time-consuming laboratory methods or indirect on-line measurements. Results are thus either delayed or insufficient to support proactive action. A novel, optical, on-line bacteria sensor with a 10-minute time resolution has been developed. The sensor is based on 3D image recognition, and the obtained pictures are analyzed with algorithms considering 59 quantified image parameters. The sensor counts individual suspended particles and classifies them as either bacteria or abiotic particles. The technology is capable of distinguishing and quantifying bacteria and particles in pure and mixed suspensions, and the quantification correlates with total bacterial counts. Several field applications have demonstrated that the technology can monitor changes in the concentration of bacteria, and is thus well suited for rapid detection of critical conditions such as pollution events in drinking water.

Robust Online Monitoring for Calibration Assessment of Transmitters and Instrumentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Coble, Jamie B.; Shumaker, Brent

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. These advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this article, we discuss an overview of research being performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or moremore » sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. Algorithm development is focused on the following OLM functions: • Signal validation • Virtual sensing • Sensor response-time assessment These algorithms incorporate, at their base, a Gaussian Process-based uncertainty quantification (UQ) method. Various plant models (using kernel regression, GP, or hierarchical models) may be used to predict sensor responses under various plant conditions. These predicted responses can then be applied in fault detection (sensor output and response time) and in computing the correct value (virtual sensing) of a failing physical sensor. The methods being evaluated in this work can compute confidence levels along with the predicted sensor responses, and as a result, may have the potential for compensating for sensor drift in real-time (online recalibration). Evaluation was conducted using data from multiple sources (laboratory flow loops and plant data). Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants.« less

Online Robot Dead Reckoning Localization Using Maximum Relative Entropy Optimization With Model Constraints

DOE Office of Scientific and Technical Information (OSTI.GOV)

Urniezius, Renaldas

2011-03-14

The principle of Maximum relative Entropy optimization was analyzed for dead reckoning localization of a rigid body when observation data of two attached accelerometers was collected. Model constraints were derived from the relationships between the sensors. The experiment's results confirmed that accelerometers each axis' noise can be successfully filtered utilizing dependency between channels and the dependency between time series data. Dependency between channels was used for a priori calculation, and a posteriori distribution was derived utilizing dependency between time series data. There was revisited data of autocalibration experiment by removing the initial assumption that instantaneous rotation axis of a rigidmore » body was known. Performance results confirmed that such an approach could be used for online dead reckoning localization.« less

Development of on-line monitoring system for Nuclear Power Plant (NPP) using neuro-expert, noise analysis, and modified neural networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Subekti, M.; Center for Development of Reactor Safety Technology, National Nuclear Energy Agency of Indonesia, Puspiptek Complex BO.80, Serpong-Tangerang, 15340; Ohno, T.

2006-07-01

The neuro-expert has been utilized in previous monitoring-system research of Pressure Water Reactor (PWR). The research improved the monitoring system by utilizing neuro-expert, conventional noise analysis and modified neural networks for capability extension. The parallel method applications required distributed architecture of computer-network for performing real-time tasks. The research aimed to improve the previous monitoring system, which could detect sensor degradation, and to perform the monitoring demonstration in High Temperature Engineering Tested Reactor (HTTR). The developing monitoring system based on some methods that have been tested using the data from online PWR simulator, as well as RSG-GAS (30 MW research reactormore » in Indonesia), will be applied in HTTR for more complex monitoring. (authors)« less

Gas Sensors Based on Tin Oxide Nanoparticles Synthesized from a Mini-Arc Plasma Source

DOE PAGES

Lu, Ganhua; Huebner, Kyle L.; Ocola, Leonidas E.; ...

2006-01-01

Minimore » aturized gas sensors or electronic noses to rapidly detect and differentiate trace amount of chemical agents are extremely attractive. In this paper, we report on the fabrication and characterization of a functional tin oxide nanoparticle gas sensor. Tin oxide nanoparticles are first synthesized using a convenient and low-cost mini-arc plasma source. The nanoparticle size distribution is measured online using a scanning electrical mobility spectrometer (SEMS). The product nanoparticles are analyzed ex-situ by high resolution transmission electron microscopy (HRTEM) for morphology and defects, energy dispersive X-ray (EDX) spectroscopy for elemental composition, electron diffraction for crystal structure, and X-ray photoelectron spectroscopy (XPS) for surface composition. Nonagglomerated rutile tin oxide ( SnO 2 ) nanoparticles as small as a few nm have been produced. Larger particles bear a core-shell structure with a metallic core and an oxide shell. The nanoparticles are then assembled onto an e-beam lithographically patterned interdigitated electrode using electrostatic force to fabricate the gas sensor. The nanoparticle sensor exhibits a fast response and a good sensitivity when exposed to 100 ppm ethanol vapor in air.« less

Fused smart sensor network for multi-axis forward kinematics estimation in industrial robots.

PubMed

Rodriguez-Donate, Carlos; Osornio-Rios, Roque Alfredo; Rivera-Guillen, Jesus Rooney; Romero-Troncoso, Rene de Jesus

2011-01-01

Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint's angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot.

A Survey of Online Activity Recognition Using Mobile Phones

PubMed Central

Shoaib, Muhammad; Bosch, Stephan; Incel, Ozlem Durmaz; Scholten, Hans; Havinga, Paul J.M.

2015-01-01

Physical activity recognition using embedded sensors has enabled many context-aware applications in different areas, such as healthcare. Initially, one or more dedicated wearable sensors were used for such applications. However, recently, many researchers started using mobile phones for this purpose, since these ubiquitous devices are equipped with various sensors, ranging from accelerometers to magnetic field sensors. In most of the current studies, sensor data collected for activity recognition are analyzed offline using machine learning tools. However, there is now a trend towards implementing activity recognition systems on these devices in an online manner, since modern mobile phones have become more powerful in terms of available resources, such as CPU, memory and battery. The research on offline activity recognition has been reviewed in several earlier studies in detail. However, work done on online activity recognition is still in its infancy and is yet to be reviewed. In this paper, we review the studies done so far that implement activity recognition systems on mobile phones and use only their on-board sensors. We discuss various aspects of these studies. Moreover, we discuss their limitations and present various recommendations for future research. PMID:25608213

A Virtual Sensor for Online Fault Detection of Multitooth-Tools

PubMed Central

Bustillo, Andres; Correa, Maritza; Reñones, Anibal

2011-01-01

The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a Bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases. PMID:22163766

A virtual sensor for online fault detection of multitooth-tools.

PubMed

Bustillo, Andres; Correa, Maritza; Reñones, Anibal

2011-01-01

The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases.

Multi-Satellite Synergy for Aerosol Analysis in the Asian Monsoon Region

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym

2012-01-01

Atmospheric aerosols represent one of the greatest uncertainties in environmental and climate research, particularly in tropical monsoon regions such as the Southeast Asian regions, where significant contributions from a variety of aerosol sources and types is complicated by unstable atmospheric dynamics. Although aerosols are now routinely retrieved from multiple satellite Sensors, in trying to answer important science questions about aerosol distribution, properties, and impacts, researchers often rely on retrievals from only one or two sensors, thereby running the risk of incurring biases due to sensor/algorithm peculiarities. We are conducting detailed studies of aerosol retrieval uncertainties from various satellite sensors (including Terra-/ Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, SeaWiFS, and Calipso-CALIOP), based on the collocation of these data products over AERONET and other important ground stations, within the online Multi-sensor Aerosol Products Sampling System (MAPSS) framework that was developed recently. Such analyses are aimed at developing a synthesis of results that can be utilized in building reliable unified aerosol information and climate data records from multiple satellite measurements. In this presentation, we will show preliminary results of. an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors, particularly focused on the Asian Monsoon region, along with some comparisons from the African Monsoon region.

The Multi-Sensor Aerosol Products Sampling System (MAPSS) for Integrated Analysis of Satellite Retrieval Uncertainties

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

2010-01-01

Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.

Toward a Coherent Detailed Evaluation of Aerosol Data Products from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

2011-01-01

Atmospheric aerosols represent one of the greatest uncertainties in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood, there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource, an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, TerraMISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MASS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors.

Hybrid online sensor error detection and functional redundancy for systems with time-varying parameters.

PubMed

Feng, Jianyuan; Turksoy, Kamuran; Samadi, Sediqeh; Hajizadeh, Iman; Littlejohn, Elizabeth; Cinar, Ali

2017-12-01

Supervision and control systems rely on signals from sensors to receive information to monitor the operation of a system and adjust manipulated variables to achieve the control objective. However, sensor performance is often limited by their working conditions and sensors may also be subjected to interference by other devices. Many different types of sensor errors such as outliers, missing values, drifts and corruption with noise may occur during process operation. A hybrid online sensor error detection and functional redundancy system is developed to detect errors in online signals, and replace erroneous or missing values detected with model-based estimates. The proposed hybrid system relies on two techniques, an outlier-robust Kalman filter (ORKF) and a locally-weighted partial least squares (LW-PLS) regression model, which leverage the advantages of automatic measurement error elimination with ORKF and data-driven prediction with LW-PLS. The system includes a nominal angle analysis (NAA) method to distinguish between signal faults and large changes in sensor values caused by real dynamic changes in process operation. The performance of the system is illustrated with clinical data continuous glucose monitoring (CGM) sensors from people with type 1 diabetes. More than 50,000 CGM sensor errors were added to original CGM signals from 25 clinical experiments, then the performance of error detection and functional redundancy algorithms were analyzed. The results indicate that the proposed system can successfully detect most of the erroneous signals and substitute them with reasonable estimated values computed by functional redundancy system.

Toward a Real-Time (Day) Dreamcatcher: Sensor-Free Detection of Mind Wandering during Online Reading

ERIC Educational Resources Information Center

Mills, Caitlin; D'Mello, Sidney

2015-01-01

This paper reports the results from a sensor-free detector of mind wandering during an online reading task. Features consisted of reading behaviors (e.g., reading time) and textual features (e.g., level of difficulty) extracted from self-paced reading log files. Supervised machine learning was applied to two datasets in order to predict if…

Online, In-Situ Monitoring Combustion Turbines Using Wireless Passive Ceramic Sensors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gong, Xun; An, Linan; Xu, Chengying

2013-06-30

The overall objective of this project is to develop high-temperature wireless passive ceramic sensors for online, real-time monitoring combustion turbines. During this project period, we have successfully demonstrated temperature sensors up to 1300°C and pressure sensors up to 800°C. The temperature sensor is based on a high-Q-factor dielectric resonator and the pressure sensor utilizes the evanescent-mode cavity to realize a pressure-sensitive high-Q-factor resonator. Both sensors are efficiently integrated with a compact antenna. These sensors are wirelessly interrogated. The resonant frequency change corresponding to either temperature or pressure can be identified using a time-domain gating technique. The sensors realized in thismore » project can survive harsh environments characterized by high temperatures (>1000°C) and corrosive gases, owing to the excellent material properties of polymer-derived ceramics (PDCs) developed at University of Central Florida. It is anticipated that this work will significantly advance the capability of high-temperature sensor technologies and be of a great benefit to turbine industry and their customers.« less

The Implementation Internet of Things(IoT) Technology in Real Time Monitoring of Electrical Quantities

NASA Astrophysics Data System (ADS)

Despa, D.; Nama, G. F.; Muhammad, M. A.; Anwar, K.

2018-04-01

Electrical quantities such as Voltage, Current, Power, Power Factor, Energy, and Frequency in electrical power system tends to fluctuate, as a result of load changes, disturbances, or other abnormal states. The change-state in electrical quantities should be identify immediately, otherwise it can lead to serious problem for whole system. Therefore a necessity is required to determine the condition of electricity change-state quickly and appropriately in order to make effective decisions. Online monitoring of power distribution system based on Internet of Things (IoT) technology was deploy and implemented on Department of Mechanical Engineering University of Lampung (Unila), especially at three-phase main distribution panel H-building. The measurement system involve multiple sensors such current sensors and voltage sensors, while data processing conducted by Arduino, the measurement data stored in to the database server and shown in a real-time through a web-based application. This measurement system has several important features especially for realtime monitoring, robust data acquisition and logging, system reporting, so it will produce an important information that can be used for various purposes of future power analysis such estimation and planning. The result of this research shown that the condition of electrical power system at H-building performed unbalanced load, which often leads to drop-voltage condition

A novel pH optical sensor using methyl orange based on triacetylcellulose membranes as support.

PubMed

Hosseini, Mohammad; Heydari, Rouhollah; Alimoradi, Mohammad

2014-07-15

A novel pH optical sensor based on triacetylcellulose membrane as solid support was developed by using immobilization of methyl orange indicator. The prepared optical sensor was fixed into a flow cell for on-line pH monitoring. Variables affecting sensor performance, such as pH of dye bonding to triacetylcellulose membrane and dye concentration have been fully evaluated and optimized. The calibration curve showed good behavior and precision (RSD<0.4%) in the pH range of 4.0-12.0. No significant variation was observed on sensor response with increasing the ionic strength in the range of 0.0-0.5M of sodium chloride. Determination of pH by using the proposed optical sensor is on-line, quick, inexpensive, selective and sensitive in the pH range of 4.0-12.0. Copyright © 2014 Elsevier B.V. All rights reserved.

Virtual sensors for on-line wheel wear and part roughness measurement in the grinding process.

PubMed

Arriandiaga, Ander; Portillo, Eva; Sánchez, Jose A; Cabanes, Itziar; Pombo, Iñigo

2014-05-19

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 μm). In the case of surface finish, the absolute error is well below Ra 1 μm (average value 0.32 μm). The present approach can be easily generalized to other grinding operations.

ATR performance modeling concepts

NASA Astrophysics Data System (ADS)

Ross, Timothy D.; Baker, Hyatt B.; Nolan, Adam R.; McGinnis, Ryan E.; Paulson, Christopher R.

2016-05-01

Performance models are needed for automatic target recognition (ATR) development and use. ATRs consume sensor data and produce decisions about the scene observed. ATR performance models (APMs) on the other hand consume operating conditions (OCs) and produce probabilities about what the ATR will produce. APMs are needed for many modeling roles of many kinds of ATRs (each with different sensing modality and exploitation functionality combinations); moreover, there are different approaches to constructing the APMs. Therefore, although many APMs have been developed, there is rarely one that fits a particular need. Clarified APM concepts may allow us to recognize new uses of existing APMs and identify new APM technologies and components that better support coverage of the needed APMs. The concepts begin with thinking of ATRs as mapping OCs of the real scene (including the sensor data) to reports. An APM is then a mapping from explicit quantized OCs (represented with less resolution than the real OCs) and latent OC distributions to report distributions. The roles of APMs can be distinguished by the explicit OCs they consume. APMs used in simulations consume the true state that the ATR is attempting to report. APMs used online with the exploitation consume the sensor signal and derivatives, such as match scores. APMs used in sensor management consume neither of those, but estimate performance from other OCs. This paper will summarize the major building blocks for APMs, including knowledge sources, OC models, look-up tables, analytical and learned mappings, and tools for signal synthesis and exploitation.

NSIDC's passive microwave satellite record: The story behind 30 years of data across multiple satellite platforms

NASA Astrophysics Data System (ADS)

Scott, D. J.; Brandt, M.; Savoie, M. H.; Stewart, J. S.

2016-12-01

The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) has been producing and distributing passive microwave snow and ice data sets from the Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS) for over two decades. Aboard the Defense Meteorological Satellite Program (DMSP) platforms, SSM/I and SSMIS have been operating across eight different orbiting DMSP satellites since 1987, providing an invaluable 30 year record for snow and ice climate data studies. Each sensor has performed within or beyond its expected life cycle, ultimately resulting in a transition across platforms to continue the data record. On occasion the satellites have failed unexpectedly, requiring an unplanned need for science and data management to come together and adjust production code and services to get the data back online in a timely fashion. In recent years, this has become a greater importance as climate blogging sites have increased the visibility of near-real-time passive microwave products to communicate the current changes in the Polar Regions. This presentation summarizes the history and most recent activities surrounding satellite transitions, including the scientific assessment and development required in maintaining a streamlined data record across multiple sensors. In addition, we examine challenges in long-term provenance as well as the considerations and decisions made based on value added products utilizing these data, as well as cryospheric research and general public needs.

Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots

PubMed Central

Rodriguez-Donate, Carlos; Osornio-Rios, Roque Alfredo; Rivera-Guillen, Jesus Rooney; de Jesus Romero-Troncoso, Rene

2011-01-01

Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint’s angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot. PMID:22163850

Online recognition of the multiphase flow regime and study of slug flow in pipeline

NASA Astrophysics Data System (ADS)

Liejin, Guo; Bofeng, Bai; Liang, Zhao; Xin, Wang; Hanyang, Gu

2009-02-01

Multiphase flow is the phenomenon existing widely in nature, daily life, as well as petroleum and chemical engineering industrial fields. The interface structure among multiphase and their movement are complicated, which distribute random and heterogeneously in the spatial and temporal scales and have multivalue of the flow structure and state[1]. Flow regime is defined as the macro feature about the multiphase interface structure and its distribution, which is an important feature to describe multiphase flow. The energy and mass transport mechanism differ much for each flow regimes. It is necessary to solve the flow regime recognition to get a clear understanding of the physical phenomena and their mechanism of multiphase flow. And the flow regime is one of the main factors affecting the online measurement accuracy of phase fraction, flow rate and other phase parameters. Therefore, it is of great scientific and technological importance to develop new principles and methods of multiphase flow regime online recognition, and of great industrial background. In this paper, the key reasons that the present method cannot be used to solve the industrial multiphase flow pattern recognition are clarified firstly. Then the prerequisite to realize the online recognition of multiphase flow regime is analyzed, and the recognition rules for partial flow pattern are obtained based on the massive experimental data. The standard templates for every flow regime feature are calculated with self-organization cluster algorithm. The multi-sensor data fusion method is proposed to realize the online recognition of multiphase flow regime with the pressure and differential pressure signals, which overcomes the severe influence of fluid flow velocity and the oil fraction on the recognition. The online recognition method is tested in the practice, which has less than 10 percent measurement error. The method takes advantages of high confidence, good fault tolerance and less requirement of single sensor performance. Among various flow patterns of gas-liquid flow, slug flow occurs frequently in the petroleum, chemical, civil and nuclear industries. In the offshore oil and gas field, the maximum slug length and its statistical distribution are very important for the design of separator and downstream processing facility at steady state operations. However transient conditions may be encountered in the production, such as operational upsets, start-up, shut-down, pigging and blowdown, which are key operational and safety issues related to oil field development. So it is necessary to have an understanding the flow parameters under transient conditions. In this paper, the evolution of slug length along a horizontal pipe in gas-liquid flow is also studied in details and then an experimental study of flowrate transients in slug flow is provided. Also, the special gas-liquid flow phenomena easily encountered in the life span of offshore oil fields, called severe slugging, is studied experimentally and some results are presented.

Electrochemical Impedance Sensors for Monitoring Trace Amounts of NO3 in Selected Growing Media.

PubMed

Ghaffari, Seyed Alireza; Caron, William-O; Loubier, Mathilde; Normandeau, Charles-O; Viens, Jeff; Lamhamedi, Mohammed S; Gosselin, Benoit; Messaddeq, Younes

2015-07-21

With the advent of smart cities and big data, precision agriculture allows the feeding of sensor data into online databases for continuous crop monitoring, production optimization, and data storage. This paper describes a low-cost, compact, and scalable nitrate sensor based on electrochemical impedance spectroscopy for monitoring trace amounts of NO3- in selected growing media. The nitrate sensor can be integrated to conventional microelectronics to perform online nitrate sensing continuously over a wide concentration range from 0.1 ppm to 100 ppm, with a response time of about 1 min, and feed data into a database for storage and analysis. The paper describes the structural design, the Nyquist impedance response, the measurement sensitivity and accuracy, and the field testing of the nitrate sensor performed within tree nursery settings under ISO/IEC 17025 certifications.

Electrochemical Impedance Sensors for Monitoring Trace Amounts of NO3 in Selected Growing Media

PubMed Central

Ghaffari, Seyed Alireza; Caron, William-O.; Loubier, Mathilde; Normandeau, Charles-O.; Viens, Jeff; Lamhamedi, Mohammed S.; Gosselin, Benoit; Messaddeq, Younes

2015-01-01

With the advent of smart cities and big data, precision agriculture allows the feeding of sensor data into online databases for continuous crop monitoring, production optimization, and data storage. This paper describes a low-cost, compact, and scalable nitrate sensor based on electrochemical impedance spectroscopy for monitoring trace amounts of NO3− in selected growing media. The nitrate sensor can be integrated to conventional microelectronics to perform online nitrate sensing continuously over a wide concentration range from 0.1 ppm to 100 ppm, with a response time of about 1 min, and feed data into a database for storage and analysis. The paper describes the structural design, the Nyquist impedance response, the measurement sensitivity and accuracy, and the field testing of the nitrate sensor performed within tree nursery settings under ISO/IEC 17025 certifications. PMID:26197322

On-line carbon balance of yeast fermentations using miniaturized optical sensors.

PubMed

Beuermann, Thomas; Egly, Dominik; Geoerg, Daniel; Klug, Kerris Isolde; Storhas, Winfried; Methner, Frank-Juergen

2012-03-01

Monitoring of microbiological processes using optical sensors and spectrometers has gained in importance over the past few years due to its advantage in enabling non-invasive on-line analysis. Near-infrared (NIR) and mid-infrared (MIR) spectrometer set-ups in combination with multivariate calibrations have already been successfully employed for the simultaneous determination of different metabolites in microbiological processes. Photometric sensors, in addition to their low price compared to spectrometer set-ups, have the advantage of being compact and are easy to calibrate and operate. In this work, the detection of ethanol and CO(2) in the exhaust gas during aerobic yeast fermentation was performed by two photometric gas analyzers, and dry yeast biomass was monitored using a fiber optic backscatter set-up. The optical sensors could be easily fitted to the bioreactor and exhibited high robustness during measuring. The ethanol content of the fermentation broth was monitored on-line by measuring the ethanol concentration in the fermentation exhaust and applying a conversion factor. The vapor/liquid equilibrium and the associated conversion factor strongly depend on the process parameter temperature but not on aeration and stirring rate. Dry yeast biomass was determined in-line by a backscattering signal applying a linear calibration. An on-line balance with a recovery rate of 95-97% for carbon was achieved with the use of three optical sensors (two infrared gas analyzers and one fiber optic backscatter set-up). Copyright © 2011 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology

PubMed Central

Zao, John K.; Gan, Tchin-Tze; You, Chun-Kai; Chung, Cheng-En; Wang, Yu-Te; Rodríguez Méndez, Sergio José; Mullen, Tim; Yu, Chieh; Kothe, Christian; Hsiao, Ching-Teng; Chu, San-Liang; Shieh, Ce-Kuen; Jung, Tzyy-Ping

2014-01-01

EEG-based Brain-computer interfaces (BCI) are facing basic challenges in real-world applications. The technical difficulties in developing truly wearable BCI systems that are capable of making reliable real-time prediction of users' cognitive states in dynamic real-life situations may seem almost insurmountable at times. Fortunately, recent advances in miniature sensors, wireless communication and distributed computing technologies offered promising ways to bridge these chasms. In this paper, we report an attempt to develop a pervasive on-line EEG-BCI system using state-of-art technologies including multi-tier Fog and Cloud Computing, semantic Linked Data search, and adaptive prediction/classification models. To verify our approach, we implement a pilot system by employing wireless dry-electrode EEG headsets and MEMS motion sensors as the front-end devices, Android mobile phones as the personal user interfaces, compact personal computers as the near-end Fog Servers and the computer clusters hosted by the Taiwan National Center for High-performance Computing (NCHC) as the far-end Cloud Servers. We succeeded in conducting synchronous multi-modal global data streaming in March and then running a multi-player on-line EEG-BCI game in September, 2013. We are currently working with the ARL Translational Neuroscience Branch to use our system in real-life personal stress monitoring and the UCSD Movement Disorder Center to conduct in-home Parkinson's disease patient monitoring experiments. We shall proceed to develop the necessary BCI ontology and introduce automatic semantic annotation and progressive model refinement capability to our system. PMID:24917804

Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology.

PubMed

Zao, John K; Gan, Tchin-Tze; You, Chun-Kai; Chung, Cheng-En; Wang, Yu-Te; Rodríguez Méndez, Sergio José; Mullen, Tim; Yu, Chieh; Kothe, Christian; Hsiao, Ching-Teng; Chu, San-Liang; Shieh, Ce-Kuen; Jung, Tzyy-Ping

2014-01-01

EEG-based Brain-computer interfaces (BCI) are facing basic challenges in real-world applications. The technical difficulties in developing truly wearable BCI systems that are capable of making reliable real-time prediction of users' cognitive states in dynamic real-life situations may seem almost insurmountable at times. Fortunately, recent advances in miniature sensors, wireless communication and distributed computing technologies offered promising ways to bridge these chasms. In this paper, we report an attempt to develop a pervasive on-line EEG-BCI system using state-of-art technologies including multi-tier Fog and Cloud Computing, semantic Linked Data search, and adaptive prediction/classification models. To verify our approach, we implement a pilot system by employing wireless dry-electrode EEG headsets and MEMS motion sensors as the front-end devices, Android mobile phones as the personal user interfaces, compact personal computers as the near-end Fog Servers and the computer clusters hosted by the Taiwan National Center for High-performance Computing (NCHC) as the far-end Cloud Servers. We succeeded in conducting synchronous multi-modal global data streaming in March and then running a multi-player on-line EEG-BCI game in September, 2013. We are currently working with the ARL Translational Neuroscience Branch to use our system in real-life personal stress monitoring and the UCSD Movement Disorder Center to conduct in-home Parkinson's disease patient monitoring experiments. We shall proceed to develop the necessary BCI ontology and introduce automatic semantic annotation and progressive model refinement capability to our system.

Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of a Baseline System

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2008-01-01

In this paper, a baseline system which utilizes dual-channel sensor measurements for aircraft engine on-line diagnostics is developed. This system is composed of a linear on-board engine model (LOBEM) and fault detection and isolation (FDI) logic. The LOBEM provides the analytical third channel against which the dual-channel measurements are compared. When the discrepancy among the triplex channels exceeds a tolerance level, the FDI logic determines the cause of the discrepancy. Through this approach, the baseline system achieves the following objectives: (1) anomaly detection, (2) component fault detection, and (3) sensor fault detection and isolation. The performance of the baseline system is evaluated in a simulation environment using faults in sensors and components.

Change Semantic Constrained Online Data Cleaning Method for Real-Time Observational Data Stream

NASA Astrophysics Data System (ADS)

Ding, Yulin; Lin, Hui; Li, Rongrong

2016-06-01

Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment's status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events) caused by various effects produced by the environment they are monitoring. The "big but dirty" real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo) Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational data streams, which may led to large estimation error. In order to achieve the best generalization error, it is an important challenge for the data cleaning methodology to be able to characterize the behavior of data stream distributions and adaptively update a model to include new information and remove old information. However, the complicated data changing property invalidates traditional data cleaning methods, which rely on the assumption of a stationary data distribution, and drives the need for more dynamic and adaptive online data cleaning methods. To overcome these shortcomings, this paper presents a change semantics constrained online filtering method for real-time observational data. Based on the principle that the filter parameter should vary in accordance to the data change patterns, this paper embeds semantic description, which quantitatively depicts the change patterns in the data distribution to self-adapt the filter parameter automatically. Real-time observational water level data streams of different precipitation scenarios are selected for testing. Experimental results prove that by means of this method, more accurate and reliable water level information can be available, which is prior to scientific and prompt flood assessment and decision-making.

Optical Inspection In Hostile Industrial Environments: Single-Sensor VS. Imaging Methods

NASA Astrophysics Data System (ADS)

Cielo, P.; Dufour, M.; Sokalski, A.

1988-11-01

On-line and unsupervised industrial inspection for quality control and process monitoring is increasingly required in the modern automated factory. Optical techniques are particularly well suited to industrial inspection in hostile environments because of their noncontact nature, fast response time and imaging capabilities. Optical sensors can be used for remote inspection of high temperature products or otherwise inaccessible parts, provided they are in a line-of-sight relation with the sensor. Moreover, optical sensors are much easier to adapt to a variety of part shapes, position or orientation and conveyor speeds as compared to contact-based sensors. This is an important requirement in a flexible automation environment. A number of choices are possible in the design of optical inspection systems. General-purpose two-dimensional (2-D) or three-dimensional (3-D) imaging techniques have advanced very rapidly in the last years thanks to a substantial research effort as well as to the availability of increasingly powerful and affordable hardware and software. Imaging can be realized using 2-D arrays or simpler one-dimensional (1-D) line-array detectors. Alternatively, dedicated single-spot sensors require a smaller amount of data processing and often lead to robust sensors which are particularly appropriate to on-line operation in hostile industrial environments. Many specialists now feel that dedicated sensors or clusters of sensors are often more effective for specific industrial automation and control tasks, at least in the short run. This paper will discuss optomechanical and electro-optical choices with reference to the design of a number of on-line inspection sensors which have been recently developed at our institute. Case studies will include real-time surface roughness evaluation on polymer cables extruded at high speed, surface characterization of hot-rolled or galvanized-steel sheets, temperature evaluation and pinhole detection in aluminum foil, multi-wavelength polymer sheet thickness gauging and thermographic imaging, 3-D lumber profiling, line-array inspection of textiles and glassware, as well as on-line optical inspection for the control of automated arc welding. In each case the design choices between single or multiple-element detectors, mechanical vs. electronic scanning, laser vs. incoherent illumination, etc. will be discussed in terms of industrial constraints such as speed requirements, protection against the environment or reliability of the sensor output.

21 CFR 870.4330 - Cardiopulmonary bypass on-line blood gas monitor.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Cardiopulmonary bypass on-line blood gas monitor... Cardiopulmonary bypass on-line blood gas monitor. (a) Identification. A cardiopulmonary bypass on-line blood gas monitor is a device used in conjunction with a blood gas sensor to measure the level of gases in the blood...

21 CFR 870.4330 - Cardiopulmonary bypass on-line blood gas monitor.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Cardiopulmonary bypass on-line blood gas monitor... Cardiopulmonary bypass on-line blood gas monitor. (a) Identification. A cardiopulmonary bypass on-line blood gas monitor is a device used in conjunction with a blood gas sensor to measure the level of gases in the blood...

21 CFR 870.4330 - Cardiopulmonary bypass on-line blood gas monitor.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Cardiopulmonary bypass on-line blood gas monitor... Cardiopulmonary bypass on-line blood gas monitor. (a) Identification. A cardiopulmonary bypass on-line blood gas monitor is a device used in conjunction with a blood gas sensor to measure the level of gases in the blood...

21 CFR 870.4330 - Cardiopulmonary bypass on-line blood gas monitor.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Cardiopulmonary bypass on-line blood gas monitor. (a) Identification. A cardiopulmonary bypass on-line blood gas monitor is a device used in conjunction with a blood gas sensor to measure the level of gases in the blood... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Cardiopulmonary bypass on-line blood gas monitor...

21 CFR 870.4330 - Cardiopulmonary bypass on-line blood gas monitor.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Cardiopulmonary bypass on-line blood gas monitor. (a) Identification. A cardiopulmonary bypass on-line blood gas monitor is a device used in conjunction with a blood gas sensor to measure the level of gases in the blood... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Cardiopulmonary bypass on-line blood gas monitor...

Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process

PubMed Central

Arriandiaga, Ander; Portillo, Eva; Sánchez, Jose A.; Cabanes, Itziar; Pombo, Iñigo

2014-01-01

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 μm). In the case of surface finish, the absolute error is well below Ra 1 μm (average value 0.32 μm). The present approach can be easily generalized to other grinding operations. PMID:24854055

Local Spatial Obesity Analysis and Estimation Using Online Social Network Sensors.

PubMed

Sun, Qindong; Wang, Nan; Li, Shancang; Zhou, Hongyi

2018-03-15

Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network 'sensor' that can provide valuable health information. The OSN-based obesity analytic model requires each sensor node in an OSN to provide associated features, including dietary habit, physical activity, integral/incidental emotions, and self-consciousness. Based on the detailed measurements on the correlation of obesity and proposed features, the OSN obesity analytic model is able to estimate the obesity rate in certain urban areas and the experimental results demonstrate a high success estimation rate. The measurements and estimation experimental findings created by the proposed obesity analytic model show that the online social networks could be used in analyzing the local spatial obesity problems effectively. Copyright © 2018. Published by Elsevier Inc.

A Soft Sensor for Bioprocess Control Based on Sequential Filtering of Metabolic Heat Signals

PubMed Central

Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

2014-01-01

Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel. PMID:25264951

A soft sensor for bioprocess control based on sequential filtering of metabolic heat signals.

PubMed

Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

2014-09-26

Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

New instrument for on-line viscosity measurement of fermentation media.

PubMed

Picque, D; Corrieu, G

1988-01-01

In an attempt to resolve the difficult problem of on-line determination of the viscosity of non-Newtonian fermentation media, the authors have used a vibrating rod sensor mounted on a bioreactor. The sensor signal decreases nonlinearly with increased apparent viscosity. Electronic filtering of the signal damps the interfering effect of aeration and mechanical agitation. Sensor drift is very low (0.03% of measured value per hour). On the rheological level the sensor is primarily an empirical tool that must be specifically calibrated for each fermentation process. Once this is accomplished, it becomes possible to establish linear or second-degree correlations between the electrical signal from the sensor and the essential parameters of the fermentation process in question (pH of a fermented milk during acidification, concentration of extra cellular polysaccharide). In addition, by applying the power law to describe the rheological behavior of fermentation media, we observe a second-order polynomial correlation between the sensor signal and the behavior index (n).

Online machining error estimation method of numerical control gear grinding machine tool based on data analysis of internal sensors

NASA Astrophysics Data System (ADS)

Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin

2016-12-01

This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.

Investigation of Gear and Bearing Fatigue Damage Using Debris Particle Distributions

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Lewicki, David G.; Decker, Harry J.

2004-01-01

A diagnostic tool was developed for detecting fatigue damage to spur gears, spiral bevel gears, and rolling element bearings. This diagnostic tool was developed and evaluated experimentally by collecting oil debris data from fatigue tests performed in the NASA Glenn Spur Gear Fatigue Rig, Spiral Bevel Gear Test Facility, and the 500hp Helicopter Transmission Test Stand. During each test, data from an online, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of pitting damage. Results indicate oil debris alone cannot discriminate between bearing and gear fatigue damage.

Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

PubMed

Eide, Ingvar; Westad, Frank

2018-01-01

A pilot study demonstrating real-time environmental monitoring with automated multivariate analysis of multi-sensor data submitted online has been performed at the cabled LoVe Ocean Observatory located at 258 m depth 20 km off the coast of Lofoten-Vesterålen, Norway. The major purpose was efficient monitoring of many variables simultaneously and early detection of changes and time-trends in the overall response pattern before changes were evident in individual variables. The pilot study was performed with 12 sensors from May 16 to August 31, 2015. The sensors provided data for chlorophyll, turbidity, conductivity, temperature (three sensors), salinity (calculated from temperature and conductivity), biomass at three different depth intervals (5-50, 50-120, 120-250 m), and current speed measured in two directions (east and north) using two sensors covering different depths with overlap. A total of 88 variables were monitored, 78 from the two current speed sensors. The time-resolution varied, thus the data had to be aligned to a common time resolution. After alignment, the data were interpreted using principal component analysis (PCA). Initially, a calibration model was established using data from May 16 to July 31. The data on current speed from two sensors were subject to two separate PCA models and the score vectors from these two models were combined with the other 10 variables in a multi-block PCA model. The observations from August were projected on the calibration model consecutively one at a time and the result was visualized in a score plot. Automated PCA of multi-sensor data submitted online is illustrated with an attached time-lapse video covering the relative short time period used in the pilot study. Methods for statistical validation, and warning and alarm limits are described. Redundant sensors enable sensor diagnostics and quality assurance. In a future perspective, the concept may be used in integrated environmental monitoring.

Quantitative modeling of coupled piezo-elastodynamic behavior of piezoelectric actuators bonded to an elastic medium for structural health monitoring: a review.

PubMed

Huang, Guoliang; Song, Fei; Wang, Xiaodong

2010-01-01

Elastic waves, especially guided waves, generated by a piezoelectric actuator/sensor network, have shown great potential for on-line health monitoring of advanced aerospace, nuclear, and automotive structures in recent decades. Piezoelectric materials can function as both actuators and sensors in these applications due to wide bandwidth, quick response and low costs. One of the most fundamental issues surrounding the effective use of piezoelectric actuators is the quantitative evaluation of the resulting elastic wave propagation by considering the coupled piezo-elastodynamic behavior between the actuator and the host medium. Accurate characterization of the local interfacial stress distribution between the actuator and the host medium is the key issue for the problem. This paper presents a review of the development of analytical, numerical and hybrid approaches for modeling of the coupled piezo-elastodynamic behavior. The resulting elastic wave propagation for structural health monitoring is also summarized.

The use of 3-D sensing techniques for on-line collision-free path planning

NASA Technical Reports Server (NTRS)

Hayward, V.; Aubry, S.; Jasiukajc, Z.

1987-01-01

The state of the art in collision prevention for manipulators with revolute joints, showing that it is a particularly computationally hard problem, is discussed. Based on the analogy with other hard or undecidable problems such as theorem proving, an extensible multi-resolution architecture for path planning, based on a collection of weak methods is proposed. Finally, the role that sensors can play for an on-line use of sensor data is examined.

Online catalog of world-wide test sites for the post-launch characterization and calibration of optical sensors

USGS Publications Warehouse

Chander, G.; Christopherson, J.B.; Stensaas, G.L.; Teillet, P.M.

2007-01-01

In an era when the number of Earth-observing satellites is rapidly growing and measurements from these sensors are used to answer increasingly urgent global issues, it is imperative that scientists and decision-makers can rely on the accuracy of Earth-observing data products. The characterization and calibration of these sensors are vital to achieve an integrated Global Earth Observation System of Systems (GEOSS) for coordinated and sustained observations of Earth. The U.S. Geological Survey (USGS), as a supporting member of the Committee on Earth Observation Satellites (CEOS) and GEOSS, is working with partners around the world to establish an online catalog of prime candidate test sites for the post-launch characterization and calibration of space-based optical imaging sensors. The online catalog provides easy public Web site access to this vital information for the global community. This paper describes the catalog, the test sites, and the methodologies to use the test sites. It also provides information regarding access to the online catalog and plans for further development of the catalog in cooperation with calibration specialists from agencies and organizations around the world. Through greater access to and understanding of these vital test sites and their use, the validity and utility of information gained from Earth remote sensing will continue to improve. Copyright IAF/IAA. All rights reserved.

On-line monitoring of H2 generation and the HTF degradation in parabolic trough solar thermal power plants: Development of an optical sensor based on an innovative approach

NASA Astrophysics Data System (ADS)

Pagola, Iñigo; Funcia, Ibai; Sánchez, Marcelino; Gil, Javier; González-Vallejo, Victoria; Bedoya, Maxi; Orellana, Guillermo

2017-06-01

The work presented in this paper offers a robust, effective and economically competitive method for online detection and monitoring of the presence of molecular hydrogen in the heat transfer fluids of parabolic trough collector plants. The novel method is based on a specific fluorescent sensor according to the ES2425002 patent ("Method for the detection and quantification of hydrogen in a heat transfer fluid").

Recent progress in distributed optical fiber Raman photon sensors at China Jiliang University

NASA Astrophysics Data System (ADS)

Zhang, Zaixuan; Wang, Jianfeng; Li, Yi; Gong, Huaping; Yu, Xiangdong; Liu, Honglin; Jin, Yongxing; Kang, Juan; Li, Chenxia; Zhang, Wensheng; Zhang, Wenping; Niu, Xiaohui; Sun, Zhongzhou; Zhao, Chunliu; Dong, Xinyong; Jin, Shangzhong

2012-06-01

A brief review of recent progress in researches, productions and applications of full distributed fiber Raman photon sensors at China Jiliang University (CJLU) is presented. In order to improve the measurement distance, the accuracy, the space resolution, the ability of multi-parameter measurements, and the intelligence of full distributed fiber sensor systems, a new generation fiber sensor technology based on the optical fiber nonlinear scattering fusion principle is proposed. A series of new generation full distributed fiber sensors are investigated and designed, which consist of new generation ultra-long distance full distributed fiber Raman and Rayleigh scattering photon sensors integrated with a fiber Raman amplifier, auto-correction full distributed fiber Raman photon temperature sensors based on Raman correlation dual sources, full distributed fiber Raman photon temperature sensors based on a pulse coding source, full distributed fiber Raman photon temperature sensors using a fiber Raman wavelength shifter, a new type of Brillouin optical time domain analyzers (BOTDAs) integrated with a fiber Raman amplifier for replacing a fiber Brillouin amplifier, full distributed fiber Raman and Brillouin photon sensors integrated with a fiber Raman amplifier, and full distributed fiber Brillouin photon sensors integrated with a fiber Brillouin frequency shifter. The Internet of things is believed as one of candidates of the next technological revolution, which has driven hundreds of millions of class markets. Sensor networks are important components of the Internet of things. The full distributed optical fiber sensor network (Rayleigh, Raman, and Brillouin scattering) is a 3S (smart materials, smart structure, and smart skill) system, which is easy to construct smart fiber sensor networks. The distributed optical fiber sensor can be embedded in the power grids, railways, bridges, tunnels, roads, constructions, water supply systems, dams, oil and gas pipelines and other facilities, and can be integrated with wireless networks.

Stream Tracker: Crowd sourcing and remote sensing to monitor stream flow intermittence

NASA Astrophysics Data System (ADS)

Puntenney, K.; Kampf, S. K.; Newman, G.; Lefsky, M. A.; Weber, R.; Gerlich, J.

2017-12-01

Streams that do not flow continuously in time and space support diverse aquatic life and can be critical contributors to downstream water supply. However, these intermittent streams are rarely monitored and poorly mapped. Stream Tracker is a community powered stream monitoring project that pairs citizen contributed observations of streamflow presence or absence with a network of streamflow sensors and remotely sensed data from satellites to track when and where water is flowing in intermittent stream channels. Citizens can visit sites on roads and trails to track flow and contribute their observations to the project site hosted by CitSci.org. Data can be entered using either a mobile application with offline capabilities or an online data entry portal. The sensor network provides a consistent record of streamflow and flow presence/absence across a range of elevations and drainage areas. Capacitance, resistance, and laser sensors have been deployed to determine the most reliable, low cost sensor that could be mass distributed to track streamflow intermittence over a larger number of sites. Streamflow presence or absence observations from the citizen and sensor networks are then compared to satellite imagery to improve flow detection algorithms using remotely sensed data from Landsat. In the first two months of this project, 1,287 observations have been made at 241 sites by 24 project members across northern and western Colorado.

Modular Analytical Multicomponent Analysis in Gas Sensor Aarrays

PubMed Central

Chaiyboun, Ali; Traute, Rüdiger; Kiesewetter, Olaf; Ahlers, Simon; Müller, Gerhard; Doll, Theodor

2006-01-01

A multi-sensor system is a chemical sensor system which quantitatively and qualitatively records gases with a combination of cross-sensitive gas sensor arrays and pattern recognition software. This paper addresses the issue of data analysis for identification of gases in a gas sensor array. We introduce a software tool for gas sensor array configuration and simulation. It concerns thereby about a modular software package for the acquisition of data of different sensors. A signal evaluation algorithm referred to as matrix method was used specifically for the software tool. This matrix method computes the gas concentrations from the signals of a sensor array. The software tool was used for the simulation of an array of five sensors to determine gas concentration of CH4, NH3, H2, CO and C2H5OH. The results of the present simulated sensor array indicate that the software tool is capable of the following: (a) identify a gas independently of its concentration; (b) estimate the concentration of the gas, even if the system was not previously exposed to this concentration; (c) tell when a gas concentration exceeds a certain value. A gas sensor data base was build for the configuration of the software. With the data base one can create, generate and manage scenarios and source files for the simulation. With the gas sensor data base and the simulation software an on-line Web-based version was developed, with which the user can configure and simulate sensor arrays on-line.

QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms.

PubMed

Zwartjes, Ardjan; Havinga, Paul J M; Smit, Gerard J M; Hurink, Johann L

2016-10-01

In this work, we introduce QUEST (QUantile Estimation after Supervised Training), an adaptive classification algorithm for Wireless Sensor Networks (WSNs) that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting raw sensor data puts high demands on the battery, reducing network life time. By merely transmitting partial results or classifications based on the sampled data, the amount of traffic on the network can be significantly reduced. Such classifications can be made by learning based algorithms using sampled data. An important issue, however, is the training phase of these learning based algorithms. Training a deployed sensor network requires a lot of communication and an impractical amount of human involvement. QUEST is a hybrid algorithm that combines supervised learning in a controlled environment with unsupervised learning on the location of deployment. Using the SITEX02 dataset, we demonstrate that the presented solution works with a performance penalty of less than 10% in 90% of the tests. Under some circumstances, it even outperforms a network of classifiers completely trained with supervised learning. As a result, the need for on-site supervised learning and communication for training is completely eliminated by our solution.

Study and Experiment on Non-Contact Voltage Sensor Suitable for Three-Phase Transmission Line

PubMed Central

Zhou, Qiang; He, Wei; Xiao, Dongping; Li, Songnong; Zhou, Kongjun

2015-01-01

A voltage transformer, as voltage signal detection equipment, plays an important role in a power system. Presently, more and more electric power systems are adopting potential transformer and capacitance voltage transformers. Transformers are often large in volume and heavyweight, their insulation design is difficult, and an iron core or multi-grade capacitance voltage division structure is generally adopted. As a result, the detection accuracy of transformer is reduced, a huge phase difference exists between detection signal and voltage signal to be measured, and the detection signal cannot accurately and timely reflect the change of conductor voltage signal to be measured. By aiming at the current problems of electric transformation, based on electrostatic induction principle, this paper designed a non-contact voltage sensor and gained detection signal of the sensor through electrostatic coupling for the electric field generated by electric charges of the conductor to be measured. The insulation structure design of the sensor is simple and its volume is small; phase difference of sensor measurement is effectively reduced through optimization design of the electrode; and voltage division ratio and measurement accuracy are increased. The voltage sensor was tested on the experimental platform of simulating three-phase transmission line. According to the result, the designed non-contact voltage sensor can realize accurate and real-time measurement for the conductor voltage. It can be applied to online monitoring for the voltage of three-phase transmission line or three-phase distribution network line, which is in accordance with the development direction of the smart grid. PMID:26729119

Study and Experiment on Non-Contact Voltage Sensor Suitable for Three-Phase Transmission Line.

PubMed

Zhou, Qiang; He, Wei; Xiao, Dongping; Li, Songnong; Zhou, Kongjun

2015-12-30

A voltage transformer, as voltage signal detection equipment, plays an important role in a power system. Presently, more and more electric power systems are adopting potential transformer and capacitance voltage transformers. Transformers are often large in volume and heavyweight, their insulation design is difficult, and an iron core or multi-grade capacitance voltage division structure is generally adopted. As a result, the detection accuracy of transformer is reduced, a huge phase difference exists between detection signal and voltage signal to be measured, and the detection signal cannot accurately and timely reflect the change of conductor voltage signal to be measured. By aiming at the current problems of electric transformation, based on electrostatic induction principle, this paper designed a non-contact voltage sensor and gained detection signal of the sensor through electrostatic coupling for the electric field generated by electric charges of the conductor to be measured. The insulation structure design of the sensor is simple and its volume is small; phase difference of sensor measurement is effectively reduced through optimization design of the electrode; and voltage division ratio and measurement accuracy are increased. The voltage sensor was tested on the experimental platform of simulating three-phase transmission line. According to the result, the designed non-contact voltage sensor can realize accurate and real-time measurement for the conductor voltage. It can be applied to online monitoring for the voltage of three-phase transmission line or three-phase distribution network line, which is in accordance with the development direction of the smart grid.

Aircraft engine sensor fault diagnostics using an on-line OBEM update method.

PubMed

Liu, Xiaofeng; Xue, Naiyu; Yuan, Ye

2017-01-01

This paper proposed a method to update the on-line health reference baseline of the On-Board Engine Model (OBEM) to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI) system, in which a Hybrid Kalman Filter (HKF) was incorporated. Generated from a rapid in-flight engine degradation, a large health condition mismatch between the engine and the OBEM can corrupt the performance of the FDI. Therefore, it is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV) model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault.

Aircraft engine sensor fault diagnostics using an on-line OBEM update method

PubMed Central

Liu, Xiaofeng; Xue, Naiyu; Yuan, Ye

2017-01-01

This paper proposed a method to update the on-line health reference baseline of the On-Board Engine Model (OBEM) to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI) system, in which a Hybrid Kalman Filter (HKF) was incorporated. Generated from a rapid in-flight engine degradation, a large health condition mismatch between the engine and the OBEM can corrupt the performance of the FDI. Therefore, it is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV) model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault. PMID:28182692

Non-specific monitoring to resolve intermittent pollutant problems associated with wastewater treatment and potable supply.

PubMed

Stuetz, R M

2004-01-01

An online monitoring system based on an array of non-specific sensors was used for the detection of chemical pollutants in wastewater and water. By superimposing sensor profiles for defined sampling window, the identification of data points outside these normal sensor response patterns was used to represent potential pollution episodes or other abnormalities within the process stream. Principle component analysis supported the detection of outliers or rapid changes in the sensor responses as an indicator of chemical pollutants. A model based on the comparison of sensor relative responses to a moving average for a defined sample window was tested for detecting and identifying sudden changes in the online data over a 6-month period. These results show the technical advantages of using a non-specific based monitoring system that can respond to a range of chemical species, due to broad selectivity of the sensor compositions. The findings demonstrate how this non-invasive technique could be further developed to provide early warning systems for application at the inlet of wastewater treatment plants.

Photo-acoustic sensor for detection of oil contamination in compressed air systems.

PubMed

Lassen, Mikael; Harder, David Baslev; Brusch, Anders; Nielsen, Ole Stender; Heikens, Dita; Persijn, Stefan; Petersen, Jan C

2017-02-06

We demonstrate an online (in-situ) sensor for continuous detection of oil contamination in compressed air systems complying with the ISO-8573 standard. The sensor is based on the photo-acoustic (PA) effect. The online and real-time PA sensor system has the potential to benefit a wide range of users that require high purity compressed air. Among these are hospitals, pharmaceutical industries, electronics manufacturers, and clean room facilities. The sensor was tested for sensitivity, repeatability, robustness to molecular cross-interference, and stability of calibration. Explicit measurements of hexane (C₆H₁₄) and decane (C₁₀H₂₂) vapors via excitation of molecular C-H vibrations at approx. 2950 cm^-1 (3.38 μm) were conducted with a custom made interband cascade laser (ICL). For the decane measurements a (1 σ) standard deviation (STD) of 0.3 ppb was demonstrated, which corresponds to a normalized noise equivalent absorption (NNEA) coefficient for the prototype PA sensor of 2.8×10^-9 W cm^-1 Hz^1/2.

Demonstrating the use of web analytics and an online survey to understand user groups of a national network of river level data

NASA Astrophysics Data System (ADS)

Macleod, Christopher Kit; Braga, Joao; Arts, Koen; Ioris, Antonio; Han, Xiwu; Sripada, Yaji; van der Wal, Rene

2016-04-01

The number of local, national and international networks of online environmental sensors are rapidly increasing. Where environmental data are made available online for public consumption, there is a need to advance our understanding of the relationships between the supply of and the different demands for such information. Understanding how individuals and groups of users are using online information resources may provide valuable insights into their activities and decision making. As part of the 'dot.rural wikiRivers' project we investigated the potential of web analytics and an online survey to generate insights into the use of a national network of river level data from across Scotland. These sources of online information were collected alongside phone interviews with volunteers sampled from the online survey, and interviews with providers of online river level data; as part of a larger project that set out to help improve the communication of Scotland's online river data. Our web analytics analysis was based on over 100 online sensors which are maintained by the Scottish Environmental Protection Agency (SEPA). Through use of Google Analytics data accessed via the R Ganalytics package we assessed: if the quality of data provided by Google Analytics free service is good enough for research purposes; if we could demonstrate what sensors were being used, when and where; how the nature and pattern of sensor data may affect web traffic; and whether we can identify and profile these users based on information from traffic sources. Web analytics data consists of a series of quantitative metrics which capture and summarize various dimensions of the traffic to a certain web page or set of pages. Examples of commonly used metrics include the number of total visits to a site and the number of total page views. Our analyses of the traffic sources from 2009 to 2011 identified several different major user groups. To improve our understanding of how the use of this national network of river level data may provide insights into the interactions between individuals and their usage of hydrological information, we ran an online survey linked to the SEPA river level pages for one year. We collected over 2000 complete responses to the survey. The survey included questions on user activities and the importance of river level information for their activities; alongside questions on what additional information they used in their decision making e.g. precipitation, and when and what river pages they visited. In this presentation we will present results from our analysis of the web analytics and online survey, and the insights they provide to understanding user groups of this national network of river level data.

Determination of Chlorinated Hydrocarbons in Water Using Highly Sensitive Mid-Infrared Sensor Technology

NASA Astrophysics Data System (ADS)

Lu, Rui; Mizaikoff, Boris; Li, Wen-Wei; Qian, Chen; Katzir, Abraham; Raichlin, Yosef; Sheng, Guo-Ping; Yu, Han-Qing

2013-08-01

Chlorinated aliphatic hydrocarbons and chlorinated aromatic hydrocarbons (CHCs) are toxic and carcinogenic contaminants commonly found in environmental samples, and efficient online detection of these contaminants is still challenging at the present stage. Here, we report an advanced Fourier transform infrared spectroscopy-attenuated total reflectance (FTIR-ATR) sensor for in-situ and simultaneous detection of multiple CHCs, including monochlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, trichloroethylene, perchloroethylene, and chloroform. The polycrystalline silver halide sensor fiber had a unique integrated planar-cylindric geometry, and was coated with an ethylene/propylene copolymer membrane to act as a solid phase extractor, which greatly amplified the analytical signal and contributed to a higher detection sensitivity compared to the previously reported sensors. This system exhibited a high detection sensitivity towards the CHCs mixture at a wide concentration range of 5~700 ppb. The FTIR-ATR sensor described in this study has a high potential to be utilized as a trace-sensitive on-line device for water contamination monitoring.

Determination of Chlorinated Hydrocarbons in Water Using Highly Sensitive Mid-Infrared Sensor Technology

PubMed Central

Lu, Rui; Mizaikoff, Boris; Li, Wen-Wei; Qian, Chen; Katzir, Abraham; Raichlin, Yosef; Sheng, Guo-Ping; Yu, Han-Qing

2013-01-01

Chlorinated aliphatic hydrocarbons and chlorinated aromatic hydrocarbons (CHCs) are toxic and carcinogenic contaminants commonly found in environmental samples, and efficient online detection of these contaminants is still challenging at the present stage. Here, we report an advanced Fourier transform infrared spectroscopy-attenuated total reflectance (FTIR-ATR) sensor for in-situ and simultaneous detection of multiple CHCs, including monochlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, trichloroethylene, perchloroethylene, and chloroform. The polycrystalline silver halide sensor fiber had a unique integrated planar-cylindric geometry, and was coated with an ethylene/propylene copolymer membrane to act as a solid phase extractor, which greatly amplified the analytical signal and contributed to a higher detection sensitivity compared to the previously reported sensors. This system exhibited a high detection sensitivity towards the CHCs mixture at a wide concentration range of 5~700 ppb. The FTIR-ATR sensor described in this study has a high potential to be utilized as a trace-sensitive on-line device for water contamination monitoring. PMID:23982222

Determination of chlorinated hydrocarbons in water using highly sensitive mid-infrared sensor technology.

PubMed

Lu, Rui; Mizaikoff, Boris; Li, Wen-Wei; Qian, Chen; Katzir, Abraham; Raichlin, Yosef; Sheng, Guo-Ping; Yu, Han-Qing

2013-01-01

Chlorinated aliphatic hydrocarbons and chlorinated aromatic hydrocarbons (CHCs) are toxic and carcinogenic contaminants commonly found in environmental samples, and efficient online detection of these contaminants is still challenging at the present stage. Here, we report an advanced Fourier transform infrared spectroscopy-attenuated total reflectance (FTIR-ATR) sensor for in-situ and simultaneous detection of multiple CHCs, including monochlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, trichloroethylene, perchloroethylene, and chloroform. The polycrystalline silver halide sensor fiber had a unique integrated planar-cylindric geometry, and was coated with an ethylene/propylene copolymer membrane to act as a solid phase extractor, which greatly amplified the analytical signal and contributed to a higher detection sensitivity compared to the previously reported sensors. This system exhibited a high detection sensitivity towards the CHCs mixture at a wide concentration range of 5~700 ppb. The FTIR-ATR sensor described in this study has a high potential to be utilized as a trace-sensitive on-line device for water contamination monitoring.

Development and Validation of an On-Line Water Toxicity Sensor with Immobilized Luminescent Bacteria for On-Line Surface Water Monitoring

PubMed Central

Woutersen, Marjolijn; van der Gaag, Bram; Abrafi Boakye, Afua; Mink, Jan; Marks, Robert S.; Wagenvoort, Arco J.; Ketelaars, Henk A. M.; Brouwer, Bram; Heringa, Minne B.

2017-01-01

Surface water used for drinking water production is frequently monitored in The Netherlands using whole organism biomonitors, with for example Daphnia magna or Dreissena mussels, which respond to changes in the water quality. However, not all human-relevant toxic compounds can be detected by these biomonitors. Therefore, a new on-line biosensor has been developed, containing immobilized genetically modified bacteria, which respond to genotoxicity in the water by emitting luminescence. The performance of this sensor was tested under laboratory conditions, as well as under field conditions at a monitoring station along the river Meuse in The Netherlands. The sensor was robust and easy to clean, with inert materials, temperature control and nutrient feed for the reporter organisms. The bacteria were immobilized in sol-gel on either an optical fiber or a glass slide and then continuously exposed to water. Since the glass slide was more sensitive and robust, only this setup was used in the field. The sensor responded to spikes of genotoxic compounds in the water with a minimal detectable concentration of 0.01 mg/L mitomycin C in the laboratory and 0.1 mg/L mitomycin C in the field. With further optimization, which should include a reduction in daily maintenance, the sensor has the potential to become a useful addition to the currently available biomonitors. PMID:29165334

Development and Validation of an On-Line Water Toxicity Sensor with Immobilized Luminescent Bacteria for On-Line Surface Water Monitoring.

PubMed

Woutersen, Marjolijn; van der Gaag, Bram; Abrafi Boakye, Afua; Mink, Jan; Marks, Robert S; Wagenvoort, Arco J; Ketelaars, Henk A M; Brouwer, Bram; Heringa, Minne B

2017-11-22

Surface water used for drinking water production is frequently monitored in The Netherlands using whole organism biomonitors, with for example Daphnia magna or Dreissena mussels, which respond to changes in the water quality. However, not all human-relevant toxic compounds can be detected by these biomonitors. Therefore, a new on-line biosensor has been developed, containing immobilized genetically modified bacteria, which respond to genotoxicity in the water by emitting luminescence. The performance of this sensor was tested under laboratory conditions, as well as under field conditions at a monitoring station along the river Meuse in The Netherlands. The sensor was robust and easy to clean, with inert materials, temperature control and nutrient feed for the reporter organisms. The bacteria were immobilized in sol-gel on either an optical fiber or a glass slide and then continuously exposed to water. Since the glass slide was more sensitive and robust, only this setup was used in the field. The sensor responded to spikes of genotoxic compounds in the water with a minimal detectable concentration of 0.01 mg/L mitomycin C in the laboratory and 0.1 mg/L mitomycin C in the field. With further optimization, which should include a reduction in daily maintenance, the sensor has the potential to become a useful addition to the currently available biomonitors.

Adaptive inferential sensors based on evolving fuzzy models.

PubMed

Angelov, Plamen; Kordon, Arthur

2010-04-01

A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance. This is achieved by the adaptive and flexible open-structure EFM used. The novelty of this paper lies in the following: (1) the overall concept of inferential sensors with evolving and self-developing structure from the data streams; (2) the new methodology for online automatic selection of input variables that are most relevant for the prediction; (3) the technique to detect automatically a shift in the data pattern using the age of the clusters (and fuzzy rules); (4) the online standardization technique used by the learning procedure of the evolving model; and (5) the application of this innovative approach to several real-life industrial processes from the chemical industry (evolving inferential sensors, namely, eSensors, were used for predicting the chemical properties of different products in The Dow Chemical Company, Freeport, TX). It should be noted, however, that the methodology and conclusions of this paper are valid for the broader area of chemical and process industries in general. The results demonstrate that well-interpretable and with-simple-structure inferential sensors can automatically be designed from the data stream in real time, which predict various process variables of interest. The proposed approach can be used as a basis for the development of a new generation of adaptive and evolving inferential sensors that can address the challenges of the modern advanced process industry.

Fast and accurate determination of the detergent efficiency by optical fiber sensors

NASA Astrophysics Data System (ADS)

Patitsa, Maria; Pfeiffer, Helge; Wevers, Martine

2011-06-01

An optical fiber sensor was developed to control the cleaning efficiency of surfactants. Prior to the measurements, the sensing part of the probe is covered with a uniform standardized soil layer (lipid multilayer), and a gold mirror is deposited at the end of the optical fiber. For the lipid multilayer deposition on the fiber, Langmuir-Blodgett technique was used and the progress of deposition was followed online by ultraviolet spectroscopy. The invention provides a miniaturized Surface Plasmon Resonance dip-sensor for automated on-line testing that can replace the cost and time consuming existing methods and develop a breakthrough in detergent testing in combining optical sensing, surface chemistry and automated data acquisition. The sensor is to be used to evaluate detergency of different cleaning products and also indicate how formulation, concentration, lipid nature and temperature affect the cleaning behavior of a surfactant.

Deposition Of Thin-Film Sensors On Glass-Fiber/Epoxy Models

NASA Technical Reports Server (NTRS)

Tran, Sang Q.

1995-01-01

Direct-deposition process devised for fabrication of thin-film sensors on three-dimensional, curved surfaces of models made of stainless steel covered with glass-fiber/epoxy-matrix composite material. Models used under cryogenic conditions, and sensors used to detect on-line transitions between laminar and turbulent flows in wind tunnel environments. Sensors fabricated by process used at temperatures from minus 300 degrees F to 175 degrees F.

Metallic wear debris sensors: promising developments in failure prevention for wind turbine gearsets and similar components

NASA Astrophysics Data System (ADS)

Poley, Jack; Dines, Michael

2011-04-01

Wind turbines are frequently located in remote, hard-to-reach locations, making it difficult to apply traditional oil analysis sampling of the machine's critical gearset at timely intervals. Metal detection sensors are excellent candidates for sensors designed to monitor machine condition in vivo. Remotely sited components, such as wind turbines, therefore, can be comfortably monitored from a distance. Online sensor technology has come of age with products now capable of identifying onset of wear in time to avoid or mitigate failure. Online oil analysis is now viable, and can be integrated with onsite testing to vet sensor alarms, as well as traditional oil analysis, as furnished by offsite laboratories. Controlled laboratory research data were gathered from tests conducted on a typical wind turbine gearbox, wherein total ferrous particle measurement and metallic particle counting were employed and monitored. The results were then compared with a physical inspection for wear experienced by the gearset. The efficacy of results discussed herein strongly suggests the viability of metallic wear debris sensors in today's wind turbine gearsets, as correlation between sensor data and machine trauma were very good. By extension, similar components and settings would also seem amenable to wear particle sensor monitoring. To our knowledge no experiments such as described herein, have previously been conducted and published.

Propagation of measurement accuracy to biomass soft-sensor estimation and control quality.

PubMed

Steinwandter, Valentin; Zahel, Thomas; Sagmeister, Patrick; Herwig, Christoph

2017-01-01

In biopharmaceutical process development and manufacturing, the online measurement of biomass and derived specific turnover rates is a central task to physiologically monitor and control the process. However, hard-type sensors such as dielectric spectroscopy, broth fluorescence, or permittivity measurement harbor various disadvantages. Therefore, soft-sensors, which use measurements of the off-gas stream and substrate feed to reconcile turnover rates and provide an online estimate of the biomass formation, are smart alternatives. For the reconciliation procedure, mass and energy balances are used together with accuracy estimations of measured conversion rates, which were so far arbitrarily chosen and static over the entire process. In this contribution, we present a novel strategy within the soft-sensor framework (named adaptive soft-sensor) to propagate uncertainties from measurements to conversion rates and demonstrate the benefits: For industrially relevant conditions, hereby the error of the resulting estimated biomass formation rate and specific substrate consumption rate could be decreased by 43 and 64 %, respectively, compared to traditional soft-sensor approaches. Moreover, we present a generic workflow to determine the required raw signal accuracy to obtain predefined accuracies of soft-sensor estimations. Thereby, appropriate measurement devices and maintenance intervals can be selected. Furthermore, using this workflow, we demonstrate that the estimation accuracy of the soft-sensor can be additionally and substantially increased.

Goddard Atmospheric Composition Data Center: Aura Data and Services in One Place

NASA Technical Reports Server (NTRS)

Leptoukh, G.; Kempler, S.; Gerasimov, I.; Ahmad, S.; Johnson, J.

2005-01-01

The Goddard Atmospheric Composition Data and Information Services Center (AC-DISC) is a portal to the Atmospheric Composition specific, user driven, multi-sensor, on-line, easy access archive and distribution system employing data analysis and visualization, data mining, and other user requested techniques for the better science data usage. It provides convenient access to Atmospheric Composition data and information from various remote-sensing missions, from TOMS, UARS, MODIS, and AIRS, to the most recent data from Aura OMI, MLS, HIRDLS (once these datasets are released to the public), as well as Atmospheric Composition datasets residing at other remote archive site.

Online Sensor Fault Detection Based on an Improved Strong Tracking Filter

PubMed Central

Wang, Lijuan; Wu, Lifeng; Guan, Yong; Wang, Guohui

2015-01-01

We propose a method for online sensor fault detection that is based on the evolving Strong Tracking Filter (STCKF). The cubature rule is used to estimate states to improve the accuracy of making estimates in a nonlinear case. A residual is the difference in value between an estimated value and the true value. A residual will be regarded as a signal that includes fault information. The threshold is set at a reasonable level, and will be compared with residuals to determine whether or not the sensor is faulty. The proposed method requires only a nominal plant model and uses STCKF to estimate the original state vector. The effectiveness of the algorithm is verified by simulation on a drum-boiler model. PMID:25690553

Applying Distributed Learning Theory in Online Business Communication Courses.

ERIC Educational Resources Information Center

Walker, Kristin

2003-01-01

Focuses on the critical use of technology in online formats that entail relatively new teaching media. Argues that distributed learning theory is valuable for teachers of online business communication courses for several reasons. Discusses the application of distributed learning theory to the teaching of business communication online. (SG)

Virtual sensors for robust on-line monitoring (OLM) and Diagnostics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tipireddy, Ramakrishna; Lerchen, Megan E.; Ramuhalli, Pradeep

Unscheduled shutdown of nuclear power facilities for recalibration and replacement of faulty sensors can be expensive and disruptive to grid management. In this work, we present virtual (software) sensors that can replace a faulty physical sensor for a short duration thus allowing recalibration to be safely deferred to a later time. The virtual sensor model uses a Gaussian process model to process input data from redundant and other nearby sensors. Predicted data includes uncertainty bounds including spatial association uncertainty and measurement noise and error. Using data from an instrumented cooling water flow loop testbed, the virtual sensor model has predictedmore » correct sensor measurements and the associated error corresponding to a faulty sensor.« less

'Do-It-Yourself' Healthcare? Quality of Health and Healthcare Through Wearable Sensors.

PubMed

Vesnic-Alujevic, Lucia; Breitegger, Melina; Guimarães Pereira, Ângela

2018-06-01

Wearable sensors are an integral part of the new telemedicine concept supporting the idea that Information Technologies will improve the quality and efficiency of healthcare. The use of sensors in diagnosis, treatment and monitoring of patients not only potentially changes medical practice but also one's relationship with one's body and mind, as well as the role and responsibilities of patients and healthcare professionals. In this paper, we focus on knowledge assessment of the online communities of Fitbit (a commercial wearable device) and the Quantified Self movement. Through their online forums, we investigate how users' knowledge claims, shared experiences and imaginations about wearable sensors interrogate or confirm the narratives through which they are introduced to the publics. Citizen initiatives like the Quantified Self movement claim the right to 'own' the sensor generated data. But how these data can be used through traditional healthcare systems is an open question. More importantly, wearable sensors trigger a social function that is transformative of the current idea of care and healthcare, focused on sharing, socialising and collectively reflecting about individual problems. Whether this is aligned with current policy making about healthcare, whose central narrative is focused on efficiency and productivity, is to be seen.

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults.

PubMed

Sun, Rui; Cheng, Qi; Wang, Guanyu; Ochieng, Washington Yotto

2017-09-29

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

A novel fiber-optical vibration defending system with on-line intelligent identification function

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Xie, Xin; Li, Hanyu; Li, Xiaoyu; Wu, Yu; Gong, Yuan; Rao, Yunjiang

2013-09-01

Capacity of the sensor network is always a bottleneck problem for the novel FBG-based quasi-distributed fiberoptical defending system. In this paper, a highly sensitive sensing network with FBG vibration sensors is presented to relieve stress of the capacity and the system cost. However, higher sensitivity may cause higher Nuisance Alarm Rates (NARs) in practical uses. It is necessary to further classify the intrusion pattern or threat level and determine the validity of an unexpected event. Then an intelligent identification method is proposed by extracting the statistical features of the vibration signals in the time domain, and inputting them into a 3-layer Back-Propagation(BP) Artificial Neural Network to classify the events of interest. Experiments of both simulation and field tests are carried out to validate its effectiveness. The results show the recognition rate can be achieved up to 100% for the simulation signals and as high as 96.03% in the real tests.

Quantitative Modeling of Coupled Piezo-Elastodynamic Behavior of Piezoelectric Actuators Bonded to an Elastic Medium for Structural Health Monitoring: A Review

PubMed Central

Huang, Guoliang; Song, Fei; Wang, Xiaodong

2010-01-01

Elastic waves, especially guided waves, generated by a piezoelectric actuator/sensor network, have shown great potential for on-line health monitoring of advanced aerospace, nuclear, and automotive structures in recent decades. Piezoelectric materials can function as both actuators and sensors in these applications due to wide bandwidth, quick response and low costs. One of the most fundamental issues surrounding the effective use of piezoelectric actuators is the quantitative evaluation of the resulting elastic wave propagation by considering the coupled piezo-elastodynamic behavior between the actuator and the host medium. Accurate characterization of the local interfacial stress distribution between the actuator and the host medium is the key issue for the problem. This paper presents a review of the development of analytical, numerical and hybrid approaches for modeling of the coupled piezo-elastodynamic behavior. The resulting elastic wave propagation for structural health monitoring is also summarized. PMID:22319319

Game theoretic sensor management for target tracking

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Blasch, Erik; Pham, Khanh; Douville, Philip; Yang, Chun; Kadar, Ivan

2010-04-01

This paper develops and evaluates a game-theoretic approach to distributed sensor-network management for target tracking via sensor-based negotiation. We present a distributed sensor-based negotiation game model for sensor management for multi-sensor multi-target tacking situations. In our negotiation framework, each negotiation agent represents a sensor and each sensor maximizes their utility using a game approach. The greediness of each sensor is limited by the fact that the sensor-to-target assignment efficiency will decrease if too many sensor resources are assigned to a same target. It is similar to the market concept in real world, such as agreements between buyers and sellers in an auction market. Sensors are willing to switch targets so that they can obtain their highest utility and the most efficient way of applying their resources. Our sub-game perfect equilibrium-based negotiation strategies dynamically and distributedly assign sensors to targets. Numerical simulations are performed to demonstrate our sensor-based negotiation approach for distributed sensor management.

A novel capacitance sensor for fireside corrosion measurement.

PubMed

Ban, Heng; Li, Zuoping

2009-11-01

Fireside corrosion in coal-fired power plants is a leading mechanism for boiler tube failures. Online monitoring of fireside corrosion can provide timely data to plant operators for mitigation implementation. This paper presents a novel sensor concept for measuring metal loss based on electrical capacitance. Laboratory-scale experiments demonstrated the feasibility of design, fabrication, and operation of the sensor. The fabrication of the prototype sensor involved sputtering deposition of a thin metal coating with varying thickness on a ceramic substrate. Corrosion metal loss resulted in a proportional decrease in electrical capacitance of the sensor. Laboratory experiments using a muffle furnace with an oxidation environment demonstrated that low carbon steel coatings on ceramic substrate survived cyclic temperatures over 500 degrees C. Measured corrosion rates of sputtered coating in air had an Arrhenius exponential dependence on temperature, with metal thickness loss ranging from 2.0 nm/h at 200 degrees C to 2.0 microm/h at 400 degrees C. Uncertainty analysis indicated that the overall measurement uncertainty was within 4%. The experimental system showed high signal-to-noise ratio, and the sensor could measure submicrometer metal thickness changes. The laboratory experiments demonstrated that the sensor concept and measurement system are capable of short term, online monitoring of metal loss, indicating the potential for the sensor to be used for fireside corrosion monitoring and other metal loss measurement.

A novel capacitance sensor for fireside corrosion measurement

NASA Astrophysics Data System (ADS)

Ban, Heng; Li, Zuoping

2009-11-01

Fireside corrosion in coal-fired power plants is a leading mechanism for boiler tube failures. Online monitoring of fireside corrosion can provide timely data to plant operators for mitigation implementation. This paper presents a novel sensor concept for measuring metal loss based on electrical capacitance. Laboratory-scale experiments demonstrated the feasibility of design, fabrication, and operation of the sensor. The fabrication of the prototype sensor involved sputtering deposition of a thin metal coating with varying thickness on a ceramic substrate. Corrosion metal loss resulted in a proportional decrease in electrical capacitance of the sensor. Laboratory experiments using a muffle furnace with an oxidation environment demonstrated that low carbon steel coatings on ceramic substrate survived cyclic temperatures over 500 °C. Measured corrosion rates of sputtered coating in air had an Arrhenius exponential dependence on temperature, with metal thickness loss ranging from 2.0 nm/h at 200 °C to 2.0 μm/h at 400 °C. Uncertainty analysis indicated that the overall measurement uncertainty was within 4%. The experimental system showed high signal-to-noise ratio, and the sensor could measure submicrometer metal thickness changes. The laboratory experiments demonstrated that the sensor concept and measurement system are capable of short term, online monitoring of metal loss, indicating the potential for the sensor to be used for fireside corrosion monitoring and other metal loss measurement.

Exploring NASA and ESA Atmospheric Data Using GIOVANNI, the Online Visualization and Analysis Tool

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory

2007-01-01

Giovanni, the NASA Goddard online visualization and analysis tool (http://giovanni.gsfc.nasa.gov) allows users explore various atmospheric phenomena without learning remote sensing data formats and downloading voluminous data. Using NASA MODIS (Terra and Aqua) and ESA MERIS (ENVISAT) aerosol data as an example, we demonstrate Giovanni usage for online multi-sensor remote sensing data comparison and analysis.

Application of a mechanistic model as a tool for on-line monitoring of pilot scale filamentous fungal fermentation processes-The importance of evaporation effects.

PubMed

Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Sin, Gürkan; Gernaey, Krist V

2017-03-01

A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate, dissolved oxygen and mass, as well as other process parameters including k L a, viscosity and partial pressure of CO 2 . State estimation at this scale requires a robust mass model including evaporation, which is a factor not often considered at smaller scales of operation. The model is developed using a historical data set of 11 batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on 14 new batches utilizing a new strain. The product concentration in the validation batches was predicted with an average root mean sum of squared error (RMSSE) of 16.6%. In addition, calculation of the Janus coefficient for the validation batches shows a suitably calibrated model. The robustness of the model prediction is assessed with respect to the accuracy of the input data. Parameter estimation uncertainty is also carried out. The application of this on-line state estimator allows for on-line monitoring of pilot scale batches, including real-time estimates of multiple parameters which are not able to be monitored on-line. With successful application of a soft sensor at this scale, this allows for improved process monitoring, as well as opening up further possibilities for on-line control algorithms, utilizing these on-line model outputs. Biotechnol. Bioeng. 2017;114: 589-599. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Online Resource for Earth-Observing Satellite Sensor Calibration

NASA Technical Reports Server (NTRS)

McCorkel, J.; Czapla-Myers, J.; Thome, K.; Wenny, B.

2015-01-01

The Radiometric Calibration Test Site (RadCaTS) at Railroad Valley Playa, Nevada is being developed by the University of Arizona to enable improved accuracy and consistency for airborne and satellite sensor calibration. Primary instrumentation at the site consists of ground-viewing radiometers, a sun photometer, and a meteorological station. Measurements made by these instruments are used to calculate surface reflectance, atmospheric properties and a prediction for top-of-atmosphere reflectance and radiance. This work will leverage research for RadCaTS, and describe the requirements for an online database, associated data formats and quality control, and processing levels.

A General theory of Signal Integration for Fault-Tolerant Dynamic Distributed Sensor Networks

DTIC Science & Technology

1993-10-01

related to a) the architecture and fault- tolerance of the distributed sensor network, b) the proper synchronisation of sensor signals, c) the...Computational complexities of the problem of distributed detection. 5) Issues related to recording of events and synchronization in distributed sensor...Intervals for Synchronization in Real Time Distributed Systems", Submitted to Electronic Encyclopedia. 3. V. G. Hegde and S. S. Iyengar "Efficient

Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of an Enhanced System

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2008-01-01

In this paper, an enhanced on-line diagnostic system which utilizes dual-channel sensor measurements is developed for the aircraft engine application. The enhanced system is composed of a nonlinear on-board engine model (NOBEM), the hybrid Kalman filter (HKF) algorithm, and fault detection and isolation (FDI) logic. The NOBEM provides the analytical third channel against which the dual-channel measurements are compared. The NOBEM is further utilized as part of the HKF algorithm which estimates measured engine parameters. Engine parameters obtained from the dual-channel measurements, the NOBEM, and the HKF are compared against each other. When the discrepancy among the signals exceeds a tolerance level, the FDI logic determines the cause of discrepancy. Through this approach, the enhanced system achieves the following objectives: 1) anomaly detection, 2) component fault detection, and 3) sensor fault detection and isolation. The performance of the enhanced system is evaluated in a simulation environment using faults in sensors and components, and it is compared to an existing baseline system.

Embedded spectroscopic fiber sensor for on-line arc-welding analysis.

PubMed

Mirapeix, Jesús; Cobo, Adolfo; Quintela, Antonio; López-Higuera, José-Miguel

2007-06-01

A new fiber sensor system designed for spectroscopic analysis and on-line quality assurance of arc-welding processes is presented here. Although several different approaches have been considered for the optical capture of plasma emission in arc-welding processes, they tend to be invasive and make use of optical devices such as collimators or photodiodes. The solution proposed here is based on the arrangement of an optical fiber, which is used at the same time as the optical capturing device and also to deliver the optical information to a spectrometer, embedded within an arc-welding torch. It will be demonstrated that, by using the shielding gas as a protection for the fiber end, the plasma light emission is efficiently collected, forming a sensor system completely transparent and noninvasive for the welding operator. The feasibility of the proposed sensor designed to be used as the input optics of a welding quality-assurance system based on plasma spectroscopy will be demonstrated by means of several welding tests.

A fiber optic sensor for on-line non-touch monitoring of roll shape

NASA Astrophysics Data System (ADS)

Guo, Yuan; Qu, Weijian; Yuan, Qi

2009-07-01

Basing on the principle of reflective displacement fibre-optic sensor, a high accuracy non-touch on-line optical fibre sensor for detecting roll shape is presented. The principle and composition of the detection system and the operation process are expatiated also. By using a novel probe of three optical fibres in equal transverse space, the effects of fluctuations in the light source, reflective changing of target surface and the intensity losses in the fibre lines are automatically compensated. Meantime, an optical fibre sensor model of correcting static error based on BP artificial neural network (ANN) is set up. Also by using interpolation method and value filtering to process the signals, effectively reduce the influence of random noise and the vibration of the roll bearing. So the accuracy and resolution were enhanced remarkably. Experiment proves that the resolution is 1μm and the precision can reach to 0.1%. So the system reaches to the demand of practical production process.

“Are you sure?”: Lapses in Self-Reported Activities Among Healthy Older Adults Reporting Online

PubMed Central

Wild, Katherine V.; Mattek, Nora; Austin, Daniel; Kaye, Jeffrey A.

2015-01-01

Accurate retrospective reporting of activities and symptoms has been shown to be problematic for older adults, yet standard clinical care relies on self-reports to aid in assessment and management. Our aim was to examine the relationship between self-report and sensor-based measures of activity. We administered an online activity survey to participants in our ongoing longitudinal study of in-home ubiquitous monitoring. We found a wide range of accuracy when comparing self-report with time-stamped sensor data. Of the 95 participants who completed the two-hour activity log, nearly one quarter did not complete the task in a way that could potentially be compared with sensor data. Where comparisons were possible, agreement between self-reported and sensor-based activity was achieved by a minority of participants. The findings suggest that capture of real time events with unobtrusive activity monitoring may be a more reliable approach to describing behaviors patterns and meaningful changes in older adults. PMID:25669877

Blood platelet adhesion to protein studied by on-line acoustic wave sensor.

PubMed

Cavic, B A; Freedman, J; Morel, Z; Mody, M; Rand, M L; Stone, D C; Thompson, M

2001-03-01

The attachment of blood platelets to the surface of bare and protein-coated thickness-shear mode acoustic wave devices operating in a flow-through configuration has been studied. Platelets in washed from bind to the gold electrodes of such sensors, but the resulting frequency shifts are far less than predicted by the conventional mass-based model of device operation. Adherence to albumin and various types of collagen can be produced by on-line introduction of protein or by a pre-coating strategy. Differences in attachment of platelets to collagen types I and IV and the Horm variety can be detected. Platelets attached to collagen yield an interesting delayed, but reversible signal on exposure to a flowing medium of low pH. Scanning electron microscopy of sensor surfaces at various time points in this experiment reveals that originally intact platelets are eventually destroyed by the high acidity of the medium. The reversible frequency is attributed to the presence of removable platelet granular components at the sensor-liquid interface.

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds

PubMed Central

Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman

2017-01-01

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions. PMID:28657595

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds.

PubMed

Spinelle, Laurent; Gerboles, Michel; Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman

2017-06-28

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions.

LWT Based Sensor Node Signal Processing in Vehicle Surveillance Distributed Sensor Network

NASA Astrophysics Data System (ADS)

Cha, Daehyun; Hwang, Chansik

Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.

Unsteady Aerodynamic Force Sensing from Measured Strain

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2016-01-01

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm. A cantilevered rectangular wing built and tested at the NASA Langley Research Center (Hampton, Virginia, USA) in 1959 is used to validate the simple approach. Unsteady aerodynamic forces as well as wing deflections, velocities, accelerations, and strains are computed using the CFL3D computational fluid dynamics (CFD) code and an MSC/NASTRAN code (MSC Software Corporation, Newport Beach, California, USA), and these CFL3D-based results are assumed as measured quantities. Based on the measured strains, wing deflections, velocities, accelerations, and aerodynamic forces are computed using the proposed approach. These computed deflections, velocities, accelerations, and unsteady aerodynamic forces are compared with the CFL3D/NASTRAN-based results. In general, computed aerodynamic forces based on the lifting surface theory in subsonic speeds are in good agreement with the target aerodynamic forces generated using CFL3D code with the Euler equation. Excellent aeroelastic responses are obtained even with unsteady strain data under the signal to noise ratio of -9.8dB. The deflections, velocities, and accelerations at each sensor location are independent of structural and aerodynamic models. Therefore, the distributed strain data together with the current proposed approaches can be used as distributed deflection, velocity, and acceleration sensors. This research demonstrates the feasibility of obtaining induced drag and lift forces through the use of distributed sensor technology with measured strain data. An active induced drag control system thus can be designed using the two computed aerodynamic forces, induced drag and lift, to improve the fuel efficiency of an aircraft. Interpolation elements between structural finite element grids and the CFD grids and centroids are successfully incorporated with the unsteady aeroelastic computation scheme. The most critical technology for the success of the proposed approach is the robust on-line parameter estimator, since the least-squares curve fitting method depends heavily on aeroelastic system frequencies and damping factors.

Upper Klamath Basin Landsat Image for September 30, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 18, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for October 29, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 23, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for August 29, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for September 21, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 25, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 28, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for October 22, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for November 8, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for September 27, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for August 19, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for August 19, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for October 16, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for August 4, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for September 20, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for October 7, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 9, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for May 6, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 26, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for April 29, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 12, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 2, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for April 30, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for May 25, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 1, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 17, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 16, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for April 7, 2004: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Graph Design via Convex Optimization: Online and Distributed Perspectives

NASA Astrophysics Data System (ADS)

Meng, De

Network and graph have long been natural abstraction of relations in a variety of applications, e.g. transportation, power system, social network, communication, electrical circuit, etc. As a large number of computation and optimization problems are naturally defined on graphs, graph structures not only enable important properties of these problems, but also leads to highly efficient distributed and online algorithms. For example, graph separability enables the parallelism for computation and operation as well as limits the size of local problems. More interestingly, graphs can be defined and constructed in order to take best advantage of those problem properties. This dissertation focuses on graph structure and design in newly proposed optimization problems, which establish a bridge between graph properties and optimization problem properties. We first study a new optimization problem called Geodesic Distance Maximization Problem (GDMP). Given a graph with fixed edge weights, finding the shortest path, also known as the geodesic, between two nodes is a well-studied network flow problem. We introduce the Geodesic Distance Maximization Problem (GDMP): the problem of finding the edge weights that maximize the length of the geodesic subject to convex constraints on the weights. We show that GDMP is a convex optimization problem for a wide class of flow costs, and provide a physical interpretation using the dual. We present applications of the GDMP in various fields, including optical lens design, network interdiction, and resource allocation in the control of forest fires. We develop an Alternating Direction Method of Multipliers (ADMM) by exploiting specific problem structures to solve large-scale GDMP, and demonstrate its effectiveness in numerical examples. We then turn our attention to distributed optimization on graph with only local communication. Distributed optimization arises in a variety of applications, e.g. distributed tracking and localization, estimation problems in sensor networks, multi-agent coordination. Distributed optimization aims to optimize a global objective function formed by summation of coupled local functions over a graph via only local communication and computation. We developed a weighted proximal ADMM for distributed optimization using graph structure. This fully distributed, single-loop algorithm allows simultaneous updates and can be viewed as a generalization of existing algorithms. More importantly, we achieve faster convergence by jointly designing graph weights and algorithm parameters. Finally, we propose a new problem on networks called Online Network Formation Problem: starting with a base graph and a set of candidate edges, at each round of the game, player one first chooses a candidate edge and reveals it to player two, then player two decides whether to accept it; player two can only accept limited number of edges and make online decisions with the goal to achieve the best properties of the synthesized network. The network properties considered include the number of spanning trees, algebraic connectivity and total effective resistance. These network formation games arise in a variety of cooperative multiagent systems. We propose a primal-dual algorithm framework for the general online network formation game, and analyze the algorithm performance by the competitive ratio and regret.

Integration of piezo-capacitive and piezo-electric nanoweb based pressure sensors for imaging of static and dynamic pressure distribution.

PubMed

Jeong, Y J; Oh, T I; Woo, E J; Kim, K J

2017-07-01

Recently, highly flexible and soft pressure distribution imaging sensor is in great demand for tactile sensing, gait analysis, ubiquitous life-care based on activity recognition, and therapeutics. In this study, we integrate the piezo-capacitive and piezo-electric nanowebs with the conductive fabric sheets for detecting static and dynamic pressure distributions on a large sensing area. Electrical impedance tomography (EIT) and electric source imaging are applied for reconstructing pressure distribution images from measured current-voltage data on the boundary of the hybrid fabric sensor. We evaluated the piezo-capacitive nanoweb sensor, piezo-electric nanoweb sensor, and hybrid fabric sensor. The results show the feasibility of static and dynamic pressure distribution imaging from the boundary measurements of the fabric sensors.

Developing LED UV fluorescence sensors for online monitoring DOM and predicting DBPs formation potential during water treatment.

PubMed

Li, Wen-Tao; Jin, Jing; Li, Qiang; Wu, Chen-Fei; Lu, Hai; Zhou, Qing; Li, Ai-Min

2016-04-15

Online monitoring dissolved organic matter (DOM) is urgent for water treatment management. In this study, high performance size exclusion chromatography with multi-UV absorbance and multi-emission fluorescence scans were applied to spectrally characterize samples from 16 drinking water sources across Yangzi River and Huai River Watersheds. The UV absorbance indices at 254 nm and 280 nm referred to the same DOM components and concentration, and the 280 nm UV light could excite both protein-like and humic-like fluorescence. Hence a novel UV fluorescence sensor was developed out using only one UV280 light-emitting diode (LED) as light source. For all samples, enhanced coagulation was mainly effective for large molecular weight biopolymers; while anion exchange further substantially removed humic substances. During chlorination tests, UVA280 and UVA254 showed similar correlations with yields of disinfection byproducts (DBPs); the humic-like fluorescence obtained from LED sensors correlated well with both trihalomethanes and haloacetic acids yields, while the correlation between protein-like fluorescence and trihalomethanes was relatively poor. Anion exchange exhibited more reduction of DBPs yields as well as UV absorbance and fluorescence signals than enhanced coagulation. The results suggest that the LED UV fluorescence sensors are very promising for online monitoring DOM and predicting DBPs formation potential during water treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Yeast Based Sensors

NASA Astrophysics Data System (ADS)

Shimomura-Shimizu, Mifumi; Karube, Isao

Since the first microbial cell sensor was studied by Karube et al. in 1977, many types of yeast based sensors have been developed as analytical tools. Yeasts are known as facultative anaerobes. Facultative anaerobes can survive in both aerobic and anaerobic conditions. The yeast based sensor consisted of a DO electrode and an immobilized omnivorous yeast. In yeast based sensor development, many kinds of yeast have been employed by applying their characteristics to adapt to the analyte. For example, Trichosporon cutaneum was used to estimate organic pollution in industrial wastewater. Yeast based sensors are suitable for online control of biochemical processes and for environmental monitoring. In this review, principles and applications of yeast based sensors are summarized.

A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process.

PubMed

Choi, D J; Park, H

2001-11-01

For control and automation of biological treatment processes, lack of reliable on-line sensors to measure water quality parameters is one of the most important problems to overcome. Many parameters cannot be measured directly with on-line sensors. The accuracy of existing hardware sensors is also not sufficient and maintenance problems such as electrode fouling often cause trouble. This paper deals with the development of software sensor techniques that estimate the target water quality parameter from other parameters using the correlation between water quality parameters. We focus our attention on the preprocessing of noisy data and the selection of the best model feasible to the situation. Problems of existing approaches are also discussed. We propose a hybrid neural network as a software sensor inferring wastewater quality parameter. Multivariate regression, artificial neural networks (ANN), and a hybrid technique that combines principal component analysis as a preprocessing stage are applied to data from industrial wastewater processes. The hybrid ANN technique shows an enhancement of prediction capability and reduces the overfitting problem of neural networks. The result shows that the hybrid ANN technique can be used to extract information from noisy data and to describe the nonlinearity of complex wastewater treatment processes.

Distributed-effect optical fiber sensors for trusses and plates

NASA Technical Reports Server (NTRS)

Reichard, Karl; Lindner, Douglas K.

1991-01-01

Modal domain optical fiber sensors, or distributed effect sensors, for active vibration suppression in flexible structures are considered. Preliminary modeling results indicate that these sensors can be used to sense vibrations in a flexible beam and the signal can be used to damp vibrations in the beam. Weighted distributed-effect sensors can be used to implement high order compensators with low order functional observers.

Investigation into the use of microwave sensors to monitor particulate manufacturing processes

NASA Astrophysics Data System (ADS)

Austin, John Samuel, III

Knowledge of a material's properties in-line during manufacture is of critical importance to many industries, including the pharmaceutical industry, and can be used for either process or quality control. Different microwave sensor configurations were tested to determine both the moisture content and the bulk density in pharmaceutical powders during processing on-line. Although these parameters can significantly affect a material's flowability, compressibility, and cohesivity, in the presence of blends, the picture is incomplete. Due to the ease with which particulate blends tend to segregate, blend uniformity and chemical composition are two critical parameters in nearly all solids manufacturing industries. The prevailing wisdom has been that microwave sensors are not capable of or sensitive enough to measure the relative concentrations of components in a blend. Consequently, it is common to turn to near infrared sensing to determine material composition on-line. In this study, a novel microwave sensor was designed and utilized to determine, separately, the concentrations of different components in a blend of pharmaceutical powders. This custom microwave sensor was shown to have comparable accuracy to the state-of-the-art for both chemical composition and moisture content determination.

ON-LINE MONITORING OF I&C TRANSMITTERS AND SENSORS FOR CALIBRATION VERIFICATION AND RESPONSE TIME TESTING WAS SUCCESSFULLY IMPLEMENTED AT ATR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson, Phillip A.; O'Hagan, Ryan; Shumaker, Brent

The Advanced Test Reactor (ATR) has always had a comprehensive procedure to verify the performance of its critical transmitters and sensors, including RTDs, and pressure, level, and flow transmitters. These transmitters and sensors have been periodically tested for response time and calibration verification to ensure accuracy. With implementation of online monitoring techniques at ATR, the calibration verification and response time testing of these transmitters and sensors are verified remotely, automatically, hands off, include more portions of the system, and can be performed at almost any time during process operations. The work was done under a DOE funded SBIR project carriedmore » out by AMS. As a result, ATR is now able to save the manpower that has been spent over the years on manual calibration verification and response time testing of its temperature and pressure sensors and refocus those resources towards more equipment reliability needs. More importantly, implementation of OLM will help enhance the overall availability, safety, and efficiency. Together with equipment reliability programs of ATR, the integration of OLM will also help with I&C aging management goals of the Department of Energy and long-time operation of ATR.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Rajeeva; Kumar, Aditya; Dai, Dan

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 developedmore » 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 these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.« less

Recent progress in online ultrasonic process monitoring

NASA Astrophysics Data System (ADS)

Wen, Szu-Sheng L.; Chen, Tzu-Fang; Ramos-Franca, Demartonne; Nguyen, Ky T.; Jen, Cheng-Kuei; Ihara, Ikuo; Derdouri, A.; Garcia-Rejon, Andres

1998-03-01

On-line ultrasonic monitoring of polymer co-extrusion and gas-assisted injection molding are presented. During the co- extrusion of high density polyethylene and Santoprene ultrasonic sensors consisting of piezoelectric transducers and clad ultrasonic buffer rods are used to detect the interface between these two polymers and the stability of the extrusion. The same ultrasonic sensor also measures the surface temperature of the extruded polymer. The results indicate that temperature measurements using ultrasound have a faster response time than those obtained by conventional thermocouple. In gas-assisted injection molding the polymer and gas flow front positions are monitored simultaneously. This information may be used to control the plunger movement.

Fiber-coupled LED gas sensor and its application to online monitoring of ecoefficient dielectric insulation gases in high-voltage circuit breakers.

PubMed

Kramer, Axel; Over, Daniel; Stoller, Patrick; Paul, Thomas A

2017-05-20

Novel dielectric insulation gases used as alternatives to sulfur hexafluoride in gas-insulated switchgear (GIS) include several mixtures containing fluorinated organic compounds. We developed a fiber-optic analyzer enabling concentration measurement of fluoroketones used in medium- and high-voltage switchgear applications by ABB, with concurrent compensation of disturbing effects caused by dust and dirt. The sensor enables measurements in GIS and even in operating high-voltage circuit breakers. The online availability of concentration readings of fluoroketones is important for development tests, but can also be applied for monitoring or diagnostics of field installations.

Research on On-Line Modeling of Fed-Batch Fermentation Process Based on v-SVR

NASA Astrophysics Data System (ADS)

Ma, Yongjun

The fermentation process is very complex and non-linear, many parameters are not easy to measure directly on line, soft sensor modeling is a good solution. This paper introduces v-support vector regression (v-SVR) for soft sensor modeling of fed-batch fermentation process. v-SVR is a novel type of learning machine. It can control the accuracy of fitness and prediction error by adjusting the parameter v. An on-line training algorithm is discussed in detail to reduce the training complexity of v-SVR. The experimental results show that v-SVR has low error rate and better generalization with appropriate v.

Distributed Detection with Collisions in a Random, Single-Hop Wireless Sensor Network

DTIC Science & Technology

2013-05-26

public release; distribution is unlimited. Distributed detection with collisions in a random, single-hop wireless sensor network The views, opinions...1274 2 ABSTRACT Distributed detection with collisions in a random, single-hop wireless sensor network Report Title We consider the problem of... WIRELESS SENSOR NETWORK Gene T. Whipps?† Emre Ertin† Randolph L. Moses† ?U.S. Army Research Laboratory, Adelphi, MD 20783 †The Ohio State University

Embry-Riddle Aeronautical University multispectral sensor and data fusion laboratory: a model for distributed research and education

NASA Astrophysics Data System (ADS)

McMullen, Sonya A. H.; Henderson, Troy; Ison, David

2017-05-01

The miniaturization of unmanned systems and spacecraft, as well as computing and sensor technologies, has opened new opportunities in the areas of remote sensing and multi-sensor data fusion for a variety of applications. Remote sensing and data fusion historically have been the purview of large government organizations, such as the Department of Defense (DoD), National Aeronautics and Space Administration (NASA), and National Geospatial-Intelligence Agency (NGA) due to the high cost and complexity of developing, fielding, and operating such systems. However, miniaturized computers with high capacity processing capabilities, small and affordable sensors, and emerging, commercially available platforms such as UAS and CubeSats to carry such sensors, have allowed for a vast range of novel applications. In order to leverage these developments, Embry-Riddle Aeronautical University (ERAU) has developed an advanced sensor and data fusion laboratory to research component capabilities and their employment on a wide-range of autonomous, robotic, and transportation systems. This lab is unique in several ways, for example, it provides a traditional campus laboratory for students and faculty to model and test sensors in a range of scenarios, process multi-sensor data sets (both simulated and experimental), and analyze results. Moreover, such allows for "virtual" modeling, testing, and teaching capability reaching beyond the physical confines of the facility for use among ERAU Worldwide students and faculty located around the globe. Although other institutions such as Georgia Institute of Technology, Lockheed Martin, University of Dayton, and University of Central Florida have optical sensor laboratories, the ERAU virtual concept is the first such lab to expand to multispectral sensors and data fusion, while focusing on the data collection and data products and not on the manufacturing aspect. Further, the initiative is a unique effort among Embry-Riddle faculty to develop multi-disciplinary, cross-campus research to facilitate faculty- and student-driven research. Specifically, the ERAU Worldwide Campus, with locations across the globe and delivering curricula online, will be leveraged to provide novel approaches to remote sensor experimentation and simulation. The purpose of this paper and presentation is to present this new laboratory, research, education, and collaboration process.

Pure random search for ambient sensor distribution optimisation in a smart home environment.

PubMed

Poland, Michael P; Nugent, Chris D; Wang, Hui; Chen, Liming

2011-01-01

Smart homes are living spaces facilitated with technology to allow individuals to remain in their own homes for longer, rather than be institutionalised. Sensors are the fundamental physical layer with any smart home, as the data they generate is used to inform decision support systems, facilitating appropriate actuator actions. Positioning of sensors is therefore a fundamental characteristic of a smart home. Contemporary smart home sensor distribution is aligned to either a) a total coverage approach; b) a human assessment approach. These methods for sensor arrangement are not data driven strategies, are unempirical and frequently irrational. This Study hypothesised that sensor deployment directed by an optimisation method that utilises inhabitants' spatial frequency data as the search space, would produce more optimal sensor distributions vs. the current method of sensor deployment by engineers. Seven human engineers were tasked to create sensor distributions based on perceived utility for 9 deployment scenarios. A Pure Random Search (PRS) algorithm was then tasked to create matched sensor distributions. The PRS method produced superior distributions in 98.4% of test cases (n=64) against human engineer instructed deployments when the engineers had no access to the spatial frequency data, and in 92.0% of test cases (n=64) when engineers had full access to these data. These results thus confirmed the hypothesis.

Transformer partial discharge monitoring based on optical fiber sensing

NASA Astrophysics Data System (ADS)

Wang, Kun; Tong, Xinglin; Zhu, Xiaolong

2014-06-01

The power transformer is the most important equipment of the high voltage power grid, however, some traditional methods of online partial discharge monitoring have some limitations. Based on many advantages of the optical fiber sensing technology, we have done some research on fiber optics Fabry-Perot (FP) sensing which can be useful for the transformer on online partial discharge monitoring. This research aimed at improving the reliability of power system safety monitoring. We have done some work as follows: designing a set for fiber optics FP sensor preparation, according to the fabrication procedure strictly making out the sensors, building a reasonable signal demodulation system for fiber optics FP sensing, doing a preliminary analysis about online partial discharge signal monitoring, including the research on different discharge intensities with the same measuring distance and different measuring distances with the same discharge intensity, and then making a detailed analysis of the experimental results.

Evaporometer | A Wireless Mesh of Open-Source Rainfall/Evaporation Gauge and Sensor Suite for In Situ Near-Real-Time Environmental Data

NASA Astrophysics Data System (ADS)

Kwon, M.; Lopez Alcala, J. M.; DeBell, T. C.; Udell, C.; Selker, J. S.

2017-12-01

Access to in situ near real-time environmental sensor data in remote locations provides invaluable utility in the fields of agricultural and environmental sciences. For studies where data needs to be gathered frequently, it could be costly and dangerous to take numerous trips into the field to collect this information and to inspect multitudes of distributed devices to ensure proper operation. One solution is to develop remote sensors capable of transmitting data and status updates (like battery level) over long distances from unserviced locations to a receiver hub to be accessed in near real-time online. The Openly Published Environmental Sensing Lab at Oregon State University (OPEnS Lab) produced a low-cost Open Source environmental sensing station called the Evaporometer that collects data at precisely timed intervals including rainfall amount, rate of evaporation, temperature, humidity and light (IR and Visible spectra), while CO2 and other sensors are also being evaluated for inclusion. This project focuses on the development and deployment of the prototype Evaporometer in HJ Andrew's Experimental Forest located in Blue River Oregon. The Evaporometer was designed for efficiency and succeeds in systematically collecting environmental data in hard to reach places over long periods of time. A real time clock interrupt enables the device to enter and exit "sleep mode", allowing Evaporometers to remain in the field over long periods of time and controlling the how frequently data should be collected. A load cell measures the weight of collected water in a container. This container is tightly packed with a fiberglass wick, which draws water from the bottom to the surface for efficient evaporation. A siphon has been designed into the container to prevent any possible water overflow situations and lost collected rainfall. All data collection and transmission processes are handled by an Adafruit Feather development board equipped with a long range, low power wireless (LoRa) radio that sends encrypted data via 900MHz ISM band. This data can be transmitted up to 20km to a receiver hub with an internet connection, and uploaded directly to Google cloud storage or other online data services for convenience.

An Evaluation of Short-Term Distributed Online Learning Events

ERIC Educational Resources Information Center

Barker, Bradley; Brooks, David

2005-01-01

The purpose of this study was to evaluate the effectiveness of short-term distributed online training events using an adapted version of the compressed evaluation form developed by Wisher and Curnow (1998). Evaluating online distributed training events provides insight into course effectiveness, the contribution of prior knowledge to learning, and…

Localization of Mobile Robots Using Odometry and an External Vision Sensor

PubMed Central

Pizarro, Daniel; Mazo, Manuel; Santiso, Enrique; Marron, Marta; Jimenez, David; Cobreces, Santiago; Losada, Cristina

2010-01-01

This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields. PMID:22319318

Estimation of tool wear during CNC milling using neural network-based sensor fusion

NASA Astrophysics Data System (ADS)

Ghosh, N.; Ravi, Y. B.; Patra, A.; Mukhopadhyay, S.; Paul, S.; Mohanty, A. R.; Chattopadhyay, A. B.

2007-01-01

Cutting tool wear degrades the product quality in manufacturing processes. Monitoring tool wear value online is therefore needed to prevent degradation in machining quality. Unfortunately there is no direct way of measuring the tool wear online. Therefore one has to adopt an indirect method wherein the tool wear is estimated from several sensors measuring related process variables. In this work, a neural network-based sensor fusion model has been developed for tool condition monitoring (TCM). Features extracted from a number of machining zone signals, namely cutting forces, spindle vibration, spindle current, and sound pressure level have been fused to estimate the average flank wear of the main cutting edge. Novel strategies such as, signal level segmentation for temporal registration, feature space filtering, outlier removal, and estimation space filtering have been proposed. The proposed approach has been validated by both laboratory and industrial implementations.

NPK NMR Sensor: Online Monitoring of Nitrogen, Phosphorus, and Potassium in Animal Slurry.

PubMed

Sørensen, Morten K; Jensen, Ole; Bakharev, Oleg N; Nyord, Tavs; Nielsen, Niels Chr

2015-07-07

Knowledge of the actual content of nitrogen, phosphorus, and potassium (NPK) in animal slurry is highly important to optimize crop production and avoid environmental pollution when slurry is spread on agricultural fields. Here, we present a mobile, low-field nuclear magnetic resonance (NMR) sensor suitable for online monitoring of the NPK content in animal slurry as an alternative to crude estimates or tedious nonspecific, off-site laboratory analysis. The sensor is based on (14)N, (17)O, (31)P, and (39)K NMR in a digital NMR instrument equipped with a 1.5 T Halbach magnet for direct detection of ammonium N, total P, and K and indirect evaluation of the organic N content, covering all practical components of NPK in animal slurry. In correlation studies, the obtained NMR measurements show good agreement with reference measurements from commercial laboratories.

Localization of mobile robots using odometry and an external vision sensor.

PubMed

Pizarro, Daniel; Mazo, Manuel; Santiso, Enrique; Marron, Marta; Jimenez, David; Cobreces, Santiago; Losada, Cristina

2010-01-01

This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields.

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

2017-02-01

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

Knock probability estimation through an in-cylinder temperature model with exogenous noise

NASA Astrophysics Data System (ADS)

Bares, P.; Selmanaj, D.; Guardiola, C.; Onder, C.

2018-01-01

This paper presents a new knock model which combines a deterministic knock model based on the in-cylinder temperature and an exogenous noise disturbing this temperature. The autoignition of the end-gas is modelled by an Arrhenius-like function and the knock probability is estimated by propagating a virtual error probability distribution. Results show that the random nature of knock can be explained by uncertainties at the in-cylinder temperature estimation. The model only has one parameter for calibration and thus can be easily adapted online. In order to reduce the measurement uncertainties associated with the air mass flow sensor, the trapped mass is derived from the in-cylinder pressure resonance, which improves the knock probability estimation and reduces the number of sensors needed for the model. A four stroke SI engine was used for model validation. By varying the intake temperature, the engine speed, the injected fuel mass, and the spark advance, specific tests were conducted, which furnished data with various knock intensities and probabilities. The new model is able to predict the knock probability within a sufficient range at various operating conditions. The trapped mass obtained by the acoustical model was compared in steady conditions by using a fuel balance and a lambda sensor and differences below 1 % were found.

An Integrated Instrumentation System for Velocity, Concentration and Mass Flow Rate Measurement of Solid Particles Based on Electrostatic and Capacitance Sensors.

PubMed

Li, Jian; Kong, Ming; Xu, Chuanlong; Wang, Shimin; Fan, Ying

2015-12-10

The online and continuous measurement of velocity, concentration and mass flow rate of pneumatically conveyed solid particles for the high-efficiency utilization of energy and raw materials has become increasingly significant. In this paper, an integrated instrumentation system for the velocity, concentration and mass flow rate measurement of dense phase pneumatically conveyed solid particles based on electrostatic and capacitance sensorsis developed. The electrostatic sensors are used for particle mean velocity measurement in combination with the cross-correlation technique, while the capacitance sensor with helical surface-plate electrodes, which has relatively homogeneous sensitivity distribution, is employed for the measurement of particle concentration and its capacitance is measured by an electrostatic-immune AC-based circuit. The solid mass flow rate can be further calculated from the measured velocity and concentration. The developed instrumentation system for velocity and concentration measurement is verified and calibrated on a pulley rig and through static experiments, respectively. Finally the system is evaluated with glass beads on a gravity-fed rig. The experimental results demonstrate that the system is capable of the accurate solid mass flow rate measurement, and the relative error is within -3%-8% for glass bead mass flow rates ranging from 0.13 kg/s to 0.9 kg/s.

Wearable sweat detector device design for health monitoring and clinical diagnosis

NASA Astrophysics Data System (ADS)

Wu, Qiuchen; Zhang, Xiaodong; Tian, Bihao; Zhang, Hongyan; Yu, Yang; Wang, Ming

2017-06-01

Miniaturized sensor is necessary part for wearable detector for biomedical applications. Wearable detector device is indispensable for online health care. This paper presents a concept of an wearable digital health monitoring device design for sweat analysis. The flexible sensor is developed to quantify the amount of hydrogen ions in sweat and skin temperature in real time. The detection system includes pH sensor, temperature sensor, signal processing module, power source, microprocessor, display module and so on. The sweat monitoring device is designed for sport monitoring or clinical diagnosis.

Online tools for uncovering data quality issues in satellite-based global precipitation products

NASA Astrophysics Data System (ADS)

Liu, Z.; Heo, G.

2015-12-01

Accurate and timely available global precipitation products are important to many applications such as flood forecasting, hydrological modeling, vector-borne disease research, crop yield estimates, etc. However, data quality issues such as biases and uncertainties are common in satellite-based precipitation products and it is important to understand these issues in applications. In recent years, algorithms using multi-satellites and multi-sensors for satellite-based precipitation estimates have become popular, such as the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA) and the latest Integrated Multi-satellitE Retrievals for GPM (IMERG). Studies show that data quality issues for multi-satellite and multi-sensor products can vary with space and time and can be difficult to summarize. Online tools can provide customized results for a given area of interest, allowing customized investigation or comparison on several precipitation products. Because downloading data and software is not required, online tools can facilitate precipitation product evaluation and comparison. In this presentation, we will present online tools to uncover data quality issues in satellite-based global precipitation products. Examples will be presented as well.

Potential of on-line visible and near infrared spectroscopy for measurement of pH for deriving variable rate lime recommendations.

PubMed

Tekin, Yücel; Kuang, Boyan; Mouazen, Abdul M

2013-08-08

This paper aims at exploring the potential of visible and near infrared (vis-NIR) spectroscopy for on-line measurement of soil pH, with the intention to produce variable rate lime recommendation maps. An on-line vis-NIR soil sensor set up to a frame was used in this study. Lime application maps, based on pH predicted by vis-NIR techniques, were compared with maps based on traditional lab-measured pH. The validation of the calibration model using off-line spectra provided excellent prediction accuracy of pH (R2 = 0.85, RMSEP = 0.18 and RPD = 2.52), as compared to very good accuracy obtained with the on-line measured spectra (R2 = 0.81, RMSEP = 0.20 and RPD = 2.14). On-line predicted pH of all points (e.g., 2,160) resulted in the largest overall field virtual lime requirement (1.404 t), as compared to those obtained with 16 validation points off-line prediction (0.28 t), on-line prediction (0.14 t) and laboratory reference measurement (0.48 t). The conclusion is that the vis-NIR spectroscopy can be successfully used for the prediction of soil pH and for deriving lime recommendations. The advantage of the on-line sensor over sampling with limited number of samples is that more detailed information about pH can be obtained, which is the reason for a higher but precise calculated lime recommendation rate.

Potential of On-Line Visible and Near Infrared Spectroscopy for Measurement of pH for Deriving Variable Rate Lime Recommendations

PubMed Central

Tekin, Yücel; Kuang, Boyan; Mouazen, Abdul M.

2013-01-01

This paper aims at exploring the potential of visible and near infrared (vis-NIR) spectroscopy for on-line measurement of soil pH, with the intention to produce variable rate lime recommendation maps. An on-line vis-NIR soil sensor set up to a frame was used in this study. Lime application maps, based on pH predicted by vis-NIR techniques, were compared with maps based on traditional lab-measured pH. The validation of the calibration model using off-line spectra provided excellent prediction accuracy of pH (R2 = 0.85, RMSEP = 0.18 and RPD = 2.52), as compared to very good accuracy obtained with the on-line measured spectra (R2 = 0.81, RMSEP = 0.20 and RPD = 2.14). On-line predicted pH of all points (e.g., 2,160) resulted in the largest overall field virtual lime requirement (1.404 t), as compared to those obtained with 16 validation points off-line prediction (0.28 t), on-line prediction (0.14 t) and laboratory reference measurement (0.48 t). The conclusion is that the vis-NIR spectroscopy can be successfully used for the prediction of soil pH and for deriving lime recommendations. The advantage of the on-line sensor over sampling with limited number of samples is that more detailed information about pH can be obtained, which is the reason for a higher but precise calculated lime recommendation rate. PMID:23966186

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

PubMed Central

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N.

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

PubMed

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

Environmental Monitoring Using Sensor Networks

NASA Astrophysics Data System (ADS)

Yang, J.; Zhang, C.; Li, X.; Huang, Y.; Fu, S.; Acevedo, M. F.

2008-12-01

Environmental observatories, consisting of a variety of sensor systems, computational resources and informatics, are important for us to observe, model, predict, and ultimately help preserve the health of the nature. The commoditization and proliferation of coin-to-palm sized wireless sensors will allow environmental monitoring with unprecedented fine spatial and temporal resolution. Once scattered around, these sensors can identify themselves, locate their positions, describe their functions, and self-organize into a network. They communicate through wireless channel with nearby sensors and transmit data through multi-hop protocols to a gateway, which can forward information to a remote data server. In this project, we describe an environmental observatory called Texas Environmental Observatory (TEO) that incorporates a sensor network system with intertwined wired and wireless sensors. We are enhancing and expanding the existing wired weather stations to include wireless sensor networks (WSNs) and telemetry using solar-powered cellular modems. The new WSNs will monitor soil moisture and support long-term hydrologic modeling. Hydrologic models are helpful in predicting how changes in land cover translate into changes in the stream flow regime. These models require inputs that are difficult to measure over large areas, especially variables related to storm events, such as soil moisture antecedent conditions and rainfall amount and intensity. This will also contribute to improve rainfall estimations from meteorological radar data and enhance hydrological forecasts. Sensor data are transmitted from monitoring site to a Central Data Collection (CDC) Server. We incorporate a GPRS modem for wireless telemetry, a single-board computer (SBC) as Remote Field Gateway (RFG) Server, and a WSN for distributed soil moisture monitoring. The RFG provides effective control, management, and coordination of two independent sensor systems, i.e., a traditional datalogger-based wired sensor system and the WSN-based wireless sensor system. The RFG also supports remote manipulation of the devices in the field such as the SBC, datalogger, and WSN. Sensor data collected from the distributed monitoring stations are stored in a database (DB) Server. The CDC Server acts as an intermediate component to hide the heterogeneity of different devices and support data validation required by the DB Server. Daemon programs running on the CDC Server pre-process the data before it is inserted into the database, and periodically perform synchronization tasks. A SWE-compliant data repository is installed to enable data exchange, accepting data from both internal DB Server and external sources through the OGC web services. The web portal, i.e. TEO Online, serves as a user-friendly interface for data visualization, analysis, synthesis, modeling, and K-12 educational outreach activities. It also provides useful capabilities for system developers and operators to remotely monitor system status and remotely update software and system configuration, which greatly simplifies the system debugging and maintenance tasks. We also implement Sensor Observation Services (SOS) at this layer, conforming to the SWE standard to facilitate data exchange. The standard SensorML/O&M data representation makes it easy to integrate our sensor data into the existing Geographic Information Systems (GIS) web services and exchange the data with other organizations.

Control systems using modal domain optical fiber sensors for smart structure applications

NASA Technical Reports Server (NTRS)

Lindner, Douglas K.; Reichard, Karl M.

1991-01-01

Recently, a new class of sensors has emerged for structural control which respond to environmental changes over a significant gauge length; these sensors are called distributed-effect sensors. These sensors can be fabricated with spatially varying sensitivity to the distributed measurand, and can be configured to measure a variety of structural parameters which can not be measured directly using point sensors. Examples of distributed-effect sensors include piezoelectric film, holographic sensors, and modal domain optical fiber sensors. Optical fiber sensors are particularly attractive for smart structure applications because they are flexible, have low mass, and can easily be embedded directly into materials. In this paper we describe the implementation of weighted modal domain optical fiber sensors. The mathematical model of the modal domain optical fiber sensor model is described and used to derive an expression for the sensor sensitivity. The effects of parameter variations on the sensor sensitivity are demonstrated to illustrate methods of spatially varying the sensor sensitivity.

Chemical, biochemical, and environmental fiber sensors III; Proceedings of the Meeting, Boston, MA, Sept. 4, 5, 1991

NASA Astrophysics Data System (ADS)

Lieberman, Robert A.

Various papers on chemical, biochemical, and environmental fiber sensors are presented. Individual topics addressed include: fiber optic pressure sensor for combustion monitoring and control, viologen-based fiber optic oxygen sensors, renewable-reagent fiber optic sensor for ocean pCO2, transition metal complexes as indicators for a fiber optic oxygen sensor, fiber optic pH measurements using azo indicators, simple reversible fiber optic chemical sensors using solvatochromic dyes, totally integrated optical measuring sensors, integrated optic biosensor for environmental monitoring, radiation dosimetry using planar waveguide sensors, optical and piezoelectric analysis of polymer films for chemical sensor characterization, source polarization effects in an optical fiber fluorosensor, lens-type refractometer for on-line chemical analysis, fiber optic hydrocarbon sensor system, chemical sensors for environmental monitoring, optical fibers for liquid-crystal sensing and logic devices, suitability of single-mode fluoride fibers for evanescent-wave sensing, integrated modules for fiber optic sensors, optoelectronic sensors based on narrowband A3B5 alloys, fiber Bragg grating chemical sensor.

Online identification algorithms for integrated dielectric electroactive polymer sensors and self-sensing concepts

NASA Astrophysics Data System (ADS)

Hoffstadt, Thorben; Griese, Martin; Maas, Jürgen

2014-10-01

Transducers based on dielectric electroactive polymers (DEAP) use electrostatic pressure to convert electric energy into strain energy or vice versa. Besides this, they are also designed for sensor applications in monitoring the actual stretch state on the basis of the deformation dependent capacitive-resistive behavior of the DEAP. In order to enable an efficient and proper closed loop control operation of these transducers, e.g. in positioning or energy harvesting applications, on the one hand, sensors based on DEAP material can be integrated into the transducers and evaluated externally, and on the other hand, the transducer itself can be used as a sensor, also in terms of self-sensing. For this purpose the characteristic electrical behavior of the transducer has to be evaluated in order to determine the mechanical state. Also, adequate online identification algorithms with sufficient accuracy and dynamics are required, independent from the sensor concept utilized, in order to determine the electrical DEAP parameters in real time. Therefore, in this contribution, algorithms are developed in the frequency domain for identifications of the capacitance as well as the electrode and polymer resistance of a DEAP, which are validated by measurements. These algorithms are designed for self-sensing applications, especially if the power electronics utilized is operated at a constant switching frequency, and parasitic harmonic oscillations are induced besides the desired DC value. These oscillations can be used for the online identification, so an additional superimposed excitation is no longer necessary. For this purpose a dual active bridge (DAB) is introduced to drive the DEAP transducer. The capabilities of the real-time identification algorithm in combination with the DAB are presented in detail and discussed, finally.

Research on on-line monitoring technology for steel ball's forming process based on load signal analysis method

NASA Astrophysics Data System (ADS)

Li, Ying-jun; Ai, Chang-sheng; Men, Xiu-hua; Zhang, Cheng-liang; Zhang, Qi

2013-04-01

This paper presents a novel on-line monitoring technology to obtain forming quality in steel ball's forming process based on load signal analysis method, in order to reveal the bottom die's load characteristic in initial cold heading forging process of steel balls. A mechanical model of the cold header producing process is established and analyzed by using finite element method. The maximum cold heading force is calculated. The results prove that the monitoring on the cold heading process with upsetting force is reasonable and feasible. The forming defects are inflected on the three feature points of the bottom die signals, which are the initial point, infection point, and peak point. A novel PVDF piezoelectric force sensor which is simple on construction and convenient on installation is designed. The sensitivity of the PVDF force sensor is calculated. The characteristics of PVDF force sensor are analyzed by FEM. The PVDF piezoelectric force sensor is fabricated to acquire the actual load signals in the cold heading process, and calibrated by a special device. The measuring system of on-line monitoring is built. The characteristics of the actual signals recognized by learning and identification algorithm are in consistence with simulation results. Identification of actual signals shows that the timing difference values of all feature points for qualified products are not exceed ±6 ms, and amplitude difference values are less than ±3%. The calibration and application experiments show that PVDF force sensor has good static and dynamic performances, and is competent at dynamic measuring on upsetting force. It greatly improves automatic level and machining precision. Equipment capacity factor with damages identification method depends on grade of steel has been improved to 90%.

Preparing Precipitation Data Access, Value-added Services and Scientific Exploration Tools for the Integrated Multi-satellitE Retrievals for GPM (IMERG)

NASA Astrophysics Data System (ADS)

Ostrenga, D.; Liu, Z.; Kempler, S. J.; Vollmer, B.; Teng, W. L.

2013-12-01

The Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google: NASA PDISC), located at the NASA Goddard Space Flight Center (GSFC) Earth Sciences (GES) Data and Information Services Center (DISC), is home of the Tropical Rainfall Measuring Mission (TRMM) data archive. For over 15 years, the GES DISC has served not only TRMM, but also other space-based, airborne-based, field campaign and ground-based precipitation data products to the precipitation community and other disciplinary communities as well. The TRMM Multi-Satellite Precipitation Analysis (TMPA) products are the most popular products in the TRMM product family in terms of data download and access through Mirador, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) and other services. The next generation of TMPA, the Integrated Multi-satellitE Retrievals for GPM (IMERG) to be released in 2014 after the launch of GPM, will be significantly improved in terms of spatial and temporal resolutions. To better serve the user community, we are preparing data services and samples are listed below. To enable scientific exploration of Earth science data products without going through complicated and often time consuming processes, such as data downloading, data processing, etc., the GES DISC has developed Giovanni in consultation with members of the user community, requesting quick search, subset, analysis and display capabilities for their specific data of interest. For example, the TRMM Online Visualization and Analysis System (TOVAS, http://disc2.nascom.nasa.gov/Giovanni/tovas/) has proven extremely popular, especially as additional datasets have been added upon request. Giovanni will continue to evolve to accommodate GPM data and the multi-sensor data inter-comparisons that will be sure to follow. Additional PDISC tool and service capabilities being adapted for GPM data include: An on-line PDISC Portal (includes user guide, etc.); Data ingest, processing, distribution from on-line archive; Google-like Mirador data search and access engine; electronic distribution, Subscriptions; Uses semantic technology to help manage large amounts of multi-sensor data and their relationships; Data drill down and search capabilities; Data access through various web services, i.e., OPeNDAP, GDS, WMS, WCS; Conversion into various formats, e.g., netCDF, HDF, KML (for Google Earth), ascii; Exploration, visualization and statistical online analysis through Giovanni; Visualization and analysis of L2 data profiles and maps; Generation of derived products, such as, daily products; Parameter and spatial subsetting; Time and temporal aggregation; Regridding; Data version control and provenance; Data Stewardship - Continuous archive verification; Documentation; Science support for proper data usage, help desk; Monitoring services for applications; Expertise in data related standards and interoperability. This presentation will further describe the data services at the PDISC that are currently being utilized by precipitation science and application researchers, and the preparation plan for IMERG. Comments and feedback are welcome.

Online-offline activities and game-playing behaviors of avatars in a massive multiplayer online role-playing game

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing; Tan, Qun-Zhao

2009-11-01

Massive multiplayer online role-playing games (MMORPGs) are very popular in China, which provides a potential platform for scientific research. We study the online-offline activities of avatars in an MMORPG to understand their game-playing behavior. The statistical analysis unveils that the active avatars can be classified into three types. The avatars of the first type are owned by game cheaters who go online and offline in preset time intervals with the online duration distributions dominated by pulses. The second type of avatars is characterized by a Weibull distribution in the online durations, which is confirmed by statistical tests. The distributions of online durations of the remaining individual avatars differ from the above two types and cannot be described by a simple form. These findings have potential applications in the game industry.

Publicly Available Geosynchronous (GEO) Space Object Catalog for Future Space Situational Awareness (SSA) Studies

NASA Astrophysics Data System (ADS)

Koblick, D. C.; Shankar, P.; Xu, S.

Previously, there have been many commercial proposals and extensive academic studies regarding ground and space based sensors to assist a space surveillance network in obtaining metric observations of satellites and debris near Geosynchronous Earth Orbit (GEO). Most use physics based models for geometric constraints, lighting, and tasker/scheduler operations of sensor architectures. Under similar physics modeling assumptions, the space object catalog is often different due to proprietary standards and datasets. Lack of catalog commonality between studies creates barriers and difficulty comparing performance benefits of sensor trades. To solve this problem, we have constructed a future GEO space catalog from publicly available datasets and literature. The annual number of new payloads and rocket bodies is drawn from a Poisson distribution while the growth of the current GEO catalog is bootstrapped from the historical payload, upper stage, and debris data. We adopt a spherically symmetric explosion model and couple it with the NASA standard breakup model to simulate explosions of payloads and rocket bodies as they are the primary drivers of the debris population growth. The cumulative number of fragments follow a power-law distribution. Result from 1,000 random catalog growth simulations indicates that the GEO space object population in the year 2050 will include over 3,600 objects, nearly half of which are debris greater than 10 cm spherical diameter. The number of rocket bodies and dead payloads is projected to nearly double over the next 33 years. For comparison, the current Air Force Space Command catalog snapshot contains fewer than 50 pieces of debris and coarse Radar Cross Section (RCS) estimates which include: small, medium, and large. The current catalog may be sufficient for conjunction studies, but not for analyzing future sensor system performance. The 2050 GEO projected catalog will be available online for commercial/academic research and development.

Analysis of the reflection of a micro drop fiber sensor

NASA Astrophysics Data System (ADS)

Sun, Weimin; Liu, Qiang; Zhao, Lei; Li, Yingjuan; Yuan, Libo

2005-01-01

Micro drop fiber sensors are effective tools for measuring characters of liquids. These types of sensors are wildly used in biotechnology, beverage and food markets. For a fiber micro drop sensor, the signal of the output light is wavy with two peaks, normally. Carefully analyzing the wavy process can identify the liquid components. Understanding the reason of forming this wavy signal is important to design a suitable sensing head and to choose a suitable signal-processing method. The dripping process of a type of liquids is relative to the characters of the liquid and the shape of the sensing head. The quasi-Gauss model of the light field from the input-fiber end is used to analyse the distribution of the light field in the liquid drop. In addition, considering the characters of the liquid to be measured, the dripping process of the optical signal from the output-fiber end can be expected. The reflection surface of the micro drop varies as serials of spheres with different radiuses and global centers. The intensity of the reflection light changes with the shape of the surface. The varying process of the intensity relates to the tense, refractive index, transmission et al. To support the analyse above, an experimental system is established. In the system, LED is chosen as the light source and the PIN transform the light signal to the electrical signal, which is collected by a data acquisition card. An on-line testing system is made to check the theory discussed above.

Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

NASA Technical Reports Server (NTRS)

Ramirez, W. Fred; Skliar, Mikhail; Narayan, Anand; Morgenthaler, George W.; Smith, Gerald J.

1996-01-01

Progress and results in the development of an integrated air quality modeling, monitoring, fault detection, and isolation system are presented. The focus was on development of distributed models of the air contaminants transport, the study of air quality monitoring techniques based on the model of transport process and on-line contaminant concentration measurements, and sensor placement. Different approaches to the modeling of spacecraft air contamination are discussed, and a three-dimensional distributed parameter air contaminant dispersion model applicable to both laminar and turbulent transport is proposed. A two-dimensional approximation of a full scale transport model is also proposed based on the spatial averaging of the three dimensional model over the least important space coordinate. A computer implementation of the transport model is considered and a detailed development of two- and three-dimensional models illustrated by contaminant transport simulation results is presented. The use of a well established Kalman filtering approach is suggested as a method for generating on-line contaminant concentration estimates based on both real time measurements and the model of contaminant transport process. It is shown that high computational requirements of the traditional Kalman filter can render difficult its real-time implementation for high-dimensional transport model and a novel implicit Kalman filtering algorithm is proposed which is shown to lead to an order of magnitude faster computer implementation in the case of air quality monitoring.

Structure and yarn sensor for fabric

DOEpatents

Mee, David K.; Allgood, Glenn O.; Mooney, Larry R.; Duncan, Michael G.; Turner, John C.; Treece, Dale A.

1998-01-01

A structure and yarn sensor for fabric directly determines pick density in a fabric thereby allowing fabric length and velocity to be calculated from a count of the picks made by the sensor over known time intervals. The structure and yarn sensor is also capable of detecting full length woven defects and fabric. As a result, an inexpensive on-line pick (or course) density measurement can be performed which allows a loom or knitting machine to be adjusted by either manual or automatic means to maintain closer fiber density tolerances. Such a sensor apparatus dramatically reduces fabric production costs and significantly improves fabric consistency and quality for woven or knitted fabric.

Structure and yarn sensor for fabric

DOEpatents

Mee, D.K.; Allgood, G.O.; Mooney, L.R.; Duncan, M.G.; Turner, J.C.; Treece, D.A.

1998-10-20

A structure and yarn sensor for fabric directly determines pick density in a fabric thereby allowing fabric length and velocity to be calculated from a count of the picks made by the sensor over known time intervals. The structure and yarn sensor is also capable of detecting full length woven defects and fabric. As a result, an inexpensive on-line pick (or course) density measurement can be performed which allows a loom or knitting machine to be adjusted by either manual or automatic means to maintain closer fiber density tolerances. Such a sensor apparatus dramatically reduces fabric production costs and significantly improves fabric consistency and quality for woven or knitted fabric. 13 figs.

Novel Corrosion Sensor for Vision 21 Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heng Ban; Bharat Soni

2007-03-31

Advanced sensor technology is identified as a key component for advanced power systems for future energy plants that would have virtually no environmental impact. This project intends to develop a novel high temperature corrosion sensor and subsequent measurement system for advanced power systems. Fireside corrosion is the leading mechanism for boiler tube failures and has emerged to be a significant concern for current and future energy plants due to the introduction of technologies targeting emissions reduction, efficiency improvement, or fuel/oxidant flexibility. Corrosion damage can lead to catastrophic equipment failure, explosions, and forced outages. Proper management of corrosion requires real-time indicationmore » of corrosion rate. However, short-term, on-line corrosion monitoring systems for fireside corrosion remain a technical challenge to date due to the extremely harsh combustion environment. The overall goal of this project is to develop a technology for on-line fireside corrosion monitoring. This objective is achieved by the laboratory development of sensors and instrumentation, testing them in a laboratory muffle furnace, and eventually testing the system in a coal-fired furnace. This project successfully developed two types of sensors and measurement systems, and successful tested them in a muffle furnace in the laboratory. The capacitance sensor had a high fabrication cost and might be more appropriate in other applications. The low-cost resistance sensor was tested in a power plant burning eastern bituminous coals. The results show that the fireside corrosion measurement system can be used to determine the corrosion rate at waterwall and superheater locations. Electron microscope analysis of the corroded sensor surface provided detailed picture of the corrosion process.« less

Application of an Online-Biomass Sensor in an Optical Multisensory Platform Prototype for Growth Monitoring of Biotechnical Relevant Microorganism and Cell Lines in Single-Use Shake Flasks

PubMed Central

Ude, Christian; Schmidt-Hager, Jörg; Findeis, Michael; John, Gernot Thomas; Scheper, Thomas; Beutel, Sascha

2014-01-01

In the context of this work we evaluated a multisensory, noninvasive prototype platform for shake flask cultivations by monitoring three basic parameters (pH, pO2 and biomass). The focus lies on the evaluation of the biomass sensor based on backward light scattering. The application spectrum was expanded to four new organisms in addition to E. coli K12 and S. cerevisiae [1]. It could be shown that the sensor is appropriate for a wide range of standard microorganisms, e.g., L. zeae, K. pastoris, A. niger and CHO-K1. The biomass sensor signal could successfully be correlated and calibrated with well-known measurement methods like OD600, cell dry weight (CDW) and cell concentration. Logarithmic and Bleasdale-Nelder derived functions were adequate for data fitting. Measurements at low cell concentrations proved to be critical in terms of a high signal to noise ratio, but the integration of a custom made light shade in the shake flask improved these measurements significantly. This sensor based measurement method has a high potential to initiate a new generation of online bioprocess monitoring. Metabolic studies will particularly benefit from the multisensory data acquisition. The sensor is already used in labscale experiments for shake flask cultivations. PMID:25232914

Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

PubMed

La, Hung Manh; Sheng, Weihua

2013-04-01

In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

Technical note: Efficient online source identification algorithm for integration within a contamination event management system

NASA Astrophysics Data System (ADS)

Deuerlein, Jochen; Meyer-Harries, Lea; Guth, Nicolai

2017-07-01

Drinking water distribution networks are part of critical infrastructures and are exposed to a number of different risks. One of them is the risk of unintended or deliberate contamination of the drinking water within the pipe network. Over the past decade research has focused on the development of new sensors that are able to detect malicious substances in the network and early warning systems for contamination. In addition to the optimal placement of sensors, the automatic identification of the source of a contamination is an important component of an early warning and event management system for security enhancement of water supply networks. Many publications deal with the algorithmic development; however, only little information exists about the integration within a comprehensive real-time event detection and management system. In the following the analytical solution and the software implementation of a real-time source identification module and its integration within a web-based event management system are described. The development was part of the SAFEWATER project, which was funded under FP 7 of the European Commission.

Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Zubko, V.; Gopalan, A.

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

A highly scalable information system as extendable framework solution for medical R&D projects.

PubMed

Holzmüller-Laue, Silke; Göde, Bernd; Stoll, Regina; Thurow, Kerstin

2009-01-01

For research projects in preventive medicine a flexible information management is needed that offers a free planning and documentation of project specific examinations. The system should allow a simple, preferably automated data acquisition from several distributed sources (e.g., mobile sensors, stationary diagnostic systems, questionnaires, manual inputs) as well as an effective data management, data use and analysis. An information system fulfilling these requirements has been developed at the Center for Life Science Automation (celisca). This system combines data of multiple investigations and multiple devices and displays them on a single screen. The integration of mobile sensor systems for comfortable, location-independent capture of time-based physiological parameter and the possibility of observation of these measurements directly by this system allow new scenarios. The web-based information system presented in this paper is configurable by user interfaces. It covers medical process descriptions, operative process data visualizations, a user-friendly process data processing, modern online interfaces (data bases, web services, XML) as well as a comfortable support of extended data analysis with third-party applications.

Body area network--a key infrastructure element for patient-centered telemedicine.

PubMed

Norgall, Thomas; Schmidt, Robert; von der Grün, Thomas

2004-01-01

The Body Area Network (BAN) extends the range of existing wireless network technologies by an ultra-low range, ultra-low power network solution optimised for long-term or continuous healthcare applications. It enables wireless radio communication between several miniaturised, intelligent Body Sensor (or actor) Units (BSU) and a single Body Central Unit (BCU) worn at the human body. A separate wireless transmission link from the BCU to a network access point--using different technology--provides for online access to BAN components via usual network infrastructure. The BAN network protocol maintains dynamic ad-hoc network configuration scenarios and co-existence of multiple networks.BAN is expected to become a basic infrastructure element for electronic health services: By integrating patient-attached sensors and mobile actor units, distributed information and data processing systems, the range of medical workflow can be extended to include applications like wireless multi-parameter patient monitoring and therapy support. Beyond clinical use and professional disease management environments, private personal health assistance scenarios (without financial reimbursement by health agencies / insurance companies) enable a wide range of applications and services in future pervasive computing and networking environments.

Enhanced intelligence through optimized TCPED concepts for airborne ISR

NASA Astrophysics Data System (ADS)

Spitzer, M.; Kappes, E.; Böker, D.

2012-06-01

Current multinational operations show an increased demand for high quality actionable intelligence for different operational levels and users. In order to achieve sufficient availability, quality and reliability of information, various ISR assets are orchestrated within operational theatres. Especially airborne Intelligence, Surveillance and Reconnaissance (ISR) assets provide - due to their endurance, non-intrusiveness, robustness, wide spectrum of sensors and flexibility to mission changes - significant intelligence coverage of areas of interest. An efficient and balanced utilization of airborne ISR assets calls for advanced concepts for the entire ISR process framework including the Tasking, Collection, Processing, Exploitation and Dissemination (TCPED). Beyond this, the employment of current visualization concepts, shared information bases and information customer profiles, as well as an adequate combination of ISR sensors with different information age and dynamic (online) retasking process elements provides the optimization of interlinked TCPED processes towards higher process robustness, shorter process duration, more flexibility between ISR missions and, finally, adequate "entry points" for information requirements by operational users and commands. In addition, relevant Trade-offs of distributed and dynamic TCPED processes are examined and future trends are depicted.

Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.

PubMed

Abbaspour, Alireza; Aboutalebi, Payam; Yen, Kang K; Sargolzaei, Arman

2017-03-01

A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Distributed estimation for adaptive sensor selection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

2014-05-01

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

Remote Sensing Data Visualization, Fusion and Analysis via Giovanni

NASA Technical Reports Server (NTRS)

Leptoukh, G.; Zubko, V.; Gopalan, A.; Khayat, M.

2007-01-01

We describe Giovanni, the NASA Goddard developed online visualization and analysis tool that allows users explore various phenomena without learning remote sensing data formats and downloading voluminous data. Using MODIS aerosol data as an example, we formulate an approach to the data fusion for Giovanni to further enrich online multi-sensor remote sensing data comparison and analysis.

Source Localization in Wireless Sensor Networks with Randomly Distributed Elements under Multipath Propagation Conditions

DTIC Science & Technology

2009-03-01

IN WIRELESS SENSOR NETWORKS WITH RANDOMLY DISTRIBUTED ELEMENTS UNDER MULTIPATH PROPAGATION CONDITIONS by Georgios Tsivgoulis March 2009...COVERED Engineer’s Thesis 4. TITLE Source Localization in Wireless Sensor Networks with Randomly Distributed Elements under Multipath Propagation...the non-line-of-sight information. 15. NUMBER OF PAGES 111 14. SUBJECT TERMS Wireless Sensor Network , Direction of Arrival, DOA, Random

Evaluation of Fiber Bragg Grating and Distributed Optical Fiber Temperature Sensors

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCary, Kelly Marie

Fiber optic temperature sensors were evaluated in the High Temperature Test Lab (HTTL) to determine the accuracy of the measurements at various temperatures. A distributed temperature sensor was evaluated up to 550C and a fiber Bragg grating sensor was evaluated up to 750C. HTTL measurements indicate that there is a drift in fiber Bragg sensor over time of approximately -10C with higher accuracy at temperatures above 300C. The distributed sensor produced some bad data points at and above 500C but produced measurements with less than 2% error at increasing temperatures up to 400C

Distributed optical fibre temperature measurements in a low dose rate radiation environment based on Rayleigh backscattering

NASA Astrophysics Data System (ADS)

Faustov, A.; Gussarov, A.; Wuilpart, M.; Fotiadi, A. A.; Liokumovich, L. B.; Kotov, O. I.; Zolotovskiy, I. O.; Tomashuk, A. L.; Deschoutheete, T.; Mégret, P.

2012-04-01

On-line monitoring of environmental conditions in nuclear facilities is becoming a more and more important problem. Standard electronic sensors are not the ideal solution due to radiation sensitivity and difficulties in installation of multiple sensors. In contrast, radiation-hard optical fibres can sustain very high radiation doses and also naturally offer multi-point or distributed monitoring of external perturbations. Multiple local electro-mechanical sensors can be replaced by just one measuring fibre. At present, there are over four hundred operational nuclear power plants (NPPs) in the world 1. Operating experience has shown that ineffective control of the ageing degradation of major NPP components can threaten plant safety and also plant life. Among those elements, cables are vital components of I&C systems in NPPs. To ensure their safe operation and predict remaining life, environmental monitoring is necessary. In particular, temperature and radiation dose are considered to be the two most important parameters. The aim of this paper is to assess experimentally the feasibility of optical fibre temperature measurements in a low doserate radiation environment, using a commercially available reflectometer based on Rayleigh backscattering. Four different fibres were installed in the Sub-Pile Room of the BR2 Material testing nuclear reactor in Mol, Belgium. This place is man-accessible during the reactor shut-down, allowing easy fibre installation. When the reactor operates, the dose-rates in the room are in a range 0.005-5 Gy/h with temperatures of 40-60 °C, depending on the location. Such a surrounding is not much different to some "hot" environments in NPPs, where I&C cables are located.

Distributed fiber optic sensor-enhanced detection and prediction of shrinkage-induced delamination of ultra-high-performance concrete overlay

NASA Astrophysics Data System (ADS)

Bao, Yi; Valipour, Mahdi; Meng, Weina; Khayat, Kamal H.; Chen, Genda

2017-08-01

This study develops a delamination detection system for smart ultra-high-performance concrete (UHPC) overlays using a fully distributed fiber optic sensor. Three 450 mm (length) × 200 mm (width) × 25 mm (thickness) UHPC overlays were cast over an existing 200 mm thick concrete substrate. The initiation and propagation of delamination due to early-age shrinkage of the UHPC overlay were detected as sudden increases and their extension in spatial distribution of shrinkage-induced strains measured from the sensor based on pulse pre-pump Brillouin optical time domain analysis. The distributed sensor is demonstrated effective in detecting delamination openings from microns to hundreds of microns. A three-dimensional finite element model with experimental material properties is proposed to understand the complete delamination process measured from the distributed sensor. The model is validated using the distributed sensor data. The finite element model with cohesive elements for the overlay-substrate interface can predict the complete delamination process.

An End-to-End System to Enable Quick, Easy and Inexpensive Deployment of Hydrometeorological Stations

NASA Astrophysics Data System (ADS)

Celicourt, P.; Piasecki, M.

2014-12-01

The high cost of hydro-meteorological data acquisition, communication and publication systems along with limited qualified human resources is considered as the main reason why hydro-meteorological data collection remains a challenge especially in developing countries. Despite significant advances in sensor network technologies which gave birth to open hardware and software, low-cost (less than $50) and low-power (in the order of a few miliWatts) sensor platforms in the last two decades, sensors and sensor network deployment remains a labor-intensive, time consuming, cumbersome, and thus expensive task. These factors give rise for the need to develop a affordable, simple to deploy, scalable and self-organizing end-to-end (from sensor to publication) system suitable for deployment in such countries. The design of the envisioned system will consist of a few Sensed-And-Programmed Arduino-based sensor nodes with low-cost sensors measuring parameters relevant to hydrological processes and a Raspberry Pi micro-computer hosting the in-the-field back-end data management. This latter comprises the Python/Django model of the CUAHSI Observations Data Model (ODM) namely DjangODM backed by a PostgreSQL Database Server. We are also developing a Python-based data processing script which will be paired with the data autoloading capability of Django to populate the DjangODM database with the incoming data. To publish the data, the WOFpy (WaterOneFlow Web Services in Python) developed by the Texas Water Development Board for 'Water Data for Texas' which can produce WaterML web services from a variety of back-end database installations such as SQLite, MySQL, and PostgreSQL will be used. A step further would be the development of an appealing online visualization tool using Python statistics and analytics tools (Scipy, Numpy, Pandas) showing the spatial distribution of variables across an entire watershed as a time variant layer on top of a basemap.

On-line estimation and detection of abnormal substrate concentrations in WWTPs using a software sensor: a benchmark study.

PubMed

Benazzi, F; Gernaey, K V; Jeppsson, U; Katebi, R

2007-08-01

In this paper, a new approach for on-line monitoring and detection of abnormal readily biodegradable substrate (S(s)) and slowly biodegradable substrate (X(s)) concentrations, for example due to input of toxic loads from the sewer, or due to influent substrate shock load, is proposed. Considering that measurements of S(s) and X(s) concentrations are not available in real wastewater treatment plants, the S(s) / X(s) software sensor can activate an alarm with a response time of about 60 and 90 minutes, respectively, based on the dissolved oxygen measurement. The software sensor implementation is based on an extended Kalman filter observer and disturbances are modelled using fast Fourier transform and spectrum analyses. Three case studies are described. The first one illustrates the fast and accurate convergence of the extended Kalman filter algorithm, which is achieved in less than 2 hours. Furthermore, the difficulties of estimating X(s) when off-line analysis is not available are depicted, and the S(s) / X(s) software sensor performances when no measurements of S(s) and X(s) are available are illustrated. Estimation problems related to the death-regeneration concept of the activated sludge model no.1 and possible application of the software sensor in wastewater monitoring are discussed.

A new debris sensor based on dual excitation sources for online debris monitoring

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Tomovic, Mileta M.; Liu, Haokuo; Wang, Xingjian

2015-09-01

Mechanical systems could be severely damaged by loose debris generated through wear processes between contact surfaces. Hence, debris detection is necessary for effective fault diagnosis, life prediction, and prevention of catastrophic failures. This paper presents a new in-line debris sensor for hydraulic systems based on dual excitation sources. The proposed sensor makes magnetic lines more concentrated while at the same time improving magnetic field uniformity. As a result the sensor has higher sensitivity and improved precision. This paper develops the sensor model, discusses sensor structural features, and introduces a measurement method for debris size identification. Finally, experimental verification is presented indicating that that the sensor can effectively detect 81 μm (cube) or larger particles in 12 mm outside diameter (OD) organic glass pipe.

Fiber optic sensors; Proceedings of the Meeting, Cannes, France, November 26, 27, 1985

NASA Technical Reports Server (NTRS)

Arditty, Herve J. (Editor); Jeunhomme, Luc B. (Editor)

1986-01-01

The conference presents papers on distributed sensors and sensor networks, signal processing and detection techniques, temperature measurements, chemical sensors, and the measurement of pressure, strain, and displacements. Particular attention is given to optical fiber distributed sensors and sensor networks, tactile sensing in robotics using an optical network and Z-plane techniques, and a spontaneous Raman temperature sensor. Other topics include coherence in optical fiber gyroscopes, a high bandwidth two-phase flow void fraction fiber optic sensor, and a fiber-optic dark-field microbend sensor.

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition

PubMed Central

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-01-01

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition. PMID:28467371

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-05-03

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition.

Assessment of pollutant load emission from combined sewer overflows based on the online monitoring.

PubMed

Brzezińska, Agnieszka; Zawilski, Marek; Sakson, Grażyna

2016-09-01

Cities equipped with combined sewer systems discharge during wet weather a lot of pollutants into receiving waters by combined storm overflows (CSOs). According to the Polish legislation, CSOs should be activated no more than ten times per year, but in Lodz, most of the 18 existing CSOs operate much more frequently. To assess the pollutant load emitted by one of the existing CSOs, the sensors for measuring the concentration of total suspended solids (SOLITAX sc) and dissolved chemical oxygen demand (UVAS plus) installed in the overflow chamber as well as two flowmeters placed in the outflow sewer were used. In order to check the data from sensors, laboratory tests of combined wastewater quality were conducted simultaneously. For the analysis of the total pollutant load emitted from the overflow, the raw data was denoised using the Savitzky-Golay method. Comparing the load calculated from the analytical results to online smoothed measurements, negligible differences were found, which confirms the usefulness of applying the sensors in the combined sewer system. Online monitoring of the quantity and quality of wastewater emitted by the combined sewer overflows to water receivers, provides a considerable amount of data very useful for combined sewerage upgrading based on computer modelling, and allows for a significant reduction of laboratory analysis.

Fiber Fabry-Perot sensors for detection of partial discharges in power transformers.

PubMed

Yu, Bing; Kim, Dae Woong; Deng, Jiangdong; Xiao, Hai; Wang, Anbo

2003-06-01

A diaphragm-based interferometric fiberoptic sensor that uses a low-coherence light source was designed and tested for on-line detection of the acoustic waves generated by partial discharges inside high-voltage power transformers. The sensor uses a fused-silica diaphragm and a single-mode optical fiber encapsulated in a fused-silica glass tube to form an extrinsic Fabry-Perot interferometer, which is interrogated by low-coherence light. Test results indicate that these fiber optic acoustic sensors are capable of faithfully detecting acoustic signals propagating inside transformer oil with high sensitivity and wide bandwidth.

An integrated probe design for measuring food quality in a microwave environment

NASA Astrophysics Data System (ADS)

O'Farrell, M.; Sheridan, C.; Lewis, E.; Zhao, W. Z.; Sun, T.; Grattan, K. T. V.

2007-07-01

The work presented describes the development of a novel integrated optical sensor system for the simultaneous and online measurement of the colour and temperature of food as it cooks in a large-scale microwave and hybrid oven systems. The integrated probe contains two different sensor concepts, one to monitor temperature and based on Fibre Bragg Grating (FBG) technology and a second for meat quality, based on reflection spectroscopy in the visible wavelength range. The combination of the two sensors into a single probe requires a careful configuration of the sensor approaches in the creation of an integrated probe design.

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

PubMed Central

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; de Jesus Romero-Troncoso, Rene

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node. PMID:22163602

A field programmable gate array-based reconfigurable smart-sensor network for wireless monitoring of new generation computer numerically controlled machines.

PubMed

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; Romero-Troncoso, Rene de Jesus

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node.

A real-time spectroscopic sensor for monitoring laser welding processes.

PubMed

Sibillano, Teresa; Ancona, Antonio; Berardi, Vincenzo; Lugarà, Pietro Mario

2009-01-01

In this paper we report on the development of a sensor for real time monitoring of laser welding processes based on spectroscopic techniques. The system is based on the acquisition of the optical spectra emitted from the laser generated plasma plume and their use to implement an on-line algorithm for both the calculation of the plasma electron temperature and the analysis of the correlations between selected spectral lines. The sensor has been patented and it is currently available on the market.

Interactive display/graphics systems for remote sensor data analysis.

NASA Technical Reports Server (NTRS)

Eppler, W. G.; Loe, D. L.; Wilson, E. L.; Whitley, S. L.; Sachen, R. J.

1971-01-01

Using a color-television display system and interactive graphics equipment on-line to an IBM 360/44 computer, investigators at the Manned Spacecraft Center have developed a variety of interactive displays which aid in analyzing remote sensor data. This paper describes how such interactive displays are used to: (1) analyze data from a multispectral scanner, (2) develop automatic pattern recognition systems based on multispectral scanner measurements, and (3) analyze data from nonimaging sensors such as the infrared radiometer and microwave scatterometer.

A Theoretical Study and Numerical Simulation of a Quasi-Distributed Sensor Based on the Low-Finesse Fabry-Perot Interferometer: Frequency-Division Multiplexing.

PubMed

Guillen Bonilla, José Trinidad; Guillen Bonilla, Alex; Rodríguez Betancourtt, Verónica M; Guillen Bonilla, Héctor; Casillas Zamora, Antonio

2017-04-14

The application of the sensor optical fibers in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum was analyzed and sensor's properties were defined. Following that, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system, and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolution. Both resolutions are conceivable because the Fourier Domain Phase Analysis (FDPA) algorithm elaborates two evaluations of Bragg wavelength shift.

Looped back fiber mode for reduction of false alarm in leak detection using distributed optical fiber sensor.

PubMed

Chelliah, Pandian; Murgesan, Kasinathan; Samvel, Sosamma; Chelamchala, Babu Rao; Tammana, Jayakumar; Nagarajan, Murali; Raj, Baldev

2010-07-10

Optical-fiber-based sensors have inherent advantages, such as immunity to electromagnetic interference, compared to the conventional sensors. Distributed optical fiber sensor (DOFS) systems, such as Raman and Brillouin distributed temperature sensors are used for leak detection. The inherent noise of fiber-based systems leads to occasional false alarms. In this paper, a methodology is proposed to overcome this. This uses a looped back fiber mode in DOFS and voting logic is employed to considerably reduce the false alarm rate.

Compressive sensing-based electrostatic sensor array signal processing and exhausted abnormal debris detecting

NASA Astrophysics Data System (ADS)

Tang, Xin; Chen, Zhongsheng; Li, Yue; Yang, Yongmin

2018-05-01

When faults happen at gas path components of gas turbines, some sparsely-distributed and charged debris will be generated and released into the exhaust gas. The debris is called abnormal debris. Electrostatic sensors can detect the debris online and further indicate the faults. It is generally considered that, under a specific working condition, a more serious fault generates more and larger debris, and a piece of larger debris carries more charge. Therefore, the amount and charge of the abnormal debris are important indicators of the fault severity. However, because an electrostatic sensor can only detect the superposed effect on the electrostatic field of all the debris, it can hardly identify the amount and position of the debris. Moreover, because signals of electrostatic sensors depend on not only charge but also position of debris, and the position information is difficult to acquire, measuring debris charge accurately using the electrostatic detecting method is still a technical difficulty. To solve these problems, a hemisphere-shaped electrostatic sensors' circular array (HSESCA) is used, and an array signal processing method based on compressive sensing (CS) is proposed in this paper. To research in a theoretical framework of CS, the measurement model of the HSESCA is discretized into a sparse representation form by meshing. In this way, the amount and charge of the abnormal debris are described as a sparse vector. It is further reconstructed by constraining l1-norm when solving an underdetermined equation. In addition, a pre-processing method based on singular value decomposition and a result calibration method based on weighted-centroid algorithm are applied to ensure the accuracy of the reconstruction. The proposed method is validated by both numerical simulations and experiments. Reconstruction errors, characteristics of the results and some related factors are discussed.

Nonparametric Density Estimation Based on Self-Organizing Incremental Neural Network for Large Noisy Data.

PubMed

Nakamura, Yoshihiro; Hasegawa, Osamu

2017-01-01

With the ongoing development and expansion of communication networks and sensors, massive amounts of data are continuously generated in real time from real environments. Beforehand, prediction of a distribution underlying such data is difficult; furthermore, the data include substantial amounts of noise. These factors make it difficult to estimate probability densities. To handle these issues and massive amounts of data, we propose a nonparametric density estimator that rapidly learns data online and has high robustness. Our approach is an extension of both kernel density estimation (KDE) and a self-organizing incremental neural network (SOINN); therefore, we call our approach KDESOINN. An SOINN provides a clustering method that learns about the given data as networks of prototype of data; more specifically, an SOINN can learn the distribution underlying the given data. Using this information, KDESOINN estimates the probability density function. The results of our experiments show that KDESOINN outperforms or achieves performance comparable to the current state-of-the-art approaches in terms of robustness, learning time, and accuracy.

FPGA-based fused smart sensor for dynamic and vibration parameter extraction in industrial robot links.

PubMed

Rodriguez-Donate, Carlos; Morales-Velazquez, Luis; Osornio-Rios, Roque Alfredo; Herrera-Ruiz, Gilberto; de Jesus Romero-Troncoso, Rene

2010-01-01

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA).

FPGA-Based Fused Smart Sensor for Dynamic and Vibration Parameter Extraction in Industrial Robot Links

PubMed Central

Rodriguez-Donate, Carlos; Morales-Velazquez, Luis; Osornio-Rios, Roque Alfredo; Herrera-Ruiz, Gilberto; de Jesus Romero-Troncoso, Rene

2010-01-01

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA). PMID:22319345

Incrementally learning objects by touch: online discriminative and generative models for tactile-based recognition.

PubMed

Soh, Harold; Demiris, Yiannis

2014-01-01

Human beings not only possess the remarkable ability to distinguish objects through tactile feedback but are further able to improve upon recognition competence through experience. In this work, we explore tactile-based object recognition with learners capable of incremental learning. Using the sparse online infinite Echo-State Gaussian process (OIESGP), we propose and compare two novel discriminative and generative tactile learners that produce probability distributions over objects during object grasping/palpation. To enable iterative improvement, our online methods incorporate training samples as they become available. We also describe incremental unsupervised learning mechanisms, based on novelty scores and extreme value theory, when teacher labels are not available. We present experimental results for both supervised and unsupervised learning tasks using the iCub humanoid, with tactile sensors on its five-fingered anthropomorphic hand, and 10 different object classes. Our classifiers perform comparably to state-of-the-art methods (C4.5 and SVM classifiers) and findings indicate that tactile signals are highly relevant for making accurate object classifications. We also show that accurate "early" classifications are possible using only 20-30 percent of the grasp sequence. For unsupervised learning, our methods generate high quality clusterings relative to the widely-used sequential k-means and self-organising map (SOM), and we present analyses into the differences between the approaches.

Multiple UAV Cooperation for Wildfire Monitoring

NASA Astrophysics Data System (ADS)

Lin, Zhongjie

Wildfires have been a major factor in the development and management of the world's forest. An accurate assessment of wildfire status is imperative for fire management. This thesis is dedicated to the topic of utilizing multiple unmanned aerial vehicles (UAVs) to cooperatively monitor a large-scale wildfire. This is achieved through wildfire spreading situation estimation based on on-line measurements and wise cooperation strategy to ensure efficiency. First, based on the understanding of the physical characteristics of the wildfire propagation behavior, a wildfire model and a Kalman filter-based method are proposed to estimate the wildfire rate of spread and the fire front contour profile. With the enormous on-line measurements from on-board sensors of UAVs, the proposed method allows a wildfire monitoring mission to benefit from on-line information updating, increased flexibility, and accurate estimation. An independent wildfire simulator is utilized to verify the effectiveness of the proposed method. Second, based on the filter analysis, wildfire spreading situation and vehicle dynamics, the influence of different cooperation strategies of UAVs to the overall mission performance is studied. The multi-UAV cooperation problem is formulated in a distributed network. A consensus-based method is proposed to help address the problem. The optimal cooperation strategy of UAVs is obtained through mathematical analysis. The derived optimal cooperation strategy is then verified in an independent fire simulation environment to verify its effectiveness.

FPGA-Based Smart Sensor for Online Displacement Measurements Using a Heterodyne Interferometer

PubMed Central

Vera-Salas, Luis Alberto; Moreno-Tapia, Sandra Veronica; Garcia-Perez, Arturo; de Jesus Romero-Troncoso, Rene; Osornio-Rios, Roque Alfredo; Serroukh, Ibrahim; Cabal-Yepez, Eduardo

2011-01-01

The measurement of small displacements on the nanometric scale demands metrological systems of high accuracy and precision. In this context, interferometer-based displacement measurements have become the main tools used for traceable dimensional metrology. The different industrial applications in which small displacement measurements are employed requires the use of online measurements, high speed processes, open architecture control systems, as well as good adaptability to specific process conditions. The main contribution of this work is the development of a smart sensor for large displacement measurement based on phase measurement which achieves high accuracy and resolution, designed to be used with a commercial heterodyne interferometer. The system is based on a low-cost Field Programmable Gate Array (FPGA) allowing the integration of several functions in a single portable device. This system is optimal for high speed applications where online measurement is needed and the reconfigurability feature allows the addition of different modules for error compensation, as might be required by a specific application. PMID:22164040

Temperature Resistant Fiber Bragg Gratings for On-Line and Structural Health Monitoring of the Next-Generation of Nuclear Reactors.

PubMed

Laffont, Guillaume; Cotillard, Romain; Roussel, Nicolas; Desmarchelier, Rudy; Rougeault, Stéphane

2018-06-02

The harsh environment associated with the next generation of nuclear reactors is a great challenge facing all new sensing technologies to be deployed for on-line monitoring purposes and for the implantation of SHM methods. Sensors able to resist sustained periods at very high temperatures continuously as is the case within sodium-cooled fast reactors require specific developments and evaluations. Among the diversity of optical fiber sensing technologies, temperature resistant fiber Bragg gratings are increasingly being considered for the instrumentation of future nuclear power plants, especially for components exposed to high temperature and high radiation levels. Research programs are supporting the developments of optical fiber sensors under mixed high temperature and radiative environments leading to significant increase in term of maturity. This paper details the development of temperature-resistant wavelength-multiplexed fiber Bragg gratings for temperature and strain measurements and their characterization for on-line monitoring into the liquid sodium used as a coolant for the next generation of fast reactors.

Temperature measurement and damage detection in concrete beams exposed to fire using PPP-BOTDA based fiber optic sensors

NASA Astrophysics Data System (ADS)

Bao, Yi; Hoehler, Matthew S.; Smith, Christopher M.; Bundy, Matthew; Chen, Genda

2017-10-01

In this study, Brillouin scattering-based distributed fiber optic sensor is implemented to measure temperature distributions and detect cracks in concrete structures subjected to fire for the first time. A telecommunication-grade optical fiber is characterized as a high temperature sensor with pulse pre-pump Brillouin optical time domain analysis (PPP-BODTA), and implemented to measure spatially-distributed temperatures in reinforced concrete beams in fire. Four beams were tested to failure in a natural gas fueled compartment fire, each instrumented with one fused silica, single-mode optical fiber as a distributed sensor and four thermocouples. Prior to concrete cracking, the distributed temperature was validated at locations of the thermocouples by a relative difference of less than 9%. The cracks in concrete can be identified as sharp peaks in the temperature distribution since the cracks are locally filled with hot air. Concrete cracking did not affect the sensitivity of the distributed sensor but concrete spalling broke the optical fiber loop required for PPP-BOTDA measurements.

Ion-selective optical sensor for continuous on-line monitoring of dialysate sodium during dialysis

NASA Astrophysics Data System (ADS)

Sharma, Manoj K.; Frijns, Arjan J. H.; Mandamparambil, Rajesh; Kooman, Jeroen P.; Smeulders, David M. J.

2017-02-01

Patients with end stage renal disease are dependent on dialysis. In most outpatient centers, the dialysate is prepared with a fixed electrolyte concentration without taking into account the inter-individual differences of essential electrolytes (sodium, potassium and calcium). This one-size fits all approach can lead to acute and chronic cardiovascular complications in dialysis patients. On-line monitoring of these essential electrolytes is an important physiological step towards patient specific dialysate leading to individualized treatment. Currently, changes in electrolyte concentrations are indirectly measured by conductivity measurements, which are not ion- specific. In this paper, we present a novel optical sensor for on-line monitoring of sodium concentrations in dialysate. This sensor is ion-specific and can detect up to a single ion. The working principle is based on the selective fluorescence quenching of photo-induced electron transfer (PET) molecules. The PET molecules when complexed with sodium ions start fluorescing upon laser excitation. The emission intensity is directly correlated to the sodium concentration. To prove the working principle, a micro-optofluidic device has been fabricated in polydimethylsiloxane (PDMS) with integrated optical fibers for fluorescence light collection. The PET molecules are covalently grafted in the PDMS microchannel for continuous monitoring of the sodium dialysate concentrations. The experimental setup consists of a laser module (λ=450nm) operating at 4.5mW, a syringe pump to precisely control the sample flow and a spectrometer for fluorescence collection. The performance of the sensor has been evaluated for sodium ions ranging from 0-50mM. A clear signal and good response time was observed.

Development and implementation of an automatic integration system for fibre optic sensors in the braiding process with the objective of online-monitoring of composite structures

NASA Astrophysics Data System (ADS)

Hufenbach, W.; Gude, M.; Czulak, A.; Kretschmann, Martin

2014-04-01

Increasing economic, political and ecological pressure leads to steadily rising percentage of modern processing and manufacturing processes for fibre reinforced polymers in industrial batch production. Component weights beneath a level achievable by classic construction materials, which lead to a reduced energy and cost balance during product lifetime, justify the higher fabrication costs. However, complex quality control and failure prediction slow down the substitution by composite materials. High-resolution fibre-optic sensors (FOS), due their low diameter, high measuring point density and simple handling, show a high applicability potential for an automated sensor-integration in manufacturing processes, and therefore the online monitoring of composite products manufactured in industrial scale. Integrated sensors can be used to monitor manufacturing processes, part tests as well as the component structure during product life cycle, which simplifies allows quality control during production and the optimization of single manufacturing processes.[1;2] Furthermore, detailed failure analyses lead to a enhanced understanding of failure processes appearing in composite materials. This leads to a lower wastrel number and products of a higher value and longer product life cycle, whereby costs, material and energy are saved. This work shows an automation approach for FOS-integration in the braiding process. For that purpose a braiding wheel has been supplemented with an appliance for automatic sensor application, which has been used to manufacture preforms of high-pressure composite vessels with FOS-networks integrated between the fibre layers. All following manufacturing processes (vacuum infiltration, curing) and component tests (quasi-static pressure test, programmed delamination) were monitored with the help of the integrated sensor networks. Keywords: SHM, high-pressure composite vessel, braiding, automated sensor integration, pressure test, quality control, optic-fibre sensors, Rayleigh, Luna Technologies

A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-07-24

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04-0.24 m/s; height RMSE was in the range 5-68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions.

An adaptive distributed data aggregation based on RCPC for wireless sensor networks

NASA Astrophysics Data System (ADS)

Hua, Guogang; Chen, Chang Wen

2006-05-01

One of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks

Network Computing for Distributed Underwater Acoustic Sensors

DTIC Science & Technology

2014-03-31

underwater sensor network with mobility. In preparation. [3] EvoLogics (2013), Underwater Acoustic Modems, (Product Information Guide... Wireless Communications, 9(9), 2934–2944. [21] Pompili, D. and Akyildiz, I. (2010), A multimedia cross-layer protocol for underwater acoustic sensor networks ... Network Computing for Distributed Underwater Acoustic Sensors M. Barbeau E. Kranakis

On-line defect detection of aluminum coating using fiber optic sensor

NASA Astrophysics Data System (ADS)

Patil, Supriya S.; Shaligram, A. D.

2015-03-01

Aluminum metallization using the sprayed coating for exhaust mild steel (MS) pipes of tractors is a standard practice for avoiding rusting. Patches of thin metal coats are prone to rusting and are thus considered as defects in the surface coating. This paper reports a novel configuration of the fiber optic sensor for on-line checking the aluminum metallization uniformity and hence for defect detection. An optimally chosen high bright 440 nm BLUE LED (light-emitting diode) launches light into a transmitting fiber inclined at the angle of 60° to the surface under inspection placed adequately. The reflected light is transported by a receiving fiber to a blue enhanced photo detector. The metallization thickness on the coated surface results in visually observable variation in the gray shades. The coated pipe is spirally inspected by a combination of linear and rotary motions. The sensor output is the signal conditioned and monitored with RISHUBH DAS. Experimental results show the good repeatability in the defect detection and coating non-uniformity measurement.

Artificial Fruit: Postharvest Online Monitoring of Agricultural Food by Measuring Humidity and Temperature

NASA Astrophysics Data System (ADS)

Hübert, T.; Lang, C.

2012-09-01

An online monitoring of environmental and inherent product parameters is required during transportation and storage of fruit and vegetables to avoid quality degradation and spoilage. The control of transpiration losses is suggested as an indicator for fruit freshness by humidity measurements. For that purpose, an electronic sensor is surrounded by a wet porous fiber material which is in contact with the outer atmosphere. Transpiration reduces the water content of the porous material and thus also the internal water activity. The sensor system, known as "artificial fruit," measures the relative humidity and temperature inside the wet material. Humidity and temperature data are collected and transmitted on demand by a miniaturized radio communication unit. The decrease in the measured relative humidity has been calibrated against the mass loss of tomatoes under different external influencing parameters such as temperature, humidity, and air flow. Current battery life allows the sensor system, embedded in a fruit crate, to transmit data on transpiration losses via radio transmission for up to two weeks.

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID

PubMed Central

Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

2018-01-01

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm–neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS. PMID:29671822

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID.

PubMed

Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

2018-04-19

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.

On-line Ammonia Sensor and Invisible Security Ink by Fluorescent Zwitterionic Spirocyclic Meisenheimer Complex

PubMed Central

Das, Tanmay; Pramanik, Apurba; Haldar, Debasish

2017-01-01

Ammonia is not only a highly important gas for civilization but also contribute significantly for climate change and human health hazard. Highly sensitive ammonia sensor has been developed from a fluorescent zwitterionic spirocyclic Meisenheimer complex. Moreover, formation of this Meisenheimer complex can also be utilized for selective as well as naked eye instant detection of nitro aromatic explosive picric acid. The presence of a quaternary nitrogen atom directly attached to the spiro carbon is the unique feature of this Meisenheimer complex. This excellent photoluminescent (PL) Meisenheimer complex has two distinct stimuli responsive sites. One is sensitive towards acid while the other one is towards the base. These two positions can be modulated by adding one equivalent acid and one equivalent base to result two new products which are non fluorescent. One of these two non fluorescent species was found very exciting because of its UV/Vis transparency. Utilizing this concept we have fabricated an on-line sensor for measuring ammonia in dry or humid and condensing sewer air. The sensor was robust against ambient temperature and humidity variation. We have also developed an invisible ink from this Meisenheimer complex, with potential application for security purpose. PMID:28091542

On-line Ammonia Sensor and Invisible Security Ink by Fluorescent Zwitterionic Spirocyclic Meisenheimer Complex.

PubMed

Das, Tanmay; Pramanik, Apurba; Haldar, Debasish

2017-01-16

Ammonia is not only a highly important gas for civilization but also contribute significantly for climate change and human health hazard. Highly sensitive ammonia sensor has been developed from a fluorescent zwitterionic spirocyclic Meisenheimer complex. Moreover, formation of this Meisenheimer complex can also be utilized for selective as well as naked eye instant detection of nitro aromatic explosive picric acid. The presence of a quaternary nitrogen atom directly attached to the spiro carbon is the unique feature of this Meisenheimer complex. This excellent photoluminescent (PL) Meisenheimer complex has two distinct stimuli responsive sites. One is sensitive towards acid while the other one is towards the base. These two positions can be modulated by adding one equivalent acid and one equivalent base to result two new products which are non fluorescent. One of these two non fluorescent species was found very exciting because of its UV/Vis transparency. Utilizing this concept we have fabricated an on-line sensor for measuring ammonia in dry or humid and condensing sewer air. The sensor was robust against ambient temperature and humidity variation. We have also developed an invisible ink from this Meisenheimer complex, with potential application for security purpose.

Vehicle dynamic prediction systems with on-line identification of vehicle parameters and road conditions.

PubMed

Hsu, Ling-Yuan; Chen, Tsung-Lin

2012-11-13

This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event.

On-line Ammonia Sensor and Invisible Security Ink by Fluorescent Zwitterionic Spirocyclic Meisenheimer Complex

NASA Astrophysics Data System (ADS)

Das, Tanmay; Pramanik, Apurba; Haldar, Debasish

2017-01-01

Ammonia is not only a highly important gas for civilization but also contribute significantly for climate change and human health hazard. Highly sensitive ammonia sensor has been developed from a fluorescent zwitterionic spirocyclic Meisenheimer complex. Moreover, formation of this Meisenheimer complex can also be utilized for selective as well as naked eye instant detection of nitro aromatic explosive picric acid. The presence of a quaternary nitrogen atom directly attached to the spiro carbon is the unique feature of this Meisenheimer complex. This excellent photoluminescent (PL) Meisenheimer complex has two distinct stimuli responsive sites. One is sensitive towards acid while the other one is towards the base. These two positions can be modulated by adding one equivalent acid and one equivalent base to result two new products which are non fluorescent. One of these two non fluorescent species was found very exciting because of its UV/Vis transparency. Utilizing this concept we have fabricated an on-line sensor for measuring ammonia in dry or humid and condensing sewer air. The sensor was robust against ambient temperature and humidity variation. We have also developed an invisible ink from this Meisenheimer complex, with potential application for security purpose.

Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

PubMed Central

Hsu, Ling-Yuan; Chen, Tsung-Lin

2012-01-01

This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event. PMID:23202231

Spectrum online-tunable Mach-Zehnder interferometer based on step-like tapers and its refractive index sensing characteristics

NASA Astrophysics Data System (ADS)

Zhao, Yong; Chen, Mao-qing; Xia, Feng; Hu, Hai-feng

2017-11-01

A novel refractive index (RI) sensor based on an asymmetrical Mach-Zehnder interferometer (MZI) with two different step-like tapers is proposed. The step-like taper is fabricated by fusion splicing two half tapers with an appropriate offset. By further applying offset and discharging to the last fabricated step-like taper of MZI, influence of taper parameters on interference spectrum is investigated using only one device. This simple technique provides an on-line method to sweep parameters of step-like tapers and speeds up the optimization process of interference spectrum, meanwhile. In RI sensing experiment, the sensor has a high sensitivity of -185.79 nm/RIU (refractive index unit) in the RI range of 1.3333-1.3673.

Online Learners’ Reading Ability Detection Based on Eye-Tracking Sensors

PubMed Central

Zhan, Zehui; Zhang, Lei; Mei, Hu; Fong, Patrick S. W.

2016-01-01

The detection of university online learners’ reading ability is generally problematic and time-consuming. Thus the eye-tracking sensors have been employed in this study, to record temporal and spatial human eye movements. Learners’ pupils, blinks, fixation, saccade, and regression are recognized as primary indicators for detecting reading abilities. A computational model is established according to the empirical eye-tracking data, and applying the multi-feature regularization machine learning mechanism based on a Low-rank Constraint. The model presents good generalization ability with an error of only 4.9% when randomly running 100 times. It has obvious advantages in saving time and improving precision, with only 20 min of testing required for prediction of an individual learner’s reading ability. PMID:27626418

A Theoretical Study and Numerical Simulation of a Quasi-Distributed Sensor Based on the Low-Finesse Fabry-Perot Interferometer: Frequency-Division Multiplexing

PubMed Central

Guillen Bonilla, José Trinidad; Guillen Bonilla, Alex; Rodríguez Betancourtt, Verónica M.; Guillen Bonilla, Héctor; Casillas Zamora, Antonio

2017-01-01

The application of the sensor optical fibers in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum was analyzed and sensor’s properties were defined. Following that, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system, and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolution. Both resolutions are conceivable because the Fourier Domain Phase Analysis (FDPA) algorithm elaborates two evaluations of Bragg wavelength shift. PMID:28420083

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device

PubMed Central

He, Xiang; Aloi, Daniel N.; Li, Jia

2015-01-01

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.

PubMed

He, Xiang; Aloi, Daniel N; Li, Jia

2015-12-14

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.

Distributed Localization of Active Transmitters in a Wireless Sensor Network

DTIC Science & Technology

2012-03-01

Distributed Localization of Active Transmitters in a Wireless Sensor Network THESIS Oba L. Vincent, 2nd Lieutenant, USAF AFIT/GE/ENG/12-41 DEPARTMENT...protection in the United States. AFIT/GE/ENG/12-41 Distributed Localization of Active Transmitters in a Wireless Sensor Network THESIS Presented to the...Transmitters in a Wireless Sensor Network Oba L. Vincent, B.S.E.E. 2nd Lieutenant, USAF Approved: /signed/ 29 Feb 2012 Maj. Mark D. Silvius, Ph.D. (Chairman

Managed traffic evacuation using distributed sensor processing

NASA Astrophysics Data System (ADS)

Ramuhalli, Pradeep; Biswas, Subir

2005-05-01

This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.

Distributed sensor management for space situational awareness via a negotiation game

NASA Astrophysics Data System (ADS)

Jia, Bin; Shen, Dan; Pham, Khanh; Blasch, Erik; Chen, Genshe

2015-05-01

Space situational awareness (SSA) is critical to many space missions serving weather analysis, communications, and navigation. However, the number of sensors used in space situational awareness is limited which hinders collision avoidance prediction, debris assessment, and efficient routing. Hence, it is critical to use such sensor resources efficiently. In addition, it is desired to develop the SSA sensor management algorithm in a distributed manner. In this paper, a distributed sensor management approach using the negotiation game (NG-DSM) is proposed for the SSA. Specifically, the proposed negotiation game is played by each sensor and its neighboring sensors. The bargaining strategies are developed for each sensor based on negotiating for accurately tracking desired targets (e.g., satellite, debris, etc.) . The proposed NG-DSM method is tested in a scenario which includes eight space objects and three different sensor modalities which include a space based optical sensor, a ground radar, or a ground Electro-Optic sensor. The geometric relation between the sensor, the Sun, and the space object is also considered. The simulation results demonstrate the effectiveness of the proposed NG-DSM sensor management methods, which facilitates an application of multiple-sensor multiple-target tracking for space situational awareness.

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

NASA Technical Reports Server (NTRS)

Lo, C. F.; Wu, K.; Whitehead, B. A.

1993-01-01

The statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.

Application of a genetically encoded biosensor for live cell imaging of L-valine production in pyruvate dehydrogenase complex-deficient Corynebacterium glutamicum strains.

PubMed

Mustafi, Nurije; Grünberger, Alexander; Mahr, Regina; Helfrich, Stefan; Nöh, Katharina; Blombach, Bastian; Kohlheyer, Dietrich; Frunzke, Julia

2014-01-01

The majority of biotechnologically relevant metabolites do not impart a conspicuous phenotype to the producing cell. Consequently, the analysis of microbial metabolite production is still dominated by bulk techniques, which may obscure significant variation at the single-cell level. In this study, we have applied the recently developed Lrp-biosensor for monitoring of amino acid production in single cells of gradually engineered L-valine producing Corynebacterium glutamicum strains based on the pyruvate dehydrogenase complex-deficient (PDHC) strain C. glutamicum ΔaceE. Online monitoring of the sensor output (eYFP fluorescence) during batch cultivation proved the sensor's suitability for visualizing different production levels. In the following, we conducted live cell imaging studies on C. glutamicum sensor strains using microfluidic chip devices. As expected, the sensor output was higher in microcolonies of high-yield producers in comparison to the basic strain C. glutamicum ΔaceE. Microfluidic cultivation in minimal medium revealed a typical Gaussian distribution of single cell fluorescence during the production phase. Remarkably, low amounts of complex nutrients completely changed the observed phenotypic pattern of all strains, resulting in a phenotypic split of the population. Whereas some cells stopped growing and initiated L-valine production, others continued to grow or showed a delayed transition to production. Depending on the cultivation conditions, a considerable fraction of non-fluorescent cells was observed, suggesting a loss of metabolic activity. These studies demonstrate that genetically encoded biosensors are a valuable tool for monitoring single cell productivity and to study the phenotypic pattern of microbial production strains.

Mapping planetary caves with an autonomous, heterogeneous robot team

NASA Astrophysics Data System (ADS)

Husain, Ammar; Jones, Heather; Kannan, Balajee; Wong, Uland; Pimentel, Tiago; Tang, Sarah; Daftry, Shreyansh; Huber, Steven; Whittaker, William L.

Caves on other planetary bodies offer sheltered habitat for future human explorers and numerous clues to a planet's past for scientists. While recent orbital imagery provides exciting new details about cave entrances on the Moon and Mars, the interiors of these caves are still unknown and not observable from orbit. Multi-robot teams offer unique solutions for exploration and modeling subsurface voids during precursor missions. Robot teams that are diverse in terms of size, mobility, sensing, and capability can provide great advantages, but this diversity, coupled with inherently distinct low-level behavior architectures, makes coordination a challenge. This paper presents a framework that consists of an autonomous frontier and capability-based task generator, a distributed market-based strategy for coordinating and allocating tasks to the different team members, and a communication paradigm for seamless interaction between the different robots in the system. Robots have different sensors, (in the representative robot team used for testing: 2D mapping sensors, 3D modeling sensors, or no exteroceptive sensors), and varying levels of mobility. Tasks are generated to explore, model, and take science samples. Based on an individual robot's capability and associated cost for executing a generated task, a robot is autonomously selected for task execution. The robots create coarse online maps and store collected data for high resolution offline modeling. The coordination approach has been field tested at a mock cave site with highly-unstructured natural terrain, as well as an outdoor patio area. Initial results are promising for applicability of the proposed multi-robot framework to exploration and modeling of planetary caves.

Application of a Genetically Encoded Biosensor for Live Cell Imaging of L-Valine Production in Pyruvate Dehydrogenase Complex-Deficient Corynebacterium glutamicum Strains

PubMed Central

Mahr, Regina; Helfrich, Stefan; Nöh, Katharina; Blombach, Bastian; Kohlheyer, Dietrich; Frunzke, Julia

2014-01-01

The majority of biotechnologically relevant metabolites do not impart a conspicuous phenotype to the producing cell. Consequently, the analysis of microbial metabolite production is still dominated by bulk techniques, which may obscure significant variation at the single-cell level. In this study, we have applied the recently developed Lrp-biosensor for monitoring of amino acid production in single cells of gradually engineered L-valine producing Corynebacterium glutamicum strains based on the pyruvate dehydrogenase complex-deficient (PDHC) strain C. glutamicum ΔaceE. Online monitoring of the sensor output (eYFP fluorescence) during batch cultivation proved the sensor's suitability for visualizing different production levels. In the following, we conducted live cell imaging studies on C. glutamicum sensor strains using microfluidic chip devices. As expected, the sensor output was higher in microcolonies of high-yield producers in comparison to the basic strain C. glutamicum ΔaceE. Microfluidic cultivation in minimal medium revealed a typical Gaussian distribution of single cell fluorescence during the production phase. Remarkably, low amounts of complex nutrients completely changed the observed phenotypic pattern of all strains, resulting in a phenotypic split of the population. Whereas some cells stopped growing and initiated L-valine production, others continued to grow or showed a delayed transition to production. Depending on the cultivation conditions, a considerable fraction of non-fluorescent cells was observed, suggesting a loss of metabolic activity. These studies demonstrate that genetically encoded biosensors are a valuable tool for monitoring single cell productivity and to study the phenotypic pattern of microbial production strains. PMID:24465669

System approach to distributed sensor management

NASA Astrophysics Data System (ADS)

Mayott, Gregory; Miller, Gordon; Harrell, John; Hepp, Jared; Self, Mid

2010-04-01

Since 2003, the US Army's RDECOM CERDEC Night Vision Electronic Sensor Directorate (NVESD) has been developing a distributed Sensor Management System (SMS) that utilizes a framework which demonstrates application layer, net-centric sensor management. The core principles of the design support distributed and dynamic discovery of sensing devices and processes through a multi-layered implementation. This results in a sensor management layer that acts as a System with defined interfaces for which the characteristics, parameters, and behaviors can be described. Within the framework, the definition of a protocol is required to establish the rules for how distributed sensors should operate. The protocol defines the behaviors, capabilities, and message structures needed to operate within the functional design boundaries. The protocol definition addresses the requirements for a device (sensors or processes) to dynamically join or leave a sensor network, dynamically describe device control and data capabilities, and allow dynamic addressing of publish and subscribe functionality. The message structure is a multi-tiered definition that identifies standard, extended, and payload representations that are specifically designed to accommodate the need for standard representations of common functions, while supporting the need for feature-based functions that are typically vendor specific. The dynamic qualities of the protocol enable a User GUI application the flexibility of mapping widget-level controls to each device based on reported capabilities in real-time. The SMS approach is designed to accommodate scalability and flexibility within a defined architecture. The distributed sensor management framework and its application to a tactical sensor network will be described in this paper.

Data center thermal management

DOEpatents

Hamann, Hendrik F.; Li, Hongfei

2016-02-09

Historical high-spatial-resolution temperature data and dynamic temperature sensor measurement data may be used to predict temperature. A first formulation may be derived based on the historical high-spatial-resolution temperature data for determining a temperature at any point in 3-dimensional space. The dynamic temperature sensor measurement data may be calibrated based on the historical high-spatial-resolution temperature data at a corresponding historical time. Sensor temperature data at a plurality of sensor locations may be predicted for a future time based on the calibrated dynamic temperature sensor measurement data. A three-dimensional temperature spatial distribution associated with the future time may be generated based on the forecasted sensor temperature data and the first formulation. The three-dimensional temperature spatial distribution associated with the future time may be projected to a two-dimensional temperature distribution, and temperature in the future time for a selected space location may be forecasted dynamically based on said two-dimensional temperature distribution.

Diagnosis of Insulation Condition of MV Switchgears by Application of Different Partial Discharge Measuring Methods and Sensors

PubMed Central

2018-01-01

Partial discharges (PD) measurement provides valuable information for the condition assessment of the insulation status of high-voltage (HV) electrical installations. During the last three decades, several PD sensors and measuring techniques have been developed to perform accurate diagnostics when PD measurements are carried out on-site and on-line. For utilities, the most attractive characteristics of on-line measurements are that once the sensors are installed in the grid, the electrical service is uninterrupted and that electrical systems are tested in real operating conditions. In medium-voltage (MV) and HV installations, one of the critical points where an insulation defect can occur is inside metal-clad switchgears (including the cable terminals connected to them). Thus, this kind of equipment is increasingly being monitored to carry out proper maintenance based on their condition. This paper presents a study concerning the application of different electromagnetic measuring techniques (compliant with IEC 62478 and IEC 60270 standards), together with the use of suitable sensors, which enable the evaluation of the insulation condition mainly in MV switchgears. The main scope is to give a general overview about appropriate types of electromagnetic measuring methods and sensors to be applied, while considering the level of detail and accuracy in the diagnosis and the particular fail-save requirements of the electrical installations where the switchgears are located. PMID:29495601

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.

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

An Innovative Optical Sensor for the Online Monitoring and Control of Biomass Concentration in a Membrane Bioreactor System for Lactic Acid Production

PubMed Central

Fan, Rong; Ebrahimi, Mehrdad; Quitmann, Hendrich; Aden, Matthias; Czermak, Peter

2016-01-01

Accurate real-time process control is necessary to increase process efficiency, and optical sensors offer a competitive solution because they provide diverse system information in a noninvasive manner. We used an innovative scattered light sensor for the online monitoring of biomass during lactic acid production in a membrane bioreactor system because biomass determines productivity in this type of process. The upper limit of the measurement range in fermentation broth containing Bacillus coagulans was ~2.2 g·L−1. The specific cell growth rate (µ) during the exponential phase was calculated using data representing the linear range (cell density ≤ 0.5 g·L−1). The results were consistently and reproducibly more accurate than offline measurements of optical density and cell dry weight, because more data were gathered in real-time over a shorter duration. Furthermore, µmax was measured under different filtration conditions (transmembrane pressure 0.3–1.2 bar, crossflow velocity 0.5–1.5 m·s−1), showing that energy input had no significant impact on cell growth. Cell density was monitored using the sensor during filtration and was maintained at a constant level by feeding with glucose according to the fermentation kinetics. Our novel sensor is therefore suitable for integration into control strategies for continuous fermentation in membrane bioreactor systems. PMID:27007380

Online monitoring of dynamic tip clearance of turbine blades in high temperature environments

NASA Astrophysics Data System (ADS)

Han, Yu; Zhong, Chong; Zhu, Xiaoliang; Zhe, Jiang

2018-04-01

Minimized tip clearance reduces the gas leakage over turbine blade tips and improves the thrust and efficiency of turbomachinery. An accurate tip clearance sensor, measuring the dynamic clearances between blade tips and the turbine case, is a critical component for tip clearance control. This paper presents a robust inductive tip clearance sensor capable of monitoring dynamic tip clearances of turbine machines in high-temperature environments and at high rotational speeds. The sensor can also self-sense the temperature at a blade tip in situ such that temperature effect on tip clearance measurement can be estimated and compensated. To evaluate the sensor’s performance, the sensor was tested for measuring the tip clearances of turbine blades under various working temperatures ranging from 700 K to 1300 K and at turbine rotational speeds ranging from 3000 to 10 000 rpm. The blade tip clearance was varied from 50 to 2000 µm. The experiment results proved that the sensor can accurately measure the blade tip clearances with a temporal resolution of 10 µm. The capability of accurately measuring the tip clearances at high temperatures (~1300 K) and high turbine rotation speeds (~30 000 rpm), along with its compact size, makes it promising for online monitoring and active control of blade tip clearances of high-temperature turbomachinery.

Nanotechnology Propellant Health Monitoring Sensors; Success Through Multi-Stakeholder Interests

DTIC Science & Technology

2014-11-01

Passive AgeAlert sensors integrate well with passive (no battery!) RFID technology: • RFID reader provides rf energy to read tag providing tag...be added • Reader access to secure server means real time updates Propellant aging sensor Shock sensor Passive RFID tag RFID reader Polymer Aging...Aging Concepts, Inc., Distribution A: Approved for Public Release; Distribution Unlimited Integration of AgeAlert Sensors and Passive RFID 12

A Research on Low Modulus Distributed Fiber Optical Sensor for Pavement Material Strain Monitoring

PubMed Central

Meng, Lingjian; Wang, Linbing; Hou, Yue; Yan, Guannan

2017-01-01

The accumulated irreversible deformation in pavement under repeated vehicle loadings will cause fatigue failure of asphalt concrete. It is necessary to monitor the mechanical response of pavement under load by using sensors. Previous studies have limitations in modulus accommodation between the sensor and asphalt pavement, and it is difficult to achieve the distributed monitoring goal. To solve these problems, a new type of low modulus distributed optical fiber sensor (DOFS) for asphalt pavement strain monitoring is fabricated. Laboratory experiments have proved the applicability and accuracy of the newly-designed sensor. This paper presents the results of the development. PMID:29048393

Cross-coherent vector sensor processing for spatially distributed glider networks.

PubMed

Nichols, Brendan; Sabra, Karim G

2015-09-01

Autonomous underwater gliders fitted with vector sensors can be used as a spatially distributed sensor array to passively locate underwater sources. However, to date, the positional accuracy required for robust array processing (especially coherent processing) is not achievable using dead-reckoning while the gliders remain submerged. To obtain such accuracy, the gliders can be temporarily surfaced to allow for global positioning system contact, but the acoustically active sea surface introduces locally additional sensor noise. This letter demonstrates that cross-coherent array processing, which inherently mitigates the effects of local noise, outperforms traditional incoherent processing source localization methods for this spatially distributed vector sensor network.

A Research on Low Modulus Distributed Fiber Optical Sensor for Pavement Material Strain Monitoring.

PubMed

Meng, Lingjian; Wang, Linbing; Hou, Yue; Yan, Guannan

2017-10-19

The accumulated irreversible deformation in pavement under repeated vehicle loadings will cause fatigue failure of asphalt concrete. It is necessary to monitor the mechanical response of pavement under load by using sensors. Previous studies have limitations in modulus accommodation between the sensor and asphalt pavement, and it is difficult to achieve the distributed monitoring goal. To solve these problems, a new type of low modulus distributed optical fiber sensor (DOFS) for asphalt pavement strain monitoring is fabricated. Laboratory experiments have proved the applicability and accuracy of the newly-designed sensor. This paper presents the results of the development.

An Optical Fibre Depth (Pressure) Sensor for Remote Operated Vehicles in Underwater Applications

PubMed Central

Duraibabu, Dinesh Babu; Poeggel, Sven; Omerdic, Edin; Capocci, Romano; Lewis, Elfed; Newe, Thomas; Leen, Gabriel; Toal, Daniel; Dooly, Gerard

2017-01-01

A miniature sensor for accurate measurement of pressure (depth) with temperature compensation in the ocean environment is described. The sensor is based on an optical fibre Extrinsic Fabry-Perot interferometer (EFPI) combined with a Fibre Bragg Grating (FBG). The EFPI provides pressure measurements while the Fibre Bragg Grating (FBG) provides temperature measurements. The sensor is mechanically robust, corrosion-resistant and suitable for use in underwater applications. The combined pressure and temperature sensor system was mounted on-board a mini remotely operated underwater vehicle (ROV) in order to monitor the pressure changes at various depths. The reflected optical spectrum from the sensor was monitored online and a pressure or temperature change caused a corresponding observable shift in the received optical spectrum. The sensor exhibited excellent stability when measured over a 2 h period underwater and its performance is compared with a commercially available reference sensor also mounted on the ROV. The measurements illustrates that the EFPI/FBG sensor is more accurate for depth measurements (depth of ~0.020 m). PMID:28218727

Atmospheric Composition Data and Information Services Center (ACDISC)

NASA Technical Reports Server (NTRS)

Kempler, S.

2005-01-01

NASA's GSFC Earth Sciences (GES) Data and Information and Data Services Center (DISC) manages the archive, distribution and data access for atmospheric composition data from AURA'S OMI, MLS, and hopefully one day, HIRDLS instruments, as well as heritage datasets from TOMS, UARS, MODIS, and AIRS. This data is currently archived in the GES Distributed Active Archive Center (DAAC). The GES DISC has begun the development of a community driven data management system that's sole purpose is to manage and provide value added services to NASA's Atmospheric Composition (AC) Data. This system, called the Atmospheric Composition Data and Information Services Center (ACDISC) will provide access all AC datasets from the above mentioned instruments, as well as AC datasets residing at remote archive sites (e.g, LaRC DAAC) The goals of the ACDISC are to: 1) Provide a data center for Atmospheric Scientists, guided by Atmospheric Scientists; 2) Be absolutely responsive to the data and data service needs of the Atmospheric Composition (AC) community; 3) Provide services (i.e., expertise) that will facilitate the effortless access to and usage of AC data; 4) Collaborate with AC scientists to facilitate the use of data from multiple sensors for long term atmospheric research. The ACDISC is an AC specific, user driven, multi-sensor, on-line, easy access archive and distribution system employing data analysis and visualization, data mining, and other user requested techniques that facilitate science data usage. The purpose of this presentation is to provide the evolution path that the GES DISC in order to better serve AC data, and also to receive continued community feedback and further foster collaboration with AC data users and providers.

Online fluorescence spectroscopy for the real-time evaluation of the microbial quality of drinking water.

PubMed

Sorensen, J P R; Vivanco, A; Ascott, M J; Gooddy, D C; Lapworth, D J; Read, D S; Rushworth, C M; Bucknall, J; Herbert, K; Karapanos, I; Gumm, L P; Taylor, R G

2018-06-15

We assessed the utility of online fluorescence spectroscopy for the real-time evaluation of the microbial quality of untreated drinking water. Online fluorimeters were installed on the raw water intake at four groundwater-derived UK public water supplies alongside existing turbidity sensors that are used to forewarn of the presence of microbial contamination in the water industry. The fluorimeters targeted fluorescent dissolved organic matter (DOM) peaks at excitation/emission wavelengths of 280/365 nm (tryptophan-like fluorescence, TLF) and 280/450 nm (humic-like fluorescence, HLF). Discrete samples were collected for Escherichia coli, total bacterial cell counts by flow cytometry, and laboratory-based fluorescence and absorbance. Both TLF and HLF were strongly correlated with E. coli (ρ = 0.71-0.77) and total bacterial cell concentrations (ρ = 0.73-0.76), whereas the correlations between turbidity and E. coli (ρ = 0.48) and total bacterial cell counts (ρ = 0.40) were much weaker. No clear TLF peak was observed at the sites and all apparent TLF was considered to be optical bleed-through from the neighbouring HLF peak. Therefore, a HLF fluorimeter alone would be sufficient to evaluate the microbial water quality at these sources. Fluorescent DOM was also influenced by site operations such as pump start-up and the precipitation of cations on the sensor windows. Online fluorescent DOM sensors are a better indicator of the microbial quality of untreated drinking water than turbidity and they have wide-ranging potential applications within the water industry. Copyright © 2018 British Geological Survey, a component institute of NERC - 'BGS © NERC 2018'. Published by Elsevier Ltd.. All rights reserved.

Continuous monitoring of bisulfide variation in microdialysis effluents by on-line droplet-based microfluidic fluorescent sensor.

PubMed

Zhu, Xiaocui; Xu, Lei; Wu, Tongbo; Xu, Anqin; Zhao, Meiping; Liu, Shaorong

2014-05-15

We demonstrate a novel fluorescent sensor for real-time and continuous monitoring of the variation of bisulfide in microdialysis effluents by using a nanoparticle-glutathione-fluorescein isothiocyanate (AuNP-GSH-FITC) probe coupled with on-line droplet-based microfluidic chip. The AuNP-GSH-FITC fluorescent probe was firstly developed and used for bisulfide detection in bulk solution by quantitative real-time PCR, which achieved a linear working range from 0.1 μM to 5.0 μM and a limit of detection of ~50 nM. The response time was less than 2 min. With the aid of co-immobilized thiol-polyethylene glycol, the probe exhibited excellent stability and reproducibility in high salinity solutions, including artificial cerebrospinal fluids (aCSF). By adding 0.1% glyoxal to the probe solution, the assay allowed quantification of bisulfide in the presence of cysteine at the micro-molarity level. Using the AuNP-GSH-FITC probe, a droplet-based microfluidic fluorescent sensor was further constructed for online monitoring of bisulfide variation in the effluent of microdialysis. By using fluorescence microscope-charge-coupled device camera as the detector, the integrated microdialysis/microfluidic chip device achieved a detection limit of 2.0 μM and a linear response from 5.0 μM to 50 μM for bisulfide in the tested sample. The method was successfully applied for the on-line measurement of bisulfide variation in aCSF and serum samples. It will be a very useful tool for tracking the variation of bisulfide or hydrogen sulfide in extracellular fluids. Copyright © 2013 Elsevier B.V. All rights reserved.

Real-Time Adaptation of Decision Thresholds in Sensor Networks for Detection of Moving Targets (PREPRINT)

DTIC Science & Technology

2010-01-01

target kinematics for multiple sensor detections is referred to as the track - before - detect strategy, and is commonly adopted in multi-sensor surveillance...of moving targets. Wettergren [4] presented an application of track - before - detect strategies to undersea distributed sensor networks. In de- signing...the deployment of a distributed passive sensor network that employs this track - before - detect procedure, it is impera- tive that the placement of

ADAPTable Sensor Systems Phase 2. Topic 2: Reusable Core Software. Distributed Synchronization Software for the Sensor Nodes

DTIC Science & Technology

2015-03-01

Wireless Sensor Network Using Unreliable GPS Signals Daniel R. Fuhrmann*, Joshua Stomberg§, Saeid Nooshabadi*§ Dustin McIntire†, William Merill... wireless sensor network , when the timing jitter is subject to a empirically determined bimodal non-Gaussian distribution. Specifically, we 1) estimate the...over a nominal 19.2 MHz frequency with an adjustment made every four hours. Index Terms— clock synchronization, GPS, wireless sensor networks , Kalman

Probability and Statistics in Sensor Performance Modeling

DTIC Science & Technology

2010-12-01

language software program is called Environmental Awareness for Sensor and Emitter Employment. Some important numerical issues in the implementation...3 Statistical analysis for measuring sensor performance...complementary cumulative distribution function cdf cumulative distribution function DST decision-support tool EASEE Environmental Awareness of

A distributed monitoring system for photovoltaic arrays based on a two-level wireless sensor network

NASA Astrophysics Data System (ADS)

Su, F. P.; Chen, Z. C.; Zhou, H. F.; Wu, L. J.; Lin, P. J.; Cheng, S. Y.; Li, Y. F.

2017-11-01

In this paper, a distributed on-line monitoring system based on a two-level wireless sensor network (WSN) is proposed for real time status monitoring of photovoltaic (PV) arrays to support the fine management and maintenance of PV power plants. The system includes the sensing nodes installed on PV modules (PVM), sensing and routing nodes installed on combiner boxes of PV sub-arrays (PVA), a sink node and a data management centre (DMC) running on a host computer. The first level WSN is implemented by the low-cost wireless transceiver nRF24L01, and it is used to achieve single hop communication between the PVM nodes and their corresponding PVA nodes. The second level WSN is realized by the CC2530 based ZigBee network for multi-hop communication among PVA nodes and the sink node. The PVM nodes are used to monitor the PVM working voltage and backplane temperature, and they send the acquired data to their PVA node via the nRF24L01 based first level WSN. The PVA nodes are used to monitor the array voltage, PV string current and environment irradiance, and they send the acquired and received data to the DMC via the ZigBee based second level WSN. The DMC is designed using the MATLAB GUIDE and MySQL database. Laboratory experiment results show that the system can effectively acquire, display, store and manage the operating and environment parameters of PVA in real time.

Geographical Topics Learning of Geo-Tagged Social Images.

PubMed

Zhang, Xiaoming; Ji, Shufan; Wang, Senzhang; Li, Zhoujun; Lv, Xueqiang

2016-03-01

With the availability of cheap location sensors, geotagging of images in online social media is very popular. With a large amount of geo-tagged social images, it is interesting to study how these images are shared across geographical regions and how the geographical language characteristics and vision patterns are distributed across different regions. Unlike textual document, geo-tagged social image contains multiple types of content, i.e., textual description, visual content, and geographical information. Existing approaches usually mine geographical characteristics using a subset of multiple types of image contents or combining those contents linearly, which ignore correlations between different types of contents, and their geographical distributions. Therefore, in this paper, we propose a novel method to discover geographical characteristics of geo-tagged social images using a geographical topic model called geographical topic model of social images (GTMSIs). GTMSI integrates multiple types of social image contents as well as the geographical distributions, in which image topics are modeled based on both vocabulary and visual features. In GTMSI, each region of the image would have its own topic distribution, and hence have its own language model and vision pattern. Experimental results show that our GTMSI could identify interesting topics and vision patterns, as well as provide location prediction and image tagging.

A Sensor Fusion Method for Tracking Vertical Velocity and Height Based on Inertial and Barometric Altimeter Measurements

PubMed Central

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-01-01

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04–0.24 m/s; height RMSE was in the range 5–68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions. PMID:25061835

An Integrated Hydrologic Monitoring Network

NASA Astrophysics Data System (ADS)

Tedesco, L. P.; Baker, M. P.; Hall, B. E.

2004-12-01

Ecological studies depend on the ability to monitor an environment, collect data at appropriate spatial and temporal scales, and analyze that data from the diverse viewpoints of many relevant disciplines. Historically, environmental studies have been conducted by small teams of researchers, usually collecting data by hand at some set but low frequency, and organizing it according to ad hoc, project-specific goals. Recent years have seen dramatic advancement in the ability to gather environmental data remotely and therefore at much higher frequency. We are working to create a dynamic and integrated network of environmental sensors in natural environments to acquire real time data and create tools for visualization appropriate for different audiences to promote scientific exploration. Instrumentation includes an array of water quality and water level sondes and probes distributed throughout three Central Indiana counties. Instrument platforms currently include five river monitoring platforms utilizing YSI water quality and level probes; a lake buoy array that includes three YSI sonde packages monitoring physical, chemical and biological parameters; and over fifteen YSI and Solinist groundwater probes recording both level and water quality. Many sites are providing real-time data and several additional sites are scheduled to be online in the coming months. Visualization of this real time data from remote sensors distributed throughout Central Indiana provides numerous challenges. The benefits of successfully integrating remotely deployed environmental sensors in a post 9-11 world is obvious. We are working to bridge both the extremes associated with the frequency of data collection and the lack of data coordination by creating techniques for data networking and retrieval, and data management, analysis, and visualization capabilities that operate across a range of computing platforms to make this data immediately accessible and useful to a range of interested parties, across multiple disciplines. We are working to integrate multiple data streams into a coherent data base and create applications that allow users to view data from multiple instruments at different sites. Creating visualizations of real time, dynamic data from the everyday world and delivering it via web applications as well as through innovative display spaces will be a key outcome of this program. On-line tools for QA/QC, data queries, graphing, and sensitivity analysis are under development. Our goal is to use the instrumented sites to create analysis and presentation applications to foster a community of learners interested in understanding these ecosystems, and the larger environmental issues that they represent. This broad-based community will include environmental researchers, university faculty in lecture halls, math and science teachers, university and K-12 students, civic leaders, and educators at informal learning centers.

Fast and accurate spectral estimation for online detection of partial broken bar in induction motors

NASA Astrophysics Data System (ADS)

Samanta, Anik Kumar; Naha, Arunava; Routray, Aurobinda; Deb, Alok Kanti

2018-01-01

In this paper, an online and real-time system is presented for detecting partial broken rotor bar (BRB) of inverter-fed squirrel cage induction motors under light load condition. This system with minor modifications can detect any fault that affects the stator current. A fast and accurate spectral estimator based on the theory of Rayleigh quotient is proposed for detecting the spectral signature of BRB. The proposed spectral estimator can precisely determine the relative amplitude of fault sidebands and has low complexity compared to available high-resolution subspace-based spectral estimators. Detection of low-amplitude fault components has been improved by removing the high-amplitude fundamental frequency using an extended-Kalman based signal conditioner. Slip is estimated from the stator current spectrum for accurate localization of the fault component. Complexity and cost of sensors are minimal as only a single-phase stator current is required. The hardware implementation has been carried out on an Intel i7 based embedded target ported through the Simulink Real-Time. Evaluation of threshold and detectability of faults with different conditions of load and fault severity are carried out with empirical cumulative distribution function.

The Approximate Bayesian Computation methods in the localization of the atmospheric contamination source

NASA Astrophysics Data System (ADS)

Kopka, P.; Wawrzynczak, A.; Borysiewicz, M.

2015-09-01

In many areas of application, a central problem is a solution to the inverse problem, especially estimation of the unknown model parameters to model the underlying dynamics of a physical system precisely. In this situation, the Bayesian inference is a powerful tool to combine observed data with prior knowledge to gain the probability distribution of searched parameters. We have applied the modern methodology named Sequential Approximate Bayesian Computation (S-ABC) to the problem of tracing the atmospheric contaminant source. The ABC is technique commonly used in the Bayesian analysis of complex models and dynamic system. Sequential methods can significantly increase the efficiency of the ABC. In the presented algorithm, the input data are the on-line arriving concentrations of released substance registered by distributed sensor network from OVER-LAND ATMOSPHERIC DISPERSION (OLAD) experiment. The algorithm output are the probability distributions of a contamination source parameters i.e. its particular location, release rate, speed and direction of the movement, start time and duration. The stochastic approach presented in this paper is completely general and can be used in other fields where the parameters of the model bet fitted to the observable data should be found.

Fibre Optic Sensors for Selected Wastewater Characteristics

PubMed Central

Chong, Su Sin; Abdul Aziz, A. R.; Harun, Sulaiman W.

2013-01-01

Demand for online and real-time measurements techniques to meet environmental regulation and treatment compliance are increasing. However the conventional techniques, which involve scheduled sampling and chemical analysis can be expensive and time consuming. Therefore cheaper and faster alternatives to monitor wastewater characteristics are required as alternatives to conventional methods. This paper reviews existing conventional techniques and optical and fibre optic sensors to determine selected wastewater characteristics which are colour, Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD). The review confirms that with appropriate configuration, calibration and fibre features the parameters can be determined with accuracy comparable to conventional method. With more research in this area, the potential for using FOS for online and real-time measurement of more wastewater parameters for various types of industrial effluent are promising. PMID:23881131

Acoustic emission based damage localization in composites structures using Bayesian identification

NASA Astrophysics Data System (ADS)

Kundu, A.; Eaton, M. J.; Al-Jumali, S.; Sikdar, S.; Pullin, R.

2017-05-01

Acoustic emission based damage detection in composite structures is based on detection of ultra high frequency packets of acoustic waves emitted from damage sources (such as fibre breakage, fatigue fracture, amongst others) with a network of distributed sensors. This non-destructive monitoring scheme requires solving an inverse problem where the measured signals are linked back to the location of the source. This in turn enables rapid deployment of mitigative measures. The presence of significant amount of uncertainty associated with the operating conditions and measurements makes the problem of damage identification quite challenging. The uncertainties stem from the fact that the measured signals are affected by the irregular geometries, manufacturing imprecision, imperfect boundary conditions, existing damages/structural degradation, amongst others. This work aims to tackle these uncertainties within a framework of automated probabilistic damage detection. The method trains a probabilistic model of the parametrized input and output model of the acoustic emission system with experimental data to give probabilistic descriptors of damage locations. A response surface modelling the acoustic emission as a function of parametrized damage signals collected from sensors would be calibrated with a training dataset using Bayesian inference. This is used to deduce damage locations in the online monitoring phase. During online monitoring, the spatially correlated time data is utilized in conjunction with the calibrated acoustic emissions model to infer the probabilistic description of the acoustic emission source within a hierarchical Bayesian inference framework. The methodology is tested on a composite structure consisting of carbon fibre panel with stiffeners and damage source behaviour has been experimentally simulated using standard H-N sources. The methodology presented in this study would be applicable in the current form to structural damage detection under varying operational loads and would be investigated in future studies.

Low cost self-made pressure distribution sensors for ergonomic chair: Are they suitable for posture monitoring?

PubMed

Martinaitis, Arnas; Daunoraviciene, Kristina

2018-05-18

Long sitting causes many health problems for people. Healthy sitting monitoring systems, like real-time pressure distribution measuring, is in high demand and many methods of posture recognition were developed. Such systems are usually expensive and hardly available for the regular user. The aim of study is to develop low cost but sensitive enough pressure sensors and posture monitoring system. New self-made pressure sensors have been developed and tested, and prototype of pressure distribution measuring system was designed. Sensors measured at average noise amplitude of a = 56 mV (1.12%), average variation in sequential measurements of the same sensor s = 17 mV (0.34%). Signal variability between sensors averaged at 100 mV (2.0%). Weight to signal dependency graph was measured and hysteresis calculated. Results suggested the use of total sixteen sensors for posture monitoring system with accuracy of < 1.5% after relaxation and repeatability of around 2%. Results demonstrate that hand-made sensor sensitivity and repeatability are acceptable for posture monitoring, and it is possible to build low cost pressure distribution measurement system with graphical visualization without expensive equipment or complicated software.

Distributed sensor for water and pH measurements using fiber optics and swellable polymeric systems

NASA Astrophysics Data System (ADS)

Michie, W. C.; Culshaw, B.; McKenzie, I.; Konstantakis, M.; Graham, N. B.; Moran, C.; Santos, F.; Bergqvist, E.; Carlstrom, B.

1995-01-01

We report on the design, construction and test of a generic form of sensor for making distributed measurements of a range of chemical parameters. The technique combines optical time-domain reflectometry with chemically sensitive water-swellable polymers (hydrogels). Initial experiments have concentrated on demonstrating a distributed water detector; however, gels have been developed that enable this sensor to be

Development of High Frequency Transition-Edge-Sensor Polarimeters for Next Generation Cosmic Microwave Background Experiments and Galactic Foreground Measurements

NASA Astrophysics Data System (ADS)

Walker, Samantha; Sierra, Carlos E.; Austermann, Jason Edward; Beall, James; Becker, Dan; Dober, Bradley; Duff, Shannon; Hilton, Gene; Hubmayr, Johannes; Van Lanen, Jeffrey L.; McMahon, Jeff; Simon, Sara M.; Ullom, Joel; Vissers, Michael R.; NIST Quantum Sensors Group

2018-06-01

Observations of the cosmic microwave background (CMB) provide a powerful tool for probing the earliest moments of the universe and therefore have the potential to transform our understanding of cosmology. In particular, precision measurements of its polarization can reveal the existence of gravitational waves produced during cosmic inflation. However, these observations are complicated by the presence of astrophysical foregrounds, which may be separated by using broad frequency coverage, as the spectral energy distribution between foregrounds and the CMB is distinct. For this purpose, we are developing large-bandwidth, feedhorn-coupled transition-edge-sensor (TES) arrays that couple polarized light from waveguide to superconducting microstrip by use of a symmetric, planar orthomode transducer (OMT). In this work, we describe two types of pixels, an ultra-high frequency (UHF) design, which operates from 195 GHz-315 GHz, and an extended ultra-high frequency (UHF++) design, which operates from 195 GHz-420 GHz, being developed for next generation CMB experiments that will come online in the next decade, such as CCAT-prime and the Simons Observatory. We present the designs, simulation results, fabrication, and preliminary measurements of these prototype pixels.

Shuttle Transportation System Case-Study Development

NASA Technical Reports Server (NTRS)

Ransom, Khadijah

2012-01-01

A case-study collection was developed for NASA's Space Shuttle Program. Using lessons learned and documented by NASA KSC engineers, analysts, and contractors, decades of information related to processing and launching the Space Shuttle was gathered into a single database. The goal was to provide educators with an alternative means to teach real-world engineering processes and to enhance critical thinking, decision making, and problem solving skills. Suggested formats were created to assist both external educators and internal NASA employees to develop and contribute their own case-study reports to share with other educators and students. Via group project, class discussion, or open-ended research format, students will be introduced to the unique decision making process related to Shuttle missions and development. Teaching notes, images, and related documents will be made accessible to the public for presentation of Space Shuttle reports. Lessons investigated included the engine cutoff (ECO) sensor anomaly which occurred during mission STS-114. Students will be presented with general mission infom1ation as well as an explanation of ECO sensors. The project will conclude with the design of a website that allows for distribution of information to the public as well as case-study report submissions from other educators online.

Dual-hole Photonic Crystal Fiber Intermodal Interference based Refractometer

NASA Astrophysics Data System (ADS)

Liu, Feng; Guo, Xuan; Zhang, Qing; Fu, Xinghu

2017-12-01

A refractive-index (RI) sensor and its sensing characteristics based on intermodal interference of dual-hole Polarization Maintaining Photonic Crystal Fiber (PM-PCF) are demonstrated in this letter. The sensor works from the interference between LP01 and LP11 modes of hydrofluoric acid etched PM-PCF. The influence of corrosion zone radius on the RI sensing sensitivity is also discussed. Via choosing a 2.5 cm etched PM-PCF(the etched area radius is 27.5 μm) and 650 nm laser, the sensor exhibits the RI sensitivity of 7.48 V/RIU. The simple sensor structure and inexpensive demodulation method can make this technology for online refractive index measurement in widespread areas.

Fluorescence excitation-emission matrix spectroscopy for degradation monitoring of machinery lubricants

NASA Astrophysics Data System (ADS)

Sosnovski, Oleg; Suresh, Pooja; Dudelzak, Alexander E.; Green, Benjamin

2018-02-01

Lubrication oil is a vital component of heavy rotating machinery defining the machine's health, operational safety and effectiveness. Recently, the focus has been on developing sensors that provide real-time/online monitoring of oil condition/lubricity. Industrial practices and standards for assessing oil condition involve various analytical methods. Most these techniques are unsuitable for online applications. The paper presents the results of studying degradation of antioxidant additives in machinery lubricants using Fluorescence Excitation-Emission Matrix (EEM) Spectroscopy and Machine Learning techniques. EEM Spectroscopy is capable of rapid and even standoff sensing; it is potentially applicable to real-time online monitoring.

An approach to built-in test for shipboard machinery systems

NASA Astrophysics Data System (ADS)

Hegner, H. R.

This paper presents an approach for incorporating built-in test (BIT) into shipboard machinery systems. BIT, as used herein, denotes both built-in test and on-line monitoring. Since sensors are a key element to a successful machinery monitoring system, an assessment of shipboard sensors is included in the paper. Specific design examples are also presented for a marine diesel engine, gas turbine engine, and air conditioning plant.

Peer-to-peer model for the area coverage and cooperative control of mobile sensor networks

NASA Astrophysics Data System (ADS)

Tan, Jindong; Xi, Ning

2004-09-01

This paper presents a novel model and distributed algorithms for the cooperation and redeployment of mobile sensor networks. A mobile sensor network composes of a collection of wireless connected mobile robots equipped with a variety of sensors. In such a sensor network, each mobile node has sensing, computation, communication, and locomotion capabilities. The locomotion ability enhances the autonomous deployment of the system. The system can be rapidly deployed to hostile environment, inaccessible terrains or disaster relief operations. The mobile sensor network is essentially a cooperative multiple robot system. This paper first presents a peer-to-peer model to define the relationship between neighboring communicating robots. Delaunay Triangulation and Voronoi diagrams are used to define the geometrical relationship between sensor nodes. This distributed model allows formal analysis for the fusion of spatio-temporal sensory information of the network. Based on the distributed model, this paper discusses a fault tolerant algorithm for autonomous self-deployment of the mobile robots. The algorithm considers the environment constraints, the presence of obstacles and the nonholonomic constraints of the robots. The distributed algorithm enables the system to reconfigure itself such that the area covered by the system can be enlarged. Simulation results have shown the effectiveness of the distributed model and deployment algorithms.

On-line condition monitoring applications in nuclear power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hastiemian, H. M.; Feltus, M. A.

2006-07-01

Existing signals from process instruments in nuclear power plants can be sampled while the plant is operating and analyzed to verify the static and dynamic performance of process sensors, identify process-to-sensor problems, detect instrument anomalies such as venturi fouling, measure the vibration of the reactor vessel and its internals, or detect thermal hydraulic anomalies within the reactor coolant system. These applications are important in nuclear plants to satisfy a variety of objectives such as: 1) meeting the plant technical specification requirements; 2) complying with regulatory regulations; 3) guarding against equipment and process degradation; 4) providing a means for incipient failuremore » detection and predictive maintenance; or 5) identifying the root cause of anomalies in equipment and plant processes. The technologies that are used to achieve these objectives are collectively referred to as 'on-line condition monitoring.' This paper presents a review of key elements of these technologies, provides examples of their use in nuclear power plants, and illustrates how they can be integrated into an on-line condition monitoring system for nuclear power plants. (authors)« less

Spectroscopic On-Line Monitoring of Cu/W Contacts Erosion in HVCBs Using Optical-Fibre Based Sensor and Chromatic Methodology

PubMed Central

Wang, Zhixiang; Jones, Gordon R.; Spencer, Joseph W.; Wang, Xiaohua; Rong, Mingzhe

2017-01-01

Contact erosion is one of the most crucial factors affecting the electrical service lifetime of high-voltage circuit breakers (HVCBs). On-line monitoring the contacts’ erosion degree is increasingly in demand for the sake of condition based maintenance to guarantee the functional operation of HVCBs. A spectroscopic monitoring system has been designed based upon a commercial 245 kV/40 kA SF6 live tank circuit breaker with copper–tungsten (28 wt % and 72 wt %) arcing contacts at atmospheric SF6 pressure. Three optical-fibre based sensors are used to capture the time-resolved spectra of arcs. A novel approach using chromatic methods to process the time-resolved spectral signal has been proposed. The processed chromatic parameters have been interpreted to show that the time variation of spectral emission from the contact material and quenching gas are closely correlated to the mass loss and surface degradation of the plug arcing contact. The feasibility of applying this method to online monitoring of contact erosion is indicated. PMID:28272295

Spectroscopic On-Line Monitoring of Cu/W Contacts Erosion in HVCBs Using Optical-Fibre Based Sensor and Chromatic Methodology.

PubMed

Wang, Zhixiang; Jones, Gordon R; Spencer, Joseph W; Wang, Xiaohua; Rong, Mingzhe

2017-03-06

Contact erosion is one of the most crucial factors affecting the electrical service lifetime of high-voltage circuit breakers (HVCBs). On-line monitoring the contacts' erosion degree is increasingly in demand for the sake of condition based maintenance to guarantee the functional operation of HVCBs. A spectroscopic monitoring system has been designed based upon a commercial 245 kV/40 kA S F 6 live tank circuit breaker with copper-tungsten (28 wt % and 72 wt %) arcing contacts at atmospheric S F 6 pressure. Three optical-fibre based sensors are used to capture the time-resolved spectra of arcs. A novel approach using chromatic methods to process the time-resolved spectral signal has been proposed. The processed chromatic parameters have been interpreted to show that the time variation of spectral emission from the contact material and quenching gas are closely correlated to the mass loss and surface degradation of the plug arcing contact. The feasibility of applying this method to online monitoring of contact erosion is indicated.

Towards the development of a hybrid-integrated chip interferometer for online surface profile measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, P.; Martin, H.; Jiang, X.

Non-destructive testing and online measurement of surface features are pressing demands in manufacturing. Thus optical techniques are gaining importance for characterization of complex engineering surfaces. Harnessing integrated optics for miniaturization of interferometry systems onto a silicon wafer and incorporating a compact optical probe would enable the development of a handheld sensor for embedded metrology applications. In this work, we present the progress in the development of a hybrid photonics based metrology sensor device for online surface profile measurements. The measurement principle along with test and measurement results of individual components has been presented. For non-contact measurement, a spectrally encoded lateralmore » scanning probe based on the laser scanning microscopy has been developed to provide fast measurement with lateral resolution limited to the diffraction limit. The probe demonstrates a lateral resolution of ∼3.6 μm while high axial resolution (sub-nanometre) is inherently achieved by interferometry. Further the performance of the hybrid tuneable laser and the scanning probe was evaluated by measuring a standard step height sample of 100 nm.« less

An online input force time history reconstruction algorithm using dynamic principal component analysis

NASA Astrophysics Data System (ADS)

Prawin, J.; Rama Mohan Rao, A.

2018-01-01

The knowledge of dynamic loads acting on a structure is always required for many practical engineering problems, such as structural strength analysis, health monitoring and fault diagnosis, and vibration isolation. In this paper, we present an online input force time history reconstruction algorithm using Dynamic Principal Component Analysis (DPCA) from the acceleration time history response measurements using moving windows. We also present an optimal sensor placement algorithm to place limited sensors at dynamically sensitive spatial locations. The major advantage of the proposed input force identification algorithm is that it does not require finite element idealization of structure unlike the earlier formulations and therefore free from physical modelling errors. We have considered three numerical examples to validate the accuracy of the proposed DPCA based method. Effects of measurement noise, multiple force identification, different kinds of loading, incomplete measurements, and high noise levels are investigated in detail. Parametric studies have been carried out to arrive at optimal window size and also the percentage of window overlap. Studies presented in this paper clearly establish the merits of the proposed algorithm for online load identification.

Dynamic control of nutrient-removal from industrial wastewater in a sequencing batch reactor, using common and low-cost online sensors.

PubMed

Dries, Jan

2016-01-01

On-line control of the biological treatment process is an innovative tool to cope with variable concentrations of chemical oxygen demand and nutrients in industrial wastewater. In the present study we implemented a simple dynamic control strategy for nutrient-removal in a sequencing batch reactor (SBR) treating variable tank truck cleaning wastewater. The control system was based on derived signals from two low-cost and robust sensors that are very common in activated sludge plants, i.e. oxidation reduction potential (ORP) and dissolved oxygen. The amount of wastewater fed during anoxic filling phases, and the number of filling phases in the SBR cycle, were determined by the appearance of the 'nitrate knee' in the profile of the ORP. The phase length of the subsequent aerobic phases was controlled by the oxygen uptake rate measured online in the reactor. As a result, the sludge loading rate (F/M ratio), the volume exchange rate and the SBR cycle length adapted dynamically to the activity of the activated sludge and the actual characteristics of the wastewater, without affecting the final effluent quality.

In-Situ Acoustic Measurements of Temperature Profile in Extreme Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skliar, Mikhail

2015-03-31

A gasifier’s temperature is the primary characteristic that must be monitored to ensure its performance and the longevity of its refractory. One of the key technological challenges impacting the reliability and economics of coal and biomass gasification is the lack of temperature sensors that are capable of providing accurate, reliable, and long-life performance in an extreme gasification environment. This research has proposed, demonstrated, and validated a novel approach that uses a noninvasive ultrasound method that provides real-time temperature distribution monitoring across the refractory, especially the hot face temperature of the refractory. The essential idea of the ultrasound measurements of segmentalmore » temperature distribution is to use an ultrasound propagation waveguide across a refractory that has been engineered to contain multiple internal partial reflectors at known locations. When an ultrasound excitation pulse is introduced on the cold side of the refractory, it will be partially reflected from each scatterer in the US propagation path in the refractory wall and returned to the receiver as a train of partial echoes. The temperature in the corresponding segment can be determined based on recorded ultrasonic waveform and experimentally defined relationship between the speed of sound and temperature. The ultrasound measurement method offers a powerful solution to provide continuous real time temperature monitoring for the occasions that conventional thermal, optical and other sensors are infeasible, such as the impossibility of insertion of temperature sensor, harsh environment, unavailable optical path, and more. Our developed ultrasound system consists of an ultrasound engineered waveguide, ultrasound transducer/receiver, and data acquisition, logging, interpretation, and online display system, which is simple to install on the existing units with minimal modification on the gasifier or use with new units. This system has been successfully tested with a 100 kW pilot scale down flow oxyfuel combustor, capturing in real time temperature changes during all relevant combustion process changes. The ultrasound measurements have excellent agreement with thermo- couple measurements, and appear to be more sensitive to temperature changes before the thermocouples response, which is believed to be the first demonstration of ultrasound measurements segmental temperature distribution across refractories.« less

The Identity Mapping Project: Demographic differences in patterns of distributed identity.

PubMed

Gilbert, Richard L; Dionisio, John David N; Forney, Andrew; Dorin, Philip

2015-01-01

The advent of cloud computing and a multi-platform digital environment is giving rise to a new phase of human identity called "The Distributed Self." In this conception, aspects of the self are distributed into a variety of 2D and 3D digital personas with the capacity to reflect any number of combinations of now malleable personality traits. In this way, the source of human identity remains internal and embodied, but the expression or enactment of the self becomes increasingly external, disembodied, and distributed on demand. The Identity Mapping Project (IMP) is an interdisciplinary collaboration between psychology and computer Science designed to empirically investigate the development of distributed forms of identity. Methodologically, it collects a large database of "identity maps" - computerized graphical representations of how active someone is online and how their identity is expressed and distributed across 7 core digital domains: email, blogs/personal websites, social networks, online forums, online dating sites, character based digital games, and virtual worlds. The current paper reports on gender and age differences in online identity based on an initial database of distributed identity profiles.

Knowledge Management in Sensor Enabled Online Services

NASA Astrophysics Data System (ADS)

Smyth, Dominick; Cappellari, Paolo; Roantree, Mark

The Future Internet, has as its vision, the development of improved features and usability for services, applications and content. In many cases, services can be provided automatically through the use of monitors or sensors. This means web generated sensor data becoming available not only to the companies that own the sensors but also to the domain users who generate the data and to information and knowledge workers who harvest the output. The goal is improving the service through better usage of the information provided by the service. Applications and services vary from climate, traffic, health and sports event monitoring. In this paper, we present the WSW system that harvests web sensor data to provide additional and, in some cases, more accurate information using an analysis of both live and warehoused information.

Distributed Fiber-Optic Sensors for Vibration Detection

PubMed Central

Liu, Xin; Jin, Baoquan; Bai, Qing; Wang, Yu; Wang, Dong; Wang, Yuncai

2016-01-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach–Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications. PMID:27472334

Distributed Fiber-Optic Sensors for Vibration Detection.

PubMed

Liu, Xin; Jin, Baoquan; Bai, Qing; Wang, Yu; Wang, Dong; Wang, Yuncai

2016-07-26

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach-Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications.

Relaxation techniques for stress

MedlinePlus

... of your body. These sensors measure your skin temperature, brain waves, breathing, and muscle activity. You can ... more about any of these techniques through local classes, books, videos, or online. Alternative Names Relaxation response ...

Temperature Measurement and Damage Detection in Concrete Beams Exposed to Fire Using PPP-BOTDA Based Fiber Optic Sensors.

PubMed

Bao, Yi; Hoehler, Matthew S; Smith, Christopher M; Bundy, Matthew; Chen, Genda

2017-10-01

In this study, distributed fiber optic sensors based on pulse pre-pump Brillouin optical time domain analysis (PPP-BODTA) are characterized and deployed to measure spatially-distributed temperatures in reinforced concrete specimens exposed to fire. Four beams were tested to failure in a natural gas fueled compartment fire, each instrumented with one fused silica, single-mode optical fiber as a distributed sensor and four thermocouples. Prior to concrete cracking, the distributed temperature was validated at locations of the thermocouples by a relative difference of less than 9 %. The cracks in concrete can be identified as sharp peaks in the temperature distribution since the cracks are locally filled with hot air. Concrete cracking did not affect the sensitivity of the distributed sensor but concrete spalling broke the optical fiber loop required for PPP-BOTDA measurements.

Two-Dimensional Automatic Measurement for Nozzle Flow Distribution Using Improved Ultrasonic Sensor

PubMed Central

Zhai, Changyuan; Zhao, Chunjiang; Wang, Xiu; Wang, Ning; Zou, Wei; Li, Wei

2015-01-01

Spray deposition and distribution are affected by many factors, one of which is nozzle flow distribution. A two-dimensional automatic measurement system, which consisted of a conveying unit, a system control unit, an ultrasonic sensor, and a deposition collecting dish, was designed and developed. The system could precisely move an ultrasonic sensor above a pesticide deposition collecting dish to measure the nozzle flow distribution. A sensor sleeve with a PVC tube was designed for the ultrasonic sensor to limit its beam angle in order to measure the liquid level in the small troughs. System performance tests were conducted to verify the designed functions and measurement accuracy. A commercial spray nozzle was also used to measure its flow distribution. The test results showed that the relative error on volume measurement was less than 7.27% when the liquid volume was 2 mL in trough, while the error was less than 4.52% when the liquid volume was 4 mL or more. The developed system was also used to evaluate the flow distribution of a commercial nozzle. It was able to provide the shape and the spraying width of the flow distribution accurately. PMID:26501288

Engineering of Sensor Network Structure for Dependable Fusion

DTIC Science & Technology

2014-08-15

Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller

Measurement of cosmic-ray muons with the Distributed Electronic Cosmic-ray Observatory, a network of smartphones

NASA Astrophysics Data System (ADS)

Vandenbroucke, J.; BenZvi, S.; Bravo, S.; Jensen, K.; Karn, P.; Meehan, M.; Peacock, J.; Plewa, M.; Ruggles, T.; Santander, M.; Schultz, D.; Simons, A. L.; Tosi, D.

2016-04-01

Solid-state camera image sensors can be used to detect ionizing radiation in addition to optical photons. We describe the Distributed Electronic Cosmic-ray Observatory (DECO), an app and associated public database that enables a network of consumer devices to detect cosmic rays and other ionizing radiation. In addition to terrestrial background radiation, cosmic-ray muon candidate events are detected as long, straight tracks passing through multiple pixels. The distribution of track lengths can be related to the thickness of the active (depleted) region of the camera image sensor through the known angular distribution of muons at sea level. We use a sample of candidate muon events detected by DECO to measure the thickness of the depletion region of the camera image sensor in a particular consumer smartphone model, the HTC Wildfire S. The track length distribution is fit better by a cosmic-ray muon angular distribution than an isotropic distribution, demonstrating that DECO can detect and identify cosmic-ray muons despite a background of other particle detections. Using the cosmic-ray distribution, we measure the depletion thickness to be 26.3 ± 1.4 μm. With additional data, the same method can be applied to additional models of image sensor. Once measured, the thickness can be used to convert track length to incident polar angle on a per-event basis. Combined with a determination of the incident azimuthal angle directly from the track orientation in the sensor plane, this enables direction reconstruction of individual cosmic-ray events using a single consumer device. The results simultaneously validate the use of cell phone camera image sensors as cosmic-ray muon detectors and provide a measurement of a parameter of camera image sensor performance which is not otherwise publicly available.

Optimal design of the absolute positioning sensor for a high-speed maglev train and research on its fault diagnosis.

PubMed

Zhang, Dapeng; Long, Zhiqiang; Xue, Song; Zhang, Junge

2012-01-01

This paper studies an absolute positioning sensor for a high-speed maglev train and its fault diagnosis method. The absolute positioning sensor is an important sensor for the high-speed maglev train to accomplish its synchronous traction. It is used to calibrate the error of the relative positioning sensor which is used to provide the magnetic phase signal. On the basis of the analysis for the principle of the absolute positioning sensor, the paper describes the design of the sending and receiving coils and realizes the hardware and the software for the sensor. In order to enhance the reliability of the sensor, a support vector machine is used to recognize the fault characters, and the signal flow method is used to locate the faulty parts. The diagnosis information not only can be sent to an upper center control computer to evaluate the reliability of the sensors, but also can realize on-line diagnosis for debugging and the quick detection when the maglev train is off-line. The absolute positioning sensor we study has been used in the actual project.

A Novel Hybrid Error Criterion-Based Active Control Method for on-Line Milling Vibration Suppression with Piezoelectric Actuators and Sensors

PubMed Central

Zhang, Xingwu; Wang, Chenxi; Gao, Robert X.; Yan, Ruqiang; Chen, Xuefeng; Wang, Shibin

2016-01-01

Milling vibration is one of the most serious factors affecting machining quality and precision. In this paper a novel hybrid error criterion-based frequency-domain LMS active control method is constructed and used for vibration suppression of milling processes by piezoelectric actuators and sensors, in which only one Fast Fourier Transform (FFT) is used and no Inverse Fast Fourier Transform (IFFT) is involved. The correction formulas are derived by a steepest descent procedure and the control parameters are analyzed and optimized. Then, a novel hybrid error criterion is constructed to improve the adaptability, reliability and anti-interference ability of the constructed control algorithm. Finally, based on piezoelectric actuators and acceleration sensors, a simulation of a spindle and a milling process experiment are presented to verify the proposed method. Besides, a protection program is added in the control flow to enhance the reliability of the control method in applications. The simulation and experiment results indicate that the proposed method is an effective and reliable way for on-line vibration suppression, and the machining quality can be obviously improved. PMID:26751448

Distributed sensor coordination for advanced energy systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tumer, Kagan

Motivation: The ability to collect key system level information is critical to the safe, efficient and reliable operation of advanced power systems. Recent advances in sensor technology have enabled some level of decision making directly at the sensor level. However, coordinating large numbers of sensors, particularly heterogeneous sensors, to achieve system level objectives such as predicting plant efficiency, reducing downtime or predicting outages requires sophisticated coordination algorithms. Indeed, a critical issue in such systems is how to ensure the interaction of a large number of heterogenous system components do not interfere with one another and lead to undesirable behavior. Objectivesmore » and Contributions: The long-term objective of this work is to provide sensor deployment, coordination and networking algorithms for large numbers of sensors to ensure the safe, reliable, and robust operation of advanced energy systems. Our two specific objectives are to: 1. Derive sensor performance metrics for heterogeneous sensor networks. 2. Demonstrate effectiveness, scalability and reconfigurability of heterogeneous sensor network in advanced power systems. The key technical contribution of this work is to push the coordination step to the design of the objective functions of the sensors, allowing networks of heterogeneous sensors to be controlled. By ensuring that the control and coordination is not specific to particular sensor hardware, this approach enables the design and operation of large heterogeneous sensor networks. In addition to the coordination coordination mechanism, this approach allows the system to be reconfigured in response to changing needs (e.g., sudden external events requiring new responses) or changing sensor network characteristics (e.g., sudden changes to plant condition). Impact: The impact of this work extends to a large class of problems relevant to the National Energy Technology Laboratory including sensor placement, heterogeneous sensor coordination, and sensor network control in advanced power systems. Each application has specific needs, but they all share the one crucial underlying problem: how to ensure that the interactions of a large number of heterogenous agents lead to coordinated system behavior. This proposal describes a new paradigm that addresses that very issue in a systematic way. Key Results and Findings: All milestones have been completed. Our results demonstrate that by properly shaping agent objective functions, we can develop large (up to 10,000 devices) heterogeneous sensor networks with key desirable properties. The first milestone shows that properly choosing agent-specific objective functions increases system performance by up to 99.9% compared to global evaluations. The second milestone shows evolutionary algorithms learn excellent sensor network coordination policies prior to network deployment, and these policies can be refined online once the network is deployed. The third milestone shows the resulting sensor networks networks are extremely robust to sensor noise, where networks with up to 25% sensor noise are capable of providing measurements with errors on the order of 10⁻³. The fourth milestone shows the resulting sensor networks are extremely robust to sensor failure, with 25% of the sensors in the system failing resulting in no significant performance losses after system reconfiguration.« less

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation.

PubMed

Tkach, Itshak; Jevtić, Aleksandar; Nof, Shimon Y; Edan, Yael

2018-03-02

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors' performance, tasks' priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems.

Real-time sensor validation and fusion for distributed autonomous sensors

NASA Astrophysics Data System (ADS)

Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

2004-04-01

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

Decentralized Online Social Networks

NASA Astrophysics Data System (ADS)

Datta, Anwitaman; Buchegger, Sonja; Vu, Le-Hung; Strufe, Thorsten; Rzadca, Krzysztof

Current Online social networks (OSN) are web services run on logically centralized infrastructure. Large OSN sites use content distribution networks and thus distribute some of the load by caching for performance reasons, nevertheless there is a central repository for user and application data. This centralized nature of OSNs has several drawbacks including scalability, privacy, dependence on a provider, need for being online for every transaction, and a lack of locality. There have thus been several efforts toward decentralizing OSNs while retaining the functionalities offered by centralized OSNs. A decentralized online social network (DOSN) is a distributed system for social networking with no or limited dependency on any dedicated central infrastructure. In this chapter we explore the various motivations of a decentralized approach to online social networking, discuss several concrete proposals and types of DOSN as well as challenges and opportunities associated with decentralization.

MASM: a market architecture for sensor management in distributed sensor networks

NASA Astrophysics Data System (ADS)

Viswanath, Avasarala; Mullen, Tracy; Hall, David; Garga, Amulya

2005-03-01

Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for Sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

A mobile ferromagnetic shape detection sensor using a Hall sensor array and magnetic imaging.

PubMed

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a mobile Hall sensor array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the mobile Hall sensor array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of mobile Hall sensor array system for actual shape detection. The results prove that the mobile Hall sensor array system is able to perform magnetic imaging in identifying various ferromagnetic materials.

A Mobile Ferromagnetic Shape Detection Sensor Using a Hall Sensor Array and Magnetic Imaging

PubMed Central

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a Mobile Hall Sensor Array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the Mobile Hall Sensor Array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of Mobile Hall Sensor Array system for actual shape detection. The results prove that the Mobile Hall Sensor Array system is able to perform magnetic imaging in identifying various ferromagnetic materials. PMID:22346653

Tailor-made resealable micro(bio)reactors providing easy integration of in situ sensors

NASA Astrophysics Data System (ADS)

Viefhues, Martina; Sun, Shiwen; Valikhani, Donya; Nidetzky, Bernd; Vrouwe, Elwin X.; Mayr, Torsten; Bolivar, Juan M.

2017-06-01

Flow microreactors utilizing immobilized enzymes are of great interest in biocatalysis development. Most of the common devices are permanently closed, single-use systems, which allow limited physical and chemical surface modifications and evaluation methods. In this paper we will present resealable flowcells that overcome these limitations and moreover allow a quick and easy integration of sensor systems, because of the use of modular building blocks. The devices were utilized to study the enzyme activity of glucose oxidase immobilized on chemically modified glass surfaces under flow conditions, employing integrated optical oxygen sensors for on-line monitoring.

Flow line sampler

DOEpatents

Nicholls, Colin I.

1992-07-14

An on-line product sampling apparatus and method for measuring product samples from a product stream (12) in a flow line (14) having a sampling aperture (11), includes a sampling tube (18) for containing product samples removed from flow line (14). A piston (22) removes product samples from the product stream (12) through the sampling aperture (11) and returns samples to product stream (12). A sensor (20) communicates with sample tube (18), and senses physical properties of samples while the samples are within sample tube (18). In one embodiment, sensor (20) comprises a hydrogen transient nuclear magnetic resonance sensor for measuring physical properties of hydrogen molecules.

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

PubMed

Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

2017-09-21

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

Virtual Sensor Web Architecture

NASA Astrophysics Data System (ADS)

Bose, P.; Zimdars, A.; Hurlburt, N.; Doug, S.

2006-12-01

NASA envisions the development of smart sensor webs, intelligent and integrated observation network that harness distributed sensing assets, their associated continuous and complex data sets, and predictive observation processing mechanisms for timely, collaborative hazard mitigation and enhanced science productivity and reliability. This paper presents Virtual Sensor Web Infrastructure for Collaborative Science (VSICS) Architecture for sustained coordination of (numerical and distributed) model-based processing, closed-loop resource allocation, and observation planning. VSICS's key ideas include i) rich descriptions of sensors as services based on semantic markup languages like OWL and SensorML; ii) service-oriented workflow composition and repair for simple and ensemble models; event-driven workflow execution based on event-based and distributed workflow management mechanisms; and iii) development of autonomous model interaction management capabilities providing closed-loop control of collection resources driven by competing targeted observation needs. We present results from initial work on collaborative science processing involving distributed services (COSEC framework) that is being extended to create VSICS.

Spatially distributed modal signals of free shallow membrane shell structronic system

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

2008-11-01

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last 20 years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of shallow paraboloidal membrane shells are not clearly understood. In this paper, modeling of free flexible paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Distributed temperature sensor testing in liquid sodium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerardi, Craig; Bremer, Nathan; Lisowski, Darius

Rayleigh-backscatter-based distributed fiber optic sensors were immersed in sodium to obtain high-resolution liquid-sodium temperature measurements. Distributed temperature sensors (DTSs) functioned well up to 400°C in a liquid sodium environment. The DTSs measured sodium column temperature and the temperature of a complex geometrical pattern that leveraged the flexibility of fiber optics. A single Ø 360 lm OD sensor registered dozens of temperatures along a length of over one meter at 100 Hz. We also demonstrated the capability to use a single DTS to simultaneously detect thermal interfaces (e.g. sodium level) and measure temperature.

Temperature grid sensor for the measurement of spatial temperature distributions at object surfaces.

PubMed

Schäfer, Thomas; Schubert, Markus; Hampel, Uwe

2013-01-25

This paper presents results of the development and application of a new temperature grid sensor based on the wire-mesh sensor principle. The grid sensor consists of a matrix of 256 Pt1000 platinum chip resistors and an associated electronics that measures the grid resistances with a multiplexing scheme at high speed. The individual sensor elements can be spatially distributed on an object surface and measure transient temperature distributions in real time. The advantage compared with other temperature field measurement approaches such as infrared cameras is that the object under investigation can be thermally insulated and the radiation properties of the surface do not affect the measurement accuracy. The sensor principle is therefore suited for various industrial monitoring applications. Its applicability for surface temperature monitoring has been demonstrated through heating and mixing experiments in a vessel.

Airborne agent concentration analysis

DOEpatents

Gelbard, Fred

2004-02-03

A method and system for inferring airborne contaminant concentrations in rooms without contaminant sensors, based on data collected by contaminant sensors in other rooms of a building, using known airflow interconnectivity data. The method solves a least squares problem that minimizes the difference between measured and predicted contaminant sensor concentrations with respect to an unknown contaminant release time. Solutions are constrained to providing non-negative initial contaminant concentrations in all rooms. The method can be used to identify a near-optimal distribution of sensors within the building, when then number of available sensors is less than the total number of rooms. This is achieved by having a system-sensor matrix that is non-singular, and by selecting that distribution which yields the lowest condition number of all the distributions considered. The method can predict one or more contaminant initial release points from the collected data.

Thermal sensors to control polymer forming. Challenge and solutions

NASA Astrophysics Data System (ADS)

Lemeunier, F.; Boyard, N.; Sarda, A.; Plot, C.; Lefèvre, N.; Petit, I.; Colomines, G.; Allanic, N.; Bailleul, J. L.

2017-10-01

Many thermal sensors are already used, for many years, to better understand and control material forming processes, especially polymer processing. Due to technical constraints (high pressure, sealing, sensor dimensions…) the thermal measurement is often performed in the tool or close its surface. Thus, it only gives partial and disturbed information. Having reliable information about the heat flux exchanges between the tool and the material during the process would be very helpful to improve the control of the process and to favor the development of new materials. In this work, we present several sensors developed in labs to study the molding steps in forming processes. The analysis of the obtained thermal measurements (temperature, heat flux) shows the required sensitivity threshold of sensitivity of thermal sensors to be able to detect on-line the rate of thermal reaction. Based on these data, we will present new sensor designs which have been patented.

State estimation for distributed systems with sensing delay

NASA Astrophysics Data System (ADS)

Alexander, Harold L.

1991-08-01

Control of complex systems such as remote robotic vehicles requires combining data from many sensors where the data may often be delayed by sensory processing requirements. The number and variety of sensors make it desirable to distribute the computational burden of sensing and estimation among multiple processors. Classic Kalman filters do not lend themselves to distributed implementations or delayed measurement data. The alternative Kalman filter designs presented in this paper are adapted for delays in sensor data generation and for distribution of computation for sensing and estimation over a set of networked processors.

Laboratory evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor

USGS Publications Warehouse

Snazelle, Teri T.

2017-12-18

Sequoia Scientific’s LISST-ABS is an acoustic backscatter sensor designed to measure suspended-sediment concentration at a point source. Three LISST-ABS were evaluated at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF). Serial numbers 6010, 6039, and 6058 were assessed for accuracy in solutions with varying particle-size distributions and for the effect of temperature on sensor accuracy. Certified sediment samples composed of different ranges of particle size were purchased from Powder Technology Inc. These sediment samples were 30–80-micron (µm) Arizona Test Dust; less than 22-µm ISO 12103-1, A1 Ultrafine Test Dust; and 149-µm MIL-STD 810E Silica Dust. The sensor was able to accurately measure suspended-sediment concentration when calibrated with sediment of the same particle-size distribution as the measured. Overall testing demonstrated that sensors calibrated with finer sized sediments overdetect sediment concentrations with coarser sized sediments, and sensors calibrated with coarser sized sediments do not detect increases in sediment concentrations from small and fine sediments. These test results are not unexpected for an acoustic-backscatter device and stress the need for using accurate site-specific particle-size distributions during sensor calibration. When calibrated for ultrafine dust with a less than 22-µm particle size (silt) and with the Arizona Test Dust with a 30–80-µm range, the data from sensor 6039 were biased high when fractions of the coarser (149-µm) Silica Dust were added. Data from sensor 6058 showed similar results with an elevated response to coarser material when calibrated with a finer particle-size distribution and a lack of detection when subjected to finer particle-size sediment. Sensor 6010 was also tested for the effect of dissimilar particle size during the calibration and showed little effect. Subsequent testing revealed problems with this sensor, including an inadequate temperature compensation, making this data questionable. The sensor was replaced by Sequoia Scientific with serial number 6039. Results from the extended temperature testing showed proper temperature compensation for sensor 6039, and results from the dissimilar calibration/testing particle-size distribution closely corroborated the results from sensor 6058.

Innovative Embedded Fiber Sensor System for Spacecraft's Health in Situ Monitoring

NASA Astrophysics Data System (ADS)

Haddad, E.; Kruzelecky, R.; Zou, J.; Wong, B.; Mohammad, N.; Thatte, G.; Jamroz, W.; Riendeau, S.

2009-01-01

Monitoring of various parameters in satellites is desirable to provide the necessary information on the condition and status of the spacecraft and its various subsystems (AOCS, thermal, propulsion, power, mechanisms etc.) throughout its lifecycle. Fiber-Optic Bragg Grating (FBG) sensors represent an alternative to current technological approaches, enabling in situ distributed dynamic health monitoring, to provide a mapping of the spacecraft strain and temperature distributions, for varying operating and orbital conditions. In addition, these sensors may be implemented in the very early spacecraft fabrication stages, as built-in testing and diagnostic tools, and then used continuously through the mission phases until the end of the spacecraft mission. This can substantially reduce the cost of ground qualification and facilitate improved spacecraft design. MPBC has developed and ground qualified a demonstrator fiber sensor network, the Fiber Sensor Demonstrator (FSD) that has been successfully integrated with ESA's Proba-2. This is scheduled to launch in the fall of 2008, and will be the first complete fiber-optic sensing system in space. The advantages of the MPBC approach include a central interrogation system that can be used to control a multi-parameter sensing incorporating various types of sensors. Using a combination of both parallel signal distribution and serial wavelength division sensor multiplexing along single strands of optical fiber enables a high sensor capacity. In a continuous effort, MPB Communications (MPBC) is developing an innovative Embedded Distributed Fiber Sensor (EDFOS) within space composite structures. It addresses the challenges of embedding very thin fiber sensors within a selected material matrix, the decoupling of the strain and temperature effects on the fiber, and the sensor distribution. The embedded sensor approach allows the sensor system to follow the status of the space structure through its entire life cycle; from fabrication and assembly, to ground testing, to the space mission itself. By providing a history of the structure, any changes are more readily discernable, and the in situ sensor information can be used to further improve the design and reliability of the structure.

Steam distribution and energy delivery optimization using wireless sensors

NASA Astrophysics Data System (ADS)

Olama, Mohammed M.; Allgood, Glenn O.; Kuruganti, Teja P.; Sukumar, Sreenivas R.; Djouadi, Seddik M.; Lake, Joe E.

2011-05-01

The Extreme Measurement Communications Center at Oak Ridge National Laboratory (ORNL) explores the deployment of a wireless sensor system with a real-time measurement-based energy efficiency optimization framework in the ORNL campus. With particular focus on the 12-mile long steam distribution network in our campus, we propose an integrated system-level approach to optimize the energy delivery within the steam distribution system. We address the goal of achieving significant energy-saving in steam lines by monitoring and acting on leaking steam valves/traps. Our approach leverages an integrated wireless sensor and real-time monitoring capabilities. We make assessments on the real-time status of the distribution system by mounting acoustic sensors on the steam pipes/traps/valves and observe the state measurements of these sensors. Our assessments are based on analysis of the wireless sensor measurements. We describe Fourier-spectrum based algorithms that interpret acoustic vibration sensor data to characterize flows and classify the steam system status. We are able to present the sensor readings, steam flow, steam trap status and the assessed alerts as an interactive overlay within a web-based Google Earth geographic platform that enables decision makers to take remedial action. We believe our demonstration serves as an instantiation of a platform that extends implementation to include newer modalities to manage water flow, sewage and energy consumption.

Research on a Defects Detection Method in the Ferrite Phase Shifter Cementing Process Based on a Multi-Sensor Prognostic and Health Management (PHM) System.

PubMed

Wan, Bo; Fu, Guicui; Li, Yanruoyue; Zhao, Youhu

2016-08-10

The cementing manufacturing process of ferrite phase shifters has the defect that cementing strength is insufficient and fractures always appear. A detection method of these defects was studied utilizing the multi-sensors Prognostic and Health Management (PHM) theory. Aiming at these process defects, the reasons that lead to defects are analyzed in this paper. In the meanwhile, the key process parameters were determined and Differential Scanning Calorimetry (DSC) tests during the cure process of resin cementing were carried out. At the same time, in order to get data on changing cementing strength, multiple-group cementing process tests of different key process parameters were designed and conducted. A relational model of cementing strength and cure temperature, time and pressure was established, by combining data of DSC and process tests as well as based on the Avrami formula. Through sensitivity analysis for three process parameters, the on-line detection decision criterion and the process parameters which have obvious impact on cementing strength were determined. A PHM system with multiple temperature and pressure sensors was established on this basis, and then, on-line detection, diagnosis and control for ferrite phase shifter cementing process defects were realized. It was verified by subsequent process that the on-line detection system improved the reliability of the ferrite phase shifter cementing process and reduced the incidence of insufficient cementing strength defects.

Multi-modal myocontrol: Testing combined force- and electromyography.

PubMed

Nowak, Markus; Eiband, Thomas; Castellini, Claudio

2017-07-01

Myocontrol, that is control of prostheses using bodily signals, has proved in the decades to be a surprisingly hard problem for the scientific community of assistive and rehabilitation robotics. In particular, traditional surface electromyography (sEMG) seems to be no longer enough to guarantee dexterity (i.e., control over several degrees of freedom) and, most importantly, reliability. Multi-modal myocontrol is concerned with the idea of using novel signal gathering techniques as a replacement of, or alongside, sEMG, to provide high-density and diverse signals to improve dexterity and make the control more reliable. In this paper we present an offline and online assessment of multi-modal sEMG and force myography (FMG) targeted at hand and wrist myocontrol. A total number of twenty sEMG and FMG sensors were used simultaneously, in several combined configurations, to predict opening/closing of the hand and activation of two degrees of freedom of the wrist of ten intact subjects. The analysis was targeted at determining the optimal sensor combination and control parameters; the experimental results indicate that sEMG sensors alone perform worst, yielding a nRMSE of 9.1%, while mixing FMG and sEMG or using FMG only reduces the nRMSE to 5.2-6.6%. To validate these results, we engaged the subject with median performance in an online goal-reaching task. Analysis of this further experiment reveals that the online behaviour is similar to the offline one.

Evaluating online data of water quality changes in a pilot drinking water distribution system with multivariate data exploration methods.

PubMed

Mustonen, Satu M; Tissari, Soile; Huikko, Laura; Kolehmainen, Mikko; Lehtola, Markku J; Hirvonen, Arja

2008-05-01

The distribution of drinking water generates soft deposits and biofilms in the pipelines of distribution systems. Disturbances in water distribution can detach these deposits and biofilms and thus deteriorate the water quality. We studied the effects of simulated pressure shocks on the water quality with online analysers. The study was conducted with copper and composite plastic pipelines in a pilot distribution system. The online data gathered during the study was evaluated with Self-Organising Map (SOM) and Sammon's mapping, which are useful methods in exploring large amounts of multivariate data. The objective was to test the usefulness of these methods in pinpointing the abnormal water quality changes in the online data. The pressure shocks increased temporarily the number of particles, turbidity and electrical conductivity. SOM and Sammon's mapping were able to separate these situations from the normal data and thus make those visible. Therefore these methods make it possible to detect abrupt changes in water quality and thus to react rapidly to any disturbances in the system. These methods are useful in developing alert systems and predictive applications connected to online monitoring.

Characterize Aerosols from MODIS/MISR/OMI/MERRA-2: Dynamic Image Browse Perspective

NASA Astrophysics Data System (ADS)

Wei, J. C.; Yang, W.; Shen, S.; Zhao, P.; Albayrak, A.; Johnson, J. E.; Kempler, S. J.; Pham, L.

2016-12-01

Among the known atmospheric constituents, aerosols still represent the greatest uncertainty in climate research. To understand the uncertainty is to bring altogether of observational (in-situ and remote sensing) and modeling datasets and inter-compare them synergistically for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if these earth science data (satellite and modeling) are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite-borne sensors routinely measure aerosols. There is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) have developed multiple MAPSS (Multi-sensor Aerosol Products Sampling System) applications as a part of Giovanni (Geospatial Interactive Online Visualization and Analysis Interface) data visualization and analysis tool since 2007. The MAPSS database provides spatio-temporal statistics for multiple spatial spaceborne Level 2 aerosol products (MODIS Terra, MODIS Aqua, MISR, POLDER, OMI, CALIOP, SeaWiFS Deep Blue, and VIIRS) sampled over AERONET ground stations. In this presentation, I will demonstrate a new visualization service (NASA Level 2 Data Quality Visualization, DQViz) supporting various visualization and data accessing capabilities from satellite Level 2 (MODIS/MISR/OMI) and long term assimilated aerosols from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2 displaying at their own native physical-retrieved spatial resolution. Functionality will include selecting data sources (e.g., multiple parameters under the same measurement), defining area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting and reformatting.

Distributed multimodal data fusion for large scale wireless sensor networks

NASA Astrophysics Data System (ADS)

Ertin, Emre

2006-05-01

Sensor network technology has enabled new surveillance systems where sensor nodes equipped with processing and communication capabilities can collaboratively detect, classify and track targets of interest over a large surveillance area. In this paper we study distributed fusion of multimodal sensor data for extracting target information from a large scale sensor network. Optimal tracking, classification, and reporting of threat events require joint consideration of multiple sensor modalities. Multiple sensor modalities improve tracking by reducing the uncertainty in the track estimates as well as resolving track-sensor data association problems. Our approach to solving the fusion problem with large number of multimodal sensors is construction of likelihood maps. The likelihood maps provide a summary data for the solution of the detection, tracking and classification problem. The likelihood map presents the sensory information in an easy format for the decision makers to interpret and is suitable with fusion of spatial prior information such as maps, imaging data from stand-off imaging sensors. We follow a statistical approach to combine sensor data at different levels of uncertainty and resolution. The likelihood map transforms each sensor data stream to a spatio-temporal likelihood map ideally suitable for fusion with imaging sensor outputs and prior geographic information about the scene. We also discuss distributed computation of the likelihood map using a gossip based algorithm and present simulation results.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information.

PubMed

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-10-27

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information

PubMed Central

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-01-01

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads. PMID:27801794

Ocean Color Data at the Goddard Earth Sciences (GES) DAAC: CZCS, SeaWiFS, OCTS, MODIS-Terra, MODIS-Aqua

NASA Technical Reports Server (NTRS)

2002-01-01

The Goddard Earth Sciences Distributed Active Archive Center (DAAC) is the designated archive for all of the ocean color data produced by NASA satellite missions. The DAAC is a long-term, high volume, secure repository for many different kinds of environmental data. With respect to ocean color, the Goddard DAAC holds all the data obtained during the eight-year mission of the Coastal Zone Color Scanner (CZCS). The DAAC is currently receiving data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and the MODIS-Terra instrument. The DAAC recently received reformatted data from the Ocean Color and Temperature Scanner (OCTS) and will also archive MODIS-Aqua Ocean products. In addition to its archive and distribution services, the Goddard DAAC strives to improve data access, ease-of-use, and data applicability for a broad spectrum of customers. The DAAC's data support teams practice dual roles, both insuring the integrity of the DAAC data archive and serving the user community with answers to user inquiries, online and print documentation, and customized data services.

The on-line detection of biological particle emissions from selected agricultural materials using the WIBS-4 (Waveband Integrated Bioaerosol Sensor) technique

NASA Astrophysics Data System (ADS)

O'Connor, David J.; Healy, David A.; Sodeau, John R.

2013-12-01

Agricultural activities have, for some time, been linked to adverse health effects such as Farmers' lung, hypersensitivity pneumonitis, aspergillosis and chronic obstructive pulmonary disease (COPD) This connection is known to be, at least in part, due to the numerous microbiological organisms that live and grow on materials found in occupational settings such as barns, animal shelters, stables and composting sites. Traditional techniques for determining biological release of fungal spores and bacteria require intensive, experienced human resources and considerable time to determine ambient concentrations. However more recently the fluorescence and light scattering signals obtained from primary biological aerosol particles (PBAP) have been utilised for their near real-time counting and characterisation abilities. In the current study, data collected for the bioaerosol types released from hay and silage were counted and identified using a combination of the WIBS-4 bioaerosol sensor approach and impaction/optical microscopy. Particle emissions were characterised according to particle numbers, their size distributions, particle asymmetry values and fluorescence characteristics. The variables obtained were shown to provide potential “fingerprint” signatures for PBAP emissions emanating from two important compost components, namely, silage and hay. Comparisons between the data acquired by the WIBS-4 bioaerosol sensor, optical microscopy findings and also previous literature suggest that the likely identification of Aspergillus/Penicillium type spores and bacterial species released from hay and silage was achieved on a relatively rapid time-scale.

RF Emitter Tracking and Intent Assessment

DTIC Science & Technology

2013-03-21

telecommunications sector. In 2010 there were 6,000 location-based applications for the iPhone, 900 for the Android and 300 for the Blackberry [2]. An example...Location-Aware Apps Keeps Growing Rapidly - But Very Few are Cross-Platform,” February 2010. [Online]. Available: http: //readwrite.com/2010/02/05...number of location-aware apps keeps growing - but. 3. L. Wang and Q. Xu, “Gps-Free Localization Algorithm for Wireless Sensor Networks,” Sensors, vol. 10

Few-mode fiber based distributed curvature sensor through quasi-single-mode Brillouin frequency shift.

PubMed

Wu, Hao; Wang, Ruoxu; Liu, Deming; Fu, Songnian; Zhao, Can; Wei, Huifeng; Tong, Weijun; Shum, Perry Ping; Tang, Ming

2016-04-01

We proposed and demonstrated a few-mode fiber (FMF) based optical-fiber sensor for distributed curvature measurement through quasi-single-mode Brillouin frequency shift (BFS). By central-alignment splicing FMF and single-mode fiber (SMF) with a fusion taper, a SMF-components-compatible distributed curvature sensor based on FMF is realized using the conventional Brillouin optical time-domain analysis system. The distributed BFS change induced by bending in FMF has been theoretically and experimentally investigated. The precise BFS response to the curvature along the fiber link has been calibrated. A proof-of-concept experiment is implemented to validate its effectiveness in distributed curvature measurement.

Distributed Sensor Nodes Charged by Mobile Charger with Directional Antenna and by Energy Trading for Balancing.

PubMed

Moraes, Celso; Myung, Sunghee; Lee, Sangkeum; Har, Dongsoo

2017-01-10

Provision of energy to wireless sensor networks is crucial for their sustainable operation. Sensor nodes are typically equipped with batteries as their operating energy sources. However, when the sensor nodes are sited in almost inaccessible locations, replacing their batteries incurs high maintenance cost. Under such conditions, wireless charging of sensor nodes by a mobile charger with an antenna can be an efficient solution. When charging distributed sensor nodes, a directional antenna, rather than an omnidirectional antenna, is more energy-efficient because of smaller proportion of off-target radiation. In addition, for densely distributed sensor nodes, it can be more effective for some undercharged sensor nodes to harvest energy from neighboring overcharged sensor nodes than from the remote mobile charger, because this reduces the pathloss of charging signal due to smaller distances. In this paper, we propose a hybrid charging scheme that combines charging by a mobile charger with a directional antenna, and energy trading, e.g., transferring and harvesting, between neighboring sensor nodes. The proposed scheme is compared with other charging scheme. Simulations demonstrate that the hybrid charging scheme with a directional antenna achieves a significant reduction in the total charging time required for all sensor nodes to reach a target energy level.

Distributed Sensor Nodes Charged by Mobile Charger with Directional Antenna and by Energy Trading for Balancing

PubMed Central

Moraes, Celso; Myung, Sunghee; Lee, Sangkeum; Har, Dongsoo

2017-01-01

Provision of energy to wireless sensor networks is crucial for their sustainable operation. Sensor nodes are typically equipped with batteries as their operating energy sources. However, when the sensor nodes are sited in almost inaccessible locations, replacing their batteries incurs high maintenance cost. Under such conditions, wireless charging of sensor nodes by a mobile charger with an antenna can be an efficient solution. When charging distributed sensor nodes, a directional antenna, rather than an omnidirectional antenna, is more energy-efficient because of smaller proportion of off-target radiation. In addition, for densely distributed sensor nodes, it can be more effective for some undercharged sensor nodes to harvest energy from neighboring overcharged sensor nodes than from the remote mobile charger, because this reduces the pathloss of charging signal due to smaller distances. In this paper, we propose a hybrid charging scheme that combines charging by a mobile charger with a directional antenna, and energy trading, e.g., transferring and harvesting, between neighboring sensor nodes. The proposed scheme is compared with other charging scheme. Simulations demonstrate that the hybrid charging scheme with a directional antenna achieves a significant reduction in the total charging time required for all sensor nodes to reach a target energy level. PMID:28075372

Distributed adaptive diagnosis of sensor faults using structural response data

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-10-01

The reliability and consistency of wireless structural health monitoring (SHM) systems can be compromised by sensor faults, leading to miscalibrations, corrupted data, or even data loss. Several research approaches towards fault diagnosis, referred to as ‘analytical redundancy’, have been proposed that analyze the correlations between different sensor outputs. In wireless SHM, most analytical redundancy approaches require centralized data storage on a server for data analysis, while other approaches exploit the on-board computing capabilities of wireless sensor nodes, analyzing the raw sensor data directly on board. However, using raw sensor data poses an operational constraint due to the limited power resources of wireless sensor nodes. In this paper, a new distributed autonomous approach towards sensor fault diagnosis based on processed structural response data is presented. The inherent correlations among Fourier amplitudes of acceleration response data, at peaks corresponding to the eigenfrequencies of the structure, are used for diagnosis of abnormal sensor outputs at a given structural condition. Representing an entirely data-driven analytical redundancy approach that does not require any a priori knowledge of the monitored structure or of the SHM system, artificial neural networks (ANN) are embedded into the sensor nodes enabling cooperative fault diagnosis in a fully decentralized manner. The distributed analytical redundancy approach is implemented into a wireless SHM system and validated in laboratory experiments, demonstrating the ability of wireless sensor nodes to self-diagnose sensor faults accurately and efficiently with minimal data traffic. Besides enabling distributed autonomous fault diagnosis, the embedded ANNs are able to adapt to the actual condition of the structure, thus ensuring accurate and efficient fault diagnosis even in case of structural changes.

Compact Tactile Sensors for Robot Fingers

NASA Technical Reports Server (NTRS)

Martin, Toby B.; Lussy, David; Gaudiano, Frank; Hulse, Aaron; Diftler, Myron A.; Rodriguez, Dagoberto; Bielski, Paul; Butzer, Melisa

2004-01-01

Compact transducer arrays that measure spatial distributions of force or pressure have been demonstrated as prototypes of tactile sensors to be mounted on fingers and palms of dexterous robot hands. The pressure- or force-distribution feedback provided by these sensors is essential for the further development and implementation of robot-control capabilities for humanlike grasping and manipulation.

Innovations in Online Learning: Moving beyond No Significant Difference. The Pew Symposia in Learning and Technology (4th, Phoenix, Arizona, December 8-9, 2000).

ERIC Educational Resources Information Center

Twigg, Carol A.

Symposium participants gathered to discuss how to move online learning beyond being "as good as" traditional education. Participants were asked to analyze their assumptions about distributed learning, identify the strengths of each type of distributed learning discussed, and explore what needs to be done to improve online education. This paper…

Development of a novel pH sensor based upon Janus Green B immobilized on triacetyl cellulose membrane: Experimental design and optimization.

PubMed

Chamkouri, Narges; Niazi, Ali; Zare-Shahabadi, Vali

2016-03-05

A novel pH optical sensor was prepared by immobilizing an azo dye called Janus Green B on the triacetylcellulose membrane. Condition of the dye solution used in the immobilization step, including concentration of the dye, pH, and duration were considered and optimized using the Box-Behnken design. The proposed sensor showed good behavior and precision (RSD<5%) in the pH range of 2.0-10.0. Advantages of this optical sensor include on-line applicability, no leakage, long-term stability (more than 6 months), fast response time (less than 1 min), high selectivity and sensitivity as well as good reversibility and reproducibility. Copyright © 2015. Published by Elsevier B.V.

Adaptive sensor-fault tolerant control for a class of multivariable uncertain nonlinear systems.

PubMed

Khebbache, Hicham; Tadjine, Mohamed; Labiod, Salim; Boulkroune, Abdesselem

2015-03-01

This paper deals with the active fault tolerant control (AFTC) problem for a class of multiple-input multiple-output (MIMO) uncertain nonlinear systems subject to sensor faults and external disturbances. The proposed AFTC method can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. By employing backstepping technique, a novel adaptive backstepping-based AFTC scheme is developed using the fact that sensor faults and system uncertainties (including external disturbances and unexpected nonlinear functions caused by sensor faults) can be on-line estimated and compensated via robust adaptive schemes. The stability analysis of the closed-loop system is rigorously proven using a Lyapunov approach. The effectiveness of the proposed controller is illustrated by two simulation examples. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Distributed fault detection over sensor networks with Markovian switching topologies

NASA Astrophysics Data System (ADS)

Ge, Xiaohua; Han, Qing-Long

2014-05-01

This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.

Energy-efficient sensing in wireless sensor networks using compressed sensing.

PubMed

Razzaque, Mohammad Abdur; Dobson, Simon

2014-02-12

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.

Distributed electrochemical sensors: recent advances and barriers to market adoption.

PubMed

Hoekstra, Rafael; Blondeau, Pascal; Andrade, Francisco J

2018-07-01

Despite predictions of their widespread application in healthcare and environmental monitoring, electrochemical sensors are yet to be distributed at scale, instead remaining largely confined to R&D labs. This contrasts sharply with the situation for physical sensors, which are now ubiquitous and seamlessly embedded in the mature ecosystem provided by electronics and connectivity protocols. Although chemical sensors could be integrated into the same ecosystem, there are fundamental issues with these sensors in the three key areas of analytical performance, usability, and affordability. Nevertheless, advances are being made in each of these fields, leading to hope that the deployment of automated and user-friendly low-cost electrochemical sensors is on the horizon. Here, we present a brief survey of key challenges and advances in the development of distributed electrochemical sensors for liquid samples, geared towards applications in healthcare and wellbeing, environmental monitoring, and homeland security. As will be seen, in many cases the analytical performance of the sensor is acceptable; it is usability that is the major barrier to commercial viability at this moment. Were this to be overcome, the issue of affordability could be addressed. Graphical Abstract ᅟ.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation †

PubMed Central

Nof, Shimon Y.; Edan, Yael

2018-01-01

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors’ performance, tasks’ priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems. PMID:29498683

Distributed dual-parameter optical fiber sensor based on cascaded microfiber Fabry-Pérot interferometers

NASA Astrophysics Data System (ADS)

Xiang, Yang; Luo, Yiyang; Zhang, Wei; Liu, Deming; Sun, Qizhen

2017-04-01

We propose and demonstrate a distributed fiber sensor based on cascaded microfiber Fabry-Perot interferometers (MFPI) for simultaneous refractive index (SRI) and temperature measurement. By employing MFPI which is fabricated by taper-drawing the center of a uniform fiber Bragg grating (FBG) on standard fiber into a section of microfiber, dual parameters including SRI and temperature can be detected through demodulating the reflection spectrum of the MFPI. Further, wavelength-division-multiplexing (WDM) is applied to realize distributed dual-parameter fiber sensor by using cascaded MFPIs with different Bragg wavelengths. A prototype sensor system with 5 cascaded MFPIs is constructed to experimentally demonstrate the sensing performance.

High performance architecture design for large scale fibre-optic sensor arrays using distributed EDFAs and hybrid TDM/DWDM

NASA Astrophysics Data System (ADS)

Liao, Yi; Austin, Ed; Nash, Philip J.; Kingsley, Stuart A.; Richardson, David J.

2013-09-01

A distributed amplified dense wavelength division multiplexing (DWDM) array architecture is presented for interferometric fibre-optic sensor array systems. This architecture employs a distributed erbium-doped fibre amplifier (EDFA) scheme to decrease the array insertion loss, and employs time division multiplexing (TDM) at each wavelength to increase the number of sensors that can be supported. The first experimental demonstration of this system is reported including results which show the potential for multiplexing and interrogating up to 4096 sensors using a single telemetry fibre pair with good system performance. The number can be increased to 8192 by using dual pump sources.

Design and performance investigation of a highly accurate apodized fiber Bragg grating-based strain sensor in single and quasi-distributed systems.

PubMed

Ali, Taha A; Shehata, Mohamed I; Mohamed, Nazmi A

2015-06-01

In this work, fiber Bragg grating (FBG) strain sensors in single and quasi-distributed systems are investigated, seeking high-accuracy measurement. Since FBG-based strain sensors of small lengths are preferred in medical applications, and that causes the full width at half-maximum (FWHM) to be larger, a new apodization profile is introduced for the first time, to the best of our knowledge, with a remarkable FWHM at small sensor lengths compared to the Gaussian and Nuttall profiles, in addition to a higher mainlobe slope at these lengths. A careful selection of apodization profiles with detailed investigation is performed-using sidelobe analysis and the FWHM, which are primary judgment factors especially in a quasi-distributed configuration. A comparison between the elite selection of apodization profiles (extracted from related literature) and the proposed new profile is carried out covering the reflectivity peak, FWHM, and sidelobe analysis. The optimization process concludes that the proposed new profile with a chosen small length (L) of 10 mm and Δn_ac of 1.4×10^-4 is the optimum choice for single stage and quasi-distributed strain-sensor networks, even better than the Gaussian profile at small sensor lengths. The proposed profile achieves the smallest FWHM of 15 GHz (suitable for UDWDM), and the highest mainlobe slope of 130 dB/nm. For the quasi-distributed scenario, a noteworthy high isolation of 6.953 dB is achieved while applying a high strain value of 1500 μstrain (με) for a five-stage strain-sensing network. Further investigation was undertaken, proving that consistency in choosing the apodization profile in the quasi-distributed network is mandatory. A test was made of the inclusion of a uniform apodized sensor among other apodized sensors with the proposed profile in an FBG strain-sensor network.

State Online College Job Market: Ranking the States

ERIC Educational Resources Information Center

Carnevale, Anthony; Jayasundera, Tamara; Repnikov, Dmitri; Gulish, Artem

2015-01-01

"State Online College Job Market: Ranking the States" analyzes the online college labor market on a state-by-state basis. We examine the geographic distribution of online job ads for college graduates within industries and occupational clusters, and compare the relative strength of the online college labor market across states. We…

Functionalized multi-walled carbon nanotube based sensors for distributed methane leak detection

EPA Science Inventory

This paper presents a highly sensitive, energy efficient and low-cost distributed methane (CH4) sensor system (DMSS) for continuous monitoring, detection and localization of CH4 leaks in natural gas infrastructure such as transmission and distribution pipelines, wells, and produc...

Spatial Signal Characteristics of Shallow Paraboloidal Shell Structronic Systems

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last twenty years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of thin flexible membrane shells are not clearly understood. In this paper, modeling of free thin paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Discrete shaped strain sensors for intelligent structures

NASA Technical Reports Server (NTRS)

Andersson, Mark S.; Crawley, Edward F.

1992-01-01

Design of discrete, highly distributed sensor systems for intelligent structures has been studied. Data obtained indicate that discrete strain-averaging sensors satisfy the functional requirements for distributed sensing of intelligent structures. Bartlett and Gauss-Hanning sensors, in particular, provide good wavenumber characteristics while meeting the functional requirements. They are characterized by good rolloff rates and positive Fourier transforms for all wavenumbers. For the numerical integration schemes, Simpson's rule is considered to be very simple to implement and consistently provides accurate results for five sensors or more. It is shown that a sensor system that satisfies the functional requirements can be applied to a structure that supports mode shapes with purely sinusoidal curvature.

SCHeMA open and modular in situ sensing solution

NASA Astrophysics Data System (ADS)

Tercier-Waeber, Marie Louise; Novellino, Antonio

2017-04-01

Marine environments are highly vulnerable and influenced by a wide diversity of anthropogenic and natural substances and organisms that may have adverse effects on the ecosystem equilibrium, on living resources and, ultimately, on human health. Identification of relevant types of hazards at the appropriate temporal and spatial scale is crucial to detect their sources and origin, to understand the processes governing their magnitude and distribution, and to ultimately evaluate and manage their risks and consequences preventing economic losses. This can be addressed only by the development of innovative, compact, rugged, automated, sensor networks allowing long-term monitoring. Development of such tools is a challenging task as it requires many analytical and technical innovations. The FP7-OCEAN 2013-SCHeMA project aims to contribute to meet this challenge by providing an open and modular sensing solution for autonomous in situ high resolution mapping of a range of anthropogenic and natural chemical compounds (trace metals, nutrients, anthropogenic organic compounds, toxic algae species and toxins, species relevant to the carbon cycle). To achieve this, SCHeMA activities focus on the development of : 1) an array of miniature sensor probes taking advantage of various innovative solutions, namely: (polymer-based) gel-integrated sensors; solid state ion-selective membrane sensors coupled to an on-line desalination module; mid-infrared optical sensors; optochemical multichannel devices; enOcean technology; 2) dedicated hardware, firmware and software components allowing their plug-and-play integration, localization as well as wireless bidirectional communication via advanced OGC-SWE wired/wireless dedicated interfaces; 3) a web-based front-end system compatible with EU standard requirements and principles (INSPIRE, GEO/GEOSS) and configured to insure easy interoperability with national, regional and local marine observation systems. This lecture will present examples of innovative approaches and devices successfully developed and currently explored. Potentiality of the SCHeMA individual probes and integrated system to provide new type of high-resolution environmental data will be illustrated by examples of field application in selected coastal areas. www.schema-ocean.eu

Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory.

PubMed

Qin, Jiahu; Fu, Weiming; Gao, Huijun; Zheng, Wei Xing

2016-03-03

This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

Autonomous distributed self-organization for mobile wireless sensor networks.

PubMed

Wen, Chih-Yu; Tang, Hung-Kai

2009-01-01

This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity.

PubMed

Pang, Yu; Zhang, Kunning; Yang, Zhen; Jiang, Song; Ju, Zhenyi; Li, Yuxing; Wang, Xuefeng; Wang, Danyang; Jian, Muqiang; Zhang, Yingying; Liang, Renrong; Tian, He; Yang, Yi; Ren, Tian-Ling

2018-03-27

Recently, wearable pressure sensors have attracted tremendous attention because of their potential applications in monitoring physiological signals for human healthcare. Sensitivity and linearity are the two most essential parameters for pressure sensors. Although various designed micro/nanostructure morphologies have been introduced, the trade-off between sensitivity and linearity has not been well balanced. Human skin, which contains force receptors in a reticular layer, has a high sensitivity even for large external stimuli. Herein, inspired by the skin epidermis with high-performance force sensing, we have proposed a special surface morphology with spinosum microstructure of random distribution via the combination of an abrasive paper template and reduced graphene oxide. The sensitivity of the graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa -1 in a wide linearity range of 0-2.6 kPa. Our pressure sensor exhibits superior comprehensive properties compared with previous surface-modified pressure sensors. According to simulation and mechanism analyses, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range, respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heartbeat, respiration, phonation, and human motions of a pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral, and pronation. The RDS microstructure provides an alternative strategy to improve the performance of pressure sensors and extend their potential applications in monitoring human activities.

Marine realms information bank: A distributed geolibrary for the ocean

USGS Publications Warehouse

Marincioni, F.; Lightsom, F.; ,

2002-01-01

The Marine Realms Information Bank (MRIB) is a prototype web-based distributed geolibrary that organizes, indexes, and delivers online information about the oceanic and coastal environments. It implements the distributed geolibrary concept to organize, index, and deliver online information about the oceanic and coastal environments. The significance of MRIB lies both in the utility of the information bank and in the implementation of the distributed geolibraries concept.

Distributed cluster management techniques for unattended ground sensor networks

NASA Astrophysics Data System (ADS)

Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

2005-05-01

Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also simplify multi-target tracking within the cluster.

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

PubMed Central

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

A Research Program in Computer Technology. Volume 1

DTIC Science & Technology

1981-08-01

rigidity, sensor networks 10. command and control, digital voice communication, graphic input device for terminal, multimedia communications, portable...satellite channel in the internetwork environment; Distributed Sensor Networks - formulation of algorithms and communication protocols to support the...operation of geographically distributed sensors ; Personal Communicator - work intended to result in a demonstration-level portable terminal to test and

UV disinfection in drinking water supplies.

PubMed

Hoyer, O

2000-01-01

UV disinfection has become a practical and safely validatable disinfection procedure by specifying the requirements for testing and monitoring in DVGW standard W 294. A standardized biodosimetric testing procedure and monitoring with standardized UV sensors is introduced and successfully applied. On-line monitoring of irradiance can be counterchecked with handheld reference sensors and makes it possible that UV systems can be used for drinking water disinfection with the same level of confidence and safety as is conventional chemical disinfection.

Optimal Design of the Absolute Positioning Sensor for a High-Speed Maglev Train and Research on Its Fault Diagnosis

PubMed Central

Zhang, Dapeng; Long, Zhiqiang; Xue, Song; Zhang, Junge

2012-01-01

This paper studies an absolute positioning sensor for a high-speed maglev train and its fault diagnosis method. The absolute positioning sensor is an important sensor for the high-speed maglev train to accomplish its synchronous traction. It is used to calibrate the error of the relative positioning sensor which is used to provide the magnetic phase signal. On the basis of the analysis for the principle of the absolute positioning sensor, the paper describes the design of the sending and receiving coils and realizes the hardware and the software for the sensor. In order to enhance the reliability of the sensor, a support vector machine is used to recognize the fault characters, and the signal flow method is used to locate the faulty parts. The diagnosis information not only can be sent to an upper center control computer to evaluate the reliability of the sensors, but also can realize on-line diagnosis for debugging and the quick detection when the maglev train is off-line. The absolute positioning sensor we study has been used in the actual project. PMID:23112619

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

PubMed Central

Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

2017-01-01

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors. PMID:28934163

Compression in wearable sensor nodes: impacts of node topology.

PubMed

Imtiaz, Syed Anas; Casson, Alexander J; Rodriguez-Villegas, Esther

2014-04-01

Wearable sensor nodes monitoring the human body must operate autonomously for very long periods of time. Online and low-power data compression embedded within the sensor node is therefore essential to minimize data storage/transmission overheads. This paper presents a low-power MSP430 compressive sensing implementation for providing such compression, focusing particularly on the impact of the sensor node architecture on the compression performance. Compression power performance is compared for four different sensor nodes incorporating different strategies for wireless transmission/on-sensor-node local storage of data. The results demonstrate that the compressive sensing used must be designed differently depending on the underlying node topology, and that the compression strategy should not be guided only by signal processing considerations. We also provide a practical overview of state-of-the-art sensor node topologies. Wireless transmission of data is often preferred as it offers increased flexibility during use, but in general at the cost of increased power consumption. We demonstrate that wireless sensor nodes can highly benefit from the use of compressive sensing and now can achieve power consumptions comparable to, or better than, the use of local memory.

SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data.

PubMed

Salehi, Ali; Jimenez-Berni, Jose; Deery, David M; Palmer, Doug; Holland, Edward; Rozas-Larraondo, Pablo; Chapman, Scott C; Georgakopoulos, Dimitrios; Furbank, Robert T

2015-01-01

To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au.

FPGA-based fused smart-sensor for tool-wear area quantitative estimation in CNC machine inserts.

PubMed

Trejo-Hernandez, Miguel; Osornio-Rios, Roque Alfredo; de Jesus Romero-Troncoso, Rene; Rodriguez-Donate, Carlos; Dominguez-Gonzalez, Aurelio; Herrera-Ruiz, Gilberto

2010-01-01

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used.

Optical control and diagnostics sensors for gas turbine machinery

NASA Astrophysics Data System (ADS)

Trolinger, James D.; Jenkins, Thomas P.; Heeg, Bauke

2012-10-01

There exists a vast range of optical techniques that have been under development for solving complex measurement problems related to gas-turbine machinery and phenomena. For instance, several optical techniques are ideally suited for studying fundamental combustion phenomena in laboratory environments. Yet other techniques hold significant promise for use as either on-line gas turbine control sensors, or as health monitoring diagnostics sensors. In this paper, we briefly summarize these and discuss, in more detail, some of the latter class of techniques, including phosphor thermometry, hyperspectral imaging and low coherence interferometry, which are particularly suited for control and diagnostics sensing on hot section components with ceramic thermal barrier coatings (TBCs).

Distributed Underwater Sensing: A Paradigm Change for the Future

NASA Astrophysics Data System (ADS)

Yang, T. C.

Distributed netted underwater sensors (DNUS) present a paradigm change that has generated high interest all over the world. It utilizes many small spatially distributed, inexpensive sensors, and a certain number of mobile nodes, such as autonomous underwater vehicles (AUVs), forming a wireless acoustic network to relate data and provide real time monitoring of the ocean. Distributed underwater sensors can be used for oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications over wide areas. These functions were traditionally accomplished by a cabled system, such as an array of sensors deployed from a platform, or a large number of sensors moored on the ocean bottom, connected by a cable. The cabled systems are not only expensive but often require heavy ocean engineering (e.g., equipment to deploy heavy armored cables). In the future, as fabrication technology advances making low cost sensors a reality, DNUS is expected to be affordable and will become the undersea "OceanNet" for the marine industry like the current "internet" on land. This paper gives a layman view of the system concept, the state of the art, and future challenges. One of challenges, of particular interest to this conference, is to develop technologies for miniature-size sensors that are energy efficient, allowing long time deployment in the ocean.

Automated monitoring of recovered water quality

NASA Technical Reports Server (NTRS)

Misselhorn, J. E.; Hartung, W. H.; Witz, S. W.

1974-01-01

Laboratory prototype water quality monitoring system provides automatic system for online monitoring of chemical, physical, and bacteriological properties of recovered water and for signaling malfunction in water recovery system. Monitor incorporates whenever possible commercially available sensors suitably modified.

Continuous Odour Measurement with Chemosensor Systems

NASA Astrophysics Data System (ADS)

Boeker, Peter; Haas, T.; Diekmann, B.; Lammer, P. Schulze

2009-05-01

The continuous odour measurement is a challenging task for chemosensor systems. Firstly, a long term and stable measurement mode must be guaranteed in order to preserve the validity of the time consuming and expensive olfactometric calibration data. Secondly, a method is needed to deal with the incoming sensor data. The continuous online detection of signal patterns, the correlated gas emission and the assigned odour data is essential for the continuous odour measurement. Thirdly, a severe danger of over-fitting in the process of the odour calibration is present, because of the high measurement uncertainty of the olfactometry. In this contribution we present a technical solution for continuous measurements comprising of a hybrid QMB-sensor array and electrochemical cells. A set of software tools enables the efficient data processing and calibration and computes the calibration parameters. The internal software of the measurement systems microcontroller processes the calibration parameters online for the output of the desired odour information.

Research and application of online measurement system of tire tread profile in automobile tire production

NASA Astrophysics Data System (ADS)

Wang, Pengyao; Chen, Xiangguang; Yang, Kai; Liu, Xuejiao

2017-01-01

To improve the measuring efficiency of width and thickness of tire tread in the process of automobile tire production, the actual condition for the tire production process is analyzed, and a fast online measurement system based on moving tire tread of tire specifications is established in this paper. The coordinate data of tire tread profile is acquired by 3D laser sensor, and we use C# language for programming which is an object-oriented programming language to complete the development of client program. The system with laser sensor can provide real-time display of tire tread profile and the data to require in the process of tire production. Experimental results demonstrate that the measuring precision of the system is <= 1mm, it can meet the measurement requirements of the production process, and the system has the characteristics of convenient installation and testing, system stable operation.

On-line remote monitoring of radioactive waste repositories

NASA Astrophysics Data System (ADS)

Calì, Claudio; Cosentino, Luigi; Litrico, Pietro; Pappalardo, Alfio; Scirè, Carlotta; Scirè, Sergio; Vecchio, Gianfranco; Finocchiaro, Paolo; Alfieri, Severino; Mariani, Annamaria

2014-12-01

A low-cost array of modular sensors for online monitoring of radioactive waste was developed at INFN-LNS. We implemented a new kind of gamma counter, based on Silicon PhotoMultipliers and scintillating fibers, that behaves like a cheap scintillating Geiger-Muller counter. It can be placed in shape of a fine grid around each single waste drum in a repository. Front-end electronics and an FPGA-based counting system were developed to handle the field data, also implementing data transmission, a graphical user interface and a data storage system. A test of four sensors in a real radwaste storage site was performed with promising results. Following the tests an agreement was signed between INFN and Sogin for the joint development and installation of a prototype DMNR (Detector Mesh for Nuclear Repository) system inside the Garigliano radwaste repository in Sessa Aurunca (CE, Italy). Such a development is currently under way, with the installation foreseen within 2014.

Characterisation and qualification of natural organic matter with a new online fluorescene sensor

NASA Astrophysics Data System (ADS)

Wagner, Martin; Dahlaus, Anna; Moldaenke, Christian; Schmidt, Wido

2016-04-01

Natural organic water compounds are determined usually with the bulk parameter DOC (dissolved organic carbon). The DOC is a heterogeneous parameter which consists of various organic fractions and shows often spatially as well as temporally a high dynamic range. The fluorescence spectroscopy is a tool for measuring individual DOC groups in a quick and easy way. A fluorescence sensor was developed within the framework of a research project that provides online detection of humic substances and organic polymers. Humic substances can be differentiated fulvic and humic acids, bio-polymers in proteins and algal chlorophyll-a. The chlorophyll fluorescence can be additionally assigned to green algae and diatoms as well as in cyanobacteria. The sensor has been tested during several measurement programs and was used in various waterworks for monitoring of raw water and treated water. The sensor is based on LED technology, works long term stable and is of low maintenance due to an autonomous cleaning unit. Using the sensor qualitative and quantitative changes of the raw water during drinking water treatment could be estimated efficiently. The processing stage of flocculation/filtration showed a significant reduction in the humic substances concentration, where macromolecular humic acids were removed with higher efficiency than low molecular weighted fulvic acids. Dynamical, seasonal-related processes in the water body of a drinking water reservoir could also be traced. Seasonal and single-event-related changes in temperature, turbidity and the composition of humic substances and algae were collected with high sensitivity for example during the autumn circulation in the water body.

Summary of the First Network-Centric Sensing Community Workshop, ’Netted Sensors: A Government, Industry and Academia Dialogue’

DTIC Science & Technology

2006-04-01

and Scalability, (2) Sensors and Platforms, (3) Distributed Computing and Processing , (4) Information Management, (5) Fusion and Resource Management...use of the deployed system. 3.3 Distributed Computing and Processing Session The Distributed Computing and Processing Session consisted of three

Data-driven strategies for robust forecast of continuous glucose monitoring time-series.

PubMed

Fiorini, Samuele; Martini, Chiara; Malpassi, Davide; Cordera, Renzo; Maggi, Davide; Verri, Alessandro; Barla, Annalisa

2017-07-01

Over the past decade, continuous glucose monitoring (CGM) has proven to be a very resourceful tool for diabetes management. To date, CGM devices are employed for both retrospective and online applications. Their use allows to better describe the patients' pathology as well as to achieve a better control of patients' level of glycemia. The analysis of CGM sensor data makes possible to observe a wide range of metrics, such as the glycemic variability during the day or the amount of time spent below or above certain glycemic thresholds. However, due to the high variability of the glycemic signals among sensors and individuals, CGM data analysis is a non-trivial task. Standard signal filtering solutions fall short when an appropriate model personalization is not applied. State-of-the-art data-driven strategies for online CGM forecasting rely upon the use of recursive filters. Each time a new sample is collected, such models need to adjust their parameters in order to predict the next glycemic level. In this paper we aim at demonstrating that the problem of online CGM forecasting can be successfully tackled by personalized machine learning models, that do not need to recursively update their parameters.

Social voting advice applications-definitions, challenges, datasets and evaluation.

PubMed

Katakis, Ioannis; Tsapatsoulis, Nicolas; Mendez, Fernando; Triga, Vasiliki; Djouvas, Constantinos

2014-07-01

Voting advice applications (VAAs) are online tools that have become increasingly popular and purportedly aid users in deciding which party/candidate to vote for during an election. In this paper we present an innovation to current VAA design which is based on the introduction of a social network element. We refer to this new type of online tool as a social voting advice application (SVAA). SVAAs extend VAAs by providing (a) community-based recommendations, (b) comparison of users' political opinions, and (c) a channel of user communication. In addition, SVAAs enriched with data mining modules, can operate as citizen sensors recording the sentiment of the electorate on issues and candidates. Drawing on VAA datasets generated by the Preference Matcher research consortium, we evaluate the results of the first VAA-Choose4Greece-which incorporated social voting features and was launched during the landmark Greek national elections of 2012. We demonstrate how an SVAA can provide community based features and, at the same time, serve as a citizen sensor. Evaluation of the proposed techniques is realized on a series of datasets collected from various VAAs, including Choose4Greece. The collection is made available online in order to promote research in the field.

Influence of the internal wall thickness of electrical capacitance tomography sensors on image quality

NASA Astrophysics Data System (ADS)

Liang, Shiguo; Ye, Jiamin; Wang, Haigang; Wu, Meng; Yang, Wuqiang

2018-03-01

In the design of electrical capacitance tomography (ECT) sensors, the internal wall thickness can vary with specific applications, and it is a key factor that influences the sensitivity distribution and image quality. This paper will discuss the effect of the wall thickness of ECT sensors on image quality. Three flow patterns are simulated for wall thicknesses of 2.5 mm to 15 mm on eight-electrode ECT sensors. The sensitivity distributions and potential distributions are compared for different wall thicknesses. Linear back-projection and Landweber iteration algorithms are used for image reconstruction. Relative image error and correlation coefficients are used for image evaluation using both simulation and experimental data.

Distributed transition-edge sensors for linearized position response in a phonon-mediated X-ray imaging spectrometer

NASA Astrophysics Data System (ADS)

Cabrera, Blas; Brink, Paul L.; Leman, Steven W.; Castle, Joseph P.; Tomada, Astrid; Young, Betty A.; Martínez-Galarce, Dennis S.; Stern, Robert A.; Deiker, Steve; Irwin, Kent D.

2004-03-01

For future solar X-ray satellite missions, we are developing a phonon-mediated macro-pixel composed of a Ge crystal absorber with four superconducting transition-edge sensors (TES) distributed on the backside. The X-rays are absorbed on the opposite side and the energy is converted into phonons, which are absorbed into the four TES sensors. By connecting together parallel elements into four channels, fractional total energy absorbed between two of the sensors provides x-position information and the other two provide y-position information. We determine the optimal distribution for the TES sub-elements to obtain linear position information while minimizing the degradation of energy resolution.

Parallel task processing of very large datasets

NASA Astrophysics Data System (ADS)

Romig, Phillip Richardson, III

This research concerns the use of distributed computer technologies for the analysis and management of very large datasets. Improvements in sensor technology, an emphasis on global change research, and greater access to data warehouses all are increase the number of non-traditional users of remotely sensed data. We present a framework for distributed solutions to the challenges of datasets which exceed the online storage capacity of individual workstations. This framework, called parallel task processing (PTP), incorporates both the task- and data-level parallelism exemplified by many image processing operations. An implementation based on the principles of PTP, called Tricky, is also presented. Additionally, we describe the challenges and practical issues in modeling the performance of parallel task processing with large datasets. We present a mechanism for estimating the running time of each unit of work within a system and an algorithm that uses these estimates to simulate the execution environment and produce estimated runtimes. Finally, we describe and discuss experimental results which validate the design. Specifically, the system (a) is able to perform computation on datasets which exceed the capacity of any one disk, (b) provides reduction of overall computation time as a result of the task distribution even with the additional cost of data transfer and management, and (c) in the simulation mode accurately predicts the performance of the real execution environment.

Online location of a break in water distribution systems

NASA Astrophysics Data System (ADS)

Liang, Jianwen; Xiao, Di; Zhao, Xinhua; Zhang, Hongwei

2003-08-01

Breaks often occur to urban water distribution systems under severely cold weather, or due to corrosion of pipes, deformation of ground, etc., and the breaks cannot easily be located, especially immediately after the events. This paper develops a methodology to locate a break in a water distribution system by monitoring water pressure online at some nodes in the water distribution system. For the purpose of online monitoring, supervisory control and data acquisition (SCADA) technology can well be used. A neural network-based inverse analysis method is constructed for locating the break based on the variation of water pressure. The neural network is trained by using analytically simulated data from the water distribution system, and validated by using a set of data that have never been used in the training. It is found that the methodology provides a quick, effective, and practical way in which a break in a water distribution system can be located.

Analyzing spatial coherence using a single mobile field sensor.

PubMed

Fridman, Peter

2007-04-01

According to the Van Cittert-Zernike theorem, the intensity distribution of a spatially incoherent source and the mutual coherence function of the light impinging on two wave sensors are related. It is the comparable relationship using a single mobile sensor moving at a certain velocity relative to the source that is calculated in this paper. The auto-corelation function of the electric field at the sensor contains information about the intensity distribution. This expression could be employed in aperture synthesis.

Air Pollution Monitoring and Mining Based on Sensor Grid in London

PubMed Central

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-01-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a two-layer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm. PMID:27879895

Air Pollution Monitoring and Mining Based on Sensor Grid in London.

PubMed

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-06-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.

Development of anomaly detection models for deep subsurface monitoring

NASA Astrophysics Data System (ADS)

Sun, A. Y.

2017-12-01

Deep subsurface repositories are used for waste disposal and carbon sequestration. Monitoring deep subsurface repositories for potential anomalies is challenging, not only because the number of sensor networks and the quality of data are often limited, but also because of the lack of labeled data needed to train and validate machine learning (ML) algorithms. Although physical simulation models may be applied to predict anomalies (or the system's nominal state for that sake), the accuracy of such predictions may be limited by inherent conceptual and parameter uncertainties. The main objective of this study was to demonstrate the potential of data-driven models for leakage detection in carbon sequestration repositories. Monitoring data collected during an artificial CO2 release test at a carbon sequestration repository were used, which include both scalar time series (pressure) and vector time series (distributed temperature sensing). For each type of data, separate online anomaly detection algorithms were developed using the baseline experiment data (no leak) and then tested on the leak experiment data. Performance of a number of different online algorithms was compared. Results show the importance of including contextual information in the dataset to mitigate the impact of reservoir noise and reduce false positive rate. The developed algorithms were integrated into a generic Web-based platform for real-time anomaly detection.

The Simple Concurrent Online Processing System (SCOPS) - An open-source interface for remotely sensed data processing

NASA Astrophysics Data System (ADS)

Warren, M. A.; Goult, S.; Clewley, D.

2018-06-01

Advances in technology allow remotely sensed data to be acquired with increasingly higher spatial and spectral resolutions. These data may then be used to influence government decision making and solve a number of research and application driven questions. However, such large volumes of data can be difficult to handle on a single personal computer or on older machines with slower components. Often the software required to process data is varied and can be highly technical and too advanced for the novice user to fully understand. This paper describes an open-source tool, the Simple Concurrent Online Processing System (SCOPS), which forms part of an airborne hyperspectral data processing chain that allows users accessing the tool over a web interface to submit jobs and process data remotely. It is demonstrated using Natural Environment Research Council Airborne Research Facility (NERC-ARF) instruments together with other free- and open-source tools to take radiometrically corrected data from sensor geometry into geocorrected form and to generate simple or complex band ratio products. The final processed data products are acquired via an HTTP download. SCOPS can cut data processing times and introduce complex processing software to novice users by distributing jobs across a network using a simple to use web interface.

On-line classification of pollutants in water using wireless portable electronic noses.

PubMed

Herrero, José Luis; Lozano, Jesús; Santos, José Pedro; Suárez, José Ignacio

2016-06-01

A portable electronic nose with database connection for on-line classification of pollutants in water is presented in this paper. It is a hand-held, lightweight and powered instrument with wireless communications capable of standalone operation. A network of similar devices can be configured for distributed measurements. It uses four resistive microsensors and headspace as sampling method for extracting the volatile compounds from glass vials. The measurement and control program has been developed in LabVIEW using the database connection toolkit to send the sensors data to a server for training and classification with Artificial Neural Networks (ANNs). The use of a server instead of the microprocessor of the e-nose increases the capacity of memory and the computing power of the classifier and allows external users to perform data classification. To address this challenge, this paper also proposes a web-based framework (based on RESTFul web services, Asynchronous JavaScript and XML and JavaScript Object Notation) that allows remote users to train ANNs and request classification values regardless user's location and the type of device used. Results show that the proposed prototype can discriminate the samples measured (Blank water, acetone, toluene, ammonia, formaldehyde, hydrogen peroxide, ethanol, benzene, dichloromethane, acetic acid, xylene and dimethylacetamide) with a 94% classification success rate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of information theoretic divergences for sensor management

NASA Astrophysics Data System (ADS)

Yang, Chun; Kadar, Ivan; Blasch, Erik; Bakich, Michael

2011-06-01

In this paper, we compare the information-theoretic metrics of the Kullback-Leibler (K-L) and Renyi (α) divergence formulations for sensor management. Information-theoretic metrics have been well suited for sensor management as they afford comparisons between distributions resulting from different types of sensors under different actions. The difference in distributions can also be measured as entropy formulations to discern the communication channel capacity (i.e., Shannon limit). In this paper, we formulate a sensor management scenario for target tracking and compare various metrics for performance evaluation as a function of the design parameter (α) so as to determine which measures might be appropriate for sensor management given the dynamics of the scenario and design parameter.

Fiber optic evanescent wave biosensor

NASA Astrophysics Data System (ADS)

Duveneck, Gert L.; Ehrat, Markus; Widmer, H. M.

1991-09-01

The role of modern analytical chemistry is not restricted to quality control and environmental surveillance, but has been extended to process control using on-line analytical techniques. Besides industrial applications, highly specific, ultra-sensitive biochemical analysis becomes increasingly important as a diagnostic tool, both in central clinical laboratories and in the doctor's office. Fiber optic sensor technology can fulfill many of the requirements for both types of applications. As an example, the experimental arrangement of a fiber optic sensor for biochemical affinity assays is presented. The evanescent electromagnetic field, associated with a light ray guided in an optical fiber, is used for the excitation of luminescence labels attached to the biomolecules in solution to be analyzed. Due to the small penetration depth of the evanescent field into the medium, the generation of luminescence is restricted to the close proximity of the fiber, where, e.g., the luminescent analyte molecules combine with their affinity partners, which are immobilized on the fiber. Both cw- and pulsed light excitation can be used in evanescent wave sensor technology, enabling the on-line observation of an affinity assay on a macroscopic time scale (seconds and minutes), as well as on a microscopic, molecular time scale (nanoseconds or microseconds).

Blade resonance parameter identification based on tip-timing method without the once-per revolution sensor

NASA Astrophysics Data System (ADS)

Guo, Haotian; Duan, Fajie; Zhang, Jilong

2016-01-01

Blade tip-timing is the most effective method for blade vibration online measurement of turbomachinery. In this article a synchronous resonance vibration measurement method of blade based on tip-timing is presented. This method requires no once-per revolution sensor which makes it more generally applicable in the condition where this sensor is difficult to install, especially for the high-pressure rotors of dual-rotor engines. Only three casing mounted probes are required to identify the engine order, amplitude, natural frequency and the damping coefficient of the blade. A method is developed to identify the blade which a tip-timing data belongs to without once-per revolution sensor. Theoretical analyses of resonance parameter measurement are presented. Theoretic error of the method is investigated and corrected. Experiments are conducted and the results indicate that blade resonance parameter identification is achieved without once-per revolution sensor.

Online Toxicity Monitors (OTM) for Distribution System Water Quality Monitoring

EPA Science Inventory

Drinking water distribution systems in the U.S. are vulnerable to episodic contamination events (both unintentional and intentional). The U.S. Environmental Protection Agency (EPA) is conducting research to investigate the use of broad-spectrum online toxicity monitors (OTMs) in ...

Laser beam welding quality monitoring system based in high-speed (10 kHz) uncooled MWIR imaging sensors

NASA Astrophysics Data System (ADS)

Linares, Rodrigo; Vergara, German; Gutiérrez, Raúl; Fernández, Carlos; Villamayor, Víctor; Gómez, Luis; González-Camino, Maria; Baldasano, Arturo; Castro, G.; Arias, R.; Lapido, Y.; Rodríguez, J.; Romero, Pablo

2015-05-01

The combination of flexibility, productivity, precision and zero-defect manufacturing in future laser-based equipment are a major challenge that faces this enabling technology. New sensors for online monitoring and real-time control of laserbased processes are necessary for improving products quality and increasing manufacture yields. New approaches to fully automate processes towards zero-defect manufacturing demand smarter heads where lasers, optics, actuators, sensors and electronics will be integrated in a unique compact and affordable device. Many defects arising in laser-based manufacturing processes come from instabilities in the dynamics of the laser process. Temperature and heat dynamics are key parameters to be monitored. Low cost infrared imagers with high-speed of response will constitute the next generation of sensors to be implemented in future monitoring and control systems for laser-based processes, capable to provide simultaneous information about heat dynamics and spatial distribution. This work describes the result of using an innovative low-cost high-speed infrared imager based on the first quantum infrared imager monolithically integrated with Si-CMOS ROIC of the market. The sensor is able to provide low resolution images at frame rates up to 10 KHz in uncooled operation at the same cost as traditional infrared spot detectors. In order to demonstrate the capabilities of the new sensor technology, a low-cost camera was assembled on a standard production laser welding head, allowing to register melting pool images at frame rates of 10 kHz. In addition, a specific software was developed for defect detection and classification. Multiple laser welding processes were recorded with the aim to study the performance of the system and its application to the real-time monitoring of laser welding processes. During the experiments, different types of defects were produced and monitored. The classifier was fed with the experimental images obtained. Self-learning strategies were implemented with very promising results, demonstrating the feasibility of using low-cost high-speed infrared imagers in advancing towards a real-time / in-line zero-defect production systems.

Fiber optic distributed temperature sensor mapping of a jet-mixing flow field

DOE PAGES

Lomperski, Stephen; Gerardi, Craig; Pointer, William David

2015-03-04

In this paper, we introduce the use of a Rayleigh backscatter-based distributed fiber optic sensor to map the temperature field in air flow for a thermal fatigue application. The experiment involves a pair of air jets at 22 and 70°C discharging from 136 mm hexagonal channels into a 1 × 1 × 1.7 m tank at atmospheric pressure. A 40 m-long, Φ155 µm fiber optic sensor was wound back and forth across the tank midplane to form 16 horizontal measurement sections with a vertical spacing of 51 mm. This configuration generated a 2D temperature map with 2800 data points overmore » a 0.76 × 1.7 m plane. Fiber optic sensor readings were combined with PIV and infrared measurements to relate flow field characteristics to the thermal signature of the tank lid. The paper includes sensor stability data and notes issues encountered using the distributed temperature sensor in a flow field. In conclusion, sensors are sensitive to strain and humidity, and so accuracy relies upon strict control of both.« less

Fiber optic distributed temperature sensor mapping of a jet-mixing flow field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lomperski, Stephen; Gerardi, Craig; Pointer, William David

In this paper, we introduce the use of a Rayleigh backscatter-based distributed fiber optic sensor to map the temperature field in air flow for a thermal fatigue application. The experiment involves a pair of air jets at 22 and 70°C discharging from 136 mm hexagonal channels into a 1 × 1 × 1.7 m tank at atmospheric pressure. A 40 m-long, Φ155 µm fiber optic sensor was wound back and forth across the tank midplane to form 16 horizontal measurement sections with a vertical spacing of 51 mm. This configuration generated a 2D temperature map with 2800 data points overmore » a 0.76 × 1.7 m plane. Fiber optic sensor readings were combined with PIV and infrared measurements to relate flow field characteristics to the thermal signature of the tank lid. The paper includes sensor stability data and notes issues encountered using the distributed temperature sensor in a flow field. In conclusion, sensors are sensitive to strain and humidity, and so accuracy relies upon strict control of both.« less

Distributed sensing of RC beams with HCFRP sensors

NASA Astrophysics Data System (ADS)

Yang, Caiqian; Wu, Zhishen; Ye, Lieping

2005-05-01

This paper addresses a novel type of hybrid carbon fiber-reinforced polymer (HCFRP) sensors suitable for the structural health monitoring (SHM) of civil engineering structures. The HCFRP sensors are composed of different types of carbon tows, which are active materials due to their electrical conductivity, piezoresistivity, excellent mechanical properties and resistance to corrosion. The HCFRP sensors are designed to comprise three types of carbon tows-high strength (HS), high modulus (HM) and middle modulus (MM), in order to realize a distributed and broad-based sensing function. Two types of HCFRP sensors, with and without pretreatment, are fabricated and investigated. The HCFRP sensors are bonded with epoxy resins on the bottom concrete surface of RC beam specimens to monitor the average strain, the initiation and propagation of cracks. The experimental results indicate that such kinds of sensors are characterized with broad-based and distributed sensing feasibilities. As a result, the structural health of the RC beams can be monitored and evaluated through characterizing the relationships between the change in electrical resistance of the HCFRP sensors, the average strain and the crack width of the RC beams. In addition, it is also revealed that the damages can also be located by properly adding the number of electrodes.

Upper Klamath Basin Landsat Image for May 30, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for April 28, 2006: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for June 24, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-7 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 11, 2004: Path 45 Rows 30 and 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This image is a mosaic of Landsat-7 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Upper Klamath Basin Landsat Image for July 10, 2006: Path 44 Row 31

USGS Publications Warehouse

Snyder, Daniel T.

2012-01-01

This subset of a Landsat-7 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

NASA Astrophysics Data System (ADS)

Schlichting, A.; Brenner, C.

2016-06-01

LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

Current trends in molecular sensing

NASA Astrophysics Data System (ADS)

Wlodarski, Wojtek

1992-08-01

The biosphere contains a myriad of substances which can influence or stimulate various aspects of the health and behavior of living organisms. Not surprisingly, in the last decade or so researchers have appreciated the potential of developing a range of molecular sensor technologies, designed to estimate and monitor biological and chemical substances with a view to eventually controlling the biological processes themselves. This development has been accelerated recently by the realization that molecular sensors offer considerable commercial potential. At the same time, it was quickly appreciated that such sensors could revolutionize several areas, including health care, pollution and contamination monitoring, agriculture, on-line monitoring and control of industrial chemical processing, and strategic and tactical monitoring of chemical warfare. This brief review considers the changing scene in molecular sensor research by reference to a few key examples.

Signal processing for distributed sensor concept: DISCO

NASA Astrophysics Data System (ADS)

Rafailov, Michael K.

2007-04-01

Distributed Sensor concept - DISCO proposed for multiplication of individual sensor capabilities through cooperative target engagement. DISCO relies on ability of signal processing software to format, to process and to transmit and receive sensor data and to exploit those data in signal synthesis process. Each sensor data is synchronized formatted, Signal-to-Noise Ration (SNR) enhanced and distributed inside of the sensor network. Signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique that was initially proposed [1] as a way to improve the SNR, reduce data rate and mitigate FPA correlated noise of an individual sensor digital video-signal processing. In Distributed Sensor Concept RAFIL technique is used in segmented way, when constituencies of the technique are spatially and/or temporally separated between transmitters and receivers. Those constituencies include though not limited to two thresholds - one is tuned for optimum probability of detection, the other - to manage required false alarm rate, and limited frame integration placed somewhere between the thresholds as well as formatters, conventional integrators and more. RAFIL allows a non-linear integration that, along with SNR gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability [2]. DISCO architecture allows flexible optimization of SNR gain, data rates and noise suppression on sensor's side and limited integration, re-formatting and final threshold on node's side. DISCO with Recursive Adaptive Frame Integration of Limited data may have flexible architecture that allows segmenting the hardware and software to be best suitable for specific DISCO applications and sensing needs - whatever it is air-or-space platforms, ground terminals or integration of sensors network.

Numerical analysis of the blade tip-timing signal of a fiber bundle sensor probe

NASA Astrophysics Data System (ADS)

Guo, Haotian; Duan, Fajie; Cheng, Zhonghai

2015-03-01

Blade tip-timing is the most effective method for online blade vibration measurement of large rotating machines like turbine engines. Fiber bundle sensors are utilized in tip-timing system to measure the arrival time of the blade. The model of the tip-timing signal of the fiber bundle sensor is established. Experiments are conducted and the results are in concordance with the model established. The rising speed of the tip-timing signal is analyzed. To minimize the tip-timing error, the effects of the clearance change between the sensor and the blade and the deflection of the tip surface are analyzed. Simulation results indicate that the variable gain amplifier, which amplifies the signals to a similar level, can eliminate the measurement error caused by the variation of the clearance between the sensor and blade. Increasing the clearance between the sensor and blade can reduce the measurement error introduced by deflection of the tip surface.

Lag compensation of optical fibers or thermocouples to achieve waveform fidelity in dynamic gas pyrometry

NASA Technical Reports Server (NTRS)

Warshawsky, I.

1991-01-01

Fidelity of waveform reproduction requires constant amplitude ratio and constant time lag of a temperature sensor's indication, at all frequencies of interest. However, heat-transfer type sensors usually cannot satisfy these requirements. Equations for the actual indication of a thermocouple and an optical-fiber pyrometer are given explicitly, in terms of sensor and flowing-gas properties. A practical, realistic design of each type of sensor behaves like a first-order system with amplitude-ratio attenuation inversely proportional to frequency when the frequency exceeds the corner frequency. Only at much higher frequencies does the amplitude-ratio attenuation for the optical fiber sensor become inversely proportional to the square root of the frequency. Design options for improving the frequency response are discussed. On-line electrical lag compensation, using a linear amplifier and a passive compensation network, can extend the corner frequency of the thermocouple 100-fold or more; a similar passive network can be used for the optical-fiber sensor. Design details for these networks are presented.

Sensing and Measurement Architecture for Grid Modernization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taft, Jeffrey D.; De Martini, Paul

2016-02-01

This paper addresses architecture for grid sensor networks, with primary emphasis on distribution grids. It describes a forward-looking view of sensor network architecture for advanced distribution grids, and discusses key regulatory, financial, and planning issues.

Pilot Program for the Development of Classification and Accuracy Assessment Methods and Improved Accessibility for Landsat and Related GIS Data and Technology Transfer of These Methods to State and Local Governments

NASA Technical Reports Server (NTRS)

Limp, W. Fredrick

1996-01-01

This project has a single, comprehensive objective that is manifested in many tangible products and impacts throughout the state and the mid-south region. The primary objective or mission of this project is to expose the broadest possible cross-section of public sector decision makers responsible for developing and maintaining policy at the state, local and national levels, private sector professionals and students to the power, flexibility and utility of sensor based imagery and the mapping and interpretive products that are derived from these digital geodata. In accomplishing this mission this project has worked to provide hands-on exposure and training to primary and secondary teachers; developed and distributed instructional materials to students across the state; created an on-line archive of satellite images and related geographic data; implemented a service that enables users throughout the region and around the world to develop customized mapping products suitable for visualization and/or decision support from the comfort of their classroom or office via an internet connection to our facility; extended the use of sensor based imagery in natural resource management and commercial applications through a range of pilot research initiatives, demonstrations, presentations and professional papers.

Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys.

PubMed

Mastrandrea, Rossana; Fournet, Julie; Barrat, Alain

2015-01-01

Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations.

Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys

PubMed Central

Mastrandrea, Rossana; Fournet, Julie; Barrat, Alain

2015-01-01

Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations. PMID:26325289

Intelligent optical fiber sensor system for measurement of gas concentration

NASA Astrophysics Data System (ADS)

Pan, Jingming; Yin, Zongmin

1991-08-01

A measuring, controlling, and alarming system for the concentration of a gas or transparent liquid is described. In this system, a Fabry-Perot etalon with an optical fiber is used as the sensor, a charge-coupled device (CCD) is used as the photoelectric converter, and a single- chip microcomputer 8031 along with an interface circuit is used to measure the interference ring signal. The system has such features as real-time and on-line operation, continuous dynamic handling, and intelligent control.

Stability of Fiber Optic Networked Decentralized Distributed Engine Control Under Time Delays

DTIC Science & Technology

2009-08-01

Nomenclature FADEC = Full Authority Digital Engine Control D2FADEC = Decentralized Distributed Full Authority Digital Engine Control DEC...Corporation (IFOS), bm@ifos.com. I American Institute of Aeronautics and Astronautics 2 II. Distributed Engine Control Systems FADEC Based on...of Full Authority Digital Engine Control ( FADEC ) are distributed at the component level. Each sensor/actuator is to be replaced by a smart sensor

Facility Monitoring: A Qualitative Theory for Sensor Fusion

NASA Technical Reports Server (NTRS)

Figueroa, Fernando

2001-01-01

Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.

Online monitoring of seismic damage in water distribution systems

NASA Astrophysics Data System (ADS)

Liang, Jianwen; Xiao, Di; Zhao, Xinhua; Zhang, Hongwei

2004-07-01

It is shown that water distribution systems can be damaged by earthquakes, and the seismic damages cannot easily be located, especially immediately after the events. Earthquake experiences show that accurate and quick location of seismic damage is critical to emergency response of water distribution systems. This paper develops a methodology to locate seismic damage -- multiple breaks in a water distribution system by monitoring water pressure online at limited positions in the water distribution system. For the purpose of online monitoring, supervisory control and data acquisition (SCADA) technology can well be used. A neural network-based inverse analysis method is constructed for locating the seismic damage based on the variation of water pressure. The neural network is trained by using analytically simulated data from the water distribution system, and validated by using a set of data that have never been used in the training. It is found that the methodology provides an effective and practical way in which seismic damage in a water distribution system can be accurately and quickly located.

Online analysis and process control in recombinant protein production (review).

PubMed

Palmer, Shane M; Kunji, Edmund R S

2012-01-01

Online analysis and control is essential for efficient and reproducible bioprocesses. A key factor in real-time control is the ability to measure critical variables rapidly. Online in situ measurements are the preferred option and minimize the potential loss of sterility. The challenge is to provide sensors with a good lifespan that withstand harsh bioprocess conditions, remain stable for the duration of a process without the need for recalibration, and offer a suitable working range. In recent decades, many new techniques that promise to extend the possibilities of analysis and control, not only by providing new parameters for analysis, but also through the improvement of accepted, well practiced, measurements have arisen.

Convergence Rate Analysis of Distributed Gossip (Linear Parameter) Estimation: Fundamental Limits and Tradeoffs

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-08-01

The paper considers gossip distributed estimation of a (static) distributed random field (a.k.a., large scale unknown parameter vector) observed by sparsely interconnected sensors, each of which only observes a small fraction of the field. We consider linear distributed estimators whose structure combines the information \\emph{flow} among sensors (the \\emph{consensus} term resulting from the local gossiping exchange among sensors when they are able to communicate) and the information \\emph{gathering} measured by the sensors (the \\emph{sensing} or \\emph{innovations} term.) This leads to mixed time scale algorithms--one time scale associated with the consensus and the other with the innovations. The paper establishes a distributed observability condition (global observability plus mean connectedness) under which the distributed estimates are consistent and asymptotically normal. We introduce the distributed notion equivalent to the (centralized) Fisher information rate, which is a bound on the mean square error reduction rate of any distributed estimator; we show that under the appropriate modeling and structural network communication conditions (gossip protocol) the distributed gossip estimator attains this distributed Fisher information rate, asymptotically achieving the performance of the optimal centralized estimator. Finally, we study the behavior of the distributed gossip estimator when the measurements fade (noise variance grows) with time; in particular, we consider the maximum rate at which the noise variance can grow and still the distributed estimator being consistent, by showing that, as long as the centralized estimator is consistent, the distributed estimator remains consistent.

A Virtual Hosting Environment for Distributed Online Gaming

NASA Astrophysics Data System (ADS)

Brossard, David; Prieto Martinez, Juan Luis

With enterprise boundaries becoming fuzzier, it’s become clear that businesses need to share resources, expose services, and interact in many different ways. In order to achieve such a distribution in a dynamic, flexible, and secure way, we have designed and implemented a virtual hosting environment (VHE) which aims at integrating business services across enterprise boundaries and virtualising the ICT environment within which these services operate in order to exploit economies of scale for the businesses as well as achieve shorter concept-to-market time scales. To illustrate the relevance of the VHE, we have applied it to the online gaming world. Online gaming is an early adopter of distributed computing and more than 30% of gaming developer companies, being aware of the shift, are focusing on developing high performance platforms for the new online trend.

Distributed measurement of high electric current by means of polarimetric optical fiber sensor.

PubMed

Palmieri, Luca; Sarchi, Davide; Galtarossa, Andrea

2015-05-04

A novel distributed optical fiber sensor for spatially resolved monitoring of high direct electric current is proposed and analyzed. The sensor exploits Faraday rotation and is based on the polarization analysis of the Rayleigh backscattered light. Preliminary laboratory tests, performed on a section of electric cable for currents up to 2.5 kA, have confirmed the viability of the method.

Colour cyclic code for Brillouin distributed sensors

NASA Astrophysics Data System (ADS)

Le Floch, Sébastien; Sauser, Florian; Llera, Miguel; Rochat, Etienne

2015-09-01

For the first time, a colour cyclic coding (CCC) is theoretically and experimentally demonstrated for Brillouin optical time-domain analysis (BOTDA) distributed sensors. Compared to traditional intensity-modulated cyclic codes, the code presents an additional gain of √2 while keeping the same number of sequences as for a colour coding. A comparison with a standard BOTDA sensor is realized and validates the theoretical coding gain.

Distributed Data-aggregation Consensus for Sensor Networks: Global Connectivity Assessment through Local Data Exchange

DTIC Science & Technology

2014-08-01

Distributed data-aggregation consensus for sensor networks Global connectivity assessment through local data exchange A. Ajorlou Concordia...k − i) i = 1, 2, ..., k − 1 3 Acoustic Channel Characterization *! f

Three-Axis Ground Reaction Force Distribution during Straight Walking.

PubMed

Hori, Masataka; Nakai, Akihito; Shimoyama, Isao

2017-10-24

We measured the three-axis ground reaction force (GRF) distribution during straight walking. Small three-axis force sensors composed of rubber and sensor chips were fabricated and calibrated. After sensor calibration, 16 force sensors were attached to the left shoe. The three-axis force distribution during straight walking was measured, and the local features of the three-axis force under the sole of the shoe were analyzed. The heel area played a role in receiving the braking force, the base area of the fourth and fifth toes applied little vertical or shear force, the base area of the second and third toes generated a portion of the propulsive force and received a large vertical force, and the base area of the big toe helped move the body's center of mass to the other foot. The results demonstrate that measuring the three-axis GRF distribution is useful for a detailed analysis of bipedal locomotion.

Differential pressure distribution measurement for the development of insect-sized wings

NASA Astrophysics Data System (ADS)

Takahashi, Hidetoshi; Matsumoto, Kiyoshi; Shimoyama, Isao

2013-05-01

This paper reports on the measurement of the differential pressure distribution over a flat, thin wing using a micro-electro-mechanical systems sensor. Sensors featuring a piezoresistive cantilever were attached to a polyimide/Cu wing. Because the weight of the cantilever element was less than 10 ng, the sensor can measure the differential pressure without interference from inertial forces, such as wing flapping motions. The dimensions of the sensor chips and the wing were 1.0 mm × 1.0 mm × 0.3 mm and 100 mm × 30 mm × 1 mm, respectively. The differential pressure distribution along the wing's chord direction was measured in a wind tunnel at an air velocity of 4.0 m s­-1 by changing the angle of attack. It was confirmed that the pressure coefficient calculated by the measured differential pressure distribution was similar to the value measured by a load cell.

Fatigue Damage Monitoring of a Composite Step Lap Joint Using Distributed Optical Fibre Sensors

PubMed Central

Wong, Leslie; Chowdhury, Nabil; Wang, John; Chiu, Wing Kong; Kodikara, Jayantha

2016-01-01

Over the past few decades, there has been a considerable interest in the use of distributed optical fibre sensors (DOFS) for structural health monitoring of composite structures. In aerospace-related work, health monitoring of the adhesive joints of composites has become more significant, as they can suffer from cracking and delamination, which can have a significant impact on the integrity of the joint. In this paper, a swept-wavelength interferometry (SWI) based DOFS technique is used to monitor the fatigue in a flush step lap joint composite structure. The presented results will show the potential application of distributed optical fibre sensor for damage detection, as well as monitoring the fatigue crack growth along the bondline of a step lap joint composite structure. The results confirmed that a distributed optical fibre sensor is able to enhance the detection of localised damage in a structure. PMID:28773496

Thermal Characterization of a Simulated Fission Engine via Distributed Fiber Bragg Gratings

NASA Astrophysics Data System (ADS)

Duncan, Roger G.; Fielder, Robert S.; Seeley, Ryan J.; Kozikowski, Carrie L.; Raum, Matthew T.

2005-02-01

We report the use of distributed fiber Bragg gratings to monitor thermal conditions within a simulated nuclear reactor core located at the Early Flight Fission Test Facility of the NASA Marshall Space Flight Center. Distributed fiber-optic temperature measurements promise to add significant capability and advance the state-of-the-art in high-temperature sensing. For the work reported herein, seven probes were constructed with ten sensors each for a total of 70 sensor locations throughout the core. These discrete temperature sensors were monitored over a nine hour period while the test article was heated to over 700 °C and cooled to ambient through two operational cycles. The sensor density available permits a significantly elevated understanding of thermal effects within the simulated reactor. Fiber-optic sensor performance is shown to compare very favorably with co-located thermocouples where such co-location was feasible.

CompatPM: enabling energy efficient multimedia workloads for distributed mobile platforms

NASA Astrophysics Data System (ADS)

Nathuji, Ripal; O'Hara, Keith J.; Schwan, Karsten; Balch, Tucker

2007-01-01

The computation and communication abilities of modern platforms are enabling increasingly capable cooperative distributed mobile systems. An example is distributed multimedia processing of sensor data in robots deployed for search and rescue, where a system manager can exploit the application's cooperative nature to optimize the distribution of roles and tasks in order to successfully accomplish the mission. Because of limited battery capacities, a critical task a manager must perform is online energy management. While support for power management has become common for the components that populate mobile platforms, what is lacking is integration and explicit coordination across the different management actions performed in a variety of system layers. This papers develops an integration approach for distributed multimedia applications, where a global manager specifies both a power operating point and a workload for a node to execute. Surprisingly, when jointly considering power and QoS, experimental evaluations show that using a simple deadline-driven approach to assigning frequencies can be non-optimal. These trends are further affected by certain characteristics of underlying power management mechanisms, which in our research, are identified as groupings that classify component power management as "compatible" (VFC) or "incompatible" (VFI) with voltage and frequency scaling. We build on these findings to develop CompatPM, a vertically integrated control strategy for power management in distributed mobile systems. Experimental evaluations of CompatPM indicate average energy improvements of 8% when platform resources are managed jointly rather than independently, demonstrating that previous attempts to maximize battery life by simply minimizing frequency are inappropriate from a platform-level perspective.

Distributed data fusion across multiple hard and soft mobile sensor platforms

NASA Astrophysics Data System (ADS)

Sinsley, Gregory

One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras, radar, laser range finders, chemical sensors, accelerometers, gyros, and global positioning systems. By effectively fusing the data from these sensors, a robot would be able to form a coherent view of its world that could then be used to facilitate both autonomous and intelligent operation. Another distinct fusion problem is that of fusing data from teammates with data from onboard sensors. If an entire team of vehicles has the same worldview they will be able to cooperate much more effectively. Sharing worldviews is made even more difficult if the teammates have different sensor types. The final fusion challenge the robotics field faces is that of fusing data gathered by robots with data gathered by human teammates (soft sensors). Humans sense the world completely differently from robots, which makes this problem particularly difficult. The advantage of fusing data from humans is that it makes more information available to the entire team, thus helping each agent to make the best possible decisions. This thesis presents a system for fusing data from multiple unmanned aerial vehicles, unmanned ground vehicles, and human observers. The first issue this thesis addresses is that of centralized data fusion. This is a foundational data fusion issue, which has been very well studied. Important issues in centralized fusion include data association, classification, tracking, and robotics problems. Because these problems are so well studied, this thesis does not make any major contributions in this area, but does review it for completeness. The chapter on centralized fusion concludes with an example unmanned aerial vehicle surveillance problem that demonstrates many of the traditional fusion methods. The second problem this thesis addresses is that of distributed data fusion. Distributed data fusion is a younger field than centralized fusion. The main issues in distributed fusion that are addressed are distributed classification and distributed tracking. There are several well established methods for performing distributed fusion that are first reviewed. The chapter on distributed fusion concludes with a multiple unmanned vehicle collaborative test involving an unmanned aerial vehicle and an unmanned ground vehicle. The third issue this thesis addresses is that of soft sensor only data fusion. Soft-only fusion is a newer field than centralized or distributed hard sensor fusion. Because of the novelty of the field, the chapter on soft only fusion contains less background information and instead focuses on some new results in soft sensor data fusion. Specifically, it discusses a novel fuzzy logic based soft sensor data fusion method. This new method is tested using both simulations and field measurements. The biggest issue addressed in this thesis is that of combined hard and soft fusion. Fusion of hard and soft data is the newest area for research in the data fusion community; therefore, some of the largest theoretical contributions in this thesis are in the chapter on combined hard and soft fusion. This chapter presents a novel combined hard and soft data fusion method based on random set theory, which processes random set data using a particle filter. Furthermore, the particle filter is designed to be distributed across multiple robots and portable computers (used by human observers) so that there is no centralized failure point in the system. After laying out a theoretical groundwork for hard and soft sensor data fusion the thesis presents practical applications for hard and soft sensor data fusion in simulation. Through a series of three progressively more difficult simulations, some important hard and soft sensor data fusion capabilities are demonstrated. The first simulation demonstrates fusing data from a single soft sensor and a single hard sensor in order to track a car that could be driving normally or erratically. The second simulation adds the extra complication of classifying the type of target to the simulation. The third simulation uses multiple hard and soft sensors, with a limited field of view, to track a moving target and classify it as a friend, foe, or neutral. The final chapter builds on the work done in previous chapters by performing a field test of the algorithms for hard and soft sensor data fusion. The test utilizes an unmanned aerial vehicle, an unmanned ground vehicle, and a human observer with a laptop. The test is designed to mimic a collaborative human and robot search and rescue problem. This test makes some of the most important practical contributions of the thesis by showing that the algorithms that have been developed for hard and soft sensor data fusion are capable of running in real time on relatively simple hardware.

Designing Online Learning Communities of Practice: A Democratic Perspective

ERIC Educational Resources Information Center

Sorensen, Elsebeth Korsgaard; Murchu, Daithi O.

2004-01-01

This study addresses the problem of designing an appropriate learning space or architecture for distributed online courses using net-based communication technologies. We apply Wenger's criteria to explore, identify and discuss the design architectures of two online courses from two comparable online Master's programmes, developed and delivered in…

EDITORIAL: Industrial Process Tomography

NASA Astrophysics Data System (ADS)

Anton Johansen, Geir; Wang, Mi

2008-09-01

There has been tremendous development within measurement science and technology over the past couple of decades. New sensor technologies and compact versatile signal recovery electronics are continuously expanding the limits of what can be measured and the accuracy with which this can be done. Miniaturization of sensors and the use of nanotechnology push these limits further. Also, thanks to powerful and cost-effective computer systems, sophisticated measurement and reconstruction algorithms previously only accessible in advanced laboratories are now available for in situ online measurement systems. The process industries increasingly require more process-related information, motivated by key issues such as improved process control, process utilization and process yields, ultimately driven by cost-effectiveness, quality assurance, environmental and safety demands. Industrial process tomography methods have taken advantage of the general progress in measurement science, and aim at providing more information, both quantitatively and qualitatively, on multiphase systems and their dynamics. The typical approach for such systems has been to carry out one local or bulk measurement and assume that this is representative of the whole system. In some cases, this is sufficient. However, there are many complex systems where the component distribution varies continuously and often unpredictably in space and time. The foundation of industrial tomography is to conduct several measurements around the periphery of a multiphase process, and use these measurements to unravel the cross-sectional distribution of the process components in time and space. This information is used in the design and optimization of industrial processes and process equipment, and also to improve the accuracy of multiphase system measurements in general. In this issue we are proud to present a selection of the 145 papers presented at the 5th World Congress on Industrial Process Tomography in Bergen, September 2007. Interestingly, x-ray technologies, one of the first imaging modalities available, keep on moving the limits on both spatial and temporal measurement resolution; experimental results of less than 100 nm and several thousand frames/s are reported, respectively. Important progress is demonstrated in research and development on sensor technologies and algorithms for data processing and image reconstruction, including unconventional sensor design and adaptation of the sensors to the application in question. The number of applications to which tomographic methods are applied is steadily increasing, and results obtained in a representative selection of applications are included. As guest editors we would like express our appreciation and thanks to all authors who have contributed and to IOP staff for excellent collaboration in the process of finalizing this special feature.

Gossip and Distributed Kalman Filtering: Weak Consensus Under Weak Detectability

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-04-01

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \\emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.

Development of a smart home simulator for use as a heuristic tool for management of sensor distribution.

PubMed

Poland, Michael P; Nugent, Chris D; Wang, Hui; Chen, Liming

2009-01-01

Smart Homes offer potential solutions for various forms of independent living for the elderly. The assistive and protective environment afforded by smart homes offer a safe, relatively inexpensive, dependable and viable alternative to vulnerable inhabitants. Nevertheless, the success of a smart home rests upon the quality of information its decision support system receives and this in turn places great importance on the issue of correct sensor deployment. In this article we present a software tool that has been developed to address the elusive issue of sensor distribution within smart homes. Details of the tool will be presented and it will be shown how it can be used to emulate any real world environment whereby virtual sensor distributions can be rapidly implemented and assessed without the requirement for physical deployment for evaluation. As such, this approach offers the potential of tailoring sensor distributions to the specific needs of a patient in a non-evasive manner. The heuristics based tool presented here has been developed as the first part of a three stage project.

Quartz crystal microbalance biosensor for rapid detection of aerosolized microorganisms

NASA Astrophysics Data System (ADS)

Farka, Zdenĕk.; Kovár, David; Skládal, Petr

2015-05-01

Biological warfare agents (BWAs) represent the current menace of the asymmetric war. The early detection of BWAs, especially in the form of bioaerosol, is a challenging task for governments all around the world. Label-free quartz crystal microbalance (QCM) immunosensor and electrochemical immunosensor were developed and tested for rapid detection of BWA surrogate (E. coli) in the form of bioaerosol. Two immobilization strategies for the attachment of antibody were tested; the gold sensor surface was activated by cysteamine and then antibody was covalently linked either using glutaraldehyde, or the reduced antibodies were attached via Sulfo-SMCC. A portable bioaerosol chamber was constructed and used for safe manipulation with aerosolized microorganisms. The dissemination was done using a piezoelectric humidifier, distribution of bioaerosol inside the chamber was ensured using three 12-cm fans. The whole system was controlled remotely using LAN network. The disseminated microbial cells were collected and preconcentrated using the wetted-wall cyclone SASS 2300, the analysis was done using the on-line linked immunosensors. The QCM immunosensor had limit of detection 1×104 CFU·L-1 of air with analysis time 16 min, the whole experiment including dissemination and sensor surface regeneration took 40 min. In case of blank (disseminated sterile buffer), no signal change was observed. The electrochemical immunosensor was able to detect 150 CFU·L-1 of air in 20 min; also in this case, no interferences were observed. Reference measurements were done using particle counter Met One 3400 and by cultivation method on agar plates. The sensors have proved to be applicable for rapid screening of microorganisms in air.

High spatial resolution distributed optical fiber dynamic strain sensor with enhanced frequency and strain resolution.

PubMed

Masoudi, Ali; Newson, Trevor P

2017-01-15

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the ϕ-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

FPGA-Based Fused Smart-Sensor for Tool-Wear Area Quantitative Estimation in CNC Machine Inserts

PubMed Central

Trejo-Hernandez, Miguel; Osornio-Rios, Roque Alfredo; de Jesus Romero-Troncoso, Rene; Rodriguez-Donate, Carlos; Dominguez-Gonzalez, Aurelio; Herrera-Ruiz, Gilberto

2010-01-01

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used. PMID:22319304

A New User Interface for On-Demand Customizable Data Products for Sensors in a SensorWeb

NASA Technical Reports Server (NTRS)

Mandl, Daniel; Cappelaere, Pat; Frye, Stuart; Sohlberg, Rob; Ly, Vuong; Chien, Steve; Sullivan, Don

2011-01-01

A SensorWeb is a set of sensors, which can consist of ground, airborne and space-based sensors interoperating in an automated or autonomous collaborative manner. The NASA SensorWeb toolbox, developed at NASA/GSFC in collaboration with NASA/JPL, NASA/Ames and other partners, is a set of software and standards that (1) enables users to create virtual private networks of sensors over open networks; (2) provides the capability to orchestrate their actions; (3) provides the capability to customize the output data products and (4) enables automated delivery of the data products to the users desktop. A recent addition to the SensorWeb Toolbox is a new user interface, together with web services co-resident with the sensors, to enable rapid creation, loading and execution of new algorithms for processing sensor data. The web service along with the user interface follows the Open Geospatial Consortium (OGC) standard called Web Coverage Processing Service (WCPS). This presentation will detail the prototype that was built and how the WCPS was tested against a HyspIRI flight testbed and an elastic computation cloud on the ground with EO-1 data. HyspIRI is a future NASA decadal mission. The elastic computation cloud stores EO-1 data and runs software similar to Amazon online shopping.

Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks

ERIC Educational Resources Information Center

Yu, Chao

2013-01-01

In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…

Practical comparison of distributed ledger technologies for IoT

NASA Astrophysics Data System (ADS)

Red, Val A.

2017-05-01

Existing distributed ledger implementations - specifically, several blockchain implementations - embody a cacophony of divergent capabilities augmenting innovations of cryptographic hashes, consensus mechanisms, and asymmetric cryptography in a wide variety of applications. Whether specifically designed for cryptocurrency or otherwise, several distributed ledgers rely upon modular mechanisms such as consensus or smart contracts. These components, however, can vary substantially among implementations; differences involving proof-of-work, practical byzantine fault tolerance, and other consensus approaches exemplify distinct distributed ledger variations. Such divergence results in unique combinations of modules, performance, latency, and fault tolerance. As implementations continue to develop rapidly due to the emerging nature of blockchain technologies, this paper encapsulates a snapshot of sensor and internet of things (IoT) specific implementations of blockchain as of the end of 2016. Several technical risks and divergent approaches preclude standardization of a blockchain for sensors and IoT in the foreseeable future; such issues will be assessed alongside the practicality of IoT applications among Hyperledger, Iota, and Ethereum distributed ledger implementations suggested for IoT. This paper contributes a comparison of existing distributed ledger implementations intended for practical sensor and IoT utilization. A baseline for characterizing distributed ledger implementations in the context of IoT and sensors is proposed. Technical approaches and performance are compared considering IoT size, weight, and power limitations. Consensus and smart contracts, if applied, are also analyzed for the respective implementations' practicality and security. Overall, the maturity of distributed ledgers with respect to sensor and IoT applicability will be analyzed for enterprise interoperability.

Exploring Distributed Leadership for the Quality Management of Online Learning Environments

ERIC Educational Resources Information Center

Palmer, Stuart; Holt, Dale; Gosper, Maree; Sankey, Michael; Allan, Garry

2013-01-01

Online learning environments (OLEs) are complex information technology (IT) systems that intersect with many areas of university organisation. Distributed models of leadership have been proposed as appropriate for the good governance of OLEs. Based on theoretical and empirical research, a group of Australian universities proposed a framework for…

Geometry-driven distributed compression of the plenoptic function: performance bounds and constructive algorithms.

PubMed

Gehrig, Nicolas; Dragotti, Pier Luigi

2009-03-01

In this paper, we study the sampling and the distributed compression of the data acquired by a camera sensor network. The effective design of these sampling and compression schemes requires, however, the understanding of the structure of the acquired data. To this end, we show that the a priori knowledge of the configuration of the camera sensor network can lead to an effective estimation of such structure and to the design of effective distributed compression algorithms. For idealized scenarios, we derive the fundamental performance bounds of a camera sensor network and clarify the connection between sampling and distributed compression. We then present a distributed compression algorithm that takes advantage of the structure of the data and that outperforms independent compression algorithms on real multiview images.

Autonomous chemical and biological miniature wireless-sensor

NASA Astrophysics Data System (ADS)

Goldberg, Bar-Giora

2005-05-01

The presentation discusses a new concept and a paradigm shift in biological, chemical and explosive sensor system design and deployment. From large, heavy, centralized and expensive systems to distributed wireless sensor networks utilizing miniature platforms (nodes) that are lightweight, low cost and wirelessly connected. These new systems are possible due to the emergence and convergence of new innovative radio, imaging, networking and sensor technologies. Miniature integrated radio-sensor networks, is a technology whose time has come. These network systems are based on large numbers of distributed low cost and short-range wireless platforms that sense and process their environment and communicate data thru a network to a command center. The recent emergence of chemical and explosive sensor technology based on silicon nanostructures, coupled with the fast evolution of low-cost CMOS imagers, low power DSP engines and integrated radio chips, has created an opportunity to realize the vision of autonomous wireless networks. These threat detection networks will perform sophisticated analysis at the sensor node and convey alarm information up the command chain. Sensor networks of this type are expected to revolutionize the ability to detect and locate biological, chemical, or explosive threats. The ability to distribute large numbers of low-cost sensors over large areas enables these devices to be close to the targeted threats and therefore improve detection efficiencies and enable rapid counter responses. These sensor networks will be used for homeland security, shipping container monitoring, and other applications such as laboratory medical analysis, drug discovery, automotive, environmental and/or in-vivo monitoring. Avaak"s system concept is to image a chromatic biological, chemical and/or explosive sensor utilizing a digital imager, analyze the images and distribute alarm or image data wirelessly through the network. All the imaging, processing and communications would take place within the miniature, low cost distributed sensor platforms. This concept however presents a significant challenge due to a combination and convergence of required new technologies, as mentioned above. Passive biological and chemical sensors with very high sensitivity and which require no assaying are in development using a technique to optically and chemically encode silicon wafers with tailored nanostructures. The silicon wafer is patterned with nano-structures designed to change colors ad patterns when exposed to the target analytes (TICs, TIMs, VOC). A small video camera detects the color and pattern changes on the sensor. To determine if an alarm condition is present, an on board DSP processor, using specialized image processing algorithms and statistical analysis, determines if color gradient changes occurred on the sensor array. These sensors can detect several agents simultaneously. This system is currently under development by Avaak, with funding from DARPA through an SBIR grant.

ROBUST ONLINE MONITORING FOR CALIBRATION ASSESSMENT OF TRANSMITTERS AND INSTRUMENTATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Tipireddy, Ramakrishna; Lerchen, Megan E.

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. Specifically, the next generation of OLM technology is expected to include newly developed advanced algorithms that improve monitoring of sensor/system performance and enable the use of plant data to derive information that currently cannot be measured. These advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this paper, we discuss an overview of research beingmore » performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. Algorithm development is focused on the following OLM functions: • Signal validation – fault detection and selection of acceptance criteria • Virtual sensing – signal value prediction and acceptance criteria • Response-time assessment – fault detection and acceptance criteria selection A GP-based uncertainty quantification (UQ) method previously developed for UQ in OLM, was adapted for use in sensor-fault detection and virtual sensing. For signal validation, the various components to the OLM residual (which is computed using an AAKR model) were explicitly defined and modeled using a GP. Evaluation was conducted using flow loop data from multiple sources. Results using experimental data from laboratory-scale flow loops indicate that the approach, while capable of detecting sensor drift, may be incapable of discriminating between sensor drift and model inadequacy. This may be due to a simplification applied in the initial modeling, where the sensor degradation is assumed to be stationary. In the case of virtual sensors, the GP model was used in a predictive mode to estimate the correct sensor reading for sensors that may have failed. Results have indicated the viability of using this approach for virtual sensing. However, the GP model has proven to be computationally expensive, and so alternative algorithms for virtual sensing are being evaluated. Finally, automated approaches to performing noise analysis for extracting sensor response time were developed. Evaluation of this technique using laboratory-scale data indicates that it compares well with manual techniques previously used for noise analysis. Moreover, the automated and manual approaches for noise analysis also compare well with the current “gold standard”, hydraulic ramp testing, for response time monitoring. Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants.« less

Scheduling policies of intelligent sensors and sensor/actuators in flexible structures

NASA Astrophysics Data System (ADS)

Demetriou, Michael A.; Potami, Raffaele

2006-03-01

In this note, we revisit the problem of actuator/sensor placement in large civil infrastructures and flexible space structures within the context of spatial robustness. The positioning of these devices becomes more important in systems employing wireless sensor and actuator networks (WSAN) for improved control performance and for rapid failure detection. The ability of the sensing and actuating devices to possess the property of spatial robustness results in reduced control energy and therefore the spatial distribution of disturbances is integrated into the location optimization measures. In our studies, the structure under consideration is a flexible plate clamped at all sides. First, we consider the case of sensor placement and the optimization scheme attempts to produce those locations that minimize the effects of the spatial distribution of disturbances on the state estimation error; thus the sensor locations produce state estimators with minimized disturbance-to-error transfer function norms. A two-stage optimization procedure is employed whereby one first considers the open loop system and the spatial distribution of disturbances is found that produces the maximal effects on the entire open loop state. Once this "worst" spatial distribution of disturbances is found, the optimization scheme subsequently finds the locations that produce state estimators with minimum transfer function norms. In the second part, we consider the collocated actuator/sensor pairs and the optimization scheme produces those locations that result in compensators with the smallest norms of the disturbance-to-state transfer functions. Going a step further, an intelligent control scheme is presented which, at each time interval, activates a subset of the actuator/sensor pairs in order provide robustness against spatiotemporally moving disturbances and minimize power consumption by keeping some sensor/actuators in sleep mode.

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

PubMed Central

Teng, Rui; Leibnitz, Kenji; Miura, Ryu

2013-01-01

An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner. PMID:23748172

mHealthMon: toward energy-efficient and distributed mobile health monitoring using parallel offloading.

PubMed

Ahnn, Jong Hoon; Potkonjak, Miodrag

2013-10-01

Although mobile health monitoring where mobile sensors continuously gather, process, and update sensor readings (e.g. vital signals) from patient's sensors is emerging, little effort has been investigated in an energy-efficient management of sensor information gathering and processing. Mobile health monitoring with the focus of energy consumption may instead be holistically analyzed and systematically designed as a global solution to optimization subproblems. This paper presents an attempt to decompose the very complex mobile health monitoring system whose layer in the system corresponds to decomposed subproblems, and interfaces between them are quantified as functions of the optimization variables in order to orchestrate the subproblems. We propose a distributed and energy-saving mobile health platform, called mHealthMon where mobile users publish/access sensor data via a cloud computing-based distributed P2P overlay network. The key objective is to satisfy the mobile health monitoring application's quality of service requirements by modeling each subsystem: mobile clients with medical sensors, wireless network medium, and distributed cloud services. By simulations based on experimental data, we present the proposed system can achieve up to 10.1 times more energy-efficient and 20.2 times faster compared to a standalone mobile health monitoring application, in various mobile health monitoring scenarios applying a realistic mobility model.

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range.

PubMed

He, Chenlong; Feng, Zuren; Ren, Zhigang

2018-02-03

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham's Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm.

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range

PubMed Central

Feng, Zuren; Ren, Zhigang

2018-01-01

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham’s Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm. PMID:29401649

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

A real-time detector system for precise timing of audiovisual stimuli.

PubMed

Henelius, Andreas; Jagadeesan, Sharman; Huotilainen, Minna

2012-01-01

The successful recording of neurophysiologic signals, such as event-related potentials (ERPs) or event-related magnetic fields (ERFs), relies on precise information of stimulus presentation times. We have developed an accurate and flexible audiovisual sensor solution operating in real-time for on-line use in both auditory and visual ERP and ERF paradigms. The sensor functions independently of the used audio or video stimulus presentation tools or signal acquisition system. The sensor solution consists of two independent sensors; one for sound and one for light. The microcontroller-based audio sensor incorporates a novel approach to the detection of natural sounds such as multipart audio stimuli, using an adjustable dead time. This aids in producing exact markers for complex auditory stimuli and reduces the number of false detections. The analog photosensor circuit detects changes in light intensity on the screen and produces a marker for changes exceeding a threshold. The microcontroller software for the audio sensor is free and open source, allowing other researchers to customise the sensor for use in specific auditory ERP/ERF paradigms. The hardware schematics and software for the audiovisual sensor are freely available from the webpage of the authors' lab.

Oxygen sensitive polymeric nanocapsules for optical dissolved oxygen sensors

NASA Astrophysics Data System (ADS)

Sun, Zhijuan; Cai, Chenxin; Guo, Fei; Ye, Changhuai; Luo, Yingwu; Ye, Shuming; Luo, Jianchao; Zhu, Fan; Jiang, Chunyue

2018-04-01

Immobilization of the oxygen-sensitive probes (OSPs) in the host matrix greatly impacts the performance and long-term usage of the optical dissolved oxygen (DO) sensors. In this work, fluorescent dyes, as the OSPs, were encapsulated with a crosslinked fluorinated polymer shell by interfacial confined reversible addition fragmentation chain transfer miniemulsion polymerization to fabricate oxygen sensitive polymeric nanocapsules (NCs). The location of fluorescent dyes and the fluorescent properties of the NCs were fully characterized by fourier transform infrared spectrometer, x-ray photoelectron spectrometer and fluorescent spectrum. Dye-encapsulated capacity can be precisely tuned from 0 to 1.3 wt% without self-quenching of the fluorescent dye. The crosslinked fluorinated polymer shell is not only extremely high gas permeability, but also prevents the fluorescent dyes from leakage in aqueous as well as in various organic solvents, such as ethanol, acetone and tetrahydrofuran (THF). An optical DO sensor based on the oxygen sensitive NCs was fabricated, showing high sensitivity, short response time, full reversibility, and long-term operational stability of online monitoring DO. The sensitivity of the optical DO sensor is 7.02 (the ratio of the response value in fully deoxygenated and saturated oxygenated water) in the range 0.96-14.16 mg l-1 and the response time is about 14.3 s. The sensor’s work curve was fit well using the modified Stern-Volmer equation by two-site model, and its response values are hardly affected by pH ranging from 2 to 12 and keep constant during continuous measurement for 3 months. It is believed that the oxygen sensitive polymeric NCs-based optical DO sensor could be particularly useful in long-term online DO monitoring in both aqueous and organic solvent systems.

Investigating energy-saving potentials in the cloud.

PubMed

Lee, Da-Sheng

2014-02-20

Collecting webpage messages can serve as a sensor for investigating the energy-saving potential of buildings. Focusing on stores, a cloud sensor system is developed to collect data and determine their energy-saving potential. The owner of a store under investigation must register online, report the store address, area, and the customer ID number on the electric meter. The cloud sensor system automatically surveys the energy usage records by connecting to the power company website and calculating the energy use index (EUI) of the store. Other data includes the chain store check, company capital, location price, and the influence of weather conditions on the store; even the exposure frequency of store under investigation may impact the energy usage collected online. After collecting data from numerous stores, a multi-dimensional data array is constructed to determine energy-saving potential by identifying stores with similarity conditions. Similarity conditions refer to analyzed results that indicate that two stores have similar capital, business scale, weather conditions, and exposure frequency on web. Calculating the EUI difference or pure technical efficiency of stores, the energy-saving potential is determined. In this study, a real case study is performed. An 8-dimensional (8D) data array is constructed by surveying web data related to 67 stores. Then, this study investigated the savings potential of the 33 stores, using a site visit, and employed the cloud sensor system to determine the saving potential. The case study results show good agreement between the data obtained by the site visit and the cloud investigation, with errors within 4.17%. Among 33 the samples, eight stores have low saving potentials of less than 5%. The developed sensor on the cloud successfully identifies them as having low saving potential and avoids wasting money on the site visit.

Investigating Energy-Saving Potentials in the Cloud

PubMed Central

Lee, Da-Sheng

2014-01-01

Collecting webpage messages can serve as a sensor for investigating the energy-saving potential of buildings. Focusing on stores, a cloud sensor system is developed to collect data and determine their energy-saving potential. The owner of a store under investigation must register online, report the store address, area, and the customer ID number on the electric meter. The cloud sensor system automatically surveys the energy usage records by connecting to the power company website and calculating the energy use index (EUI) of the store. Other data includes the chain store check, company capital, location price, and the influence of weather conditions on the store; even the exposure frequency of store under investigation may impact the energy usage collected online. After collecting data from numerous stores, a multi-dimensional data array is constructed to determine energy-saving potential by identifying stores with similarity conditions. Similarity conditions refer to analyzed results that indicate that two stores have similar capital, business scale, weather conditions, and exposure frequency on web. Calculating the EUI difference or pure technical efficiency of stores, the energy-saving potential is determined. In this study, a real case study is performed. An 8-dimensional (8D) data array is constructed by surveying web data related to 67 stores. Then, this study investigated the savings potential of the 33 stores, using a site visit, and employed the cloud sensor system to determine the saving potential. The case study results show good agreement between the data obtained by the site visit and the cloud investigation, with errors within 4.17%. Among 33 the samples, eight stores have low saving potentials of less than 5%. The developed sensor on the cloud successfully identifies them as having low saving potential and avoids wasting money on the site visit. PMID:24561405

D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things

PubMed Central

Akan, Ozgur B.

2018-01-01

Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST). PMID:29538405

D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things.

PubMed

Aktas, Metin; Kuscu, Murat; Dinc, Ergin; Akan, Ozgur B

2018-01-01

Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST).

Anesthetic level prediction using a QCM based E-nose.

PubMed

Saraoğlu, H M; Ozmen, A; Ebeoğlu, M A

2008-06-01

Anesthetic level measurement is a real time process. This paper presents a new method to measure anesthesia level in surgery rooms at hospitals using a QCM based E-Nose. The E-Nose system contains an array of eight different coated QCM sensors. In this work, the best linear reacting sensor is selected from the array and used in the experiments. Then, the sensor response time was observed about 15 min using classic method, which is impractical for on-line anesthetic level detection during a surgery. Later, the sensor transition data is analyzed to reach a decision earlier than the classical method. As a result, it is found out that the slope of transition data gives valuable information to predict the anesthetic level. With this new method, we achieved to find correct anesthetic levels within 100 s.

Greenhouse intelligent control system based on microcontroller

NASA Astrophysics Data System (ADS)

Zhang, Congwei

2018-04-01

As one of the hallmarks of agricultural modernization, intelligent greenhouse has the advantages of high yield, excellent quality, no pollution and continuous planting. Taking AT89S52 microcontroller as the main controller, the greenhouse intelligent control system uses soil moisture sensor, temperature and humidity sensors, light intensity sensor and CO2 concentration sensor to collect measurements and display them on the 12864 LCD screen real-time. Meantime, climate parameter values can be manually set online. The collected measured values are compared with the set standard values, and then the lighting, ventilation fans, warming lamps, water pumps and other facilities automatically start to adjust the climate such as light intensity, CO2 concentration, temperature, air humidity and soil moisture of the greenhouse parameter. So, the state of the environment in the greenhouse Stabilizes and the crop grows in a suitable environment.

Exploring 3D Human Action Recognition: from Offline to Online.

PubMed

Liu, Zhenyu; Li, Rui; Tan, Jianrong

2018-02-20

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems-including real-time performance and sequence segmentation-are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset.

Exploring 3D Human Action Recognition: from Offline to Online

PubMed Central

Li, Rui; Liu, Zhenyu; Tan, Jianrong

2018-01-01

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems—including real-time performance and sequence segmentation—are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset. PMID:29461502

An online condition monitoring system implemented an internet connectivity and FTP for low speed slew bearing

NASA Astrophysics Data System (ADS)

Caesarendra, W.; Kosasih, B.; Tjahjowidodo, T.; Ariyanto, M.; Daryl, LWQ; Pamungkas, D.

2018-04-01

Rapid and reliable information in slew bearing maintenance is not trivial issue. This paper presents the online monitoring system to assist maintenance engineer in order to monitor the bearing condition of low speed slew bearing in sheet metal company. The system is able to pass the vibration information from the place where the bearing and accelerometer sensors are attached to the data center; and from the data center it can be access by opening the online monitoring website from any place and by any person. The online monitoring system is built using some programming languages such as C language, MATLAB, PHP, HTML and CSS. Generally, the flow process is start with the automatic vibration data acquisition; then features are calculated from the acquired vibration data. These features are then sent to the data center; and form the data center, the vibration features can be seen through the online monitoring website. This online monitoring system has been successfully applied in School of Mechanical, Materials and Mechatronic Engineering, University of Wollongong.