WorldWideScience

Sample records for machine health monitoring

  1. Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

    2014-08-15

    The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.

  2. Application of Machine Learning to Rotorcraft Health Monitoring

    Science.gov (United States)

    Cody, Tyler; Dempsey, Paula J.

    2017-01-01

    Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

  3. Development of non-contact structural health monitoring system for machine tools

    Directory of Open Access Journals (Sweden)

    Deepam Goyal

    2016-08-01

    Full Text Available In this era of flexible manufacturing systems, a real-time structural health monitoring (SHM is paramount for machining processes which are of great relevance today, when there is a constant call for better productivity with high quality at low price. During machining, vibrations are always brought forth because of mechanical disturbances from various sources such as an engine, a sound, and noise, among others. A SHM system provides significant economic benefits when applied to machine tools and machining processes. This study demonstrates a non contact SHM system for machine tools based on the vibration signal collected through a low-cost, microcontroller based data acquisition system. The examination tests of this developed system have been carried out on a vibration rig. The readings have also been calibrated with the accelerometer to validate the proposed system. The developed system results in quick measurement, enables reliable monitoring, and is cost effective with no need to alter the structure of the machine tool. It is expected that the system can forewarn the operator for timely based maintenance actions in addition to reducing the costs of machine downtime and acquiring equipments with reduction in complexity of machine tools.

  4. VIBRATION SENSOR FOR HEALTH MONITORING OF ELECTRICAL MACHINES IN POWER STATION

    Directory of Open Access Journals (Sweden)

    Neha Gupta

    2012-04-01

    Full Text Available Vibration monitoring in high power electric machines, such as generators and transformers, presents some difficulties due to the insulation and EM immunity requirements .However, the negative influence of the electromagnetic interference (EMI can be a real problem when electrical signals are used to detect and transmitphysical parameters in noisy environments such as electric power generator plants with high levels of EMI. Such problems can be solved using optical fiber sensors, which allow in situ measurements and remote control without electrical wires. The present paper describes a novel fiber optic vibration sensor for health monitoring of electrical machines, which utilizes relatively simple technologies and offers moderate costs. The sensor is optimized for detection of mechanical vibrations in the frequency range 20-100 Hz. Design details and experimental results are reported.

  5. Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks

    Directory of Open Access Journals (Sweden)

    Rui Zhao

    2017-01-01

    Full Text Available In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classification and regression models directly. Therefore, previous work focuses on feature extraction/fusion methods requiring expensive human labor and high quality expert knowledge. With the development of deep learning methods in the last few years, which redefine representation learning from raw data, a deep neural network structure named Convolutional Bi-directional Long Short-Term Memory networks (CBLSTM has been designed here to address raw sensory data. CBLSTM firstly uses CNN to extract local features that are robust and informative from the sequential input. Then, bi-directional LSTM is introduced to encode temporal information. Long Short-Term Memory networks(LSTMs are able to capture long-term dependencies and model sequential data, and the bi-directional structure enables the capture of past and future contexts. Stacked, fully-connected layers and the linear regression layer are built on top of bi-directional LSTMs to predict the target value. Here, a real-life tool wear test is introduced, and our proposed CBLSTM is able to predict the actual tool wear based on raw sensory data. The experimental results have shown that our model is able to outperform several state-of-the-art baseline methods.

  6. Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks

    Science.gov (United States)

    Zhao, Rui; Yan, Ruqiang; Wang, Jinjiang; Mao, Kezhi

    2017-01-01

    In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classification and regression models directly. Therefore, previous work focuses on feature extraction/fusion methods requiring expensive human labor and high quality expert knowledge. With the development of deep learning methods in the last few years, which redefine representation learning from raw data, a deep neural network structure named Convolutional Bi-directional Long Short-Term Memory networks (CBLSTM) has been designed here to address raw sensory data. CBLSTM firstly uses CNN to extract local features that are robust and informative from the sequential input. Then, bi-directional LSTM is introduced to encode temporal information. Long Short-Term Memory networks (LSTMs) are able to capture long-term dependencies and model sequential data, and the bi-directional structure enables the capture of past and future contexts. Stacked, fully-connected layers and the linear regression layer are built on top of bi-directional LSTMs to predict the target value. Here, a real-life tool wear test is introduced, and our proposed CBLSTM is able to predict the actual tool wear based on raw sensory data. The experimental results have shown that our model is able to outperform several state-of-the-art baseline methods. PMID:28146106

  7. Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks.

    Science.gov (United States)

    Zhao, Rui; Yan, Ruqiang; Wang, Jinjiang; Mao, Kezhi

    2017-01-30

    In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classification and regression models directly. Therefore, previous work focuses on feature extraction/fusion methods requiring expensive human labor and high quality expert knowledge. With the development of deep learning methods in the last few years, which redefine representation learning from raw data, a deep neural network structure named Convolutional Bi-directional Long Short-Term Memory networks (CBLSTM) has been designed here to address raw sensory data. CBLSTM firstly uses CNN to extract local features that are robust and informative from the sequential input. Then, bi-directional LSTM is introduced to encode temporal information. Long Short-Term Memory networks(LSTMs) are able to capture long-term dependencies and model sequential data, and the bi-directional structure enables the capture of past and future contexts. Stacked, fully-connected layers and the linear regression layer are built on top of bi-directional LSTMs to predict the target value. Here, a real-life tool wear test is introduced, and our proposed CBLSTM is able to predict the actual tool wear based on raw sensory data. The experimental results have shown that our model is able to outperform several state-of-the-art baseline methods.

  8. Structural health monitoring for bolt loosening via a non-invasive vibro-haptics human-machine cooperative interface

    Science.gov (United States)

    Pekedis, Mahmut; Mascerañas, David; Turan, Gursoy; Ercan, Emre; Farrar, Charles R.; Yildiz, Hasan

    2015-08-01

    For the last two decades, developments in damage detection algorithms have greatly increased the potential for autonomous decisions about structural health. However, we are still struggling to build autonomous tools that can match the ability of a human to detect and localize the quantity of damage in structures. Therefore, there is a growing interest in merging the computational and cognitive concepts to improve the solution of structural health monitoring (SHM). The main object of this research is to apply the human-machine cooperative approach on a tower structure to detect damage. The cooperation approach includes haptic tools to create an appropriate collaboration between SHM sensor networks, statistical compression techniques and humans. Damage simulation in the structure is conducted by releasing some of the bolt loads. Accelerometers are bonded to various locations of the tower members to acquire the dynamic response of the structure. The obtained accelerometer results are encoded in three different ways to represent them as a haptic stimulus for the human subjects. Then, the participants are subjected to each of these stimuli to detect the bolt loosened damage in the tower. Results obtained from the human-machine cooperation demonstrate that the human subjects were able to recognize the damage with an accuracy of 88 ± 20.21% and response time of 5.87 ± 2.33 s. As a result, it is concluded that the currently developed human-machine cooperation SHM may provide a useful framework to interact with abstract entities such as data from a sensor network.

  9. Modeling the Relationship between Vibration Features and Condition Parameters Using Relevance Vector Machines for Health Monitoring of Rolling Element Bearings under Varying Operation Conditions

    Directory of Open Access Journals (Sweden)

    Lei Hu

    2015-01-01

    Full Text Available Rotational speed and load usually change when rotating machinery works. Both this kind of changing operational conditions and machine fault could make the mechanical vibration characteristics change. Therefore, effective health monitoring method for rotating machinery must be able to adjust during the change of operational conditions. This paper presents an adaptive threshold model for the health monitoring of bearings under changing operational conditions. Relevance vector machines (RVMs are used for regression of the relationships between the adaptive parameters of the threshold model and the statistical characteristics of vibration features. The adaptive threshold model is constructed based on these relationships. The health status of bearings can be indicated via detecting whether vibration features exceed the adaptive threshold. This method is validated on bearings running at changing speeds. The monitoring results show that this method is effective as long as the rotational speed is higher than a relative small value.

  10. Method and apparatus for monitoring machine performance

    Science.gov (United States)

    Smith, Stephen F.; Castleberry, Kimberly N.

    1996-01-01

    Machine operating conditions can be monitored by analyzing, in either the time or frequency domain, the spectral components of the motor current. Changes in the electric background noise, induced by mechanical variations in the machine, are correlated to changes in the operating parameters of the machine.

  11. Monitor For Electrical-Discharge Machining

    Science.gov (United States)

    Burley, Richard K.

    1993-01-01

    Circuit monitors electrical-discharge-machining (EDM) process to detect and prevent abnormal arcing, which can produce unacceptable "burn" marks on workpiece. When voltage between EDM electrode and workpiece behaves in manner indicative of abnormal arcing, relay made to switch off EDM power, which remains off until operator attends to EDM setup and resets monitor.

  12. Integrating Oil Debris and Vibration Measurements for Intelligent Machine Health Monitoring. Degree awarded by Toledo Univ., May 2002

    Science.gov (United States)

    Dempsey, Paula J.

    2003-01-01

    A diagnostic tool for detecting damage to gears was developed. Two different measurement technologies, oil debris analysis and vibration were integrated into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual measurement technologies. This diagnostic tool was developed and evaluated experimentally by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spur Gear Fatigue Rig. An oil debris sensor and the two vibration algorithms were adapted as the diagnostic tools. An inductance type oil debris sensor was selected for the oil analysis measurement technology. Gear damage data for this type of sensor was limited to data collected in the NASA Glenn test rigs. For this reason, this analysis included development of a parameter for detecting gear pitting damage using this type of sensor. The vibration data was used to calculate two previously available gear vibration diagnostic algorithms. The two vibration algorithms were selected based on their maturity and published success in detecting damage to gears. Oil debris and vibration features were then developed using fuzzy logic analysis techniques, then input into a multi sensor data fusion process. Results show combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spur gears. As a result of this research, this new diagnostic tool has significantly improved detection of gear damage in the NASA Glenn Spur Gear Fatigue Rigs. This research also resulted in several other findings that will improve the development of future health monitoring systems. Oil debris analysis was found to be more reliable than vibration analysis for detecting pitting fatigue failure of gears and is capable of indicating damage progression. Also, some vibration algorithms are as sensitive to operational effects as they

  13. Lunar Health Monitor Project

    Data.gov (United States)

    National Aeronautics and Space Administration — During the Phase II Lunar Health Monitor program, Orbital Research will develop a second generation wearable sensor suite for astronaut physiologic monitoring. The...

  14. Virtual Machine Monitor Indigenous Memory Reclamation Technique

    Directory of Open Access Journals (Sweden)

    Muhammad Shams Ul Haq

    2016-04-01

    Full Text Available Sandboxing is a mechanism to monitor and control the execution of malicious or untrusted program. Memory overhead incurred by sandbox solutions is one of bottleneck for sandboxing most of applications in a system. Memory reclamation techniques proposed for traditional full virtualization do not suit sandbox environment due to lack of full scale guest operating system in sandbox. In this paper, we propose memory reclamation technique for sandboxed applications. The proposed technique indigenously works in virtual machine monitor layer without installing any driver in VMX non root mode and without new communication channel with host kernel. Proposed Page reclamation algorithm is a simple modified form of Least recently used page reclamation and Working set page reclamation algorithms. For efficiently collecting working set of application, we use a hardware virtualization extension, page Modification logging introduced by Intel. We implemented proposed technique with one of open source sandboxes to show effectiveness of proposed memory reclamation method. Experimental results show that proposed technique successfully reclaim up to 11% memory from sandboxed applications with negligible CPU overheads

  15. Proactive condition monitoring of low-speed machines

    CERN Document Server

    Stamboliska, Zhaklina; Moczko, Przemyslaw

    2015-01-01

    This book broadens readers’ understanding of proactive condition monitoring of low-speed machines in heavy industries. It focuses on why low-speed machines are different than others and how maintenance of these machines should be implemented with particular attention. The authors explain the best available monitoring techniques for various equipment and the principle of how to get proactive information from each technique. They further put forward possible strategies for application of FEM for detection of faults and technical assessment of machinery. Implementation phases are described and industrial case-studies of proactive condition monitoring are included. Proactive Condition Monitoring of Low-Speed Machines is an essential resource for engineers and technical managers across a range of industries as well as design engineers working in industrial product development. This book also: ·         Explains the practice of proactive condition monitoring and illustrates implementation phases ·   ...

  16. Thermal Analysis for Condition Monitoring of Machine Tool Spindles

    Science.gov (United States)

    Clough, D.; Fletcher, S.; Longstaff, A. P.; Willoughby, P.

    2012-05-01

    Decreasing tolerances on parts manufactured, or inspected, on machine tools increases the requirement to have a greater understanding of machine tool capabilities, error sources and factors affecting asset availability. Continuous usage of a machine tool during production processes causes heat generation typically at the moving elements, resulting in distortion of the machine structure. These effects, known as thermal errors, can contribute a significant percentage of the total error in a machine tool. There are a number of design solutions available to the machine tool builder to reduce thermal error including, liquid cooling systems, low thermal expansion materials and symmetric machine tool structures. However, these can only reduce the error not eliminate it altogether. It is therefore advisable, particularly in the production of high value parts, for manufacturers to obtain a thermal profile of their machine, to ensure it is capable of producing in tolerance parts. This paper considers factors affecting practical implementation of condition monitoring of the thermal errors. In particular is the requirement to find links between temperature, which is easily measureable during production and the errors which are not. To this end, various methods of testing including the advantages of thermal images are shown. Results are presented from machines in typical manufacturing environments, which also highlight the value of condition monitoring using thermal analysis.

  17. Lunar Health Monitor (LHM)

    Science.gov (United States)

    Lisy, Frederick J.

    2015-01-01

    Orbital Research, Inc., has developed a low-profile, wearable sensor suite for monitoring astronaut health in both intravehicular and extravehicular activities. The Lunar Health Monitor measures respiration, body temperature, electrocardiogram (EKG) heart rate, and other cardiac functions. Orbital Research's dry recording electrode is central to the innovation and can be incorporated into garments, eliminating the need for conductive pastes, adhesives, or gels. The patented dry recording electrode has been approved by the U.S. Food and Drug Administration. The LHM is easily worn under flight gear or with civilian clothing, making the system completely versatile for applications where continuous physiological monitoring is needed. During Phase II, Orbital Research developed a second-generation LHM that allows sensor customization for specific monitoring applications and anatomical constraints. Evaluations included graded exercise tests, lunar mission task simulations, functional battery tests, and resting measures. The LHM represents the successful integration of sensors into a wearable platform to capture long-duration and ambulatory physiological markers.

  18. Wearable Health Monitoring Systems

    Science.gov (United States)

    Bell, John

    2015-01-01

    The shrinking size and weight of electronic circuitry has given rise to a new generation of smart clothing that enables biological data to be measured and transmitted. As the variation in the number and type of deployable devices and sensors increases, technology must allow their seamless integration so they can be electrically powered, operated, and recharged over a digital pathway. Nyx Illuminated Clothing Company has developed a lightweight health monitoring system that integrates medical sensors, electrodes, electrical connections, circuits, and a power supply into a single wearable assembly. The system is comfortable, bendable in three dimensions, durable, waterproof, and washable. The innovation will allow astronaut health monitoring in a variety of real-time scenarios, with data stored in digital memory for later use in a medical database. Potential commercial uses are numerous, as the technology enables medical personnel to noninvasively monitor patient vital signs in a multitude of health care settings and applications.

  19. Monitoring Vibration of A Model of Rotating Machine

    Directory of Open Access Journals (Sweden)

    Arko Djajadi

    2012-03-01

    Full Text Available Mechanical movement or motion of a rotating machine normally causes additional vibration. A vibration sensing device must be added to constantly monitor vibration level of the system having a rotating machine, since the vibration frequency and amplitude cannot be measured quantitatively by only sight or touch. If the vibration signals from the machine have a lot of noise, there are possibilities that the rotating machine has defects that can lead to failure. In this experimental research project, a vibration structure is constructed in a scaled model to simulate vibration and to monitor system performance in term of vibration level in case of rotation with balanced and unbalanced condition. In this scaled model, the output signal of the vibration sensor is processed in a microcontroller and then transferred to a computer via a serial communication medium, and plotted on the screen with data plotter software developed using C language. The signal waveform of the vibration is displayed to allow further analysis of the vibration. Vibration level monitor can be set in the microcontroller to allow shutdown of the rotating machine in case of excessive vibration to protect the rotating machine from further damage. Experiment results show the agreement with theory that unbalance condition on a rotating machine can lead to larger vibration amplitude compared to balance condition. Adding and reducing the mass for balancing can be performed to obtain lower vibration level. 

  20. Monitoring Grinding Wheel Redress-life Using Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    Xun Chen; Thitikorn Limchimchol

    2006-01-01

    Condition monitoring is a very important aspect in automated manufacturing processes. Any malfunction of a machining process will deteriorate production quality and efficiency. This paper presents an application of support vector machines in grinding process monitoring. The paper starts with an overview of grinding behaviour. Grinding force is analysed through a Short Time Fourier Transform (STFT) to identify features for condition monitoring. The Support Vector Machine (SVM) methodology is introduced as a powerful tool for the classification of different wheel wear situations.After training with available signal data, the SVM is able to identify the state of a grinding process. The requirement and strategy for using SVM for grinding process monitoring is discussed, while the result of the example illustrates how effective SVMs can be in determining wheel redress-life.

  1. Air quality monitoring using mobile microscopy and machine learning

    KAUST Repository

    Wu, Yi-Chen

    2017-09-08

    Rapid, accurate and high-throughput sizing and quantification of particulate matter (PM) in air is crucial for monitoring and improving air quality. In fact, particles in air with a diameter of ≤2.5 μm have been classified as carcinogenic by the World Health Organization. Here we present a field-portable cost-effective platform for high-throughput quantification of particulate matter using computational lens-free microscopy and machine-learning. This platform, termed c-Air, is also integrated with a smartphone application for device control and display of results. This mobile device rapidly screens 6.5 L of air in 30 s and generates microscopic images of the aerosols in air. It provides statistics of the particle size and density distribution with a sizing accuracy of ~93%. We tested this mobile platform by measuring the air quality at different indoor and outdoor environments and measurement times, and compared our results to those of an Environmental Protection Agency–approved device based on beta-attenuation monitoring, which showed strong correlation to c-Air measurements. Furthermore, we used c-Air to map the air quality around Los Angeles International Airport (LAX) over 24 h to confirm that the impact of LAX on increased PM concentration was present even at >7 km away from the airport, especially along the direction of landing flights. With its machine-learning-based computational microscopy interface, c-Air can be adaptively tailored to detect specific particles in air, for example, various types of pollen and mold and provide a cost-effective mobile solution for highly accurate and distributed sensing of air quality.

  2. Prognostics and Health Management of an Automated Machining Process

    Directory of Open Access Journals (Sweden)

    Cheng He

    2015-01-01

    Full Text Available Machine failure modes are presenting a major burden to the operator, the plant, and the enterprise causing significant downtime, labor cost, and reduced revenue. New technologies are emerging over the past years to monitor the machine’s performance, detect and isolate incipient failures or faults, and take appropriate actions to mitigate such detrimental events. This paper addresses the development and application of novel Prognostics and Health Management (PHM technologies to a prototype machining process (a screw-tightening machine. The enabling technologies are built upon a series of tasks starting with failure analysis, testing, and data processing aimed to extract useful features or condition indicators from raw data, a symbolic regression modeling framework, and a Bayesian estimation method called particle filtering to predict the feature state estimate accurately. The detection scheme declares the fault of a machine critical component with user specified accuracy or confidence and given false alarm rate while the prediction algorithm estimates accurately the remaining useful life of the failing component. Simulation results support the efficacy of the approach and match well the experimental data.

  3. Interpreting streaming biosignals : in search of best approaches to augmenting mobile health monitoring with machine learning for adaptive clinical decision support

    NARCIS (Netherlands)

    Jones, Valerie M.; Mendes Batista, R.J.; Bults, Richard G.A.; op den Akker, Harm; Widya, I.A.; Hermens, Hermanus J.; Huis in 't Veld, M.H.A.; Tönis, Thijs; Tonis, T.; Vollenbroek-Hutten, Miriam Marie Rosé

    2011-01-01

    We investigate Body Area Networks for ambulant patient monitoring. As well as sensing physiological parameters, BAN applications may provide feedback to patients. Automating formulation of feedback requires realtime analysis and interpretation of streaming biosignals and other context and knowledge

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

    Science.gov (United States)

    Cempel, Czesław

    2013-12-01

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

  5. Evolutionary Support Vector Machines for Transient Stability Monitoring

    Science.gov (United States)

    Dora Arul Selvi, B.; Kamaraj, N.

    2012-03-01

    Currently, power systems are in the need of fast and reliable contingency monitoring systems for the purpose of maintaining stability in the presence of deregulated and open market environment. In this paper, a quick and unfailing transient stability monitoring algorithm that considers both the symmetrical and unsymmetrical faults is presented. support vector machines (SVMs) are employed as pattern classifiers so as to construct fast relation mappings between the transient stability results and the selected input attributes using mutual information. The type of fault is recognized by a SVM classifier and the critical clearing time of the fault is estimated by a support vector regression machine. The SVM parameters are tuned by an elitist multi-objective non-dominated sorting genetic algorithm in such a manner that the best classification and regression performance are accomplished. To demonstrate the good potential of the scheme, IEEE 3 generator system and a South Indian Grid are utilized.

  6. An On-line Ferrograph for Monitoring Machine Wear

    Institute of Scientific and Technical Information of China (English)

    L(U) Xiao-jun; JING Min-qing; XIE You-bai

    2005-01-01

    In order to improve an on-line ferrograph, this paper simulates a three dimensional magnetic field distribution of an electromagnet, builds a sinking motion model of a wear particle, and investigates the motion law of wear particles under two different conditions. Both numeric results and experimental results show that the on-line ferrograph is capable of monitoring machine wear conditions by measuring the concentration and size distribution of wear particles in lubricating oil.

  7. Electric machines modeling, condition monitoring, and fault diagnosis

    CERN Document Server

    Toliyat, Hamid A; Choi, Seungdeog; Meshgin-Kelk, Homayoun

    2012-01-01

    With countless electric motors being used in daily life, in everything from transportation and medical treatment to military operation and communication, unexpected failures can lead to the loss of valuable human life or a costly standstill in industry. To prevent this, it is important to precisely detect or continuously monitor the working condition of a motor. Electric Machines: Modeling, Condition Monitoring, and Fault Diagnosis reviews diagnosis technologies and provides an application guide for readers who want to research, develop, and implement a more effective fault diagnosis and condi

  8. Ultrasonic wireless health monitoring

    Science.gov (United States)

    Petit, Lionel; Lefeuvre, Elie; Guyomar, Daniel; Richard, Claude; Guy, Philippe; Yuse, Kaori; Monnier, Thomas

    2006-03-01

    The integration of autonomous wireless elements in health monitoring network increases the reliability by suppressing power supplies and data transmission wiring. Micro-power piezoelectric generators are an attractive alternative to primary batteries which are limited by a finite amount of energy, a limited capacity retention and a short shelf life (few years). Our goal is to implement such an energy harvesting system for powering a single AWT (Autonomous Wireless Transmitter) using our SSH (Synchronized Switch Harvesting) method. Based on a non linear process of the piezoelement voltage, this SSH method optimizes the energy extraction from the mechanical vibrations. This AWT has two main functions : The generation of an identifier code by RF transmission to the central receiver and the Lamb wave generation for the health monitoring of the host structure. A damage index is derived from the variation between the transmitted wave spectrum and a reference spectrum. The same piezoelements are used for the energy harvesting function and the Lamb wave generation, thus reducing mass and cost. A micro-controller drives the energy balance and synchronizes the functions. Such an autonomous transmitter has been evaluated on a 300x50x2 mm 3 composite cantilever beam. Four 33x11x0.3 mm 3 piezoelements are used for the energy harvesting and for the wave lamb generation. A piezoelectric sensor is placed at the free end of the beam to track the transmitted Lamb wave. In this configuration, the needed energy for the RF emission is 0.1 mJ for a 1 byte-information and the Lamb wave emission requires less than 0.1mJ. The AWT can harvested an energy quantity of approximately 20 mJ (for a 1.5 Mpa lateral stress) with a 470 μF storage capacitor. This corresponds to a power density near to 6mW/cm 3. The experimental AWT energy abilities are presented and the damage detection process is discussed. Finally, some envisaged solutions are introduced for the implementation of the required data

  9. ANN Based Tool Condition Monitoring System for CNC Milling Machines

    Directory of Open Access Journals (Sweden)

    Mota-Valtierra G.C.

    2011-10-01

    Full Text Available Most of the companies have as objective to manufacture high-quality products, then by optimizing costs, reducing and controlling the variations in its production processes it is possible. Within manufacturing industries a very important issue is the tool condition monitoring, since the tool state will determine the quality of products. Besides, a good monitoring system will protect the machinery from severe damages. For determining the state of the cutting tools in a milling machine, there is a great variety of models in the industrial market, however these systems are not available to all companies because of their high costs and the requirements of modifying the machining tool in order to attach the system sensors. This paper presents an intelligent classification system which determines the status of cutt ers in a Computer Numerical Control (CNC milling machine. This tool state is mainly detected through the analysis of the cutting forces drawn from the spindle motors currents. This monitoring system does not need sensors so it is no necessary to modify the machine. The correct classification is made by advanced digital signal processing techniques. Just after acquiring a signal, a FIR digital filter is applied to the data to eliminate the undesired noisy components and to extract the embedded force components. A Wavelet Transformation is applied to the filtered signal in order to compress the data amount and to optimize the classifier structure. Then a multilayer perceptron- type neural network is responsible for carrying out the classification of the signal. Achieving a reliability of 95%, the system is capable of detecting breakage and a worn cutter.

  10. APPLICATION OF MACHINE LEARNING TO THE PREDICTION OF VEGETATION HEALTH

    Directory of Open Access Journals (Sweden)

    E. Burchfield

    2016-06-01

    Full Text Available This project applies machine learning techniques to remotely sensed imagery to train and validate predictive models of vegetation health in Bangladesh and Sri Lanka. For both locations, we downloaded and processed eleven years of imagery from multiple MODIS datasets which were combined and transformed into two-dimensional matrices. We applied a gradient boosted machines model to the lagged dataset values to forecast future values of the Enhanced Vegetation Index (EVI. The predictive power of raw spectral data MODIS products were compared across time periods and land use categories. Our models have significantly more predictive power on held-out datasets than a baseline. Though the tool was built to increase capacity to monitor vegetation health in data scarce regions like South Asia, users may include ancillary spatiotemporal datasets relevant to their region of interest to increase predictive power and to facilitate interpretation of model results. The tool can automatically update predictions as new MODIS data is made available by NASA. The tool is particularly well-suited for decision makers interested in understanding and predicting vegetation health dynamics in countries in which environmental data is scarce and cloud cover is a significant concern.

  11. Application of Machine Learning to the Prediction of Vegetation Health

    Science.gov (United States)

    Burchfield, Emily; Nay, John J.; Gilligan, Jonathan

    2016-06-01

    This project applies machine learning techniques to remotely sensed imagery to train and validate predictive models of vegetation health in Bangladesh and Sri Lanka. For both locations, we downloaded and processed eleven years of imagery from multiple MODIS datasets which were combined and transformed into two-dimensional matrices. We applied a gradient boosted machines model to the lagged dataset values to forecast future values of the Enhanced Vegetation Index (EVI). The predictive power of raw spectral data MODIS products were compared across time periods and land use categories. Our models have significantly more predictive power on held-out datasets than a baseline. Though the tool was built to increase capacity to monitor vegetation health in data scarce regions like South Asia, users may include ancillary spatiotemporal datasets relevant to their region of interest to increase predictive power and to facilitate interpretation of model results. The tool can automatically update predictions as new MODIS data is made available by NASA. The tool is particularly well-suited for decision makers interested in understanding and predicting vegetation health dynamics in countries in which environmental data is scarce and cloud cover is a significant concern.

  12. Unsupervised process monitoring and fault diagnosis with machine learning methods

    CERN Document Server

    Aldrich, Chris

    2013-01-01

    This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data

  13. Ozone Monitoring Using Support Vector Machine and K-Nearest Neighbors Methods

    Directory of Open Access Journals (Sweden)

    FALEH Rabeb

    2017-05-01

    Full Text Available Due to health impacts caused by the pollutant gases, monitoring and controlling air quality is an important field of interest. This paper deals with ozone monitoring in four stations measuring air quality located in many Tunisian cities using numerous measuring instruments and polluting gas analyzers. Prediction of ozone concentrations in two Tunisian cities, Tunis and Sfax is screened based on supervised classification models. The K -Nearest neighbors results reached 98.7 % success rate in the recognition and ozone identification. Support Vector Machines (SVM with the linear, polynomial and RBF kernel were applied to build a classifier and full accuracy (100% was again achieved with the RBF kernel.

  14. Lunar Health Monitor Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Orbital Research has successfully demonstrated a dry electrode (no electrolyte or gel required) for heart rate and ECG monitoring. Preliminary data has indicated...

  15. Structural health monitoring an advanced signal processing perspective

    CERN Document Server

    Chen, Xuefeng; Mukhopadhyay, Subhas

    2017-01-01

    This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.

  16. MONITORING DIAGNOSTIC INDICATORS DURING OPERATION OF A PRINT MACHIN

    Directory of Open Access Journals (Sweden)

    Jozef Dobránsky

    2015-11-01

    Full Text Available This article deals with monitoring diagnostic indicators during the operation of a machine used for production of packing materials with a print. It analyses low-frequency vibrations measured in individual spherical roller bearings in eight print positions. The rollers in these positions have a different pressure based on positioning these rollers in relation to the central roller. As a result, the article also deals with a correlation of pressure and level of measured low-frequency vibrations. The speed of the print machine (the speed of a line in meters per minute is a very important variable during its operation, this is why it is important to verify the values of vibrations in various speeds of the line, what can lead to revelation of one or more resonance areas. Moreover, it examines vibrations of the central roller drive and measurement of backlash of transmission cogs of this drive. Based on performed analyses recommendations for an operator of the machine have been conceived.

  17. Wearable Health Monitoring Systems Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this proposal is to demonstrate the feasibility of producing a wearable health monitoring system for the human body that is functional, comfortable,...

  18. Wearable Health Monitoring Systems Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this proposal is to demonstrate the feasibility of producing a wearable health monitoring system for the human body that is functional, comfortable,...

  19. A distributed monitoring system for spinning-machine's spindle

    Science.gov (United States)

    Hong, Yang; Ping, Yang; Zhou, Jian Ping

    2005-12-01

    As a key unit with textile coil process technology, spinning-machine's spindles composes of a braking switch, a threephase current motor, rolling bearings and a rotary cup. Aiming at on line monitoring and fault diagnosis, a distributed monitoring system was proposed for real-time data collection and high-speed transmission. In this system, an IPC worked as an upper deck computer and many single chip processors served as bottom controllers that working status data collection and transmission can be conveniently conducted. With the features of bulk processing data and large quantities of controlled nodal points in a workshop condition, the distributed monitoring system was developed with adoption of particular approaches such as a distributed configuration with PCI bus for real time data collection and highspeed transmission, logic compression algorithm for data processing, etc. Therefore this system realizes reliable and high-speed bulk data collection, transmission and processing to meet needs of real-time monitor and control of spindle units.

  20. Structural health monitoring of wind turbine blades

    Science.gov (United States)

    Rumsey, Mark A.; Paquette, Joshua A.

    2008-03-01

    As electric utility wind turbines increase in size, and correspondingly, increase in initial capital investment cost, there is an increasing need to monitor the health of the structure. Acquiring an early indication of structural or mechanical problems allows operators to better plan for maintenance, possibly operate the machine in a de-rated condition rather than taking the unit off-line, or in the case of an emergency, shut the machine down to avoid further damage. This paper describes several promising structural health monitoring (SHM) techniques that were recently exercised during a fatigue test of a 9 meter glass-epoxy and carbon-epoxy wind turbine blade. The SHM systems were implemented by teams from NASA Kennedy Space Center, Purdue University and Virginia Tech. A commercial off-the-shelf acoustic emission (AE) NDT system gathered blade AE data throughout the test. At a fatigue load cycle rate around 1.2 Hertz, and after more than 4,000,000 fatigue cycles, the blade was diagnostically and visibly failing at the out-board blade spar-cap termination point at 4.5 meters. For safety reasons, the test was stopped just before the blade completely failed. This paper provides an overview of the SHM and NDT system setups and some current test results.

  1. Machine-Learning Algorithms to Code Public Health Spending Accounts.

    Science.gov (United States)

    Brady, Eoghan S; Leider, Jonathon P; Resnick, Beth A; Alfonso, Y Natalia; Bishai, David

    Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the performances of machine-learning algorithms with manual classification of public health expenditures to determine if machines could provide a faster, cheaper alternative to manual classification. We used machine-learning algorithms to replicate the process of manually classifying state public health expenditures, using the standardized public health spending categories from the Foundational Public Health Services model and a large data set from the US Census Bureau. We obtained a data set of 1.9 million individual expenditure items from 2000 to 2013. We collapsed these data into 147 280 summary expenditure records, and we followed a standardized method of manually classifying each expenditure record as public health, maybe public health, or not public health. We then trained 9 machine-learning algorithms to replicate the manual process. We calculated recall, precision, and coverage rates to measure the performance of individual and ensembled algorithms. Compared with manual classification, the machine-learning random forests algorithm produced 84% recall and 91% precision. With algorithm ensembling, we achieved our target criterion of 90% recall by using a consensus ensemble of ≥6 algorithms while still retaining 93% coverage, leaving only 7% of the summary expenditure records unclassified. Machine learning can be a time- and cost-saving tool for estimating public health spending in the United States. It can be used with standardized public health spending categories based on the Foundational Public Health Services model to help parse public health expenditure information from other types of health-related spending, provide data that are more comparable across public health organizations, and evaluate the impact of evidence-based public health resource allocation.

  2. Liquid intake monitoring through breathing signal using machine learning

    Science.gov (United States)

    Dong, Bo; Biswas, Subir

    2013-05-01

    This paper presents the design, system structure and performance for a wireless and wearable diet monitoring system. Food and drink intake can be detected by the way of detecting a person's swallow events. The system works based on the key observation that a person's otherwise continuous breathing process is interrupted by a short apnea when she or he swallows as a part of solid or liquid intake process. We detect the swallows through the difference between normal breathing cycle and breathing cycle with swallows using a wearable chest-belt. Three popular machine learning algorithms have been applied on both time and frequency domain features. Discrimination power of features is then analyzed for applications where only small number of features is allowed. It is shown that high detection performance can be achieved with only few features.

  3. Diver Health Monitoring System

    Science.gov (United States)

    2011-09-15

    Software - Small Business Innovative Research (SBIR) Program clause contained in the above identified contract. No restrictions apply after the...safety and effectiveness—their body. The goal of this Small Business Technology Transfer (STTR) Phase II project is the development of a Diver Health...Between DHMS and Biopac -0.47 ± 0.86 -0.57 ± 1.39 -0.52 i 1.16 Across all tests, however, a standard deviation of 1.16 bpm is small and validates the

  4. Human health monitoring technology

    Science.gov (United States)

    Kim, Byung-Hyun; Yook, Jong-Gwan

    2017-05-01

    Monitoring vital signs from human body is very important to healthcare and medical diagnosis, because they contain valuable information about arterial occlusions, arrhythmia, atherosclerosis, autonomous nervous system pathologies, stress level, and obstructive sleep apnea. Existing methods, such as electrocardiogram (ECG) sensor and photoplethysmogram (PPG) sensor, requires direct contact to the skin and it can causes skin irritation and the inconvenience of long-term wearing. For reducing the inconvenience in the conventional sensors, microwave and millimeter-wave sensors have been proposed since 1970s using micro-Doppler effect from one's cardiopulmonary activity. The Doppler radar sensor can remotely detect the respiration and heartbeat up to few meters away from the subject, but they have a multiple subject issue and are not suitable for an ambulatory subject. As a compromise, a noncontact proximity vital sign sensor has been recently proposed and developed. The purpose of this paper is to review the noncontact proximity vital sign sensors for detection of respiration, heartbeat rate, and/or wrist pulse. This sensor basically employs near-field perturbation of radio-frequency (RF) planar resonator due to the proximity of the one's chest or radial artery at the wrist. Various sensing systems based on the SAW filter, phase-locked loop (PLL) synthesizer, reflectometer, and interferometer have been proposed. These self-sustained systems can measure the nearfield perturbation and transform it into DC voltage variation. Consequently, they can detect the respiration and heartbeat rate near the chest of subject and pulse from radial artery at the wrist.

  5. Electrical machines monitoring using partial discharges; Monitorizacion de maquinas electricas mediante descargas parciales

    Energy Technology Data Exchange (ETDEWEB)

    Cano, J. C.; Rodriguez Ruiz, S.

    2006-07-01

    Electrical Machines Monitoring is a philosophy that is being more and more accepted in maintenance, the application of these techniques has a lot of advantages as the life evaluation non-intrusively and the detection and evolution evaluation of defects. this paper presents the monitoring of electrical machines using the Partial Discharges technique, which allow the evaluation of insulation of Electrical Machines. Real Cases are included in the paper as samples in which this techniques has been useful to detecting defects. (Author)

  6. Using virtual machine monitors to overcome the challenges of monitoring and managing virtualized cloud infrastructures

    Science.gov (United States)

    Bamiah, Mervat Adib; Brohi, Sarfraz Nawaz; Chuprat, Suriayati

    2012-01-01

    Virtualization is one of the hottest research topics nowadays. Several academic researchers and developers from IT industry are designing approaches for solving security and manageability issues of Virtual Machines (VMs) residing on virtualized cloud infrastructures. Moving the application from a physical to a virtual platform increases the efficiency, flexibility and reduces management cost as well as effort. Cloud computing is adopting the paradigm of virtualization, using this technique, memory, CPU and computational power is provided to clients' VMs by utilizing the underlying physical hardware. Beside these advantages there are few challenges faced by adopting virtualization such as management of VMs and network traffic, unexpected additional cost and resource allocation. Virtual Machine Monitor (VMM) or hypervisor is the tool used by cloud providers to manage the VMs on cloud. There are several heterogeneous hypervisors provided by various vendors that include VMware, Hyper-V, Xen and Kernel Virtual Machine (KVM). Considering the challenge of VM management, this paper describes several techniques to monitor and manage virtualized cloud infrastructures.

  7. Individualized Behavioral Health Monitoring Tool

    Science.gov (United States)

    Mollicone, Daniel

    2015-01-01

    Behavioral health risks during long-duration space exploration missions are among the most difficult to predict, detect, and mitigate. Given the anticipated extended duration of future missions and their isolated, extreme, and confined environments, there is the possibility that behavior conditions and mental disorders will develop among astronaut crew. Pulsar Informatics, Inc., has developed a health monitoring tool that provides a means to detect and address behavioral disorders and mental conditions at an early stage. The tool integrates all available behavioral measures collected during a mission to identify possible health indicator warning signs within the context of quantitatively tracked mission stressors. It is unobtrusive and requires minimal crew time and effort to train and utilize. The monitoring tool can be deployed in space analog environments for validation testing and ultimate deployment in long-duration space exploration missions.

  8. Actualities and Development of Heavy-Duty CNC Machine Tool Thermal Error Monitoring Technology

    Science.gov (United States)

    Zhou, Zu-De; Gui, Lin; Tan, Yue-Gang; Liu, Ming-Yao; Liu, Yi; Li, Rui-Ya

    2017-09-01

    Thermal error monitoring technology is the key technological support to solve the thermal error problem of heavy-duty CNC (computer numerical control) machine tools. Currently, there are many review literatures introducing the thermal error research of CNC machine tools, but those mainly focus on the thermal issues in small and medium-sized CNC machine tools and seldom introduce thermal error monitoring technologies. This paper gives an overview of the research on the thermal error of CNC machine tools and emphasizes the study of thermal error of the heavy-duty CNC machine tool in three areas. These areas are the causes of thermal error of heavy-duty CNC machine tool and the issues with the temperature monitoring technology and thermal deformation monitoring technology. A new optical measurement technology called the "fiber Bragg grating (FBG) distributed sensing technology" for heavy-duty CNC machine tools is introduced in detail. This technology forms an intelligent sensing and monitoring system for heavy-duty CNC machine tools. This paper fills in the blank of this kind of review articles to guide the development of this industry field and opens up new areas of research on the heavy-duty CNC machine tool thermal error.

  9. Wearable sensors for health monitoring

    Science.gov (United States)

    Suciu, George; Butca, Cristina; Ochian, Adelina; Halunga, Simona

    2015-02-01

    In this paper we describe several wearable sensors, designed for monitoring the health condition of the patients, based on an experimental model. Wearable sensors enable long-term continuous physiological monitoring, which is important for the treatment and management of many chronic illnesses, neurological disorders, and mental health issues. The system is based on a wearable sensors network, which is connected to a computer or smartphone. The wearable sensor network integrates several wearable sensors that can measure different parameters such as body temperature, heart rate and carbon monoxide quantity from the air. After the portable sensors measuring parameter values, they are transmitted by microprocessor through the Bluetooth to the application developed on computer or smartphone, to be interpreted.

  10. A REMOTE HEALTH MONITORING MESSENGER

    Directory of Open Access Journals (Sweden)

    Sharmili Minu.DH

    2013-02-01

    Full Text Available Health is an important factor of every human being. Remote health monitoring messenger is needed for the people to reduce their inconvenience in travel to hospitals due to ailing health. Ill-patientrequires accurate decision to be taken immediately in critical situations, so that life-protecting and lifesaving therapy can be properly applied. In recent years, sensors are used in each and every fast developing application for designing the miniaturized system which is much easier for people use. A remote health monitoring messenger informs the doctor about the patient condition through wireless media such as Global System for Mobile communication. The system specifically deals with the signal conditioning and data acquisition of heart beat, temperature, and blood pressure of human body. The Heart beat sensor is used to read the patient’s beats per minute (bpm and temperature sensor to measure the body temperature of patient externally and pressure sensor to measure the level of pressure in blood. Signals obtained from sensors are fed into the microcontroller for processing and medicine is prescribed as first aid for patient to control the parameters through visual basic. A message is then sent to the doctor for further actions to be taken for treatment of patient after first aid. The system has a very good response time and it is cost effective.

  11. Solder Joint Health Monitoring Testbed

    Science.gov (United States)

    Delaney, Michael M.; Flynn, James G.; Browder, Mark E.

    2009-01-01

    A method of monitoring the health of selected solder joints, called SJ-BIST, has been developed by Ridgetop Group Inc. under a Small Business Innovative Research (SBIR) contract. The primary goal of this research program is to test and validate this method in a flight environment using realistically seeded faults in selected solder joints. An additional objective is to gather environmental data for future development of physics-based and data-driven prognostics algorithms. A test board is being designed using a Xilinx FPGA. These boards will be tested both in flight and on the ground using a shaker table and an altitude chamber.

  12. A Sensor-less Method for Online Thermal Monitoring of Switched Reluctance Machine

    DEFF Research Database (Denmark)

    Wang, Chao; Liu, Hui; Liu, Xiao

    2015-01-01

    Stator winding is one of the most vulnerable parts in Switched Reluctance Machine (SRM), especially under thermal stresses during frequently changing operation circumstances and susceptible heat dissipation conditions. Thus real-time online thermal monitoring of the stator winding is of great......, neither machine parameters nor thermal impedance parameters are required in the scheme. Simulation results under various operating conditions confirm the proposed sensor-less online thermal monitoring approach....

  13. Evolutionary Autonomous Health Monitoring System (EAHMS) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — For supporting NASA's Robotics, Tele-Robotics and Autonomous Systems Roadmap, we are proposing the "Evolutionary Autonomous Health Monitoring System" (EAHMS) for...

  14. A low cost implementation of multi-parameter patient monitor using intersection kernel support vector machine classifier

    Science.gov (United States)

    Mohan, Dhanya; Kumar, C. Santhosh

    2016-03-01

    Predicting the physiological condition (normal/abnormal) of a patient is highly desirable to enhance the quality of health care. Multi-parameter patient monitors (MPMs) using heart rate, arterial blood pressure, respiration rate and oxygen saturation (S pO2) as input parameters were developed to monitor the condition of patients, with minimum human resource utilization. The Support vector machine (SVM), an advanced machine learning approach popularly used for classification and regression is used for the realization of MPMs. For making MPMs cost effective, we experiment on the hardware implementation of the MPM using support vector machine classifier. The training of the system is done using the matlab environment and the detection of the alarm/noalarm condition is implemented in hardware. We used different kernels for SVM classification and note that the best performance was obtained using intersection kernel SVM (IKSVM). The intersection kernel support vector machine classifier MPM has outperformed the best known MPM using radial basis function kernel by an absoute improvement of 2.74% in accuracy, 1.86% in sensitivity and 3.01% in specificity. The hardware model was developed based on the improved performance system using Verilog Hardware Description Language and was implemented on Altera cyclone-II development board.

  15. Forest health monitoring: 2006 national technical report

    Science.gov (United States)

    Mark J. Ambrose; Barbara L. Conkling

    2009-01-01

    The Forest Health Monitoring Program’s annual national technical reportpresents results of forest health analyses from a national perspective usingdata from a variety of sources. The report is organized according to the

  16. Discovery machines accelerators for science, technology, health and innovation

    CERN Document Server

    Australian Academy of Sciences

    2016-01-01

    Discovery machines: Accelerators for science, technology, health and innovation explores the science of particle accelerators, the machines that supercharge our ability to discover the secrets of nature and have opened up new tools in medicine, energy, manufacturing, and the environment as well as in pure research. Particle accelerators are now an essential ingredient in discovery science because they offer new ways to analyse the world, such as by probing objects with high energy x-rays or colliding them beams of electrons. They also have a huge—but often unnoticed—impact on all our lives; medical imaging, cancer treatment, new materials and even the chips that power our phones and computers have all been transformed by accelerators of various types. Research accelerators also provide fundamental infrastructure that encourages better collaboration between international and domestic scientists, organisations and governments.

  17. Web-Enabled Remote Machine Monitoring and Prognostics

    Institute of Scientific and Technical Information of China (English)

    Jay Lee; Jun Ni

    2004-01-01

    @@ 1 INTRODUCTION Today's machine tool industries are facing unprecedented challenges brought about by development of outsourcing and low cost manufac-turing in Asia. Manufacturing outsourcing provided many opportu-nities but also added challenges to produce and deliver products with improved productivity, quality, service and costs. Lead times must be cut short to their extreme extend to meet need the changing demands of customers in different regions of the world. Products are required to be make-to-order, which requires a tight control and near-zero downtime of the plant floor, equipment and devices.

  18. ONBOARD MONITORING OF ENGINE OIL RESOURCE WORKING-OUT RATE IN WHEELED AND CATERPILLAR MACHINES

    Directory of Open Access Journals (Sweden)

    Yu. D. Karpievich

    2014-01-01

    Full Text Available An engine oil is capable reliably and longtime to perform specified functions only in the case when its properties correspond to those thermal, mechanical and chemical impacts to which the oil is subjected in the engine. Compatibility of the engine design, its uprate and oil properties is one of the main conditions for provision of high operational reliability. Type and properties of fuel, quality of an engine oil, engine type, its design, its health, its operational regime and conditions and a number of other factors influence on intensity of oil contamination in the operated engine. Oil quality is deteriorated due to accumulation of incomplete combustion products in it and this process is associated with the engine's health. This leads to reduction of viscosity, deterioration of lubrication ability, troubles in fluid friction mode. Combustion products have rather high amount of aggressive corrosive oxides.Service-life of engine oil prior to its change is determined not only by automobile mileage or tractor operating time but also by the period of time within which this work has been carried out. Corrosion processes are speeding up, protective processes are worsening, oil ageing is accelerating when vehicles have short daily and small mileages. So it is necessary to change oil at least annually.A new method for onboard monitoring of engine oil resource working-out rate in wheeled and caterpillar machines has been developed in the paper. Usage of fuel expended volume by engine while determining engine oil resource working-out rate makes it possible timely to assess a residual resource of the engine oil and also predict the date of its change at any operational period of wheeled and caterpillar machines.

  19. Structural health monitoring meets data mining

    NARCIS (Netherlands)

    Miao, Shengfa

    2014-01-01

    With the development of sensing and data processing techniques, monitoring physical systems in the field with a sensor network is becoming a feasible option for many domains. Such monitoring systems are referred to as Structural Health Monitoring (SHM) systems. By definition, SHM is the process of i

  20. Process monitoring evaluation and implementation for the wood abrasive machining process.

    Science.gov (United States)

    Saloni, Daniel E; Lemaster, Richard L; Jackson, Steven D

    2010-01-01

    Wood processing industries have continuously developed and improved technologies and processes to transform wood to obtain better final product quality and thus increase profits. Abrasive machining is one of the most important of these processes and therefore merits special attention and study. The objective of this work was to evaluate and demonstrate a process monitoring system for use in the abrasive machining of wood and wood based products. The system developed increases the life of the belt by detecting (using process monitoring sensors) and removing (by cleaning) the abrasive loading during the machining process. This study focused on abrasive belt machining processes and included substantial background work, which provided a solid base for understanding the behavior of the abrasive, and the different ways that the abrasive machining process can be monitored. In addition, the background research showed that abrasive belts can effectively be cleaned by the appropriate cleaning technique. The process monitoring system developed included acoustic emission sensors which tended to be sensitive to belt wear, as well as platen vibration, but not loading, and optical sensors which were sensitive to abrasive loading.

  1. Application of Support Vector Machine to Forex Monitoring

    Science.gov (United States)

    Kamruzzaman, Joarder; Sarker, Ruhul A.

    Previous studies have demonstrated superior performance of artificial neural network (ANN) based forex forecasting models over traditional regression models. This paper applies support vector machines to build a forecasting model from the historical data using six simple technical indicators and presents a comparison with an ANN based model trained by scaled conjugate gradient (SCG) learning algorithm. The models are evaluated and compared on the basis of five commonly used performance metrics that measure closeness of prediction as well as correctness in directional change. Forecasting results of six different currencies against Australian dollar reveal superior performance of SVM model using simple linear kernel over ANN-SCG model in terms of all the evaluation metrics. The effect of SVM parameter selection on prediction performance is also investigated and analyzed.

  2. An intelligent approach to machine component health prognostics by utilizing only truncated histories

    Science.gov (United States)

    Lu, Chen; Tao, Laifa; Fan, Huanzhen

    2014-01-01

    Numerous techniques and methods have been proposed to reduce the production downtime, spare-part inventory, maintenance cost, and safety hazards of machineries and equipment. Prognostics are regarded as a significant and promising tool for achieving these benefits for machine maintenance. However, prognostic models, particularly probabilistic-based methods, require a large number of failure instances. In practice, engineering assets are rarely being permitted to run to failure. Many studies have reported valuable models and methods that engage in maximizing both truncated and failure data. However, limited studies have focused on cases where only truncated data are available, which is common in machine condition monitoring. Therefore, this study develops an intelligent machine component prognostics system by utilizing only truncated histories. First, the truncated Minimum Quantization Error (MQE) histories were obtained by Self-organizing Map network after feature extraction. The chaos-based parallel multilayer perceptron network and polynomial fitting for residual errors were adopted to generate the predicted MQEs and failure times following the truncation times. The feed-forward neural network (FFNN) was trained with inputs both from the truncated MQE histories and from the predicted MQEs. The target vectors of survival probabilities were estimated by intelligent product limit estimator using the truncation times and generated failure times. After validation, the FFNN was applied to predict the machine component health of individual units. To validate the proposed method, two cases were considered by using the degradation data generated by bearing testing rig. Results demonstrate that the proposed method is a promising intelligent prognostics approach for machine component health.

  3. Local measurement for structural health monitoring

    Institute of Scientific and Technical Information of China (English)

    G.Z.Qi; Guo Xun; Qi Xiaozhai; W. Dong; P.Chang

    2005-01-01

    Localized nature of damage in structures requires local measurements for structural health monitoring. The local measurement means to measure the local, usually higher modes of the vibration in a structure. Three fundamental issues about the local measurement for structural health monitoring including (1) the necessity of making local measurement, (2) the difficulty of making local measurement and (3) how to make local measurement are addressed in this paper. The results from both the analysis and the tests show that the local measurement can successfully monitor the structural health status as long as the local modes are excited. Unfortunately, the results also illustrate that it is difficult to excite local modes in a structure.Therefore, in order to carry structural health monitoring into effect, we must (1) ensure that the local modes are excited, and (2) deploy enough sensors in a structure so that the local modes can be monitored.

  4. Forest health monitoring: 2001 national technical report

    Science.gov (United States)

    Barbara L. Conkling; John W. Coulston; Mark J. Ambrose

    2005-01-01

    The Forest Health Monitoring (FHM) Program’s annual national report uses FHM data, as well as data from a variety of other programs, to provide an overview of forest health based on the criteria and indicators of sustainable forestry framework of the Santiago Declaration. It presents information about the status of and trends in various forest health indicators...

  5. An Embedded Condition Monitoring and Fault Diagnosis System for Rotary Machines

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    An intelligent machine is the earnest aspiration of people. From the point of view to construct an intelligent machine with self-monitoring and self-diagnosis abilities, the technology for realizing an internet oriented embedded intelligent condition monitoring and fault diagnosis system for the rotating machine with remote monitoring, diagnosis, maintenance and upgrading functions is introduced systematically. Based on the DSP ( Digital Signal Processor) and embedded microcomputer, the system can measure and store the machine work status in real time, such as the rotating speed and vibration,etc. In the system, the DSP chip is used to do the fault signal processing and feature extraction, and the embedded microcomputer with a customized Linux operation system is used to realize the internet oriented remote software upgrading and system maintenance. Embedded fault diagnosis software based on mobile agent technology is also designed in the system, which can interconnect with the remote fault diagnosis center to realize the collaborative diagnosis. The embedded condition monitoring and fault diagnosis technology proposed in this paper will effectively improve the intelligence degree of the fault diagnosis system.

  6. Structural health monitoring using genetic fuzzy systems

    CERN Document Server

    Pawar, Prashant M

    2014-01-01

    The high profile of structural health monitoring (SHM) will add urgency to this detailed treatment of intelligent SHM development and implementation via the evolutionary system, which uses a genetic algorithm to automate the development of the fuzzy system.

  7. Integrating structural health and condition monitoring

    DEFF Research Database (Denmark)

    May, Allan; Thöns, Sebastian; McMillan, David

    2015-01-01

    There is a large financial incentive to minimise operations and maintenance (O&M) costs for offshore wind power by optimising the maintenance plan. The integration of condition monitoring (CM) and structural health monitoring (SHM) may help realise this. There is limited work on the integration...

  8. UWB Radar for health monitoring applications

    OpenAIRE

    Trullenque Ortiz, Martín

    2016-01-01

    There is a need for non-invasive monitoring system of key cardio-pulmonary functions and other internal structures. UWB radar offers advantages for health monitoring applications: - Skin contact not required - Works through clothing and skin - Extremely high-resolution UWB able to detect sub-mm movement of internal structures - Insensitive to environmental conditions - Low-power transceivers are relatively inexpensive and easily miniaturized - Enables a new class of wearable/wireless health m...

  9. Research on Key Techniques of Condition Monitoring and Fault Diagnosing Systems of Machine Groups

    Institute of Scientific and Technical Information of China (English)

    WANG Yan-kai; LIAO Ming-fu; WANG Si-ji

    2005-01-01

    This paper describes the development of the condition monitoring and fault diagnosing system of a group of rotating machinery. The data management is performed by means of double redundant data bases stored simultaneously in both the analyzing server and monitoring client. In this way, high reliability of the storage of data is guaranteed. Condensation of trend data releases much space resource of the hard disk. Diagnosing strategies orientated to different typical faults of rotating machinery are developed and incorporated into the system. Experimental verification shows that the system is suitable and effective for condition monitoring and fault diagnosing for a rotating machine group.

  10. Mobile health monitoring system for community health workers

    CSIR Research Space (South Africa)

    Sibiya, G

    2014-09-01

    Full Text Available . Functional description The application provides technology for real time, dependable and intelligent health monitoring by health workers in the field. It integrates a set of wearable wireless sensors with a mobile computing device, such as a 3... communities remain a challenge for many governments, technological innovations that can increase prevention and control of NCDs are needed. Wearable health devices such as ambulatory blood pressure (ABP) monitors are a step in the right direction. ABP...

  11. On the value of structural health monitoring

    DEFF Research Database (Denmark)

    Faber, Michael Havbro; Thöns, Sebastian

    2014-01-01

    Health monitoring has, over the last 2-3 decades, become a topic of significant interest within the structural engineering research community, but also in the broader areas of civil and mechanical engineering. Whereas the merits of Structural Health Monitoring (SHM) are generally appreciated in q...... of SHM an example is provided. The example addresses the life-cycle benefit maximization for offshore jacket structures subject to fatigue crack growth utilizing monitoring of near field fatigue stresses as a means of optimizing risk based inspection and maintenance strategies....

  12. Forest health monitoring: 2003 national technical report

    Science.gov (United States)

    John W. Coulston; Mark J. Ambrose; Kurt H. Riitters; Barbara L. Conkling; William D. Smith

    2005-01-01

    The Forest Health Monitoring Program’s annual national reports present results from forest health data analyses focusing on a national perspective. The Criteria and Indicators for the Conservation and Sustainable Management of Temperate and Boreal Forests are used as a reporting framework. This report has five main sections. The first contains introductory material....

  13. Hybrid Modeling Improves Health and Performance Monitoring

    Science.gov (United States)

    2007-01-01

    Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

  14. Research on Remote Video Monitoring System Used for Numerical Control Machine Tools Based on Embedded Technology

    Institute of Scientific and Technical Information of China (English)

    LIU Quan; QU Xuehong; ZHOU Henglin; LONG Yihong

    2006-01-01

    This paper designed an embedded video monitoring system using DSP(Digital Signal Processing) and ARM(Advanced RISC Machine). This system is an important part of self-service operation of numerical control machine tools. At first the analog input signals from the CCD(Charge Coupled Device) camera are transformed into digital signals, and then output to the DSP system, where the video sequence is encoded according to the new generation image compressing standard called H.264. The code will be transmitted to the ARM system through xBus, and then be packed in the ARM system and transmitted to the client port through the gateway. Web technology, embedded technology and image compressing as well as coding technology are integrated in the system, which can be widely used in self-service operation of numerical control machine tools and intelligent robot control areas.

  15. Structural Health Monitoring with Fiber Bragg Grating and Piezo Arrays

    Science.gov (United States)

    Black, Richard J.; Faridian, Ferey; Moslehi, Behzad; Sotoudeh, Vahid

    2012-01-01

    Structural health monitoring (SHM) is one of the most important tools available for the maintenance, safety, and integrity of aerospace structural systems. Lightweight, electromagnetic-interference- immune, fiber-optic sensor-based SHM will play an increasing role in more secure air transportation systems. Manufacturers and maintenance personnel have pressing needs for significantly improving safety and reliability while providing for lower inspection and maintenance costs. Undetected or untreated damage may grow and lead to catastrophic structural failure. Damage can originate from the strain/stress history of the material, imperfections of domain boundaries in metals, delamination in multi-layer materials, or the impact of machine tools in the manufacturing process. Damage can likewise develop during service life from wear and tear, or under extraordinary circumstances such as with unusual forces, temperature cycling, or impact of flying objects. Monitoring and early detection are key to preventing a catastrophic failure of structures, especially when these are expected to perform near their limit conditions.

  16. Optical Structural Health Monitoring Device

    Science.gov (United States)

    Buckner, Benjamin D.; Markov, Vladimir; Earthman, James C.

    2010-01-01

    This non-destructive, optical fatigue detection and monitoring system relies on a small and unobtrusive light-scattering sensor that is installed on a component at the beginning of its life in order to periodically scan the component in situ. The method involves using a laser beam to scan the surface of the monitored component. The device scans a laser spot over a metal surface to which it is attached. As the laser beam scans the surface, disruptions in the surface cause increases in scattered light intensity. As the disruptions in the surface grow, they will cause the light to scatter more. Over time, the scattering intensities over the scanned line can be compared to detect changes in the metal surface to find cracks, crack precursors, or corrosion. This periodic monitoring of the surface can be used to indicate the degree of fatigue damage on a component and allow one to predict the remaining life and/or incipient mechanical failure of the monitored component. This wireless, compact device can operate for long periods under its own battery power and could one day use harvested power. The prototype device uses the popular open-source TinyOS operating system on an off-the-shelf Mica2 sensor mote, which allows wireless command and control through dynamically reconfigurable multi-node sensor networks. The small size and long life of this device could make it possible for the nodes to be installed and left in place over the course of years, and with wireless communication, data can be extracted from the nodes by operators without physical access to the devices. While a prototype has been demonstrated at the time of this reporting, further work is required in the system s development to take this technology into the field, especially to improve its power management and ruggedness. It should be possible to reduce the size and sensitivity as well. Establishment of better prognostic methods based on these data is also needed. The increase of surface roughness with

  17. Machine and lubricant condition monitoring for extended equipment lifetimes and predictive maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Lukas, M.; Anderson, D.P. [Spectro Incorporated, Littleton, Massachusetts (United States)

    1997-12-31

    Predictive maintenance has gained wide acceptance as a cost cutting strategy in modern industry. Condition monitoring by lubricant analysis is one of the basic tools of a predictive maintenance program along with vibration monitoring, performance monitoring and thermography. In today`s modern power generation, manufacturing, refinery, transportation, mining, and military operations, the cost of equipment maintenance, service, and lubricants are ever increasing. Parts, labor, equipment downtime and lubricant prices and disposal costs are a primary concern in a well run maintenance management program. Machine condition monitoring based on oil analysis has become a prerequisite in most maintenance programs. Few operations can afford not to implement a program if they wish to remain competitive, and in some cases, profitable. This presentation describes a comprehensive Machine Condition Monitoring Program based on oil analysis. Actual operational condition monitoring programs will be used to review basic components and analytical requirements. Case histories will be cited as examples of cost savings, reduced equipment downtime and increased efficiencies of maintenance programs through a well managed oil analysis program. (orig.)

  18. In situ health monitoring of piezoelectric sensors

    Science.gov (United States)

    Jensen, Scott L. (Inventor); Drouant, George J. (Inventor)

    2013-01-01

    An in situ health monitoring apparatus may include an exciter circuit that applies a pulse to a piezoelectric transducer and a data processing system that determines the piezoelectric transducer's dynamic response to the first pulse. The dynamic response can be used to evaluate the operating range, health, and as-mounted resonance frequency of the transducer, as well as the strength of a coupling between the transducer and a structure and the health of the structure.

  19. Forest health monitoring: 2004 national technical report

    Science.gov (United States)

    John W. Coulston; Mark J. Ambrose; Kurt H. Riitters; Barbara L. Conkling

    2005-01-01

    The Forest Health Monitoring (FHM) Program’s annual national technical report presents results of forest health analyses from a national perspective using data from a variety of sources. Results presented in the report pertain to the Santiago Declaration’s Criterion 1— Conservation of Biological Diversity and Criterion 3—Maintenance of Forest Ecosystem Health and...

  20. Forest health monitoring: 2002 national technical report

    Science.gov (United States)

    John W. Coulston; Mark J. Ambrose; Kurt H. Riitters; Barbara L. Conkling

    2005-01-01

    The Forest Health Monitoring (FHM) Program’s annual national technical report presents results of forest health analyses from a national perspective using data from a variety of sources. This annual report focuses on “Criterion 3—Maintenance of Forest Ecosystem Health and Vitality” from the “Criteria and Indicators of Sustainable Forestry of the Santiago Declaration”...

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

    Science.gov (United States)

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

    2016-02-01

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

  2. Small Autonomous Aircraft Servo Health Monitoring

    Science.gov (United States)

    Quintero, Steven

    2008-01-01

    Small air vehicles offer challenging power, weight, and volume constraints when considering implementation of system health monitoring technologies. In order to develop a testbed for monitoring the health and integrity of control surface servos and linkages, the Autonomous Aircraft Servo Health Monitoring system has been designed for small Uninhabited Aerial Vehicle (UAV) platforms to detect problematic behavior from servos and the air craft structures they control, This system will serve to verify the structural integrity of an aircraft's servos and linkages and thereby, through early detection of a problematic situation, minimize the chances of an aircraft accident. Embry-Riddle Aeronautical University's rotary-winged UAV has an Airborne Power management unit that is responsible for regulating, distributing, and monitoring the power supplied to the UAV's avionics. The current sensing technology utilized by the Airborne Power Management system is also the basis for the Servo Health system. The Servo Health system measures the current draw of the servos while the servos are in Motion in order to quantify the servo health. During a preflight check, deviations from a known baseline behavior can be logged and their causes found upon closer inspection of the aircraft. The erratic behavior nay include binding as a result of dirt buildup or backlash caused by looseness in the mechanical linkages. Moreover, the Servo Health system will allow elusive problems to be identified and preventative measures taken to avoid unnecessary hazardous conditions in small autonomous aircraft.

  3. A Web-based machining process monitoring system for E-manufacturing implementation

    Institute of Scientific and Technical Information of China (English)

    SHIN Bong-cheol; KIM Gun-hee; CHOI Jin-hwa; JEON Byung-cheol; LEE Honghee; CHO Myeong-woo; HAN Jin-yong; PARK Dong-sam

    2006-01-01

    Recently, with the rapid growth ofinformation technology, many studies have been performed to implement Web-based manufacturing system. Such technologies are expected to meet the need of many manufacturing industries who want to adopt E-manufacturing system for the construction of globalization, agility, and digitalization to cope with the rapid changing market requirements. In this research, a real-time Web-based machine tool and machining process monitoring system is developed as the first step for implementing E-manufacturing system. In this system, the current variations of the main spindle and feeding motors are measured using hall sensors. And the relationship between the cutting force and the spindle motor RMS (Root Mean Square) current at various spindle rotational speeds is obtained. Thermocouples are used to measure temperature variations of important heat sources of a machine tool. Also, a rule-based expert system is applied in order to decide the machining process and machine tool are in normal conditions. Finally, the effectiveness of the developed system is verified through a series of experiments.

  4. Maintaining the Health of Software Monitors

    Science.gov (United States)

    Person, Suzette; Rungta, Neha

    2013-01-01

    Software health management (SWHM) techniques complement the rigorous verification and validation processes that are applied to safety-critical systems prior to their deployment. These techniques are used to monitor deployed software in its execution environment, serving as the last line of defense against the effects of a critical fault. SWHM monitors use information from the specification and implementation of the monitored software to detect violations, predict possible failures, and help the system recover from faults. Changes to the monitored software, such as adding new functionality or fixing defects, therefore, have the potential to impact the correctness of both the monitored software and the SWHM monitor. In this work, we describe how the results of a software change impact analysis technique, Directed Incremental Symbolic Execution (DiSE), can be applied to monitored software to identify the potential impact of the changes on the SWHM monitor software. The results of DiSE can then be used by other analysis techniques, e.g., testing, debugging, to help preserve and improve the integrity of the SWHM monitor as the monitored software evolves.

  5. STUDY OF MACHINING PROCESS MONITORING OF FMS BASED ON TIME SERIES ANALYSIS

    Institute of Scientific and Technical Information of China (English)

    Zhang Libin; Su Jian; Liu Yumei; Jia Yazhou

    2004-01-01

    FMS is a sort of highly automatic machining system,how to ensure part quality is master key to system highly active running.At first, series of machining dimension and process capability of flexible manufacturing system(FMS), is analyzed.Result of its, strong self-correlation of data series shows that time series analysis is applicable to data series analyzed.Based on-line modeling and forecasting for data series, principle and method of feedback compensation control is proposed.On a foundation of the virtual instrument platform, Labview of national instrument (NI), FMS dimension and process capability monitoring system(monitoring system) is developed.In practice, it is proved that part quality and process capability of FMS are greatly improved.

  6. Remediating radium contaminated legacy sites: Advances made through machine learning in routine monitoring of “hot” particles

    Energy Technology Data Exchange (ETDEWEB)

    Varley, Adam, E-mail: a.l.varley@stir.ac.uk [Department of Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA (United Kingdom); Tyler, Andrew, E-mail: a.n.tyler@stir.ac.uk [Department of Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA (United Kingdom); Smith, Leslie, E-mail: l.s.smith@cs.stir.ac.uk [Department of Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA (United Kingdom); Dale, Paul, E-mail: paul.dale@sepa.org.uk [Scottish Environmental Protection Agency, Radioactive Substances, Strathallan House, Castle Business Park, Stirling FK9 4TZ (United Kingdom); Davies, Mike, E-mail: Mike.Davies@nuvia.co.uk [Nuvia Limited, The Library, Eight Street, Harwell Oxford, Didcot, Oxfordshire OX11 0RL (United Kingdom)

    2015-07-15

    The extensive use of radium during the 20th century for industrial, military and pharmaceutical purposes has led to a large number of contaminated legacy sites across Europe and North America. Sites that pose a high risk to the general public can present expensive and long-term remediation projects. Often the most pragmatic remediation approach is through routine monitoring operating gamma-ray detectors to identify, in real-time, the signal from the most hazardous heterogeneous contamination (hot particles); thus facilitating their removal and safe disposal. However, current detection systems do not fully utilise all spectral information resulting in low detection rates and ultimately an increased risk to the human health. The aim of this study was to establish an optimised detector-algorithm combination. To achieve this, field data was collected using two handheld detectors (sodium iodide and lanthanum bromide) and a number of Monte Carlo simulated hot particles were randomly injected into the field data. This allowed for the detection rate of conventional deterministic (gross counts) and machine learning (neural networks and support vector machines) algorithms to be assessed. The results demonstrated that a Neural Network operated on a sodium iodide detector provided the best detection capability. Compared to deterministic approaches, this optimised detection system could detect a hot particle on average 10 cm deeper into the soil column or with half of the activity at the same depth. It was also found that noise presented by internal contamination restricted lanthanum bromide for this application. - Highlights: • Land contaminated with radium is hazardous to human health. • Routine monitoring permits identification and removal of radioactive hot particles. • Current alarm algorithms do not provide reliable hot particle detection. • Spectral processing using Machine Learning significantly improves detection.

  7. A Novel Framework for Agent-Based Production Remote Monitoring System Design: A Case Study of Injection Machines

    Directory of Open Access Journals (Sweden)

    Yun-Yao Chen

    2013-01-01

    Full Text Available Currently, many injection machine controllers in the market involve PC-based architecture, so engineers can conduct simple and quick operation on the controller via a human-machine interface. However, when there are too many machines in a factory, mining algorithms for multimachines and development of rear-end applications are often trivial and complicated. The operation systems of the machines in factories are different, and different machine models need different transfer protocols for data mining. Therefore, we need to develop different information platforms and machine production information mining systems for cross platform controllers. This research proposed an agent based remote monitoring system for injection machines to solve this problem. The agent-based production remote monitor system framework in this research has the following advantages. (1 It can transmit machine information cross platforms regard of constraints of different operating systems. Controlling frameworks can process data mining and transmission. (2 It can send back machine information actively to the manager without operation of machine operators, mine specific information effectively, and screen unnecessary machine information. (3 It can categorize the required information, filter extra information, and elicit data the user needs.

  8. Remote personal health monitoring with radio waves

    Science.gov (United States)

    Nguyen, Andrew

    2008-03-01

    We present several techniques utilizing radio-frequency identification (RFID) technology for personal health monitoring. One technique involves using RFID sensors external to the human body, while another technique uses both internal and external RFID sensors. Simultaneous monitoring of many patients in a hospital setting can also be done using networks of RFID sensors. All the monitoring are done wirelessly, either continuously or periodically in any interval, in which the sensors collect information on human parts such as the lungs or heart and transmit this information to a router, PC or PDA device connected to the internet, from which patient's condition can be diagnosed and viewed by authorized medical professionals in remote locations. Instantaneous information allows medical professionals to intervene properly and timely to prevent possible catastrophic effects to patients. The continuously monitored information provides medical professionals more complete and long-term studies of patients. All of these result in not only enhancement of the health treatment quality but also significant reduction of medical expenditure. These techniques demonstrate that health monitoring of patients can be done wirelessly at any time and any place without interfering with the patients' normal activities. Implementing the RFID technology would not only help reduce the enormous and significantly growing medical costs in the U.S.A., but also help improve the health treatment capability as well as enhance the understanding of long-term personal health and illness.

  9. A novel framework of change-point detection for machine monitoring

    Science.gov (United States)

    Lu, Guoliang; Zhou, Yiqi; Lu, Changhou; Li, Xueyong

    2017-01-01

    The need for automatic machine monitoring has been well known in industries for many years. Although it has been widely accepted that a change in the structural property can indicate the fault in rotating machinery components (e.g., bearing and gears), automatic algorithms for this task are still in progress. In this paper, we propose a novel framework for change-point detection in machine monitoring. The framework includes two phases: (1) anomaly measure: on the basis of an automatic regression (AR) model, a new computation method is proposed to measure anomalies in a given time series which does not require any reference data from other measurement(s); (2) change detection: a new statistical test is employed by using martingale for detecting a potential change in the series which can be operated in an unsupervised and self-conducted manner. Experimental results on testing data captured in real scenarios demonstrated the effectiveness and the realizability of the proposed framework for change-point detection in machine monitoring, which suggests that our framework can be directly applicable in many real-world applications.

  10. Structural health monitoring with fiber optic sensors

    Institute of Scientific and Technical Information of China (English)

    F.ANSARI

    2009-01-01

    Optical fiber sensors have been successfully implemented in aeronautics, mechanical systems, and medical applications. Civil structures pose further challenges in monitoring mainly due to their large dimensions, diversity and heterogeneity of materials involved, and hostile construction environment. This article provides a summary of basic principles pertaining to practical health monitoring of civil engineering structures with optical fiber sensors. The issues discussed include basic sensor principles, strain transfer mechanism, sensor packaging, sensor placement in construction environment, and reliability and survivability of the sensors.

  11. Research on Remote Monitoring and Fault Diagnosis Technology of Numerical Control Machine

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jianyu; GAO Lixin; CUI Lingli; LI Xianghui; WANG Yingwang

    2006-01-01

    Based on the internet technology, it has become possible to complete remote monitoring and fault diagnosis for the numerical control machine. In order to capture the micro-shock signal induced by the incipient fault on the rotating parts, the resonance demodulation technology is utilized in the system. As a subsystem of the remote monitoring system, the embedded data acquisition instrument not only integrates the demodulation board but also complete the collection and preprocess of monitoring data from different machines. Furthermore, through connecting to the internet, the data can be transferred to the remote diagnosis center and data reading and writing function can be finished in the database. At the same time, the problem of the IP address floating in the dial-up of web server is solved by the dynamic DNS technology. Finally, the remote diagnosis software developed on the LabVIEW platform can analyze the monitoring data from manufacturing field. The research results have indicated that the equipment status can be monitored by the system effectively.

  12. Acoustic Techniques for Structural Health Monitoring

    Science.gov (United States)

    Frankenstein, B.; Augustin, J.; Hentschel, D.; Schubert, F.; Köhler, B.; Meyendorf, N.

    2008-02-01

    Future safety and maintenance strategies for industrial components and vehicles are based on combinations of monitoring systems that are permanently attached to or embedded in the structure, and periodic inspections. The latter belongs to conventional nondestructive evaluation (NDE) and can be enhanced or partially replaced by structural health monitoring systems. However, the main benefit of this technology for the future will consist of systems that can be differently designed based on improved safety philosophies, including continuous monitoring. This approach will increase the efficiency of inspection procedures at reduced inspection times. The Fraunhofer IZFP Dresden Branch has developed network nodes, miniaturized transmitter and receiver systems for active and passive acoustical techniques and sensor systems that can be attached to or embedded into components or structures. These systems have been used to demonstrate intelligent sensor networks for the monitoring of aerospace structures, railway systems, wind energy generators, piping system and other components. Material discontinuities and flaws have been detected and monitored during full scale fatigue testing. This paper will discuss opportunities and future trends in nondestructive evaluation and health monitoring based on new sensor principles and advanced microelectronics. It will outline various application examples of monitoring systems based on acoustic techniques and will indicate further needs for research and development.

  13. Privacy by design in personal health monitoring.

    Science.gov (United States)

    Nordgren, Anders

    2015-06-01

    The concept of privacy by design is becoming increasingly popular among regulators of information and communications technologies. This paper aims at analysing and discussing the ethical implications of this concept for personal health monitoring. I assume a privacy theory of restricted access and limited control. On the basis of this theory, I suggest a version of the concept of privacy by design that constitutes a middle road between what I call broad privacy by design and narrow privacy by design. The key feature of this approach is that it attempts to balance automated privacy protection and autonomously chosen privacy protection in a way that is context-sensitive. In personal health monitoring, this approach implies that in some contexts like medication assistance and monitoring of specific health parameters one single automatic option is legitimate, while in some other contexts, for example monitoring in which relatives are receivers of health-relevant information rather than health care professionals, a multi-choice approach stressing autonomy is warranted.

  14. Democracy - the real 'ghost' in the machine of global health policy: Comment on "A ghost in the machine? politics in global health policy".

    Science.gov (United States)

    Harmer, Andrew

    2014-08-01

    Politics is not the ghost in the machine of global health policy. Conceptually, it makes little sense to argue otherwise, while history is replete with examples of individuals and movements engaging politically in global health policy. Were one looking for ghosts, a more likely candidate would be democracy, which is currently under attack by a new global health technocracy. Civil society movements offer an opportunity to breathe life into a vital, but dying, political component of global health policy.

  15. Democracy – The Real ‘Ghost’ in the Machine of Global Health Policy; Comment on “A Ghost in the Machine? Politics in Global Health Policy”

    Directory of Open Access Journals (Sweden)

    Andrew Harmer

    2014-08-01

    Full Text Available Politics is not the ghost in the machine of global health policy. Conceptually, it makes little sense to argue otherwise, while history is replete with examples of individuals and movements engaging politically in global health policy. Were one looking for ghosts, a more likely candidate would be democracy, which is currently under attack by a new global health technocracy. Civil society movements offer an opportunity to breathe life into a vital, but dying, political component of global health policy.

  16. On-farm udder health monitoring.

    Science.gov (United States)

    Lam, T J G M; van Veersen, J C L; Sampimon, O C; Olde Riekerink, R G M

    2011-01-01

    In this article an on-farm monitoring approach on udder health is presented. Monitoring of udder health consists of regular collection and analysis of data and of the regular evaluation of management practices. The ultimate goal is to manage critical control points in udder health management, such as hygiene, body condition, teat ends and treatments, in such a way that results (udder health parameters) are always optimal. Mastitis, however, is a multifactorial disease, and in real life it is not possible to fully prevent all mastitis problems. Therefore udder health data are also monitored with the goal to pick up deviations before they lead to (clinical) problems. By quantifying udder health data and management, a farm is approached as a business, with much attention for efficiency, thought over processes, clear agreements and goals, and including evaluation of processes and results. The whole approach starts with setting SMART (Specific, Measurable, Acceptable, Realistic, Time-bound) goals, followed by an action plan to realize these goals.

  17. The use of frequency and wavelet analysis for monitoring surface quality of wood machining applications.

    Science.gov (United States)

    Lemaster, Richard L

    2010-01-01

    The research described in this study is part of a project to provide the technology and theory to quantify surface quality for a variety of wood and wood-based products. The ultimate goal is to provide a means of monitoring trends in surface quality, which can be used to discriminate between "good" products and "bad" products (the methods described in this research are not intended to provide "grading" of individual workpieces) as well as to provide information to the machine operator as to the source of poor-quality machined surfaces. This research investigates the use of both frequency domain analysis as well as the more advanced joint time frequency analysis (JTFA). The disadvantages of traditional frequency analysis as well as the potential of the JTFA are illustrated. Sample surface profiles from actual machining defects were analyzed using traditional frequency analysis. A surface with multiple machining defects was analyzed with both traditional frequency analysis and JTFA (harmonic wavelet). Although the analysis was empirical in nature, the results show that the harmonic wavelet transform is able to detect both stationary and non-stationary surface irregularities as well as pulses (localized defects).

  18. Monitoring Hitting Load in Tennis Using Inertial Sensors and Machine Learning.

    Science.gov (United States)

    Whiteside, David; Cant, Olivia; Connolly, Molly; Reid, Machar

    2017-02-09

    Quantifying external workload is fundamental to training prescription in sport. In tennis, global positioning data are imprecise and fail to capture hitting loads. The current gold standard (manual notation) is time intensive and often not possible given players' heavy travel schedules. The aim of this study was to develop an automated stroke classification system to help quantify hitting load in tennis. 18 athletes wore an inertial measurement unit (IMU) on their wrist during 66 video-recorded training sessions. Video footage was manually notated such that known shot type (serve, rally forehand, slice forehand, forehand volley, rally backhand, slice backhand, backhand volley, smash or false positive) was associated with the corresponding IMU data for 28,582 shots. Six types of machine learning models were then constructed to classify true shot type from the IMU signals. Across 10-fold cross-validation, a cubic kernel support vector machine classified binned shots (overhead, forehand or backhand) with an accuracy of 97.4%. A second cubic kernel support vector machine achieved 93.2% accuracy when classifying all 9 shot types. With a view to monitoring external load, the combination of miniature inertial sensors and machine learning can offer a practical and automated method for quantifying shot counts and for discriminating shot types in elite tennis players.

  19. [Health economical aspects of telemedical glaucoma monitoring].

    Science.gov (United States)

    Swierk, T; Jürgens, C; Grossjohann, R; Flessa, S; Tost, F

    2011-04-01

    Telemedical home monitoring of glaucoma patients is not covered by health insurance in Germany. Various clinical studies have indicated that 24 h monitoring of intraocular and blood pressure of glaucoma patients allows a better evaluation of the individual disease condition. If the necessary parameters can be collected with telemedical home monitoring it will be possible to reduce the number of 24 h intraocular pressure profiles which necessitate hospital admission. Therefore inpatient 24 h profiles have been chosen as a health economical allocation base with a presentable economical value for the comparative examination. Assuming an at least identical or even higher clinical outcome of the telemedical glaucoma home monitoring inpatient 24 h profiles were chosen as a health economical allocation base to compare and contrast these methods. All procedures of the inpatient 24 h profiles at the ophthalmic clinic of Greifswald were measured using the stopwatch method. In a 1 day test run all activities of the medical staff were identified and documented in a list and afterwards measurements were carried out over 7 days with several stopwatches to allow the documentation of parallel activities. To determine the consumption of resources in telemedical home monitoring the self-documentation of all employees involved in the research project TT-MV were evaluated. Expert interviews helped to determine the economically relevant data about the applied medical technology, e.g. measuring devices, server and electronic health records. The number and complexity of the subprocesses of the inpatient 24 h intraocular pressure profiles were significantly higher compared to telemedical home monitoring. The total costs of the inpatient 24 h profiles were 571.21 € per patient including 291.21 € for medical care and 280 € for accommodation. In contrast the total costs of telemedical home monitoring were 288.72 € per patient. A direct cost comparison shows that telemedical home

  20. Development of Dual-Axis MEMS Accelerometers for Machine Tools Vibration Monitoring

    Directory of Open Access Journals (Sweden)

    Chih-Yung Huang

    2016-07-01

    Full Text Available With the development of intelligent machine tools, monitoring the vibration by the accelerometer is an important issue. Accelerometers used for measuring vibration signals during milling processes require the characteristics of high sensitivity, high resolution, and high bandwidth. A commonly used accelerometer is the lead zirconate titanate (PZT type; however, integrating it into intelligent modules is excessively expensive and difficult. Therefore, the micro electro mechanical systems (MEMS accelerometer is an alternative with the advantages of lower price and superior integration. In the present study, we integrated two MEMS accelerometer chips into a low-pass filter and housing to develop a low-cost dual-axis accelerometer with a bandwidth of 5 kHz and a full scale range of ±50 g for measuring machine tool vibration. In addition, a platform for measuring the linearity, cross-axis sensitivity and frequency response of the MEMS accelerometer by using the back-to-back calibration method was also developed. Finally, cutting experiments with steady and chatter cutting were performed to verify the results of comparing the MEMS accelerometer with the PZT accelerometer in the time and frequency domains. The results demonstrated that the dual-axis MEMS accelerometer is suitable for monitoring the vibration of machine tools at low cost.

  1. Physicians' appraisal of mobile health monitoring

    NARCIS (Netherlands)

    Okazaki, Shintaro; Castaneda, J. Alberto; Sanz, Silvia; Henseler, Jörg

    2013-01-01

    This study addresses what factors influence and moderate Japanese physicians' mobile health monitoring (MHM) adoption for diabetic patients. In light of the multilevel sequential check theory, the study tests whether novelty seeking, self-efficacy, and compatibility moderate the effects of overall q

  2. Wearable Sensors for Remote Health Monitoring.

    Science.gov (United States)

    Majumder, Sumit; Mondal, Tapas; Deen, M Jamal

    2017-01-12

    Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

  3. Wearable Sensors for Remote Health Monitoring

    Directory of Open Access Journals (Sweden)

    Sumit Majumder

    2017-01-01

    Full Text Available Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

  4. Design Optimization of Structural Health Monitoring Systems

    Energy Technology Data Exchange (ETDEWEB)

    Flynn, Eric B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2014-03-06

    Sensor networks drive decisions. Approach: Design networks to minimize the expected total cost (in a statistical sense, i.e. Bayes Risk) associated with making wrong decisions and with installing maintaining and running the sensor network itself. Search for optimal solutions using Monte-Carlo-Sampling-Adapted Genetic Algorithm. Applications include structural health monitoring and surveillance.

  5. Wearable Sensors for Remote Health Monitoring

    Science.gov (United States)

    Majumder, Sumit; Mondal, Tapas; Deen, M. Jamal

    2017-01-01

    Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant  burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed. PMID:28085085

  6. Intelligent Control and Health Monitoring. Chapter 3

    Science.gov (United States)

    Garg, Sanjay; Kumar, Aditya; Mathews, H. Kirk; Rosenfeld, Taylor; Rybarik, Pavol; Viassolo, Daniel E.

    2009-01-01

    Advanced model-based control architecture overcomes the limitations state-of-the-art engine control and provides the potential of virtual sensors, for example for thrust and stall margin. "Tracking filters" are used to adapt the control parameters to actual conditions and to individual engines. For health monitoring standalone monitoring units will be used for on-board analysis to determine the general engine health and detect and isolate sudden faults. Adaptive models open up the possibility of adapting the control logic to maintain desired performance in the presence of engine degradation or to accommodate any faults. Improved and new sensors are required to allow sensing at stations within the engine gas path that are currently not instrumented due in part to the harsh conditions including high operating temperatures and to allow additional monitoring of vibration, mass flows and energy properties, exhaust gas composition, and gas path debris. The environmental and performance requirements for these sensors are summarized.

  7. Machine and Woodworking Tool Safety. Module SH-24. Safety and Health.

    Science.gov (United States)

    Center for Occupational Research and Development, Inc., Waco, TX.

    This student module on machine and woodworking tool safety is one of 50 modules concerned with job safety and health. This module discusses specific practices and precautions concerned with the efficient operation and use of most machine and woodworking tools in use today. Following the introduction, 13 objectives (each keyed to a page in the…

  8. Principles in wireless building health monitoring systems.

    Science.gov (United States)

    Pentaris, F. P.; Makris, J. P.; Stonham, J.; Vallianatos, F.

    2012-04-01

    Monitoring the structural state of a building is essential for the safety of the people who work, live, visit or just use it as well as for the civil protection of urban areas. Many factors can affect the state of the health of a structure, namely man made, like mistakes in the construction, traffic, heavy loads on the structures, explosions, environmental impacts like wind loads, humidity, chemical reactions, temperature changes and saltiness, and natural hazards like earthquakes and landslides. Monitoring the health of a structure provides the ability to anticipate structural failures and secure the safe use of buildings especially those of public services. This work reviews the state of the art and the challenges of a wireless Structural Health Monitoring (WiSHM). Literature review reveals that although there is significant evolution in wireless structural health monitoring, in many cases, monitoring by itself is not enough to predict when a structure becomes inappropriate and/or unsafe for use, and the damage or low durability of a structure cannot be revealed (Chintalapudi, et al., 2006; Ramos, Aguilar, & Lourenço, 2011). Several features and specifications of WiSHM like wireless sensor networking, reliability and autonomy of sensors, algorithms of data transmission and analysis should still be evolved and improved in order to increase the predictive effectiveness of the SHM (Jinping Ou & Hui Li, 2010; Lu & Loh, 2010) . Acknowledgments This work was supported in part by the ARCHEMEDES III Program of the Ministry of Education of Greece and the European Union in the framework of the project entitled «Interdisciplinary Multi-Scale Research of Earthquake Physics and Seismotectonics at the front of the Hellenic Arc (IMPACT-ARC) ».

  9. Relational Machine Learning for Electronic Health Record-Driven Phenotyping

    Science.gov (United States)

    Peissig, Peggy L.; Costa, Vitor Santos; Caldwell, Michael D.; Rottscheit, Carla; Berg, Richard L.; Mendonca, Eneida A.; Page, David

    2014-01-01

    Objective Electronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient’s clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using Inductive Logic Programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping. Methods Two relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance. Results We developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each MLapproach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p=0.039), J48 (p=0.003) and JRIP (p=0.003). Discussion ILP has the potential to improve

  10. Relational machine learning for electronic health record-driven phenotyping.

    Science.gov (United States)

    Peissig, Peggy L; Santos Costa, Vitor; Caldwell, Michael D; Rottscheit, Carla; Berg, Richard L; Mendonca, Eneida A; Page, David

    2014-12-01

    Electronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient's clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using inductive logic programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping. Two relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance. We developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each ML approach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p=0.039), J48 (p=0.003) and JRIP (p=0.003). ILP has the potential to improve phenotyping by independently delivering

  11. Vibration health monitoring for tensegrity structures

    Science.gov (United States)

    Ashwear, Nasseradeen; Eriksson, Anders

    2017-02-01

    Tensegrities are assembly structures, getting their equilibrium from the interaction between tension in cables and compression in bars. During their service life, slacking in their cables and nearness to buckling in their bars need to be monitored to avoid a sudden collapse. This paper discusses how to design the tensegrities to make them feasible for vibrational health monitoring methods. Four topics are discussed; suitable finite elements formulation, pre-measurements analysis to find the locations of excitation and sensors for the interesting modes, the effects from some environmental conditions, and the pre-understanding of the effects from different slacking scenarios.

  12. Assessing the value of structural health monitoring

    DEFF Research Database (Denmark)

    Thöns, S.; Faber, Michael Havbro

    2013-01-01

    Structural Health Monitoring (SHM) systems are designed for assisting owners and operators with information and forecasts concerning the fitness for purpose of structures and building systems. The benefit associated with the implementation of SHM may in some cases be intuitively anticipated......-posterior decision analysis. The quantification of the value of SHM builds upon the quantification of the value of information (VoI) or rather the benefit of monitoring. The suggested approach involves a probabilistic representation of the loads and environmental conditions acting on structures as well...

  13. Designing Contestability: Interaction Design, Machine Learning, and Mental Health.

    Science.gov (United States)

    Hirsch, Tad; Merced, Kritzia; Narayanan, Shrikanth; Imel, Zac E; Atkins, David C

    2017-06-01

    We describe the design of an automated assessment and training tool for psychotherapists to illustrate challenges with creating interactive machine learning (ML) systems, particularly in contexts where human life, livelihood, and wellbeing are at stake. We explore how existing theories of interaction design and machine learning apply to the psychotherapy context, and identify "contestability" as a new principle for designing systems that evaluate human behavior. Finally, we offer several strategies for making ML systems more accountable to human actors.

  14. Monitoring Obesity Trends in Health Japan 21.

    Science.gov (United States)

    Nishi, Nobuo

    2015-01-01

    Prevention of non-communicable diseases is more important than ever especially for the elderly to live a healthy life in the super-aged society of Japan. In 2000, the Ministry of Health, Labor and Welfare of Japan started Health Japan 21 as goal-oriented health promotion plan like Healthy People in the US and the Health of the Nation in the UK. Its second term started in 2013 with the aim of prolonging healthy life expectancy and reducing health inequalities. Improvement in both individuals' lifestyle and their social environment will help achieve the goal of the 2nd Health Japan 21. The National Health and Nutrition Survey (NHNS) is conducted every year to monitor the health and nutritional situation of the Japanese using a representative population. The NHNS data are useful for target setting and evaluation of the 2nd Health Japan 21, and the NHNS has shown an increasing trend of overweight (BMI≥25) only for male adults in the most recent 10 y. In contrast, the dietary intake survey of the NHNS shows a decreasing trend of total energy intake both in male and female adults aged 69 y old or younger, and the trend for physical activity is not well known. Thus, we need further investigations on the causes of the obesity trend in Japan.

  15. 76 FR 6475 - Emergency Responder Health Monitoring and Surveillance

    Science.gov (United States)

    2011-02-04

    ... HUMAN SERVICES Centers for Disease Control and Prevention Emergency Responder Health Monitoring and... responder safety and health by monitoring and conducting surveillance of their health and safety during the... of a response. The proposed system is referred to as the ``Emergency Responder Health Monitoring...

  16. Identification methods for structural health monitoring

    CERN Document Server

    Papadimitriou, Costas

    2016-01-01

    The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method). Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.

  17. Optical metabolic imaging for monitoring tracheal health

    Science.gov (United States)

    Sharick, Joe T.; Gil, Daniel A.; Choma, Michael A.; Skala, Melissa C.

    2016-04-01

    The health of the tracheal mucosa and submucosa is a vital yet poorly understood component of critical care medicine, and a minimally-invasive method is needed to monitor tracheal health in patients. Of particular interest are the ciliated cells of the tracheal epithelium that move mucus away from the lungs and prevent respiratory infection. Optical metabolic imaging (OMI) allows cellular-level measurement of metabolism, and is a compelling method for assessing tracheal health because ciliary motor proteins require ATP to function. In this pilot study, we apply multiphoton imaging of the fluorescence intensities and lifetimes of metabolic co-enzymes NAD(P)H and FAD to the mucosa and submucosa of ex vivo mouse trachea. We demonstrate the feasibility and potential diagnostic utility of these measurements for assessing tracheal health and pathophysiology at the single-cell level.

  18. Real-time machine vision FPGA implementation for microfluidic monitoring on Lab-on-Chips.

    Science.gov (United States)

    Sotiropoulou, Calliope-Louisa; Voudouris, Liberis; Gentsos, Christos; Demiris, Athanasios M; Vassiliadis, Nikolaos; Nikolaidis, Spyridon

    2014-04-01

    A machine vision implementation on a field-programmable gate array (FPGA) device for real-time microfluidic monitoring on Lab-On-Chips is presented in this paper. The machine vision system is designed to follow continuous or plug flows, for which the menisci of the fluids are always visible. The system discriminates between the front or "head" of the flow and the back or "tail" and is able to follow flows with a maximum speed of 20 mm/sec in circular channels of a diameter of 200 μm (corresponding to approx. 60 μl/sec ). It is designed to be part of a complete Point-of-Care system, which will be portable and operate in non-ideal laboratory conditions. Thus, it is able to cope with noise due to lighting conditions and small LoC displacements during the experiment execution. The machine vision system can be used for a variety of LoC devices, without the need for fiducial markers (such as redundancy patterns) for its operation. The underlying application requirements called for a complete hardware implementation. The architecture uses a variety of techniques to improve performance and minimize memory access requirements. The system input is 8 bit grayscale uncompressed video of up to 1 Mpixel resolution. The system uses an operating frequency of 170 Mhz and achieves a computational time of 13.97 ms (worst case), which leads to a throughput of 71.6 fps for 1 Mpixel video resolution.

  19. Analysis on machine tool systems using spindle vibration monitoring for automatic tool changer

    Directory of Open Access Journals (Sweden)

    Shang-Liang Chen

    2015-12-01

    Full Text Available Recently, the intelligent systems of technology have become one of the major items in the development of machine tools. One crucial technology is the machinery status monitoring function, which is required for abnormal warnings and the improvement of cutting efficiency. During processing, the mobility act of the spindle unit determines the most frequent and important part such as automatic tool changer. The vibration detection system includes the development of hardware and software, such as vibration meter, signal acquisition card, data processing platform, and machine control program. Meanwhile, based on the difference between the mechanical configuration and the desired characteristics, it is difficult for a vibration detection system to directly choose the commercially available kits. For this reason, it was also selected as an item for self-development research, along with the exploration of a significant parametric study that is sufficient to represent the machine characteristics and states. However, we also launched the development of functional parts of the system simultaneously. Finally, we entered the conditions and the parameters generated from both the states and the characteristics into the developed system to verify its feasibility.

  20. A data-based technique for monitoring of wound rotor induction machines: A simulation study

    Directory of Open Access Journals (Sweden)

    Fouzi Harrou

    2016-09-01

    Full Text Available Detecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM. The proposed fault detection approach is based on the use of principal components analysis (PCA. However, conventional PCA-based detection indices, such as the T2 and the Q statistics, are not well suited to detect small faults because these indices only use information from the most recent available samples. Detection of small faults is one of the most crucial and challenging tasks in the area of fault detection and diagnosis. In this paper, a new statistical system monitoring strategy is proposed for detecting changes resulting from small shifts in several variables associated with WRIM. The proposed approach combines modeling using PCA modeling with the exponentially weighted moving average (EWMA control scheme. In the proposed approach, EWMA control scheme is applied on the ignored principal components to detect the presence of faults. The performance of the proposed method is compared with those of the traditional PCA-based fault detection indices. The simulation results clearly show the effectiveness of the proposed method over the conventional ones, especially in the presence of faults with small magnitudes.

  1. A data-based technique for monitoring of wound rotor induction machines: A simulation study

    KAUST Repository

    Harrou, Fouzi

    2016-05-09

    Detecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM). The proposed fault detection approach is based on the use of principal components analysis (PCA). However, conventional PCA-based detection indices, such as the T2T2 and the Q statistics, are not well suited to detect small faults because these indices only use information from the most recent available samples. Detection of small faults is one of the most crucial and challenging tasks in the area of fault detection and diagnosis. In this paper, a new statistical system monitoring strategy is proposed for detecting changes resulting from small shifts in several variables associated with WRIM. The proposed approach combines modeling using PCA modeling with the exponentially weighted moving average (EWMA) control scheme. In the proposed approach, EWMA control scheme is applied on the ignored principal components to detect the presence of faults. The performance of the proposed method is compared with those of the traditional PCA-based fault detection indices. The simulation results clearly show the effectiveness of the proposed method over the conventional ones, especially in the presence of faults with small magnitudes.

  2. Nuclear propulsion control and health monitoring

    Science.gov (United States)

    Walter, P. B.; Edwards, R. M.

    1993-01-01

    An integrated control and health monitoring architecture is being developed for the Pratt & Whitney XNR2000 nuclear rocket. Current work includes further development of the dynamic simulation modeling and the identification and configuration of low level controllers to give desirable performance for the various operating modes and faulted conditions. Artificial intelligence and knowledge processing technologies need to be investigated and applied in the development of an intelligent supervisory controller module for this control architecture.

  3. New trends in structural health monitoring

    CERN Document Server

    Güemes, J

    2013-01-01

    Experts actively working in structural health monitoring and control techniques present the current research, areas of application and tendencies for the future of this technology, including various design issues involved. Examples using some of the latest hardware and software tools, experimental data from small scale laboratory demonstrators and measurements made on real structures illustrate the book. It will be a reference for professionals and students in the areas of engineering, applied natural sciences and engineering management.

  4. A DSP-Based Beam Current Monitoring System for Machine Protection Using Adaptive Filtering

    Energy Technology Data Exchange (ETDEWEB)

    J. Musson; H. Dong; R. Flood; C. Hovater; J. Hereford

    2001-06-01

    The CEBAF accelerator at Jefferson Lab is currently using an analog beam current monitoring (BCM) system for its machine protection system (MPS), which has a loss accuracy of 2 micro-amps. Recent burn-through simulations predict catastrophic beam line component failures below 1 micro-amp of loss, resulting in a blind spot for the MPS. Revised MPS requirements target an ultimate beam loss accuracy of 250 nA. A new beam current monitoring system has been developed which utilizes modern digital receiver technology and digital signal processing concepts. The receiver employs a direct-digital down converter integrated circuit, mated with a Jefferson Lab digital signal processor VME card. Adaptive filtering is used to take advantage of current-dependent burn-through rates. Benefits of such a system include elimination of DC offsets, generic algorithm development, extensive filter options, and interfaces to UNIX-based control systems.

  5. WAMS-based monitoring and control of Hopf bifurcations in multi-machine power systems

    Institute of Scientific and Technical Information of China (English)

    Shao-bu WANG; Quan-yuan JIANG; Yi-jia CAO

    2008-01-01

    A method is proposed to monitor and control Hopf bifurcations in multi-machine power systems using the information from wide area measurement systems (WAMSs). The power method (PM) is adopted to compute the pair of conjugate eigenvalues with the algebraically largest real part and the corresponding eigenvectors of the Jacobian matrix of a power system. The distance between the current equilibrium point and the Hopf bifurcation set can be monitored dynamically by computing the pair of conjugate eigenvalues. When the current equilibrium point is close to the Hopf bifurcation set, the approximate normal vector to the Hopf bifurcation set is computed and used as a direction to regulate control parameters to avoid a Hopf bifurcation in the power system described by differential algebraic equations (DAEs). The validity of the proposed method is demonstrated by regulating the reactive power loads in a 14-bus power system.

  6. Flexible Structural-Health-Monitoring Sheets

    Science.gov (United States)

    Qing, Xinlin; Kuo, Fuo

    2008-01-01

    A generic design for a type of flexible structural-health-monitoring sheet with multiple sensor/actuator types and a method of manufacturing such sheets has been developed. A sheet of this type contains an array of sensing and/or actuation elements, associated wires, and any other associated circuit elements incorporated into various flexible layers on a thin, flexible substrate. The sheet can be affixed to a structure so that the array of sensing and/or actuation elements can be used to analyze the structure in accordance with structural-health-monitoring techniques. Alternatively, the sheet can be designed to be incorporated into the body of the structure, especially if the structure is made of a composite material. Customarily, structural-health monitoring is accomplished by use of sensors and actuators arrayed at various locations on a structure. In contrast, a sheet of the present type can contain an entire sensor/actuator array, making it unnecessary to install each sensor and actuator individually on or in a structure. Sensors of different types such as piezoelectric and fiber-optic can be embedded in the sheet to form a hybrid sensor network. Similarly, the traces for electric communication can be deposited on one or two layers as required, and an entirely separate layer can be employed to shield the sensor elements and traces.

  7. Feature and Statistical Model Development in Structural Health Monitoring

    Science.gov (United States)

    Kim, Inho

    All structures suffer wear and tear because of impact, excessive load, fatigue, corrosion, etc. in addition to inherent defects during their manufacturing processes and their exposure to various environmental effects. These structural degradations are often imperceptible, but they can severely affect the structural performance of a component, thereby severely decreasing its service life. Although previous studies of Structural Health Monitoring (SHM) have revealed extensive prior knowledge on the parts of SHM processes, such as the operational evaluation, data processing, and feature extraction, few studies have been conducted from a systematical perspective, the statistical model development. The first part of this dissertation, the characteristics of inverse scattering problems, such as ill-posedness and nonlinearity, reviews ultrasonic guided wave-based structural health monitoring problems. The distinctive features and the selection of the domain analysis are investigated by analytically searching the conditions of the uniqueness solutions for ill-posedness and are validated experimentally. Based on the distinctive features, a novel wave packet tracing (WPT) method for damage localization and size quantification is presented. This method involves creating time-space representations of the guided Lamb waves (GLWs), collected at a series of locations, with a spatially dense distribution along paths at pre-selected angles with respect to the direction, normal to the direction of wave propagation. The fringe patterns due to wave dispersion, which depends on the phase velocity, are selected as the primary features that carry information, regarding the wave propagation and scattering. The following part of this dissertation presents a novel damage-localization framework, using a fully automated process. In order to construct the statistical model for autonomous damage localization deep-learning techniques, such as restricted Boltzmann machine and deep belief network

  8. Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control.

    Science.gov (United States)

    Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

    2017-04-09

    Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

  9. Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control

    Directory of Open Access Journals (Sweden)

    Jude Adekunle Adeleke

    2017-04-01

    Full Text Available Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

  10. A novel machine learning-enabled framework for instantaneous heart rate monitoring from motion-artifact-corrupted electrocardiogram signals.

    Science.gov (United States)

    Zhang, Qingxue; Zhou, Dian; Zeng, Xuan

    2016-11-01

    This paper proposes a novel machine learning-enabled framework to robustly monitor the instantaneous heart rate (IHR) from wrist-electrocardiography (ECG) signals continuously and heavily corrupted by random motion artifacts in wearable applications. The framework includes two stages, i.e. heartbeat identification and refinement, respectively. In the first stage, an adaptive threshold-based auto-segmentation approach is proposed to select out heartbeat candidates, including the real heartbeats and large amounts of motion-artifact-induced interferential spikes. Then twenty-six features are extracted for each candidate in time, spatial, frequency and statistical domains, and evaluated by a spare support vector machine (SVM) to select out ten critical features which can effectively reveal residual heartbeat information. Afterwards, an SVM model, created on the training data using the selected feature set, is applied to find high confident heartbeats from a large number of candidates in the testing data. In the second stage, the SVM classification results are further refined by two steps: (1) a rule-based classifier with two attributes named 'continuity check' and 'locality check' for outlier (false positives) removal, and (2) a heartbeat interpolation strategy for missing-heartbeat (false negatives) recovery. The framework is evaluated on a wrist-ECG dataset acquired by a semi-customized platform and also a public dataset. When the signal-to-noise ratio is as low as  -7 dB, the mean absolute error of the estimated IHR is 1.4 beats per minute (BPM) and the root mean square error is 6.5 BPM. The proposed framework greatly outperforms well-established approaches, demonstrating that it can effectively identify the heartbeats from ECG signals continuously corrupted by intense motion artifacts and robustly estimate the IHR. This study is expected to contribute to robust long-term wearable IHR monitoring for pervasive heart health and fitness management.

  11. An autonomous structural health monitoring solution

    Science.gov (United States)

    Featherston, Carol A.; Holford, Karen M.; Pullin, Rhys; Lees, Jonathan; Eaton, Mark; Pearson, Matthew

    2013-05-01

    Combining advanced sensor technologies, with optimised data acquisition and diagnostic and prognostic capability, structural health monitoring (SHM) systems provide real-time assessment of the integrity of bridges, buildings, aircraft, wind turbines, oil pipelines and ships, leading to improved safety and reliability and reduced inspection and maintenance costs. The implementation of power harvesting, using energy scavenged from ambient sources such as thermal gradients and sources of vibration in conjunction with wireless transmission enables truly autonomous systems, reducing the need for batteries and associated maintenance in often inaccessible locations, alongside bulky and expensive wiring looms. The design and implementation of such a system however presents numerous challenges. A suitable energy source or multiple sources capable of meeting the power requirements of the system, over the entire monitoring period, in a location close to the sensor must be identified. Efficient power management techniques must be used to condition the power and deliver it, as required, to enable appropriate measurements to be taken. Energy storage may be necessary, to match a continuously changing supply and demand for a range of different monitoring states including sleep, record and transmit. An appropriate monitoring technique, capable of detecting, locating and characterising damage and delivering reliable information, whilst minimising power consumption, must be selected. Finally a wireless protocol capable of transmitting the levels of information generated at the rate needed in the required operating environment must be chosen. This paper considers solutions to some of these challenges, and in particular examines SHM in the context of the aircraft environment.

  12. Augmented Fish Health Monitoring, 1987 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Michak, Patty

    1989-04-01

    Washington Department of Fisheries has divided the sampling and data collection into three major groups: adult analysis, juvenile analysis and database development. The adult analysis done at spawning includes screening for viral pathogens and Bacterial Kidney Disease (BKD). Pre-spawning mortalities are sampled for the presence of bacterial pathogens and parasites to determine causes of pre-spawning loss. Juvenile analysis involves monthly monitoring; pre-release examinations for viral pathogens, BKD and, where appropriate, whirling disease (M. cerebralis); completion of the Organosomatic analysis on four index stocks, and midterm exams on yearling groups for BKD and M. cerebralis. Database development required constructing fish health monitoring forms and a computer based data entry and retrieval system. We have completed a full year of sampling and data collection, January, 1987 to January, 1988. This report will present and analyze this information.

  13. Augmented Fish Health Monitoring, 1989 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Michak, Patty

    1990-05-01

    Since 1986 Washington Department of Fisheries (WDF) has participated in the Columbia Basin Augmented Fish Health Monitoring Project, funded by Bonneville Power Administration (BPA). This interagency project was developed to provide a standardized level of fish health information from all Agencies rearing fish in the Columbia Basin. Agencies involved in the project are: WDF, Washington Department of Wildlife, Oregon Fish and Wildlife, Idaho Fish and Game, and the US Fish and Wildlife Service. WDF has actively participated in this project, and completed its third year of fish health monitoring, data collection and pathogen inspection during 1989. This report will present data collected from January 1, 1989 to December 31, 1989 and will compare sampling results from screening at spawning for viral pathogens and bacterial kidney disease (BKD), and evaluation of causes of pre-spawning loss. The juvenile analysis will include pre-release examination results, mid-term rearing exam results and evaluation of the Organosomatic Analysis completed on stocks. 2 refs., 4 figs., 15 tabs.

  14. Health monitoring method for composite materials

    Science.gov (United States)

    Watkins, Jr., Kenneth S.; Morris, Shelby J [Hampton, VA

    2011-04-12

    An in-situ method for monitoring the health of a composite component utilizes a condition sensor made of electrically conductive particles dispersed in a polymeric matrix. The sensor is bonded or otherwise formed on the matrix surface of the composite material. Age-related shrinkage of the sensor matrix results in a decrease in the resistivity of the condition sensor. Correlation of measured sensor resistivity with data from aged specimens allows indirect determination of mechanical damage and remaining age of the composite component.

  15. NASA Applications of Structural Health Monitoring Technology

    Science.gov (United States)

    Richards, W Lance; Madaras, Eric I.; Prosser, William H.; Studor, George

    2013-01-01

    This presentation provides examples of research and development that has recently or is currently being conducted at NASA, with a special emphasis on the application of structural health monitoring (SHM) of aerospace vehicles. SHM applications on several vehicle programs are highlighted, including Space Shuttle Orbiter, International Space Station, Uninhabited Aerial Vehicles, and Expandable Launch Vehicles. Examples of current and previous work are presented in the following categories: acoustic emission impact detection, multi-parameter fiber optic strain-based sensing, wireless sensor system development, and distributed leak detection.

  16. Electrical discharge machining: occupational hygienic characterization using emission-based monitoring.

    Science.gov (United States)

    Evertz, Sven; Dott, Wolfgang; Eisentraeger, Adolf

    2006-09-01

    Hazardous potential in industrial environments is normally assessed by means of immission-based sampling and analyses. This approach is not adequate, if effects of specific technical adjustments at machine tools or working processes on hygienic parameters should be assessed. This work has focused on the optimization of a manufacturing process (electrical discharge machining, EDM), with regard to risk reduction assessment. It is based on emission analyses rather than immision analyses. Several technical EDM parameters have been examined for their influence on air-based emissions. Worktools and workpieces used have a strong influence on aliphatic compounds and metals but not on volatile organic compounds (benzene, toluene, ethylene-benzene and xylene (BTEX)) and polycyclic aromatic hydrocarbons (PAHs) in air emissions. Increasing the dielectric (mineral oil) level above processing location decreases BTEX, chromium, nickel and PAH emissions. Aliphatic compounds, in contrast, increase in air emissions. EDM current used has a positive relationship with all substances analyzed in air emissions. Indicative immission concentrations, as can be expected under EDM conditions, are estimated in a predictive scenario. The results of this characterization give rise to an important conclusion in that risk assessment so far has been using incorrect parameters: total aliphatic compounds. Maximum level of chromium is reached long before limit values of aliphatic compounds are exceeded. Because of the fact that metals, like chromium, also have a higher hazardous potential, metal analysis should be introduced in future risk assessment. This experimental approach, that captures total emission of the electrical discharge machine, and is not solely based on immission values, has lead to a better understanding of the production process. This information is used to extract recommendations regarding monitoring aspects and protection measures.

  17. Application of Cerebellar Model Articulation Controller(CMAC) with a Modified Algorithm in Monitoring Machine Performance Degradation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jing-yong; ZHANG Lei; CAO Qi-xin; Jay Lee

    2005-01-01

    On the basis of CMAC-PDM (Pattern Discrimination Model), a novel algorithm of CMAC for monitoring machine degradation is proposed in this paper. The output of CMAC with the novel algorithm represents the state of a machine and PDM is not needed. The principle was explained by analyzing the modified mapping process of CMAC. The novel CMAC is applied to a tool condition monitoring system and two methodologies (novel CMAC and CMAC-PDM) are compared. The results prove that the novel algorithm is feasible and its computational complexity is reduced significantly.

  18. Development of Cutting Condition Monitoring System for ID-blade Saw Slicing Machine

    Institute of Scientific and Technical Information of China (English)

    JIANG Zhongwei; LI Fenlan; KAWASHIMA Kazuo

    2006-01-01

    The purpose of this study is focused on development of an online monitoring system for measuring and evaluating the cutting condition as the ID-blade saw is cutting a silicon ingot. First, the cutting experiments are carried out and the cutting signals during the blade slicing a six-inch ingot are measured by a 3-axes load sensor which is mounted on the top of the ingot. To evaluate the blade condition in slicing, a novel data processing method, combining the discrete Fourier transform(DFT) with the discrete Wavelet transform(DWT), is proposed in this paper for extracting the components due to the rotation of the blade and the cutting impedance. To validate the effect of the method, four ID-blades with three different types of the blade edge are used and discussed. The obtained results show that the component induced from the rotation and the component due to the blade slicing can be extracted efficiently by introduction of the proposed method. Furthermore, a simple online monitoring system,which consists of a 3-axes load sensor or acceleration sensor, DC cuts high-pass filter, and AD converter embedded microcomputer, is designed. The estimated cutting condition information obtained from the proposed monitoring system can be used as a feedback signal to the slicing machine for production of high quality wafer.

  19. Monitoring of cigarette smoking using wearable sensors and support vector machines.

    Science.gov (United States)

    Lopez-Meyer, Paulo; Tiffany, Stephen; Patil, Yogendra; Sazonov, Edward

    2013-07-01

    Cigarette smoking is a serious risk factor for cancer, cardiovascular, and pulmonary diseases. Current methods of monitoring of cigarette smoking habits rely on various forms of self-report that are prone to errors and under reporting. This paper presents a first step in the development of a methodology for accurate and objective assessment of smoking using noninvasive wearable sensors (Personal Automatic Cigarette Tracker-PACT) by demonstrating feasibility of automatic recognition of smoke inhalations from signals arising from continuous monitoring of breathing and hand-to-mouth gestures by support vector machine classifiers. The performance of subject-dependent (individually calibrated) models was compared to performance of subject-independent (group) classification models. The models were trained and validated on a dataset collected from 20 subjects performing 12 different activities representative of everyday living (total duration 19.5 h or 21,411 breath cycles). Precision and recall were used as the accuracy metrics. Group models obtained 87% and 80% of average precision and recall, respectively. Individual models resulted in 90% of average precision and recall, indicating a significant presence of individual traits in signal patterns. These results suggest the feasibility of monitoring cigarette smoking by means of a wearable and noninvasive sensor system in free living conditions.

  20. An Illustration of New Methods in Machine Condition Monitoring, Part II: Adaptive outlier detection

    Science.gov (United States)

    Antoniadou, I.; Worden, K.; Marchesiello, S.; Mba, C.; Garibaldi, L.

    2017-05-01

    There have been many recent developments in the application of data-based methods to machine condition monitoring. A powerful methodology based on machine learning has emerged, where diagnostics are based on a two-step procedure: extraction of damage-sensitive features, followed by unsupervised learning (novelty detection) or supervised learning (classification). The objective of the current pair of papers is simply to illustrate one state-of-the-art procedure for each step, using synthetic data representative of reality in terms of size and complexity. The second paper in the pair will deal with novelty detection. Although there has been considerable progress in the use of outlier analysis for novelty detection, most of the papers produced so far have suffered from the fact that simple algorithms break down if multiple outliers are present or if damage is already present in a training set. The objective of the current paper is to illustrate the use of phase-space thresholding; an algorithm which has the ability to detect multiple outliers inclusively in a data set.

  1. Machine Learning and Data Mining for Comprehensive Test Ban Treaty Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Russell, S; Vaidya, S

    2009-07-30

    The Comprehensive Test Ban Treaty (CTBT) is gaining renewed attention in light of growing worldwide interest in mitigating risks of nuclear weapons proliferation and testing. Since the International Monitoring System (IMS) installed the first suite of sensors in the late 1990's, the IMS network has steadily progressed, providing valuable support for event diagnostics. This progress was highlighted at the recent International Scientific Studies (ISS) Conference in Vienna in June 2009, where scientists and domain experts met with policy makers to assess the current status of the CTBT Verification System. A strategic theme within the ISS Conference centered on exploring opportunities for further enhancing the detection and localization accuracy of low magnitude events by drawing upon modern tools and techniques for machine learning and large-scale data analysis. Several promising approaches for data exploitation were presented at the Conference. These are summarized in a companion report. In this paper, we introduce essential concepts in machine learning and assess techniques which could provide both incremental and comprehensive value for event discrimination by increasing the accuracy of the final data product, refining On-Site-Inspection (OSI) conclusions, and potentially reducing the cost of future network operations.

  2. Osiris: A Malware Behavior Capturing System Implemented at Virtual Machine Monitor Layer

    Directory of Open Access Journals (Sweden)

    Ying Cao

    2013-01-01

    Full Text Available To perform behavior based malware analysis, behavior capturing is an important prerequisite. In this paper, we present Osiris system which is a tool to capture behaviors of executable files in Windows system. It collects API calls invoked not only by main process of the analysis file, but also API calls invoked by child processes which are created by main process, injected processes if process injection happens, and service processes if the main process creates services. By modifying the source code of Qemu, Osiris is implemented at the virtual machine monitor layer and has the following advantages. First, it does not rewrite the binary code of analysis file or interfere with its normal execution, so that behavior data are obtained more stealthily and transparently. Second, it employs a multi-virtual machine framework to simulate the network environment for malware analysis, so that network behaviors of a malware are stimulated to a large extend. Third, besides network environment, it also simulates most common host events to stimulate potential malicious behaviors of a malware. The experimental results show that Osiris automates the malware analysis process and provides good behavior data for the following detection algorithm.

  3. Augmented Fish Health Monitoring in Idaho, 1992 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Munson, A.Douglas

    1993-12-01

    This report documents the progress of Idaho Department of Fish and Game`s fish health monitoring during the past five years and will serve as a completion report for the Augmented Fish Health Monitoring Project. Anadromous fish at twelve IDFG facilities were monitored for various pathogens and organosomatic analyses were performed to anadromous fish prior to their release. A fish disease database has been developed and data is presently being entered. Alternate funding has been secured to continue fish health monitoring.

  4. Valve Health Monitoring System Utilizing Smart Instrumentation

    Science.gov (United States)

    Jensen, Scott L.; Drouant, George J.

    2006-01-01

    The valve monitoring system is a stand alone unit with network capabilities for integration into a higher level health management system. The system is designed for aiding in failure predictions of high-geared ball valves and linearly actuated valves. It performs data tracking and archiving for identifying degraded performance. The data collection types are cryogenic cycles, total cycles, inlet temperature, body temperature torsional strain, linear bonnet strain, preload position, total travel and total directional changes. Events are recorded and time stamped in accordance with the IRIG B True Time. The monitoring system is designed for use in a Class 1 Division II explosive environment. The basic configuration consists of several instrumentation sensor units and a base station. The sensor units are self contained microprocessor controlled and remotely mountable in three by three by two inches. Each unit is potted in a fire retardant substance without any cavities and limited to low operating power for maintaining safe operation in a hydrogen environment. The units are temperature monitored to safeguard against operation outside temperature limitations. Each contains 902-928 MHz band digital transmitters which meet Federal Communication Commission's requirements and are limited to a 35 foot transmission radius for preserving data security. The base-station controller correlates data from the sensor units and generates data event logs on a compact flash memory module for database uploading. The entries are also broadcast over an Ethernet network. Nitrogen purged National Electrical Manufactures Association (NEMA) Class 4 enclosures are used to house the base-station

  5. Augmented Fish Health Monitoring, 1988 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Warren, James W.

    1989-08-15

    Augmented Fish Health Monitoring Contract AI79-87BP35585 was implemented on July 20, 1987. Second year activities focused on full implementation of disease surveillance activities and histopathological support services to participating state agencies. Persistent and sometimes severe disease losses were caused by infectious hematopoietic necrosis (IHN) in summer steelhead trout in Idaho and in spring chinook salmon at hatcheries on the lower Columbia River. Diagnostic capability was enhanced by the installation, for field use, of enzyme-linked immunosorbent assay (ELISA) technology at the Dworshak Fish Health Center for the detection and assay of bacterial kidney disease and by a dot-blot'' training session for virus identification at the Lower Columbia Fish Health Center. Complete diagnostic and inspection services were provided to 13 Columbia River basin National Fish hatcheries. Case history data was fully documented in a computerized data base for storage and analysis. This report briefly describes work being done to meet contract requirements for fish disease surveillance at Service facilities in the Columbia River basin. It also summarizes the health status of fish reared at those hatcheries and provides a summary of case history data for calendar year 1988. 2 refs., 4 tabs.

  6. Aircraft fiber optic structural health monitoring

    Science.gov (United States)

    Mrad, Nezih

    2012-06-01

    Structural Health Monitoring (SHM) is a sought after concept that is expected to advance military maintenance programs, increase platform operational safety and reduce its life cycle cost. Such concept is further considered to constitute a major building block of any Integrated Health Management (IHM) capability. Since 65% to 80% of military assets' Life Cycle Cost (LCC) is devoted to operations and support (O&S), the aerospace industry and military sectors continue to look for opportunities to exploit SHM systems, capability and tools. Over the past several years, countless SHM concepts and technologies have emerged. Among those, fiber optic based systems were identified of significant potential. This paper introduces the elements of an SHM system and investigates key issues impeding the commercial implementation of fiber optic based SHM capability. In particular, this paper presents an experimental study of short gauge, intrinsic, spectrometric-based in-fiber Bragg grating sensors, for potential use as a component of an SHM system. Fiber optic Bragg grating sensors are evaluated against resistance strain gauges for strain monitoring, sensitivity, accuracy, reliability, and fatigue durability. Strain field disturbance is also investigated by "embedding" the sensors under a photoelastic coating in order to illustrate sensor intrusiveness in an embedded configuration.

  7. Data driven innovations in structural health monitoring

    Science.gov (United States)

    Rosales, M. J.; Liyanapathirana, R.

    2017-05-01

    At present, substantial investments are being allocated to civil infrastructures also considered as valuable assets at a national or global scale. Structural Health Monitoring (SHM) is an indispensable tool required to ensure the performance and safety of these structures based on measured response parameters. The research to date on damage assessment has tended to focus on the utilization of wireless sensor networks (WSN) as it proves to be the best alternative over the traditional visual inspections and tethered or wired counterparts. Over the last decade, the structural health and behaviour of innumerable infrastructure has been measured and evaluated owing to several successful ventures of implementing these sensor networks. Various monitoring systems have the capability to rapidly transmit, measure, and store large capacities of data. The amount of data collected from these networks have eventually been unmanageable which paved the way to other relevant issues such as data quality, relevance, re-use, and decision support. There is an increasing need to integrate new technologies in order to automate the evaluation processes as well as to enhance the objectivity of data assessment routines. This paper aims to identify feasible methodologies towards the application of time-series analysis techniques to judiciously exploit the vast amount of readily available as well as the upcoming data resources. It continues the momentum of a greater effort to collect and archive SHM approaches that will serve as data-driven innovations for the assessment of damage through efficient algorithms and data analytics.

  8. Monitoring 'monitoring' and evaluating 'evaluation': an ethical framework for monitoring and evaluation in public health.

    Science.gov (United States)

    Gopichandran, Vijayaprasad; Indira Krishna, Anil Kumar

    2013-01-01

    Monitoring and evaluation (M&E) is an essential part of public health programmes. Since M&E is the backbone of public health programmes, ethical considerations are important in their conduct. Some of the key ethical considerations are avoiding conflicts of interest, maintaining independence of judgement, maintaining fairness, transparency, full disclosure, privacy and confidentiality, respect, responsibility, accountability, empowerment and sustainability. There are several ethical frameworks in public health, but none focusing on the monitoring and evaluation process. There is a need to institutionalise the ethical review of M&E proposals. A theoretical framework for ethical considerations is proposed in this paper. This proposed theoretical framework can act as the blueprint for building the capacity of ethics committees to review M&E proposals. A case study is discussed in this context. After thorough field testing, this practical and field-based ethical framework can be widely used by donor agencies, M&E teams, institutional review boards and ethics committees.

  9. Development of hardware system using temperature and vibration maintenance models integration concepts for conventional machines monitoring: a case study

    Science.gov (United States)

    Adeyeri, Michael Kanisuru; Mpofu, Khumbulani; Kareem, Buliaminu

    2016-12-01

    This article describes the integration of temperature and vibration models for maintenance monitoring of conventional machinery parts in which their optimal and best functionalities are affected by abnormal changes in temperature and vibration values thereby resulting in machine failures, machines breakdown, poor quality of products, inability to meeting customers' demand, poor inventory control and just to mention a few. The work entails the use of temperature and vibration sensors as monitoring probes programmed in microcontroller using C language. The developed hardware consists of vibration sensor of ADXL345, temperature sensor of AD594/595 of type K thermocouple, microcontroller, graphic liquid crystal display, real time clock, etc. The hardware is divided into two: one is based at the workstation (majorly meant to monitor machines behaviour) and the other at the base station (meant to receive transmission of machines information sent from the workstation), working cooperatively for effective functionalities. The resulting hardware built was calibrated, tested using model verification and validated through principles pivoted on least square and regression analysis approach using data read from the gear boxes of extruding and cutting machines used for polyethylene bag production. The results got therein confirmed related correlation existing between time, vibration and temperature, which are reflections of effective formulation of the developed concept.

  10. Students' perspectives on promoting healthful food choices from campus vending machines: a qualitative interview study.

    Science.gov (United States)

    Ali, Habiba I; Jarrar, Amjad H; Abo-El-Enen, Mostafa; Al Shamsi, Mariam; Al Ashqar, Huda

    2015-05-28

    Increasing the healthfulness of campus food environments is an important step in promoting healthful food choices among college students. This study explored university students' suggestions on promoting healthful food choices from campus vending machines. It also examined factors influencing students' food choices from vending machines. Peer-led semi-structured individual interviews were conducted with 43 undergraduate students (33 females and 10 males) recruited from students enrolled in an introductory nutrition course in a large national university in the United Arab Emirates. Interviews were audiotaped, transcribed, and coded to generate themes using N-Vivo software. Accessibility, peer influence, and busy schedules were the main factors influencing students' food choices from campus vending machines. Participants expressed the need to improve the nutritional quality of the food items sold in the campus vending machines. Recommendations for students' nutrition educational activities included placing nutrition tips on or beside the vending machines and using active learning methods, such as competitions on nutrition knowledge. The results of this study have useful applications in improving the campus food environment and nutrition education opportunities at the university to assist students in making healthful food choices.

  11. Health Monitoring and Life on the Mississippi

    Directory of Open Access Journals (Sweden)

    Lynne S. Wilcox

    2004-04-01

    Full Text Available Designing health monitoring systems is a complex task. This issue of Preventing Chronic Disease includes a report and commentary on measuring the burden of diabetes at the individual level in minority populations (1,2 and a report on measuring heart disease and stroke indicators at the policy level (3. To inspire stalwart professionals to design such systems, I turn to an individual recognized for his insightful commentary — Mark Twain, also known as Samuel Clemens. Twain had a keen eye for the idiosyncrasies of human behavior, and his nonfiction works suggest he was adept at amateur qualitative research. Though he was a man of letters rather than a scientist, he clearly appreciated the issues involved in gathering quality information: There is something fascinating about science. One gets such wholesome returns of conjecture out of such a trifling investment of fact (4. The balance of conjecture and fact is a source of ongoing tension in public health: collecting data is time-consuming and costly, but operating health programs based on conjecture is risky.

  12. Augmented Fish Health Monitoring, 1990 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Warren, James W.

    1990-08-15

    Augmented Fish Health Monitoring Contract AI79-87BP35585 was implemented on July 20, 1987. This report briefly describes third-year work being done to meet contract requirements for fish disease surveillance at Service facilities in the Columbia River basin and for histopathological support services provided to participating state agencies. It also summarizes the health status of fish reared at participating Service hatcheries and provides a summary of case history data for calendar year 1989. Items of note included severe disease losses to infectious hematopoietic necrosis (IHN) in summer steelhead trout in Idaho, the detection of IHN virus in juvenile spring chinook salmon at hatcheries on the lower Columbia River, and improved bacterial kidney disease (BKD) detection and adult assay by enzyme-linked immunosorbent assay (ELISA) technology at the Dworshak Fish Health Center. Complete diagnostic and inspection services were provided to 13 Columbia River Basin National Fish Hatcheries. Case history data was fully documented in a computerized data base for storage and analysis and is summarized herein. 2 refs., 1 fig., 4 tabs.

  13. Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System

    Directory of Open Access Journals (Sweden)

    Hong-Chan Chang

    2014-01-01

    Full Text Available This study endeavors to develop a cloud monitoring system for solar plants. This system incorporates numerous subsystems, such as a geographic information system, an instantaneous power-consumption information system, a reporting system, and a failure diagnosis system. Visual C# was integrated with ASP.NET and SQL technologies for the proposed monitoring system. A user interface for database management system was developed to enable users to access solar power information and management systems. In addition, by using peer-to-peer (P2P streaming technology and audio/video encoding/decoding technology, real-time video data can be transmitted to the client end, providing instantaneous and direct information. Regarding smart failure diagnosis, the proposed system employs the support vector machine (SVM theory to train failure mathematical models. The solar power data are provided to the SVM for analysis in order to determine the failure types and subsequently eliminate failures at an early stage. The cloud energy-management platform developed in this study not only enhances the management and maintenance efficiency of solar power plants but also increases the market competitiveness of solar power generation and renewable energy.

  14. A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method.

    Science.gov (United States)

    Li, Wutao; Huang, Zhigang; Lang, Rongling; Qin, Honglei; Zhou, Kai; Cao, Yongbin

    2016-03-04

    Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS) receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM) is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM) algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms) level and the monitoring time is on microsecond (μs) level, which make the proposed approach usable in practical interference monitoring applications.

  15. A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method

    Directory of Open Access Journals (Sweden)

    Wutao Li

    2016-03-01

    Full Text Available Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms level and the monitoring time is on microsecond (μs level, which make the proposed approach usable in practical interference monitoring applications.

  16. A Mobile Health Application to Predict Postpartum Depression Based on Machine Learning.

    Science.gov (United States)

    Jiménez-Serrano, Santiago; Tortajada, Salvador; García-Gómez, Juan Miguel

    2015-07-01

    Postpartum depression (PPD) is a disorder that often goes undiagnosed. The development of a screening program requires considerable and careful effort, where evidence-based decisions have to be taken in order to obtain an effective test with a high level of sensitivity and an acceptable specificity that is quick to perform, easy to interpret, culturally sensitive, and cost-effective. The purpose of this article is twofold: first, to develop classification models for detecting the risk of PPD during the first week after childbirth, thus enabling early intervention; and second, to develop a mobile health (m-health) application (app) for the Android(®) (Google, Mountain View, CA) platform based on the model with best performance for both mothers who have just given birth and clinicians who want to monitor their patient's test. A set of predictive models for estimating the risk of PPD was trained using machine learning techniques and data about postpartum women collected from seven Spanish hospitals. An internal evaluation was carried out using a hold-out strategy. An easy flowchart and architecture for designing the graphical user interface of the m-health app was followed. Naive Bayes showed the best balance between sensitivity and specificity as a predictive model for PPD during the first week after delivery. It was integrated into the clinical decision support system for Android mobile apps. This approach can enable the early prediction and detection of PPD because it fulfills the conditions of an effective screening test with a high level of sensitivity and specificity that is quick to perform, easy to interpret, culturally sensitive, and cost-effective.

  17. Fiber Optic Thermal Health Monitoring of Composites

    Science.gov (United States)

    Wu, Meng-Chou; Winfree, William P.; Moore, Jason P.

    2010-01-01

    A recently developed technique is presented for thermographic detection of flaws in composite materials by performing temperature measurements with fiber optic Bragg gratings. Individual optical fibers with multiple Bragg gratings employed as surface temperature sensors were bonded to the surfaces of composites with subsurface defects. The investigated structures included a 10-ply composite specimen with subsurface delaminations of various sizes and depths. Both during and following the application of a thermal heat flux to the surface, the individual Bragg grating sensors measured the temporal and spatial temperature variations. The data obtained from grating sensors were analyzed with thermal modeling techniques of conventional thermography to reveal particular characteristics of the interested areas. Results were compared with the calculations using numerical simulation techniques. Methods and limitations for performing in-situ structural health monitoring are discussed.

  18. Structural health monitoring apparatus and methodology

    Science.gov (United States)

    Giurgiutiu, Victor (Inventor); Yu, Lingyu (Inventor); Bottai, Giola Santoni (Inventor)

    2011-01-01

    Disclosed is an apparatus and methodology for structural health monitoring (SHM) in which smart devices interrogate structural components to predict failure, expedite needed repairs, and thus increase the useful life of those components. Piezoelectric wafer active sensors (PWAS) are applied to or integrated with structural components and various data collected there from provide the ability to detect and locate cracking, corrosion, and disbanding through use of pitch-catch, pulse-echo, electro/mechanical impedance, and phased array technology. Stand alone hardware and an associated software program are provided that allow selection of multiple types of SHM investigations as well as multiple types of data analysis to perform a wholesome investigation of a structure.

  19. Towards spacecraft applications of structural health monitoring

    Directory of Open Access Journals (Sweden)

    Adrian TOADER

    2012-12-01

    Full Text Available The first part of the paper presents recent developments in the field of structural health monitoring (SHM with special attention on the piezoelectric wafer active sensors (PWAS technologies utilizing guided waves (GW as propagating waves (pitch-catch, pulse-echo, standing wave (electromechanical impedance, and phased arrays. The second part of the paper describes the challenges of extending the PWAS GW SHM approach to in-space applications. Three major issues are identified, (a cryogenic temperatures; (b high temperatures; and (c space radiation exposure. Preliminary results in which these three issues were address in a series of carefully conducted experiments are presented and discussed. The third part of the paper discusses a new project that is about to start in collaboration between three Romanian institutes to address the issues and challenging of developing space SHM technologies based on PWAS concepts. The paper finishes with conclusions and suggestions for further work.

  20. Ultrasonic vibration for structural health monitoring

    Science.gov (United States)

    Liang, Y.; Yan, F.; Borigo, C.; Rose, J. L.

    2013-01-01

    Guided waves and vibration analysis are two useful techniques in Nondestructive Evaluation and Structural Health Monitoring. Bridging the gap between guided waves and vibration, a novel testing method ultrasonic vibration is demonstrated here. Ultrasonic vibration is capable to achieve defect detection sensitivity as ultrasonic guided waves, while maintaining the efficiency of traditional vibration in the way of adopting several sensors to cover the whole structure. In this new method, continuous guided wave energy will impinge into the structure to make the structure vibrate steadily. The steady state vibration is achieved after multiple boundary reflections of the continuous guided wave. In ultrasonic vibration experiments, annual array transducer is used as the actuator. The loading functions are tuned by the frequencies and phase delays among each transducer element. Experiments demonstrate good defect detection ability of by optimally selecting guided wave loadings.

  1. Three-Dimensional Health Monitoring of Sandwich Composites Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR project delivers a single-chip structural health-monitoring (SHM) system that uses the impedance method to monitor bulk interiors and wave propagation...

  2. [The research and expectation on wearable health monitoring system].

    Science.gov (United States)

    Chang, Feiba; Yin, Jun; Zhang, Hehua; Yan, Lexian; Li, Shuying; Zhou, Deqiang

    2015-01-01

    Wearable health monitoring systems that use wearable biosensors capturing human motion and physiological parameters, to achieve the wearer's movement and health management needs. Wearable health monitoring system is a noninvasive continuous detection of human physiological information, data wireless transmission and real-time processing capabilities of integrated system, can satisfy physiological condition monitoring under the condition of low physiological and psychological load. This paper first describes the wearable health monitoring system structure and the relevant technology applied to wearable health monitoring system, and focuses on the current research work what we have done associated with wearable monitoring that wearable respiration and ECG acquisition and construction of electric multi-parameter body area network. Finally, the wearable monitoring system for the future development direction is put forward a simple expectation.

  3. Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

    DEFF Research Database (Denmark)

    Thrane, Jakob; Wass, Jesper; Piels, Molly

    2017-01-01

    Linear signal processing algorithms are effective in dealing with linear transmission channel and linear signal detection, while the nonlinear signal processing algorithms, from the machine learning community, are effective in dealing with nonlinear transmission channel and nonlinear signal...... detection. In this paper, a brief overview of the various machine learning methods and their application in optical communication is presented and discussed. Moreover, supervised machine learning methods, such as neural networks and support vector machine, are experimentally demonstrated for in-band optical...

  4. Feature Selection by Merging Sequential Bidirectional Search into Relevance Vector Machine in Condition Monitoring

    Institute of Scientific and Technical Information of China (English)

    ZHANG Kui; DONG Yu; BALL Andrew

    2015-01-01

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

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

    Science.gov (United States)

    Zhang, Kui; Dong, Yu; Ball, Andrew

    2015-11-01

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

  6. [Current state and prospects of military personnel health monitoring].

    Science.gov (United States)

    Rezvantsev, M V; Kuznetsov, S M; Ivanov, V V; Zakurdaev, V V

    2014-01-01

    The current article is dedicated to some features of the Russian Federation Armed Forces military personnel health monitoring such as legal and informational provision, methodological basis of functioning, historical aspect of formation and development of the social and hygienic monitoring in the Russian Federation Armed Forces. The term "military personnel health monitoring" is defined as an analytical system of constant and long-term observation, analysis, assessment, studying of factors determined the military personnel health, these factors correlations, health risk factors management in order to minimize them. The current state of the military personnel health monitoring allows coming to the conclusion that the military health system does have forces and resources for state policy of establishing the population health monitoring system implementation. The following directions of the militarily personnel health monitoring improvement are proposed: the Russian Federation Armed Forces medical service record and report system reorganization bringing it closer to the civilian one, implementation of the integrated approach to the medical service informatisation, namely, military personnel health status and medical service resources monitoring. The leading means in this direction are development and introduction of a military serviceman individual health status monitoring system on the basis of a serviceman electronic medical record card. Also it is proposed the current Russian Federation Armed Forces social and hygienic monitoring improvement at the expense of informational interaction between the two subsystems on the basis of unified military medical service space.

  7. Development of Client-Server Application by Using UDP Socket Programming for Remotely Monitoring CNC Machine Environment in Fixture Process

    Directory of Open Access Journals (Sweden)

    Darmawan Darmawan

    2016-08-01

    Full Text Available The use of computer technology in manufacturing industries can improve manufacturing flexibility significantly, especially in manufacturing processes; many software applications have been utilized to improve machining performance. However, none of them has discussed the abilities to perform direct machining. In this paper, an integrated system for remote operation and monitoring of Computer Numerical Control (CNC machines is put into consideration. The integrated system includes computerization, network technology, and improved holding mechanism. The work proposed by this research is mainly on the software development for such integrated system. It uses Java three-dimensional (3D programming and Virtual Reality Modeling Language (VRML at the client side for visualization of machining environment. This research is aimed at developing a control system to remotely operate and monitor a self-reconfiguration fixture mechanism of a CNC milling machine through internet connection and integration of Personal Computer (PC-based CNC controller, a server side, a client side and CNC milling. The performance of the developed system was evaluated by testing with one type of common protocols particularly User Datagram Protocol (UDP.  Using UDP, the developed system requires 3.9 seconds to complete the close clamping, less than 1 second to release the clamping and it can deliver 463 KiloByte.

  8. Accelerated Aging Experiments for Capacitor Health Monitoring and Prognostics

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper discusses experimental setups for health monitoring and prognostics of electrolytic capacitors under nominal operation and accelerated aging conditions....

  9. Preliminary Study on Machining Condition Monitoring System Using 3-Channel Force Sensor Analyzed by I-kaz Multilevel Method

    Directory of Open Access Journals (Sweden)

    Z. Karim

    2016-08-01

    Full Text Available Cutting tool wear is one of the major problems affecting the finished product in term of surface finish quality, dimensional precision and the cost of the defect. This paper discusses the preliminary study on machining condition monitoring system using force data captured using 3-channel force sensor. The data were analyzed by I-kaz multilevel method to monitor the flank wear progression during the machining. The flank wear of the cutting insert was measured using Moticom magnifier under two different operational conditions in turning process. A 3-channel Kistler force sensor was assembled to hold the tool holder to measure the force on the cutting tool in the tangential, radial and feed direction during the machining process. The signals were transmitted to the data acquisition equipment, and finally to the computer system. I-kaz multilevel method was used to identify and characterize the changes in the signals from the sensors under two different experimental set up. The values of I-kaz multilevel coefficients for all channels are strongly correlated with the cutting tool wear condition. This preliminary study can be further developed to efficiently monitor and predict flank wear level which can be used in the real machining industry.

  10. Levee Health Monitoring With Radar Remote Sensing

    Science.gov (United States)

    Jones, C. E.; Bawden, G. W.; Deverel, S. J.; Dudas, J.; Hensley, S.; Yun, S.

    2012-12-01

    Remote sensing offers the potential to augment current levee monitoring programs by providing rapid and consistent data collection over large areas irrespective of the ground accessibility of the sites of interest, at repeat intervals that are difficult or costly to maintain with ground-based surveys, and in rapid response to emergency situations. While synthetic aperture radar (SAR) has long been used for subsidence measurements over large areas, applying this technique directly to regional levee monitoring is a new endeavor, mainly because it requires both a wide imaging swath and fine spatial resolution to resolve individual levees within the scene, a combination that has not historically been available. Application of SAR remote sensing directly to levee monitoring has only been attempted in a few pilot studies. Here we describe how SAR remote sensing can be used to assess levee conditions, such as seepage, drawing from the results of two levee studies: one of the Sacramento-San Joaquin Delta levees in California that has been ongoing since July 2009 and a second that covered the levees near Vicksburg, Mississippi, during the spring 2011 floods. These studies have both used data acquired with NASA's UAVSAR L-band synthetic aperture radar, which has the spatial resolution needed for this application (1.7 m single-look), sufficiently wide imaging swath (22 km), and the longer wavelength (L-band, 0.238 m) required to maintain phase coherence between repeat collections over levees, an essential requirement for applying differential interferometry (DInSAR) to a time series of repeated collections for levee deformation measurement. We report the development and demonstration of new techniques that employ SAR polarimetry and differential interferometry to successfully assess levee health through the quantitative measurement of deformation on and near levees and through detection of areas experiencing seepage. The Sacramento-San Joaquin Delta levee study, which covers

  11. Channel Efficiency with Security Enhancement for Remote Condition Monitoring of Multi Machine System Using Hybrid Huffman Coding

    Science.gov (United States)

    Datta, Jinia; Chowdhuri, Sumana; Bera, Jitendranath

    2016-12-01

    This paper presents a novel scheme of remote condition monitoring of multi machine system where a secured and coded data of induction machine with different parameters is communicated between a state-of-the-art dedicated hardware Units (DHU) installed at the machine terminal and a centralized PC based machine data management (MDM) software. The DHUs are built for acquisition of different parameters from the respective machines, and hence are placed at their nearby panels in order to acquire different parameters cost effectively during their running condition. The MDM software collects these data through a communication channel where all the DHUs are networked using RS485 protocol. Before transmitting, the parameter's related data is modified with the adoption of differential pulse coded modulation (DPCM) and Huffman coding technique. It is further encrypted with a private key where different keys are used for different DHUs. In this way a data security scheme is adopted during its passage through the communication channel in order to avoid any third party attack into the channel. The hybrid mode of DPCM and Huffman coding is chosen to reduce the data packet length. A MATLAB based simulation and its practical implementation using DHUs at three machine terminals (one healthy three phase, one healthy single phase and one faulty three phase machine) proves its efficacy and usefulness for condition based maintenance of multi machine system. The data at the central control room are decrypted and decoded using MDM software. In this work it is observed that Chanel efficiency with respect to different parameter measurements has been increased very much.

  12. Exploring Machine Learning Techniques Using Patient Interactions in Online Health Forums to Classify Drug Safety

    Science.gov (United States)

    Chee, Brant Wah Kwong

    2011-01-01

    This dissertation explores the use of personal health messages collected from online message forums to predict drug safety using natural language processing and machine learning techniques. Drug safety is defined as any drug with an active safety alert from the US Food and Drug Administration (FDA). It is believed that this is the first…

  13. Exploring Machine Learning Techniques Using Patient Interactions in Online Health Forums to Classify Drug Safety

    Science.gov (United States)

    Chee, Brant Wah Kwong

    2011-01-01

    This dissertation explores the use of personal health messages collected from online message forums to predict drug safety using natural language processing and machine learning techniques. Drug safety is defined as any drug with an active safety alert from the US Food and Drug Administration (FDA). It is believed that this is the first…

  14. Framework for monitoring equity in access and health systems ...

    African Journals Online (AJOL)

    paper, proposes a framework for monitoring equity in access and health .... get additional data through in—depth and qualitative studies. Equity and health .... characteristics of HIV infected patients seeking care in relation to access to the Drug ...

  15. Smart health monitoring systems: an overview of design and modeling.

    Science.gov (United States)

    Baig, Mirza Mansoor; Gholamhosseini, Hamid

    2013-04-01

    Health monitoring systems have rapidly evolved during the past two decades and have the potential to change the way health care is currently delivered. Although smart health monitoring systems automate patient monitoring tasks and, thereby improve the patient workflow management, their efficiency in clinical settings is still debatable. This paper presents a review of smart health monitoring systems and an overview of their design and modeling. Furthermore, a critical analysis of the efficiency, clinical acceptability, strategies and recommendations on improving current health monitoring systems will be presented. The main aim is to review current state of the art monitoring systems and to perform extensive and an in-depth analysis of the findings in the area of smart health monitoring systems. In order to achieve this, over fifty different monitoring systems have been selected, categorized, classified and compared. Finally, major advances in the system design level have been discussed, current issues facing health care providers, as well as the potential challenges to health monitoring field will be identified and compared to other similar systems.

  16. Rotor speed estimation of induction machines by monitoring the stator voltages and currents

    Energy Technology Data Exchange (ETDEWEB)

    Ho, S.Y.S.; Langman, R.A. [Tasmania Univ., Hobart, TAS (Australia)

    1995-12-31

    Accurate measurement of induction motor speed is routinely obtained by using a transducer coupled on the shaft. In many industrial situations, this is not acceptable as there may be no room for a suitable transducer, or else the motor environment may be too unpleasant. It is in theory possible to calculate the speed by monitoring the terminal voltages and currents (plus knowing the angular synchronous speed) and then applying these to the differential equations of motor. Two rotor speed algorithms were investigated. Unsatisfactory results were obtained with an algorithm based on the machine equations in a stationary reference frame because at some stage the algorithm divides zero by zero. To avoid these problems the time varying stator voltages and currents were further transformed into the synchronous reference frame so that they end up with dc electrical quantities. This algorithm of obtaining the tangent of the phase angle, for the determination of the rotor speed, was discussed and tested. The analysis presented in this paper points out that the speed of induction motor may be estimated at about +- 0.1 percent uncertainty from measurement of the stator voltage and current. (author). 5 figs., 5 refs.

  17. Non-Intrusive Battery Health Monitoring

    Directory of Open Access Journals (Sweden)

    Gajewski Laurent

    2017-01-01

    Full Text Available The “Non-intrusive battery health monitoring”, developed by Airbus Defence and Space (ADS in cooperation with the CIRIMAT-CNRS laboratory and supported by CNES, aims at providing a diagnosis of the battery ageing in flight, called State of Health (SOH, using only the post-treatment of the battery telemetries. The battery current and voltage telemetries are used by a signal processing tool on ground to characterize and to model the battery at low frequencies which allows monitoring the evolution of its degradation with great accuracy. The frequential behaviour estimation is based on inherent disturbances on the current during the nominal functioning of the battery. For instance, on-board thermal control or equipment consumption generates random disturbances on battery current around an average current. The battery voltage response to these current random disturbances enables to model the low frequency impedance of the battery by a signal processing tool. The re-created impedance is then compared with the evolution model of the low frequencies impedance as a function of the battery ageing to estimate accurately battery degradation. Hence, this method could be applied to satellites which are already in orbit and whose battery telemetries acquisition system fulfils the constraints determined in the study. This innovative method is an improvement of present state-of-the-art and is important to have a more accurate in-flight knowledge of battery ageing which is crucial for mission and operation planning and also for possible satellite mission extension or deorbitation. This method is patented by Airbus Defence and Space and CNES.

  18. Smart sensors for health and environment monitoring

    CERN Document Server

    2015-01-01

    This book covers two most important applications of smart sensors, namely bio-health sensing and environmental monitoring.   The approach taken is holistic and covers the complete scope of the subject matter from the principles of the sensing mechanism, through device physics, circuit and system implementation techniques, and energy issues  to wireless connectivity solutions. It is written at a level suitable mainly for post-graduate level researchers interested in practical applications. The chapters are independent but complementary to each other, and the book works within the wider perspective of essential smart sensors for the Internet of Things (IoT).   This is the second of three books based on the Integrated Smart Sensors research project, which describe the development of innovative devices, circuits, and system-level enabling technologies.  The aim of the project was to develop common platforms on which various devices and sensors can be loaded, and to create systems offering significant improve...

  19. Structural health monitoring for ship structures

    Energy Technology Data Exchange (ETDEWEB)

    Farrar, Charles [Los Alamos National Laboratory; Park, Gyuhae [Los Alamos National Laboratory; Angel, Marian [Los Alamos National Laboratory; Bement, Matthew [Los Alamos National Laboratory; Salvino, Liming [NSWC, CADEROCK

    2009-01-01

    Currently the Office of Naval Research is supporting the development of structural health monitoring (SHM) technology for U.S. Navy ship structures. This application is particularly challenging because of the physical size of these structures, the widely varying and often extreme operational and environmental conditions associated with these ships missions, lack of data from known damage conditions, limited sensing that was not designed specifically for SHM, and the management of the vast amounts of data that can be collected during a mission. This paper will first define a statistical pattern recognition paradigm for SHM by describing the four steps of (1) Operational Evaluation, (2) Data Acquisition, (3) Feature Extraction, and (4) Statistical Classification of Features as they apply to ship structures. Note that inherent in the last three steps of this process are additional tasks of data cleansing, compression, normalization and fusion. The presentation will discuss ship structure SHM challenges in the context of applying various SHM approaches to sea trials data measured on an aluminum multi-hull high-speed ship, the HSV-2 Swift. To conclude, the paper will discuss several outstanding issues that need to be addressed before SHM can make the transition from a research topic to actual field applications on ship structures and suggest approaches for addressing these issues.

  20. Wireless sensor networks for structural health monitoring

    CERN Document Server

    Cao, Jiannong

    2016-01-01

    This brief covers the emerging area of wireless sensor network (WSN)-based structural health monitoring (SHM) systems, and introduces the authors’ WSN-based platform called SenetSHM. It helps the reader differentiate specific requirements of SHM applications from other traditional WSN applications, and demonstrates how these requirements are addressed by using a series of systematic approaches. The brief serves as a practical guide, explaining both the state-of-the-art technologies in domain-specific applications of WSNs, as well as the methodologies used to address the specific requirements for a WSN application. In particular, the brief offers instruction for problem formulation and problem solving based on the authors’ own experiences implementing SenetSHM. Seven concise chapters cover the development of hardware and software design of SenetSHM, as well as in-field experiments conducted while testing the platform. The brief’s exploration of the SenetSHM platform is a valuable feature for civil engine...

  1. FOREWORD: Structural Health Monitoring and Intelligent Infrastructure

    Science.gov (United States)

    Wu, Zhishen; Fujino, Yozo

    2005-06-01

    This special issue collects together 19 papers that were originally presented at the First International Conference on Structural Health Monitoring and Intelligent Infrastructure (SHMII-1'2003), held in Tokyo, Japan, on 13-15 November 2003. This conference was organized by the Japan Society of Civil Engineers (JSCE) with partial financial support from the Japan Society for the Promotion of Science (JSPS) and the Ministry of Education, Culture, Sport, Science and Technology, Japan. Many related organizations supported the conference. A total of 16 keynote papers including six state-of-the-art reports from different counties, six invited papers and 154 contributed papers were presented at the conference. The conference was attended by a diverse group of about 300 people from a variety of disciplines in academia, industry and government from all over the world. Structural health monitoring (SHM) and intelligent materials, structures and systems have been the subject of intense research and development in the last two decades and, in recent years, an increasing range of applications in infrastructure have been discovered both for existing structures and for new constructions. SHMII-1'2003 addressed progress in the development of building, transportation, marine, underground and energy-generating structures, and other civilian infrastructures that are periodically, continuously and/or actively monitored where there is a need to optimize their performance. In order to focus the current needs on SHM and intelligent technologies, the conference theme was set as 'Structures/Infrastructures Sustainability'. We are pleased to have the privilege to edit this special issue on SHM and intelligent infrastructure based on SHMII-1'2003. We invited some of the presenters to submit a revised/extended version of their paper that was included in the SHMII-1'2003 proceedings for possible publication in the special issue. Each paper included in this special issue was edited with the same

  2. Health Informatics via Machine Learning for the Clinical Management of Patients.

    Science.gov (United States)

    Clifton, D A; Niehaus, K E; Charlton, P; Colopy, G W

    2015-08-13

    To review how health informatics systems based on machine learning methods have impacted the clinical management of patients, by affecting clinical practice. We reviewed literature from 2010-2015 from databases such as Pubmed, IEEE xplore, and INSPEC, in which methods based on machine learning are likely to be reported. We bring together a broad body of literature, aiming to identify those leading examples of health informatics that have advanced the methodology of machine learning. While individual methods may have further examples that might be added, we have chosen some of the most representative, informative exemplars in each case. Our survey highlights that, while much research is taking place in this high-profile field, examples of those that affect the clinical management of patients are seldom found. We show that substantial progress is being made in terms of methodology, often by data scientists working in close collaboration with clinical groups. Health informatics systems based on machine learning are in their infancy and the translation of such systems into clinical management has yet to be performed at scale.

  3. Improving physical health monitoring for patients with chronic mental health problems who receive antipsychotic medications

    Science.gov (United States)

    Abdallah, Nihad; Conn, Rory; Latif Marini, Abdel

    2016-01-01

    Physical health monitoring is an integral part of caring for patients with mental health problems. It is proven that serious physical health problems are more common among patients with severe mental health illness (SMI), this monitoring can be challenging and there is a need for improvement. The project aimed at improving the physical health monitoring among patients with SMI who are receiving antipsychotic medications. The improvement process focused on ensuring there is a good communication with general practitioners (GPs) as well as patient's education and education of care home staff. GP letters requesting physical health monitoring were updated; care home staff and patients were given more information about the value of regular physical health monitoring. There was an improvement in patients' engagement with the monitoring and the monitoring done by GPs was more adherent to local and national guidelines and was communicated with the mental health service. PMID:27559474

  4. Improving physical health monitoring for patients with chronic mental health problems who receive antipsychotic medications.

    Science.gov (United States)

    Abdallah, Nihad; Conn, Rory; Latif Marini, Abdel

    2016-01-01

    Physical health monitoring is an integral part of caring for patients with mental health problems. It is proven that serious physical health problems are more common among patients with severe mental health illness (SMI), this monitoring can be challenging and there is a need for improvement. The project aimed at improving the physical health monitoring among patients with SMI who are receiving antipsychotic medications. The improvement process focused on ensuring there is a good communication with general practitioners (GPs) as well as patient's education and education of care home staff. GP letters requesting physical health monitoring were updated; care home staff and patients were given more information about the value of regular physical health monitoring. There was an improvement in patients' engagement with the monitoring and the monitoring done by GPs was more adherent to local and national guidelines and was communicated with the mental health service.

  5. Structural health monitoring with a wireless vibration sensor network

    NARCIS (Netherlands)

    Basten, T.G.H.; Sas, P; Schiphorst, F.B.A.; Jonckheere, S.; Moens, D.

    2012-01-01

    Advanced maintenance strategies for infrastructure assets such as bridges or off shore wind turbines require actual and reliable information of the maintenance status. Structural health monitoring based on vibration sensing can help in supplying the input needed for structural health monitoring appl

  6. Structural health monitoring with a wireless vibration sensor network

    NARCIS (Netherlands)

    Basten, T.G.H.; Sas, P; Schiphorst, F.B.A.; Jonckheere, S.; Moens, D.

    2012-01-01

    Advanced maintenance strategies for infrastructure assets such as bridges or off shore wind turbines require actual and reliable information of the maintenance status. Structural health monitoring based on vibration sensing can help in supplying the input needed for structural health monitoring

  7. Structural health monitoring with a wireless vibration sensor network

    NARCIS (Netherlands)

    Basten, T.G.H.; Schiphorst, F.B.A.

    2012-01-01

    Advanced maintenance strategies for infrastructure assets such as bridges or off shore wind turbines require actual and reliable information of the maintenance status. Structural health monitoring based on vibration sensing can help in supplying the input needed for structural health monitoring appl

  8. Structural health monitoring system/method using electroactive polymer fibers

    Science.gov (United States)

    Scott-Carnell, Lisa A. (Inventor); Siochi, Emilie J. (Inventor)

    2013-01-01

    A method for monitoring the structural health of a structure of interest by coupling one or more electroactive polymer fibers to the structure and monitoring the electroactive responses of the polymer fiber(s). Load changes that are experienced by the structure cause changes in the baseline responses of the polymer fiber(s). A system for monitoring the structural health of the structure is also provided.

  9. Health Monitoring System Technology Assessments: Cost Benefits Analysis

    Science.gov (United States)

    Kent, Renee M.; Murphy, Dennis A.

    2000-01-01

    The subject of sensor-based structural health monitoring is very diverse and encompasses a wide range of activities including initiatives and innovations involving the development of advanced sensor, signal processing, data analysis, and actuation and control technologies. In addition, it embraces the consideration of the availability of low-cost, high-quality contributing technologies, computational utilities, and hardware and software resources that enable the operational realization of robust health monitoring technologies. This report presents a detailed analysis of the cost benefit and other logistics and operational considerations associated with the implementation and utilization of sensor-based technologies for use in aerospace structure health monitoring. The scope of this volume is to assess the economic impact, from an end-user perspective, implementation health monitoring technologies on three structures. It specifically focuses on evaluating the impact on maintaining and supporting these structures with and without health monitoring capability.

  10. Lifelong personal health data and application software via virtual machines in the cloud.

    Science.gov (United States)

    Van Gorp, Pieter; Comuzzi, Marco

    2014-01-01

    Personal Health Records (PHRs) should remain the lifelong property of patients, who should be able to show them conveniently and securely to selected caregivers and institutions. In this paper, we present MyPHRMachines, a cloud-based PHR system taking a radically new architectural solution to health record portability. In MyPHRMachines, health-related data and the application software to view and/or analyze it are separately deployed in the PHR system. After uploading their medical data to MyPHRMachines, patients can access them again from remote virtual machines that contain the right software to visualize and analyze them without any need for conversion. Patients can share their remote virtual machine session with selected caregivers, who will need only a Web browser to access the pre-loaded fragments of their lifelong PHR. We discuss a prototype of MyPHRMachines applied to two use cases, i.e., radiology image sharing and personalized medicine.

  11. Fully automatic spray-LBL machine with monitoring the real time growth of multilayer films using Quartz Crystal Microbalance

    Directory of Open Access Journals (Sweden)

    Shiratori S.

    2013-08-01

    Full Text Available A fully automatic spray-LBL machine with monitoring the real time growth of multilayer films using Quartz Crystal Microbalance (QCM techniques was newly developed. We established fully automatic spray layer-by-layer method by precisely controlling air pressure, solution flow, and spray pattern. The movement pattern towards the substrate during solution spraying allowed fabrication of a nano-scale, flat, thin film over a wide area. Optimization of spray conditions permitted fabrication of the flat film with high and low refractive indexes, and they were piled up alternatively to constitute a one-dimensional photonic crystal with near-infrared reflection characteristics. The heat shield effect of the near-infrared reflective film was also confirmed under natural sunlight. It was demonstrated that the fabrication using the automatic spray-LBL machine and real-time QCM monitoring allows the fabrication of optical quality thin films with precise thickness.

  12. Asset health monitors: development, sustainment, advancement

    Science.gov (United States)

    Mauss, Fredrick J.

    2011-04-01

    Pacific Northwest National Laboratory (PNNL) has developed the Captive Carry Health Monitor Unit (HMU) and the Humidity Indicator HMU. Each of these devices provides end users information that can be used to ensure the proper maintenance and performance of the missile. These two efforts have led to the ongoing development and evolution of the next generation Captive Carry HMU and the next generation Humidity Indicator HMU. These next generation efforts are in turn, leading to the future of HMUs. This evolutionary development process inherently allows for direct and indirect impact toward new HMU functionality, operability and performance characteristics by influencing their requirements, testing, communications, data archival, and user interaction. Current designs allow systems to operate in environments outside the limits of typical consumer electronics for up to or exceeding 10 years. These designs are battery powered and typically provided in custom mechanical packages that employ sensors for temperature, shock/vibration, and humidity measurements. The data taken from these sensors is then analyzed onboard using unique algorithms. The algorithms are developed from test data and fielded prototypes. Onboard data analysis provides field users with a simple indication of missile exposure. The HMU provides missile readiness information to the user based on storage and use conditions observed. To continually advance current designs PNNL evaluates the potential for enhancing sensor capabilities by improving performance or power saving features, increasing algorithm and processing abilities, and adding new features. Future work at PNNL includes the utilization of power harvesting, using a defined wireless protocol, and defining a data/information structure. These efforts will lead to improved performance allowing the HMUs to benefit users with direct access to HMUs in the field as well as benefiting those with the ability to make strategic and high-level supply and

  13. Electronic Health Monitoring for Space Systems Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostic monitoring capabilities for space exploration aircrafts are crucial to enable safety and reliability in these platforms. Nokomis proposes to develop and...

  14. 76 FR 13969 - Notice of Request for Approval of an Information Collection; National Animal Health Monitoring...

    Science.gov (United States)

    2011-03-15

    ...; National Animal Health Monitoring System; Needs Assessments AGENCY: Animal and Plant Health Inspection... National Animal Health Monitoring System needs assessments. DATES: We will consider all comments that we...-2908. SUPPLEMENTARY INFORMATION: Title: National Animal Health Monitoring System; Needs...

  15. Recommendations for Health Monitoring and Reporting for Zebrafish Research Facilities.

    Science.gov (United States)

    Collymore, Chereen; Crim, Marcus J; Lieggi, Christine

    2016-07-01

    The presence of subclinical infection or clinical disease in laboratory zebrafish may have a significant impact on research results, animal health and welfare, and transfer of animals between institutions. As use of zebrafish as a model of disease increases, a harmonized method for monitoring and reporting the health status of animals will facilitate the transfer of animals, allow institutions to exclude diseases that may negatively impact their research programs, and improve animal health and welfare. All zebrafish facilities should implement a health monitoring program. In this study, we review important aspects of a health monitoring program, including choice of agents, samples for testing, available testing methodologies, housing and husbandry, cost, test subjects, and a harmonized method for reporting results. Facilities may use these recommendations to implement their own health monitoring program.

  16. A New Architecture of a Ubiquitous Health Monitoring System: A Prototype Of Cloud Mobile Health Monitoring System

    CERN Document Server

    Bourouis, Abderrahim; Bouchachia, Abdelhamid

    2012-01-01

    Wireless Body Area Sensor Networks (WBASN) is an emerging technology which uses wireless sensors to implement real-time wearable health monitoring of patients to enhance independent living. In this paper we propose a prototype of cloud mobile health monitoring system. The system uses WBASN and Smartphone application that uses cloud computing, location data and a neural network to determine the state of patients.

  17. IDENTIFICATION AND MONITORING OF NOISE SOURCES OF CNC MACHINE TOOLS BY ACOUSTIC HOLOGRAPHY METHODS

    Directory of Open Access Journals (Sweden)

    Jerzy Józwik

    2016-06-01

    Full Text Available The paper presents the analysis of sound field emitted by selected CNC machine tools. The identification of noise sources and level was measured by acoustic holography for the 3-axis DMC 635eco machine tool and the 5-axis vertical machining centre DMU 65 monoBlock. The acoustic holography method allows precise identification and measurement of noise sources at different bandwidths of frequency. Detection of noise sources in tested objects allows diagnosis of their technical condition, as well as choice of effective means of noise reduction, which is highly significant from the perspective of minimising noise at the CNC machine operator workstation. Test results were presented as acoustic maps in various frequency ranges. Noise sources of the machine tool itself were identified, as well as the range of noise influence and the most frequent places of reflections and their span. The results of measurements were presented in figures and diagrams.

  18. Test report on the machine-mounted continuous respirable dust monitor

    Energy Technology Data Exchange (ETDEWEB)

    Kissell, F.N.; Thimons, E.D. [Pittsburgh Research Laboratory, Pittsburgh, PA (USA). National Institute for Occupational Safety and Health

    2001-07-01

    The machine-mounted continuous respirable dust monitor (MMCRDM) is a fixed-location area sampling device developed for possible use at the working face of an underground coal mine. This device, based on proprietary technology known as the tapered element oscillating microbalance, has evolved over the past eight years through a cooperative effort of the former Bureau of Mines, MSHA, and the Rupprecht & Patashnick Company in Albany, NY. The capability to measure respirable coal mine dust levels on a continuous basis, rather than depending solely on periodic samples obtained from the traditional coal mine dust samplers, has been a goal in the mining industry for nearly two decades. Recently, an extensive series of laboratory and underground tests was conducted by NIOSH with the cooperation of MSHA and coal operators to test the performance of the MMCRDM. In preliminary laboratory testing, the MMCRDM seemed to work well. However, in every underground test, when compared to reference samplers placed close to the inlet, the MMCRDM failed to meet the 25% accuracy criterion specified in the contract under which it was developed. Two reasons explain this failure: first, in most tests the bias (the relative discrepancy between the average MMCRDM concentration and the average reference sampler concentration) was too great. Second, the variability of the samplers used for reference comparison was too large. Finally, the underground testing of the MMCRDMs showed that they are quite unreliable at this stage of development. In the majority of mine tests, no more than 10 shifts of data were taken before the MMCRDM failed to function properly. Major breakdowns, requiring the return of the MMCRDM to the factory for repairs, occurred on average every 28 days. To be considered mine-worthy, MMCRDM reliability must be substantially improved. 6 refs., 7 figs.

  19. A Taxonomy of Injuries for Public Health Monitoring and Reporting

    Science.gov (United States)

    2017-07-25

    of Injuries for Public Health Monitoring and Reporting 15 codes are required to make this distinction. Because surveillance data and field...overall burden of care required for these injuries. PHIP No. 12-01-0717, A Taxonomy of Injuries for Public Health Monitoring and Reporting...is no mandatory reporting requirement in the military health system or the civilian sector for providers and coders to use cause codes. Many medical

  20. Vibration Monitoring of Gas Turbine Engines: Machine-Learning Approaches and Their Challenges

    Directory of Open Access Journals (Sweden)

    Ioannis Matthaiou

    2017-09-01

    Full Text Available In this study, condition monitoring strategies are examined for gas turbine engines using vibration data. The focus is on data-driven approaches, for this reason a novelty detection framework is considered for the development of reliable data-driven models that can describe the underlying relationships of the processes taking place during an engine’s operation. From a data analysis perspective, the high dimensionality of features extracted and the data complexity are two problems that need to be dealt with throughout analyses of this type. The latter refers to the fact that the healthy engine state data can be non-stationary. To address this, the implementation of the wavelet transform is examined to get a set of features from vibration signals that describe the non-stationary parts. The problem of high dimensionality of the features is addressed by “compressing” them using the kernel principal component analysis so that more meaningful, lower-dimensional features can be used to train the pattern recognition algorithms. For feature discrimination, a novelty detection scheme that is based on the one-class support vector machine (OCSVM algorithm is chosen for investigation. The main advantage, when compared to other pattern recognition algorithms, is that the learning problem is being cast as a quadratic program. The developed condition monitoring strategy can be applied for detecting excessive vibration levels that can lead to engine component failure. Here, we demonstrate its performance on vibration data from an experimental gas turbine engine operating on different conditions. Engine vibration data that are designated as belonging to the engine’s “normal” condition correspond to fuels and air-to-fuel ratio combinations, in which the engine experienced low levels of vibration. Results demonstrate that such novelty detection schemes can achieve a satisfactory validation accuracy through appropriate selection of two parameters of the

  1. Promoting health equity: WHO health inequality monitoring at global and national levels

    Directory of Open Access Journals (Sweden)

    Ahmad Reza Hosseinpoor

    2015-09-01

    Full Text Available Background: Health equity is a priority in the post-2015 sustainable development agenda and other major health initiatives. The World Health Organization (WHO has a history of promoting actions to achieve equity in health, including efforts to encourage the practice of health inequality monitoring. Health inequality monitoring systems use disaggregated data to identify disadvantaged subgroups within populations and inform equity-oriented health policies, programs, and practices. Objective: This paper provides an overview of a number of recent and current WHO initiatives related to health inequality monitoring at the global and/or national level. Design: We outline the scope, content, and intended uses/application of the following: Health Equity Monitor database and theme page; State of inequality: reproductive, maternal, newborn, and child health report; Handbook on health inequality monitoring: with a focus on low- and middle-income countries; Health inequality monitoring eLearning module; Monitoring health inequality: an essential step for achieving health equity advocacy booklet and accompanying video series; and capacity building workshops conducted in WHO Member States and Regions. Conclusions: The paper concludes by considering how the work of the WHO can be expanded upon to promote the establishment of sustainable and robust inequality monitoring systems across a variety of health topics among Member States and at the global level.

  2. Forest health monitoring: national status, trends, and analysis 2016

    Science.gov (United States)

    Kevin M. Potter; Barbara L. Conkling

    2017-01-01

    The annual national report of the Forest Health Monitoring (FHM) Program of the Forest Service, U.S. Department of Agriculture, presents forest health status and trends from a national or multi-State regional perspective using a variety of sources, introducesnew techniques for analyzing forest health data, and summarizes results of recently completed...

  3. Is it worth changing pattern recognition methods for structural health monitoring?

    Science.gov (United States)

    Bull, L. A.; Worden, K.; Cross, E. J.; Dervilis, N.

    2017-05-01

    The key element of this work is to demonstrate alternative strategies for using pattern recognition algorithms whilst investigating structural health monitoring. This paper looks to determine if it makes any difference in choosing from a range of established classification techniques: from decision trees and support vector machines, to Gaussian processes. Classification algorithms are tested on adjustable synthetic data to establish performance metrics, then all techniques are applied to real SHM data. To aid the selection of training data, an informative chain of artificial intelligence tools is used to explore an active learning interaction between meaningful clusters of data.

  4. The Combat-Wireless Health Monitoring System

    Science.gov (United States)

    2009-12-01

    not monitor concussions sustained by casualties. This article proposes the develop- ment of a new C-WHMS as an alterna- tive to the WPSM. The C-WHMS...monitoring system embedded within the Advanced Combat Helmet (ACH), which measures concussions sustained during the execution of combat operations. The...component of the C-WHMS, as embedded in the ACH. Concussions sus- tained by soldiers are a major concern of military leadership. The goal is to quickly

  5. Machine Learning for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

    DEFF Research Database (Denmark)

    Wass, J.; Thrane, Jakob; Piels, Molly

    2016-01-01

    Supervised machine learning methods are applied and demonstrated experimentally for inband OSNR estimation and modulation format classification in optical communication systems. The proposed methods accurately evaluate coherent signals up to 64QAM using only intensity information....

  6. Combining discrepancy analysis with sensorless signal resampling for condition monitoring of rotating machines under fluctuating operations

    CSIR Research Space (South Africa)

    Heyns, T

    2012-12-01

    Full Text Available for extensive datasets that are representative of different machine fault conditions. The envelope of the filtered signal is referred to as a discrepancy transform, since the discrepancy signal indicates the presence of fault-induced signal distortions...

  7. Interactive machine learning for health informatics: when do we need the human-in-the-loop?

    Science.gov (United States)

    Holzinger, Andreas

    2016-06-01

    Machine learning (ML) is the fastest growing field in computer science, and health informatics is among the greatest challenges. The goal of ML is to develop algorithms which can learn and improve over time and can be used for predictions. Most ML researchers concentrate on automatic machine learning (aML), where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from big data with many training sets. However, in the health domain, sometimes we are confronted with a small number of data sets or rare events, where aML-approaches suffer of insufficient training samples. Here interactive machine learning (iML) may be of help, having its roots in reinforcement learning, preference learning, and active learning. The term iML is not yet well used, so we define it as "algorithms that can interact with agents and can optimize their learning behavior through these interactions, where the agents can also be human." This "human-in-the-loop" can be beneficial in solving computationally hard problems, e.g., subspace clustering, protein folding, or k-anonymization of health data, where human expertise can help to reduce an exponential search space through heuristic selection of samples. Therefore, what would otherwise be an NP-hard problem, reduces greatly in complexity through the input and the assistance of a human agent involved in the learning phase.

  8. The monitoring of transient regimes on machine tools based on speed, acceleration and active electric power absorbed by motors

    Science.gov (United States)

    Horodinca, M.

    2016-08-01

    This paper intend to propose some new results related with computer aided monitoring of transient regimes on machine-tools based on the evolution of active electrical power absorbed by the electric motor used to drive the main kinematic chains and the evolution of rotational speed and acceleration of the main shaft. The active power is calculated in numerical format using the evolution of instantaneous voltage and current delivered by electrical power system to the electric motor. The rotational speed and acceleration of the main shaft are calculated based on the signal delivered by a sensor. Three real-time analogic signals are acquired with a very simple computer assisted setup which contains a voltage transformer, a current transformer, an AC generator as rotational speed sensor, a data acquisition system and a personal computer. The data processing and analysis was done using Matlab software. Some different transient regimes were investigated; several important conclusions related with the advantages of this monitoring technique were formulated. Many others features of the experimental setup are also available: to supervise the mechanical loading of machine-tools during cutting processes or for diagnosis of machine-tools condition by active electrical power signal analysis in frequency domain.

  9. Prognosis-a wearable health-monitoring system for people at risk: methodology and modeling.

    Science.gov (United States)

    Pantelopoulos, Alexandros; Bourbakis, Nikolaos G

    2010-05-01

    Wearable health-monitoring systems (WHMSs) represent the new generation of healthcare by providing real-time unobtrusive monitoring of patients' physiological parameters through the deployment of several on-body and even intrabody biosensors. Although several technological issues regarding WHMS still need to be resolved in order to become more applicable in real-life scenarios, it is expected that continuous ambulatory monitoring of vital signs will enable proactive personal health management and better treatment of patients suffering from chronic diseases, of the elderly population, and of emergency situations. In this paper, we present a physiological data fusion model for multisensor WHMS called Prognosis. The proposed methodology is based on a fuzzy regular language for the generation of the prognoses of the health conditions of the patient, whereby the current state of the corresponding fuzzy finite-state machine signifies the current estimated health state and context of the patient. The operation of the proposed scheme is explained via detailed examples in hypothetical scenarios. Finally, a stochastic Petri net model of the human-device interaction is presented, which illustrates how additional health status feedback can be obtained from the WHMS' user.

  10. Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data.

    Science.gov (United States)

    Chen, Lujie; Dubrawski, Artur; Wang, Donghan; Fiterau, Madalina; Guillame-Bert, Mathieu; Bose, Eliezer; Kaynar, Ata M; Wallace, David J; Guttendorf, Jane; Clermont, Gilles; Pinsky, Michael R; Hravnak, Marilyn

    2016-07-01

    The use of machine-learning algorithms to classify alerts as real or artifacts in online noninvasive vital sign data streams to reduce alarm fatigue and missed true instability. Observational cohort study. Twenty-four-bed trauma step-down unit. Two thousand one hundred fifty-three patients. Noninvasive vital sign monitoring data (heart rate, respiratory rate, peripheral oximetry) recorded on all admissions at 1/20 Hz, and noninvasive blood pressure less frequently, and partitioned data into training/validation (294 admissions; 22,980 monitoring hours) and test sets (2,057 admissions; 156,177 monitoring hours). Alerts were vital sign deviations beyond stability thresholds. A four-member expert committee annotated a subset of alerts (576 in training/validation set, 397 in test set) as real or artifact selected by active learning, upon which we trained machine-learning algorithms. The best model was evaluated on test set alerts to enact online alert classification over time. The Random Forest model discriminated between real and artifact as the alerts evolved online in the test set with area under the curve performance of 0.79 (95% CI, 0.67-0.93) for peripheral oximetry at the instant the vital sign first crossed threshold and increased to 0.87 (95% CI, 0.71-0.95) at 3 minutes into the alerting period. Blood pressure area under the curve started at 0.77 (95% CI, 0.64-0.95) and increased to 0.87 (95% CI, 0.71-0.98), whereas respiratory rate area under the curve started at 0.85 (95% CI, 0.77-0.95) and increased to 0.97 (95% CI, 0.94-1.00). Heart rate alerts were too few for model development. Machine-learning models can discern clinically relevant peripheral oximetry, blood pressure, and respiratory rate alerts from artifacts in an online monitoring dataset (area under the curve > 0.87).

  11. Aircraft Control Augmentation and Health Monitoring Using FADS Technology Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This Phase I research proposal is aimed at demonstrating the feasibility of an innovative architecture comprising control augmentation and on-line health monitoring...

  12. Human monitoring, smart health and assisted living techniques and technologies

    CERN Document Server

    Longhi, Sauro; Freddi, Alessandro

    2017-01-01

    This book covers the three main scientific and technological areas critical for improving people's quality of life - namely human monitoring, smart health and assisted living - from both the research and development points of view.

  13. Distributed Rocket Engine Testing Health Monitoring System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Leveraging the Phase I achievements of the Distributed Rocket Engine Testing Health Monitoring System (DiRETHMS) including its software toolsets and system building...

  14. Distributed Rocket Engine Testing Health Monitoring System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The on-ground and Distributed Rocket Engine Testing Health Monitoring System (DiRETHMS) provides a system architecture and software tools for performing diagnostics...

  15. Multinational surveys for monitoring eHealth policy implementations

    DEFF Research Database (Denmark)

    Gilstad, Heidi; Faxvaag, Arild; Hyppönen, Hannele;

    2014-01-01

    Development of multinational variables for monitoring eHealth policy implementations is a complex task and requires multidisciplinary, knowledgebased international collaboration. Experts in an interdisciplinary workshop identified useful data and pitfalls for comparative variable development...

  16. Monitoring and evaluation of health sector reforms in the WHO ...

    African Journals Online (AJOL)

    Data synthesis: In terms of context and design of the cost recovery reform, there ... of appropriate policies and information to monitor and/or influence the process. ... of health services; equitable service utilisation; social sustainability through ...

  17. Passive Wireless Sensor System for Structural Health Monitoring Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Albido proposes to develop a Passive Wireless Sensor System for Structural Health Monitoring capable of measuring high-bandwidth temperature and strain of space and...

  18. Combination Method of Principal Component Analysis and Support Vector Machine for On-line Process Monitoring and Fault Diagnosis

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    On-line monitoring and fault diagnosis of chemical process is extremely important for operation safety and product quality. Principal component analysis (PCA) has been widely used in multivariate statistical process monitoring for its ability to reduce processes dimensions. PCA and other statistical techniques, however, have difficulties in differentiating faults correctly in complex chemical process.Support vector machine (SVM) is a novel approach based on statistical learning theory, which has emerged for feature identification and classification. In this paper, an integrated method is applied for process monitoring and fault diagnosis, which combines PCA for fault feature extraction and multiple SVMs for identification of different fault sources. This approach is verified and illustrated on the Tennessee Eastman benchmark process as a case study.Results show that the proposed PCA-SVMs method has good diagnosis capability and overall diagnosis correctness rate.

  19. Patient monitoring in mobile health: opportunities and challenges.

    Science.gov (United States)

    Mohammadzadeh, Niloofar; Safdari, Reza

    2014-01-01

    In most countries chronic diseases lead to high health care costs and reduced productivity of people in society. The best way to reduce costs of health sector and increase the empowerment of people is prevention of chronic diseases and appropriate health activities management through monitoring of patients. To enjoy the full benefits of E-health, making use of methods and modern technologies is very important. This literature review articles were searched with keywords like Patient monitoring, Mobile Health, and Chronic Disease in Science Direct, Google Scholar and Pub Med databases without regard to the year of publications. Applying remote medical diagnosis and monitoring system based on mobile health systems can help significantly to reduce health care costs, correct performance management particularly in chronic disease management. Also some challenges are in patient monitoring in general and specific aspects like threats to confidentiality and privacy, technology acceptance in general and lack of system interoperability with electronic health records and other IT tools, decrease in face to face communication between doctor and patient, sudden interruptions of telecommunication networks, and device and sensor type in specific aspect. It is obvious identifying the opportunities and challenges of mobile technology and reducing barriers, strengthening the positive points will have a significant role in the appropriate planning and promoting the achievements of the health care systems based on mobile and helps to design a roadmap for improvement of mobile health.

  20. Design of smart neonatal health monitoring system using SMCC.

    Science.gov (United States)

    De, Debashis; Mukherjee, Anwesha; Sau, Arkaprabha; Bhakta, Ishita

    2017-02-01

    Automated health monitoring and alert system development is a demanding research area today. Most of the currently available monitoring and controlling medical devices are wired which limits freeness of working environment. Wireless sensor network (WSN) is a better alternative in such an environment. Neonatal intensive care unit is used to take care of sick and premature neonates. Hypothermia is an independent risk factor for neonatal mortality and morbidity. To prevent it an automated monitoring system is required. In this Letter, an automated neonatal health monitoring system is designed using sensor mobile cloud computing (SMCC). SMCC is based on WSN and MCC. In the authors' system temperature sensor, acceleration sensor and heart rate measurement sensor are used to monitor body temperature, acceleration due to body movement and heart rate of neonates. The sensor data are stored inside the cloud. The health person continuously monitors and accesses these data through the mobile device using an Android Application for neonatal monitoring. When an abnormal situation arises, an alert is generated in the mobile device of the health person. By alerting health professional using such an automated system, early care is provided to the affected babies and the probability of recovery is increased.

  1. Special Tests for Monitoring Fetal Health

    Science.gov (United States)

    ... growth problems, Rh sensitization , or high blood pressure • Decreased movement of the fetus • Pregnancy that goes past ... on how far along you are in your pregnancy, you may have another BPP within the next ... BPP performed? The fetal heart rate is monitored in the same way it is ...

  2. Micro-Accelerometers Monitor Equipment Health

    Science.gov (United States)

    2014-01-01

    Glenn Research Center awarded SBIR funding to Ann Arbor, Michigan-based Evigia Systems to develop a miniaturized accelerometer to account for gravitational effects in space experiments. The company has gone on to implement the technology in its suite of prognostic sensors, which are used to monitor the integrity of industrial machinery. As a result, five employees have been hired.

  3. Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

    Science.gov (United States)

    Sztendel, S.; Pislaru, C.; Longstaff, A. P.; Fletcher, S.; Myers, A.

    2012-05-01

    This paper presents the design, development and SIMULINK implementation of the lumped parameter model of C-axis drive from GEISS five-axis CNC machine tool. The simulated results compare well with the experimental data measured from the actual machine. Also the paper describes the steps for data acquisition using ControlDesk and hardware-in-the-loop implementation of the drive models in dSPACE real-time system. The main components of the HIL system are: the drive model simulation and input - output (I/O) modules for receiving the real controller outputs. The paper explains how the experimental data obtained from the data acquisition process using dSPACE real-time system can be used for the development of machine tool diagnosis and prognosis systems that facilitate the improvement of maintenance activities.

  4. DESIGN OF CAMERA MOUNT AND ITS APPLICATION FOR MONITORING MACHINING PROCESS

    Directory of Open Access Journals (Sweden)

    Nadežda Čuboňová

    2015-05-01

    Full Text Available The article deals with the solution to the problem of holding a scanning device – GoPro camera in the vicinity of milling machine EMCO Concept MILL 105, practical part solves the design and production of the fixture. The proposal of the fixture includes the best placing of the fixture within the milling area. On this basis individual variants of this solution are elaborated. The best variant for holding of the camera was selected and fixture production was experimentally performed on a 3D printer – Easy 3D Maker. Fixture functionality was verified on the milling machine.

  5. Assessing the value of structural health monitoring

    DEFF Research Database (Denmark)

    Thöns, S.; Faber, Michael Havbro

    2013-01-01

    or proven by past experiences but in general there appears to be no rational or systematic approach for assessing the value of SHM systems a-priory to their implementation. The present paper addresses the assessment of the value of SHM with basis in structural risk assessments and the Bayesian pre......-posterior decision analysis. The quantification of the value of SHM builds upon the quantification of the value of information (VoI) or rather the benefit of monitoring. The suggested approach involves a probabilistic representation of the loads and environmental conditions acting on structures as well...... of the uncertainty associated with the performance of SHM on the value of SHM. Moreover, in order to illustrate the potential of the application of approach for monitoring of structural systems an optimal strategy for SHM is determined for a system comprised of three welded details. © 2013 Taylor & Francis Group...

  6. 'MDI Wind' machine diagnostic interface. The online condition monitoring system that's not just for wind turbines; Machine Diagnostic Interface 'MDI-Wind'. Online Condition Monitoring System nicht nur fuer Windenergieanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Eicke, Andreas [ThyssenKrupp System Engineering GmbH, Langenhagen (Germany). Messtechnik

    2012-07-01

    It is becoming increasingly important to be able to implement condition monitoring to protect high-grade investments such as wind turbines and other major industrial plant and installations. ThyssenKrupp System Engineering has developed a Machine Diagnostic Interface (MDI) for this purpose that is based on proven and reliable standard components in terms of the hardware used. As regards the software, the measuring and automation system used is based on mature technology, was developed in-house and has proved its worth over many years on testing and assembly lines in the automotive and supply industry. The basic concept of the Condition Monitoring System (CMS) and the essential technical elements of the MDI are introduced here. The development was funded by the German Federal Ministry of Economics and Technology (BMWi). (orig.)

  7. Prognostics and Health Monitoring of High Power LED

    Directory of Open Access Journals (Sweden)

    Chris Bailey

    2012-02-01

    Full Text Available Prognostics is seen as a key component of health usage monitoring systems, where prognostics algorithms can both detect anomalies in the behavior/performance of a micro-device/system, and predict its remaining useful life when subjected to monitored operational and environmental conditions. Light Emitting Diodes (LEDs are optoelectronic micro-devices that are now replacing traditional incandescent and fluorescent lighting, as they have many advantages including higher reliability, greater energy efficiency, long life time and faster switching speed. For some LED applications there is a requirement to monitor the health of LED lighting systems and predict when failure is likely to occur. This is very important in the case of safety critical and emergency applications. This paper provides both experimental and theoretical results that demonstrate the use of prognostics and health monitoring techniques for high power LEDs subjected to harsh operating conditions.

  8. Monitoring intervention coverage in the context of universal health coverage.

    Directory of Open Access Journals (Sweden)

    Ties Boerma

    2014-09-01

    Full Text Available Monitoring universal health coverage (UHC focuses on information on health intervention coverage and financial protection. This paper addresses monitoring intervention coverage, related to the full spectrum of UHC, including health promotion and disease prevention, treatment, rehabilitation, and palliation. A comprehensive core set of indicators most relevant to the country situation should be monitored on a regular basis as part of health progress and systems performance assessment for all countries. UHC monitoring should be embedded in a broad results framework for the country health system, but focus on indicators related to the coverage of interventions that most directly reflect the results of UHC investments and strategies in each country. A set of tracer coverage indicators can be selected, divided into two groups-promotion/prevention, and treatment/care-as illustrated in this paper. Disaggregation of the indicators by the main equity stratifiers is critical to monitor progress in all population groups. Targets need to be set in accordance with baselines, historical rate of progress, and measurement considerations. Critical measurement gaps also exist, especially for treatment indicators, covering issues such as mental health, injuries, chronic conditions, surgical interventions, rehabilitation, and palliation. Consequently, further research and proxy indicators need to be used in the interim. Ideally, indicators should include a quality of intervention dimension. For some interventions, use of a single indicator is feasible, such as management of hypertension; but in many areas additional indicators are needed to capture quality of service provision. The monitoring of UHC has significant implications for health information systems. Major data gaps will need to be filled. At a minimum, countries will need to administer regular household health surveys with biological and clinical data collection. Countries will also need to improve the

  9. Monitoring intervention coverage in the context of universal health coverage.

    Science.gov (United States)

    Boerma, Ties; AbouZahr, Carla; Evans, David; Evans, Tim

    2014-09-01

    Monitoring universal health coverage (UHC) focuses on information on health intervention coverage and financial protection. This paper addresses monitoring intervention coverage, related to the full spectrum of UHC, including health promotion and disease prevention, treatment, rehabilitation, and palliation. A comprehensive core set of indicators most relevant to the country situation should be monitored on a regular basis as part of health progress and systems performance assessment for all countries. UHC monitoring should be embedded in a broad results framework for the country health system, but focus on indicators related to the coverage of interventions that most directly reflect the results of UHC investments and strategies in each country. A set of tracer coverage indicators can be selected, divided into two groups-promotion/prevention, and treatment/care-as illustrated in this paper. Disaggregation of the indicators by the main equity stratifiers is critical to monitor progress in all population groups. Targets need to be set in accordance with baselines, historical rate of progress, and measurement considerations. Critical measurement gaps also exist, especially for treatment indicators, covering issues such as mental health, injuries, chronic conditions, surgical interventions, rehabilitation, and palliation. Consequently, further research and proxy indicators need to be used in the interim. Ideally, indicators should include a quality of intervention dimension. For some interventions, use of a single indicator is feasible, such as management of hypertension; but in many areas additional indicators are needed to capture quality of service provision. The monitoring of UHC has significant implications for health information systems. Major data gaps will need to be filled. At a minimum, countries will need to administer regular household health surveys with biological and clinical data collection. Countries will also need to improve the production of

  10. Structural Health Monitoring of Tall Buildings with Numerical Integrator and Convex-Concave Hull Classification

    Directory of Open Access Journals (Sweden)

    Suresh Thenozhi

    2012-01-01

    Full Text Available An important objective of health monitoring systems for tall buildings is to diagnose the state of the building and to evaluate its possible damage. In this paper, we use our prototype to evaluate our data-mining approach for the fault monitoring. The offset cancellation and high-pass filtering techniques are combined effectively to solve common problems in numerical integration of acceleration signals in real-time applications. The integration accuracy is improved compared with other numerical integrators. Then we introduce a novel method for support vector machine (SVM classification, called convex-concave hull. We use the Jarvis march method to decide the concave (nonconvex hull for the inseparable points. Finally the vertices of the convex-concave hull are applied for SVM training.

  11. Sentinel areas: a monitoring strategy in public health

    Directory of Open Access Journals (Sweden)

    Teixeira Maria da Glória

    2002-01-01

    Full Text Available Available techniques for monitoring the health situation have proven insufficient, thus leading to a discussion of the need for their improvement based on new data collection strategies allowing for data use by local health systems. This article presents the methodological basis for a strategy to monitor health problems utilizing demarcated intra-urban spaces called "sentinel areas" to collect fundamental social, economic, behavioral, and biological data for public health that allow for a closer approach to the reality of complex social spaces. The authors present an experience that is being developed in Salvador, Bahia, Brazil, to evaluate the epidemiological impact of an environmental sanitation program. They discuss selection criteria for the areas and the potential uses of this strategy allowing for the rapid utilization of epidemiological resources by health services and the timely application of the results to reorient and enhance health intervention practices.

  12. Watershed health assessment to monitor land degradation

    Science.gov (United States)

    Hamidreza Sadeghi, Seyed; Hazbavi, Zeinab; Cerdà, Artemi

    2017-04-01

    Land degradation is a worldwide issue that affects the Planet and the fate of the humankind (Cerdà et al., 2009; Choudhury et al., 2016; Fernández et al., 2016; Ferreira et al., 2016). Several processes affect the sustainability of the ecosystems, from soil erosion to soil compation, deforestation, Climate Change or water, soil and air pollution (Sadeghi et al., 2015a; 2015b; Gómez-Acanta et al., 2016; Mengistu et al., 2016; Mukai, 2016). Several ecosystem theories have been presented in the scientific literatures to monitor land degradation (Cerdà et al., 2016; Davudirad et al., 2016; Fava et al., 2016; Mahyou et al., 2016; Soulard et al., 2016). Besides the scientific tasks of improving the indication, the conviction of the potential users to change their concepts toward a higher consideration of ecosystem attributes, and toward a fruitful application of the health or integrity concepts, will be a main task of future activities. Reliability, resilience and vulnerability (R-R-V) indicators are often used in combination for quantifying risk and decision making in many systems. However, the use of hydrological series data for R-R-V computations has been rather limited. Toward this, the overall objective of this paper is to conduct a risk assessment analysis on stream flow discharge from Shazand Watershed located in the south western of Markazi Province in Iran for the period of 1972-2014 using R-R-V indicators. Based on the R-R-V analysis conducted in this study, the stream flow discharge of the study region followed a cyclic pattern with a decreasing trend. The results further showed a decreasing trend in reliability and resilience and an increasing trend in vulnerability in the Shazand Watershed. It may be concluded that the Shazand Watershed was in overall in unhealthy condition from view of stream flow discharge. Acknowledgements This research was funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant no. 603498 (RECARE Project

  13. Approaches to integrated monitoring for environmental health impact assessment

    Directory of Open Access Journals (Sweden)

    Liu Hai-Ying

    2012-11-01

    Full Text Available Abstract Although Integrated Environmental Health Monitoring (IEHM is considered an essential tool to better understand complex environmental health issues, there is no consensus on how to develop such a programme. We reviewed four existing frameworks and eight monitoring programmes in the area of environmental health. We identified the DPSEEA (Driving Force-Pressure-State-Exposure-Effect-Action framework as most suitable for developing an IEHM programme for environmental health impact assessment. Our review showed that most of the existing monitoring programmes have been designed for specific purposes, resulting in narrow scope and limited number of parameters. This therefore limits their relevance for studying complex environmental health topics. Other challenges include limited spatial and temporal data availability, limited development of data sharing mechanisms, heterogeneous data quality, a lack of adequate methodologies to link disparate data sources, and low level of interdisciplinary cooperation. To overcome some of these challenges, we propose a DPSEEA-based conceptual framework for an IEHM programme that would enable monitoring and measuring the impact of environmental changes on human health. We define IEHM as ‘a systemic process to measure, analyse and interpret the state and changes of natural-eco-anthropogenic systems and its related health impact over time at the same location with causative explanations across the various compartments of the cause-effect chain’. We develop a structural work process to integrate information that is based on existing environmental health monitoring programmes. Such a framework allows the development of combined monitoring systems that exhibit a large degree of compatibility between countries and regions.

  14. Self-report in Youth Health Monitoring: evidence from the Rotterdam Youth Monitor

    NARCIS (Netherlands)

    P.M. van de Looij-Jansen (Petra)

    2010-01-01

    textabstractUnder Dutch law, preventive youth healthcare organisations have a duty to ensure the early identification of children with health or developmental problems. Similarly, municipalities have a duty to monitor young people’s health at least every four years. For problem identification and mo

  15. Self-report in Youth Health Monitoring: evidence from the Rotterdam Youth Monitor

    NARCIS (Netherlands)

    P.M. van de Looij-Jansen (Petra)

    2010-01-01

    textabstractUnder Dutch law, preventive youth healthcare organisations have a duty to ensure the early identification of children with health or developmental problems. Similarly, municipalities have a duty to monitor young people’s health at least every four years. For problem identification and

  16. A machine learning-based framework to identify type 2 diabetes through electronic health records.

    Science.gov (United States)

    Zheng, Tao; Xie, Wei; Xu, Liling; He, Xiaoying; Zhang, Ya; You, Mingrong; Yang, Gong; Chen, You

    2017-01-01

    To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards. The goal of this work is to develop a semi-automated framework based on machine learning as a pilot study to liberalize filtering criteria to improve recall rate with a keeping of low false positive rate. We propose a data informed framework for identifying subjects with and without T2DM from EHR via feature engineering and machine learning. We evaluate and contrast the identification performance of widely-used machine learning models within our framework, including k-Nearest-Neighbors, Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Logistic Regression. Our framework was conducted on 300 patient samples (161 cases, 60 controls and 79 unconfirmed subjects), randomly selected from 23,281 diabetes related cohort retrieved from a regional distributed EHR repository ranging from 2012 to 2014. We apply top-performing machine learning algorithms on the engineered features. We benchmark and contrast the accuracy, precision, AUC, sensitivity and specificity of classification models against the state-of-the-art expert algorithm for identification of T2DM subjects. Our results indicate that the framework achieved high identification performances (∼0.98 in average AUC), which are much higher than the state-of-the-art algorithm (0.71 in AUC). Expert algorithm-based identification of T2DM subjects from EHR is often hampered by the high missing rates due to their conservative selection criteria. Our framework leverages machine learning and feature

  17. Vulnerability analysis for design of bridge health monitoring system

    Science.gov (United States)

    Sun, L. M.; Yu, G.

    2010-03-01

    The recent engineering implementation of health monitoring system for long span bridges show difficulties for precisely assessing structural physical condition as well as for accurately alarming on structural damages, although hundreds of sensors were installed on a structure and a great amount of data were collected from the monitoring system. The allocation of sensors and the alarming algorithm are still two of the most important tasks to be considered when designing the structural health monitoring system. Vulnerability, in its original meaning, is the system susceptibility to local damage. For a structural system, the vulnerability can thus be regarded as structural performance susceptibility to local damage of structure. The purpose of this study is to propose concepts and methods of structural vulnerability for determining monitoring components which are more vulnerable than others and the corresponding warning threshold once the damages occur. The structural vulnerability performances to various damage scenarios depend upon structural geometrical topology, loading pattern on the structure and the degradation of component performance. A two-parameters structural vulnerability evaluation method is proposed in this paper. The parameters are the damage consequence and the relative magnitude of the damage scenarios to the structural system, respectively. Structural vulnerability to various damage scenarios can be regarded as the tradeoff between the two parameters. Based on the results of structural vulnerability analysis, the limited structural information from health monitoring can be utilized efficiently. The approach of the design of bridge health monitoring system is illustrated for a cable-stayed bridge.

  18. An Integrated Health Monitoring System for Fission Surface Power

    Science.gov (United States)

    Hashemian, H. M.; Shumaker, B. D.; McCulley, J. R.; Morton, G. W.

    Based on such criteria as safety and mission success, programmatic risk, affordability, and extensibility/flexibility, the National Aeronautics and Space Administration (NASA) has chosen fission surface power (FSP) as the primary energy source for building a sustained human presence on the Moon, exploring Mars, and extremely long-duration space missions. The current benchmark FSP system has a mission life of at least 8 years during which time there is no opportunity for repair, sensor calibrations, or periodic maintenance tasks that are normally performed on terrestrial-based nuclear power plants during scheduled outages. Current technology relies heavily on real-time human interaction, monitoring and control. However; due to the long communication times between the Earth and Moon, or Mars, real-time human control is not possible, resulting in a critical need to develop autonomous health monitoring technology for FSP systems.This paper describes the design and development of an autonomous health monitoring system that will (1) provide on-line calibration monitoring, (2) reduce uncertainties in sensor measurements, and (3) provide sensor validation and fault detection capabilities for the control systems of various FSP subsystems. The health monitoring system design integrates a number of signal processing algorithms and techniques such as cross-calibration, empirical modeling using neural networks, and physical modeling under a modular signal processing platform that will enable robust sensor and system monitoring without the need for human interaction. Prototypes of the health monitoring system have been tested and validated on data acquired from preliminary subsystem testing of NASA's FSP Technology Demonstration Unit (TDU) as well as simulated laboratory data. Results from this testing have demonstrated the utility and benefits that such autonomous health monitoring systems can provide to FSP subsystems and other potential applications within NASA such as launch

  19. Respiratory Health and Allergies from Chemical Exposures among Machining Industry Workers in Selangor, Malaysia

    Directory of Open Access Journals (Sweden)

    Soo Hui LIAW

    2015-10-01

    Full Text Available Background: This study was to determine the prevalence of respiratory health complaints, allergy symptom, lung functions, and the association between airborne concentrations of chromium and aluminium with respiratory health and allergy symptoms among machining industry workers in Selangor, Malaysia.Methods: The study design was a cross-sectional comparative study. The respiratory and allergy symptoms were obtained through the American Thoracic Society (ATS Adult Respiratory Questionnaire (ATS-DLD-78  modified questionnaire. Results: The MWFs unexposed group had significantly higher TWA8 airborne aluminum concentration (median = 0.24 µg/m3 than the exposed group (median = 0.13 µg/m3 (P=0.027. However, no significant difference was found in the airborne chromium between both groups. Significantly higher skin itchiness was reported by the MWFs exposed group. This was further supported by the serum total IgE concentrations which was significantly higher among MWFs exposed group than the unexposed group (P=0.024. The prevalence of total serum IgE was significantly higher for the exposed group (54.3% than the unexposed group (36.9%. The exposed group reported significantly higher prevalence of cough symptom, morning cough with sputum and health worries caused by metalworking fluids than the unexposed group. Conclusion: This study showed significantly higher allergy and respiratory symptoms among the MWFs exposed group than the unexposed group.   Keywords: Machining industry, Metalworking fluids, Allergy symptoms, IgE, Lung function

  20. Mental health care Monitor Older adults (MEMO) : monitoring patient characteristics and outcome in Dutch mental health services for older adults

    NARCIS (Netherlands)

    Veerbeek, Marjolein; Voshaar, Richard Oude; Depla, Marja; Pot, Anne Margriet

    2013-01-01

    Information on which older adults attend mental health care and whether they profit from the care they receive is important for policy-makers. To assess this information in daily practice, the Mental health care Monitor Older adults (MEMO) was developed in the Netherlands. The aim of this paper is t

  1. Impact of Health Care Employees’ Job Satisfaction On Organizational Performance Support Vector Machine Approach

    Directory of Open Access Journals (Sweden)

    Cemil Kuzey

    2012-05-01

    Full Text Available This study was undertaken to search for key factors that contribute to job satisfaction among health care workers, and also to determine the impact of these underlying dimensions of employee satisfaction on organizational performance. Exploratory Factor Analysis (EFA was applied to initially uncover the key factors, and then, in the next stage of analysis, a popular data mining technique, Support Vector Machine (SVM was employed on a sample of 249 to determine the impact of job satisfaction factors on organizational performance. According to the proposed model, the main factors were revealed to be management’s attitude, pay/reward, job security and colleagues.

  2. Distributed multisensor processing, decision making, and control under constrained resources for remote health and environmental monitoring

    Science.gov (United States)

    Talukder, Ashit; Sheikh, Tanwir; Chandramouli, Lavanya

    2004-04-01

    Previous field-deployable distributed sensing systems for health/biomedical applications and environmental sensing have been designed for data collection and data transmission at pre-set intervals, rather than for on-board processing These previous sensing systems lack autonomous capabilities, and have limited lifespans. We propose the use of an integrated machine learning architecture, with automated planning-scheduling and resource management capabilities that can be used for a variety of autonomous sensing applications with very limited computing, power, and bandwidth resources. We lay out general solutions for efficient processing in a multi-tiered (three-tier) machine learning framework that is suited for remote, mobile sensing systems. Novel dimensionality reduction techniques that are designed for classification are used to compress each individual sensor data and pass only relevant information to the mobile multisensor fusion module (second-tier). Statistical classifiers that are capable of handling missing/partial sensory data due to sensor failure or power loss are used to detect critical events and pass the information to the third tier (central server) for manual analysis and/or analysis by advanced pattern recognition techniques. Genetic optimisation algorithms are used to control the system in the presence of dynamic events, and also ensure that system requirements (i.e. minimum life of the system) are met. This tight integration of control optimisation and machine learning algorithms results in a highly efficient sensor network with intelligent decision making capabilities. The applicability of our technology in remote health monitoring and environmental monitoring is shown. Other uses of our solution are also discussed.

  3. Augmented Fish Health Monitoring; Volume II of II, Completion Report.

    Energy Technology Data Exchange (ETDEWEB)

    Michak, Patty

    1991-12-01

    The Bonneville Power Administration (BPA) initiated the Augmented Fish Health Monitoring project in 1986. This project was a five year interagency project involving fish rearing agencies in the Columbia Basin. Participating agencies included: Washington Department of Fisheries (WDF), Oregon Department of Fish and Wildlife, Idaho Department of Fish and Game, and the US Fish and Wildlife Service (USFWS). This is the final data report for the Augmented Fish Health Monitoring project. Data collected and sampling results for 1990 and 1991 are presented within this report. An evaluation of this project can be found in Augmented Fish Health Monitoring, Volume 1, Completion Report.'' May, 1991. Pathogen detection methods remained the same from methods described in Augmented Fish Health Monitoring, Annual Report 1989,'' May, 1990. From January 1, 1990 to June 30, 1991 fish health monitoring sampling was conducted. In 1990 21 returning adult stocks were sampled. Juvenile pre-release exams were completed on 20 yearling releases, and 13 sub-yearling releases in 1990. In 1991 17 yearling releases and 11 sub-yearling releases were examined. Midterm sampling was completed on 19 stocks in 1990. Organosomatic analysis was performed at release on index station stocks; Cowlitz spring and fall chinook, Lewis river early coho and Lyons Ferry fall chinook.

  4. An intelligent condition monitoring system for on-line classification of machine tool wear

    Energy Technology Data Exchange (ETDEWEB)

    Fu Pan; Hope, A.D.; Javed, M. [Systems Engineering Faculty, Southampton Institute (United Kingdom)

    1997-12-31

    The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

  5. Quality Monitoring for Laser Welding Based on High-Speed Photography and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Teng Wang

    2017-03-01

    Full Text Available In order to improve the prediction ability of welding quality during high-power disk laser welding, a new approach was proposed and applied in the classification of the dynamic features of metal vapor plume. Six features were extracted through the color image processing method. Three features, including the area of plume, number of spatters, and horizontal coordinate of plume centroid, were selected based on the classification accuracy rates and Pearson product-moment correlation coefficients. A support vector machine model was adopted to classify the welding quality status into two categories, good or poor. The results demonstrated that the support vector machine model established according to the selected features had satisfactory prediction and generalization ability. The classification accuracy rate was higher than 90%, and the model could be applied in the prediction of welding quality during high-power disk laser welding.

  6. Wavelet-based AR-SVM for health monitoring of smart structures

    Science.gov (United States)

    Kim, Yeesock; Chong, Jo Woon; Chon, Ki H.; Kim, JungMi

    2013-01-01

    This paper proposes a novel structural health monitoring framework for damage detection of smart structures. The framework is developed through the integration of the discrete wavelet transform, an autoregressive (AR) model, damage-sensitive features, and a support vector machine (SVM). The steps of the method are the following: (1) the wavelet-based AR (WAR) model estimates vibration signals obtained from both the undamaged and damaged smart structures under a variety of random signals; (2) a new damage-sensitive feature is formulated in terms of the AR parameters estimated from the structural velocity responses; and then (3) the SVM is applied to each group of damaged and undamaged data sets in order to optimally separate them into either damaged or healthy groups. To demonstrate the effectiveness of the proposed structural health monitoring framework, a three-story smart building equipped with a magnetorheological (MR) damper under artificial earthquake signals is studied. It is shown from the simulation that the proposed health monitoring scheme is effective in detecting damage of the smart structures in an efficient way.

  7. Actuation, monitoring and closed-loop control of sewing machine presser foot

    OpenAIRE

    Silva, Luís F.; Lima, Mário; Carvalho, Helder; Rocha, A.M.; Ferreira, Fernando; Monteiro, João L.; Couto, Carlos

    2003-01-01

    Sewing is one of the most important processes in the apparel industry for the production of high-quality garments. Although some research and improvements have been carried out in this area, the sewing process has remained almost unchanged throughout the years, staying largely dependent on the operator skills to set up sewing parameters and to handle the fabrics being sewn. Slight changes in sewing machine settings can influence the quality of seams, as well as sewing operation time. To avoid...

  8. Integrated electronic system for ultrasonic structural health monitoring

    OpenAIRE

    Ruiz González, Mariano; Monje, Pedro María; Casado, Luciano; Aranguren, Gerardo; Cokonaj, Valerijan; Barrera Lopez de Turiso, Eduardo

    2012-01-01

    A fully integrated on-board electronic system that can perform in-situ structural health monitoring (SHM) of aircraft?s structures using specifically designed equipment for SHM based on guided wave ultrasonic method or Lamb waves? method is introduced. This equipment is called Phased Array Monitoring for Enhanced Life Assessment (PAMELA III) and is an essential part of overall PAMELA SHM? system. PAMELA III can generate any kind of excitation signals, acquire the response signals that propaga...

  9. Distributed Data Storage Model for Cattle Health Monitoring Using WSN

    Directory of Open Access Journals (Sweden)

    Ankit R. Bhavsar

    2013-05-01

    Full Text Available Now a day, wireless sensor networks (WSN are being deployed in various applications like industrial, environmental, health care, societal monitoring. The sensor networks have tendency to generate huge amount of data. Hence data storage techniques become a critical issue for the success of these applications. In this paper, we have proposed a distributed data storage model used for WSN based cattle health monitoring. We have also defined the structure for the same. We have divided this model into two levels namely a local level and a central level. The main aim of storing data locally is to get quick response for any query raised by the user. The second level where the data is centralized is used to make long term decision, planning and policy for the cattle health monitoring.

  10. Smart Materials in Structural Health Monitoring, Control and Biomechanics

    CERN Document Server

    Soh, Chee-Kiong; Bhalla, Suresh

    2012-01-01

    "Smart Materials in Structural Health Monitoring, Control and Biomechanics" presents the latest developments in structural health monitoring, vibration control and biomechanics using smart materials. The book mainly focuses on piezoelectric, fibre optic and ionic polymer metal composite materials. It introduces concepts from the very basics and leads to advanced modelling (analytical/ numerical), practical aspects (including software/ hardware issues) and case studies spanning civil, mechanical and aerospace structures, including bridges, rocks and underground structures. This book is intended for practicing engineers, researchers from academic and R&D institutions and postgraduate students in the fields of smart materials and structures, structural health monitoring, vibration control and biomedical engineering. Professor Chee-Kiong Soh and Associate Professor Yaowen Yang both work at the School of Civil and Environmental Engineering, Nanyang Technological University, Singapore. Dr. Suresh Bhalla is an A...

  11. A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care.

    Science.gov (United States)

    Alanazi, Hamdan O; Abdullah, Abdul Hanan; Qureshi, Kashif Naseer

    2017-04-01

    Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.

  12. Structural health monitoring of grandstands: a review

    Directory of Open Access Journals (Sweden)

    Gómez-Casero Fuentes Miguel Ángel

    2015-01-01

    Full Text Available This article is a state of the art about Grandstands. The Grandstands are slender structures designed to accommodate a large number of people, which are specially under the actions of wind and the human-structure interaction. Over the years, it has been discuss of this topic, although still the number of publications still remain low. The human-structure interaction is a complex issue, where the loads may have different behaviours, depending many factors, including: type of audience (active or passive, public behaviour (jumping, walking, running, clapping, vandal loads, type of event (sports, concerts, meeting, position and posture of the individual, even influences the type of seat (with or without back, stiffness. However, the structure will behave differently when empty or fully occupied. Another load to consider is the wind, especially when the structure has a roof, screens, large-scale advertising, etc. These two types of loads can interact together, which implies an increase in the normal number of load combinations to consider. There are biomechanical models of human behaviour, used for design these types of structures. In addition, there are mathematical models to simulate the behaviour of the Grandstands by numerical methods. In recent years, all these models are throwing good results, against laboratory tests performed. It has also been monitored real Grandstands. This paper compiles all existing information on this topic.

  13. Structural Health Monitoring of AN Aircraft Joint

    Science.gov (United States)

    Mickens, T.; Schulz, M.; Sundaresan, M.; Ghoshal, A.; Naser, A. S.; Reichmeider, R.

    2003-03-01

    A major concern with ageing aircraft is the deterioration of structural components in the form of fatigue cracks at fastener holes, loose rivets and debonding of joints. These faults in conjunction with corrosion can lead to multiple-site damage and pose a hazard to flight. Developing a simple vibration-based method of damage detection for monitoring ageing structures is considered in this paper. The method is intended to detect damage during operation of the vehicle before the damage can propagate and cause catastrophic failure of aircraft components. It is typical that only a limited number of sensors could be used on the structure and damage can occur anywhere on the surface or inside the structure. The research performed was to investigate use of the chirp vibration responses of an aircraft wing tip to detect, locate and approximately quantify damage. The technique uses four piezoelectric patches alternatively as actuators and sensors to send and receive vibration diagnostic signals.Loosening of selected screws simulated damage to the wing tip. The results obtained from the testing led to the concept of a sensor tape to detect damage at joints in an aircraft structure.

  14. Structural Health Monitoring Analysis for the Orbiter Wing Leading Edge

    Science.gov (United States)

    Yap, Keng C.

    2010-01-01

    This viewgraph presentation reviews Structural Health Monitoring Analysis for the Orbiter Wing Leading Edge. The Wing Leading Edge Impact Detection System (WLE IDS) and the Impact Analysis Process are also described to monitor WLE debris threats. The contents include: 1) Risk Management via SHM; 2) Hardware Overview; 3) Instrumentation; 4) Sensor Configuration; 5) Debris Hazard Monitoring; 6) Ascent Response Summary; 7) Response Signal; 8) Distribution of Flight Indications; 9) Probabilistic Risk Analysis (PRA); 10) Model Correlation; 11) Impact Tests; 12) Wing Leading Edge Modeling; 13) Ascent Debris PRA Results; and 14) MM/OD PRA Results.

  15. Using Machine Learning to Estimate Global PM2.5 for Environmental Health Studies.

    Science.gov (United States)

    Lary, D J; Lary, T; Sattler, B

    2015-01-01

    With the increasing awareness of health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground-level airborne particulate matter (PM2.5). Here we use a suite of remote sensing and meteorological data products together with ground based observations of PM2.5 from 8,329 measurement sites in 55 countries taken between 1997 and 2014 to train a machine learning algorithm to estimate the daily distributions of PM2.5 from 1997 to the present. We demonstrate that the new PM2.5 data product can reliably represent global observations of PM2.5 for epidemiological studies. An analysis of Baltimore schizophrenia emergency room admissions is presented in terms of the levels of ambient pollution. PM2.5 appears to have an impact on some aspects of mental health.

  16. Integrating Social Media Monitoring Into Public Health Emergency Response Operations.

    Science.gov (United States)

    Hadi, Tamer A; Fleshler, Keren

    2016-10-01

    Social media monitoring for public health emergency response and recovery is an essential response capability for any health department. The value of social media for emergency response lies not only in the capacity to rapidly communicate official and critical incident information, but as a rich source of incoming data that can be gathered to inform leadership decision-making. Social media monitoring is a function that can be formally integrated into the Incident Command System of any response agency. The approach to planning and required resources, such as staffing, logistics, and technology, is flexible and adaptable based on the needs of the agency and size and scope of the emergency. The New York City Department of Health and Mental Hygiene has successfully used its Social Media Monitoring Team during public health emergency responses and planned events including major Ebola and Legionnaires' disease responses. The concepts and implementations described can be applied by any agency, large or small, interested in building a social media monitoring capacity. (Disaster Med Public Health Preparedness. 2016;page 1 of 6).

  17. Design of a Human Machine Interface for a Reliability Monitoring System of Nuclear Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yuxin; Yang, Ming; Yan, Shengyuan [Harbin Engineering University, Harbin (Switzerland)

    2014-08-15

    This paper presents the design of a Reliability Monitoring System (RMS) for nuclear power plant which was newly developed by authors. The RMS, combining a dynamic reliability analysis system with an online fault management system, can assist technical personnel with their daily tasks such as system configuration management, maintenance plan making and state monitoring from a point of view that degradation of equipment performance, bad plant configurations and incorrect actions will decrease the probability of systems performing designed functions. For utilizing the RMS, technical personnel will monitor the plant operational state, conform the fault diagnosis, input the intended operating or maintenance actions, and monitor the probability changes of systems through a graphical HMI. A HMI evaluation experiment was conducted using an eye tracking system and a full scale simulator of PWR NPP. Visual data was recorded and analyzed after the experiment. The experiment results are presented and the HMI design problems revealed by the evaluation experiment are discussed.

  18. mHealthMon: toward energy-efficient and distributed mobile health monitoring using parallel offloading.

    Science.gov (United States)

    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.

  19. Monitoring Rangeland Health With MODIS Vegetation Index Data

    Science.gov (United States)

    Brown, J. F.

    2004-12-01

    Rangelands cover approximately one third of the land area of the conterminous U.S. These lands supply much of the forage for the U.S. cattle industry. Large area monitoring of these vast expanses of range has proved challenging since most of these lands are in the western U.S., are relatively sparsely populated, and are not well covered by meteorological weather stations. Improvements in the spatial and temporal precision of rangeland health information would be useful both for the cattle industry and for scientific studies of soil erosion, water runoff, ecosystem health, and carbon cycling. Optical multispectral remote sensing data from satellites are an objective source of synoptic, timely information for monitoring rangeland health. The objective of this study is to develop and evaluate a method for measuring and monitoring rangeland health over large areas. In the past, data collected by the Advanced Very High Resolution Radiometer has proved useful for this purpose, however the basic 1 km spatial resolution is not ideal when scaling up from ground observations. This study assesses MODIS 250 meter resolution vegetation index data for this purpose. MODIS data not only have finer spatial resolution and improved geolocation, but they also exhibit enhanced vegetation sensitivity and minimized variations associated with external atmospheric and non-atmospheric effects. Ground data collected over 51 sites in western South Dakota over four years are used as training for regression tree models of range health. Range health maps for the growing season derived from the models are presented and evaluated.

  20. [Biological monitoring: concepts and applications in public health].

    Science.gov (United States)

    Pivetta, F; Machado, J M; Araújo, U C; Moreira, M F; Apostoli, P

    2001-01-01

    This study provides an overview of the theoretical discussion on potential uses for biological monitoring of exposure to chemical substances as related to human health, considering different concepts: definitions, uses, and limitations of internal dose and biological effect indicators and their availability for the substances to be quantified; knowledge of reference values, action levels, and limits based on health and negotiated patterns in biological monitoring interpretation and perspectives; and ethical and social problems in practice and within different preventive practices and their use in public health. Biological monitoring is the result of an exposure situation with conclusions based on scientific and consensus values, rules, and legislation. Biological monitoring as a continuous process and related to actually observed cases has helped establish technological exposure reference values and consensus levels as indicators for improving the environment and the workplace. As a step in the decision-making process in risk analysis, biological monitoring needs to be critically assessed as to its ethical aspects in light of the end use of results and values, which are references for application of this methodology.

  1. Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges.

    Science.gov (United States)

    Banaee, Hadi; Ahmed, Mobyen Uddin; Loutfi, Amy

    2013-12-17

    The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems.

  2. Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges

    Directory of Open Access Journals (Sweden)

    Hadi Banaee

    2013-12-01

    Full Text Available The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems.

  3. Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges

    Science.gov (United States)

    Banaee, Hadi; Ahmed, Mobyen Uddin; Loutfi, Amy

    2013-01-01

    The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems. PMID:24351646

  4. Course Modules on Structural Health Monitoring with Smart Materials

    Science.gov (United States)

    Shih, Hui-Ru; Walters, Wilbur L.; Zheng, Wei; Everett, Jessica

    2009-01-01

    Structural Health Monitoring (SHM) is an emerging technology that has multiple applications. SHM emerged from the wide field of smart structures, and it also encompasses disciplines such as structural dynamics, materials and structures, nondestructive testing, sensors and actuators, data acquisition, signal processing, and possibly much more. To…

  5. Time-frequency Methods for Structural Health Monitoring

    NARCIS (Netherlands)

    Pyayt, A.L.; Kozionov, A.P.; Mokhov, I.I.; Lang, B.; Meijer, R.J.; Krzhizhanovskaya, V.V.; Sloot, P.M.A.

    2014-01-01

    Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM) of flood protection systems (levees, earthen dikes and

  6. Time-frequency methods for structural health monitoring

    NARCIS (Netherlands)

    Pyayt, A.L.; Kozionov, A.P.; Mokhov, I.I.; Lang, B.; Meijer, R.J.; Krzhizhanovskaya, V.V.; Sloot, P.M.A.

    2014-01-01

    Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM) of flood protection systems (levees, earthen dikes and

  7. Multidisciplinary health monitoring of a steel bridge deck structure

    NARCIS (Netherlands)

    Pahlavan, P.L.; Pijpers, R.J.M.; Paulissen, J.H.; Hakkesteegt, H.C.; Jansen, T.H.

    2013-01-01

    Fatigue cracks in orthotropic bridge decks are an important cause for the necessary renovation of existing bridges. Parallel utilization of various technologies based on different physical sensing principles can potentially maximize the efficiency of structural health monitoring (SHM) systems for th

  8. Nonlinear feature identification of impedance-based structural health monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Rutherford, A. C. (Amanda C.); Park, G. H. (Gyu Hae); Sohn, H. (Hoon); Farrar, C. R. (Charles R.)

    2004-01-01

    The impedance-based structural health monitoring technique, which utilizes electromechanical coupling properties of piezoelectric materials, has shown feasibility for use in a variety of structural health monitoring applications. Relying on high frequency local excitations (typically > 30 kHz), this technique is very sensitive to minor changes in structural integrity in the near field of piezoelectric sensors. Several damage sensitive features have been identified and used coupled with the impedance methods. Most of these methods are, however, limited to linearity assumptions of a structure. This paper presents the use of experimentally identified nonlinear features, combined with impedance methods, for structural health monitoring. Their applicability to damage detection in various frequency ranges is demonstrated using actual impedance signals measured from a portal frame structure. The performance of the nonlinear feature is compared with those of conventional impedance methods. This paper reinforces the utility of nonlinear features in structural health monitoring and suggests that their varying sensitivity in different frequency ranges may be leveraged for certain applications.

  9. Model-based health monitoring of hybrid systems

    CERN Document Server

    Wang, Danwei; Low, Chang Boon; Arogeti, Shai

    2013-01-01

    Offers in-depth comprehensive study on health monitoring for hybrid systems Includes new concepts, such as GARR, mode tracking and multiple failure prognosis Contains many examples, making the developed techniques easily understandable and accessible Introduces state-of-the-art algorithms and methodologies from experienced researchers

  10. Monitoring health related quality of life in adolescents with diabetes

    DEFF Research Database (Denmark)

    de Wit, M; Delemarre-van de Waal, Henriette A; Pouwer, F

    2007-01-01

    Particularly in chronic conditions, monitoring health related quality of life (HRQoL) of adolescents in clinical practice is increasingly advocated. We set out to identify and review the clinical utility of available generic and diabetes specific HRQoL questionnaires suitable for use in adolescents...

  11. A Survey of Current Rotorcraft Propulsion Health Monitoring Technologies

    Science.gov (United States)

    Delgado, Irebert R.; Dempsey, Paula J.; Simon, Donald L.

    2012-01-01

    A brief review is presented on the state-of-the-art in rotorcraft engine health monitoring technologies including summaries on current practices in the area of sensors, data acquisition, monitoring and analysis. Also, presented are guidelines for verification and validation of Health Usage Monitoring System (HUMS) and specifically for maintenance credits to extend part life. Finally, a number of new efforts in HUMS are summarized as well as lessons learned and future challenges. In particular, gaps are identified to supporting maintenance credits to extend rotorcraft engine part life. A number of data sources were consulted and include results from a survey from the HUMS community, Society of Automotive Engineers (SAE) documents, American Helicopter Society (AHS) papers, as well as references from Defence Science & Technology Organization (DSTO), Civil Aviation Authority (CAA), and Federal Aviation Administration (FAA).

  12. Non Invasive Sensors for Monitoring the Efficiency of AC Electrical Rotating Machines

    Directory of Open Access Journals (Sweden)

    Thierry Jacq

    2010-08-01

    Full Text Available This paper presents a non invasive method for estimating the energy efficiency of induction motors used in industrial applications. This method is innovative because it is only based on the measurement of the external field emitted by the motor. The paper describes the sensors used, how they should be placed around the machine in order to decouple the external field components generated by both the air gap flux and the winding end-windings. The study emphasizes the influence of the eddy currents flowing in the yoke frame on the sensor position. A method to estimate the torque from the external field use is proposed. The measurements are transmitted by a wireless module (Zig-Bee and they are centralized and stored on a PC computer.

  13. Piezoelectric Driven Antenna System for Health Monitoring Gadgets

    Directory of Open Access Journals (Sweden)

    Omar A. Saraereh

    2016-10-01

    Full Text Available Advancement in medical science is emerging day by day, and application of engineering technology in the field of medical science plays a very important role. In this paper, a novel method to monitor the health condition of an individual is developed. The proposed system uses piezoelectric devices to operate a health monitoring gadget with antenna that is suitable to operate for the piezoelectric based power source. The present day health monitoring gadgets require battery replacement or need to be charged. These would be a problem for the user when the device runs out of the charge. In order to overcome these challenges, the concept of piezoelectricity is applied to charge the gadget. The gadget consists of a transmitter, which is a wearable device, which will be worn by the patient, whose health condition has to be monitored. The receiver unit is placed in the nearest hospital, which will receive the physical conditions of the patient and, monitoring of the health condition is done. Piezoelectric based charging system is used to drive the proposed gadget. The transmission and reception is accomplished by GSM. In order to achieve better performance, microstrip antenna is used for transmission and reception. The simulation of the proposed system is done using Multisim, and simulation results are presented. The piezoelectric simulation is done using MATLAB and also the simulation of micro strip antenna is presented. Here the microstrip antennas will be stimulated for frequency range of 2-3 GHz and 5-6 GHz (preferably 2.2 and 2.5 GHz, using HFSS and MATLAB. The piezoelectric beam is simulated and the voltage produced for the deflection is noted. It was found that for deflection of 33um, a voltage of 100V is produced.The various performance parameters of the antenna, such as impedance, VSWR, reflection coefficient, return loss are obtained and presented.

  14. Augmented Fish Health Monitoring, 1987-1988 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Warren, James W.

    1988-08-01

    Augmented Fish Health Monitoring Contract DE-AI79-87BP35585 was implemented on July 20, 1987. First year highlights included remodeling of the Olympia (WA) Fish Health Center to provide laboratory space for histopathological support services to participating state agencies, acquisition of gas monitoring equipment for hatchery water systems, expanded disease detection work for bacterial kidney disease and erythrocytic inclusion body syndrome in fish stocks at 13 Columbia River Basin National Fish Hatcheries and advancements in computerized case history data storage and analysis. This report summarizes the health status of fish reared at Service facilities in the Columbia River basin, briefly describes work being done to meet contract requirements for fish disease surveillance at those hatcheries and provides a summary of case history data for calendar years 1984, 1985, 1986 and 1987. 1 ref.

  15. Augmented Fish Health Monitoring, 1987-1988 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Warren, James W.

    1988-08-01

    Augmented Fish Health Monitoring Contract DE-AI79-87BP35585 was implemented on July 20, 1987. First year highlights included remodeling of the Olympia (WA) Fish Health Center to provide laboratory space for histopathological support services to participating state agencies, acquisition of gas monitoring equipment for hatchery water systems, expanded disease detection work for bacterial kidney disease and erythrocytic inclusion body syndrome in fish stocks at 13 Columbia River Basin National Fish Hatcheries and advancements in computerized case history data storage and analysis. This report summarizes the health status of fish reared at Service facilities in the Columbia River basin, briefly describes work being done to meet contract requirements for fish disease surveillance at those hatcheries and provides a summary of case history data for calendar years 1984, 1985, 1986 and 1987. 1 ref.

  16. A Battery Health Monitoring Framework for Planetary Rovers

    Science.gov (United States)

    Daigle, Matthew J.; Kulkarni, Chetan Shrikant

    2014-01-01

    Batteries have seen an increased use in electric ground and air vehicles for commercial, military, and space applications as the primary energy source. An important aspect of using batteries in such contexts is battery health monitoring. Batteries must be carefully monitored such that the battery health can be determined, and end of discharge and end of usable life events may be accurately predicted. For planetary rovers, battery health estimation and prediction is critical to mission planning and decision-making. We develop a model-based approach utilizing computaitonally efficient and accurate electrochemistry models of batteries. An unscented Kalman filter yields state estimates, which are then used to predict the future behavior of the batteries and, specifically, end of discharge. The prediction algorithm accounts for possible future power demands on the rover batteries in order to provide meaningful results and an accurate representation of prediction uncertainty. The framework is demonstrated on a set of lithium-ion batteries powering a rover at NASA.

  17. Development of on the machine process monitoring and control strategy in Robot Assisted Polishing

    DEFF Research Database (Denmark)

    Pilny, Lukas; Bissacco, Giuliano

    2015-01-01

    Robot Assisted Polishing (RAP) can be used to polish rotational symmetric and free form components achieving surface roughness down to Sa 10 nm. With the aim to enable unmanned robust and cost efficient application of RAP, this paper presents the development of a monitoring and control strategy f...

  18. Wastewater quality monitoring system using sensor fusion and machine learning techniques.

    Science.gov (United States)

    Qin, Xusong; Gao, Furong; Chen, Guohua

    2012-03-15

    A multi-sensor water quality monitoring system incorporating an UV/Vis spectrometer and a turbidimeter was used to monitor the Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and Oil & Grease (O&G) concentrations of the effluents from the Chinese restaurant on campus and an electrocoagulation-electroflotation (EC-EF) pilot plant. In order to handle the noise and information unbalance in the fused UV/Vis spectra and turbidity measurements during the calibration model building, an improved boosting method, Boosting-Iterative Predictor Weighting-Partial Least Squares (Boosting-IPW-PLS), was developed in the present study. The Boosting-IPW-PLS method incorporates IPW into boosting scheme to suppress the quality-irrelevant variables by assigning small weights, and builds up the models for the wastewater quality predictions based on the weighted variables. The monitoring system was tested in the field with satisfactory results, underlying the potential of this technique for the online monitoring of water quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

  19. A motivational health companion in the home as part of an intelligent health monitoring sensor network

    NARCIS (Netherlands)

    Evers, V.; Wildvuur, S.; Kröse, B.

    2010-01-01

    This paper describes our work in progress to develop a personal monitoring system that can monitor the physical and emotional condition of a patient by using contextual information from a sensor network, provide the patient with feedback concerning their health status and motivate the patient to ado

  20. Putting Man in the Machine: Exploiting Expertise to Enhance Multiobjective Design of Water Supply Monitoring Network

    Science.gov (United States)

    Bode, F.; Nowak, W.; Reed, P. M.; Reuschen, S.

    2016-12-01

    Drinking-water well catchments need effective early-warning monitoring networks. Groundwater water supply wells in complex urban environments are in close proximity to a myriad of potential industrial pollutant sources that could irreversibly damage their source aquifers. These urban environments pose fiscal and physical challenges to designing monitoring networks. Ideal early-warning monitoring networks would satisfy three objectives: to detect (1) all potential contaminations within the catchment (2) as early as possible before they reach the pumping wells, (3) while minimizing costs. Obviously, the ideal case is nonexistent, so we search for tradeoffs using multiobjective optimization. The challenge of this optimization problem is the high number of potential monitoring-well positions (the search space) and the non-linearity of the underlying groundwater flow-and-transport problem. This study evaluates (1) different ways to effectively restrict the search space in an efficient way, with and without expert knowledge, (2) different methods to represent the search space during the optimization and (3) the influence of incremental increases in uncertainty in the system. Conductivity, regional flow direction and potential source locations are explored as key uncertainties. We show the need and the benefit of our methods by comparing optimized monitoring networks for different uncertainty levels with networks that seek to effectively exploit expert knowledge. The study's main contributions are the different approaches restricting and representing the search space. The restriction algorithms are based on a point-wise comparison of decision elements of the search space. The representation of the search space can be either binary or continuous. For both cases, the search space must be adjusted properly. Our results show the benefits and drawbacks of binary versus continuous search space representations and the high potential of automated search space restriction

  1. GIS Mapping and Monitoring of Health Problems Among the Elderly.

    Science.gov (United States)

    Dermatis, Zacharias; Tsaloukidis, Nikolaos; Zacharopoulou, Georgia; Lazakidou, Athina

    2017-01-01

    The electronic survey in conjunction with GIS in the current study aims at presenting the needs and health problems of the elderly in individual Open Elderly Care Centres in Greece. The online GIS survey enables the continuous monitoring and developing of the health problems of the elderly and helps them in their early care by the healthcare units. GIS survey123 is a customizable tool, which can be used to conduct research that is then published on an Android, iOS, and web platform. The ArcGIS software was used for the geographic mapping of data collected from a wide range of sources, so that health care professionals can investigate the factors associated with the onset of the diseases. Also, direct geographic mapping aims at identifying health problems of the elderly in Greece and transferring information to health care professionals in order to impose proper control measures in a very small period of time.

  2. Acronym Disambiguation in Spanish Electronic Health Narratives Using Machine Learning Techniques.

    Science.gov (United States)

    Rubio-López, Ignacio; Costumero, Roberto; Ambit, Héctor; Gonzalo-Martín, Consuelo; Menasalvas, Ernestina; Rodríguez González, Alejandro

    2017-01-01

    Electronic Health Records (EHRs) are now being massively used in hospitals what has motivated current developments of new methods to process clinical narratives (unstructured data) making it possible to perform context-based searches. Current approaches to process the unstructured texts in EHRs are based in applying text mining or natural language processing (NLP) techniques over the data. In particular Named Entity Recognition (NER) is of paramount importance to retrieve specific biomedical concepts from the text providing the semantic type of the concept retrieved. However, it is very common that clinical notes contain lots of acronyms that cannot be identified by NER processes and even if they are identified, an acronym may correspond to several meanings, so disambiguation of the found term is needed. In this work we provide an approach to perform acronym disambiguation in Spanish EHR using machine learning techniques.

  3. Challenges in Data Quality Assurance in Pervasive Health Monitoring Systems

    Science.gov (United States)

    Sriram, Janani; Shin, Minho; Kotz, David; Rajan, Anand; Sastry, Manoj; Yarvis, Mark

    Wearable, portable, and implantable medical sensors have ushered in a new paradigm for healthcare in which patients can take greater responsibility and caregivers can make well-informed, timely decisions. Health-monitoring systems built on such sensors have huge potential benefit to the quality of healthcare and quality of life for many people, such as patients with chronic medical conditions (such as blood-sugar sensors for diabetics), people seeking to change unhealthy behavior (such as losing weight or quitting smoking), or athletes wishing to monitor their condition and performance. To be effective, however, these systems must provide assurances about the quality of the sensor data. The sensors must be applied to the patient by a human, and the sensor data may be transported across multiple networks and devices before it is presented to the medical team. While no system can guarantee data quality, we anticipate that it will help for the system to annotate data with some measure of confidence. In this paper, we take a deeper look at potential health-monitoring usage scenarios and highlight research challenges required to ensure and assess quality of sensor data in health-monitoring systems.

  4. Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multi-signal Vital Sign Monitoring Data

    Science.gov (United States)

    Chen, Lujie; Dubrawski, Artur; Wang, Donghan; Fiterau, Madalina; Guillame-Bert, Mathieu; Bose, Eliezer; Kaynar, Ata M.; Wallace, David J.; Guttendorf, Jane; Clermont, Gilles; Pinsky, Michael R.; Hravnak, Marilyn

    2015-01-01

    OBJECTIVE Use machine-learning (ML) algorithms to classify alerts as real or artifacts in online noninvasive vital sign (VS) data streams to reduce alarm fatigue and missed true instability. METHODS Using a 24-bed trauma step-down unit’s non-invasive VS monitoring data (heart rate [HR], respiratory rate [RR], peripheral oximetry [SpO2]) recorded at 1/20Hz, and noninvasive oscillometric blood pressure [BP] less frequently, we partitioned data into training/validation (294 admissions; 22,980 monitoring hours) and test sets (2,057 admissions; 156,177 monitoring hours). Alerts were VS deviations beyond stability thresholds. A four-member expert committee annotated a subset of alerts (576 in training/validation set, 397 in test set) as real or artifact selected by active learning, upon which we trained ML algorithms. The best model was evaluated on alerts in the test set to enact online alert classification as signals evolve over time. MAIN RESULTS The Random Forest model discriminated between real and artifact as the alerts evolved online in the test set with area under the curve (AUC) performance of 0.79 (95% CI 0.67-0.93) for SpO2 at the instant the VS first crossed threshold and increased to 0.87 (95% CI 0.71-0.95) at 3 minutes into the alerting period. BP AUC started at 0.77 (95%CI 0.64-0.95) and increased to 0.87 (95% CI 0.71-0.98), while RR AUC started at 0.85 (95%CI 0.77-0.95) and increased to 0.97 (95% CI 0.94–1.00). HR alerts were too few for model development. CONCLUSIONS ML models can discern clinically relevant SpO2, BP and RR alerts from artifacts in an online monitoring dataset (AUC>0.87). PMID:26992068

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

    Directory of Open Access Journals (Sweden)

    Ion Stiharu

    2010-08-01

    Full Text Available 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.

  6. FBG sensor for physiologic monitoring in M-health application

    Science.gov (United States)

    Lee, Chi Chung; Hung, Kevin; Chan, Wai-Man; Wu, Y. K.; Choy, Sheung-On; Kwok, Paul

    2011-12-01

    In this paper, a wearable physiologic monitoring system using FBG sensors is investigated. The FBG sensors with the capability of sensing temperature, movement, and respiration are connected to the wireless transceiver, microcontroller and server for wireless and long distance physiologic monitoring and analysis. Biosignals recorded experimentally are analyzed and compared with the data obtained in the traditional medical data acquisition system. The system investigated in this paper can be used in an m-health shirt, which has the capability to measure and wirelessly transmit electrocardiogram, respiration, movement, and body temperature signal to a remote station, with other plug-in modules.

  7. Printed strain sensor array for application to structural health monitoring

    Science.gov (United States)

    Zymelka, Daniel; Togashi, Kazuyoshi; Ohigashi, Ryoichi; Yamashita, Takahiro; Takamatsu, Seiichi; Itoh, Toshihiro; Kobayashi, Takeshi

    2017-10-01

    We demonstrate the development and practical use of low-cost printed strain sensor arrays built for applications in structural health monitoring. Sensors embedded in the array were designed to provide compensation for temperature variations and to enable their use in different seasons. The evaluation was carried out in laboratory tests and with practical application on a highway bridge. Measurements on the bridge were performed 7 months and 1 year after their installation. The developed devices were fully operational and could detect and localize cracks accurately in the monitored bridge structure.

  8. Oscillometric continuous blood pressure sensing for wearable health monitoring system

    CERN Document Server

    Gelao, Gennaro; Passaro, Vittorio M N; Perri, Anna Gina

    2015-01-01

    In this paper we present an acquisition chain for the measurement of blood arterial pressure based on the oscillometric method. This method does not suffer from any limitation as the well-known auscultatory method and it is suited for wearable health monitoring systems. The device uses a pressure sensor whose signal is filtered, digitalized and analyzed by a microcontroller. Local analysis allows the evaluation of the systolic and diastolic pressure values which can be used for local alarms, data collection and remote monitoring.

  9. Commonality and Variability Analysis for Xenon Family of Separation Virtual Machine Monitors (CVAX)

    Science.gov (United States)

    2017-07-18

    AMD X86 c. ARM v9. The Visual Management Interface ( VMI ) provided by x can differ. Some possibilities are: a. x provides a security management... VMI that allows security administrator to author security policy, manage network security and connectivity, and monitor VM resource consumption. b...The x security management VMI provides default security policy and templates with example configurations. c. There is no VMI ; the x security policy

  10. PRISM: A DATA-DRIVEN PLATFORM FOR MONITORING MENTAL HEALTH.

    Science.gov (United States)

    Kamdar, Maulik R; Wu, Michelle J

    2016-01-01

    Neuropsychiatric disorders are the leading cause of disability worldwide and there is no gold standard currently available for the measurement of mental health. This issue is exacerbated by the fact that the information physicians use to diagnose these disorders is episodic and often subjective. Current methods to monitor mental health involve the use of subjective DSM-5 guidelines, and advances in EEG and video monitoring technologies have not been widely adopted due to invasiveness and inconvenience. Wearable technologies have surfaced as a ubiquitous and unobtrusive method for providing continuous, quantitative data about a patient. Here, we introduce PRISM-Passive, Real-time Information for Sensing Mental Health. This platform integrates motion, light and heart rate data from a smart watch application with user interactions and text entries from a web application. We have demonstrated a proof of concept by collecting preliminary data through a pilot study of 13 subjects. We have engineered appropriate features and applied both unsupervised and supervised learning to develop models that are predictive of user-reported ratings of their emotional state, demonstrating that the data has the potential to be useful for evaluating mental health. This platform could allow patients and clinicians to leverage continuous streams of passive data for early and accurate diagnosis as well as constant monitoring of patients suffering from mental disorders.

  11. Development of structural health monitoring techniques using dynamics testing

    Energy Technology Data Exchange (ETDEWEB)

    James, G.H. III [Sandia National Labs., Albuquerque, NM (United States). Experimental Structural Dynamics Dept.

    1996-03-01

    Today`s society depends upon many structures (such as aircraft, bridges, wind turbines, offshore platforms, buildings, and nuclear weapons) which are nearing the end of their design lifetime. Since these structures cannot be economically replaced, techniques for structural health monitoring must be developed and implemented. Modal and structural dynamics measurements hold promise for the global non-destructive inspection of a variety of structures since surface measurements of a vibrating structure can provide information about the health of the internal members without costly (or impossible) dismantling of the structure. In order to develop structural health monitoring for application to operational structures, developments in four areas have been undertaken within this project: operational evaluation, diagnostic measurements, information condensation, and damage identification. The developments in each of these four aspects of structural health monitoring have been exercised on a broad range of experimental data. This experimental data has been extracted from structures from several application areas which include aging aircraft, wind energy, aging bridges, offshore structures, structural supports, and mechanical parts. As a result of these advances, Sandia National Laboratories is in a position to perform further advanced development, operational implementation, and technical consulting for a broad class of the nation`s aging infrastructure problems.

  12. Computer aided diagnosis for mental health care : On the clinical validation of sensitive machines

    NARCIS (Netherlands)

    Sluis, F. van der; Dijkstra, T.; Broek, E.L. van den

    2012-01-01

    This study explores the feasibility of sensitive machines; that is, machines with empathic abilities, at least to some extent. A signal processing and machine learning pipeline is presented that is used to analyze data from two studies in which 25 Post-Traumatic Stress Disorder (PTSD) patients parti

  13. Computer aided diagnosis for mental health care : On the clinical validation of sensitive machines

    NARCIS (Netherlands)

    Sluis, F. van der; Dijkstra, T.; Broek, E.L. van den

    2012-01-01

    This study explores the feasibility of sensitive machines; that is, machines with empathic abilities, at least to some extent. A signal processing and machine learning pipeline is presented that is used to analyze data from two studies in which 25 Post-Traumatic Stress Disorder (PTSD) patients

  14. Computer aided diagnosis for mental health care : On the clinical validation of sensitive machines

    NARCIS (Netherlands)

    Sluis, F. van der; Dijkstra, T.; Broek, E.L. van den

    2012-01-01

    This study explores the feasibility of sensitive machines; that is, machines with empathic abilities, at least to some extent. A signal processing and machine learning pipeline is presented that is used to analyze data from two studies in which 25 Post-Traumatic Stress Disorder (PTSD) patients parti

  15. Mobile health-monitoring system through visible light communication.

    Science.gov (United States)

    Tan, Yee-Yong; Chung, Wan-Young

    2014-01-01

    Promising development in the light emitting diode (LED) technology has spurred the interest to adapt LED for both illumination and data transmission. This has fostered the growth of interest in visible light communication (VLC), with on-going research to utilize VLC in various applications. This paper presents a mobile-health monitoring system, where healthcare information such as biomedical signals and patient information are transmitted via the LED lighting. A small and portable receiver module is designed and developed to be attached to the mobile device, providing a seamless monitoring environment. Three different healthcare information including ECG, PPG signals and HL7 text information is transmitted simultaneously, using a single channel VLC. This allows for a more precise and accurate monitoring and diagnosis. The data packet size is carefully designed, to transmit information in a minimal packet error rate. A comprehensive monitoring application is designed and developed through the use of a tablet computer in our study. Monitoring and evaluation such as heart rate and arterial blood pressure measurement can be performed concurrently. Real-time monitoring is demonstrated through experiment, where non-hazardous transmission method can be implemented alongside a portable device for better and safer healthcare service.

  16. 78 FR 58268 - Notice of Request for Approval of an Information Collection; National Animal Health Monitoring...

    Science.gov (United States)

    2013-09-23

    ...; National Animal Health Monitoring System; Cervid 2014 Study AGENCY: Animal and Plant Health Inspection... intention to request approval of a new information collection for the National Animal Health Monitoring...: National Animal Health Monitoring System; Cervid 2014 Study. OMB Number: 0579-XXXX. Type of...

  17. 78 FR 58269 - Notice of Request for Approval of an Information Collection; National Animal Health Monitoring...

    Science.gov (United States)

    2013-09-23

    ...; National Animal Health Monitoring System; Bison 2014 Study AGENCY: Animal and Plant Health Inspection... intention to request approval of a new information collection for the National Animal Health Monitoring...: National Animal Health Monitoring System; Bison 2014 Study. OMB Number: 0579-XXXX. Type of...

  18. Design of Online Monitoring and Fault Diagnosis System for Belt Conveyors Based on Wavelet Packet Decomposition and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Wei Li

    2013-01-01

    Full Text Available Belt conveyors are the equipment widely used in coal mines and other manufacturing factories, whose main components are a number of idlers. The faults of belt conveyors can directly influence the daily production. In this paper, a fault diagnosis method combining wavelet packet decomposition (WPD and support vector machine (SVM is proposed for monitoring belt conveyors with the focus on the detection of idler faults. Since the number of the idlers could be large, one acceleration sensor is applied to gather the vibration signals of several idlers in order to reduce the number of sensors. The vibration signals are decomposed with WPD, and the energy of each frequency band is extracted as the feature. Then, the features are employed to train an SVM to realize the detection of idler faults. The proposed fault diagnosis method is firstly tested on a testbed, and then an online monitoring and fault diagnosis system is designed for belt conveyors. An experiment is also carried out on a belt conveyor in service, and it is verified that the proposed system can locate the position of the faulty idlers with a limited number of sensors, which is important for operating belt conveyors in practices.

  19. Machine Learning

    CERN Document Server

    CERN. Geneva

    2017-01-01

    Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

  20. Optimized Radar Remote Sensing for Levee Health Monitoring

    Science.gov (United States)

    Jones, Cathleen E.

    2013-01-01

    Radar remote sensing offers great potential for high resolution monitoring of ground surface changes over large areas at one time to detect movement on and near levees and for location of seepage through levees. Our NASA-funded projects to monitor levees in the Sacramento Delta and the Mississippi River have developed and demonstrated methods to use radar remote sensing to measure quantities relevant to levee health and of great value to emergency response. The DHS-funded project will enable us is to define how to optimally monitor levees in this new way and set the stage for transition to using satellite SAR (synthetic aperture radar) imaging for better temporal and spatial coverage at lower cost to the end users.

  1. Ubiquitous Mobile Health Monitoring System for Elderly (UMHMSE)

    CERN Document Server

    Bourouis, Abderrahim; Bouchachia, Abdelhamid

    2011-01-01

    Recent research in ubiquitous computing uses technologies of Body Area Networks (BANs) to monitor the person's kinematics and physiological parameters. In this paper we propose a real time mobile health system for monitoring elderly patients from indoor or outdoor environments. The system uses a bio- signal sensor worn by the patient and a Smartphone as a central node. The sensor data is collected and transmitted to the intelligent server through GPRS/UMTS to be analyzed. The prototype (UMHMSE) monitors the elderly mobility, location and vital signs such as Sp02 and Heart Rate. Remote users (family and medical personnel) might have a real time access to the collected information through a web application.

  2. UBIQUITOUS MOBILE HEALTH MONITORING SYSTEM FOR ELDERLY (UMHMSE

    Directory of Open Access Journals (Sweden)

    Abderrahim BOUROUIS

    2011-06-01

    Full Text Available Recent research in ubiquitous computing uses technologies of Body Area Networks (BANs to monitor the person's kinematics and physiological parameters. In this paper we propose a real time mobile health system for monitoring elderly patients from indoor or outdoor environments. The system uses a biosignal sensor worn by the patient and a Smartphone as a central node. The sensor data is collected and transmitted to the intelligent server through GPRS/UMTS to be analyzed. The prototype (UMHMSE monitors the elderly mobility, location and vital signs such as Sp02 and Heart Rate. Remote users (family and medical personnel might have a real time access to the collected information through a web application.

  3. Patient Health Monitoring Using Wireless Body Area Network

    Directory of Open Access Journals (Sweden)

    Hsu Myat Thwe

    2015-06-01

    Full Text Available Abstract Nowadays remote patient health monitoring using wireless technology plays very vigorous role in a society. Wireless technology helps monitoring of physiological parameters like body temperature heart rate respiration blood pressure and ECG. The main aim of this paper is to propose a wireless sensor network system in which both heart rate and body temperature ofmultiplepatients can monitor on PC at the same time via RF network. The proposed prototype system includes two sensor nodes and receiver node base station. The sensor nodes are able to transmit data to receiver using wireless nRF transceiver module.The nRF transceiver module is used to transfer the data from microcontroller to PC and a graphical user interface GUI is developed to display the measured data and save to database. This system can provide very cheaper easier and quick respondent history of patient.

  4. Investigation of Wireless Sensor Networks for Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Ping Wang

    2012-01-01

    Full Text Available Wireless sensor networks (WSNs are one of the most able technologies in the structural health monitoring (SHM field. Through intelligent, self-organising means, the contents of this paper will test a variety of different objects and different working principles of sensor nodes connected into a network and integrated with data processing functions. In this paper the key issues of WSN applied in SHM are discussed, including the integration of different types of sensors with different operational modalities, sampling frequencies, issues of transmission bandwidth, real-time ability, and wireless transmitter frequency. Furthermore, the topology, data fusion, integration, energy saving, and self-powering nature of different systems will be investigated. In the FP7 project “Health Monitoring of Offshore Wind Farms,” the above issues are explored.

  5. TPS In-Flight Health Monitoring Project Progress Report

    Science.gov (United States)

    Kostyk, Chris; Richards, Lance; Hudston, Larry; Prosser, William

    2007-01-01

    Progress in the development of new thermal protection systems (TPS) is reported. New approaches use embedded lightweight, sensitive, fiber optic strain and temperature sensors within the TPS. Goals of the program are to develop and demonstrate a prototype TPS health monitoring system, develop a thermal-based damage detection algorithm, characterize limits of sensor/system performance, and develop ea methodology transferable to new designs of TPS health monitoring systems. Tasks completed during the project helped establish confidence in understanding of both test setup and the model and validated system/sensor performance in a simple TPS structure. Other progress included complete initial system testing, commencement of the algorithm development effort, generation of a damaged thermal response characteristics database, initial development of a test plan for integration testing of proven FBG sensors in simple TPS structure, and development of partnerships to apply the technology.

  6. Airborne Transducer Integrity under Operational Environment for Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Mohammad Saleh Salmanpour

    2016-12-01

    Full Text Available This paper investigates the robustness of permanently mounted transducers used in airborne structural health monitoring systems, when exposed to the operational environment. Typical airliners operate in a range of conditions, hence, structural health monitoring (SHM transducer robustness and integrity must be demonstrated for these environments. A set of extreme temperature, altitude and vibration environment test profiles are developed using the existing Radio Technical Commission for Aeronautics (RTCA/DO-160 test methods. Commercially available transducers and manufactured versions bonded to carbon fibre reinforced polymer (CFRP composite materials are tested. It was found that the DuraAct transducer is robust to environmental conditions tested, while the other transducer types degrade under the same conditions.

  7. Thermal sensitivity of Lamb waves for structural health monitoring applications.

    Science.gov (United States)

    Dodson, J C; Inman, D J

    2013-03-01

    One of the drawbacks of the current Lamb wave structural health monitoring methods are the false positives due to changing environmental conditions such as temperature. To create an environmental insensitive damage detection scheme, the physics of thermal effects on Lamb waves must be understood. Dispersion and thermal sensitivity curves for an isotropic plate with thermal stress and thermally varying elastic modulus are presented. The thermal sensitivity of dispersion curves is analytically developed and validated by experimental measurements. The group velocity thermal sensitivity highlights temperature insensitive features at two critical frequencies. The thermal sensitivity gives us insight to how temperature affects Lamb wave speeds in different frequency ranges and will help those developing structural health monitoring algorithms.

  8. Signature Optical Cues: Emerging Technologies for Monitoring Plant Health

    Directory of Open Access Journals (Sweden)

    Anand K. Asundi

    2008-05-01

    Full Text Available Optical technologies can be developed as practical tools for monitoring plant health by providing unique spectral signatures that can be related to specific plant stresses. Signatures from thermal and fluorescence imaging have been used successfully to track pathogen invasion before visual symptoms are observed. Another approach for noninvasive plant health monitoring involves elucidating the manner with which light interacts with the plant leaf and being able to identify changes in spectral characteristics in response to specific stresses. To achieve this, an important step is to understand the biochemical and anatomical features governing leaf reflectance, transmission and absorption. Many studies have opened up possibilities that subtle changes in leaf reflectance spectra can be analyzed in a plethora of ways for discriminating nutrient and water stress, but with limited success. There has also been interest in developing transgenic phytosensors to elucidate plant status in relation to environmental conditions. This approach involves unambiguous signal creation whereby genetic modification to generate reporter plants has resulted in distinct optical signals emitted in response to specific stressors. Most of these studies are limited to laboratory or controlled greenhouse environments at leaf level. The practical translation of spectral cues for application under field conditions at canopy and regional levels by remote aerial sensing remains a challenge. The movement towards technology development is well exemplified by the Controlled Ecological Life Support System under development by NASA which brings together technologies for monitoring plant status concomitantly with instrumentation for environmental monitoring and feedback control.

  9. Health Monitoring of TPS Structures by Measuring Their Electrical Resistance

    Science.gov (United States)

    Preci, Arianit; Herdrich, Georg; Steinbeck, Andreas; Auweter-Kurtz, Monika

    Health Monitoring in aerospace applications becomes an emerging technology leading to the development of systems capable of continuously monitoring structures for damage with minimal human intervention. A promising sensing method to be applied on hot structures and thermal protection systems is the electrical resistance measurement technique, which is barely investigated up to now. This method benefits from the advantageous characteristics of self-monitoring materials, such as carbon fiber-reinforced materials. By measuring the variation of the electrical resistance of these materials information on possibly present mechanical damage can be derived. In order to set up a database on electric properties of relevant materials under relevant conditions and to perform a proof-of-concept for this health monitoring method a facility has been laid out, which allows for the measurement of the electrical resistance of thermal protection system relevant materials at temperatures up to 2000°C. First preliminary measurements of the surface resistance of a graphite sample have been performed and are presented. It has been proven necessary to make some modifications to the setup. Therefore, the remaining measurements with graphite and C/C-SiC samples are subject of further investigation which will be performed in the future.

  10. Monitoring Indoor Air Quality for Enhanced Occupational Health.

    Science.gov (United States)

    Pitarma, Rui; Marques, Gonçalo; Ferreira, Bárbara Roque

    2017-02-01

    Indoor environments are characterized by several pollutant sources. Because people spend more than 90% of their time in indoor environments, several studies have pointed out the impact of indoor air quality on the etiopathogenesis of a wide number of non-specific symptoms which characterizes the "Sick Building Syndrome", involving the skin, the upper and lower respiratory tract, the eyes and the nervous system, as well as many building related diseases. Thus, indoor air quality (IAQ) is recognized as an important factor to be controlled for the occupants' health and comfort. The majority of the monitoring systems presently available is very expensive and only allow to collect random samples. This work describes the system (iAQ), a low-cost indoor air quality monitoring wireless sensor network system, developed using Arduino, XBee modules and micro sensors, for storage and availability of monitoring data on a web portal in real time. Five micro sensors of environmental parameters (air temperature, humidity, carbon monoxide, carbon dioxide and luminosity) were used. Other sensors can be added for monitoring specific pollutants. The results reveal that the system can provide an effective indoor air quality assessment to prevent exposure risk. In fact, the indoor air quality may be extremely different compared to what is expected for a quality living environment. Systems like this would have benefit as public health interventions to reduce the burden of symptoms and diseases related to "sick buildings".

  11. Health monitoring of composite structures throughout the life cycle

    Science.gov (United States)

    Chilles, James; Croxford, Anthony; Bond, Ian

    2016-04-01

    This study demonstrates the capability of inductively coupled piezoelectric sensors to monitor the state of health throughout the lifetime of composite structures. A single sensor which generated guided elastic waves was embedded into the stacking sequence of a large glass fiber reinforced plastic plate. The progress of cure was monitored by measuring variations in the amplitude and velocity of the waveforms reflected from the plate's edges. Baseline subtraction techniques were then implemented to detect barely visible impact damage (BVID) created by a 10 Joule impact, at a distance of 350 mm from the sensor embedded in the cured plate. To investigate the influence of mechanical loading on sensor performance, a single sensor was embedded within a glass fiber panel and subjected to tensile load. The panel was loaded up to a maximum strain of 1%, in increments of 0.1% strain. Guided wave measurements were recorded by the embedded sensor before testing, when the panel was under load, and after testing. The ultrasonic measurements showed a strong dependence on the applied load. Upon removal of the mechanical load the guided wave measurements returned to their original values recorded before testing. The results in this work show that embedded piezoelectric sensors can be used to monitor the state of health throughout the life-cycle of composite parts, even when subjected to relatively large strains. However the influence of load on guided wave measurements has implications for online monitoring using embedded piezoelectric transducers.

  12. Structural health monitoring of bridges in the State of Connecticut

    Institute of Scientific and Technical Information of China (English)

    Chengyin Liu; Joshua Olund; Alan Cardini; Paul D'Attilio; Erie Feldblum; John DeWolf

    2008-01-01

    A joint effort between the Connecticut Department of Transportation and the University of Connecticut has been underway for more than 20 years to utilize various structural monitoring approaches to assess different bridges in Connecticut.This has been done to determine the performance of existing bridges,refine techniques needed to evaluate different bridge components,and develop approaches that can be used to provide a continuous status of a bridge's structural integrity,This paper briefly introduces the background of these studies,with emphasis on recent research and the development of structural health monitoring concepts.This paper presents the results from three different bridge types:a post-tensioned curved concrete box girder bridge,a curved steel box-girder bridge,and a steel multi-girder bridge.The structural health monitoring approaches to be discussed have been successfully tested using field data collected during multi-year monitoring periods,and are based on vibrations,rotations and strains.The goal has been to develop cost-effective strategies to provide critical information needed to manage the State of Connecticut's bridge infrastructure.

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

    Science.gov (United States)

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

    2015-02-28

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

  14. The environment, international standards, asset health management and condition monitoring: An integrated strategy

    Energy Technology Data Exchange (ETDEWEB)

    Roe, S. [CSD, British Institute of Non-Destructive Testing (BINDT) (United Kingdom); Mba, D. [School of Engineering, Cranfield University, MK43 0AL, Bedfordshire (United Kingdom)], E-mail: d.mba@cranfield.ac.uk

    2009-02-15

    Asset Health Management (AHM), supported by condition monitoring (CM) and performance measuring technologies, together with trending, modelling and diagnostic frameworks, is not only critical to the reliability of high-value machines, but also to a companies Overall Equipment Efficiency (OEE), system safety and profitability. In addition these protocols are also critical to the global concern of the environment. Industries involved with monitoring key performances indicators (KPI) to improve OEE would benefit from a standardised qualification and certification scheme for their personnel, particularly if it is based on internationally accepted procedures for the various CM technologies that also share the same objectives as AH and CM. Furthermore, the development of 'models' for implementation of a Carbon tax is intrinsically dependent on the integrity and accuracy of measurements contributing to these indicators. This paper reviews the global picture of condition monitoring, the environment and related international standards and then considers their relationship and equivalent global objectives. In addition, it presents the methods behind the development of such standards for certification of competence in personnel involved with data collection, modelling and measurements of KPIs. Two case studies are presented that highlight the integrated strategy in practise.

  15. CFRP Structural Health Monitoring by Ultrasonic Phased Array Technique

    OpenAIRE

    Boychuk, A.S.; Generalov, A.S.; A.V. Stepanov

    2014-01-01

    International audience; The report deals with ultrasonic phased array (PA) application for high-loaded CFRP structural health monitoring in aviation. Principles of phased array technique and most dangerous types of damages are briefly described. High-performance inspection technology suitable for periodic plane structure check is suggested. The results of numerical estimation of detection probability for impact damages and delaminations by PA technique are presented. The experience of PA impl...

  16. Statistical Process Control Charts for Public Health Monitoring

    Science.gov (United States)

    2014-12-01

    Poisson counts) [21-23].  Cumulative sum ( CUSUM ) and exponentially weighted moving average (EWMA) control charts are often used with Phase II data. These...charts have been shown to more quickly detect small changes than traditional Shewhart charts. There have been several applications of CUSUM charts in...distribution, a CUSUM or EWMA chart would be required.  Risk adjustment for health data has been applied when monitoring variables that can be

  17. Bayesian Computational Sensor Networks for Aircraft Structural Health Monitoring

    Science.gov (United States)

    2016-02-02

    emissions as well as delamination-dominated and fiber-dominated damage. The three frequency regions identified were 10 - 100 kHz, 100 - 250 kHz, and 250...the RD patterns can be used for Bayesian model accuracy assessment of the difference between a uniform grid layout of the nodes versus an irregular... grid due to error in node placement. SLAMBOT: Structural Health Monitoring Robot using Lamb Waves We developed the combination of a mobile robot and

  18. On Structural Health Monitoring of Wind Turbine Blades

    DEFF Research Database (Denmark)

    Skov, Jonas falk; Ulriksen, Martin Dalgaard; Dickow, Kristoffer Ahrens

    2013-01-01

    The aim of the present paper is to provide a state-of-the-art outline of structural health monitoring (SHM) techniques, utilizing temperature, noise and vibration, for wind turbine blades, and subsequently perform a typology on the basis of the typical four damage identification levels in SHM....... Before presenting the state-of-the-art outline, descriptions of structural damages typically occurring in wind turbine blades are provided along with a brief description of the four damage identification levels....

  19. Remote health monitoring: predicting outcome success based on contextual features for cardiovascular disease.

    Science.gov (United States)

    Alshurafa, Nabil; Eastwood, Jo-Ann; Pourhomayoun, Mohammad; Liu, Jason J; Sarrafzadeh, Majid

    2014-01-01

    Current studies have produced a plethora of remote health monitoring (RHM) systems designed to enhance the care of patients with chronic diseases. Many RHM systems are designed to improve patient risk factors for cardiovascular disease, including physiological parameters such as body mass index (BMI) and waist circumference, and lipid profiles such as low density lipoprotein (LDL) and high density lipoprotein (HDL). There are several patient characteristics that could be determining factors for a patient's RHM outcome success, but these characteristics have been largely unidentified. In this paper, we analyze results from an RHM system deployed in a six month Women's Heart Health study of 90 patients, and apply advanced feature selection and machine learning algorithms to identify patients' key baseline contextual features and build effective prediction models that help determine RHM outcome success. We introduce Wanda-CVD, a smartphone-based RHM system designed to help participants with cardiovascular disease risk factors by motivating participants through wireless coaching using feedback and prompts as social support. We analyze key contextual features that secure positive patient outcomes in both physiological parameters and lipid profiles. Results from the Women's Heart Health study show that health threat of heart disease, quality of life, family history, stress factors, social support, and anxiety at baseline all help predict patient RHM outcome success.

  20. New applications of biological monitoring for environmental exposure and susceptibility monitoring. Report of the 7th International Symposium on Biological Monitoring in Occupational and Environmental Health.

    NARCIS (Netherlands)

    Scheepers, P.T.J.; Heussen, G.A.

    2008-01-01

    Validated biological monitoring methods are used in large-scale monitoring programmes involving determination of ubiquitous environmental pollutants such as metals and pesticides. Some programmes focus on children's exposure, and policies to prevent adverse health effects. Most of these initiatives

  1. New applications of biological monitoring for environmental exposure and susceptibility monitoring. Report of the 7th International Symposium on Biological Monitoring in Occupational and Environmental Health.

    NARCIS (Netherlands)

    Scheepers, P.T.J.; Heussen, G.A.

    2008-01-01

    Validated biological monitoring methods are used in large-scale monitoring programmes involving determination of ubiquitous environmental pollutants such as metals and pesticides. Some programmes focus on children's exposure, and policies to prevent adverse health effects. Most of these initiatives

  2. Monitoring of health care personnel employee and occupational health immunization program practices in the United States.

    Science.gov (United States)

    Carrico, Ruth M; Sorrells, Nikka; Westhusing, Kelly; Wiemken, Timothy

    2014-01-01

    Recent studies have identified concerns with various elements of health care personnel immunization programs, including the handling and management of the vaccine. The purpose of this study was to assess monitoring processes that support evaluation of the care of vaccines in health care settings. An 11-question survey instrument was developed for use in scripted telephone surveys. State health departments in all 50 states in the United States and the District of Columbia were the target audience for the surveys. Data from a total of 47 states were obtained and analyzed. No states reported an existing monitoring process for evaluation of health care personnel immunization programs in their states. Our assessment indicates that vaccine evaluation processes for health care facilities are rare to nonexistent in the United States. Identifying existing practice gaps and resultant opportunities for improvements may be an important safety initiative that protects patients and health care personnel.

  3. Robust evaluation of time series classification algorithms for structural health monitoring

    Science.gov (United States)

    Harvey, Dustin Y.; Worden, Keith; Todd, Michael D.

    2014-03-01

    Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and mechanical infrastructure through analysis of structural response measurements. The supervised learning methodology for data-driven SHM involves computation of low-dimensional, damage-sensitive features from raw measurement data that are then used in conjunction with machine learning algorithms to detect, classify, and quantify damage states. However, these systems often suffer from performance degradation in real-world applications due to varying operational and environmental conditions. Probabilistic approaches to robust SHM system design suffer from incomplete knowledge of all conditions a system will experience over its lifetime. Info-gap decision theory enables nonprobabilistic evaluation of the robustness of competing models and systems in a variety of decision making applications. Previous work employed info-gap models to handle feature uncertainty when selecting various components of a supervised learning system, namely features from a pre-selected family and classifiers. In this work, the info-gap framework is extended to robust feature design and classifier selection for general time series classification through an efficient, interval arithmetic implementation of an info-gap data model. Experimental results are presented for a damage type classification problem on a ball bearing in a rotating machine. The info-gap framework in conjunction with an evolutionary feature design system allows for fully automated design of a time series classifier to meet performance requirements under maximum allowable uncertainty.

  4. STRUCTURAL HEALTH MONITORING SYSTEM – AN EMBEDDED SENSOR APPROACH

    Directory of Open Access Journals (Sweden)

    Dhivya. A

    2013-02-01

    Full Text Available Structural Health monitoring system is the implementation of improving the maintenance of any structures like buildings and bridges. It encompasses damage detection, identification and prevention of structures from natural disasters like earth quake and rain. This paper is mainly proposed for three modules. First module constitutes recognizing and alerting of abnormal vibration of the building due to an earth quake. This consists of two types of sensor to predict the abnormal vibration induced by an earth quake. Second module portrays the prediction of damage in the buildings after an earth quake or heavy rain. Damage detection includes identification of crack and the moisture content in wall bricks in real time buildings. Third module presents the smart auditorium which is used to reduce the power consumption. Depending on the number of audience inside the auditorium it can control the electric appliances like fans, lights and speakers. In any real time structural health monitoring system the main issue is the time synchronization. This paper also proposes to overcome the general issue arises in structural health monitoring system. ZigBee based reliable communication is used among the client node and server node. For the secured wireless communication between the nodes ZigBee is used.

  5. Smart sensor systems for human health breath monitoring applications.

    Science.gov (United States)

    Hunter, G W; Xu, J C; Biaggi-Labiosa, A M; Laskowski, D; Dutta, P K; Mondal, S P; Ward, B J; Makel, D B; Liu, C C; Chang, C W; Dweik, R A

    2011-09-01

    Breath analysis techniques offer a potential revolution in health care diagnostics, especially if these techniques can be brought into standard use in the clinic and at home. The advent of microsensors combined with smart sensor system technology enables a new generation of sensor systems with significantly enhanced capabilities and minimal size, weight and power consumption. This paper discusses the microsensor/smart sensor system approach and provides a summary of efforts to migrate this technology into human health breath monitoring applications. First, the basic capability of this approach to measure exhaled breath associated with exercise physiology is demonstrated. Building from this foundation, the development of a system for a portable asthma home health care system is described. A solid-state nitric oxide (NO) sensor for asthma monitoring has been identified, and efforts are underway to miniaturize this NO sensor technology and integrate it into a smart sensor system. It is concluded that base platform microsensor technology combined with smart sensor systems can address the needs of a range of breath monitoring applications and enable new capabilities for healthcare.

  6. Design and Analysis of Architectures for Structural Health Monitoring Systems

    Science.gov (United States)

    Mukkamala, Ravi; Sixto, S. L. (Technical Monitor)

    2002-01-01

    During the two-year project period, we have worked on several aspects of Health Usage and Monitoring Systems for structural health monitoring. In particular, we have made contributions in the following areas. 1. Reference HUMS architecture: We developed a high-level architecture for health monitoring and usage systems (HUMS). The proposed reference architecture is shown. It is compatible with the Generic Open Architecture (GOA) proposed as a standard for avionics systems. 2. HUMS kernel: One of the critical layers of HUMS reference architecture is the HUMS kernel. We developed a detailed design of a kernel to implement the high level architecture.3. Prototype implementation of HUMS kernel: We have implemented a preliminary version of the HUMS kernel on a Unix platform.We have implemented both a centralized system version and a distributed version. 4. SCRAMNet and HUMS: SCRAMNet (Shared Common Random Access Memory Network) is a system that is found to be suitable to implement HUMS. For this reason, we have conducted a simulation study to determine its stability in handling the input data rates in HUMS. 5. Architectural specification.

  7. Structural Health Monitoring for a Z-Type Special Vehicle

    Directory of Open Access Journals (Sweden)

    Chaolin Yuan

    2017-06-01

    Full Text Available Nowadays there exist various kinds of special vehicles designed for some purposes, which are different from regular vehicles in overall dimension and design. In that case, accidents such as overturning will lead to large economical loss and casualties. There are still no technical specifications to follow to ensure the safe operation and driving of these special vehicles. Owing to the poor efficiency of regular maintenance, it is more feasible and effective to apply real-time monitoring during the operation and driving process. In this paper, the fiber Bragg grating (FBG sensors are used to monitor the safety of a z-type special vehicle. Based on the structural features and force distribution, a reasonable structural health monitoring (SHM scheme is presented. Comparing the monitoring results with the finite element simulation results guarantees the accuracy and reliability of the monitoring results. Large amounts of data are collected during the operation and driving progress to evaluate the structural safety condition and provide reference for SHM systems developed for other special vehicles.

  8. Analysis and assessment of bridge health monitoring mass data—progress in research/development of "Structural Health Monitoring"

    Institute of Scientific and Technical Information of China (English)

    LI AiQun; DING YouLiang; WANG Hao; GUO Tong

    2012-01-01

    The "Structural Health Monitoring" is a project supported by National Natural Science Foundation for Distinguished Young Scholars of China (Grant No.50725828).To meet the urgent requirements of analysis and assessment of mass monitoring data of bridge environmental actions and structural responses,the monitoring of environmental actions and action effect modeling methods,dynamic performance monitoring and early warning methods,condition assessment and operation maintenance methods of key members are systematically studied in close combination with structural characteristics of long-span cable-stayed bridges and suspension bridges.The paper reports the progress of the project as follows.(1) The environmental action modeling methods of long-span bridges are established based on monitoring data of temperature,sustained wind and typhoon.The action effect modeling methods are further developed in combination with the multi-scale baseline finite element modeling method for long-span bridges.(2) The identification methods of global dynamic characteristics and internal forces of cables and hangers for long-span cable-stayed bridges and suspension bridges are proposed using the vibration monitoring data,on the basis of which the condition monitoring and early warning methods of bridges are developed using the environmental-condition-normalization technique.(3) The analysis methods for fatigue loading effect of welded details of steel box girder,temperature and traffic loading effect of expansion joint are presented based on long-term monitoring data of strain and beam-end displacement,on the basis of which the service performance assessment and remaining life prediction methods are developed.

  9. Condition monitoring of PARR-1 rotating machines by vibration analysis technique

    Directory of Open Access Journals (Sweden)

    Qadir Javed

    2014-01-01

    Full Text Available Vibration analysis is a key tool for preventive maintenance involving the trending and analysis of machinery performance parameters to detect and identify developing problems before failure and extensive damage can occur. A lab-based experimental setup has been established for obtaining fault-free and fault condition data. After this analysis, primary and secondary motor and pump vibration data of the Pakistan Research Reactor-1 were obtained and analyzed. Vibration signatures were acquired in horizontal, vertical, and axial directions. The 48 vibration signatures have been analyzed to assess the operational status of motors and pumps. The vibration spectrum has been recorded for a 2000 Hz frequency span with a 3200 lines resolution. The data collected should be helpful in future Pakistan Research Reactor-1 condition monitoring.

  10. Real-Time Monitoring System and Advanced Characterization Technique for Civil Infrastructure Health Monitoring

    Directory of Open Access Journals (Sweden)

    V. Bennett

    2011-01-01

    Full Text Available Real-time monitoring of civil infrastructure provides valuable information to assess the health and condition of the associated systems. This paper presents the recently developed shape acceleration array (SAA and local system identification (SI technique, which constitute a major step toward long-term effective health monitoring and analysis of soil and soil-structure systems. The SAA is based on triaxial micro-electro-mechanical system (MEMS sensors to measure in situ deformation (angles relative to gravity and dynamic accelerations up to a depth of one hundred meters. This paper provides an assessment of this array's performance for geotechnical instrumentation applications by reviewing the recorded field data from a bridge replacement site and a full-scale levee test facility. The SI technique capitalizes on the abundance of static and dynamic measurements from the SAA. The geotechnical properties and constitutive response of soil contained within a locally instrumented zone are analyzed and identified independently of adjacent soil strata.

  11. Integration of structural health monitoring solutions onto commercial aircraft via the Federal Aviation Administration structural health monitoring research program

    Science.gov (United States)

    Swindell, Paul; Doyle, Jon; Roach, Dennis

    2017-02-01

    The Federal Aviation Administration (FAA) started a research program in structural health monitoring (SHM) in 2011. The program's goal was to understand the technical gaps of implementing SHM on commercial aircraft and the potential effects on FAA regulations and guidance. The program evolved into a demonstration program consisting of a team from Sandia National Labs Airworthiness Assurance NDI Center (AANC), the Boeing Corporation, Delta Air Lines, Structural Monitoring Systems (SMS), Anodyne Electronics Manufacturing Corp (AEM) and the FAA. This paper will discuss the program from the selection of the inspection problem, the SHM system (Comparative Vacuum Monitoring-CVM) that was selected as the inspection solution and the testing completed to provide sufficient data to gain the first approved use of an SHM system for routine maintenance on commercial US aircraft.

  12. Effective coverage: a metric for monitoring Universal Health Coverage.

    Directory of Open Access Journals (Sweden)

    Marie Ng

    2014-09-01

    Full Text Available A major challenge in monitoring universal health coverage (UHC is identifying an indicator that can adequately capture the multiple components underlying the UHC initiative. Effective coverage, which unites individual and intervention characteristics into a single metric, offers a direct and flexible means to measure health system performance at different levels. We view effective coverage as a relevant and actionable metric for tracking progress towards achieving UHC. In this paper, we review the concept of effective coverage and delineate the three components of the metric - need, use, and quality - using several examples. Further, we explain how the metric can be used for monitoring interventions at both local and global levels. We also discuss the ways that current health information systems can support generating estimates of effective coverage. We conclude by recognizing some of the challenges associated with producing estimates of effective coverage. Despite these challenges, effective coverage is a powerful metric that can provide a more nuanced understanding of whether, and how well, a health system is delivering services to its populations.

  13. Wireless Zigbee strain gage sensor system for structural health monitoring

    Science.gov (United States)

    Ide, Hiroshi; Abdi, Frank; Miraj, Rashid; Dang, Chau; Takahashi, Tatsuya; Sauer, Bruce

    2009-05-01

    A compact cell phone size radio frequency (ZigBee) wireless strain measurement sensor system to measure the structural strain deformation was developed. The developed system provides an accurate strain measurement data stream to the Internet for further Diagnostic and Prognostic (DPS) correlation. Existing methods of structural measurement by strain sensors (gauges) do not completely satisfy problems posed by continuous structural health monitoring. The need for efficient health monitoring methods with real-time requirements to bidirectional data flow from sensors and to a commanding device is becoming critical for keeping our daily life safety. The use of full-field strain measurement techniques could reduce costly experimental programs through better understanding of material behavior. Wireless sensor-network technology is a monitoring method that is estimated to grow rapidly providing potential for cost savings over traditional wired sensors. The many of currently available wireless monitoring methods have: the proactive and constant data rate character of the data streams rather than traditional reactive, event-driven data delivery; mostly static node placement on structures with limited number of nodes. Alpha STAR Electronics' wireless sensor network system, ASWN, addresses some of these deficiencies, making the system easier to operate. The ASWN strain measurement system utilizes off-the-shelf sensors, namely strain gauges, with an analog-to-digital converter/amplifier and ZigBee radio chips to keep cost lower. Strain data is captured by the sensor, converted to digital form and delivered to the ZigBee radio chip, which in turn broadcasts the information using wireless protocols to a Personal Data Assistant (PDA) or Laptop/Desktop computers. From here, data is forwarded to remote computers for higher-level analysis and feedback using traditional cellular and satellite communication or the Ethernet infrastructure. This system offers a compact size, lower cost

  14. Inflatable Habitat Health Monitoring: Implementation, Lessons Learned, and Application to Lunar or Martian Habitat Health Monitoring

    Science.gov (United States)

    Rojdev, Kristina; Hong, Todd; Hafermalz, Scott; Hunkins, Robert; Valle, Gerald; Toups, Larry

    2009-01-01

    NASA's exploration mission is to send humans to the Moon and Mars, in which the purpose is to learn how to live and work safely in those harsh environments. A critical aspect of living in an extreme environment is habitation, and within that habitation element there are key systems which monitor the habitation environment to provide a safe and comfortable living and working space for humans. Expandable habitats are one of the options currently being considered due to their potential mass and volume efficiencies. This paper discusses a joint project between the National Science Foundation (NSF), ILC Dover, and NASA in which an expandable habitat was deployed in the extreme environment of Antarctica to better understand the performance and operations over a one-year period. This project was conducted through the Innovative Partnership Program (IPP) where the NSF provided the location at McMurdo Station in Antarctica and support at the location, ILC Dover provided the inflatable habitat, and NASA provided the instrumentation and data system for monitoring the habitat. The outcome of this project provided lessons learned in the implementation of an inflatable habitat and the systems that support that habitat. These lessons learned will be used to improve current habitation capabilities and systems to meet the objectives of exploration missions to the moon and Mars.

  15. Implementation of foetal e-health monitoring system through biotelemetry.

    Science.gov (United States)

    Chourasia, Vijay S; Tiwari, Anil Kumar

    2012-01-01

    Continuous foetal monitoring of physiological signals is of particular importance for early detection of complexities related to the foetus or the mother's health. The available conventional methods of monitoring mostly perform off-line analysis and restrict the mobility of subjects within a hospital or a room. Hence, the aim of this paper is to develop a foetal e-health monitoring system using mobile phones and wireless sensors for providing advanced healthcare services in the home environment. The system is tested by recording the real-time Foetal Phonocardiography (fPCG) signals from 15 subjects with different gestational periods. The performance of the developed system is compared with the existing ultrasound based Doppler shift technique, ensuring an overall accuracy of 98% of the developed system. The developed framework is non-invasive, cost-effective and simple enough to be used in home care application. It offers advanced healthcare facilities even to the pregnant women living in rural areas and avoids their unnecessary visits at the healthcare centres.

  16. Ultrasonic wave-based structural health monitoring embedded instrument

    Energy Technology Data Exchange (ETDEWEB)

    Aranguren, G.; Monje, P. M., E-mail: pedromaria.monje@ehu.es [Electronic Design Group, Faculty of Engineering of Bilbao, University of the Basque Country, Bilbao (Spain); Cokonaj, Valerijan [AERnnova Engineering Solutions Ibérica S.A., Madrid (Spain); Barrera, Eduardo; Ruiz, Mariano [Instrumentation and Applied Acoustic Research Group of the Technical University of Madrid, Madrid (Spain)

    2013-12-15

    Piezoelectric sensors and actuators are the bridge between electronic and mechanical systems in structures. This type of sensor is a key element in the integrity monitoring of aeronautic structures, bridges, pressure vessels, wind turbine blades, and gas pipelines. In this paper, an all-in-one system for Structural Health Monitoring (SHM) based on ultrasonic waves is presented, called Phased Array Monitoring for Enhanced Life Assessment. This integrated instrument is able to generate excitation signals that are sent through piezoelectric actuators, acquire the received signals in the piezoelectric sensors, and carry out signal processing to check the health of structures. To accomplish this task, the instrument uses a piezoelectric phased-array transducer that performs the actuation and sensing of the signals. The flexibility and strength of the instrument allow the user to develop and implement a substantial part of the SHM technique using Lamb waves. The entire system is controlled using configuration software and has been validated through functional, electrical loading, mechanical loading, and thermal loading resistance tests.

  17. Ultrasonic wave-based structural health monitoring embedded instrument.

    Science.gov (United States)

    Aranguren, G; Monje, P M; Cokonaj, Valerijan; Barrera, Eduardo; Ruiz, Mariano

    2013-12-01

    Piezoelectric sensors and actuators are the bridge between electronic and mechanical systems in structures. This type of sensor is a key element in the integrity monitoring of aeronautic structures, bridges, pressure vessels, wind turbine blades, and gas pipelines. In this paper, an all-in-one system for Structural Health Monitoring (SHM) based on ultrasonic waves is presented, called Phased Array Monitoring for Enhanced Life Assessment. This integrated instrument is able to generate excitation signals that are sent through piezoelectric actuators, acquire the received signals in the piezoelectric sensors, and carry out signal processing to check the health of structures. To accomplish this task, the instrument uses a piezoelectric phased-array transducer that performs the actuation and sensing of the signals. The flexibility and strength of the instrument allow the user to develop and implement a substantial part of the SHM technique using Lamb waves. The entire system is controlled using configuration software and has been validated through functional, electrical loading, mechanical loading, and thermal loading resistance tests.

  18. A Microwave Blade Tip Clearance Sensor for Propulsion Health Monitoring

    Science.gov (United States)

    Woike, Mark R.; Abdul-Aziz, Ali; Bencic, Timothy J.

    2010-01-01

    Microwave sensor technology is being investigated by the NASA Glenn Research Center as a means of making non-contact structural health measurements in the hot sections of gas turbine engines. This type of sensor technology is beneficial in that it is accurate, it has the ability to operate at extremely high temperatures, and is unaffected by contaminants that are present in turbine engines. It is specifically being targeted for use in the High Pressure Turbine (HPT) and High Pressure Compressor (HPC) sections to monitor the structural health of the rotating components. It is intended to use blade tip clearance to monitor blade growth and wear and blade tip timing to monitor blade vibration and deflection. The use of microwave sensors for this application is an emerging concept. Techniques on their use and calibration needed to be developed. As a means of better understanding the issues associated with the microwave sensors, a series of experiments have been conducted to evaluate their performance for aero engine applications. This paper presents the results of these experiments.

  19. 75 FR 57736 - Notice of Request for Approval of an Information Collection; National Animal Health Monitoring...

    Science.gov (United States)

    2010-09-22

    ... Information Collection; National Animal Health Monitoring System; Small-Scale Livestock Operations 2011 Study... National Animal Health Monitoring System Small-Scale Livestock Operations 2011 Study. DATES: We will... INFORMATION: Title: National Animal Health Monitoring System; Small-Scale Livestock Operations 2011 Study....

  20. 76 FR 28414 - Notice of Request for Approval of an Information Collection; National Animal Health Monitoring...

    Science.gov (United States)

    2011-05-17

    ...; National Animal Health Monitoring System; Emergency Epidemiologic Investigations AGENCY: Animal and Plant... to support the National Animal Health Monitoring System. DATES: We will consider all comments that we... Coordinator, at (301) 851-2908. SUPPLEMENTARY INFORMATION: Title: National Animal Health Monitoring...

  1. Health monitoring of bonded composite repair in bridge rehabilitation

    Science.gov (United States)

    Wu, Zhanjun; Qing, Xinlin P.; Ghosh, Kumar; Karbhar, Vistasp; Chang, Fu-Kuo

    2008-08-01

    Structural rehabilitation with carbon fiber reinforced composite materials has proven to be an excellent way to enhance/repair steel reinforced concrete structures and prolong their service lives. However, disbonds between composite repair patches and host structures continue to be a great concern of this technology. In this paper, a built-in piezoelectric sensor network based structural health monitoring system is introduced for monitoring the disbonds between composite repair patches and the host structures. This diagnostic system combines the sensor network, diagnostic hardware and data analysis software allowing for real-time monitoring of the integrity of the bonded repair. The effectiveness of detecting disbonds using the system has been demonstrated on a full scale bridge model in a laboratory setting. The bridge model was loaded incrementally to failure, and disbond monitoring was carried out during the loading intervals. Test results showed that the system could detect the disbonds before they have a noticeable effect on the global stiffness of the bridge model.

  2. Printing of microstructure strain sensor for structural health monitoring

    Science.gov (United States)

    Le, Minh Quyen; Ganet, Florent; Audigier, David; Capsal, Jean-Fabien; Cottinet, Pierre-Jean

    2017-05-01

    Recent advances in microelectronics and materials should allow the development of integrated sensors with transduction properties compatible with being printed directly onto a 3D substrate, especially metallic and polymer substrates. Inorganic and organic electronic materials in microstructured and nanostructured forms, intimately integrated in ink, offer particularly attractive characteristics, with realistic pathways to sophisticated embodiments. Here, we report on these strategies and demonstrate the potential of 3D-printed microelectronics based on a structural health monitoring (SHM) application for the precision weapon systems. We show that our printed sensors can be employed in non-invasive, high-fidelity and continuous strain monitoring of handguns, making it possible to implement printed sensors on a 3D substrate in either SHM or remote diagnostics. We propose routes to commercialization and novel device opportunities and highlight the remaining challenges for research.

  3. A nonlinear cointegration approach with applications to structural health monitoring

    Science.gov (United States)

    Shi, H.; Worden, K.; Cross, E. J.

    2016-09-01

    One major obstacle to the implementation of structural health monitoring (SHM) is the effect of operational and environmental variabilities, which may corrupt the signal of structural degradation. Recently, an approach inspired from the community of econometrics, called cointegration, has been employed to eliminate the adverse influence from operational and environmental changes and still maintain sensitivity to structural damage. However, the linear nature of cointegration may limit its application when confronting nonlinear relations between system responses. This paper proposes a nonlinear cointegration method based on Gaussian process regression (GPR); the method is constructed under the Engle-Granger framework, and tests for unit root processes are conducted both before and after the GPR is applied. The proposed approach is examined with real engineering data from the monitoring of the Z24 Bridge.

  4. Optical Fiber Sensors for Aircraft Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Iker García

    2015-06-01

    Full Text Available Aircraft structures require periodic and scheduled inspection and maintenance operations due to their special operating conditions and the principles of design employed to develop them. Therefore, structural health monitoring has a great potential to reduce the costs related to these operations. Optical fiber sensors applied to the monitoring of aircraft structures provide some advantages over traditional sensors. Several practical applications for structures and engines we have been working on are reported in this article. Fiber Bragg gratings have been analyzed in detail, because they have proved to constitute the most promising technology in this field, and two different alternatives for strain measurements are also described. With regard to engine condition evaluation, we present some results obtained with a reflected intensity-modulated optical fiber sensor for tip clearance and tip timing measurements in a turbine assembled in a wind tunnel.

  5. Optical Fiber Sensors for Aircraft Structural Health Monitoring.

    Science.gov (United States)

    García, Iker; Zubia, Joseba; Durana, Gaizka; Aldabaldetreku, Gotzon; Illarramendi, María Asunción; Villatoro, Joel

    2015-06-30

    Aircraft structures require periodic and scheduled inspection and maintenance operations due to their special operating conditions and the principles of design employed to develop them. Therefore, structural health monitoring has a great potential to reduce the costs related to these operations. Optical fiber sensors applied to the monitoring of aircraft structures provide some advantages over traditional sensors. Several practical applications for structures and engines we have been working on are reported in this article. Fiber Bragg gratings have been analyzed in detail, because they have proved to constitute the most promising technology in this field, and two different alternatives for strain measurements are also described. With regard to engine condition evaluation, we present some results obtained with a reflected intensity-modulated optical fiber sensor for tip clearance and tip timing measurements in a turbine assembled in a wind tunnel.

  6. Probabilistic Structural Health Monitoring of the Orbiter Wing Leading Edge

    Science.gov (United States)

    Yap, Keng C.; Macias, Jesus; Kaouk, Mohamed; Gafka, Tammy L.; Kerr, Justin H.

    2011-01-01

    A structural health monitoring (SHM) system can contribute to the risk management of a structure operating under hazardous conditions. An example is the Wing Leading Edge Impact Detection System (WLEIDS) that monitors the debris hazards to the Space Shuttle Orbiter s Reinforced Carbon-Carbon (RCC) panels. Since Return-to-Flight (RTF) after the Columbia accident, WLEIDS was developed and subsequently deployed on board the Orbiter to detect ascent and on-orbit debris impacts, so as to support the assessment of wing leading edge structural integrity prior to Orbiter re-entry. As SHM is inherently an inverse problem, the analyses involved, including those performed for WLEIDS, tend to be associated with significant uncertainty. The use of probabilistic approaches to handle the uncertainty has resulted in the successful implementation of many development and application milestones.

  7. Wake-up transceivers for structural health monitoring of bridges

    Science.gov (United States)

    Kumberg, T.; Kokert, J.; Younesi, V.; Koenig, S.; Reindl, L. M.

    2016-04-01

    In this article we present a wireless sensor network to monitor the structural health of a large-scale highway bridge in Germany. The wireless sensor network consists of several sensor nodes that use wake-up receivers to realize latency free and low-power communication. The sensor nodes are either equipped with very accurate tilt sensor developed by Northrop Grumman LITEF GmbH or with a Novatel OEM615 GNSS receiver. Relay nodes are required to forward measurement data to a base station located on the bridge. The base station is a gateway that transmits the local measurement data to a remote server where it can be further analyzed and processed. Further on, we present an energy harvesting system to supply the energy demanding GNSS sensor nodes to realize long term monitoring.

  8. Fiber Optic Sensors for Structural Health Monitoring of Air Platforms

    Directory of Open Access Journals (Sweden)

    Jianping Yao

    2011-03-01

    Full Text Available Aircraft operators are faced with increasing requirements to extend the service life of air platforms beyond their designed life cycles, resulting in heavy maintenance and inspection burdens as well as economic pressure. Structural health monitoring (SHM based on advanced sensor technology is potentially a cost-effective approach to meet operational requirements, and to reduce maintenance costs. Fiber optic sensor technology is being developed to provide existing and future aircrafts with SHM capability due to its unique superior characteristics. This review paper covers the aerospace SHM requirements and an overview of the fiber optic sensor technologies. In particular, fiber Bragg grating (FBG sensor technology is evaluated as the most promising tool for load monitoring and damage detection, the two critical SHM aspects of air platforms. At last, recommendations on the implementation and integration of FBG sensors into an SHM system are provided.

  9. Pipelining in structural health monitoring wireless sensor network

    Science.gov (United States)

    Li, Xu; Dorvash, Siavash; Cheng, Liang; Pakzad, Shamim

    2010-04-01

    Application of wireless sensor network (WSN) for structural health monitoring (SHM), is becoming widespread due to its implementation ease and economic advantage over traditional sensor networks. Beside advantages that have made wireless network preferable, there are some concerns regarding their performance in some applications. In long-span Bridge monitoring the need to transfer data over long distance causes some challenges in design of WSN platforms. Due to the geometry of bridge structures, using multi-hop data transfer between remote nodes and base station is essential. This paper focuses on the performances of pipelining algorithms. We summarize several prevent pipelining approaches, discuss their performances, and propose a new pipelining algorithm, which gives consideration to both boosting of channel usage and the simplicity in deployment.

  10. Skin-mountable stretch sensor for wearable health monitoring.

    Science.gov (United States)

    Pegan, Jonathan D; Zhang, Jasmine; Chu, Michael; Nguyen, Thao; Park, Sun-Jun; Paul, Akshay; Kim, Joshua; Bachman, Mark; Khine, Michelle

    2016-10-06

    This work presents a wrinkled Platinum (wPt) strain sensor with tunable strain sensitivity for applications in wearable health monitoring. These stretchable sensors show a dynamic range of up to 185% strain and gauge factor (GF) of 42. This is believed to be the highest reported GF of any metal thin film strain sensor over a physiologically relevant dynamic range to date. Importantly, sensitivity and dynamic range are tunable to the application by adjusting wPt film thickness. Performance is reliable over 1000 cycles with low hysteresis after sensor conditioning. The possibility of using such a sensor for real-time respiratory monitoring by measuring chest wall displacement and correlating with lung volume is demonstrated.

  11. Performance Health Monitoring of Large-Scale Systems

    Energy Technology Data Exchange (ETDEWEB)

    Rajamony, Ram [IBM Research, Austin, TX (United States)

    2014-11-20

    This report details the progress made on the ASCR funded project Performance Health Monitoring for Large Scale Systems. A large-­scale application may not achieve its full performance potential due to degraded performance of even a single subsystem. Detecting performance faults, isolating them, and taking remedial action is critical for the scale of systems on the horizon. PHM aims to develop techniques and tools that can be used to identify and mitigate such performance problems. We accomplish this through two main aspects. The PHM framework encompasses diagnostics, system monitoring, fault isolation, and performance evaluation capabilities that indicates when a performance fault has been detected, either due to an anomaly present in the system itself or due to contention for shared resources between concurrently executing jobs. Software components called the PHM Control system then build upon the capabilities provided by the PHM framework to mitigate degradation caused by performance problems.

  12. Progress Monitoring in an Integrated Health Care System: Tracking Behavioral Health Vital Signs.

    Science.gov (United States)

    Steinfeld, Bradley; Franklin, Allie; Mercer, Brian; Fraynt, Rebecca; Simon, Greg

    2016-05-01

    Progress monitoring implementation in an integrated health care system is a complex process that must address factors such as measurement, technology, delivery system care processes, patient needs and provider requirements. This article will describe how one organization faced these challenges by identifying the key decision points (choice of measure, process for completing rating scale, interface with electronic medical record and clinician engagement) critical to implementation. Qualitative and quantitative data will be presented describing customer and stakeholder satisfaction with the mental health progress monitoring tool (MHPMT) as well as organizational performance with key measurement targets.

  13. A Simple Demonstration of Concrete Structural Health Monitoring Framework

    Energy Technology Data Exchange (ETDEWEB)

    Mahadevan, Sankaran [Idaho National Lab. (INL), Idaho Falls, ID (United States); Agarwal, Vivek [Idaho National Lab. (INL), Idaho Falls, ID (United States); Cai, Guowei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Nath, Paromita [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bao, Yanqing [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bru Brea, Jose Maria [Idaho National Lab. (INL), Idaho Falls, ID (United States); Koester, David [Idaho National Lab. (INL), Idaho Falls, ID (United States); Adams, Douglas [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kosson, David [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-03-01

    Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Structural health monitoring of concrete structures aims to understand the current health condition of a structure based on heterogeneous measurements to produce high confidence actionable information regarding structural integrity that supports operational and maintenance decisions. This ongoing research project is seeking to develop a probabilistic framework for health diagnosis and prognosis of aging concrete structures in a nuclear power plant subjected to physical, chemical, environment, and mechanical degradation. The proposed framework consists of four elements—damage modeling, monitoring, data analytics, and uncertainty quantification. This report describes a proof-of-concept example on a small concrete slab subjected to a freeze-thaw experiment that explores techniques in each of the four elements of the framework and their integration. An experimental set-up at Vanderbilt University’s Laboratory for Systems Integrity and Reliability is used to research effective combination of full-field techniques that include infrared thermography, digital image correlation, and ultrasonic measurement. The measured data are linked to the probabilistic framework: the thermography, digital image correlation data, and ultrasonic measurement data are used for Bayesian calibration of model parameters, for diagnosis of damage, and for prognosis of future damage. The proof-of-concept demonstration presented in this report highlights the significance of each element of the framework and their integration.

  14. Machine vision process monitoring on a poultry processing kill line: results from an implementation

    Science.gov (United States)

    Usher, Colin; Britton, Dougl; Daley, Wayne; Stewart, John

    2005-11-01

    Researchers at the Georgia Tech Research Institute designed a vision inspection system for poultry kill line sorting with the potential for process control at various points throughout a processing facility. This system has been successfully operating in a plant for over two and a half years and has been shown to provide multiple benefits. With the introduction of HACCP-Based Inspection Models (HIMP), the opportunity for automated inspection systems to emerge as viable alternatives to human screening is promising. As more plants move to HIMP, these systems have the great potential for augmenting a processing facilities visual inspection process. This will help to maintain a more consistent and potentially higher throughput while helping the plant remain within the HIMP performance standards. In recent years, several vision systems have been designed to analyze the exterior of a chicken and are capable of identifying Food Safety 1 (FS1) type defects under HIMP regulatory specifications. This means that a reliable vision system can be used in a processing facility as a carcass sorter to automatically detect and divert product that is not suitable for further processing. This improves the evisceration line efficiency by creating a smaller set of features that human screeners are required to identify. This can reduce the required number of screeners or allow for faster processing line speeds. In addition to identifying FS1 category defects, the Georgia Tech vision system can also identify multiple "Other Consumer Protection" (OCP) category defects such as skin tears, bruises, broken wings, and cadavers. Monitoring this data in an almost real-time system allows the processing facility to address anomalies as soon as they occur. The Georgia Tech vision system can record minute-by-minute averages of the following defects: Septicemia Toxemia, cadaver, over-scald, bruises, skin tears, and broken wings. In addition to these defects, the system also records the length and

  15. Monitoring the health of sugar maple, Acer saccharum

    Science.gov (United States)

    Carlson, Martha

    The sugar maple, Acer saccharum, is projected to decline and die in 88 to 100 percent of its current range in the United States. An iconic symbol of the northeastern temperate forest and a dominant species in this forest, the sugar maple is identified as the most sensitive tree in its ecosystem to rising temperatures and a warming climate. This study measures the health of sugar maples on 12 privately owned forests and at three schools in New Hampshire. Laboratory quantitative analyses of leaves, buds and sap as well as qualitative measures of leaf and bud indicate that record high beat in 2012 stressed the sugar maple. The study identifies several laboratory and qualitative tests of health which seem most sensitive and capable of identifying stress early when intervention in forest management or public policy change might counter decline of the species. The study presents evidence of an unusual atmospheric pollution event which defoliated sugar maples in 2010. The study examines the work of citizen scientists in Forest Watch, a K-12 school program in which students monitor the impacts of ozone on white pine, Pinus strobus, another keystone species in New Hampshire's forest. Finally, the study examines three simple measurements of bud, leaf and the tree's acclimation to light. The findings of these tests illuminate findings in the first study. And they present examples of what citizen scientists might contribute to long-term monitoring of maples. A partnership between science and citizens is proposed to begin long-term monitoring and to report on the health of sugar maples.

  16. ChemAND - a system health monitor for plant chemistry

    Energy Technology Data Exchange (ETDEWEB)

    Turner, C.W.; Mitchel, G.R.; Tosello, G.; Balakrishnan, P.V.; McKay, G.; Thompson, M. [Atomic Energy of Canada Limited, Chalk River, Ontario (Canada); Dundar, Y.; Bergeron, M.; Laporte, R. [Hydro-Quebec, Groupe Chimie, Centrale Nucleaire Gentilly-2, Gentilly, Quebec (Canada)

    2001-03-01

    Effective management of plant systems throughout their lifetime requires much more than data acquisition and display - it requires that the plant's system health be continually monitored and managed. AECL has developed a System Health Monitor called ChemAND for CANDU plant chemistry. ChemAND, a Chemistry ANalysis and Diagnostic system, monitors key chemistry parameters in the heat transport system, moderator-cover gas, annulus gas, and the steam cycle during full-power operation. These parameters can be used as inputs to models that calculate the effect of current plant operating conditions on the present and future health of the system. Chemistry data from each of the systems are extracted on a regular basis from the plant's Historical Data Server and are sorted according to function, e.g., indicators for condenser in-leakage, air in-leakage, heavy water leakage into the annulus gas, fuel failure, etc. Each parameter is conveniently displayed and is trended along with its alarm limits. ChemAND currently includes two analytical models developed for the balance-of-plant. The first model, ChemSolv, calculates crevice chemistry conditions in the steam generator (SG) from either the SG blowdown chemistry conditions or from a simulated condenser leak. This information can be used by plant staff to evaluate the susceptibility of the SG tubes to crevice corrosion. ChemSolv also calculates chemistry conditions throughout the steam-cycle system as determined by the transport of volatile species such as ammonia, hydrazine, morpholine, and oxygen. The second model, SLUDGE, calculates the deposit loading and distribution in the SG as a function of time, based on concentrations of corrosion product in the final feedwater for both normal and start-up conditions. Operations personnel can use this information to predict where to inspect and when to clean. (author)

  17. Monitoring health interventions – who's afraid of LQAS?

    Directory of Open Access Journals (Sweden)

    Lorenzo Pezzoli

    2013-11-01

    Full Text Available Lot quality assurance sampling (LQAS is used to evaluate health services. Subunits of a population (lots are accepted or rejected according to the number of failures in a random sample (N of a given lot. If failures are greater than decision value (d, we reject the lot and recommend corrective actions in the lot (i.e. intervention area; if they are equal to or less than d, we accept it. We used LQAS to monitor coverage during the last 3 days of a meningitis vaccination campaign in Niger. We selected one health area (lot per day reporting the lowest administrative coverage in the previous 2 days. In the sampling plan we considered: N to be small enough to allow us to evaluate one lot per day, deciding to sample 16 individuals from the selected villages of each health area, using probability proportionate to population size; thresholds and d to vary according to administrative coverage reported; α≤5% (meaning that, if we would have conducted the survey 100 times, we would have accepted the lot up to five times when real coverage was at an unacceptable level and β≤20% (meaning that we would have rejected the lot up to 20 times, when real coverage was equal or above the satisfactory level. We classified all three lots as with the acceptable coverage. LQAS appeared to be a rapid, simple, and statistically sound method for in-process coverage assessment. We encourage colleagues in the field to consider using LQAS in complement with other monitoring techniques such as house-to-house monitoring.

  18. Structural Health Monitoring of Bridges with Fiber Bragg Grating Sensors

    Directory of Open Access Journals (Sweden)

    Francisco Navarro-Henríquez

    2014-11-01

    Systems with fiber optic sensors FBG (Fiber Bragg Grating are consolidated in the Structural Health Monitoring (SMH of bridges, Nondestructive Testing (NDT static and dynamic measurements of deformation, displacement, deflection, temperature and vibration. This article provides a brief introduction to the technology and the fundamentals of fiber optic sensors, also present comparative advantages over its traditional counterpart is presented. Their characteristics are described and measurement graphics are presented as an application example of the FBG sensors. Finally, some key aspects to consider for proper use in the field are mentioned.

  19. Risk-Adjusted Control Charts for Health Care Monitoring

    Directory of Open Access Journals (Sweden)

    Willem Albers

    2011-01-01

    the distribution involved is negative binomial. However, in health care monitoring, (groups of patients will often belong to different risk categories. In the present paper, we will show how information about category membership can be used to adjust the basic negative binomial charts to the actual risk incurred. Attention is also devoted to comparing such conditional charts to their unconditional counterparts. The latter do take possible heterogeneity into account but refrain from risk-adjustment. Note that in the risk adjusted case several parameters are involved, which will all be typically unknown. Hence, the potentially considerable estimation effects of the new charts will be investigated as well.

  20. Uniform circular array for structural health monitoring of composite structures

    Science.gov (United States)

    Stepinski, Tadeusz; Engholm, Marcus

    2008-03-01

    Phased array with all-azimuth angle coverage would be extremely useful in structural health monitoring (SHM) of planar structures. One method to achieve the 360° coverage is to use uniform circular arrays (UCAs). In this paper we present the concept of UCA adapted for SHM applications. We start from a brief presentation of UCA beamformers based on the principle of phase mode excitation. UCA performance is illustrated by the results of beamformer simulations performed for the narrowband and wideband ultrasonic signals. Preliminary experimental results obtained with UCA used for the reception of ultrasonic signals propagating in an aluminum plate are also presented.

  1. Feature Comparison in Structural Health Monitoring of a Vehicle Crane

    Directory of Open Access Journals (Sweden)

    J. Kullaa

    2008-01-01

    Full Text Available Vibration-based structural health monitoring of a vehicle crane was studied. The performance of different features to detect damage was investigated after eliminating the normal operational variations using factor analysis. Using eight accelerometers, ten AR parameters from each record were identified for damage detection. Also transmissibilities between sensors were estimated. Damage was introduced with additional masses at different locations of the structure. All damage cases could be detected from either features using control charts, but transmissibilities proved to be more sensitive to damage than the AR coefficients.

  2. Multi-component machine monitoring and fault diagnosis using blind source separation and advanced vibration analysis

    Science.gov (United States)

    Mahvash Mohammadi, Ali

    detecting defects from a weak signal as it passes and attenuates through its transmission path. The other requirement is that it must allow robust, attainable and consistent trending. Also the feature being tracked must be consistent in the sense that its value bears some correspondence to the severity of the faults. In this thesis, cyclostationarity is examined for these requirements through two sets of experimental tests. The experimental results show that cyclic spectral analysis is indeed capable of detecting bearing faults from faint signals. Also, it can be utilized as a reliable monitoring tool, even though the correspondence between the feature value and the severity of the bearing faults may not be robustly established. (Abstract shortened by UMI.)

  3. Investigation of a Moire Based Crack Detection Technique for Propulsion Health Monitoring

    Science.gov (United States)

    Woike, Mark R.; Abudl-Aziz, Ali; Fralick, Gustave C.; Wrbanek, John D.

    2012-01-01

    The development of techniques for the health monitoring of the rotating components in gas turbine engines is of major interest to NASA s Aviation Safety Program. As part of this on-going effort several experiments utilizing a novel optical Moir based concept along with external blade tip clearance and shaft displacement instrumentation were conducted on a simulated turbine engine disk as a means of demonstrating a potential optical crack detection technique. A Moir pattern results from the overlap of two repetitive patterns with slightly different periods. With this technique, it is possible to detect very small differences in spacing and hence radial growth in a rotating disk due to a flaw such as a crack. The experiment involved etching a circular reference pattern on a subscale engine disk that had a 50.8 mm (2 in.) long notch machined into it to simulate a crack. The disk was operated at speeds up to 12 000 rpm and the Moir pattern due to the shift with respect to the reference pattern was monitored as a means of detecting the radial growth of the disk due to the defect. In addition, blade displacement data were acquired using external blade tip clearance and shaft displacement sensors as a means of confirming the data obtained from the optical technique. The results of the crack detection experiments and its associated analysis are presented in this paper.

  4. Structural Health Monitoring Using Textile Reinforcement Structures with Integrated Optical Fiber Sensors

    Directory of Open Access Journals (Sweden)

    Kort Bremer

    2017-02-01

    Full Text Available Optical fiber-based sensors “embedded” in functionalized carbon structures (FCSs and textile net structures (TNSs based on alkaline-resistant glass are introduced for the purpose of structural health monitoring (SHM of concrete-based structures. The design aims to monitor common SHM parameters such as strain and cracks while at the same time acting as a structural strengthening mechanism. The sensor performances of the two systems are characterized in situ using Mach-Zehnder interferometric (MZI and optical attenuation measurement techniques, respectively. For this purpose, different FCS samples were subjected to varying elongation using a tensile testing machine by carefully incrementing the applied force, and good correlation between the applied force and measured length change was observed. For crack detection, the functionalized TNSs were embedded into a concrete block which was then exposed to varying load using the three-point flexural test until destruction. Promising results were observed, identifying that the location of the crack can be determined using the conventional optical time domain reflectometry (OTDR technique. The embedded sensors thus evaluated show the value of the dual achievement of the schemes proposed in obtaining strain/crack measurement while being utilized as strengthening agents as well.

  5. Remote Monitoring of the Structural Health of Hydrokinetic Composite Turbine Blades

    Energy Technology Data Exchange (ETDEWEB)

    J.L. Rovey

    2012-09-21

    A health monitoring approach is investigated for hydrokinetic turbine blade applications. In-service monitoring is critical due to the difficult environment for blade inspection and the cost of inspection downtime. Composite blade designs have advantages that include long life in marine environments and great control over mechanical properties. Experimental strain characteristics are determined for static loads and free-vibration loads. These experiments are designed to simulate the dynamic characteristics of hydrokinetic turbine blades. Carbon/epoxy symmetric composite laminates are manufactured using an autoclave process. Four-layer composite beams, eight-layer composite beams, and two-dimensional eight-layer composite blades are instrumented for strain. Experimental results for strain measurements from electrical resistance gages are validated with theoretical characteristics obtained from in-house finite-element analysis for all sample cases. These preliminary tests on the composite samples show good correlation between experimental and finite-element strain results. A health monitoring system is proposed in which damage to a composite structure, e.g. delamination and fiber breakage, causes changes in the strain signature behavior. The system is based on embedded strain sensors and embedded motes in which strain information is demodulated for wireless transmission. In-service monitoring is critical due to the difficult environment for blade inspection and the cost of inspection downtime. Composite blade designs provide a medium for embedding sensors into the blades for in-situ health monitoring. The major challenge with in-situ health monitoring is transmission of sensor signals from the remote rotating reference frame of the blade to the system monitoring station. In the presented work, a novel system for relaying in-situ blade health measurements in hydrokinetic systems is described and demonstrated. An ultrasonic communication system is used to transmit

  6. Studies of the Machine Induced Background, simulations for the design of the Beam Condition Monitor and implementation of the Inclusive $\\phi$ Trigger at the LHCb experiment at CERN

    CERN Document Server

    Lieng, Magnus

    2011-01-01

    LHCb is one of the four major experiments of the LHC at CERN, built to perform precision measurements of CP violation and rare decays. In order to protect the sensitive elements of the experiment from adverse beam conditions the Beam Condition Monitor has been created. Such conditions increase the particle flux arriving from the LHC, known as Machine Induced Background. These particles interfere with the experiment, for example through the physics trigger. In this thesis software development and simulations for the design and validation of the Beam Condition Monitor is shown, ranging from LHCb-specific algorithm implementation to beam dump threshold determination. Furthermore, software development in order to attain a complete simulation chain of machine induced background is shown. The results of these simulations are compared to early data collected at LHCb. Lastly, the development and implementation of the Inclusive $\\phi$ trigger line for the High Level Trigger is presented. This line aims to reconstruct ...

  7. Toward flexible and wearable human-interactive health-monitoring devices.

    Science.gov (United States)

    Takei, Kuniharu; Honda, Wataru; Harada, Shingo; Arie, Takayuki; Akita, Seiji

    2015-03-11

    This Progress Report introduces flexible wearable health-monitoring devices that interact with a person by detecting from and stimulating the body. Interactive health-monitoring devices should be highly flexible and attach to the body without awareness like a bandage. This type of wearable health-monitoring device will realize a new class of electronics, which will be applicable not only to health monitoring, but also to other electrical devices. However, to realize wearable health-monitoring devices, many obstacles must be overcome to economically form the active electrical components on a flexible substrate using macroscale fabrication processes. In particular, health-monitoring sensors and curing functions need to be integrated. Here recent developments and advancements toward flexible health-monitoring devices are presented, including conceptual designs of human-interactive devices.

  8. Smart coatings for health monitoring and nondestructive evaluation (Invited Paper)

    Science.gov (United States)

    Bencic, Timothy J.; Eldridge, Jeffrey I.

    2005-05-01

    Luminescent coatings applications have been increased dramatically over the last decade as imaging capacities have advanced. These coatings have been used to monitor surface temperature and air pressure (oxygen sensing) in testing facilities around the world. Through the commercial suppliers of these coatings, custom assembled hardware systems and especially data reduction and analysis software, the use of smart luminescent coatings are starting to find their way in to inspection monitoring and nondestructive evaluation testing. The use of a temperature sensitive paint for example, can be a potential replacement for infrared imaging where IR techniques are limited due to access, reflections and complex geometries. Detection of the luminescent signal can use simple intensity ratio methods with synchronized pulsing systems to capture frequency responses in imaging applications. Time or frequency methods allow signals to be detected in the presence of high background noise that allow measurements that were previously unobtainable. This paper describes general luminescent sensors, detection methods and examples of coatings that are applied over test examples or embedded in materials to measure or monitor the health of a specimen.

  9. HISTORIC BIM: A NEW REPOSITORY FOR STRUCTURAL HEALTH MONITORING

    Directory of Open Access Journals (Sweden)

    F. Banfi

    2017-05-01

    Full Text Available Recent developments in Building Information Modelling (BIM technologies are facilitating the management of historic complex structures using new applications. This paper proposes a generative method combining the morphological and typological aspects of the historic buildings (H-BIM, with a set of monitoring information. This combination of 3D digital survey, parametric modelling and monitoring datasets allows for the development of a system for archiving and visualizing structural health monitoring (SHM data (Fig. 1. The availability of a BIM database allows one to integrate a different kind of data stored in different ways (e.g. reports, tables, graphs, etc. with a representation directly connected to the 3D model of the structure with appropriate levels of detail (LoD. Data can be interactively accessed by selecting specific objects of the BIM, i.e. connecting the 3D position of the sensors installed with additional digital documentation. Such innovative BIM objects, which form a new BIM family for SHM, can be then reused in other projects, facilitating data archiving and exploitation of data acquired and processed. The application of advanced modeling techniques allows for the reduction of time and costs of the generation process, and support cooperation between different disciplines using a central workspace. However, it also reveals new challenges for parametric software and exchange formats. The case study presented is the medieval bridge Azzone Visconti in Lecco (Italy, in which multi-temporal vertical movements during load testing were integrated into H-BIM.

  10. Historic Bim: a New Repository for Structural Health Monitoring

    Science.gov (United States)

    Banfi, F.; Barazzetti, L.; Previtali, M.; Roncoroni, F.

    2017-05-01

    Recent developments in Building Information Modelling (BIM) technologies are facilitating the management of historic complex structures using new applications. This paper proposes a generative method combining the morphological and typological aspects of the historic buildings (H-BIM), with a set of monitoring information. This combination of 3D digital survey, parametric modelling and monitoring datasets allows for the development of a system for archiving and visualizing structural health monitoring (SHM) data (Fig. 1). The availability of a BIM database allows one to integrate a different kind of data stored in different ways (e.g. reports, tables, graphs, etc.) with a representation directly connected to the 3D model of the structure with appropriate levels of detail (LoD). Data can be interactively accessed by selecting specific objects of the BIM, i.e. connecting the 3D position of the sensors installed with additional digital documentation. Such innovative BIM objects, which form a new BIM family for SHM, can be then reused in other projects, facilitating data archiving and exploitation of data acquired and processed. The application of advanced modeling techniques allows for the reduction of time and costs of the generation process, and support cooperation between different disciplines using a central workspace. However, it also reveals new challenges for parametric software and exchange formats. The case study presented is the medieval bridge Azzone Visconti in Lecco (Italy), in which multi-temporal vertical movements during load testing were integrated into H-BIM.

  11. Logic-centered architecture for ubiquitous health monitoring.

    Science.gov (United States)

    Lewandowski, Jacek; Arochena, Hisbel E; Naguib, Raouf N G; Chao, Kuo-Ming; Garcia-Perez, Alexeis

    2014-09-01

    One of the key points to maintain and boost research and development in the area of smart wearable systems (SWS) is the development of integrated architectures for intelligent services, as well as wearable systems and devices for health and wellness management. This paper presents such a generic architecture for multiparametric, intelligent and ubiquitous wireless sensing platforms. It is a transparent, smartphone-based sensing framework with customizable wireless interfaces and plug'n'play capability to easily interconnect third party sensor devices. It caters to wireless body, personal, and near-me area networks. A pivotal part of the platform is the integrated inference engine/runtime environment that allows the mobile device to serve as a user-adaptable personal health assistant. The novelty of this system lays in a rapid visual development and remote deployment model. The complementary visual Inference Engine Editor that comes with the package enables artificial intelligence specialists, alongside with medical experts, to build data processing models by assembling different components and instantly deploying them (remotely) on patient mobile devices. In this paper, the new logic-centered software architecture for ubiquitous health monitoring applications is described, followed by a discussion as to how it helps to shift focus from software and hardware development, to medical and health process-centered design of new SWS applications.

  12. Autonomous health monitoring of a stiffened composite plate

    Science.gov (United States)

    Mal, Ajit K.; Banerjee, Sauvik; Ricci, Fabrizio; Monaco, Ernesto; Lecce, L.

    2006-03-01

    The paper presents a unified computer assisted automatic damage identification technique based on a damage index, associated with changes in the vibrational and wave propagation characteristics in damaged structures. An improved ultrasonic and vibration test setup consisting of distributed, high fidelity, intelligent, surface mounted sensor arrays is used to examine the change in the dynamical properties of realistic composite structural components with the appearance of damage. The sensors are assumed to provide both the low frequency global response (i.e., modal frequencies, mode shapes) of the structure to external loads and the (local) high frequency signals due to wave propagation effects in either passive or active mode of the ultrasonic array. Using the initial measurements performed on an undamaged structure as baseline, the damage indices are evaluated from the comparison of the frequency response of the monitored structure with an unknown damage. The technique is applied to identify impact damage in a woven stiffened composite plate that presents practical difficulties in transmitting waves across it due to scattering and other energy dissipation effects present in the material and the geometry of the structure. Moreover, a sensitivity analysis has been carried out in order to estimate a threshold value of the index below which no reliable information about the state of health of the structure can be achieved. The feasibility of developing a practical Intelligent Structural Health Monitoring (ISHM) System, based on the concept of "a structure requesting service when needed," is discussed.

  13. Implementation of a piezoelectric energy harvester in railway health monitoring

    Science.gov (United States)

    Li, Jingcheng; Jang, Shinae; Tang, Jiong

    2014-03-01

    With development of wireless sensor technology, wireless sensor network has shown a great potential for railway health monitoring. However, how to supply continuous power to the wireless sensor nodes is one of the critical issues in long-term full-scale deployment of the wireless smart sensors. Some energy harvesting methodologies have been available including solar, vibration, wind, etc; among them, vibration-based energy harvester using piezoelectric material showed the potential for converting ambient vibration energy to electric energy in railway health monitoring even for underground subway systems. However, the piezoelectric energy harvester has two major problems including that it could only generate small amount of energy, and that it should match the exact narrow band natural frequency with the excitation frequency. To overcome these problems, a wide band piezoelectric energy harvester, which could generate more power on various frequencies regions, has been designed and validated with experimental test. Then it was applied to a full-scale field test using actual railway train. The power generation of the wide band piezoelectric array has been compared to a narrow-band, resonant-based, piezoelectric energy harvester.

  14. Accelerated Aging Experiments for Capacitor Health Monitoring and Prognostics

    Science.gov (United States)

    Kulkarni, Chetan S.; Celaya, Jose Ramon; Biswas, Gautam; Goebel, Kai

    2012-01-01

    This paper discusses experimental setups for health monitoring and prognostics of electrolytic capacitors under nominal operation and accelerated aging conditions. Electrolytic capacitors have higher failure rates than other components in electronic systems like power drives, power converters etc. Our current work focuses on developing first-principles-based degradation models for electrolytic capacitors under varying electrical and thermal stress conditions. Prognostics and health management for electronic systems aims to predict the onset of faults, study causes for system degradation, and accurately compute remaining useful life. Accelerated life test methods are often used in prognostics research as a way to model multiple causes and assess the effects of the degradation process through time. It also allows for the identification and study of different failure mechanisms and their relationships under different operating conditions. Experiments are designed for aging of the capacitors such that the degradation pattern induced by the aging can be monitored and analyzed. Experimental setups and data collection methods are presented to demonstrate this approach.

  15. Carbon Nanotube-Based Structural Health Monitoring Sensors

    Science.gov (United States)

    Wincheski, Russell; Jordan, Jeffrey; Oglesby, Donald; Watkins, Anthony; Patry, JoAnne; Smits, Jan; Williams, Phillip

    2011-01-01

    Carbon nanotube (CNT)-based sensors for structural health monitoring (SHM) can be embedded in structures of all geometries to monitor conditions both inside and at the surface of the structure to continuously sense changes. These CNTs can be manipulated into specific orientations to create small, powerful, and flexible sensors. One of the sensors is a highly flexible sensor for crack growth detection and strain field mapping that features a very dense and highly ordered array of single-walled CNTs. CNT structural health sensors can be mass-produced, are inexpensive, can be packaged in small sizes (0.5 micron(sup 2)), require less power than electronic or piezoelectric transducers, and produce less waste heat per square centimeter than electronic or piezoelectric transducers. Chemically functionalized lithographic patterns are used to deposit and align the CNTs onto metallic electrodes. This method consistently produces aligned CNTs in the defined locations. Using photo- and electron-beam lithography, simple Cr/Au thin-film circuits are patterned onto oxidized silicon substrates. The samples are then re-patterned with a CNT-attracting, self-assembled monolayer of 3-aminopropyltriethoxysilane (APTES) to delineate the desired CNT locations between electrodes. During the deposition of the solution-suspended single- wall CNTs, the application of an electric field to the metallic contacts causes alignment of the CNTs along the field direction. This innovation is a prime candidate for smart skin technologies with applications ranging from military, to aerospace, to private industry.

  16. Passive and Active Sensing Technologies for Structural Health Monitoring

    Science.gov (United States)

    Do, Richard

    A combination of passive and active sensing technologies is proposed as a structural health monitoring solution for several applications. Passive sensing is differentiated from active sensing in that with the former, no energy is intentionally imparted into the structure under test; sensors are deployed in a pure detection mode for collecting data mined for structural health monitoring purposes. In this thesis, passive sensing using embedded fiber Bragg grating optical strain gages was used to detect varying degrees of impact damage using two different classes of features drawn from traditional spectral analysis and auto-regressive time series modeling. The two feature classes were compared in detail through receiver operating curve performance analysis. The passive detection problem was then augmented with an active sensing system using ultrasonic guided waves (UGWs). This thesis considered two main challenges associated with UGW SHM including in-situ wave propagation property determination and thermal corruption of data. Regarding determination of wave propagation properties, of which dispersion characteristics are the most important, a new dispersion curve extraction method called sparse wavenumber analysis (SWA) was experimentally validated. Also, because UGWs are extremely sensitive to ambient temperature changes on the structure, it significantly affects the wave propagation properties by causing large errors in the residual error in the processing of the UGWs from an array. This thesis presented a novel method that compensates for uniform temperature change by considering the magnitude and phase of the signal separately and applying a scalable transformation.

  17. Structural health monitoring feature design by genetic programming

    Science.gov (United States)

    Harvey, Dustin Y.; Todd, Michael D.

    2014-09-01

    Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems.

  18. Wireless Health Data Exchange for Home Healthcare Monitoring Systems

    Directory of Open Access Journals (Sweden)

    Malrey Lee

    2010-04-01

    Full Text Available Ubiquitous home healthcare systems have been playing an increasingly significant role in the treatment and management of chronic diseases, such as diabetes and hypertension, but progress has been hampered by the lack of standardization in the exchange of medical health care information. In an effort to establish standardization, this paper proposes a home healthcare monitoring system data exchange scheme between the HL7 standard and the IEEE1451 standard. IEEE1451 is a standard for special sensor networks, such as industrial control and smart homes, and defines a suite of interfaces that communicate among heterogeneous networks. HL7 is the standard for medical information exchange among medical organizations and medical personnel. While it provides a flexible data exchange in health care domains, it does not provide for data exchange with sensors. Thus, it is necessary to develop a data exchange schema to convert data between the HL7 and the IEEE1451 standard. This paper proposes a schema that can exchange data between HL7 devices and the monitoring device, and conforms to the IEEE 1451 standard. The experimental results and conclusions of this approach are presented and show the feasibility of the proposed exchange schema.

  19. Integrating social determinants of health in the universal health coverage monitoring framework.

    Science.gov (United States)

    Vega, Jeanette; Frenz, Patricia

    2013-12-01

    Underpinning the global commitment to universal health coverage (UHC) is the fundamental role of health for well-being and sustainable development. UHC is proposed as an umbrella health goal in the post-2015 sustainable development agenda because it implies universal and equitable effective delivery of comprehensive health services by a strong health system, aligned with multiple sectors around the shared goal of better health. In this paper, we argue that social determinants of health (SDH) are central to both the equitable pursuit of healthy lives and the provision of health services for all and, therefore, should be expressly incorporated into the framework for monitoring UHC. This can be done by: (a) disaggregating UHC indicators by different measures of socioeconomic position to reflect the social gradient and the complexity of social stratification; and (b) connecting health indicators, both outcomes and coverage, with SDH and policies within and outside of the health sector. Not locating UHC in the context of action on SDH increases the risk of going down a narrow route that limits the right to health to coverage of services and financial protection.

  20. Health Monitoring System Based on Intra-Body Communication

    Science.gov (United States)

    Razak, A. H. A.; Ibrahim, I. W.; Ayub, A. H.; Amri, M. F.; Hamzi, M. H.; Halim, A. K.; Ahmad, A.; Junid, S. A. M. Al

    2015-11-01

    This paper presents a model of a Body Area Network (BAN) health monitoring system based on Intra-Body Communication. Intra-body Communication (IBC) is a communication technique that uses the human body as a medium for electrical signal communication. One of the visions in the health care industry is to provide autonomous and continuous self and the remote health monitoring system. This can be achieved via BAN, LAN and WAN integration. The BAN technology itself consists of short range data communication modules, sensors, controller and actuators. The information can be transmitted to the LAN and WAN via the RF technology such as Bluetooth, ZigBee and ANT. Although the implementations of RF communication have been successful, there are still limitations in term of power consumption, battery lifetime, interferences and signal attenuations. One of the solutions for Medical Body Area Network (MBANs) to overcome these issues is by using an IBC technique because it can operate at lower frequencies and power consumption compared to the existing techniques. The first objective is to design the IBC's transmitter and receiver modules using the off the shelf components. The specifications of the modules such as frequency, data rate, modulation and demodulation coding system were defined. The individual module were designed and tested separately. The modules was integrated as an IBC system and tested for functionality then was implemented on PCB. Next objective is to model and implement the digital parts of the transmitter and receiver modules on the Altera's FPGA board. The digital blocks were interfaced with the FPGA's on board modules and the discrete components. The signals that have been received from the transmitter were converted into a proper waveform and it can be viewed via external devices such as oscilloscope and Labview. The signals such as heartbeats or pulses can also be displayed on LCD. In conclusion, the IBC project presents medical health monitoring model

  1. Monitoring of the state of the paper machine circulation water with a wide-band impedance measurement; Paperikoneen kiertoveden tilan seuranta laajakaistaisella impedanssimittauksella - MPKT 02

    Energy Technology Data Exchange (ETDEWEB)

    Varpula, T. [VTT Automation, Espoo (Finland). Measurement Technology

    1998-12-31

    A new measurement method for monitoring the chemical state of the circulation water in the paper machine is proposed and studied. In the method, the electrical properties - conductivity and permittivity - of the water are measured in a wide frequency band: 20 Hz - 10 mhz. Large-molecule organic compounds in the water are expected cause characteristic changes in the dielectric properties of the water. Continuous monitoring of the permittivity in the wide frequency band thus reveals their presence. Various electronic measurement setups for the measurement are constructed and studied by using test samples. If the method turns out to be promising, a prototype device will be made. (orig.)

  2. Health monitoring of pipeline girth weld using empirical mode decomposition

    Science.gov (United States)

    Rezaei, Davood; Taheri, Farid

    2010-05-01

    In the present paper the Hilbert-Huang transform (HHT), as a time-series analysis technique, has been combined with a local diagnostic approach in an effort to identify flaws in pipeline girth welds. This method is based on monitoring the free vibration signals of the pipe at its healthy and flawed states, and processing the signals through the HHT and its associated signal decomposition technique, known as empirical mode decomposition (EMD). The EMD method decomposes the vibration signals into a collection of intrinsic mode functions (IMFs). The deviations in structural integrity, measured from a healthy-state baseline, are subsequently evaluated by two damage sensitive parameters. The first is a damage index, referred to as the EM-EDI, which is established based on an energy comparison of the first or second IMF of the vibration signals, before and after occurrence of damage. The second parameter is the evaluation of the lag in instantaneous phase, a quantity derived from the HHT. In the developed methodologies, the pipe's free vibration is monitored by piezoceramic sensors and a laser Doppler vibrometer. The effectiveness of the proposed techniques is demonstrated through a set of numerical and experimental studies on a steel pipe with a mid-span girth weld, for both pressurized and nonpressurized conditions. To simulate a crack, a narrow notch is cut on one side of the girth weld. Several damage scenarios, including notches of different depths and at various locations on the pipe, are investigated. Results from both numerical and experimental studies reveal that in all damage cases the sensor located at the notch vicinity could successfully detect the notch and qualitatively predict its severity. The effect of internal pressure on the damage identification method is also monitored. Overall, the results are encouraging and promise the effectiveness of the proposed approaches as inexpensive systems for structural health monitoring purposes.

  3. Wireless Structural Sensing for Health Monitoring and Control Applications

    Science.gov (United States)

    Lynch, J. P.

    2003-12-01

    health monitoring) have been included in the unit's computational core. Additionally, an actuation interface has recently been added to the sensing unit design to allow for direct operation of structural actuators. With a computational core capable of real-time data processing, the data acquisition and actuation interfaces can be coupled through discrete-time feedback control loops implemented in software. Looking to the future, this intelligent monitoring infrastructure can possibly tune a structural control system in real-time after early warning of a pending seismic disturbance has been communicated to the wireless sensor network.

  4. Vestas V90-3MW Wind Turbine Gearbox Health Assessment Using a Vibration-Based Condition Monitoring System

    Directory of Open Access Journals (Sweden)

    A. Romero

    2016-01-01

    Full Text Available Reliable monitoring for the early fault diagnosis of gearbox faults is of great concern for the wind industry. This paper presents a novel approach for health condition monitoring (CM and fault diagnosis in wind turbine gearboxes using vibration analysis. This methodology is based on a machine learning algorithm that generates a baseline for the identification of deviations from the normal operation conditions of the turbine and the intrinsic characteristic-scale decomposition (ICD method for fault type recognition. Outliers picked up during the baseline stage are decomposed by the ICD method to obtain the product components which reveal the fault information. The new methodology proposed for gear and bearing defect identification was validated by laboratory and field trials, comparing well with the methods reviewed in the literature.

  5. Structural Health Monitoring of Composite Structures Using Fiber Optic Sensors

    Science.gov (United States)

    Whitaker, Anthony

    Structural health monitoring is the process of detecting damage to a structure, where damage can be characterized as changes to material/mechanical properties including but not limited to plastically deforming the material or the modification of connections. Fiber optic cables with fiber Bragg gratings have emerged as a reliable method of locally measuring strains within a structure. During the manufacturing of composite structures, the fiber optic cables can be embedded between lamina plies, allowing the ability to measure strain at discrete locations within the structure as opposed to electrical strain gauges, which must typically be applied to the surface only. The fiber optic sensors may be used to see if the local strain at the sensor location is beyond desired limits, or the array response may be mined to determine additional information about the loading applied to the structure. The work presented in this thesis is to present novel and potential applications of FBG sensors being used to assess the health of the structure. The first application is the dual application of the FBG sensor as a method to determine the strain around a bolt connection as well as the preload of the fastener using a single fiber optic sensor. The composite material around the bolted connections experience stress concentrations and are often the location of damage to the structure from operational cyclic loading over the lifetime of the structure. The degradation can occur more quickly if the fastener is insufficiently tight to transfer load properly. The second application is the ability to locate the impact location of a projectile with damaging and non-damaging energy. By locating and quantifying the damage, the sensor array provides the basis for a structural health monitoring system that has the potential to determine if the damage is extensive enough to replace, or if the part can be salvaged and retrofitted.

  6. The influence of health system organizational structure and culture on integration of health services: the example of HIV service monitoring in South Africa.

    Science.gov (United States)

    Kawonga, Mary; Blaauw, Duane; Fonn, Sharon

    2016-11-01

    Administrative integration of disease control programmes (DCPs) within the district health system has been a health sector reform priority in South Africa for two decades. The reforms entail district managers assuming authority for the planning and monitoring of DCPs in districts, with DCP managers providing specialist support. There has been little progress in achieving this, and a dearth of research exploring why. Using a case study of HIV programme monitoring and evaluation (M&E), this article explores whether South Africa's health system is configured to support administrative integration. The article draws on data from document reviews and interviews with 54 programme and district managers in two of nine provinces, exploring their respective roles in decision-making regarding HIV M&E system design and in using HIV data for monitoring uptake of HIV interventions in districts. Using Mintzberg's configurations framework, we describe three organizational parameters: (a) extent of centralization (whether district managers play a role in decisions regarding the design of the HIV M&E system); (b) key part of the organization (extent to which sub-national programme managers vs district managers play the central role in HIV monitoring in districts); and (c) coordination mechanisms used (whether highly formalized and rules-based or more output-based to promote agency). We find that the health system can be characterized as Mintzberg's machine bureaucracy. It is centralized and highly formalized with structures, management styles and practices that promote programme managers as lead role players in the monitoring of HIV interventions within districts. This undermines policy objectives of district managers assuming this leadership role. Our study enhances the understanding of organizational factors that may limit the success of administrative integration reforms and suggests interventions that may mitigate this. © The Author 2016. Published by Oxford University Press in

  7. Time-Frequency Methods for Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Alexander L. Pyayt

    2014-03-01

    Full Text Available Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM of flood protection systems (levees, earthen dikes and concrete dams using sensor data. We present a robust data-driven anomaly detection method that combines time-frequency feature extraction, using wavelet analysis and phase shift, with one-sided classification techniques to identify the onset of failure anomalies in real-time sensor measurements. The methodology has been successfully tested at three operational levees. We detected a dam leakage in the retaining dam (Germany and “strange” behaviour of sensors installed in a Boston levee (UK and a Rhine levee (Germany.

  8. Air quality monitoring in NIS (SERBIA) and health impact assessment.

    Science.gov (United States)

    Nikic, Dragana; Bogdanovic, Dragan; Nikolic, Maja; Stankovic, Aleksandra; Zivkovic, Nenad; Djordjevic, Amelija

    2009-11-01

    The aim of this study is to indicate the significance of air quality monitoring and to determine the air quality fields for the assessment of air pollution health effects, with special attention to risk population. Radial basis function network was used for air quality index mapping. Between 1991 and 2005, on the territory of Nis, several epidemiological studies were performed on risk groups (pre-school children, school children, pregnant women and persons older than 65). The total number of subjects was 5837. The exposed group comprised individuals living in the areas with unhealthy AQI, while the control group comprised individuals living in city areas with good or moderate AQI. It was determined that even relatively low levels of air pollution had impact on respiratory system and the occurrence of anaemia, allergy and skin symptoms.

  9. Lamb wave propagation modeling for structure health monitoring

    Institute of Scientific and Technical Information of China (English)

    Xiaoyue ZHANG; Shenfang YUAN; Tong HAO

    2009-01-01

    This study aims to model the propagation of Lamb waves used in structure health monitoring. A number of different numerical computational techniques have been developed for wave propagation studies. The local interaction simulation approach, used for modeling sharp interfaces and discontinuities in complex media (LISA/SIM theory), has been effectively applied to numerical simulations of elastic wave interaction. This modeling is based on the local interaction simulation approach theory and is finally accomplished through the finite elements software Ansys11. In this paper, the Lamb waves propagating characteristics and the LISA/SIM theory are introduced. The finite difference equations describing wave propagation used in the LISA/SIM theory are obtained. Then, an anisotropic metallic plate model is modeled and a simulating Lamb waves signal is loaded on. Finally, the Lamb waves propagation modeling is implemented.

  10. Converting signals to knowledge in structural health monitoring systems

    Science.gov (United States)

    Brownjohn, James M. W.; Moyo, Pilate; Omenzetter, Piotr; Chakraboorty, Sushanta

    2005-04-01

    Academic approaches in structural health monitoring (SHM) usually focus on fine detail or on aspects of the technology such as sensors and data collection, and areas that may be less useful to operators than information about the level of performance of their structures. The steps in the process of SHM such as data management, data mining, conversion to knowledge of structural behaviour and integrity are frequently absent, and even the most operationally successful SHM systems may lack the component where deep understanding on the nature of the structure performance is obtained. This paper presents experience gained in a number of SHM exercises where static and dynamic response data have been interpreted, with or without the aid of calibrated structural models, in order to characterise the mechanisms at work and the experiences of the structure.

  11. Networked Computing in Wireless Sensor Networks for Structural Health Monitoring

    CERN Document Server

    Jindal, Apoorva

    2010-01-01

    This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a well-known centralized operation, into components, we seek to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on w...

  12. Damage detection and health monitoring of operational structures

    Energy Technology Data Exchange (ETDEWEB)

    James, G.; Mayes, R.; Carne, T.; Reese, G.

    1994-09-01

    Initial damage detection/health monitoring experiments have been performed on three different operational structures: a fracture critical bridge, a composite wind turbine blade, and an aging aircraft. An induced damage test was performed on the Rio Grande/I40 bridge before its demolition. The composite wind turbine test was fatgued to failure with periodic modal testing performed throughout the testing. The front fuselage of a DC-9 aircraft was used as the testbed for an induced damage test. These tests have yielded important insights into techniques for experimental damage detection on real structures. Additionally, the data are currently being used with current damage detection algorithms to further develop the numerical technology. State of the art testing technologies such as, high density modal testing, scanning laser vibrometry and natural excitation testing have also been utilized for these tests.

  13. Dynamic time warping for temperature compensation in structural health monitoring

    Science.gov (United States)

    Douglass, Alexander; Harley, Joel B.

    2017-02-01

    Guided wave structural health monitoring uses ultrasonic waves to identify changes in structures. To identify these changes, most guided wave methods require a pristine baseline measurement with which other measurements are compared. Damage signatures arise when there is a deviation between the baseline and the recorded measurement. However, temperature significantly complicates this analysis by creating misalignment between the baseline and measurements. This leads to false alarms of damage and significantly reduces the reliability of these systems. Several methods have been created to account for these temperature perturbations. Yet, most of these compensation methods fail in harsh, highly variable temperature conditions or require a prohibitive amount of prior data. In this paper, we use an algorithm known as dynamic time warping to compensate for temperature in these harsh conditions. We demonstrate that dynamic time warping is able to account for temperature variations whereas the more traditional baseline signal stretch method is unable to resolve damage under high temperature fluctuations.

  14. 3D Ultrasonic Wave Simulations for Structural Health Monitoring

    Science.gov (United States)

    Campbell, Leckey Cara A/; Miler, Corey A.; Hinders, Mark K.

    2011-01-01

    Structural health monitoring (SHM) for the detection of damage in aerospace materials is an important area of research at NASA. Ultrasonic guided Lamb waves are a promising SHM damage detection technique since the waves can propagate long distances. For complicated flaw geometries experimental signals can be difficult to interpret. High performance computing can now handle full 3-dimensional (3D) simulations of elastic wave propagation in materials. We have developed and implemented parallel 3D elastodynamic finite integration technique (3D EFIT) code to investigate ultrasound scattering from flaws in materials. EFIT results have been compared to experimental data and the simulations provide unique insight into details of the wave behavior. This type of insight is useful for developing optimized experimental SHM techniques. 3D EFIT can also be expanded to model wave propagation and scattering in anisotropic composite materials.

  15. Fiber Optic Thermal Health Monitoring of Aerospace Structures and Materials

    Science.gov (United States)

    Wu, Meng-Chou; Winfree, William P.; Allison, Sidney G.

    2009-01-01

    A new technique is presented for thermographic detection of flaws in materials and structures by performing temperature measurements with fiber Bragg gratings. Individual optical fibers with multiple Bragg gratings employed as surface temperature sensors were bonded to the surfaces of structures with subsurface defects or thickness variations. Both during and following the application of a thermal heat flux to the surface, the individual Bragg grating sensors measured the temporal and spatial temperature variations. The investigated structures included a 10-ply composite specimen with subsurface delaminations of various sizes and depths. The data obtained from grating sensors were further analyzed with thermal modeling to reveal particular characteristics of the interested areas. These results were found to be consistent with those from conventional thermography techniques. Limitations of the technique were investigated using both experimental and numerical simulation techniques. Methods for performing in-situ structural health monitoring are discussed.

  16. Redirection of Lamb Waves for Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    W. H. Ong

    2012-01-01

    Full Text Available Currently, structures are designed without structural health monitoring (SHM in mind. It is proposed that SHM should be addressed at the design stage of new structures. This paper explores the benefit which can be gained from such considerations. The scope encompasses Lamb-wave-based SHM and a given fatigue critical location (FCL. Optimization is performed using specialised ray tracing. A case study is carried out using a specimen that simulates a hard-to-inspect region in a fuel vent hole in wings structures of aircraft. This work will report on the potential use of the focussing of stress wave to improve detectability of defect in this hard-to-inspect location. Following optimization, results are produced numerically and experimentally. The results revealed sensitivity to damage is nearly doubled while minimum detectable damage size is significantly decreased. As a result, this study brings together an assortment of specialised tools to form a workflow ready for implementation.

  17. Predictive simulation of guide-wave structural health monitoring

    Science.gov (United States)

    Giurgiutiu, Victor

    2017-04-01

    This paper presents an overview of recent developments on predictive simulation of guided wave structural health monitoring (SHM) with piezoelectric wafer active sensor (PWAS) transducers. The predictive simulation methodology is based on the hybrid global local (HGL) concept which allows fast analytical simulation in the undamaged global field and finite element method (FEM) simulation in the local field around and including the damage. The paper reviews the main results obtained in this area by researchers of the Laboratory for Active Materials and Smart Structures (LAMSS) at the University of South Carolina, USA. After thematic introduction and research motivation, the paper covers four main topics: (i) presentation of the HGL analysis; (ii) analytical simulation in 1D and 2D; (iii) scatter field generation; (iv) HGL examples. The paper ends with summary, discussion, and suggestions for future work.

  18. Analysis of remote reflection spectroscopy to monitor plant health.

    Science.gov (United States)

    Woodhouse, R; Heeb, M; Berry, W; Hoshizaki, T; Wood, M

    1994-11-01

    Remote non-contact reflection spectroscopy is examined as a method for detecting stress in Controlled Ecological Life Support System CELSS type crops. Lettuce (Lactuca [correction of Latuca] Sativa L. cv. Waldmans Green) and wheat (Triticum Aestivum L. cv. Yecora Rojo) were grown hydroponically. Copper and zinc treatments provided toxic conditions. Nitrogen, phosphorous, and potassium treatments were used for deficiency conditions. Water stress was also induced in test plants. Reflectance spectra were obtained in the visible and near infrared (400nm to 2600nm) wavebands. Numerous effects of stress conditions can be observed in the collected spectra and this technique appears to have promise as a remote monitor of plant health, but significant research remains to be conducted to realize the promise.

  19. Review on pressure sensors for structural health monitoring

    Science.gov (United States)

    Sikarwar, Samiksha; Satyendra; Singh, Shakti; Yadav, B. C.

    2017-08-01

    This paper reports the state of art in a variety of pressure and the detailed study of various matrix based pressure sensors. The performances of the bridges, buildings, etc. are threatened by earthquakes, material degradations, and other environmental effects. Structural health monitoring (SHM) is crucial to protect the people and also for assets planning. This study is a contribution in developing the knowledge about self-sensing smart materials and structures for the construction industry. It deals with the study of self-sensing as well as mechanical and electrical properties of different matrices based on pressure sensors. The relationships among the compression, tensile strain, and crack length with electrical resistance change are also reviewed.

  20. Assessment of an Anomaly Detector for Jet Engine Health Monitoring

    Directory of Open Access Journals (Sweden)

    Sebastien Borguet

    2011-01-01

    Full Text Available The goal of module performance analysis is to reliably assess the health of the main components of an aircraft engine. A predictive maintenance strategy can leverage this information to increase operability and safety as well as to reduce costs. Degradation undergone by an engine can be divided into gradual deterioration and accidental events. Kalman filters have proven very efficient at tracking progressive deterioration but are poor performers in the face of abrupt events. Adaptive estimation is considered as an appropriate solution to this deficiency. This paper reports the evaluation of the detection capability of an adaptive diagnosis tool on the basis of simulated scenarios that may be encountered during the operation of a commercial turbofan engine. The diagnosis tool combines a Kalman filter and a secondary system that monitors the residuals. This auxiliary component implements a generalised likelihood ratio test in order to detect abrupt events.

  1. Inspection of Piezoceramic Transducers Used for Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Inka Mueller

    2017-01-01

    Full Text Available The use of piezoelectric wafer active sensors (PWAS for structural health monitoring (SHM purposes is state of the art for acousto-ultrasonic-based methods. For system reliability, detailed information about the PWAS itself is necessary. This paper gives an overview on frequent PWAS faults and presents the effects of these faults on the wave propagation, used for active acousto-ultrasonics-based SHM. The analysis of the wave field is based on velocity measurements using a laser Doppler vibrometer (LDV. New and established methods of PWAS inspection are explained in detail, listing advantages and disadvantages. The electro-mechanical impedance spectrum as basis for these methods is discussed for different sensor faults. This way this contribution focuses on a detailed analysis of PWAS and the need of their inspection for an increased reliability of SHM systems.

  2. Analysis of remote reflectin spectroscopy to monitor plant health

    Science.gov (United States)

    Woodhouse, R.; Heeb, M.; Berry, W.; Hoshizaki, T.; Wood, M.

    1994-01-01

    Remote non-contact reflection spectroscopy is examined as a method for detecting stress in Controlled Ecological Life Support System (CELSS) type crops. Lettuce (Latuca Sativa L. cv. Waldmans Green) and wheat (Triticum Aestivum L. cv. Yecora Rojo) were grown hydroponically. Copper and zinc treatments provided toxic conditions. Nitrogen, phosphorous, and potassium treatments were used for deficiency conditions. Water stress was also induced in test plants. Reflectance spectra were obtained in the visible and near infrared (400nm to 2600nm) wavebands. Numerous effects of stress conditions can be observed in the collected spectra and this technique appears to have promise as a remote monitor of plant health, but significant research remains to be conducted to realize the promise.

  3. Analysis of remote reflection spectroscopy to monitor plant health

    Science.gov (United States)

    Woodhouse, R.; Heeb, M.; Berry, W.; Hoshizaki, T.; Wood, M.

    1994-11-01

    Remote non-contact reflection spectroscopy is examined as a method for detecting stress in Controlled Ecological Life Support System CELSS type crops. Lettuce (Latuca Sativa L. cv. Waldmans Green) and wheat (Triticum Aestivum L. cv. Yecora Rojo) were grown hydroponically. Copper and zinc treatments provided toxic conditions. Nitrogen, phosphorous, and potassium treatments were used for deficiency conditions. Water stress was also induced in test plants. Reflectance spectra were obtained in the visible and near infrared (400nm to 2600nm) wavebands. Numerous effects of stress conditions can be observed in the collected spectra and this technique appears to have promise as a remote monitor of plant health, but significant research remains to be conducted to realize the promise.

  4. On structural health monitoring of aircraft adhesively bonded repairs

    Science.gov (United States)

    Pavlopoulou, Sofia

    The recent interest in life extension of ageing aircraft and the need to address the repair challenges in the new age composite ones, led to the investigation of new repair methodologies such as adhesively bonded repair patches. The present thesis focuses on structural health monitoring aspects of the repairs, evaluating their performance with guided ultrasonic waves aiming to develop a monitoring strategy which would eliminate unscheduled maintenance and unnecessary inspection costs. To address the complex nature of the wave propagation phenomena, a finite element based model identified the existing challenges by exploring the interaction of the excitation waves with different levels of damage. The damage sensitivity of the first anti-symmetric mode was numerically investigated. An external bonded patch and a scarf repair, were further tested in static and dynamic loadings, and their performance was monitored with Lamb waves, excited by surface-bonded piezoelectric transducers.. The response was processed by means of advanced pattern recognition and data dimension reduction techniques such as novelty detection and principal component analysis. An optimisation of these tools enabled an accurate damage detection under complex conditions. The phenomena of mode isolation and precise arrival time determination under a noisy environment and the problem of inadequate training data were investigated and solved through appropriate transducer arrangements and advanced signal processing respectively. The applicability of the established techniques was demonstrated on an aluminium repaired helicopter tail stabilizer. Each case study utilised alternative non-destructive techniques for validation such as 3D digital image correlation, X-ray radiography and thermography. Finally a feature selection strategy was developed through the analysis of the instantaneous properties of guided waves for damage detection purposes..

  5. Smart Structures and Intelligent Systems for Health Monitoring and Diagnostics

    Directory of Open Access Journals (Sweden)

    M. A. El-Sherif

    2005-01-01

    Full Text Available “Smart and intelligent” structures are defined as structures capable of monitoring their own “health” condition and structural behavior, such structures are capable of sensing external environmental conditions, making decisions, and sending the information to other locations. Available conventional devices and systems are not technologically mature for such applications. New classes of miniature devices and networking systems are urgently needed for such applications. In this paper, two examples of the successful work achieved so far, in biomedical application of smart structures, are presented. The first one is based on the development of a smart bone fixation device for rehabilitation and treatment. This device includes a smart composite bar that can sense physical stress applied to the fractured bones, and send the information to the patient's physician remotely. The second is on the development of smart fabrics for many applications including health monitoring and diagnostics. Successful development of such smart fabrics with embedded fiber optic sensors and networks is mainly dependent on the development of the proper miniature sensor technology, and on the integration of these sensors into textile structures. The developed smart structures will be discussed and samples of the results will be presented.

  6. Mobile Personal Health System for Ambulatory Blood Pressure Monitoring

    Directory of Open Access Journals (Sweden)

    Luis J. Mena

    2013-01-01

    Full Text Available The ARVmobile v1.0 is a multiplatform mobile personal health monitor (PHM application for ambulatory blood pressure (ABP monitoring that has the potential to aid in the acquisition and analysis of detailed profile of ABP and heart rate (HR, improve the early detection and intervention of hypertension, and detect potential abnormal BP and HR levels for timely medical feedback. The PHM system consisted of ABP sensor to detect BP and HR signals and smartphone as receiver to collect the transmitted digital data and process them to provide immediate personalized information to the user. Android and Blackberry platforms were developed to detect and alert of potential abnormal values, offer friendly graphical user interface for elderly people, and provide feedback to professional healthcare providers via e-mail. ABP data were obtained from twenty-one healthy individuals (>51 years to test the utility of the PHM application. The ARVmobile v1.0 was able to reliably receive and process the ABP readings from the volunteers. The preliminary results demonstrate that the ARVmobile 1.0 application could be used to perform a detailed profile of ABP and HR in an ordinary daily life environment, bedsides of estimating potential diagnostic thresholds of abnormal BP variability measured as average real variability.

  7. Development of smart sensing system for structural health monitoring

    Science.gov (United States)

    Lu, Kung-Chun; Loh, Chin-Hsiung; Weng, Jian Huang

    2010-04-01

    The objective of this paper is to upgrade a wireless sensing unit which can meet the following requirements: 1) Improvement of system powering and analog signal processing 2) Enhancement of signal resolution and provide reliable wireless communication data, 3) Enhance capability for continuous long-term monitoring. Based on the prototype of the wireless sensing unit developed by Prof. Lynch at the Stanford University, the following upgrading steps are summarized: 1. Reduce system noise by using SMD passive elements and preventing the coupling digital and analog circuits, and increasing the capacity of power. 2. Improve the ADC sampling resolution and accuracy with a higher resolution Analog-to-Digital Converter (ADC): a 24bits ADC with programmable gain amplifier. 3. Improve wireless communication by using the wireless radio 9XTend which supported by the router (Digi MESH) communication function using 900MHz frequency band. Based on the upgrade wireless sensing unit, verification of the new wireless sensing unit was conducted from the ambient vibration survey of a base-isolated building. This new upgrade wireless sensing unit can provide more reliable data for continuous structural health monitoring. Incorporated with the identification software (modified stochastic subspace identification method) the smart sensing system for SHM is developed.

  8. Automated structural health monitoring based on adaptive kernel spectral clustering

    Science.gov (United States)

    Langone, Rocco; Reynders, Edwin; Mehrkanoon, Siamak; Suykens, Johan A. K.

    2017-06-01

    Structural health monitoring refers to the process of measuring damage-sensitive variables to assess the functionality of a structure. In principle, vibration data can capture the dynamics of the structure and reveal possible failures, but environmental and operational variability can mask this information. Thus, an effective outlier detection algorithm can be applied only after having performed data normalization (i.e. filtering) to eliminate external influences. Instead, in this article we propose a technique which unifies the data normalization and damage detection steps. The proposed algorithm, called adaptive kernel spectral clustering (AKSC), is initialized and calibrated in a phase when the structure is undamaged. The calibration process is crucial to ensure detection of early damage and minimize the number of false alarms. After the calibration, the method can automatically identify new regimes which may be associated with possible faults. These regimes are discovered by means of two complementary damage (i.e. outlier) indicators. The proposed strategy is validated with a simulated example and with real-life natural frequency data from the Z24 pre-stressed concrete bridge, which was progressively damaged at the end of a one-year monitoring period.

  9. Manufacturing of Wearable Sensors for Human Health and Performance Monitoring

    Science.gov (United States)

    Alizadeh, Azar

    2015-03-01

    Continuous monitoring of physiological and biological parameters is expected to improve performance and medical outcomes by assessing overall health status and alerting for life-saving interventions. Continuous monitoring of these parameters requires wearable devices with an appropriate form factor (lightweight, comfortable, low energy consuming and even single-use) to avoid disrupting daily activities thus ensuring operation relevance and user acceptance. Many previous efforts to implement remote and wearable sensors have suffered from high cost and poor performance, as well as low clinical and end-use acceptance. New manufacturing and system level design approaches are needed to make the performance and clinical benefits of these sensors possible while satisfying challenging economic, regulatory, clinical, and user-acceptance criteria. In this talk we will review several recent design and manufacturing efforts aimed at designing and building prototype wearable sensors. We will discuss unique opportunities and challenges provided by additive manufacturing, including 3D printing, to drive innovation through new designs, faster prototyping and manufacturing, distributed networks, and new ecosystems. We will also show alternative hybrid self-assembly based integration techniques for low cost large scale manufacturing of single use wearable devices. Coauthors: Prabhjot Singh and Jeffrey Ashe.

  10. Ferroelectric thin-film active sensors for structural health monitoring

    Science.gov (United States)

    Lin, Bin; Giurgiutiu, Victor; Yuan, Zheng; Liu, Jian; Chen, Chonglin; Jiang, Jiechao; Bhalla, Amar S.; Guo, Ruyan

    2007-04-01

    Piezoelectric wafer active sensors (PWAS) have been proven a valuable tool in structural health monitoring. Piezoelectric wafer active sensors are able to send and receive guided Lamb/Rayleigh waves that scan the structure and detect the presence of incipient cracks and structural damage. In-situ thin-film active sensor deposition can eliminate the bonding layer to improve the durability issue and reduce the acoustic impedance mismatch. Ferroelectric thin films have been shown to have piezoelectric properties that are close to those of single-crystal ferroelectrics but the fabrication of ferroelectric thin films on structural materials (steel, aluminum, titanium, etc.) has not been yet attempted. In this work, in-situ fabrication method of piezoelectric thin-film active sensors arrays was developed using the nano technology approach. Specification for the piezoelectric thin-film active sensors arrays was based on electro-mechanical-acoustical model. Ferroelectric BaTiO3 (BTO) thin films were successfully deposited on Ni tapes by pulsed laser deposition under the optimal synthesis conditions. Microstructural studies by X-ray diffractometer and transmission electron microscopy reveal that the as-grown BTO thin films have the nanopillar structures with an average size of approximately 80 nm in diameter and the good interface structures with no inter-diffusion or reaction. The dielectric and ferroelectric property measurements exhibit that the BTO films have a relatively large dielectric constant, a small dielectric loss, and an extremely large piezoelectric response with a symmetric hysteresis loop. The research objective is to develop the fabrication and optimum design of thin-film active sensor arrays for structural health monitoring applications. The short wavelengths of the micro phased arrays will permit the phased-array imaging of smaller parts and smaller damage than is currently not possible with existing technology.

  11. Autonomus I&C Maintenance and Health Monitoring System for Fission Surface Power Project

    Data.gov (United States)

    National Aeronautics and Space Administration — There currently exists no end-to-end reactor/power conversion monitoring system that can provide both autonomous health monitoring, but also in-situ sensor...

  12. Monitoring hemlock crown health in Delaware Water Gap National Recreation Area

    Science.gov (United States)

    Michael E. Montgomery; Bradley Onken; Richard A. Evans; Richard A. Evans

    2005-01-01

    Decline of the health of hemlocks in Delaware Water Gap National Recreation Area was noticeable in the southern areas of the park by 1992. The following year, a series of plots were established to monitor hemlock health and the abundance of hemlock woolly adelgid. This poster examines only the health rating of the hemlocks in the monitoring plots.

  13. Radiation health consequences for astronauts: mechanisms, monitoring and prevention

    Science.gov (United States)

    Neyfakh, E.

    During space flights crews are exposed chronically to uneven irradiation of enhanced bioefficiency following with significant elevation for chromosomal aberrations as minimum. To protect in space rationally monitoring and preventing of health radiogenic individual primary consequences for astronauts are of high importance. Majority of Chernobyl-touched population has some common etiologic radiogenic mechanisms and radioloads with astronauts ones during long-term missions and former is able to be used well as the close ground-level model. Primary radiogenic deviations. Two radiogenic pathologies as lipoperoxic ( LP ) stress with coupled deficits for essential bioantioxidants ( BAO ) were typical for chronic low-dose Chernobyl-touched contingents. When BAO expenditure had led to their subnormal levels, radiogenic free radical chain -b ranched LP processes occurred in vivo hyperbolically. Catabolites and their free radicals of the abnormal LP cascade are known to be toxic, mutagenic / carcinogenic and teratogenic factors as such, as they are for retinol and tocopherol deficiencies. Both coupled pathogenic factors interrelated synergistically. Simultaneous dysbalances for LP and / or BAO systems were evaluated as the cause and markers for metabolic disregulations. Human LP stress was proved to be the most radiosensible known marker to mo nitor least invasively of blood microsamples in a ground lab via the developed PC Program. But for capsule conditions the best approach is assumed to be LP monitoring via skin ultraweak green-blue chemiluminescence ( CL ) caused by recombination of peroxyl radicals. CL from surfaces of organs was embedded first ( E. Neyfakh, 1964 - 71 ) to reflect their internal LP velocities in vivo and it is the non-invasive on-line simple method of the highest sensitivity, supplying with data transmissible to the ground directly. Related deviations. a) Radiogenic hypermutagenesis: LP catabolites and their free radicals are responsible for direct DNA

  14. Real-time Monitoring of our Warfighters Health State: The Good, The Bad, and The Ugly

    Science.gov (United States)

    2008-04-05

    time Monitoring of our Warfighters Health State: The Good , The Bad , and The Ugly 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Status Physiological Monitor Concept 98 The GOOD Technologies & a solution framework have been greatly advanced. Health state monitoring is no...Medical Monitoring Telemetry System – In Action Results – Physiology, Real Time Display Th e GO OD The BAD Unique challenges make the creation and

  15. Home health monitoring – EyKos HealthHub (product design concept)

    OpenAIRE

    Phillips, Mark; Dulake, Nick; Willox, Matt; Gwilt, Ian; Craig, Claire; Auton, Kevin

    2015-01-01

    This work focused on creating a product design concept for a home health monitoring system, known as EyKos HealthHub, which is intended to be a ‘crossover product’ in the emerging medical/consumer product space. Working collaboratively with Aseptika Ltd, the team carried out product concept design and interaction design for the EyKos system, and undertook further design and prototyping work to create an object for use in research. Aseptika is carrying out technical development of this project...

  16. New smart materials to address issues of structural health monitoring.

    Energy Technology Data Exchange (ETDEWEB)

    Chaplya, Pavel Mikhail

    2004-12-01

    Nuclear weapons and their storage facilities may benefit from in-situ structural health monitoring systems. Appending health-monitoring functionality to conventional materials and structures has been only marginally successful. The purpose of this project was to evaluate feasibility of a new smart material that includes self-sensing health monitoring functions similar to that of a nervous system of a living organism. Reviews of current efforts in the fields of heath-monitoring, nanotechnology, micro-electromechanical systems (MEMS), and wireless sensor networks were conducted. Limitations of the current nanotechnology methods were identified and new approaches were proposed to accelerate the development of self-sensing materials. Wireless networks of MEMS sensors have been researched as possible prototypes of self-sensing materials. Sensor networks were also examined as enabling technologies for dense data collection techniques to be used for validation of numerical methods and material parameter identification. Each grain of the envisioned material contains sensors that are connected in a dendritic manner similar to networks of neurons in a nervous system. Each sensor/neuron can communicate with the neighboring grains. Both the state of the sensor (on/off) and the quality of communication signal (speed/amplitude) should indicate not only a presence of a structural defect but the nature of the defect as well. For example, a failed sensor may represent a through-grain crack, while a lost or degraded communication link may represent an inter-granular crack. A technology to create such material does not exist. While recent progress in the fields of MEMS and nanotechnology allows to envision these new smart materials, it is unrealistic to expect creation of self-sensing materials in the near future. The current state of MEMS, nanotechnology, communication, sensor networks, and data processing technologies indicates that it will take more than ten years for the

  17. An Identification Model of Health States of Machine Wear Based on Oil Analysis

    Institute of Scientific and Technical Information of China (English)

    FU Jun-qing; LI Han-xiong; XUAO Xin-hua

    2005-01-01

    This paper presents a modeling procedure for deriving a single value measure based on a regression model, and a method for determining a statistical threshold value as identification criterion of normal or abnormal states of machine wear. A real numerical example is examined by the method and identification criterion presented. The results indicate that the judgments by the presented methods are basically consistent with the real facts, and therefore the method and identification criterion are valuable for judging the normal or abnormal state of machine wear based on oil analysis.

  18. Health Monitoring Survey of Bell 412EP Transmissions

    Science.gov (United States)

    Tucker, Brian E.; Dempsey, Paula J.

    2016-01-01

    Health and usage monitoring systems (HUMS) use vibration-based Condition Indicators (CI) to assess the health of helicopter powertrain components. A fault is detected when a CI exceeds its threshold value. The effectiveness of fault detection can be judged on the basis of assessing the condition of actual components from fleet aircraft. The Bell 412 HUMS-equipped helicopter is chosen for such an evaluation. A sample of 20 aircraft included 12 aircraft with confirmed transmission and gearbox faults (detected by CIs) and eight aircraft with no known faults. The associated CI data is classified into "healthy" and "faulted" populations based on actual condition and these populations are compared against their CI thresholds to quantify the probability of false alarm and the probability of missed detection. Receiver Operator Characteristic analysis is used to optimize thresholds. Based on the results of the analysis, shortcomings in the classification method are identified for slow-moving CI trends. Recommendations for improving classification using time-dependent receiver-operator characteristic methods are put forth. Finally, lessons learned regarding OEM-operator communication are presented.

  19. Distributed Health Monitoring System for Reusable Liquid Rocket Engines

    Science.gov (United States)

    Lin, C. F.; Figueroa, F.; Politopoulos, T.; Oonk, S.

    2009-01-01

    The ability to correctly detect and identify any possible failure in the systems, subsystems, or sensors within a reusable liquid rocket engine is a major goal at NASA John C. Stennis Space Center (SSC). A health management (HM) system is required to provide an on-ground operation crew with an integrated awareness of the condition of every element of interest by determining anomalies, examining their causes, and making predictive statements. However, the complexity associated with relevant systems, and the large amount of data typically necessary for proper interpretation and analysis, presents difficulties in implementing complete failure detection, identification, and prognostics (FDI&P). As such, this paper presents a Distributed Health Monitoring System for Reusable Liquid Rocket Engines as a solution to these problems through the use of highly intelligent algorithms for real-time FDI&P, and efficient and embedded processing at multiple levels. The end result is the ability to successfully incorporate a comprehensive HM platform despite the complexity of the systems under consideration.

  20. Intelligent Wireless Sensor Networks for System Health Monitoring

    Science.gov (United States)

    Alena, Rick

    2011-01-01

    Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of

  1. Hybrid Nanostructured Textile Bioelectrode for Unobtrusive Health Monitoring

    Science.gov (United States)

    Rai, Pratyush

    Coronary heart disease, cardiovascular diseases and strokes are the leading causes of mortality in United States of America. Timely point-of-care health diagnostics and therapeutics for person suffering from these diseases can save thousands of lives. However, lack of accessible minimally intrusive health monitoring systems makes timely diagnosis difficult and sometimes impossible. To remedy this problem, a textile based nano-bio-sensor was developed and evaluated in this research. The sensor was made of novel array of vertically standing nanostructures that are conductive nano-fibers projecting from a conductive fabric. These sensor electrodes were tested for the quality of electrical contact that they made with the skin based on the fundamental skin impedance model and electromagnetic theory. The hybrid nanostructured dry electrodes provided large surface area and better contact with skin that improved electrode sensitivity and reduced the effect of changing skin properties, which are the problems usually faced by conventional dry textile electrodes. The dry electrodes can only register strong physiological signals because of high background noise levels, thus limiting the use of existing dry electrodes to heart rate measurement and respiration. Therefore, dry electrode systems cannot be used for recording complete ECG waveform, EEG or measurement of bioimpedance. Because of their improved sensitivity these hybrid nanostructured dry electrodes can be applied to measurement of ECG and bioimpedance with very low baseline noise. These textile based electrodes can be seamlessly integrated into garments of daily use such as vests and bra. In combination with embedded wireless network device that can communicate with smart phone, laptop or GPRS, they can function as wearable wireless health diagnostic systems.

  2. 一种可抗TCPFlooding攻击的网络流量监测机制①%Network Monitoring Machine Against TCP Flooding Attacks

    Institute of Scientific and Technical Information of China (English)

    2013-01-01

      DDoS攻击是互联网的主要安全威胁之一,而大部分DDoS攻击工具都使用TCP Flooding攻击方式,基于大量研究相关技术的基础上,提出了一种可用于局域网的网络流量监测机制,可以有效的检测出TCP Flooding攻击,解决当前各种网络安全设备在此方面存在的问题。%DDoS attacks are a major threat to internet and almost all of DDoS attacker use TCP Flooding attacks. Based on lots of studying, a network monitoring machine is presented. The machine can detect TCP Flooding attacks for local area network and solve problems of other security production.

  3. Flexible High Energy-Conversion Sensing Materials for Structural Health Monitoring Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The applicant is developing flexible highly-efficient piezoelectric materials for use in structural health monitoring (SHM) as contemplated in the solicitation...

  4. Highly Reliable Structural Health Monitoring of Smart Composite Vanes for Jet Engine Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Intelligent Fiber Optic Systems and Auburn University propose a Fiber Bragg Grating (FBG) integrated Structural Health Monitoring (SHM) sensor system capable of...

  5. Highly Reliable Structural Health Monitoring of Smart Composite Vanes for Jet Engine Project

    Data.gov (United States)

    National Aeronautics and Space Administration — In Phase 1, Intelligent Fiber Optic Systems (IFOS) successfully demonstrated a Fiber Bragg Grating (FBG) based integrated Structural Health Monitoring (SHM) sensor...

  6. Structural Health Monitoring with Fiber Bragg Grating and Piezo Arrays Project

    Data.gov (United States)

    National Aeronautics and Space Administration — IFOS and its research institute collaborator, Washington State University (WSU), have demonstrated feasibility of a structural health monitoring (SHM) system for...

  7. A methodological review of piezoelectric based acoustic wave generation and detection techniques for structural health monitoring

    National Research Council Canada - National Science Library

    Sun, Z; Rocha, B; Wu, K.-T; Mrad, N

    2013-01-01

    .... As condition based maintenance has emerged as a valuable approach to enhancing continued aircraft airworthiness while reducing the life cycle cost, its enabling structural health monitoring (SHM...

  8. Data gateway for prognostic health monitoring of ocean-based power generation

    Science.gov (United States)

    Gundel, Joseph

    On August 5, 2010 the U.S. Department of Energy (DOE) has designated the Center for Ocean Energy Technology (COET) at Florida Atlantic University (FAU) as a national center for ocean energy research and development. Their focus is the research and development of open-ocean current systems and associated infrastructure needed to development and testing prototypes. The generation of power is achieved by using a specialized electric generator with a rotor called a turbine. As with all machines, the turbines will need maintenance and replacement as they near the end of their lifecycle. This prognostic health monitoring (PHM) requires data to be collected, stored, and analyzed in order to maximize the lifespan, reduce downtime and predict when failure is eminent. This thesis explores the use of a data gateway which will separate high level software with low level hardware including sensors and actuators. The gateway will standardize and store the data collected from various sensors with different speeds, formats, and interfaces allowing an easy and uniform transition to a database system for analysis.

  9. 基于机床做功量的监控系统开发%Development of Monitoring System Based on the Work Load of Machine Tool

    Institute of Scientific and Technical Information of China (English)

    李平; 黄泽森

    2013-01-01

    在分析机床维护保养不良是影响机床可靠性的关键因素的基础上,将一种新的可靠性思想——用户监控维护方法引入数控机床可靠性研究领域中.提出了机床定功维护的概念,并以丝杆螺母副维护保养为例,建立了丝杆螺母副与电机做功关系的数学模型.给出了主轴电机功率的获取方法,并通过对数控系统西门子840D进行二次编程,开发了基于用户角度来提高机床可靠性的用户监控维护系统.该系统在数控机床上的成功应用为机床可靠性的研究提供了一种新的思路和方法.%On the basis of poor maintenance of NC machine tool is the key factor of influencing the machine tool reliability, a new method which called User Monitor and Maintenance was introduced, and a creational concept of maintenance based on work to the field of NC machine reliability research was put forward. By the example of maintenance of ball screw and nut, the math model between the ball screw and nut, and the work of electromotor was established. The method of obtaining power of main spindle motor was given, and the System of User Monitor and Maintenance based on secondary development of NC Simens 840D system by users to improve the reliability of NC machine tool was developed. The successful application of the system on the NC machine tool provides a new method and idea for the research of NC machine tool's reliability.

  10. Active sensors for health monitoring of aging aerospace structures

    Energy Technology Data Exchange (ETDEWEB)

    GIURGIUTIU,VICTOR; REDMOND,JAMES M.; ROACH,DENNIS P.; RACKOW,KIRK A.

    2000-02-29

    A project to develop non-intrusive active sensors that can be applied on existing aging aerospace structures for monitoring the onset and progress of structural damage (fatigue cracks and corrosion) is presented. The state of the art in active sensors structural health monitoring and damage detection is reviewed. Methods based on (a) elastic wave propagation and (b) electro-mechanical (E/M) impedance technique are cited and briefly discussed. The instrumentation of these specimens with piezoelectric active sensors is illustrated. The main detection strategies (E/M impedance for local area detection and wave propagation for wide area interrogation) are discussed. The signal processing and damage interpretation algorithms are tuned to the specific structural interrogation method used. In the high-frequency E/M impedance approach, pattern recognition methods are used to compare impedance signatures taken at various time intervals and to identify damage presence and progression from the change in these signatures. In the wave propagation approach, the acousto-ultrasonic methods identifying additional reflection generated from the damage site and changes in transmission velocity and phase are used. Both approaches benefit from the use of artificial intelligence neural networks algorithms that can extract damage features based on a learning process. Design and fabrication of a set of structural specimens representative of aging aerospace structures is presented. Three built-up specimens (pristine, with cracks, and with corrosion damage) are used. The specimen instrumentation with active sensors fabricated at the University of South Carolina is illustrated. Preliminary results obtained with the E/M impedance method on pristine and cracked specimens are presented.

  11. Building a Successful Machine Safeguarding Program

    Energy Technology Data Exchange (ETDEWEB)

    McConnell, S

    2003-03-06

    Safeguarding hazards associated with machines is a goal common to all health and safety professionals. Whether the individual is new to the safety field or has held associated responsibilities for a period of time, safeguarding personnel who work with or around machine tools and equipment should be considered an important aspect of the job. Although significant progress has been made in terms of safeguarding machines since the era prior to the organized safety movement, companies continue to be cited by the Occupational Safety and Health Administration (OSHA) and workers continue to be injured, even killed by machine tools and equipment. In the early 1900s, it was common practice to operate transmission machinery (gears, belts, pulleys, shafting, etc.) completely unguarded. At that time, the countersunk set screw used on shafting had not been invented and projecting set screws were involved in many horrific accidents. Manufacturers built machines with little regard for worker safety. Workers were killed or seriously injured before definitive actions were taken to improve safety in the workplace. Many states adopted legislation aimed at requiring machine guarding and improved injury reduction. The first patent for a machine safeguard was issued in 1868 for a mechanical interlock. Other patents followed. As methods for safeguarding machinery and tools were developed, standards were written and programs were set up to monitor factories for compliance. Many of those standards continue to govern how we protect workers today. It is common to see machine tools built in the forties, fifties and sixties being used in machine shops today. In terms of safeguarding, these machines may be considered poorly designed, improperly safeguarded or simply unguarded. In addition to the potential threat of an OSHA citation, these conditions expose the operator to serious hazards that must be addressed. The safety professional can help line management determine workable solutions for

  12. Advanced instrumentation for acousto-ultrasonic based structural health monitoring

    Science.gov (United States)

    Smithard, Joel; Galea, Steve; van der Velden, Stephen; Powlesland, Ian; Jung, George; Rajic, Nik

    2016-04-01

    Structural health monitoring (SHM) systems using structurally-integrated sensors potentially allow the ability to inspect for damage in aircraft structures on-demand and could provide a basis for the development of condition-based maintenance approaches for airframes. These systems potentially offer both substantial cost savings and performance improvements over conventional nondestructive inspection (NDI). Acousto-ultrasonics (AU), using structurallyintegrated piezoelectric transducers, offers a promising basis for broad-field damage detection in aircraft structures. For these systems to be successfully applied in the field the hardware for AU excitation and interrogation needs to be easy to use, compact, portable, light and, electrically and mechanically robust. Highly flexible and inexpensive instrumentation for basic background laboratory investigations is also required to allow researchers to tackle the numerous scientific and engineering issues associated with AU based SHM. The Australian Defence Science and Technology Group (DST Group) has developed the Acousto Ultrasonic Structural health monitoring Array Module (AUSAM+), a compact device for AU excitation and interrogation. The module, which has the footprint of a typical current generation smart phone, provides autonomous control of four send and receive piezoelectric elements, which can operate in pitch-catch or pulse-echo modes and can undertake electro-mechanical impedance measurements for transducer and structural diagnostics. Modules are designed to operate synchronously with other units, via an optical link, to accommodate larger transducer arrays. The module also caters for fibre optic sensing of acoustic waves with four intensity-based optical inputs. Temperature and electrical resistance strain gauge inputs as well as external triggering functionality are also provided. The development of a Matlab hardware object allows users to easily access the full hardware functionality of the device and

  13. Structural health monitoring of compression connectors for overhead transmission lines

    Science.gov (United States)

    Wang, Hong; Wang, Jy-An John; Swindeman, Joseph P.; Ren, Fei; Chan, John

    2017-04-01

    Two-stage aluminum conductor steel-reinforced (ACSR) compression connectors are extensively used in US overhead transmission lines. The connectors are made by crimping a steel sleeve onto a steel core and an aluminum sleeve over electrical conducting aluminum strands. The connectors are designed to operate at temperatures up to 125°C, but their performance is increasingly degrading because of overloading of lines. Currently, electric utilities conduct routine line inspections using thermal and electrical measurements, but these methods do not provide information about the structural integrity of connectors. In this work, structural health monitoring (SHM) of compression connectors was studied using electromechanical impedance (EMI) analysis. Lead zirconate titanate (PZT)-5A was identified as a smart material for SHM. A flexible high-temperature bonding layer was used to address challenges in PZT integration due to a significant difference in the coefficients of thermal expansion of PZT and the aluminum substrate. The steel joint on the steel core was investigated because it is responsible for the ultimate tensile strength of the connector. Tensile testing was used to induce structural damage to the joint, or steel core pullout, and thermal cycling introduced additional structural perturbations. EMI measurements were conducted between the tests. The root mean square deviation (RMSD) of EMI was identified as a damage index. The use of steel joints has been shown to enable SHM under simulated conditions. The EMI signature is sensitive to variations in structural conditions. RMSD can be correlated to the structural health of a connector and has potential for use in the SHM and structural integrity evaluation.

  14. Machine medical ethics

    CERN Document Server

    Pontier, Matthijs

    2015-01-01

    The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

  15. A ride in the time machine: information management capabilities health departments will need

    National Research Council Canada - National Science Library

    Foldy, Seth; Grannis, Shaun; Ross, David; Smith, Torney

    2014-01-01

    .... Developments in electronic health records, interoperability and information exchange, public information sharing, decision support, and cloud technologies can support information management if health...

  16. Improved Stochastic Subspace System Identification for Structural Health Monitoring

    Science.gov (United States)

    Chang, Chia-Ming; Loh, Chin-Hsiung

    2015-07-01

    Structural health monitoring acquires structural information through numerous sensor measurements. Vibrational measurement data render the dynamic characteristics of structures to be extracted, in particular of the modal properties such as natural frequencies, damping, and mode shapes. The stochastic subspace system identification has been recognized as a power tool which can present a structure in the modal coordinates. To obtain qualitative identified data, this tool needs to spend computational expense on a large set of measurements. In study, a stochastic system identification framework is proposed to improve the efficiency and quality of the conventional stochastic subspace system identification. This framework includes 1) measured signal processing, 2) efficient space projection, 3) system order selection, and 4) modal property derivation. The measured signal processing employs the singular spectrum analysis algorithm to lower the noise components as well as to present a data set in a reduced dimension. The subspace is subsequently derived from the data set presented in a delayed coordinate. With the proposed order selection criteria, the number of structural modes is determined, resulting in the modal properties. This system identification framework is applied to a real-world bridge for exploring the feasibility in real-time applications. The results show that this improved system identification method significantly decreases computational time, while qualitative modal parameters are still attained.

  17. Energy Harvesting for Structural Health Monitoring Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Park, G.; Farrar, C. R.; Todd, M. D.; Hodgkiss, T.; Rosing, T.

    2007-02-26

    This report has been developed based on information exchanges at a 2.5-day workshop on energy harvesting for embedded structural health monitoring (SHM) sensing systems that was held June 28-30, 2005, at Los Alamos National Laboratory. The workshop was hosted by the LANL/UCSD Engineering Institute (EI). This Institute is an education- and research-focused collaboration between Los Alamos National Laboratory (LANL) and the University of California, San Diego (UCSD), Jacobs School of Engineering. A Statistical Pattern Recognition paradigm for SHM is first presented and the concept of energy harvesting for embedded sensing systems is addressed with respect to the data acquisition portion of this paradigm. Next, various existing and emerging sensing modalities used for SHM and their respective power requirements are summarized, followed by a discussion of SHM sensor network paradigms, power requirements for these networks and power optimization strategies. Various approaches to energy harvesting and energy storage are discussed and limitations associated with the current technology are addressed. This discussion also addresses current energy harvesting applications and system integration issues. The report concludes by defining some future research directions and possible technology demonstrations that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes.

  18. Bridges analysis, design, structural health monitoring, and rehabilitation

    CERN Document Server

    Bakht, Baidar

    2015-01-01

    This book offers a valuable guide for practicing bridge engineers and graduate students in structural engineering; its main purpose is to present the latest concepts in bridge engineering in fairly easy-to-follow terms. The book provides details of easy-to-use computer programs for: ·      Analysing slab-on-girder bridges for live load distribution. ·      Analysing slab and other solid bridge components for live load distribution. ·      Analysing and designing concrete deck slab overhangs of girder bridges under vehicular loads. ·      Determining the failure loads of concrete deck slabs of girder bridges under concentrated wheel loads. In addition, the book includes extensive chapters dealing with the design of wood bridges and soil-steel bridges. Further, a unique chapter on structural health monitoring (SHM) will help bridge engineers determine the actual load carrying capacities of bridges, as opposed to their perceived analytical capacities. The chapter addressing structures...

  19. Defect classification in sparsity-based structural health monitoring

    Science.gov (United States)

    Golato, Andrew; Ahmad, Fauzia; Santhanam, Sridhar; Amin, Moeness G.

    2017-05-01

    Guided waves have gained popularity in structural health monitoring (SHM) due to their ability to inspect large areas with little attenuation, while providing rich interactions with defects. For thin-walled structures, the propagating waves are Lamb waves, which are a complex but well understood type of guided waves. Recent works have cast the defect localization problem of Lamb wave based SHM within the sparse reconstruction framework. These methods make use of a linear model relating the measurements with the scene reflectivity under the assumption of point-like defects. However, most structural defects are not perfect points but tend to assume specific forms, such as surface cracks or internal cracks. Knowledge of the "type" of defects is useful in the assessment phase of SHM. In this paper, we present a dual purpose sparsity-based imaging scheme which, in addition to accurately localizing defects, properly classifies the defects present simultaneously. The proposed approach takes advantage of the bias exhibited by certain types of defects toward a specific Lamb wave mode. For example, some defects strongly interact with the anti-symmetric modes, while others strongly interact with the symmetric modes. We build model based dictionaries for the fundamental symmetric and anti-symmetric wave modes, which are then utilized in unison to properly localize and classify the defects present. Simulated data of surface and internal defects in a thin Aluminum plate are used to validate the proposed scheme.

  20. Simultaneous excitation system for efficient guided wave structural health monitoring

    Science.gov (United States)

    Hua, Jiadong; Michaels, Jennifer E.; Chen, Xin; Lin, Jing

    2017-10-01

    Many structural health monitoring systems utilize guided wave transducer arrays for defect detection and localization. Signals are usually acquired using the ;pitch-catch; method whereby each transducer is excited in turn and the response is received by the remaining transducers. When extensive signal averaging is performed, the data acquisition process can be quite time-consuming, especially for metallic components that require a low repetition rate to allow signals to die out. Such a long data acquisition time is particularly problematic if environmental and operational conditions are changing while data are being acquired. To reduce the total data acquisition time, proposed here is a methodology whereby multiple transmitters are simultaneously triggered, and each transmitter is driven with a unique excitation. The simultaneously transmitted waves are captured by one or more receivers, and their responses are processed by dispersion-compensated filtering to extract the response from each individual transmitter. The excitation sequences are constructed by concatenating a series of chirps whose start and stop frequencies are randomly selected from a specified range. The process is optimized using a Monte-Carlo approach to select sequences with impulse-like autocorrelations and relatively flat cross-correlations. The efficacy of the proposed methodology is evaluated by several metrics and is experimentally demonstrated with sparse array imaging of simulated damage.

  1. A Wireless Laser Displacement Sensor Node for Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Se Woon Choi

    2013-09-01

    Full Text Available This study describes a wireless laser displacement sensor node that measures displacement as a representative damage index for structural health monitoring (SHM. The proposed measurement system consists of a laser displacement sensor (LDS and a customized wireless sensor node. Wireless communication is enabled by a sensor node that consists of a sensor module, a code division multiple access (CDMA communication module, a processor, and a power module. An LDS with a long measurement distance is chosen to increase field applicability. For a wireless sensor node driven by a battery, we use a power control module with a low-power processor, which facilitates switching between the sleep and active modes, thus maximizing the power consumption efficiency during non-measurement and non-transfer periods. The CDMA mode is also used to overcome the limitation of communication distance, which is a challenge for wireless sensor networks and wireless communication. To evaluate the reliability and field applicability of the proposed wireless displacement measurement system, the system is tested onsite to obtain the required vertical displacement measurements during the construction of mega-trusses and an edge truss, which are the primary structural members in a large-scale irregular building currently under construction. The measurement values confirm the validity of the proposed wireless displacement measurement system and its potential for use in safety evaluations of structural elements.

  2. A wireless laser displacement sensor node for structural health monitoring.

    Science.gov (United States)

    Park, Hyo Seon; Kim, Jong Moon; Choi, Se Woon; Kim, Yousok

    2013-09-30

    This study describes a wireless laser displacement sensor node that measures displacement as a representative damage index for structural health monitoring (SHM). The proposed measurement system consists of a laser displacement sensor (LDS) and a customized wireless sensor node. Wireless communication is enabled by a sensor node that consists of a sensor module, a code division multiple access (CDMA) communication module, a processor, and a power module. An LDS with a long measurement distance is chosen to increase field applicability. For a wireless sensor node driven by a battery, we use a power control module with a low-power processor, which facilitates switching between the sleep and active modes, thus maximizing the power consumption efficiency during non-measurement and non-transfer periods. The CDMA mode is also used to overcome the limitation of communication distance, which is a challenge for wireless sensor networks and wireless communication. To evaluate the reliability and field applicability of the proposed wireless displacement measurement system, the system is tested onsite to obtain the required vertical displacement measurements during the construction of mega-trusses and an edge truss, which are the primary structural members in a large-scale irregular building currently under construction. The measurement values confirm the validity of the proposed wireless displacement measurement system and its potential for use in safety evaluations of structural elements.

  3. Applications of nonlinear system identification to structural health monitoring.

    Energy Technology Data Exchange (ETDEWEB)

    Farrar, C. R. (Charles R.); Sohn, H. (Hoon); Robertson, A. N. (Amy N.)

    2004-01-01

    The process of implementing a damage detection strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). In many cases damage causes a structure that initially behaves in a predominantly linear manner to exhibit nonlinear response when subject to its operating environment. The formation of cracks that subsequently open and close under operating loads is an example of such damage. The damage detection process can be significantly enhanced if one takes advantage of these nonlinear effects when extracting damage-sensitive features from measured data. This paper will provide an overview of nonlinear system identification techniques that are used for the feature extraction process. Specifically, three general approaches that apply nonlinear system identification techniques to the damage detection process are discussed. The first two approaches attempt to quantify the deviation of the system from its initial linear characteristics that is a direct result of damage. The third approach is to extract features from the data that are directly related to the specific nonlinearity associated with the damaged condition. To conclude this discussion, a summary of outstanding issues associated with the application of nonlinear system identification techniques to the SHM problem is presented.

  4. A Model-Driven Framework to Develop Personalized Health Monitoring

    Directory of Open Access Journals (Sweden)

    Algimantas Venčkauskas

    2016-07-01

    Full Text Available Both distributed healthcare systems and the Internet of Things (IoT are currently hot topics. The latter is a new computing paradigm to enable advanced capabilities in engineering various applications, including those for healthcare. For such systems, the core social requirement is the privacy/security of the patient information along with the technical requirements (e.g., energy consumption and capabilities for adaptability and personalization. Typically, the functionality of the systems is predefined by the patient’s data collected using sensor networks along with medical instrumentation; then, the data is transferred through the Internet for treatment and decision-making. Therefore, systems creation is indeed challenging. In this paper, we propose a model-driven framework to develop the IoT-based prototype and its reference architecture for personalized health monitoring (PHM applications. The framework contains a multi-layered structure with feature-based modeling and feature model transformations at the top and the application software generation at the bottom. We have validated the framework using available tools and developed an experimental PHM to test some aspects of the functionality of the reference architecture in real time. The main contribution of the paper is the development of the model-driven computational framework with emphasis on the synergistic effect of security and energy issues.

  5. PVDF Multielement Lamb Wave Sensor for Structural Health Monitoring.

    Science.gov (United States)

    Ren, Baiyang; Lissenden, Cliff J

    2016-01-01

    The characteristics of Lamb waves, which are multimodal and dispersive, provide both challenges and opportunities for structural health monitoring (SHM). Methods for nondestructive testing with Lamb waves are well established. For example, mode content can be determined by moving a sensor to different positions and then transforming the spatial-temporal data into the wavenumber-frequency domain. This mode content information is very useful because at every frequency each mode has a unique wavestructure, which is largely responsible for its sensitivity to material damage. Furthermore, mode conversion occurs when the waves interact with damage, making mode content an excellent damage detection feature. However, in SHM, the transducers are typically at fixed locations and are immovable. Here, an affixed polyvinylidene fluoride (PVDF) multielement sensor is shown to provide these same capabilities. The PVDF sensor is bonded directly to the waveguide surface, conforms to curved surfaces, has low mass, low profile, low cost, and minimal influence on passing Lamb waves. While the mode receivability is dictated by the sensor being located on the surface of the waveguide, both symmetric and antisymmetric modes can be detected and group velocities measured.

  6. Temperature effects in ultrasonic Lamb wave structural health monitoring systems.

    Science.gov (United States)

    Lanza di Scalea, Francesco; Salamone, Salvatore

    2008-07-01

    There is a need to better understand the effect of temperature changes on the response of ultrasonic guided-wave pitch-catch systems used for structural health monitoring. A model is proposed to account for all relevant temperature-dependent parameters of a pitch-catch system on an isotropic plate, including the actuator-plate and plate-sensor interactions through shear-lag behavior, the piezoelectric and dielectric permittivity properties of the transducers, and the Lamb wave dispersion properties of the substrate plate. The model is used to predict the S(0) and A(0) response spectra in aluminum plates for the temperature range of -40-+60 degrees C, which accounts for normal aircraft operations. The transducers examined are monolithic PZT-5A [PZT denotes Pb(Zr-Ti)O3] patches and flexible macrofiber composite type P1 patches. The study shows substantial changes in Lamb wave amplitude response caused solely by temperature excursions. It is also shown that, for the transducers considered, the response amplitude changes follow two opposite trends below and above ambient temperature (20 degrees C), respectively. These results can provide a basis for the compensation of temperature effects in guided-wave damage detection systems.

  7. Fundamental modeling issues on benchmark structure for structural health monitoring

    Institute of Scientific and Technical Information of China (English)

    HU; Sau-Lon; James

    2009-01-01

    The IASC-ASCE Structural Health Monitoring Task Group developed a series of benchmark problems, and participants of the benchmark study were charged with using a 12-degree-of-freedom (DOF) shear building as their identification model. The present article addresses improperness, including the parameter and modeling errors, of using this particular model for the intended purpose of damage detec- tion, while the measurements of damaged structures are synthesized from a full-order finite-element model. In addressing parameter errors, a model calibration procedure is utilized to tune the mass and stiffness matrices of the baseline identification model, and a 12-DOF shear building model that preserves the first three modes of the full-order model is obtained. Sequentially, this calibrated model is employed as the baseline model while performing the damage detection under various damage scenarios. Numerical results indicate that the 12-DOF shear building model is an over-simplified identification model, through which only idealized damage situations for the benchmark structure can be detected. It is suggested that a more sophisticated 3-dimensional frame structure model should be adopted as the identification model, if one intends to detect local member damages correctly.

  8. Structural Health Monitoring under Nonlinear Environmental or Operational Influences

    Directory of Open Access Journals (Sweden)

    Jyrki Kullaa

    2014-01-01

    Full Text Available Vibration-based structural health monitoring is based on detecting changes in the dynamic characteristics of the structure. It is well known that environmental or operational variations can also have an influence on the vibration properties. If these effects are not taken into account, they can result in false indications of damage. If the environmental or operational variations cause nonlinear effects, they can be compensated using a Gaussian mixture model (GMM without the measurement of the underlying variables. The number of Gaussian components can also be estimated. For the local linear components, minimum mean square error (MMSE estimation is applied to eliminate the environmental or operational influences. Damage is detected from the residuals after applying principal component analysis (PCA. Control charts are used for novelty detection. The proposed approach is validated using simulated data and the identified lowest natural frequencies of the Z24 Bridge under temperature variation. Nonlinear models are most effective if the data dimensionality is low. On the other hand, linear models often outperform nonlinear models for high-dimensional data.

  9. Statistical Pattern-Based Assessment of Structural Health Monitoring Data

    Directory of Open Access Journals (Sweden)

    Mohammad S. Islam

    2014-01-01

    Full Text Available In structural health monitoring (SHM, various sensors are installed at critical locations of a structure. The signals from sensors are either continuously or periodically analyzed to determine the state and performance of the structure. An objective comparison of the sensor data at different time ranges is essential for assessing the structural condition or excessive load experienced by the structure which leads to potential damage in the structure. The objectives of the current study are to establish a relationship between the data from various sensors to estimate the reliability of the data and potential damage using the statistical pattern matching techniques. In order to achieve these goals, new methodologies based on statistical pattern recognition techniques have been developed. The proposed methodologies have been developed and validated using sensor data obtained from an instrumented bridge and road test data from heavy vehicles. The application of statistical pattern matching techniques are relatively new in SHM data interpretation and current research demonstrates that it has high potential in assessing structural conditions, especially when the data are noisy and susceptible to environmental disturbances.

  10. On Assessing the Robustness of Structural Health Monitoring Technologies

    Energy Technology Data Exchange (ETDEWEB)

    Stull, Christopher J. [Los Alamos National Laboratory; Hemez, Francois M. [Los Alamos National Laboratory; Farrar, Charles R. [Los Alamos National Laboratory

    2012-08-24

    As Structural Health Monitoring (SHM) continues to gain popularity, both as an area of research and as a tool for use in industrial applications, the number of technologies associated with SHM will also continue to grow. As a result, the engineer tasked with developing a SHM system is faced with myriad hardware and software technologies from which to choose, often adopting an ad hoc qualitative approach based on physical intuition or past experience to making such decisions. This paper offers a framework that aims to provide the engineer with a quantitative approach for choosing from among a suite of candidate SHM technologies. The framework is outlined for the general case, where a supervised learning approach to SHM is adopted, and the presentation will focus on applying the framework to two commonly encountered problems: (1) selection of damage-sensitive features and (2) selection of a damage classifier. The data employed for these problems will be drawn from a study that examined the feasibility of applying SHM to the RAPid Telescopes for Optical Response observatory network.

  11. Health monitoring studies on composite structures for aerospace applications

    Energy Technology Data Exchange (ETDEWEB)

    James, G.; Roach, D.; Hansche, B.; Meza, R.; Robinson, N.

    1996-02-01

    This paper discusses ongoing work to develop structural health monitoring techniques for composite aerospace structures such as aircraft control surfaces, fuselage sections or repairs, and reusable launch vehicle fuel tanks. The overall project is divided into four tasks: Operational evaluation, diagnostic measurements, information condensation, and damage detection. Five composite plates were constructed to study delaminations, disbonds, and fluid retention issues as the initial step in creating an operational system. These four square feet plates were graphite-epoxy with nomex honeycomb cores. The diagnostic measurements are composed of modal tests with a scanning laser vibrometer at over 500 scan points per plate covering the frequency range up to 2000 Hz. This data has been reduced into experimental dynamics matrices using a generic, software package developed at the University of Colorado at Boulder. The continuing effort will entail performing a series of damage identification studies to detect, localize, and determine the extent of the damage. This work is providing understanding and algorithm development for a global NDE technique for composite aerospace structures.

  12. Fundamental modeling issues on benchmark structure for structural health monitoring

    Institute of Scientific and Technical Information of China (English)

    LI HuaJun; ZHANG Min; WANG JunRong; HU Sau-Lon James

    2009-01-01

    The IASC-ASCE Structural Health Monitoring Task Group developed a series of benchmark problems,and participants of the benchmark study were charged with using a 12-degree-of-freedom (DOF) shear building as their identification model. The present article addresses improperness, including the parameter and modeling errors, of using this particular model for the intended purpose of damage detection, while the measurements of damaged structures are synthesized from a full-order finite-element model. In addressing parameter errors, a model calibration procedure is utilized to tune the mass and stiffness matrices of the baseline identification model, and a 12-DOF shear building model that preserves the first three modes of the full-order model is obtained. Sequentially, this calibrated model is employed as the baseline model while performing the damage detection under various damage scenarios. Numerical results indicate that the 12-DOF shear building model is an over-simplified identification model, through which only idealized damage situations for the benchmark structure can be detected. It is suggested that a more sophisticated 3-dimensional frame structure model should be adopted as the identification model, if one intends to detect local member damages correctly.

  13. Phase Space Dissimilarity Measures for Structural Health Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Bubacz, Jacob A [ORNL; Chmielewski, Hana T [ORNL; Pape, Alexander E [ORNL; Depersio, Andrew J [ORNL; Hively, Lee M [ORNL; Abercrombie, Robert K [ORNL; Boone, Shane [ORNL

    2011-11-01

    A novel method for structural health monitoring (SHM), known as the Phase Space Dissimilarity Measures (PSDM) approach, is proposed and developed. The patented PSDM approach has already been developed and demonstrated for a variety of equipment and biomedical applications. Here, we investigate SHM of bridges via analysis of time serial accelerometer measurements. This work has four aspects. The first is algorithm scalability, which was found to scale linearly from one processing core to four cores. Second, the same data are analyzed to determine how the use of the PSDM approach affects sensor placement. We found that a relatively low-density placement sufficiently captures the dynamics of the structure. Third, the same data are analyzed by unique combinations of accelerometer axes (vertical, longitudinal, and lateral with respect to the bridge) to determine how the choice of axes affects the analysis. The vertical axis is found to provide satisfactory SHM data. Fourth, statistical methods were investigated to validate the PSDM approach for this application, yielding statistically significant results.

  14. Health Monitor for Multitasking, Safety-Critical, Real-Time Software

    Science.gov (United States)

    Zoerner, Roger

    2011-01-01

    Health Manager can detect Bad Health prior to a failure occurring by periodically monitoring the application software by looking for code corruption errors, and sanity-checking each critical data value prior to use. A processor s memory can fail and corrupt the software, or the software can accidentally write to the wrong address and overwrite the executing software. This innovation will continuously calculate a checksum of the software load to detect corrupted code. This will allow a system to detect a failure before it happens. This innovation monitors each software task (thread) so that if any task reports "bad health," or does not report to the Health Manager, the system is declared bad. The Health Manager reports overall system health to the outside world by outputting a square wave signal. If the square wave stops, this indicates that system health is bad or hung and cannot report. Either way, "bad health" can be detected, whether caused by an error, corrupted data, or a hung processor. A separate Health Monitor Task is started and run periodically in a loop that starts and stops pending on a semaphore. Each monitored task registers with the Health Manager, which maintains a count for the task. The registering task must indicate if it will run more or less often than the Health Manager. If the task runs more often than the Health Manager, the monitored task calls a health function that increments the count and verifies it did not go over max-count. When the periodic Health Manager runs, it verifies that the count did not go over the max-count and zeroes it. If the task runs less often than the Health Manager, the periodic Health Manager will increment the count. The monitored task zeroes the count, and both the Health Manager and monitored task verify that the count did not go over the max-count.

  15. Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

    Science.gov (United States)

    2004-01-01

    Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate

  16. VA Health Care: Processes to Evaluate, Implement, and Monitor Organizational Structure Changes Needed

    Science.gov (United States)

    2016-09-01

    VA HEALTH CARE Processes to Evaluate, Implement, and Monitor Organizational Structure Changes Needed Report to...Monitor Organizational Structure Changes Needed What GAO Found Recent internal and external reviews of Veterans Health Administration (VHA...operations have identified deficiencies in its organizational structure and recommended changes that would require significant restructuring to address

  17. Tunable Laser Development for In-flight Fiber Optic Based Structural Health Monitoring Systems

    Science.gov (United States)

    Richards, Lance; Parker, Allen; Chan, Patrick

    2014-01-01

    The objective of this task is to investigate, develop, and demonstrate a low-cost swept lasing light source for NASA DFRC's fiber optics sensing system (FOSS) to perform structural health monitoring on current and future aerospace vehicles. This is the regular update of the Tunable Laser Development for In-flight Fiber Optic Based Structural Health Monitoring Systems website.

  18. Design of an embedded health monitoring infrastructure for accessing multi-processor soc degradation

    NARCIS (Netherlands)

    Kerkhoff, Hans G.; Zhao, Yong

    An embedded health-monitoring infrastructure for a highly reliable MP-SoC for data-streaming systems is presented. Different from the traditional approach of a dependable design, our infrastructure is based on life-time prognostics from health- monitoring sensors that are embedded near the target

  19. A ride in the time machine: information management capabilities health departments will need.

    Science.gov (United States)

    Foldy, Seth; Grannis, Shaun; Ross, David; Smith, Torney

    2014-09-01

    We have proposed needed information management capabilities for future US health departments predicated on trends in health care reform and health information technology. Regardless of whether health departments provide direct clinical services (and many will), they will manage unprecedented quantities of sensitive information for the public health core functions of assurance and assessment, including population-level health surveillance and metrics. Absent improved capabilities, health departments risk vestigial status, with consequences for vulnerable populations. Developments in electronic health records, interoperability and information exchange, public information sharing, decision support, and cloud technologies can support information management if health departments have appropriate capabilities. The need for national engagement in and consensus on these capabilities and their importance to health department sustainability make them appropriate for consideration in the context of accreditation.

  20. National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors.

    Science.gov (United States)

    Schatz, Bruce R

    2015-12-01

    At the core of the healthcare crisis is fundamental lack of actionable data. Such data could stratify individuals within populations to predict which persons have which outcomes. If baselines existed for all variations of all conditions, then managing health could be improved by matching the measuring of individuals to their cohort in the population. The scale required for complete baselines involves effective National Surveys of Population Health (NSPH). Traditionally, these have been focused upon acute medicine, measuring people to contain the spread of epidemics. In recent decades, the focus has moved to chronic conditions as well, which require smaller measures over longer times. NSPH have long utilized quality of life questionnaires. Mobile Health Monitors, where computing technologies eliminate manual administration, provide richer data sets for health measurement. Older technologies of telephone interviews will be replaced by newer technologies of smartphone sensors to provide deeper individual measures at more frequent timings across larger-sized populations. Such continuous data can provide personal health records, supporting treatment guidelines specialized for population cohorts. Evidence-based medicine will become feasible by leveraging hundreds of millions of persons carrying mobile devices interacting with Internet-scale services for Big Data Analytics.

  1. New smart materials to address issues of structural health monitoring.

    Energy Technology Data Exchange (ETDEWEB)

    Chaplya, Pavel Mikhail

    2004-12-01

    Nuclear weapons and their storage facilities may benefit from in-situ structural health monitoring systems. Appending health-monitoring functionality to conventional materials and structures has been only marginally successful. The purpose of this project was to evaluate feasibility of a new smart material that includes self-sensing health monitoring functions similar to that of a nervous system of a living organism. Reviews of current efforts in the fields of heath-monitoring, nanotechnology, micro-electromechanical systems (MEMS), and wireless sensor networks were conducted. Limitations of the current nanotechnology methods were identified and new approaches were proposed to accelerate the development of self-sensing materials. Wireless networks of MEMS sensors have been researched as possible prototypes of self-sensing materials. Sensor networks were also examined as enabling technologies for dense data collection techniques to be used for validation of numerical methods and material parameter identification. Each grain of the envisioned material contains sensors that are connected in a dendritic manner similar to networks of neurons in a nervous system. Each sensor/neuron can communicate with the neighboring grains. Both the state of the sensor (on/off) and the quality of communication signal (speed/amplitude) should indicate not only a presence of a structural defect but the nature of the defect as well. For example, a failed sensor may represent a through-grain crack, while a lost or degraded communication link may represent an inter-granular crack. A technology to create such material does not exist. While recent progress in the fields of MEMS and nanotechnology allows to envision these new smart materials, it is unrealistic to expect creation of self-sensing materials in the near future. The current state of MEMS, nanotechnology, communication, sensor networks, and data processing technologies indicates that it will take more than ten years for the

  2. Recent Advances in Energy Harvesting Technologies for Structural Health Monitoring Applications

    OpenAIRE

    Joseph Davidson; Changki Mo

    2014-01-01

    This paper reviews recent developments in energy harvesting technologies for structural health monitoring applications. Many industries have a great deal of interest in obtaining technology that can be used to monitor the health of machinery and structures. In particular, the need for autonomous monitoring of structures has been ever-increasing in recent years. Autonomous SHM systems typically include embedded sensors, data acquisition, wireless communication, and energy harvesting systems. A...

  3. Data Processing Algorithms in Wireless Sensor Networks får Structural Health Monitoring

    OpenAIRE

    Danna, Nigatu Mitiku; Mekonnen, Esayas Getachew

    2012-01-01

    The gradual deterioration and failure of old buildings, bridges and other civil engineering structures invoked the need for Structural Health Monitoring (SHM) systems to develop a means to monitor the health of structures. Dozens of sensing, processing and monitoring mechanisms have been implemented and widely deployed with wired sensors. Wireless sensor networks (WSNs), on the other hand, are networks of large numbers of low cost wireless sensor nodes that communicate through a wireless medi...

  4. Systems Health Monitoring — From Ground to Air — The Aerospace Challenges

    Science.gov (United States)

    Austin, Mary

    2007-03-01

    The aerospace industry and the government are significantly investing in jet engine systems health monitoring. Government organizations such as the Air Force, Navy, Army, National Labs and NASA are investing in the development of state aware sensing for health monitoring of jet engines such as the Joint Strike Fighter, F119 and F100's. This paper will discuss on-going work in systems health monitoring for jet engines. Topics will include a general discussion of the approaches to engine structural health monitoring and the prognosis of engine component life. Real-world implementation challenges on the ground and in the air will be reviewed. The talk will conclude with a prediction of where engine health monitoring will be in twenty years.

  5. 健康监测的发展动态%Health monitoring development

    Institute of Scientific and Technical Information of China (English)

    张岩

    2009-01-01

    首先介绍了桥梁健康监测的概况,接着论述了桥梁健康监测系统的组成,然后阐述了桥梁健康监测系统在国内外的应用,最后对桥梁健康监测进行了展望,从而进一步改进桥梁健康监测技术.%It introduces the general situation of bridge health monitoring first, discusses the constitution of bridge health monitoring system, il-lustrates the application of bridge health monitoring system in country and abroad, and prospects bridge health monitoring, so as to further im-prove bridge health monitoring technology.

  6. 嵌入虚拟机监视器的高性能虚拟网络%High performance virtual network embedding virtual machine monitor

    Institute of Scientific and Technical Information of China (English)

    唐源; 夏磊; 崔峥; John Lange; Peter Dinda; Patrick Bridges; 李建平

    2012-01-01

    由虚拟机和嘘拟覆盖网相结合而构成的虚拟计算环境,在云计算和绿色计算中发挥非常重要的作用,然而,现有的虚拟计算环境在性能上难以满足高性能分布式计算的要求.设计和实现了一种高性能虚拟网络:VNET/P.基于网络第2层建立虚拟机互连模型,对一组虚拟机进行抽象,使其位于同一局域网中.与早期的用户层虚拟网络系统不同,VNET/P嵌入于可扩展、高性能的Palacios虚拟机监视器中.试验结果表明,VNET/P具有高带宽的特点,其性能接近于实际硬件的性能.%The virtual computing environment integrated with virtual machines (VMs) and virtual overlay networks possesses many important advantages in cloud computing and green computing. However, the un-negligible overhead of existing virtual networks prevents their vast use in high-performance distributed computing. This paper has designed and implemented a high-speed virtual network system VNET/P. VNET/P is a layer 2 network abstract for virtual machines, which enables a distributed collection of virtual machines to be maintained in a location independent way across wide-area network. Different from the existing virtual network in user layer, VNET/P is embedded into an open-sourced Palacios virtual machine monitor (VMM) , has much higher bandwidth and performance scalability, and achieves near-native performance and negligible overhead on lGbps Ethernet.

  7. Application of Wireless Monitoring System to Structural Health Monitoring of Long-Spanned Cable-Stayed Bridge

    Institute of Scientific and Technical Information of China (English)

    MENG Qing-cheng; QI Xin; Li Qiao

    2007-01-01

    The remote monitoring system applied to the construction control and health monitoring of the Nanjing Third Yangtze River Bridge is introduced. The system makes it possible to get the structure capabilities and environmental parameters of the bridge at the predetermined moment. It sends the collected data over a long distance to an assigned position for display and analysis. The related methods and working condition of the wireless monitoring system are discussed. The measured data during 48 h are employed to determine the feasibility for the closure of the bridge.

  8. Stennis Space Center's approach to liquid rocket engine health monitoring using exhaust plume diagnostics

    Science.gov (United States)

    Gardner, D. G.; Tejwani, G. D.; Bircher, F. E.; Loboda, J. A.; Van Dyke, D. B.; Chenevert, D. J.

    1991-01-01

    Details are presented of the approach used in a comprehensive program to utilize exhaust plume diagnostics for rocket engine health-and-condition monitoring and assessing SSME component wear and degradation. This approach incorporates both spectral and video monitoring of the exhaust plume. Video monitoring provides qualitative data for certain types of component wear while spectral monitoring allows both quantitative and qualitative information. Consideration is given to spectral identification of SSME materials and baseline plume emissions.

  9. Automated Impedance Tomography for Monitoring Permeable Reactive Barrier Health

    Energy Technology Data Exchange (ETDEWEB)

    LaBrecque, D J; Adkins, P L

    2009-07-02

    The objective of this research was the development of an autonomous, automated electrical geophysical monitoring system which allows for near real-time assessment of Permeable Reactive Barrier (PRB) health and aging and which provides this assessment through a web-based interface to site operators, owners and regulatory agencies. Field studies were performed at four existing PRB sites; (1) a uranium tailing site near Monticello, Utah, (2) the DOE complex at Kansas City, Missouri, (3) the Denver Federal Center in Denver, Colorado and (4) the Asarco Smelter site in East Helena, Montana. Preliminary surface data over the PRB sites were collected (in December, 2005). After the initial round of data collection, the plan was modified to include studies inside the barriers in order to better understand barrier aging processes. In September 2006 an autonomous data collection system was designed and installed at the EPA PRB and the electrode setups in the barrier were revised and three new vertical electrode arrays were placed in dedicated boreholes which were in direct contact with the PRB material. Final data were collected at the Kansas City, Denver and Monticello, Utah PRB sites in the fall of 2007. At the Asarco Smelter site in East Helena, Montana, nearly continuous data was collected by the autonomous monitoring system from June 2006 to November 2007. This data provided us with a picture of the evolution of the barrier, enabling us to examine barrier changes more precisely and determine whether these changes are due to installation issues or are normal barrier aging. Two rounds of laboratory experiments were carried out during the project. We conducted column experiments to investigate the effect of mineralogy on the electrical signatures resulting from iron corrosion and mineral precipitation in zero valent iron (ZVI) columns. In the second round of laboratory experiments we observed the electrical response from simulation of actual field PRBs at two sites: the

  10. Ultrasonic guided wave mechanics for composite material structural health monitoring

    Science.gov (United States)

    Gao, Huidong

    The ultrasonic guided wave based method is very promising for structural health monitoring of aging and modern aircraft. An understanding of wave mechanics becomes very critical for exploring the potential of this technology. However, the guided wave mechanics in complex structures, especially composite materials, are very challenging due to the nature of multi-layer, anisotropic, and viscoelastic behavior. The purpose of this thesis is to overcome the challenges and potentially take advantage of the complex wave mechanics for advanced sensor design and signal analysis. Guided wave mechanics is studied in three aspects, namely wave propagation, excitation, and damage sensing. A 16 layer quasi-isotropic composite with a [(0/45/90/-45)s]2 lay up sequence is used in our study. First, a hybrid semi-analytical finite element (SAFE) and global matrix method (GMM) is used to simulate guided wave propagation in composites. Fast and accurate simulation is achieved by using SAFE for dispersion curve generation and GMM for wave structure calculation. Secondly, the normal mode expansion (NME) technique is used for the first time to study the wave excitation characteristics in laminated composites. A clear and simple definition of wave excitability is put forward as a result of NME analysis. Source influence for guided wave excitation is plotted as amplitude on a frequency and phase velocity spectrum. This spectrum also provides a guideline for transducer design in guided wave excitation. The ultrasonic guided wave excitation characteristics in viscoelastic media are also studied for the first time using a modified normal mode expansion technique. Thirdly, a simple physically based feature is developed to estimate the guided wave sensitivity to damage in composites. Finally, a fuzzy logic decision program is developed to perform mode selection through a quantitative evaluation of the wave propagation, excitation and sensitivity features. Numerical simulation algorithms are

  11. Health Care Utilization and Expenditures Associated With Remote Monitoring in Patients With Implantable Cardiac Devices.

    Science.gov (United States)

    Ladapo, Joseph A; Turakhia, Mintu P; Ryan, Michael P; Mollenkopf, Sarah A; Reynolds, Matthew R

    2016-05-01

    Several randomized trials and decision analysis models have found that remote monitoring may reduce health care utilization and expenditures in patients with cardiac implantable electronic devices (CIEDs), compared with in-office monitoring. However, little is known about the generalizability of these findings to unselected populations in clinical practice. To compare health care utilization and expenditures associated with remote monitoring and in-office monitoring in patients with CIEDs, we used Truven Health MarketScan Commercial Claims and Medicare Supplemental Databases. We selected patients newly implanted with an implantable cardioverter defibrillators (ICD), cardiac resynchronization therapy defibrillator (CRT-D), or permanent pacemaker (PPM), in 2009, who had continuous health plan enrollment 2 years after implantation. Generalized linear models and propensity score matching were used to adjust for confounders and estimate differences in health care utilization and expenditures in patients with remote or in-office monitoring. We identified 1,127; 427; and 1,295 pairs of patients with a similar propensity for receiving an ICD, CRT-D, or PPM, respectively. Remotely monitored patients with ICDs experienced fewer emergency department visits resulting in discharge (p = 0.050). Remote monitoring was associated with lower health care expenditures in office visits among patients with PPMs (p = 0.025) and CRT-Ds (p = 0.006) and lower total inpatient and outpatient expenditures in patients with ICDs (p monitoring of patients with CIEDs may be associated with reductions in health care utilization and expenditures compared with exclusive in-office care.

  12. A correlation between pulse diagnosis of human body and health monitoring of structures

    Institute of Scientific and Technical Information of China (English)

    C.C.Chang; Henry T. Y. Yang

    2004-01-01

    The concept of health monitoring is a key aspect of the field of medicine that has been practiced for a long time. A commonly used diagnostic and health monitoring practice is pulse diagnosis, which can be traced back approximately five thousand years in the recorded history of China. With advances in the development of modem technology, the concept of health monitoring of a variety of engineering structures in several applications has begun to attract widespread attention.Of particular interest in this study is the health monitoring of civil structures. It seems natural, and even beneficial, that these two health-monitoring methods, one as applies to the human body and the other to civil structures, should be analyzed and compared. In this paper, the basic concepts and theories of the two monitoring methods are first discussed. Similarities are then summarized and commented upon. It is hoped that this correlation analysis may help provide structural engineers with some insights into the intrinsic concept of using pulse diagnosis in human health monitoring, which may be of some benefit in the development of modern structural health monitoring methods.

  13. Roller Bearing Health Monitoring Using CPLE Frequency Analysis Method

    Science.gov (United States)

    Jong, Jen-Yi; Jones, Jess H.

    2007-01-01

    This paper describes a unique vibration signature analysis technique Coherence Phase Line Enhancer (CPLE) Frequency Analysis - for roller bearing health monitoring. Defects of roller bearing (e.g. wear, foreign debris, crack in bearing supporting structure, etc.) can cause small bearing characteristic frequency shifts due to minor changes in bearing geometry. Such frequency shifts are often too small to detect by the conventional Power Spectral Density (PSD) due to its frequency bandwidth limitation. This Coherent Phase Line Enhancer technology has been evolving over the last few years and has culminated in the introduction of a new and novel frequency spectrum which is fully described in this paper. This CPLE technology uses a "key phasor" or speed probe as a preprocessor for this analysis. With the aid of this key phasor, this CPLE technology can develop a two dimensional frequency spectrum that preserves both amplitude and phase that is not normally obtained using conventional frequency analysis. This two-dimensional frequency transformation results in several newly defined spectral functions; i. e. CPLE-PSD, CPLE-Coherence and the CPLE-Frequency. This paper uses this CPLE frequency analysis to detect subtle, low level bearing related signals in the High Pressure Fuel Pump (HPFP) of the Space Shuttle Main Engine (SSME). For many rotating machinery applications, a key phasor is an essential measurement that is used in the detection of bearing related signatures. There are times however, when a key phasor is not available; i. e. during flight of any of the SSME turbopumps or on the SSME High Pressure Oxygen Turbopump (HPOTP) where no speed probe is present. In this case, the CPLE analysis approach can still be achieved using a novel Pseudo Key Phasor (PKP) technique to reconstruct a 1/Rev PKP signal directly from external vibration measurements. This paper develops this Pseudo Key Phasor technique and applies it to the SSME vibration data.

  14. Optical sensor for precision in-situ spindle health monitoring

    Science.gov (United States)

    Zhao, Rui

    An optical sensor which can record in-situ measurements of the dynamic runout of a precision miniature spindle system in a simple and low-cost manner is proposed in this dissertation. Spindle error measurement technology utilizes a cylindrical or spherical target artifact attached to the miniature spindle with non-contact sensors, typically capacitive sensors which are calibrated with a flat target surface not a curved target surface. Due to the different behavior of an electric field between a flat plate and a curved surface and an electric field between two flat plates, capacitive sensors is not suitable for measuring target surfaces smaller than its effective sensing area. The proposed sensor utilizes curved-edge diffraction (CED), which uses the effect of cylindrical surface curvature on the diffraction phenomenon in the transition regions adjacent to shadow, transmission, and reflection boundaries. The laser diodes light incident on the cylindrical surface of precision spindle and photodetectors collect the total field produced by the diffraction around the target surface. Laser diode in the different two direction are incident to the spindle shaft edges along the X and Y axes, four photodetectors collect the total fields produced by interference of multiple waves due to CED around the spindle shaft edges. The X and Y displacement can be obtained from the total fields using two differential amplifier configurations, respectively. Precision miniature spindle (shaft φ5.0mm) runout was measured, and the proposed sensor can perform curve at the different speed of rotation from 1500rpm to 8000rpm in the X and Y axes, respectively. On the other hand, CED also show changes for different running time and temperature of spindle. These results indicate that the proposed sensor promises to be effective for in-situ monitoring of the miniature spindle's health with high resolution, wide bandwidth, and low-cost.

  15. Development of a model based Structural-Health-Monitoring-Systems for condition monitoring of rotor blades; Entwicklung eines modellgestuetzten Structural-Health-Monitoring-Systems zur Zustandsueberwachung von Rotorblaettern

    Energy Technology Data Exchange (ETDEWEB)

    Ebert, C.; Friedmann, H.; Henkel, F.O. [Woelfel Beratende Ingenieure GmbH und Co.KG, Hoechberg (Germany); Frankenstein, B.; Schubert, L. [Fraunhofer-Institut fuer Zerstoerungsfreie Pruefverfahren, Dresden (Germany)

    2010-07-01

    The authors of the contribution under consideration report on a development of a Structural-Health-Monitoring-System which is to supervise the condition of the rotor blades of wind power plants and to detect in time structural changes before total failures. It is based on a combination of measuring techniques from the areas of the led rollers in the ultrasonic range and low-frequency modal analysis. The combination of both techniques was already promisingly used with past investigations of rotor blades. By means of modal analysis, statements to the total behaviour of the structure of rotor blades are possible. Endangered and strongly stressed areas additionally are supervised by led rollers within the ultrasonic range. The authors also report on the conception and execution of a fatigue test at a material rotor blade with a length by 39.1 m.

  16. When Machines Design Machines!

    DEFF Research Database (Denmark)

    2011-01-01

    Until recently we were the sole designers, alone in the driving seat making all the decisions. But, we have created a world of complexity way beyond human ability to understand, control, and govern. Machines now do more trades than humans on stock markets, they control our power, water, gas...... and food supplies, manage our elevators, microclimates, automobiles and transport systems, and manufacture almost everything. It should come as no surprise that machines are now designing machines. The chips that power our computers and mobile phones, the robots and commercial processing plants on which we...... depend, all are now largely designed by machines. So what of us - will be totally usurped, or are we looking at a new symbiosis with human and artificial intelligences combined to realise the best outcomes possible. In most respects we have no choice! Human abilities alone cannot solve any of the major...

  17. Hardware Specific Integration Strategy for Impedance-Based Structural Health Monitoring of Aerospace Systems

    Science.gov (United States)

    Owen, Robert B.; Gyekenyesi, Andrew L.; Inman, Daniel J.; Ha, Dong S.

    2011-01-01

    The Integrated Vehicle Health Management (IVHM) Project, sponsored by NASA's Aeronautics Research Mission Directorate, is conducting research to advance the state of highly integrated and complex flight-critical health management technologies and systems. An effective IVHM system requires Structural Health Monitoring (SHM). The impedance method is one such SHM technique for detection and monitoring complex structures for damage. This position paper on the impedance method presents the current state of the art, future directions, applications and possible flight test demonstrations.

  18. [Four axiological considerations in social epidemiology for the monitoring of health inequality].

    Science.gov (United States)

    Mújica, Oscar J

    2015-12-01

    As the conceptual components of the most important contemporary public health agendas at the global and regional levels are brought into alignment and as it becomes more clearly understood that equity is a constitutive principle of these agendas, there is also a growing awareness of the strategic value of monitoring social inequalities in health. This is the health intelligence tool par excellence, not only for objectively assessing progress towards achieving health equity, but also for reporting action on the social determinants of health, progress towards the attainment of health for all, and the success of intersectoral efforts that take a "health in all policies" approach. These transformations are taking place in the context of an increasingly evident paradigm shift in public health. This essay presents four axiological considerations inherent to-and essential for -conceptualizing and implementing ways to measure and monitor health inequalities: ecoepidemiology as an emerging field in contemporary public health; the determinants of health as the causal model and core of the new paradigm; the relationship between the social hierarchy and health to understand the health gradient; and the practical need for a socioeconomic classification system that captures the social dimension in the determinants of health. The essay argues that these four axiological considerations lend epidemiologic coherence and rationality to the process of measuring and monitoring health inequalities and, by extension, to the development of pro-equity health policy proposals.

  19. Monitoring progress towards universal health coverage at country and global levels.

    Science.gov (United States)

    Boerma, Ties; Eozenou, Patrick; Evans, David; Evans, Tim; Kieny, Marie-Paule; Wagstaff, Adam

    2014-09-01

    Universal health coverage (UHC) has been defined as the desired outcome of health system performance whereby all people who need health services (promotion, prevention, treatment, rehabilitation, and palliation) receive them, without undue financial hardship. UHC has two interrelated components: the full spectrum of good-quality, essential health services according to need, and protection from financial hardship, including possible impoverishment, due to out-of-pocket payments for health services. Both components should benefit the entire population. This paper summarizes the findings from 13 country case studies and five technical reviews, which were conducted as part of the development of a global framework for monitoring progress towards UHC. The case studies show the relevance and feasibility of focusing UHC monitoring on two discrete components of health system performance: levels of coverage with health services and financial protection, with a focus on equity. These components link directly to the definition of UHC and measure the direct results of strategies and policies for UHC. The studies also show how UHC monitoring can be fully embedded in often existing, regular overall monitoring of health sector progress and performance. Several methodological and practical issues related to the monitoring of coverage of essential health services, financial protection, and equity, are highlighted. Addressing the gaps in the availability and quality of data required for monitoring progress towards UHC is critical in most countries.

  20. Monitoring progress towards universal health coverage at country and global levels.

    Directory of Open Access Journals (Sweden)

    Ties Boerma

    2014-09-01

    Full Text Available Universal health coverage (UHC has been defined as the desired outcome of health system performance whereby all people who need health services (promotion, prevention, treatment, rehabilitation, and palliation receive them, without undue financial hardship. UHC has two interrelated components: the full spectrum of good-quality, essential health services according to need, and protection from financial hardship, including possible impoverishment, due to out-of-pocket payments for health services. Both components should benefit the entire population. This paper summarizes the findings from 13 country case studies and five technical reviews, which were conducted as part of the development of a global framework for monitoring progress towards UHC. The case studies show the relevance and feasibility of focusing UHC monitoring on two discrete components of health system performance: levels of coverage with health services and financial protection, with a focus on equity. These components link directly to the definition of UHC and measure the direct results of strategies and policies for UHC. The studies also show how UHC monitoring can be fully embedded in often existing, regular overall monitoring of health sector progress and performance. Several methodological and practical issues related to the monitoring of coverage of essential health services, financial protection, and equity, are highlighted. Addressing the gaps in the availability and quality of data required for monitoring progress towards UHC is critical in most countries.

  1. Automated Cognitive Health Assessment Using Smart Home Monitoring of Complex Tasks.

    Science.gov (United States)

    Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

    2013-11-01

    One of the many services that intelligent systems can provide is the automated assessment of resident well-being. We hypothesize that the functional health of individuals, or ability of individuals to perform activities independently without assistance, can be estimated by tracking their activities using smart home technologies. In this paper, we introduce a machine learning-based method for assessing activity quality in smart homes. To validate our approach we quantify activity quality for 179 volunteer participants who performed a complex, interweaved set of activities in our smart home apartment. We observed a statistically significant correlation (r=0.79) between automated assessment of task quality and direct observation scores. Using machine learning techniques to predict the cognitive health of the participants based on task quality is accomplished with an AUC value of 0.64. We believe that this capability is an important step in understanding everyday functional health of individuals in their home environments.

  2. Smart homes and home health monitoring technologies for older adults: A systematic review.

    Science.gov (United States)

    Liu, Lili; Stroulia, Eleni; Nikolaidis, Ioanis; Miguel-Cruz, Antonio; Rios Rincon, Adriana

    2016-07-01

    Around the world, populations are aging and there is a growing concern about ways that older adults can maintain their health and well-being while living in their homes. The aim of this paper was to conduct a systematic literature review to determine: (1) the levels of technology readiness among older adults and, (2) evidence for smart homes and home-based health-monitoring technologies that support aging in place for older adults who have complex needs. We identified and analyzed 48 of 1863 relevant papers. Our analyses found that: (1) technology-readiness level for smart homes and home health monitoring technologies is low; (2) the highest level of evidence is 1b (i.e., one randomized controlled trial with a PEDro score ≥6); smart homes and home health monitoring technologies are used to monitor activities of daily living, cognitive decline and mental health, and heart conditions in older adults with complex needs; (3) there is no evidence that smart homes and home health monitoring technologies help address disability prediction and health-related quality of life, or fall prevention; and (4) there is conflicting evidence that smart homes and home health monitoring technologies help address chronic obstructive pulmonary disease. The level of technology readiness for smart homes and home health monitoring technologies is still low. The highest level of evidence found was in a study that supported home health technologies for use in monitoring activities of daily living, cognitive decline, mental health, and heart conditions in older adults with complex needs. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  3. Effects of payment method on work control, work risk and work-related musculoskeletal health among sewing machine operators

    Directory of Open Access Journals (Sweden)

    R. Nawawi

    2015-12-01

    Full Text Available Effects of payment method on work control, work risk and work-related musculoskeletal health among sewing machine operators R. Nawawi1, B.M. Deros1*, D.D.I. Daruis2, A. Ramli3, R.M. Zein4 and L.H. Joseph3 1Dept. of Mechanical and Materials Engineering Faculty of Engineering & Built Environment Universiti Kebangsaan Malaysia, Malaysia *Email: hjbaba@ukm.edu.my 2Faculty of Engineering, Universiti Pertahanan Nasional Malaysia, Malaysia 3Department of Physiotherapy Faculty of Science, Lincoln University College, Malaysia 4Department of Consultation, Research & Development, National Institute of Occupational Safety and Health (NIOSH, Malaysia ABSTRACT This study aimed to identify payment method and its effects on work control, work risk and work-related musculoskeletal health among Malaysian sewing machine operators. The study sample comprised 337 sewing machine operators (male, n=122, female, n=215; aged between 18-54 years old; mean 30.74±8.44 from four different garment-making companies in Malaysia. They were being paid via time rate wages (n=246 and piece rate wages (n=91. Data was collected through Nordic Musculoskeletal Questionnaire and pen-and-paper assessment via Rapid Upper Limb Assessment (RULA. From the study, the piece rate wage group was found to take fewer breaks, had high work production demands, worked at a faster pace and experienced more exhaustion and pressure due to increasing work demands as compared to the time rate group. They were also observed working with higher physical exposure such as repetitive tasks, awkward static postures, awkward grips and hand movements, pulling, lifting and pushing as compared to those in the time rate wage group. The final RULA scores was also higher from the piece rate wage group (72.53% RULA score 7 which indicated higher work risks among them. The study found that the type of wage payment was significantly associated with work risks (p=0.036, df=1 and WRMSD at the shoulder, lower back

  4. Lifelong personal health data and application software via virtual machines in the cloud

    OpenAIRE

    Van Gorp, P.; Comuzzi, M.

    2014-01-01

    Personal Health Records (PHRs) should remain the lifelong property of patients, who should be able to show them conveniently and securely to selected caregivers and institutions. In this paper, we present MyPHRMachines, a cloud-based PHR system taking a radically new architectural solution to health record portability. In MyPHRMachines, health-related data and the application software to view and/or analyze it are separately deployed in the PHR system. After uploading their medical data to My...

  5. Field on monitoring partial discharges in rotating machines; Experiencias en campo en monitorizacion de descargas parciales en maquinas rotativas

    Energy Technology Data Exchange (ETDEWEB)

    Cano Gonzalez, J. C.; Blokhintsev, I.

    2010-07-01

    The partial discharge monitoring is now an accepted technique in the market, however there are different measurement solutions. Equipment manufacturers partial discharge using different equipment, different measurement frequencies, different sensors and different solutions to noise.

  6. An online substructure identification method for local structural health monitoring

    Science.gov (United States)

    Hou, Jilin; Jankowski, Łukasz; Ou, Jinping

    2013-09-01

    This paper proposes a substructure isolation method, which uses time series of measured local response for online monitoring of substructures. The proposed monitoring process consists of two key steps: construction of the isolated substructure, and its identification. The isolated substructure is an independent virtual structure, which is numerically isolated from the global structure by placing virtual supports on the interface. First, the isolated substructure is constructed by a specific linear combination of time series of its measured local responses. Then, the isolated substructure is identified using its local natural frequencies extracted from the combined responses. The substructure is assumed to be linear; the outside part of the global structure can have any characteristics. The method has no requirements on the initial state of the structure, and so the process can be carried out repetitively for online monitoring. Online isolation and monitoring is illustrated in a numerical example with a frame model, and then verified in a cantilever beam experiment.

  7. Use of FBG sensors for health monitoring of pipelines

    Science.gov (United States)

    Felli, Ferdinando; Paolozzi, Antonio; Vendittozzi, Cristian; Paris, Claudio; Asanuma, Hiroshi

    2016-04-01

    The infrastructures for oil and gas production and distribution need reliable monitoring systems. The risks for pipelines, in particular, are not only limited to natural disasters (landslides, earthquakes, extreme environmental conditions) and accidents, but involve also the damages related to criminal activities, such as oil theft. The existing monitoring systems are not adequate for detecting damages from oil theft, and in several occasion the illegal activities resulted in leakage of oil and catastrophic environmental pollution. Systems based on fiber optic FBG (Fiber Bragg Grating) sensors present a number of advantages for pipeline monitoring. FBG sensors can withstand harsh environment, are immune to interferences, and can be used to develop a smart system for monitoring at the same time several physical characteristics, such as strain, temperature, acceleration, pressure, and vibrations. The monitoring station can be positioned tens of kilometers away from the measuring points, lowering the costs and the complexity of the system. This paper describes tests on a sensor, based on FBG technology, developed specifically for detecting damages of pipeline due to illegal activities (drilling of the pipes), that can be integrated into a smart monitoring chain.

  8. Monitoring mangrove biomass change in Vietnam using SPOT images and an object-based approach combined with machine learning algorithms

    Science.gov (United States)

    Pham, Lien T. H.; Brabyn, Lars

    2017-06-01

    Mangrove forests are well-known for their provision of ecosystem services and capacity to reduce carbon dioxide concentrations in the atmosphere. Mapping and quantifying mangrove biomass is useful for the effective management of these forests and maximizing their ecosystem service performance. The objectives of this research were to model, map, and analyse the biomass change between 2000 and 2011 of mangrove forests in the Cangio region in Vietnam. SPOT 4 and 5 images were used in conjunction with object-based image analysis and machine learning algorithms. The study area included natural and planted mangroves of diverse species. After image preparation, three different mangrove associations were identified using two levels of image segmentation followed by a Support Vector Machine classifier and a range of spectral, texture and GIS information for classification. The overall classification accuracy for the 2000 and 2011 images were 77.1% and 82.9%, respectively. Random Forest regression algorithms were then used for modelling and mapping biomass. The model that integrated spectral, vegetation association type, texture, and vegetation indices obtained the highest accuracy (R2adj = 0.73). Among the different variables, vegetation association type was the most important variable identified by the Random Forest model. Based on the biomass maps generated from the Random Forest, total biomass in the Cangio mangrove forest increased by 820,136 tons over this period, although this change varied between the three different mangrove associations.

  9. The CINDI Health Monitor Survey. Health behaviour among the Italian adult population, 2001-2002

    Directory of Open Access Journals (Sweden)

    Maria Teresa Tenconi

    2004-12-01

    Full Text Available

    In accordance to the WHO-CINDI (Countrywide Integrated Non-communicable Diseases Intervention Programme, in 2001-2002 Italy participated in the Health Monitor Survey (HMS along with all the other CINDI member countries.

    The survey aimed to investigate, by the use of a standard questionnaire, the self-reported health status, life-habits, social and health conditions, use of health services and other features of the study population.

    Following the international CINDI protocol, the adult population (25-64 years of age from six Italian demonstration areas were chosen: Bassiano-Lenola (LT, Brisighella (RA, Rovescala (PV, Sardinia (CA, SS, Udine (UD; Valle dell’Irno (SA. A total number of 4095 subjects, including both males and females were enrolled, with a participation rate of 53%, equal to 2202 subjects [45.7% males (M and 54.3% females (F]. All age groups were equally represented. From the analysis of the age-standardised rates, the following results were obtained. Self-reported “good state of health”: M 71%, F 56.9%; Hypertension: M 15.6%, F 17.5%; Diabetes: M 6.1%, F 4.2%; Back-illness: M 18%, F 22%; Gastritis: M 12.8%, F 12.6%; Headache: M 31.7%, F 54.6%; Insomnia: M 15.9%, F 28.5%; Daily smokers: M 35.7%, F 23.5%; Daily consumption of wine: M 40.2%, F 15.7%; BMI ≥ 30: M 12.3%, F 13.5%; Regular leisure physical activity: M 27.6%, F 23.1%; Hard physical activity: M 40.5%, F 24%. The results demonstrate how rural areas (Rovescala and Valle dell’Irno experience worse health conditions. Thanks to the HMS, the population’s health needs have been focused and compared to those of other CINDI countries, in order to plan specific interventions aimed at the improvement of lifestyle and health conditions.

  10. Remote health monitoring with wearable non-invasive mobile system: The HealthWear project.

    Science.gov (United States)

    Paradiso, R; Alonso, A; Cianflone, D; Milsis, A; Vavouras, T; Malliopoulos, C

    2008-01-01

    This paper focuses on the technical solutions enabling the monitoring of health conditions by means of ECG, HR, oxygen saturation, impedance pneumography and activity patterns. The Healthwear service is based on the Wealthy prototype system. A new design has been made to increase comfort in wearing of the system during daily patient activities. The cloth is connected to a patient portable electronic unit (PPU) that acquires and elaborates the signals from the sensors. The PPU transmits the signal to a central processing site through the use of GPRS wireless technology. This service is applied to three distinct clinical contexts: rehabilitation of cardiac patients, following an acute event; early discharge program in chronic respiration patients; promotion of physical activity in ambulatory stable cardio-respiratory patients.

  11. Design of remote machine room monitoring base on IOT%基于物联网技术的远程机房监控系统设计

    Institute of Scientific and Technical Information of China (English)

    付祥

    2013-01-01

    Aiming at the problem existing in the domestic computer room monitoring and management, a remote room equipment and environmental information monitoring system based on IOT sensor technology is proposed. With the system, the relevant departments can off-site or even remote monitor and manage the equipment in the machine room and relevant environmental controls (such as temperature, smoke, power supply, etc.). According to the default strategy thresholds, the room management automation can be achieved.%  针对国内计算机机房监控和管理存在的问题,提出了一种基于物联网传感技术的远程机房设备和环境信息监控系统。通过该系统,相关部门可以在机房外,甚至异地远程监视和管理机房内的设备和相应的环境控制(如温度、烟感、电源等),也可以根据预设的策略阈值来实现机房管理的自动化。

  12. Preliminary analysis of the use of smartwatches for longitudinal health monitoring.

    Science.gov (United States)

    Jovanov, Emil

    2015-08-01

    New generations of smartwatches feature continuous measurement of physiological parameters, such as heart rate, galvanic skin resistance (GSR), and temperature. In this paper we present the results of preliminary analysis of the use of Basis Peak smartwatch for longitudinal health monitoring during a 4 month period. Physiological measurements during sleep are validated using Zephyr Bioharness 3 monitor and SOMNOscreen+ polysomnographic monitoring system from SOMNOmedics. Average duration of sequences with no missed data was 49.9 minutes, with maximum length of 17 hours, and they represent 88.88% of recording time. Average duration of the charging event was 221.9 min, and average time between charges was 54 hours, with maximum duration of the charging event of 16.3 hours. Preliminary results indicate that the physiological monitoring performance of existing smartwatches provides sufficient performance for longitudinal monitoring of health status and analysis of health and wellness trends.

  13. NORMATIVE MEASUREMENTS OF NOISE AT CNC MACHINES WORK STATIONS

    Directory of Open Access Journals (Sweden)

    Dariusz Mika

    2016-06-01

    Full Text Available Minimisation of noise at a workstation is among fundamental tasks for maintaining safety at work, both in terms of health (the auditory system in particular as well as work comfort. Thus, it is very important to systematically monitor noise levels by carrying out reliable measurements at a workstation. The method of performing noise measurements at workstations of specific machines is normalised so the results of such measurements for different machines is comparable. This paper presents noise measurements for DMC 635 numerically controlled milling machine, performed in accordance with PN ISO 230-5:2002 norm. The results showed that the level of noise at the operator’s workstation significantly exceeds the norm at certain machining parameters. The results of tests are concluded as detailed recommendation for the CNC machine tool operator to use hearing protection when at work.

  14. On-Orbit Health Monitoring and Repair Assessment of Thermal Protection Systems Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR project delivers On-orbit health MoNItoring and repair assessment of THERMal protection systems (OMNI_THERM). OMNI_THERM features impedance-based...

  15. Application of near field communication for health monitoring in daily life.

    Science.gov (United States)

    Strömmer, Esko; Kaartinen, Jouni; Pärkkä, Juha; Ylisaukko-Oja, Arto; Korhonen, Ilkka

    2006-01-01

    We study the possibility of applying an emerging RFID-based communication technology, NFC (Near Field Communication), to health monitoring. We suggest that NFC is, compared to other competing technologies, a high-potential technology for short-range connectivity between health monitoring devices and mobile terminals. We propose practices to apply NFC to some health monitoring applications and study the benefits that are attainable with NFC. We compare NFC to other short-range communication technologies such as Bluetooth and IrDA, and study the possibility of improving the usability of health monitoring devices with NFC. We also introduce a research platform for technical evaluation, applicability study and application demonstrations of NFC.

  16. Time Reversal Acoustic Structural Health Monitoring Using Array of Embedded Sensors Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Time Reversal Acoustic (TRA) structural health monitoring with an embedded sensor array represents a new approach to in-situ nondestructive evaluation of air-space...

  17. Space Qualified Non-Destructive Evaluation and Structural Health Monitoring Technology Project

    Data.gov (United States)

    National Aeronautics and Space Administration — NextGen Aeronautics is proposing an innovative space qualified non-destructive evaluation and health monitoring technology. The technology is built on concepts...

  18. Airspora concentrations in the Vaal-triangle-monitoring and potential health-effects.2, fungal spores

    CSIR Research Space (South Africa)

    Vismer, HF

    1995-08-01

    Full Text Available Atmospheric fungal spores were monitored in Vanderbijlpark for the period 1991-92 as part of the Vaal triangle air pollution health study of the medical research council and the CSIR. Cladosporium, Aspergillus/ Penicillium, Alternaria and Epicoccum...

  19. Autonomus I&C Maintenance and Health Monitoring System for Fission Surface Power Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The primary goal of this project is to design and develop an autonomous instrumentation and control (I&C) health monitoring system for space nuclear power...

  20. Unpowered Wireless Ultrasound Generation and Sensing for Structural Health Monitoring of Composites Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Damage detection based on ultrasonic waves is one of the most popular inspection schemes employed by many structural health monitoring (SHM) systems. We propose a...