WorldWideScience

Sample records for intelligent condition monitoring

  1. Intelligent condition monitoring of railway catenary systems : A Bayesian Network approach

    NARCIS (Netherlands)

    Wang, H.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Liu, Zhigang; Chen, Junwen; Spiryagin, Maksym; Gordon, Timothy; Cole, Colin; McSweeney, Tim

    2017-01-01

    This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of railway catenary systems. It combines five types of measurements related to catenary condition, namely the contact wire stagger, contact wire height, pantograph head displacement, pantograph head

  2. Artificial intelligence-based condition monitoring for practical electrical drives

    OpenAIRE

    Ashari, Djoni; Pislaru, Crinela; Ball, Andrew; Gu, Fengshou

    2012-01-01

    The main types of existing Condition Monitoring methods (MCSA, GA, IAS) for electrical drives are\\ud described. Then the steps for the design of expert systems are presented: problem identification and analysis, system specification, development tool selection, knowledge based, prototyping and testing. The employment of SOMA (Self-Organizing Migrating Algorithm) used for the optimization of ambient\\ud vibration energy harvesting is analyzed. The power electronics devices are becoming smaller ...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-12-31

    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.

  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. Condition Monitoring Using Computational Intelligence Methods Applications in Mechanical and Electrical Systems

    CERN Document Server

    Marwala, Tshilidzi

    2012-01-01

    Condition monitoring uses the observed operating characteristics of a machine or structure to diagnose trends in the signal being monitored and to predict the need for maintenance before a breakdown occurs. This reduces the risk, inherent in a fixed maintenance schedule, of performing maintenance needlessly early or of having a machine fail before maintenance is due either of which can be expensive with the latter also posing a risk of serious accident especially in systems like aeroengines in which a catastrophic failure would put lives at risk. The technique also measures responses from the whole of the system under observation so it can detect the effects of faults which might be hidden deep within a system, hidden from traditional methods of inspection. Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, m...

  6. Artificial intelligence tools decision support systems in condition monitoring and diagnosis

    CERN Document Server

    Galar Pascual, Diego

    2015-01-01

    Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

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

    Science.gov (United States)

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

    2017-02-01

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

  8. On-line Cutting Tool Condition Monitoring in Machining Processes Using Artificial Intelligence

    OpenAIRE

    Vallejo, Antonio J.; Morales-Menéndez, Rub&#;n; Alique, J.R.

    2008-01-01

    This chapter presented new ideas for monitoring and diagnosis of the cutting tool condition with two different algorithms for pattern recognition: HMM, and ANN. The monitoring and diagnosis system was implemented for peripheral milling process in HSM, where several Aluminium alloys and cutting tools were used. The flank wear (VB) was selected as the criterion to evaluate the tool's life and four cutting tool conditions were defined to be recognized: New, half new, half worn, and worn conditio...

  9. Welding station condition monitoring using bluetooth enabled sensors and intelligent data management

    Energy Technology Data Exchange (ETDEWEB)

    Eyers, D R; Grosvenor, R I; Prickett, P W [Intelligent Process Monitoring and Management (IPMM) Group, Cardiff School of Engineering, Cardiff University, Wales (United Kingdom)

    2005-01-01

    This paper reports on the first phase deployment of bluetooth enabled condition monitoring systems at a large multinational engineering company. The radio networking of sensor signals is a fast developing area and the facilities afforded by the Wisnet device were used in the monitoring of a welding station. This and any of the planned further monitoring systems had to comply to a carefully managed IT information plan at the company. For the example application, the development and testing of microcontoller-based pre-processing of data is reported. This includes further development of the Petri Net approach to provide event-based monitoring as a sensible alternative to the continuous transmission of the sensory data.

  10. Area monitoring intelligent system - SIMA

    International Nuclear Information System (INIS)

    Bhoem, P.; Hisas, F.; Gelardi, G.

    1990-01-01

    The area monitoring intelligent system (SIMA) is an equipment to be used in radioprotection. SIMA has the function of monitoring the radiation levels of determined areas of the installations where radioactive materials are handled. (Author) [es

  11. An intelligent fetal monitoring system

    International Nuclear Information System (INIS)

    Inaba, J.; Akatsuka, T.; Kubo, T.; Iwasaki, H.

    1986-01-01

    An intelligent monitoring system is constructed by a multi-micro-computer system. The monitoring signals are fetal heart rate (FHR) and uterine contraction (UC) through the conventional monitoring device for a day until the delivery. These signals are fed to a micro-computer in digital format, and evaluated by the computer in real time according to the diagnostic algorithm of the expert physician. Monitoring signals are always displayed on the CRT screen and in the case of dangerous state of the fetus, warning signal will appear on the screen and the doctor or nurse will be called. All these signals are sent to the next micro-computer with 10MB hard disk system. On this computer, the doctor and nurse can retrieve and inspect the details of the process by clock-key and/or events-key. After finishing monitoring process, summarized report is constructed and printed out on the paper

  12. Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features

    Science.gov (United States)

    Ahmed, H. O. A.; Wong, M. L. D.; Nandi, A. K.

    2018-01-01

    Condition classification of rolling element bearings in rotating machines is important to prevent the breakdown of industrial machinery. A considerable amount of literature has been published on bearing faults classification. These studies aim to determine automatically the current status of a roller element bearing. Of these studies, methods based on compressed sensing (CS) have received some attention recently due to their ability to allow one to sample below the Nyquist sampling rate. This technology has many possible uses in machine condition monitoring and has been investigated as a possible approach for fault detection and classification in the compressed domain, i.e., without reconstructing the original signal. However, previous CS based methods have been found to be too weak for highly compressed data. The present paper explores computationally, for the first time, the effects of sparse autoencoder based over-complete sparse representations on the classification performance of highly compressed measurements of bearing vibration signals. For this study, the CS method was used to produce highly compressed measurements of the original bearing dataset. Then, an effective deep neural network (DNN) with unsupervised feature learning algorithm based on sparse autoencoder is used for learning over-complete sparse representations of these compressed datasets. Finally, the fault classification is achieved using two stages, namely, pre-training classification based on stacked autoencoder and softmax regression layer form the deep net stage (the first stage), and re-training classification based on backpropagation (BP) algorithm forms the fine-tuning stage (the second stage). The experimental results show that the proposed method is able to achieve high levels of accuracy even with extremely compressed measurements compared with the existing techniques.

  13. Distributed intelligent monitoring and reporting facilities

    Science.gov (United States)

    Pavlou, George; Mykoniatis, George; Sanchez-P, Jorge-A.

    1996-06-01

    Distributed intelligent monitoring and reporting facilities are of paramount importance in both service and network management as they provide the capability to monitor quality of service and utilization parameters and notify degradation so that corrective action can be taken. By intelligent, we refer to the capability of performing the monitoring tasks in a way that has the smallest possible impact on the managed network, facilitates the observation and summarization of information according to a number of criteria and in its most advanced form and permits the specification of these criteria dynamically to suit the particular policy in hand. In addition, intelligent monitoring facilities should minimize the design and implementation effort involved in such activities. The ISO/ITU Metric, Summarization and Performance management functions provide models that only partially satisfy the above requirements. This paper describes our extensions to the proposed models to support further capabilities, with the intention to eventually lead to fully dynamically defined monitoring policies. The concept of distributing intelligence is also discussed, including the consideration of security issues and the applicability of the model in ODP-based distributed processing environments.

  14. Intelligent Monitoring of Rocket Test Systems

    Science.gov (United States)

    Duran, Esteban; Rocha, Stephanie; Figueroa, Fernando

    2016-01-01

    Stephanie Rocha is an undergraduate student pursuing a degree in Mechanical Engineering. Esteban Duran is pursuing a degree in Computer Science. Our mentor is Fernando Figueroa. Our project involved developing Intelligent Health Monitoring at the High Pressure Gas Facility (HPGF) utilizing the software GensymG2.

  15. Monitoring osseointegration and developing intelligent systems (Conference Presentation)

    Science.gov (United States)

    Salvino, Liming W.

    2017-05-01

    Effective monitoring of structural and biological systems is an extremely important research area that enables technology development for future intelligent devices, platforms, and systems. This presentation provides an overview of research efforts funded by the Office of Naval Research (ONR) to establish structural health monitoring (SHM) methodologies in the human domain. Basic science efforts are needed to utilize SHM sensing, data analysis, modeling, and algorithms to obtain the relevant physiological and biological information for human-specific health and performance conditions. This overview of current research efforts is based on the Monitoring Osseointegrated Prosthesis (MOIP) program. MOIP develops implantable and intelligent prosthetics that are directly anchored to the bone of residual limbs. Through real-time monitoring, sensing, and responding to osseointegration of bones and implants as well as interface conditions and environment, our research program aims to obtain individualized actionable information for implant failure identification, load estimation, infection mitigation and treatment, as well as healing assessment. Looking ahead to achieve ultimate goals of SHM, we seek to expand our research areas to cover monitoring human, biological and engineered systems, as well as human-machine interfaces. Examples of such include 1) brainwave monitoring and neurological control, 2) detecting and evaluating brain injuries, 3) monitoring and maximizing human-technological object teaming, and 4) closed-loop setups in which actions can be triggered automatically based on sensors, actuators, and data signatures. Finally, some ongoing and future collaborations across different disciplines for the development of knowledge automation and intelligent systems will be discussed.

  16. Modelling speech intelligibility in adverse conditions

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2013-01-01

    Jørgensen and Dau (J Acoust Soc Am 130:1475-1487, 2011) proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII) in conditions with nonlinearly processed speech...... subjected to phase jitter, a condition in which the spectral structure of the intelligibility of speech signal is strongly affected, while the broadband temporal envelope is kept largely intact. In contrast, the effects of this distortion can be predicted -successfully by the spectro-temporal modulation...... suggest that the SNRenv might reflect a powerful decision metric, while some explicit across-frequency analysis seems crucial in some conditions. How such across-frequency analysis is "realized" in the auditory system remains unresolved....

  17. Toward Intelligent Hemodynamic Monitoring: A Functional Approach

    Directory of Open Access Journals (Sweden)

    Pierre Squara

    2012-01-01

    Full Text Available Technology is now available to allow a complete haemodynamic analysis; however this is only used in a small proportion of patients and seems to occur when the medical staff have the time and inclination. As a result of this, significant delays occur between an event, its diagnosis and therefore, any treatment required. We can speculate that we should be able to collect enough real time information to make a complete, real time, haemodynamic diagnosis in all critically ill patients. This article advocates for “intelligent haemodynamic monitoring”. Following the steps of a functional analysis, we answered six basic questions. (1 What is the actual best theoretical model for describing haemodynamic disorders? (2 What are the needed and necessary input/output data for describing this model? (3 What are the specific quality criteria and tolerances for collecting each input variable? (4 Based on these criteria, what are the validated available technologies for monitoring each input variable, continuously, real time, and if possible non-invasively? (5 How can we integrate all the needed reliably monitored input variables into the same system for continuously describing the global haemodynamic model? (6 Is it possible to implement this global model into intelligent programs that are able to differentiate clinically relevant changes as opposed to artificial changes and to display intelligent messages and/or diagnoses?

  18. Modeling speech intelligibility in adverse conditions

    DEFF Research Database (Denmark)

    Dau, Torsten

    2012-01-01

    ) in conditions with nonlinearly processed speech. Instead of considering the reduction of the temporal modulation energy as the intelligibility metric, as assumed in the STI, the sEPSM applies the signal-to-noise ratio in the envelope domain (SNRenv). This metric was shown to be the key for predicting...... understanding speech when more than one person is talking, even when reduced audibility has been fully compensated for by a hearing aid. The reasons for these difficulties are not well understood. This presentation highlights recent concepts of the monaural and binaural signal processing strategies employed...... by the normal as well as impaired auditory system. Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII...

  19. Intelligent Component Monitoring for Nuclear Power Plants

    International Nuclear Information System (INIS)

    Tsoukalas, Lefteri

    2010-01-01

    Reliability and economy are two major concerns for a nuclear power generation system. Next generation nuclear power reactors are being developed to be more reliable and economic. An effective and efficient surveillance system can generously contribute toward this goal. Recent progress in computer systems and computational tools has made it necessary and possible to upgrade current surveillance/monitoring strategy for better performance. For example, intelligent computing techniques can be applied to develop algorithm that help people better understand the information collected from sensors and thus reduce human error to a new low level. Incidents incurred from human error in nuclear industry are not rare and have been proven costly. The goal of this project is to develop and test an intelligent prognostics methodology for predicting aging effects impacting long-term performance of nuclear components and systems. The approach is particularly suitable for predicting the performance of nuclear reactor systems which have low failure probabilities (e.g., less than 10 -6 year -1 ). Such components and systems are often perceived as peripheral to the reactor and are left somewhat unattended. That is, even when inspected, if they are not perceived to be causing some immediate problem, they may not be paid due attention. Attention to such systems normally involves long term monitoring and possibly reasoning with multiple features and evidence, requirements that are not best suited for humans.

  20. 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

  1. Tool path strategy and cutting process monitoring in intelligent machining

    Science.gov (United States)

    Chen, Ming; Wang, Chengdong; An, Qinglong; Ming, Weiwei

    2018-06-01

    Intelligent machining is a current focus in advanced manufacturing technology, and is characterized by high accuracy and efficiency. A central technology of intelligent machining—the cutting process online monitoring and optimization—is urgently needed for mass production. In this research, the cutting process online monitoring and optimization in jet engine impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring are introduced as examples of intelligent machining. Results show that intelligent tool path optimization and cutting process online monitoring are efficient techniques for improving the efficiency, quality, and reliability of machining.

  2. Towards intelligent video understanding applied to plasma facing component monitoring

    International Nuclear Information System (INIS)

    Martin, V.; Travere, J.M.; Moncada, V.; Bremond, F.

    2011-01-01

    In this paper, we promote intelligent plasma facing component video monitoring for both real-time purposes (machine protection issues) and post event analysis purposes (plasma-wall interaction understanding). We propose a vision-based system able to automatically detect and classify into different pre-defined categories thermal phenomena such as localized hot spots or transient thermal events (e.g. electrical arcing) from infrared imaging data of PFCs. This original computer vision system is made intelligent by endowing it with high level reasoning (i.e. integration of a priori knowledge of thermal event spatio-temporal properties to guide the recognition), self-adaptability to varying conditions (e.g. different thermal scenes and plasma scenarios), and learning capabilities (e.g. statistical modelling of event behaviour based on training samples). (authors)

  3. Condition Indicators for Gearbox Condition Monitoring Systems

    Directory of Open Access Journals (Sweden)

    P. Večeř

    2005-01-01

    Full Text Available Condition monitoring systems for manual transmissions based on vibration diagnostics are widely applied in industry. The systems deal with various condition indicators, most of which are focused on a specific type of gearbox fault. Frequently used condition indicators (CIs are described in this paper. The ability of a selected condition indicator to describe the degree of gearing wear was tested using vibration signals acquired during durability testing of manual transmission with helical gears. 

  4. 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.

  5. BUSINESS INTELLIGENCE INSTRUMENTS FOR HR MONITORING

    Directory of Open Access Journals (Sweden)

    Radulescu Magdalena

    2009-05-01

    Full Text Available Business Intelligence is the combination of the information from several sources, and presenting results in a form that can be used in taking business decisions. Processed and presented in an intelligent way, this information gives the company the advanta

  6. Control of framed structures using intelligent monitoring networks

    Directory of Open Access Journals (Sweden)

    Foti Dora

    2017-01-01

    Full Text Available The paper proposes the integration of structural monitoring with Building Management Systems for electricity and gas distributions. To assess the state of damage of existing buildings the technics of Structural Health Monitoring (SHM is adopted. SHM as well as to record the occurrence of sudden structural damage resulting from exceptional events (earthquakes, explosions, shocks and collisions with vehicles, etc., allows the monitoring of the progressive damage and structural performance under operating conditions through the extraction of the modal parameters of the structure. This approach requires time to process acquired data that, depending on the size of the building and the number of monitored points, varies from minutes to hours. In this paper, an intelligent system is proposed to immediately communicate during an earthquake the overrun of a certain ground shaking threshold so that gas delivery and selected power loads are interrupted, as suggested by current national regulations on structures. The use of low-cost and reduced size accelerometric sensors integrated with Energy Monitoring Systems is proposed in both highrisk earthquake centers and in all “strategic” buildings that must ensure their operation use immediately after the earthquake. The procedure for calibrating the horizontal and vertical acceleration threshold is also sketched.

  7. Remote intelligent nuclear facility monitoring in LabVIEW

    International Nuclear Information System (INIS)

    Kucewicz, J.C.; Argo, P.E.; Caffrey, M.; Loveland, R.C.; McNeil, P.J.

    1996-01-01

    A prototype system implemented in LabVIEW for the intelligent monitoring of the movement of radioactive' material within a nuclear facility is presented. The system collects and analyzes radiation sensor and video data to identify suspicious movement of material within the facility. The facility system also transmits wavelet- compressed data to a remote system for concurrent monitoring. 2 refs., 2 figs

  8. Pure intelligent monitoring system for steam economizer trips

    Directory of Open Access Journals (Sweden)

    Basim Ismail Firas

    2017-01-01

    Full Text Available Steam economizer represents one of the main equipment in the power plant. Some steam economizer's behavior lead to failure and shutdown in the entire power plant. This will lead to increase in operating and maintenance cost. By detecting the cause in the early stages maintain normal and safe operational conditions of power plant. However, these methodologies are hard to be achieved due to certain boundaries such as system learning ability and the weakness of the system beyond its domain of expertise. The best solution for these problems, an intelligent modeling system specialized in steam economizer trips have been proposed and coded within MATLAB environment to be as a potential solution to insure a fault detection and diagnosis system (FDD. An integrated plant data preparation framework for 10 trips was studied as framework variables. The most influential operational variables have been trained and validated by adopting Artificial Neural Network (ANN. The Extreme Learning Machine (ELM neural network methodology has been proposed as a major computational intelligent tool in the system. It is shown that ANN can be implemented for monitoring any process faults in thermal power plants. Better speed of learning algorithms by using the Extreme Learning Machine has been approved as well.

  9. Automation of neutral beam source conditioning with artificial intelligence techniques

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.W.; Lager, D.L.

    1985-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

  10. Automation of neutral beam source conditioning with artificial intelligence techniques

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.; Lager, D.

    1986-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

  11. Predicting speech intelligibility in conditions with nonlinearly processed noisy speech

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2013-01-01

    The speech-based envelope power spectrum model (sEPSM; [1]) was proposed in order to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII). The sEPSM applies the signal-tonoise ratio in the envelope domain (SNRenv), which was demonstrated...... to successfully predict speech intelligibility in conditions with nonlinearly processed noisy speech, such as processing with spectral subtraction. Moreover, a multiresolution version (mr-sEPSM) was demonstrated to account for speech intelligibility in various conditions with stationary and fluctuating...

  12. Acoustic multivariate condition monitoring - AMCM

    Energy Technology Data Exchange (ETDEWEB)

    Rosenhave, P E [Vestfold College, Maritime Dept., Toensberg (Norway)

    1998-12-31

    In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.

  13. Acoustic multivariate condition monitoring - AMCM

    Energy Technology Data Exchange (ETDEWEB)

    Rosenhave, P.E. [Vestfold College, Maritime Dept., Toensberg (Norway)

    1997-12-31

    In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.

  14. Towards intelligent video understanding applied to plasma facing component monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Martin, V.; Bremond, F. [INRIA, Pulsa team-project, Sophia Antipolis (France); Travere, J.M. [CEA IRFM, Saint Paul-lez-Durance (France); Moncada, V.; Dunand, G. [Sophia Conseil Company, Sophia Antipolis (France)

    2011-07-01

    Infrared thermography has become a routine diagnostic in many magnetic fusion devices to monitor the heat loads on the plasma facing components (PFCs) for both physics studies and machine protection. The good results of the developed systems obtained so far motivate the use of imaging diagnostics for control, especially during long pulse tokamak operation (e.g. lasting several minutes). In this paper, we promote intelligent monitoring for both real-time purposes (machine protection issues) and post event analysis purposes (PWI understanding). We propose a vision-based system able to automatically detect and classify into different pre-defined categories phenomena as localized hot spots, transient thermal events (e.g. electrical arcing), and unidentified flying objects (UFOs) as dusts from infrared imaging data of PFCs. This original vision system is made intelligent by endowing it with high-level reasoning (i.e. integration of a priori knowledge of thermal event spatial and temporal properties to guide the recognition), self-adaptability to varying conditions (e.g. different plasma scenarios), and learning capabilities (e.g. statistical modelling of thermal event behaviour based on training samples). This approach has been already successfully applied to the recognition of one critical thermal event at Tore Supra. We present here latest results of its extension for the recognition of others thermal events (e.g., B{sub 4}C flakes, impact of fast particles, UFOs) and show how extracted information can be used during plasma operation at Tore Supra to improve the real time control system, and for further analysis of PFC aging. This document is composed of an abstract followed by the slides of the presentation. (authors)

  15. Monitoring Thermal Conditions in Footwear

    Science.gov (United States)

    Silva-Moreno, Alejandra. A.; Lopez Vela, Martín; Alcalá Ochoa, Noe

    2006-09-01

    Thermal conditions inside the foot were evaluated on a volunteer subject. We have designed and constructed an electronic system which can monitors temperature and humidity of the foot inside the shoe. The data is stored in a battery-powered device for later uploading to a host computer for data analysis. The apparatus potentially can be used to provide feedback to patients who are prone to having skin breakdowns.

  16. Distributed intelligent urban environment monitoring system

    Science.gov (United States)

    Du, Jinsong; Wang, Wei; Gao, Jie; Cong, Rigang

    2018-02-01

    The current environmental pollution and destruction have developed into a world-wide major social problem that threatens human survival and development. Environmental monitoring is the prerequisite and basis of environmental governance, but overall, the current environmental monitoring system is facing a series of problems. Based on the electrochemical sensor, this paper designs a small, low-cost, easy to layout urban environmental quality monitoring terminal, and multi-terminal constitutes a distributed network. The system has been small-scale demonstration applications and has confirmed that the system is suitable for large-scale promotion

  17. The development report of an intelligent neutron fluence integration monitor

    International Nuclear Information System (INIS)

    Jiang Zongbing; Wei Ying

    1996-10-01

    An intelligent neutron fluence integration monitor is introduced. It is used to measure the received neutron fluence of the monocrystalline silicon in reactor radiation channel. The significance of study and specifications of the instrument are briefly described. The emphasis is on the working principle, structure and characteristics of the instrument is intelligent due to use of monolithic microcomputer. It has many advantages proved in the actual practice, such as powerful function, high accuracy, diversity of application, high level automatization, easy to operate, high reliability, etc. After using this instrument the monocrystalline silicon radiation technology is improved and the efficiency of production is raised. (1 fig.)

  18. Advanced power cycler with intelligent monitoring strategy of IGBT module under test

    DEFF Research Database (Denmark)

    Choi, U. M.; Blaabjerg, F.; Iannuzzo, F.

    2017-01-01

    and diode, which for the wear-out condition monitoring are presented. This advanced power cycler allows to perform power cycling test cost-effectively under conditions close to real power converter applications. In addition, an intelligent monitoring strategy for the separation of package-related wear......-out failure mechanisms has been proposed. By means of the proposed method, the wear-out failure mechanisms of an IGBT module can be separated without any additional efforts during the power cycling tests. The validity and effectiveness of the proposed monitoring strategy are also verified by experiments....

  19. Intelligent Belt Conveyor Monitoring and Control

    NARCIS (Netherlands)

    Pang, Y.

    2010-01-01

    Belt conveyors have been used worldwide in continuous material transport for about 250 years. Traditional inspection and monitoring of large-scale belt conveyors focus on individual critical components and response to catastrophic system failures. To prevent operational problems caused by the lack

  20. Optimizing acoustical conditions for speech intelligibility in classrooms

    Science.gov (United States)

    Yang, Wonyoung

    High speech intelligibility is imperative in classrooms where verbal communication is critical. However, the optimal acoustical conditions to achieve a high degree of speech intelligibility have previously been investigated with inconsistent results, and practical room-acoustical solutions to optimize the acoustical conditions for speech intelligibility have not been developed. This experimental study validated auralization for speech-intelligibility testing, investigated the optimal reverberation for speech intelligibility for both normal and hearing-impaired listeners using more realistic room-acoustical models, and proposed an optimal sound-control design for speech intelligibility based on the findings. The auralization technique was used to perform subjective speech-intelligibility tests. The validation study, comparing auralization results with those of real classroom speech-intelligibility tests, found that if the room to be auralized is not very absorptive or noisy, speech-intelligibility tests using auralization are valid. The speech-intelligibility tests were done in two different auralized sound fields---approximately diffuse and non-diffuse---using the Modified Rhyme Test and both normal and hearing-impaired listeners. A hybrid room-acoustical prediction program was used throughout the work, and it and a 1/8 scale-model classroom were used to evaluate the effects of ceiling barriers and reflectors. For both subject groups, in approximately diffuse sound fields, when the speech source was closer to the listener than the noise source, the optimal reverberation time was zero. When the noise source was closer to the listener than the speech source, the optimal reverberation time was 0.4 s (with another peak at 0.0 s) with relative output power levels of the speech and noise sources SNS = 5 dB, and 0.8 s with SNS = 0 dB. In non-diffuse sound fields, when the noise source was between the speaker and the listener, the optimal reverberation time was 0.6 s with

  1. ATLAS diamond Beam Condition Monitor

    Energy Technology Data Exchange (ETDEWEB)

    Gorisek, A. [CERN (Switzerland)]. E-mail: andrej.gorisek@cern.ch; Cindro, V. [J. Stefan Institute (Slovenia); Dolenc, I. [J. Stefan Institute (Slovenia); Frais-Koelbl, H. [Fotec (Austria); Griesmayer, E. [Fotec (Austria); Kagan, H. [Ohio State University, OH (United States); Korpar, S. [J. Stefan Institute (Slovenia); Kramberger, G. [J. Stefan Institute (Slovenia); Mandic, I. [J. Stefan Institute (Slovenia); Meyer, M. [CERN (Switzerland); Mikuz, M. [J. Stefan Institute (Slovenia); Pernegger, H. [CERN (Switzerland); Smith, S. [Ohio State University, OH (United States); Trischuk, W. [University of Toronto (Canada); Weilhammer, P. [CERN (Switzerland); Zavrtanik, M. [J. Stefan Institute (Slovenia)

    2007-03-01

    The ATLAS experiment has chosen to use diamond for its Beam Condition Monitor (BCM) given its radiation hardness, low capacitance and short charge collection time. In addition, due to low leakage current diamonds do not require cooling. The ATLAS Beam Condition Monitoring system is based on single beam bunch crossing measurements rather than integrating the accumulated particle flux. Its fast electronics will allow separation of LHC collisions from background events such as beam gas interactions or beam accidents. There will be two stations placed symmetrically about the interaction point along the beam axis at z=+/-183.8cm. Timing of signals from the two stations will provide almost ideal separation of beam-beam interactions and background events. The ATLAS BCM module consists of diamond pad detectors of 1cm{sup 2} area and 500{mu}m thickness coupled to a two-stage RF current amplifier. The production of the final detector modules is almost done. A S/N ratio of 10:1 has been achieved with minimum ionizing particles (MIPs) in the test beam setup at KEK. Results from the test beams and bench measurements are presented.

  2. ATLAS diamond Beam Condition Monitor

    International Nuclear Information System (INIS)

    Gorisek, A.; Cindro, V.; Dolenc, I.; Frais-Koelbl, H.; Griesmayer, E.; Kagan, H.; Korpar, S.; Kramberger, G.; Mandic, I.; Meyer, M.; Mikuz, M.; Pernegger, H.; Smith, S.; Trischuk, W.; Weilhammer, P.; Zavrtanik, M.

    2007-01-01

    The ATLAS experiment has chosen to use diamond for its Beam Condition Monitor (BCM) given its radiation hardness, low capacitance and short charge collection time. In addition, due to low leakage current diamonds do not require cooling. The ATLAS Beam Condition Monitoring system is based on single beam bunch crossing measurements rather than integrating the accumulated particle flux. Its fast electronics will allow separation of LHC collisions from background events such as beam gas interactions or beam accidents. There will be two stations placed symmetrically about the interaction point along the beam axis at z=+/-183.8cm. Timing of signals from the two stations will provide almost ideal separation of beam-beam interactions and background events. The ATLAS BCM module consists of diamond pad detectors of 1cm 2 area and 500μm thickness coupled to a two-stage RF current amplifier. The production of the final detector modules is almost done. A S/N ratio of 10:1 has been achieved with minimum ionizing particles (MIPs) in the test beam setup at KEK. Results from the test beams and bench measurements are presented

  3. ATLAS diamond Beam Condition Monitor

    CERN Document Server

    Gorišek, A; Dolenc, I; Frais-Kölbl, H; Griesmayer, E; Kagan, H; Korpar, S; Kramberger, G; Mandic, I; Meyer, M; Mikuz, M; Pernegger, H; Smith, S; Trischuk, W; Weilhammer, P; Zavrtanik, M

    2007-01-01

    The ATLAS experiment has chosen to use diamond for its Beam Condition Monitor (BCM) given its radiation hardness, low capacitance and short charge collection time. In addition, due to low leakage current diamonds do not require cooling. The ATLAS Beam Condition Monitoring system is based on single beam bunch crossing measurements rather than integrating the accumulated particle flux. Its fast electronics will allow separation of LHC collisions from background events such as beam gas interactions or beam accidents. There will be two stations placed symmetrically about the interaction point along the beam axis at . Timing of signals from the two stations will provide almost ideal separation of beam–beam interactions and background events. The ATLAS BCM module consists of diamond pad detectors of area and thickness coupled to a two-stage RF current amplifier. The production of the final detector modules is almost done. A S/N ratio of 10:1 has been achieved with minimum ionizing particles (MIPs) in the test bea...

  4. Intelligent Packaging Systems: Sensors and Nanosensors to Monitor Food Quality and Safety

    Directory of Open Access Journals (Sweden)

    Guillermo Fuertes

    2016-01-01

    Full Text Available The application of nanotechnology in different areas of food packaging is an emerging field that will grow rapidly in the coming years. Advances in food safety have yielded promising results leading to the development of intelligent packaging (IP. By these containers, it is possible to monitor and provide information of the condition of food, packaging, or the environment. This article describes the role of the different concepts of intelligent packaging. It is possible that this new technology could reach enhancing food safety, improving pathogen detection time, and controlling the quality of food and packaging throughout the supply chain.

  5. Intelligent monitoring system of bedridden elderly

    Science.gov (United States)

    Dong, Rue Shao; Tanaka, Motohiro; Ushijima, Miki; Ishimatsu, Takakazu

    2005-12-01

    In this paper we propose a system to detect physical behavior of the elderly under bedridden status. This system is used to prevent those elderly from falling down and being wounded. Basic idea of our approach is to measure the body movements of the elderly using the acceleration sensor. Based on the data measured, dangerous actions of the elderly are extracted and warning signals to the caseworkers are generated via wireless signals. A feature of the system is that the senor part is compactly assembled as a wearable unit. Another feature of the system is that the system adopts a simplified wireless network system. Due to the network capability the system can monitor physical movements of multi-patients. Applicability of the system is now being examined at hospitals.

  6. The Automator: Intelligent control system monitoring

    International Nuclear Information System (INIS)

    M. Bickley; D.A. Bryan; K.S. White

    1999-01-01

    A large-scale control system may contain several hundred thousand control points which must be monitored to ensure smooth operation. Knowledge of the current state of such a system is often implicit in the values of these points and operators must be cognizant of the state while making decisions. Repetitive operators requiring human intervention lead to fatigue, which can in turn lead to mistakes. The authors propose a tool called the Automator based on a middleware software server. This tool would provide a user-configurable engine for monitoring control points. Based on the status of these control points, a specified action could be taken. The action could range from setting another control point, to triggering an alarm, to running an executable. Often the data presented by a system is meaningless without context information from other channels. Such a tool could be configured to present interpreted information based on values of other channels. Additionally, this tool could translate numerous values in a non-friendly form (such as numbers, bits, or return codes) into meaningful strings of information. Multiple instances of this server could be run, allowing individuals or groups to configure their own Automators. The configuration of the tool will be file-based. In the future, these files could be generated by graphical design tools, allowing for rapid development of new configurations. In addition, the server will be able to explicitly maintain information about the state of the control system. This state information can be used in decision-making processes and shared with other applications. A conceptual framework and software design for the tool are presented

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

    Science.gov (United States)

    Widodo, Achmad; Yang, Bo-Suk

    2007-08-01

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

  8. The ATLAS Beam Conditions Monitor

    International Nuclear Information System (INIS)

    Cindro, V; Dolenc, I; Kramberger, G; Macek, B; Mandic, I; Mikuz', M; Zavrtanik, M; Dobos, D; Gorisek, A; Pernegger, H; Weilhammer, P; Frais-Koelbl, H; Griesmayer, E; Niegl, M; Kagan, H; Tardif, D; Trischuk, W

    2008-01-01

    Beam conditions and the potential detector damage resulting from their anomalies have pushed the LHC experiments to build their own beam monitoring devices. The ATLAS Beam Conditions Monitor (BCM) consists of two stations (forward and backward) of detectors each with four modules. The sensors are required to tolerate doses up to 500 kGy and in excess of 10 15 charged particles per cm 2 over the lifetime of the experiment. Each module includes two diamond sensors read out in parallel. The stations are located symmetrically around the interaction point, positioning the diamond sensors at z = ±184 cm and r = 55 mm (a pseudo- rapidity of about 4.2). Equipped with fast electronics (2 ns rise time) these stations measure time-of-flight and pulse height to distinguish events resulting from lost beam particles from those normally occurring in proton-proton interactions. The BCM also provides a measurement of bunch-by-bunch luminosities in ATLAS by counting in-time and out-of-time collisions. Eleven detector modules have been fully assembled and tested. Tests performed range from characterisation of diamond sensors to full module tests with electron sources and in proton testbeams. Testbeam results from the CERN SPS show a module median-signal to noise of 11:1 for minimum ionising particles incident at a 45-degree angle. The best eight modules were installed on the ATLAS pixel support frame that was inserted into ATLAS in the summer of 2007. This paper describes the full BCM detector system along with simulation studies being used to develop the logic in the back-end FPGA coincidence hardware

  9. The ATLAS Beam Conditions Monitor

    Energy Technology Data Exchange (ETDEWEB)

    Cindro, V; Dolenc, I; Kramberger, G; Macek, B; Mandic, I; Mikuz' , M; Zavrtanik, M [Jozef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana (Slovenia); Dobos, D; Gorisek, A; Pernegger, H; Weilhammer, P [CERN, Geneva (Switzerland); Frais-Koelbl, H; Griesmayer, E; Niegl, M [University of Applied Sciences Wiener Neustadt and Fotec, Wiener Neustadt (Austria); Kagan, H [Ohio State University, Columbus (United States); Tardif, D; Trischuk, W [University of Toronto, Toronto (Canada)], E-mail: william@physics.utoronto.ca

    2008-02-15

    Beam conditions and the potential detector damage resulting from their anomalies have pushed the LHC experiments to build their own beam monitoring devices. The ATLAS Beam Conditions Monitor (BCM) consists of two stations (forward and backward) of detectors each with four modules. The sensors are required to tolerate doses up to 500 kGy and in excess of 10{sup 15} charged particles per cm{sup 2} over the lifetime of the experiment. Each module includes two diamond sensors read out in parallel. The stations are located symmetrically around the interaction point, positioning the diamond sensors at z = {+-}184 cm and r = 55 mm (a pseudo- rapidity of about 4.2). Equipped with fast electronics (2 ns rise time) these stations measure time-of-flight and pulse height to distinguish events resulting from lost beam particles from those normally occurring in proton-proton interactions. The BCM also provides a measurement of bunch-by-bunch luminosities in ATLAS by counting in-time and out-of-time collisions. Eleven detector modules have been fully assembled and tested. Tests performed range from characterisation of diamond sensors to full module tests with electron sources and in proton testbeams. Testbeam results from the CERN SPS show a module median-signal to noise of 11:1 for minimum ionising particles incident at a 45-degree angle. The best eight modules were installed on the ATLAS pixel support frame that was inserted into ATLAS in the summer of 2007. This paper describes the full BCM detector system along with simulation studies being used to develop the logic in the back-end FPGA coincidence hardware.

  10. iAssist: a software framework for intelligent patient monitoring.

    Science.gov (United States)

    Brouse, Christopher; Dumont, Guy; Yang, Ping; Lim, Joanne; Ansermino, J Mark

    2007-01-01

    A software framework (iAssist) has been developed for intelligent patient monitoring, and forms the foundation of a clinical monitoring expert system. The framework is extensible, flexible, and interoperable. It supports plugins to perform data acquisition, signal processing, graphical display, data storage, and output to external devices. iAssist currently incorporates two plugins to detect change point events in physiological trends. In 38 surgical cases, iAssist detected 868 events, of which clinicians rated more than 50% as clinically significant and less than 7% as artifacts. Clinicians found iAssist intuitive and easy to use.

  11. Maintenance cost avoidance through comprehensive condition monitoring

    International Nuclear Information System (INIS)

    Miller, G.P.; McClymonds, S.L.

    1990-01-01

    Condition monitoring, the measurement and trending of a critical parameter for predictive maintenance, has reached new levels of acceptance and application within the utility and manufacturing industry. Commercially available systems extend well beyond traditional vibration-monitoring systems to include such areas as online wear, crack and leak detection, and stress monitoring. The challenge facing industry is to integrate the information generated from condition monitoring. Current studies indicate that the effectiveness of predictive maintenance depends much more on the program that is established to apply the monitoring techniques than on the monitoring equipment itself. This paper presents a five-phase approach to developing a condition monitoring program

  12. A new type of intelligent wireless sensing network for health monitoring of large-size structures

    Science.gov (United States)

    Lei, Ying; Liu, Ch.; Wu, D. T.; Tang, Y. L.; Wang, J. X.; Wu, L. J.; Jiang, X. D.

    2009-07-01

    In recent years, some innovative wireless sensing systems have been proposed. However, more exploration and research on wireless sensing systems are required before wireless systems can substitute for the traditional wire-based systems. In this paper, a new type of intelligent wireless sensing network is proposed for the heath monitoring of large-size structures. Hardware design of the new wireless sensing units is first studied. The wireless sensing unit mainly consists of functional modules of: sensing interface, signal conditioning, signal digitization, computational core, wireless communication and battery management. Then, software architecture of the unit is introduced. The sensing network has a two-level cluster-tree architecture with Zigbee communication protocol. Important issues such as power saving and fault tolerance are considered in the designs of the new wireless sensing units and sensing network. Each cluster head in the network is characterized by its computational capabilities that can be used to implement the computational methodologies of structural health monitoring; making the wireless sensing units and sensing network have "intelligent" characteristics. Primary tests on the measurement data collected by the wireless system are performed. The distributed computational capacity of the intelligent sensing network is also demonstrated. It is shown that the new type of intelligent wireless sensing network provides an efficient tool for structural health monitoring of large-size structures.

  13. An Intelligent Monitoring Network for Detection of Cracks in Anvils of High-Press Apparatus.

    Science.gov (United States)

    Tian, Hao; Yan, Zhaoli; Yang, Jun

    2018-04-09

    Due to the endurance of alternating high pressure and temperature, the carbide anvils of the high-press apparatus, which are widely used in the synthetic diamond industry, are prone to crack. In this paper, an acoustic method is used to monitor the crack events, and the intelligent monitoring network is proposed to classify the sound samples. The pulse sound signals produced by such cracking are first extracted based on a short-time energy threshold. Then, the signals are processed with the proposed intelligent monitoring network to identify the operation condition of the anvil of the high-pressure apparatus. The monitoring network is an improved convolutional neural network that solves the problems that may occur in practice. The length of pulse sound excited by the crack growth is variable, so a spatial pyramid pooling layer is adopted to solve the variable-length input problem. An adaptive weighted algorithm for loss function is proposed in this method to handle the class imbalance problem. The good performance regarding the accuracy and balance of the proposed intelligent monitoring network is validated through the experiments finally.

  14. Advancing satellite operations with intelligent graphical monitoring systems

    Science.gov (United States)

    Hughes, Peter M.; Shirah, Gregory W.; Luczak, Edward C.

    1993-01-01

    For nearly twenty-five years, spacecraft missions have been operated in essentially the same manner: human operators monitor displays filled with alphanumeric text watching for limit violations or other indicators that signal a problem. The task is performed predominately by humans. Only in recent years have graphical user interfaces and expert systems been accepted within the control center environment to help reduce operator workloads. Unfortunately, the development of these systems is often time consuming and costly. At the NASA Goddard Space Flight Center (GSFC), a new domain specific expert system development tool called the Generic Spacecraft Analyst Assistant (GenSAA) has been developed. Through the use of a highly graphical user interface and point-and-click operation, GenSAA facilitates the rapid, 'programming-free' construction of intelligent graphical monitoring systems to serve as real-time, fault-isolation assistants for spacecraft analysts. Although specifically developed to support real-time satellite monitoring, GenSAA can support the development of intelligent graphical monitoring systems in a variety of space and commercial applications.

  15. The ATLAS beam conditions monitor

    CERN Document Server

    Mikuz, M; Dolenc, I; Kagan, H; Kramberger, G; Frais-Kölbl, H; Gorisek, A; Griesmayer, E; Mandic, I; Pernegger, H; Trischuk, W; Weilhammer, P; Zavrtanik, M

    2006-01-01

    The ATLAS beam conditions monitor is being developed as a stand-alone device allowing to separate LHC collisions from background events induced either on beam gas or by beam accidents, for example scraping at the collimators upstream the spectrometer. This separation can be achieved by timing coincidences between two stations placed symmetric around the interaction point. The 25 ns repetition of collisions poses very stringent requirements on the timing resolution. The optimum separation between collision and background events is just 12.5 ns implying a distance of 3.8 m between the two stations. 3 ns wide pulses are required with 1 ns rise time and baseline restoration in 10 ns. Combined with the radiation field of 10/sup 15/ cm/sup -2/ in 10 years of LHC operation only diamond detectors are considered suitable for this task. pCVD diamond pad detectors of 1 cm/sup 2/ and around 500 mum thickness were assembled with a two-stage RF current amplifier and tested in proton beam at MGH, Boston and SPS pion beam at...

  16. Making intelligent systems team players. A guide to developing intelligent monitoring systems

    Science.gov (United States)

    Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

    1995-01-01

    This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

  17. A simple condition monitoring model for a direct monitoring process

    NARCIS (Netherlands)

    Christer, A.H.; Wang, Wenbin

    1995-01-01

    This paper addresses the problem of condition monitoring of a component which has available a measure of condition called wear. Wear accumulates over time and monitoring inspections are performed at chosen times to monitor and measure the cumulative wear. If past measurements of wear are available

  18. Intelligent monitoring of YAG laser welding on steam generator tubes

    International Nuclear Information System (INIS)

    Hosaka, Shigetaka; Nagura, Yasumi; Ishide, Takashi; Nagashima, Tadashi; Akaba, Takashi

    1992-01-01

    The 'KASHIKOKI' intelligent device for monitoring the YAG laser welding of steam generator tubes is described in this paper. The 'KASHIKOKI', it monitors the series of six channels, for example, the reflected laser beam and the welding speed, etc. It learns the normal criteria and the anomalous criteria of welding, and discriminates between normal and anomalous welding using the learned criteria, and distinguishes the anomaly into several types. As the results of evaluation test, the degree of correspondence between this device and an expert is about 90%. This paper describes the new methods the multi-variate analysis model for discriminating between normal and anomalous welding, and a neural network model for distinguishing the types of anomaly. (author)

  19. Intelligent monitoring-based safety system of massage robot

    Institute of Scientific and Technical Information of China (English)

    胡宁; 李长胜; 王利峰; 胡磊; 徐晓军; 邹雲鹏; 胡玥; 沈晨

    2016-01-01

    As an important attribute of robots, safety is involved in each link of the full life cycle of robots, including the design, manufacturing, operation and maintenance. The present study on robot safety is a systematic project. Traditionally, robot safety is defined as follows: robots should not collide with humans, or robots should not harm humans when they collide. Based on this definition of robot safety, researchers have proposed ex ante and ex post safety standards and safety strategies and used the risk index and risk level as the evaluation indexes for safety methods. A massage robot realizes its massage therapy function through applying a rhythmic force on the massage object. Therefore, the traditional definition of safety, safety strategies, and safety realization methods cannot satisfy the function and safety requirements of massage robots. Based on the descriptions of the environment of massage robots and the tasks of massage robots, the present study analyzes the safety requirements of massage robots; analyzes the potential safety dangers of massage robots using the fault tree tool; proposes an error monitoring-based intelligent safety system for massage robots through monitoring and evaluating potential safety danger states, as well as decision making based on potential safety danger states; and verifies the feasibility of the intelligent safety system through an experiment.

  20. Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection.

    Science.gov (United States)

    Son, Junggab; Park, Juyoung; Oh, Heekuck; Bhuiyan, Md Zakirul Alam; Hur, Junbeom; Kang, Kyungtae

    2017-06-12

    Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan-Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities.

  1. Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection †

    Science.gov (United States)

    Son, Junggab; Park, Juyoung; Oh, Heekuck; Bhuiyan, Md Zakirul Alam; Hur, Junbeom; Kang, Kyungtae

    2017-01-01

    Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan–Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities. PMID:28604628

  2. Dealing with distributed intelligence in monitoring and control systems

    International Nuclear Information System (INIS)

    McLaren, R.A.

    1981-01-01

    The Euorpean Hybrid Spectrometer is built up of many individual detectors, each having widely varying monitoring and control requirements. With the advent of cheap microprocessor systems a shift from the concept of a single monitoring and control computer of that of distributed intelligent controllers has been economically feasible. A detector designer can now thoroughly test and debug a complete monitoring and control system on a local, dedicated micro-computer, while during operation, the central computer can be relieved of many simple repetitive tasks. Rapidly, however, it has become obvious that the designers of these systems have to take into account the final operational environment and build into both the hardware and software, features allowing easy integration into a central monitoring and control chain. In addition, the problems of maintenance and enventual modification have to be taken into consideration early in the development. Examples of currently operational systems will be briefly described to demonstrate how a set of basic guidelines plus standardisation of hardware/software can minimise the problems of integration and maintenance. Based on practical experience gained in the European Hybrid Spectrometer, investigations are proceeding on various possible alternatives for future micro-computer based monitoring and control systems. (orig.)

  3. Radiation monitoring of nuclear census intelligent data management and mobile monitoring data acquisition system

    International Nuclear Information System (INIS)

    Huang Libin; Zhong Zhijing; Zhou Yinhang; Guo Hongbo

    2014-01-01

    The system, employing advanced intelligent terminal, mobile applications, database technology, can achieve all kinds of field monitoring, mobile radiation monitoring data collected for laboratory analysis; employing GPS technology, can achieve the geographic information of the radiation monitoring data, time tagging and other anti-cheating measures; the system also established a mass database management system; the system is suitable for all types of nuclear-related units with special adaptive functions; system will be extended to GIS-based management capabilities of nuclear contamination distribution in latter stage. (authors)

  4. 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

  5. Simulation of Artificial Intelligence for Automotive Air-conditioning System

    Institute of Scientific and Technical Information of China (English)

    YUAN Xiao-mei; CHEN You-hua; CHEN Zhi-jiu

    2002-01-01

    The artificial intelligence is applied to the simulation of the automotive air-conditioning system ( AACS )According to the system's characteristics a model of AACS, based on neural network, is developed. Different control methods of AACS are discussed through simulation based on this model. The result shows that the neural- fuzzy control is the best one compared with the on-off control and conventional fuzzy control method.It can make the compartment's temperature descend rapidly to the designed temperature and the fluctuation is small.

  6. Intelligent IPv6 based iot network monitoring and altering system on ...

    African Journals Online (AJOL)

    Intelligent IPv6 based iot network monitoring and altering system on Cooja framework. ... Journal of Fundamental and Applied Sciences. Journal Home · ABOUT THIS ... Keywords: IoT; Cooja framework; Contiki OS; packet monitoring.

  7. Intelligent vehicle based traffic monitoring – exploring application in South Africa

    CSIR Research Space (South Africa)

    Labuschagne, FJJ

    2010-08-01

    Full Text Available The paper details the anticipated benefits of an intelligent vehicle based traffic monitoring approach holds. The approach utilises advanced technology with the potential to reduce crashes and includes the monitor of vehicle speeds and flows...

  8. 28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Monitoring and auditing of grants for the funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding...

  9. A camac-based intelligent subsystem for ATLAS example application: cryogenic monitoring and control

    International Nuclear Information System (INIS)

    Pardo, R.; Kawarasaki, Y.; Wasniewski, K.

    1985-01-01

    A subunit of the CAMAC accelerator control system of ATLAS for monitoring and, eventually, controlling the cryogenic refrigeration and distribution facility is under development. This development is the first application of a philosophy of distributed intelligence which will be applied throughout the ATLAS control system. The control concept is that of an intelligent subunit of the existing ATLAS CAMAC control highway. A single board computer resides in an auxiliary crate controller which allows access to all devices within the crate. The local SBC can communicate to the host over the CAMAC highway via a protocol involving the use of memory in the SBC which can be accessed from the host in a DMA mode. This provides a mechanism for global communications, such as for alarm conditions, as well as allowing the cryogenic system to respond to the demands of the accelerator system

  10. CAMAC-based intelligent subsystem for ATLAS example application: cryogenic monitoring and control

    International Nuclear Information System (INIS)

    Pardo, R.; Kawarasaki, Y.; Wasniewski, K.

    1985-01-01

    A subunit of the CAMAC accelerator control system of ATLAS for monitoring and, eventually, controlling the cryogenic refrigeration and distribution facility is under development. This development is the first application of a philosophy of distributed intelligence which will be applied throughout the ATLAS control system. The control concept is that of an intelligent subunit of the existing ATLAS CAMAC control highway. A single board computer resides in an auxiliary crate controller which allows access to all devices within the crate. The local SBC can communicate to the host over the CAMAC highway via a protocol involving the use of memory in the SBC which can be accessed from the host in a DMA mode. This provides a mechanism for global communications, such as for alarm conditions, as well as allowing the cryogenic system to respond to the demands of the accelerator system

  11. Reconfigurable intelligent sensors for health monitoring: a case study of pulse oximeter sensor.

    Science.gov (United States)

    Jovanov, E; Milenkovic, A; Basham, S; Clark, D; Kelley, D

    2004-01-01

    Design of low-cost, miniature, lightweight, ultra low-power, intelligent sensors capable of customization and seamless integration into a body area network for health monitoring applications presents one of the most challenging tasks for system designers. To answer this challenge we propose a reconfigurable intelligent sensor platform featuring a low-power microcontroller, a low-power programmable logic device, a communication interface, and a signal conditioning circuit. The proposed solution promises a cost-effective, flexible platform that allows easy customization, run-time reconfiguration, and energy-efficient computation and communication. The development of a common platform for multiple physical sensors and a repository of both software procedures and soft intellectual property cores for hardware acceleration will increase reuse and alleviate costs of transition to a new generation of sensors. As a case study, we present an implementation of a reconfigurable pulse oximeter sensor.

  12. Process monitoring for intelligent manufacturing processes - Methodology and application to Robot Assisted Polishing

    DEFF Research Database (Denmark)

    Pilny, Lukas

    Process monitoring provides important information on the product, process and manufacturing system during part manufacturing. Such information can be used for process optimization and detection of undesired processing conditions to initiate timely actions for avoidance of defects, thereby improving...... quality assurance. This thesis is aimed at a systematic development of process monitoring solutions, constituting a key element of intelligent manufacturing systems towards zero defect manufacturing. A methodological approach of general applicability is presented in this concern.The approach consists...... of six consecutive steps for identification of product Vital Quality Characteristics (VQCs) and Key Process Variables (KPVs), selection and characterization of sensors, optimization of sensors placement, validation of the monitoring solutions, definition of the reference manufacturing performance...

  13. Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM).

    Science.gov (United States)

    Nadiri, Ata Allah; Gharekhani, Maryam; Khatibi, Rahman; Sadeghfam, Sina; Moghaddam, Asghar Asghari

    2017-01-01

    This research presents a Supervised Intelligent Committee Machine (SICM) model to assess groundwater vulnerability indices of an aquifer. SICM uses Artificial Neural Networks (ANN) to overarch three Artificial Intelligence (AI) models: Support Vector Machine (SVM), Neuro-Fuzzy (NF) and Gene Expression Programming (GEP). Each model uses the DRASTIC index, the acronym of 7 geological, hydrological and hydrogeological parameters, which collectively represents intrinsic (or natural) vulnerability and gives a sense of contaminants, such as nitrate-N, penetrating aquifers from the surface. These models are trained to modify or condition their DRASTIC index values by measured nitrate-N concentration. The three AI-techniques often perform similarly but have differences as well and therefore SICM exploits the situation to improve the modeled values by producing a hybrid modeling results through selecting better performing SVM, NF and GEP components. The models of the study area at Ardabil aquifer show that the vulnerability indices by the DRASTIC framework produces sharp fronts but AI models smoothen the fronts and reflect a better correlation with observed nitrate values; SICM improves on the performances of three AI models and cope well with heterogeneity and uncertain parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Road Vehicle Monitoring System Based on Intelligent Visual Internet of Things

    Directory of Open Access Journals (Sweden)

    Qingwu Li

    2015-01-01

    Full Text Available In recent years, with the rapid development of video surveillance infrastructure, more and more intelligent surveillance systems have employed computer vision and pattern recognition techniques. In this paper, we present a novel intelligent surveillance system used for the management of road vehicles based on Intelligent Visual Internet of Things (IVIoT. The system has the ability to extract the vehicle visual tags on the urban roads; in other words, it can label any vehicle by means of computer vision and therefore can easily recognize vehicles with visual tags. The nodes designed in the system can be installed not only on the urban roads for providing basic information but also on the mobile sensing vehicles for providing mobility support and improving sensing coverage. Visual tags mentioned in this paper consist of license plate number, vehicle color, and vehicle type and have several additional properties, such as passing spot and passing moment. Moreover, we present a fast and efficient image haze removal method to deal with haze weather condition. The experiment results show that the designed road vehicle monitoring system achieves an average real-time tracking accuracy of 85.80% under different conditions.

  15. Development of an intelligent hydroinformatic system for real-time monitoring and assessment of civil infrastructure

    Science.gov (United States)

    Cahill, Paul; Michalis, Panagiotis; Solman, Hrvoje; Kerin, Igor; Bekic, Damir; Pakrashi, Vikram; McKeogh, Eamon

    2017-04-01

    With the effects of climate change becoming more apparent, extreme weather events are now occurring with greater frequency throughout the world. Such extreme events have resulted in increased high intensity flood events which are having devastating consequences on hydro-structures, especially on bridge infrastructure. The remote and often inaccessible nature of such bridges makes inspections problematic, a major concern if safety assessments are required during and after extreme flood events. A solution to this is the introduction of smart, low cost sensing solutions at locations susceptible to hydro-hazards. Such solutions can provide real-time information on the health of the bridge and its environments, with such information aiding in the mitigation of the risks associated with extreme weather events. This study presents the development of an intelligent system for remote, real-time monitoring of hydro-hazards to bridge infrastructure. The solution consists of two types of remote monitoring stations which have the capacity to monitor environmental conditions and provide real-time information to a centralized, big data database solution, from which an intelligent decision support system will accommodate the results to control and manage bridge, river and catchment assets. The first device developed as part of the system is the Weather Information Logging Device (WILD), which monitors rainfall, temperature and air and soil moisture content. The ability of the WILD to monitor rainfall in real time enables flood early warning alerts and predictive river flow conditions, thereby enabling decision makers the ability to make timely and effective decisions about critical infrastructures in advance of extreme flood events. The WILD is complemented by a second monitoring device, the Bridge Information Recording Device (BIRD), which monitors water levels at a given location in real-time. The monitoring of water levels of a river allows for, among other applications

  16. Condition based monitoring, diagnosis and maintenance on operating equipments of a hydraulic generator unit

    International Nuclear Information System (INIS)

    Liu, X T; Feng, F Z; Si, A W

    2012-01-01

    According to performance characteristics of operating equipments in a hydraulic generator unit (HGU), the relative techniques on condition monitoring and fault diagnosis (CMFD) are introduced in this paper, especially the key technologies are emphasized, such as equipment monitoring, expert system (ES), intelligent diagnosis and condition based maintenance (CBM). Meanwhile, according to the instructor on CBM proposed by State electric power corporation, based on integrated mode, the main steps on implementation of CBM are discussed in this paper.

  17. Decision Support System for Condition Monitoring Technologies

    NARCIS (Netherlands)

    Mouatamir, Abderrahim

    2018-01-01

    The technological feasibility of a condition-based maintenance (CBM) policy is intrinsically related to the suitable selection of condition monitoring (CM) technologies such as vibration- and oil analysis or other non-destructive testing (NDT) techniques such as radiographic- and magnetic particle

  18. Machinery condition monitoring principles and practices

    CERN Document Server

    Mohanty, Amiya Ranjan

    2015-01-01

    Find the Fault in the MachinesDrawing on the author's more than two decades of experience with machinery condition monitoring and consulting for industries in India and abroad, Machinery Condition Monitoring: Principles and Practices introduces the practicing engineer to the techniques used to effectively detect and diagnose faults in machines. Providing the working principle behind the instruments, the important elements of machines as well as the technique to understand their conditions, this text presents every available method of machine fault detection occurring in machines in general, an

  19. Ambient intelligence for monitoring and research in clinical neurophysiology and medicine: the MIMERICA* project and prototype.

    Science.gov (United States)

    Pignolo, L; Riganello, F; Dolce, G; Sannita, W G

    2013-04-01

    Ambient Intelligence (AmI) provides extended but unobtrusive sensing and computing devices and ubiquitous networking for human/environment interaction. It is a new paradigm in information technology compliant with the international Integrating Healthcare Enterprise board (IHE) and eHealth HL7 technological standards in the functional integration of biomedical domotics and informatics in hospital and home care. AmI allows real-time automatic recording of biological/medical information and environmental data. It is extensively applicable to patient monitoring, medicine and neuroscience research, which require large biomedical data sets; for example, in the study of spontaneous or condition-dependent variability or chronobiology. In this respect, AML is equivalent to a traditional laboratory for data collection and processing, with minimal dedicated equipment, staff, and costs; it benefits from the integration of artificial intelligence technology with traditional/innovative sensors to monitor clinical or functional parameters. A prototype AmI platform (MIMERICA*) has been implemented and is operated in a semi-intensive unit for the vegetative and minimally conscious states, to investigate the spontaneous or environment-related fluctuations of physiological parameters in these conditions.

  20. Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

    Science.gov (United States)

    Guikema, Seth

    2012-07-01

    Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

  1. Proposal of an intelligent wayside monitoring system for detection of critical ice accumulations on railway vehicles

    Science.gov (United States)

    Michelberger, Frank; Wagner, Adrian; Ostermann, Michael; Maly, Thomas

    2017-09-01

    At railway lines with ballasted tracks, under unfavourable conditions, the so-called flying ballast can occur predominantly for trains driving at high speeds. Especially in wintertime, it is highly likely that the causes are adhered snow or ice deposits, which are falling off the vehicle. Due to the high kinetic energy, the impact can lead to the removal of ballast stones from the structure of the ballasted track. If the stones reach the height of vehicles underside, they may be accelerated significantly due to the collision with the vehicle or may detach further ice blocks. In the worst case, a reinforcing effect occurs, which can lead to considerable damage to railway vehicles (under-floor-area, vehicle exteriors, etc.) and infrastructure (signal masts, noise barriers, etc.). Additionally the flying gravel is a significant danger to people in the nearby area of the tracks. With this feasibility study the applicability and meaningfulness of an intelligent monitoring system for identification of the critical ice accumulation to prevent the ballast fly induced by ice dropping was examined. The key findings of the research are that the detection of ice on railway vehicles and the development of an intelligent monitoring seem to be possible with existing technologies, but a proof of concept in terms of field tests is necessary.

  2. Design and Development of Intelligent Electrodes for Future Digital Health Monitoring: A Review

    Science.gov (United States)

    Khairuddin, A. M.; Azir, K. N. F. Ku; Kan, P. Eh

    2018-03-01

    Electrodes are sensors used in electrocardiography (ECG) monitoring system to diagnose heart diseases. Over the years, diverse types of electrodes have been designed and developed to improve ECG monitoring system. However, more recently, with the technological advances and capabilities from the Internet of Things (IoT), cloud computing and data analytics in personalized healthcare, researchers are attempting to design and develop more effective as well as flexible ECG devices by using intelligent electrodes. This paper reviews previous works on electrodes used in electrocardiography (ECG) monitoring devices to identify the key ftures for designing and developing intelligent electrodes in digital health monitoring devices.

  3. Automated Machinery Health Monitoring Using Stress Wave Analysis & Artificial Intelligence

    National Research Council Canada - National Science Library

    Board, David

    1998-01-01

    .... Army, for application to helicopter drive train components. The system will detect structure borne, high frequency acoustic data, and process it with feature extraction and polynomial network artificial intelligence software...

  4. Using Wireless Sensor Networks to Achieve Intelligent Monitoring for High-Temperature Gas-Cooled Reactor

    Directory of Open Access Journals (Sweden)

    Jianghai Li

    2017-01-01

    Full Text Available High-temperature gas-cooled reactors (HTGR can incorporate wireless sensor network (WSN technology to improve safety and economic competitiveness. WSN has great potential in monitoring the equipment and processes within nuclear power plants (NPPs. This technology not only reduces the cost of regular monitoring but also enables intelligent monitoring. In intelligent monitoring, large sets of heterogeneous data collected by the WSN can be used to optimize the operation and maintenance of the HTGR. In this paper, WSN-based intelligent monitoring schemes that are specific for applications of HTGR are proposed. Three major concerns regarding wireless technology in HTGR are addressed: wireless devices interference, cybersecurity of wireless networks, and wireless standards selected for wireless platform. To process nonlinear and non-Gaussian data obtained by WSN for fault diagnosis, novel algorithms combining Kernel Entropy Component Analysis (KECA and support vector machine (SVM are developed.

  5. Operational performance of generator condition monitors

    International Nuclear Information System (INIS)

    Braun, J.M.; Brown, G.

    1990-01-01

    This paper reports on the generator condition monitor (GCM) developed in an attempt to detect overheating inside large turbine generators. As part of a broader study on rotating machinery diagnostics, generator condition monitors were evaluated under field conditions in a 550 MW turbogenerator. Small 100 W resistors coated with insulating paints and varnishes were mounted inside the generator to simulate insulation overheating. The GCM responded very rapidly to an overheating event, typically within two minutes, even for hot spots as small s 10 cm 2 . Similarly the aerosols produced on overheating were found extremely short lived, decaying within two to three minutes after overheating was discontinued. Use of heated ion chambers was found to desensitize the GCM regardless of the nature of the overheated insulation and in some cases would altogether prevent the GCM from reaching the 50% pre-set alarm level commonly used on GCMs

  6. Integrating structural health and condition monitoring

    DEFF Research Database (Denmark)

    May, Allan; Thöns, Sebastian; McMillan, David

    2015-01-01

    window’ allowing for the possible detection of faults up to 6 months in advance. The SHM system model uses a reduction in the probability of failure factor to account for lower modelling uncertainties. A case study is produced that shows a reduction in operating costs and also a reduction in risk......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...

  7. Electrical condition monitoring method for polymers

    Science.gov (United States)

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

    2010-02-16

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

  8. Automated Intelligent Monitoring and the Controlling Software System for Solar Panels

    OpenAIRE

    Nalamvar, Hitesh Sanzhay; Ivanov, Maksim Anatoljevich; Baydali, Sergey Anatolievich

    2017-01-01

    The inspection of the solar panels on a periodic basis is important to improve longevity and ensure performance of the solar system. To get the most solar potential of the photovoltaic (PV) system is possible through an intelligent monitoring & controlling system. The monitoring & controlling system has rapidly increased its popularity because of its user-friendly graphical interface for data acquisition, monitoring, controlling and measurements. In order to monitor the performance of the sys...

  9. Advanced condition monitoring program for turbine system

    International Nuclear Information System (INIS)

    Ono, Shigetoshi

    2015-01-01

    It is important for utilities to achieve a stable operation in nuclear power plants. To achieve it, plant anomalies that affect a stable operation must be found out and eliminated. Therefore, the advanced condition monitoring program was developed. In this program, a sophisticated heat balance model based on the actual plant data is adopted to identify plant anomalies at an incipient stage and the symptoms of plant anomalies are found by heat balance changes from the model calculation. The model calculation results have shown precise prediction for actual plant parameters. Moreover, this program has the diagnostic engine that helps operators derive the cause of plant anomalies. By using this monitoring program, the component reliability in the turbine system can be periodically monitored and assessed, and as a result the stable operation of nuclear power plants can be achieved. (author)

  10. An Intelligent Sensor for the Ultra-High-Frequency Partial Discharge Online Monitoring of Power Transformers

    Directory of Open Access Journals (Sweden)

    Jian Li

    2016-05-01

    Full Text Available Ultra-high-frequency (UHF partial discharge (PD online monitoring is an effective way to inspect potential faults and insulation defects in power transformers. The construction of UHF PD online monitoring system is a challenge because of the high-frequency and wide-frequency band of the UHF PD signal. This paper presents a novel, intelligent sensor for UHF PD online monitoring based on a new method, namely a level scanning method. The intelligent sensor can directly acquire the statistical characteristic quantities and is characterized by low cost, few data to output and transmit, Ethernet functionality, and small size for easy installation. The prototype of an intelligent sensor was made. Actual UHF PD experiments with three typical artificial defect models of power transformers were carried out in a laboratory, and the waveform recording method and intelligent sensor proposed were simultaneously used for UHF PD measurement for comparison. The results show that the proposed intelligent sensor is qualified for the UHF PD online monitoring of power transformers. Additionally, three methods to improve the performance of intelligent sensors were proposed according to the principle of the level scanning method.

  11. Condition Monitoring of the SSE Generation Fleet

    Science.gov (United States)

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

    2012-05-01

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

  12. A radioactive waste transportation package monitoring system for normal transport and accident emergency response conditions

    International Nuclear Information System (INIS)

    Brown, G.S.; Cashwell, J.W.; Apple, M.L.

    1993-01-01

    This paper addresses spent fuel and high level waste transportation history and prospects, discusses accident histories of radioactive material transport, discusses emergency responder needs and provides a general description of the Transportation Intelligent Monitoring System (TRANSIMS) design. The key objectives of the monitoring system are twofold: (1) to facilitate effective emergency response to accidents involving a radioactive waste transportation package, while minimizing risk to the public and emergency first-response personnel, and (2) to allow remote monitoring of transportation vehicle and payload conditions to enable research into radioactive material transportation for normal and accident conditions. (J.P.N.)

  13. Quaternion Based Thermal Condition Monitoring System

    Science.gov (United States)

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

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

  14. Intelligent monitoring, control, and security of critical infrastructure systems

    CERN Document Server

    Polycarpou, Marios

    2015-01-01

    This book describes the challenges that critical infrastructure systems face, and presents state of the art solutions to address them. How can we design intelligent systems or intelligent agents that can make appropriate real-time decisions in the management of such large-scale, complex systems? What are the primary challenges for critical infrastructure systems? The book also provides readers with the relevant information to recognize how important infrastructures are, and their role in connection with a society’s economy, security and prosperity. It goes on to describe state-of-the-art solutions to address these points, including new methodologies and instrumentation tools (e.g. embedded software and intelligent algorithms) for transforming and optimizing target infrastructures. The book is the most comprehensive resource to date for professionals in both the private and public sectors, while also offering an essential guide for students and researchers in the areas of modeling and analysis of critical in...

  15. Prediction and Optimization of Speech Intelligibility in Adverse Conditions

    NARCIS (Netherlands)

    Taal, C.H.

    2013-01-01

    In digital speech-communication systems like mobile phones, public address systems and hearing aids, conveying the message is one of the most important goals. This can be challenging since the intelligibility of the speech may be harmed at various stages before, during and after the transmission

  16. Nanosensors for a Monitoring System in Intelligent and Active Packaging

    Directory of Open Access Journals (Sweden)

    Guillermo Fuertes

    2016-01-01

    Full Text Available A theoretical wireless nanosensor network (WNSN system that gives information about the food packaging condition is proposed. The protection effectiveness is estimated by measuring many factors, such as the existence of microorganisms, bacteria, gases, and contaminants. This study is focused on the detection of an antimicrobial agent (AA attached on a polymer forming an active integrated package. All monitoring technologies for food conservation are analyzed. Nanobiosensor nanomachine (NM, which converts biological or chemical signals into electrical signals, is used. A mathematical model, which describes the constituent’s emigration from the package to food, is programmed in MatLab software. The results show three nanobiosensors forming a WNSN. The nanobiosensors are able to carry out the average concentration for different spots in the package. This monitoring system shows reading percentages in three degrees and different colors: excellent (green, good (cyan, and lacking (red. To confirm the utility of the model, different simulations are performed. Using the WNSNs, results of AA existing in food package (FP through time were successfully obtained.

  17. Intelligent monitoring of water chemistry - Diagnostic expert system DIWATM

    International Nuclear Information System (INIS)

    Metzner, W.; Streit, K.

    2002-01-01

    For fast and comprehensive evaluation of power plant water chemistry conditions and reliable diagnosis in the event of disturbances considerable advantages are provided by employment of the Diagnostic Expert System DIWA. The interface to the process control system (I and C) and the integration of the DIWA system in the office PC network are the preconditions that DIWA operates as a monitoring system in real time. The performance of diagnosis, which are processed by a fuzzy-logic-supported knowledge base ensures not only the detection of all disturbances but also different analyses of the plant operation mode. By editing the knowledge base the Al of the system can increase without system programming. (authors)

  18. Intelligent data management for real-time spacecraft monitoring

    Science.gov (United States)

    Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

    1992-01-01

    Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

  19. Condition Monitoring and Management from Acoustic Emissions

    DEFF Research Database (Denmark)

    Pontoppidan, Niels Henrik Bohl

    2005-01-01

    In the following, I will use technical terms without explanation as it gives the freedom to describe the project in a shorter form for those who already know. The thesis is about condition monitoring of large diesel engines from acoustic emission signals. The experiments have been focused...... is the analysis of the angular position changes of the engine related events such as fuel injection and valve openings, caused by operational load changes. With inspiration from speech recognition and voice effects the angular timing changes have been inverted with the event alignment framework. With the event...

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

    Energy Technology Data Exchange (ETDEWEB)

    Villaran, M.; Lofaro, R.; na

    2009-11-30

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

  1. System for monitoring microclimate conditions in greenhouse

    Directory of Open Access Journals (Sweden)

    Marković Dušan B.

    2014-01-01

    Full Text Available Monitoring microclimate parameters in different kind of environments has significant contribution to many areas of human activity and production processes. One of them is vegetable production in greenhouses where measurement of its microclimate parameters may influence the decision on taking appropriate action and protect crops. It is also important to preserve optimal condition in greenhouses to facilitate the process of transpiration, plant mineral nutrition and prevent of a variety physiological damage caused by a deficit of some specific nutrients. Systems for monitoring have wide application in the last years thanks to development of modern computer technology. In this paper model of the monitoring system based on smart transducer concept was introduced. Within the system components are based on MSP430 ultra low power micro controllers. They are using wireless communication to exchange data within the system that was structured according to smart transducer concept. User applications from the network could access to system interface using HTTP protocol where web server could be running on the computer or it could be an embedded web server running on micro controller based device.

  2. Realization of Intelligent Household Appliance Wireless Monitoring Network Based on LEACH Protocol

    Directory of Open Access Journals (Sweden)

    Weilong ZHOU

    2014-06-01

    Full Text Available The intelligent household appliance wireless monitoring network can real-time monitor the apparent power and power factor of various household appliances in different indoor regions, and can realize the real-time monitoring on the household appliance working status and performance. The household appliance wireless monitoring network based on LEACH protocol is designed in the paper. Firstly, the basic idea of LEACH routing algorithm is proposed. Aiming at the node-distribution feature of intelligent home, the selection of cluster head in the routing algorithm and the data transmission method at the stable communication phase is modified. Moreover, the hardware circuit of power acquisition and power factor measurement is designed. The realization of wireless monitoring network based on CC2530 is described, each module and the whole system were conducted the on-line debugging. Finally, the system is proved to meet the practical requirement through the networking test.

  3. Artificial Intelligence Monitoring of Hardening Methods and Cutting Conditions and Their Effects on Surface Roughness, Performance, and Finish Turning Costs of Solid-State Recycled Aluminum Alloy 6061 Сhips

    Directory of Open Access Journals (Sweden)

    Adel Taha Abbas

    2018-05-01

    Full Text Available Aluminum Alloy 6061 components are frequently manufactured for various industries—aeronautics, yachting, and optical instruments—due to their excellent physical and mechanical properties, including corrosion resistance. There is little research on the mechanical tooling of AA6061 and none on its structure and properties and their effects on surface roughness after finish turning. The objective of this comprehensive study is, therefore, to ascertain the effects of both the modern method of hardening AA6061 shafts and the finish turning conditions on surface roughness, Ra, and the minimum machining time for unit-volume removal, Tm, while also establishing the cost price of processing one part, C. The hardening methods improved both the physical and the mechanical material properties processed with 2, 4, and 6 passes of equal channel angular pressing (ECAP at room temperature, using an ECAP-matrix with a channel angle of 90°. The reference workpiece sample was a hot extruded chip under an extrusion ratio (ER of 5.2 at an extrusion temperature of 500 °С (ET = 500 °C. The following results were obtained: grain size in ECAP-6 decreased from 15.9 to 2.46 μm, increasing both microhardness from 41 Vickers hardness value (HV to 110 HV and ultimate tensile strength from 132.4 to 403 MPa. The largest decrease in surface roughness, Ra—70%, was obtained turning a workpiece treated with ECAP-6. The multicriteria optimization was computed in a multilayer perceptron-based artificial neural network that yielded the following optimum values: the minimal length of the three-dimensional estimates vector with the coordinates Ra = 0.800 μm, Tm = 0.341 min/cm3, and С = 6.955 $ corresponded to the optimal finish turning conditions: cutting speed vc = 200 m/min, depth of cut ap = 0.2 mm, and feed per revolution fr = 0.103 mm/rev (ET-500 extrusion without hardening.

  4. A Multisensing Setup for the Intelligent Tire Monitoring.

    Science.gov (United States)

    Coppo, Francesco; Pepe, Gianluca; Roveri, Nicola; Carcaterra, Antonio

    2017-03-12

    The present paper offers the chance to experimentally measure, for the first time, the internal tire strain by optical fiber sensors during the tire rolling in real operating conditions. The phenomena that take place during the tire rolling are in fact far from being completely understood. Despite several models available in the technical literature, there is not a correspondently large set of experimental observations. The paper includes the detailed description of the new multi-sensing technology for an ongoing vehicle measurement, which the research group has developed in the context of the project OPTYRE. The experimental apparatus is mainly based on the use of optical fibers with embedded Fiber Bragg Gratings sensors for the acquisition of the circumferential tire strain. Other sensors are also installed on the tire, such as a phonic wheel, a uniaxial accelerometer, and a dynamic temperature sensor. The acquired information is used as input variables in dedicated algorithms that allow the identification of key parameters, such as the dynamic contact patch, instantaneous dissipation and instantaneous grip. The OPTYRE project brings a contribution into the field of experimental grip monitoring of wheeled vehicles, with implications both on passive and active safety characteristics of cars and motorbikes.

  5. A Multisensing Setup for the Intelligent Tire Monitoring

    Directory of Open Access Journals (Sweden)

    Francesco Coppo

    2017-03-01

    Full Text Available The present paper offers the chance to experimentally measure, for the first time, the internal tire strain by optical fiber sensors during the tire rolling in real operating conditions. The phenomena that take place during the tire rolling are in fact far from being completely understood. Despite several models available in the technical literature, there is not a correspondently large set of experimental observations. The paper includes the detailed description of the new multi-sensing technology for an ongoing vehicle measurement, which the research group has developed in the context of the project OPTYRE. The experimental apparatus is mainly based on the use of optical fibers with embedded Fiber Bragg Gratings sensors for the acquisition of the circumferential tire strain. Other sensors are also installed on the tire, such as a phonic wheel, a uniaxial accelerometer, and a dynamic temperature sensor. The acquired information is used as input variables in dedicated algorithms that allow the identification of key parameters, such as the dynamic contact patch, instantaneous dissipation and instantaneous grip. The OPTYRE project brings a contribution into the field of experimental grip monitoring of wheeled vehicles, with implications both on passive and active safety characteristics of cars and motorbikes.

  6. An integrated system for pipeline condition monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Strong, Andrew P.; Lees, Gareth; Hartog, Arthur; Twohig, Richard; Kader, Kamal; Hilton, Graeme; Mullens, Stephen; Khlybov, Artem [Schlumberger, Southampton (United Kingdom); Sanderson, Norman [BP Exploration, Sunbury (United Kingdom)

    2009-07-01

    In this paper we present the unique and innovative 'Integriti' pipeline and flow line integrity monitoring system developed by Schlumberger in collaboration with BP. The system uses optical fiber distributed sensors to provide simultaneous distributed measurements of temperature, strain and vibration for the detection, monitoring, and location of events including: Third Party Interference (TPI), including multiple simultaneous disturbances; geo-hazards and landslides; gas and oil leaks; permafrost protection. The Integriti technology also provides a unique means for tracking the progress of cleaning and instrumented pigs using existing optical telecom and data communications cables buried close to pipelines. The Integriti solution provides a unique and proactive approach to pipeline integrity management. It performs analysis of a combination of measurands to provide the pipeline operator with an event recognition and location capability, in effect providing a hazard warning system, and offering the operator the potential to take early action to prevent loss. Through the use of remote, optically powered amplification, an unprecedented detection range of 100 km is possible without the need for any electronics and therefore remote power in the field. A system can thus monitor 200 km of pipeline when configured to monitor 100 km upstream and downstream from a single location. As well as detecting conditions and events leading to leaks, this fully integrated system provides a means of detecting and locating small leaks in gas pipelines below the threshold of present online leak detection systems based on monitoring flow parameters. Other significant benefits include: potential reductions in construction costs; enhancement of the operator's existing integrity management program; potential reductions in surveillance costs and HSE risks. In addition to onshore pipeline systems this combination of functionality and range is available for practicable

  7. An intelligent system for monitoring and diagnosis of the CO{sub 2} capture process

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Q.; Chan, C.W.; Tontiwachwuthikul, P. [University of Regina, Regina, SK (Canada). Faculty of Engineering

    2011-07-15

    Amine-based carbon dioxide capture has been widely considered as a feasible ideal technology for reducing large-scale CO{sub 2} emissions and mitigating global warming. The operation of amine-based CO{sub 2} capture is a complicated task, which involves monitoring over 100 process parameters and careful manipulation of numerous valves and pumps. The current research in the field of CO{sub 2} capture has emphasized the need for improving CO{sub 2} capture efficiency and enhancing plant performance. In the present study, artificial intelligence techniques were applied for developing a knowledge-based expert system that aims at effectively monitoring and controlling the CO{sub 2} capture process and thereby enhancing CO{sub 2} capture efficiency. In developing the system, the inferential modeling technique (IMT) was applied to analyze the domain knowledge and problem-solving techniques, and a knowledge base was developed on DeltaV Simulate. The expert system helps to enhance CO{sub 2} capture system performance and efficiency by reducing the time required for diagnosis and problem solving if abnormal conditions occur. The expert system can be used as a decision-support tool that helps inexperienced operators control the plant: it can be used also for training novice operators.

  8. Condition monitoring of main coolant pumps, Dhruva

    International Nuclear Information System (INIS)

    Prasad, V.; Satheesh, C.; Acharya, V.N.; Tikku, A.C.; Mishra, S.K.

    2002-01-01

    Full text: Dhruva is a 100 MW research reactor with natural uranium fuel, heavy water as moderator and primary coolant. Three Centrifugal pumps circulate the primary coolant across the core and the heat exchangers. Each pump is coupled to a flywheel (FW) assembly in order to meet operational safety requirements. All the 3 main coolant pump (MCP) sets are required to operate during operation of the reactor. The pump-sets are in operation since the year 1984 and have logged more than 1,00,000 hrs. Frequent breakdowns of its FW bearings were experienced during initial years of operation. Condition monitoring of these pumps, largely on vibration based parameters, was initiated on regular basis. Break-downs of main coolant pumps reduced considerably due to the fair accurate predictions of incipient break-downs and timely maintenance efforts. An effort is made in this paper to share the experience

  9. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  10. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  11. Using business intelligence to monitor clinical quality metrics.

    Science.gov (United States)

    Resetar, Ervina; Noirot, Laura A; Reichley, Richard M; Storey, Patricia; Skiles, Ann M; Traynor, Patrick; Dunagan, W Claiborne; Bailey, Thomas C

    2007-10-11

    BJC HealthCare (BJC) uses a number of industry standard indicators to monitor the quality of services provided by each of its hospitals. By establishing an enterprise data warehouse as a central repository of clinical quality information, BJC is able to monitor clinical quality performance in a timely manner and improve clinical outcomes.

  12. Artificial intelligence and finite element modelling for monitoring flood defence structures

    NARCIS (Netherlands)

    Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

    2011-01-01

    We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the

  13. 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.

  14. Remote condition-based monitoring of turbines

    International Nuclear Information System (INIS)

    2005-01-01

    specific point in time; Timewave: Amount of motion and symmetry of wave shape (i.e., a truncated wave can be an indication of a rub); Orbits: A cross-sectional view of shaft movement; DC Gap Voltage: A measurement of the distance (e.g., gap) between the shaft and the proximity probes. This value is useful in determining bearing wear of shaft centerline location. Daily monitoring of these metrics will not only warn of impending failure, but provide valuable information regarding the possible cause of the impending failure and an approximate indication of time to failure. In the event of a sudden problem and subsequent trip of a turbine, this data helps determine the root cause of the failure. This results in faster problem resolution and a quicker restart of the turbine. Additionally, daily monitoring of these metrics allows companies to watch a problematic turbine's health until the next scheduled outage. Azima's remote, condition-based monitoring system and diagnostics service is an effective way to collect and trend these metrics on a daily basis, as well as supply expert advice in the event of any anomalies. The Azima system aggregates the analog data from the proximity probes mounted on the turbine at a sensor hub. The sensor hub digitizes the analog data and then, either wirelessly or through a wired Ethernet connection, sends the data via the Internet to a hosted server. The hosted server maintains the software that trends the data (e.g., vibration, spectrum, timewave, DC gap voltage, and orbits) and provides automatic alerting. The data can be accessed anywhere, anytime through a standard Web browser. The advantages of daily, remote, condition-based monitoring include: Daily monitoring of vital turbine health metrics to detect impending problems before they become critical; Automatic alerting when a change in condition is detected; Anywhere, anytime access via a standard Web browser. This allows multiple groups at different locations to simultaneously review and

  15. An agent-based intelligent environmental monitoring system

    OpenAIRE

    Athanasiadis, Ioannis N; Mitkas, Pericles A

    2004-01-01

    Fairly rapid environmental changes call for continuous surveillance and on-line decision making. There are two main areas where IT technologies can be valuable. In this paper we present a multi-agent system for monitoring and assessing air-quality attributes, which uses data coming from a meteorological station. A community of software agents is assigned to monitor and validate measurements coming from several sensors, to assess air-quality, and, finally, to fire alarms to appropriate recipie...

  16. Experimental Study on Intelligent Control Scheme for Fan Coil Air-Conditioning System

    Directory of Open Access Journals (Sweden)

    Yanfeng Li

    2013-01-01

    Full Text Available An intelligent control scheme for fan coil air-conditioning systems has been put forward in order to overcome the shortcomings of the traditional proportion-integral-derivative (PID control scheme. These shortcomings include the inability of anti-interference and large inertia. An intelligent control test rig of fan coil air-conditioning system has been built, and MATLAB/Simulink dynamics simulation software has been adopted to implement the intelligent control scheme. A software for data exchange has been developed to combine the intelligence control system and the building automation (BA system. Experimental tests have been conducted to investigate the effectiveness of different control schemes including the traditional PID control, fuzzy control, and fuzzy-PID control for fan coil air-conditioning system. The effects of control schemes have been compared and analyzed in robustness, static and dynamic character, and economy. The results have shown that the developed data exchange interface software can induce the intelligent control scheme of the BA system more effectively. Among the proposed control strategies, fuzzy-PID control scheme which has the advantages of both traditional PID and fuzzy schemes is the optimal control scheme for the fan coil air-conditioning system.

  17. Quantum Bayesian perspective for intelligence reservoir characterization, monitoring and management

    Science.gov (United States)

    Lozada Aguilar, Miguel Ángel; Khrennikov, Andrei; Oleschko, Klaudia; de Jesús Correa, María

    2017-10-01

    The paper starts with a brief review of the literature about uncertainty in geological, geophysical and petrophysical data. In particular, we present the viewpoints of experts in geophysics on the application of Bayesian inference and subjective probability. Then we present arguments that the use of classical probability theory (CP) does not match completely the structure of geophysical data. We emphasize that such data are characterized by contextuality and non-Kolmogorovness (the impossibility to use the CP model), incompleteness as well as incompatibility of some geophysical measurements. These characteristics of geophysical data are similar to the characteristics of quantum physical data. Notwithstanding all this, contextuality can be seen as a major deviation of quantum theory from classical physics. In particular, the contextual probability viewpoint is the essence of the Växjö interpretation of quantum mechanics. We propose to use quantum probability (QP) for decision-making during the characterization, modelling, exploring and management of the intelligent hydrocarbon reservoir. Quantum Bayesianism (QBism), one of the recently developed information interpretations of quantum theory, can be used as the interpretational basis for such QP decision-making in geology, geophysics and petroleum projects design and management. This article is part of the themed issue `Second quantum revolution: foundational questions'.

  18. Quantum Bayesian perspective for intelligence reservoir characterization, monitoring and management.

    Science.gov (United States)

    Lozada Aguilar, Miguel Ángel; Khrennikov, Andrei; Oleschko, Klaudia; de Jesús Correa, María

    2017-11-13

    The paper starts with a brief review of the literature about uncertainty in geological, geophysical and petrophysical data. In particular, we present the viewpoints of experts in geophysics on the application of Bayesian inference and subjective probability. Then we present arguments that the use of classical probability theory (CP) does not match completely the structure of geophysical data. We emphasize that such data are characterized by contextuality and non-Kolmogorovness (the impossibility to use the CP model), incompleteness as well as incompatibility of some geophysical measurements. These characteristics of geophysical data are similar to the characteristics of quantum physical data. Notwithstanding all this, contextuality can be seen as a major deviation of quantum theory from classical physics. In particular, the contextual probability viewpoint is the essence of the Växjö interpretation of quantum mechanics. We propose to use quantum probability (QP) for decision-making during the characterization, modelling, exploring and management of the intelligent hydrocarbon reservoir Quantum Bayesianism (QBism), one of the recently developed information interpretations of quantum theory, can be used as the interpretational basis for such QP decision-making in geology, geophysics and petroleum projects design and management.This article is part of the themed issue 'Second quantum revolution: foundational questions'. © 2017 The Author(s).

  19. An intelligent and networking solution of radiation monitoring system for LHC

    International Nuclear Information System (INIS)

    Shao Beibei; Gong Guanghua

    2001-01-01

    The LHC (the Large Hadron Collider), the largest accelerator in the world, is under designing and construction at CERN. It shares the 27 km LEP tunnel and is expected to be on the air in 2005. The Radiation Monitoring System of LEP was a central system with non-intelligent detectors. While as the proposed new RMS for LHC is a distributing intelligent networked system. Around 350 detectors will be employed. To save the cost, the design should make the old LEP's non-intelligent detectors reusable. To allow the detector controller automatic reports the detector database and net location through the world Fip bus, 1 wire components are embedded into the detectors and the network sockets. The radiation tolerance and the reliability of the communication of the wire components have been tested in a strong radiation field at CERN. The low cost components based position detection technique is valuable for most networked control system

  20. Intelligent energy management control of vehicle air conditioning system coupled with engine

    International Nuclear Information System (INIS)

    Khayyam, Hamid; Abawajy, Jemal; Jazar, Reza N.

    2012-01-01

    Vehicle Air Conditioning (AC) systems consist of an engine powered compressor activated by an electrical clutch. The AC system imposes an extra load to the vehicle's engine increasing the vehicle fuel consumption and emissions. Energy management control of the vehicle air conditioning is a nonlinear dynamic system, influenced by uncertain disturbances. In addition, the vehicle energy management control system interacts with different complex systems, such as engine, air conditioning system, environment, and driver, to deliver fuel consumption improvements. In this paper, we describe the energy management control of vehicle AC system coupled with vehicle engine through an intelligent control design. The Intelligent Energy Management Control (IEMC) system presented in this paper includes an intelligent algorithm which uses five exterior units and three integrated fuzzy controllers to produce desirable internal temperature and air quality, improved fuel consumption, low emission, and smooth driving. The three fuzzy controllers include: (i) a fuzzy cruise controller to adapt vehicle cruise speed via prediction of the road ahead using a Look-Ahead system, (ii) a fuzzy air conditioning controller to produce desirable temperature and air quality inside vehicle cabin room via a road information system, and (iii) a fuzzy engine controller to generate the required engine torque to move the vehicle smoothly on the road. We optimised the integrated operation of the air conditioning and the engine under various driving patterns and performed three simulations. Results show that the proposed IEMC system developed based on Fuzzy Air Conditioning Controller with Look-Ahead (FAC-LA) method is a more efficient controller for vehicle air conditioning system than the previously developed Coordinated Energy Management Systems (CEMS). - Highlights: ► AC interacts: vehicle, environment, driver components, and the interrelationships between them. ► Intelligent AC algorithm which uses

  1. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    OpenAIRE

    Bo Sun; Qiang Feng; Songjie Li

    2012-01-01

    According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

  2. Tiger: knowledge based gas turbine condition monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Trave-Massuyes, L. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Quevedo, J. [University of Catalonia, (Spain); Milne, R.; Nicol, Ch.

    1995-12-31

    Exxon petrochemical plant in Scotland requires continuous ethylene supply from offshore site in North Sea. The supply is achieved thanks to compressors driven by a 28 MW gas turbine, whose monitoring is of major importance. The TIGER fault diagnostic system is a knowledge base system containing a prediction model. (D.L.) 11 refs.

  3. Tiger: knowledge based gas turbine condition monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Trave-Massuyes, L [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Quevedo, J [University of Catalonia, (Spain); Milne, R; Nicol, Ch

    1996-12-31

    Exxon petrochemical plant in Scotland requires continuous ethylene supply from offshore site in North Sea. The supply is achieved thanks to compressors driven by a 28 MW gas turbine, whose monitoring is of major importance. The TIGER fault diagnostic system is a knowledge base system containing a prediction model. (D.L.) 11 refs.

  4. Integrated environmental control and monitoring in the intelligent workplace. Final report

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-31

    This project involved the design and engineering of the control and monitoring of environmental quality - visual, thermal, air - in the Intelligent Workplace. The research objectives were to study the performance of the individual systems, to study the integration issues related to each system, to develop a control plan, and to implement and test the integrated systems in a real setting. In this project, a control strategy with related algorithms for distributed sensors, actuators, and controllers for negotiating central and individual control of HVAC, lighting, and enclosure was developed in order to maximize user comfort, and energy and environmental effectiveness. The goal of the control system design in the Intelligent Workplace is the integration of building systems for optimization of occupant satisfaction, organizational flexibility, energy efficiency and environmental effectiveness. The task of designing this control system involves not only the research, development and demonstration of state-of-the-art mechanical and electrical systems, but also their integration. The ABSIC research team developed functional requirements for the environmental systems considering the needs of both facility manager and the user. There are three levels of control for the environmental systems: scheduled control, sensor control, and user control. The challenges are to achieve the highest possible levels of energy effectiveness simultaneously with the highest levels of user satisfaction. The report describes the components of each system, their implementation in the Intelligent Workplace and related control and monitoring issues.

  5. Technology review: prototyping platforms for monitoring ambient conditions.

    Science.gov (United States)

    Afolaranmi, Samuel Olaiya; Ramis Ferrer, Borja; Martinez Lastra, Jose Luis

    2018-05-08

    The monitoring of ambient conditions in indoor spaces is very essential owing to the amount of time spent indoors. Specifically, the monitoring of air quality is significant because contaminated air affects the health, comfort and productivity of occupants. This research work presents a technology review of prototyping platforms for monitoring ambient conditions in indoor spaces. It involves the research on sensors (for CO 2 , air quality and ambient conditions), IoT platforms, and novel and commercial prototyping platforms. The ultimate objective of this review is to enable the easy identification, selection and utilisation of the technologies best suited for monitoring ambient conditions in indoor spaces. Following the review, it is recommended to use metal oxide sensors, optical sensors and electrochemical sensors for IAQ monitoring (including NDIR sensors for CO 2 monitoring), Raspberry Pi for data processing, ZigBee and Wi-Fi for data communication, and ThingSpeak IoT platform for data storage, analysis and visualisation.

  6. Gearbox Condition Monitoring Using Advanced Classifiers

    Directory of Open Access Journals (Sweden)

    P. Večeř

    2010-01-01

    Full Text Available New efficient and reliable methods for gearbox diagnostics are needed in automotive industry because of growing demand for production quality. This paper presents the application of two different classifiers for gearbox diagnostics – Kohonen Neural Networks and the Adaptive-Network-based Fuzzy Interface System (ANFIS. Two different practical applications are presented. In the first application, the tested gearboxes are separated into two classes according to their condition indicators. In the second example, ANFIS is applied to label the tested gearboxes with a Quality Index according to the condition indicators. In both applications, the condition indicators were computed from the vibration of the gearbox housing. 

  7. Relationship between IQ, cultural intelligence and self-monitoring in the students of Birjand University of Medical Sciences

    Directory of Open Access Journals (Sweden)

    Aliakbar Esmaeili

    2016-09-01

    Full Text Available Background and Aim: Intelligence quotient (IQ, cultural intelligence, and self-monitoring are among important and influential parameters in learning-teaching process of students. Thus, the current study examined the relationship between these parameters in the students of Birjand University of Medical Science. Materials and Methods: The present study was a descriptive-analytic, cross-sectional type. The study population included all the students at Birjand University of Medical Sciences, selected through stratified randomized sampling method. In order to study IQ, cultural intelligence, and self-monitoring parameters R & B Cattell scale (Scale III, Erli’s Cultural Intelligence Inventory, and Snyder’s Self-monitoring Test were applied, respectively. The obtained data was fed into SPSS (V:21 software using Pearson correlation test, ANOVA, and t-test at the significant level of P≤0.05. Results: From a total of 171 subjects participating in the study, 53.2% were female. The average age of the participants was 21.3±2.7 years. The average IQ, cultural intelligence, and self-monitoring scores were 106±10.44, 85.73±17.31, and 12.35±3.20, respectively. There was a significant correlation between cultural intelligence and self-monitoring (P<0.000; r=0/37. However, there were no significant associations between cultural intelligence and IQ scores as well as between self-monitoring and IQ scores. Conclusion: Regarding the unfavorable cultural intelligence’ skills and abilities ;and their acquirable nature, it is suggested that University consider a significant position for educational and cultural programs in order to enhance cultural intelligence.

  8. Relationship between IQ, cultural intelligence and self-monitoring in the students of Birjand University of Medical Sciences

    Directory of Open Access Journals (Sweden)

    Aliakbar Esmaeili

    2016-12-01

    Full Text Available Background and Aim: Intelligence quotient (IQ, cultural intelligence, and self-monitoring are among important and influential parameters in learning-teaching process of students. Thus, the current study examined the relationship between these parameters in the students of Birjand University of Medical Science. Materials and Methods: The present study was a descriptive-analytic, cross-sectional type. The study population included all the students at Birjand University of Medical Sciences, selected through stratified randomized sampling method. In order to study IQ, cultural intelligence, and self-monitoring parameters R & B Cattell scale (Scale III, Erli’s Cultural Intelligence Inventory, and Snyder’s Self-monitoring Test were applied, respectively. The obtained data was fed into SPSS (V:21 software using Pearson correlation test, ANOVA, and t-test at the significant level of P≤0.05. Results: From a total of 171 subjects participating in the study, 53.2% were female. The average age of the participants was 21.3±2.7 years. The average IQ, cultural intelligence, and self-monitoring scores were 106±10.44, 85.73±17.31, and 12.35±3.20, respectively. There was a significant correlation between cultural intelligence and self-monitoring (P<0.000; r=0/37. However, there were no significant associations between cultural intelligence and IQ scores as well as between self-monitoring and IQ scores. Conclusion: Regarding the unfavorable cultural intelligence’ skills and abilities ;and their acquirable nature, it is suggested that University consider a significant position for educational and cultural programs in order to enhance cultural intelligence.

  9. Wireless Intelligent Monitoring and Control System of Greenhouse Temperature Based on Fuzzy-PID

    Directory of Open Access Journals (Sweden)

    Mei ZHAN

    2014-03-01

    Full Text Available Control effect is not ideal for traditional control method and wired control system, since greenhouse temperature has such characteristics as nonlinear and longtime lag. Therefore, Fuzzy- PID control method was introduced and radio frequency chip CC1110 was applied to design greenhouse wireless intelligent monitoring and control system. The design of the system, the component of nodes and the developed intelligent management software system were explained in this paper. Then describe the design of the control algorithm Fuzzy-PID. By simulating the new method in Matlab software, the results showed that Fuzzy-PID method small overshoot and better dynamic performance compared with general PID control. It has shorter settling time and no steady-state error compared with fuzzy control. It can meet requirements in greenhouse production.

  10. Intelligence and Neurophysiological Markers of Error Monitoring Relate to Children's Intellectual Humility.

    Science.gov (United States)

    Danovitch, Judith H; Fisher, Megan; Schroder, Hans; Hambrick, David Z; Moser, Jason

    2017-09-18

    This study explored developmental and individual differences in intellectual humility (IH) among 127 children ages 6-8. IH was operationalized as children's assessment of their knowledge and willingness to delegate scientific questions to experts. Children completed measures of IH, theory of mind, motivational framework, and intelligence, and neurophysiological measures indexing early (error-related negativity [ERN]) and later (error positivity [Pe]) error-monitoring processes related to cognitive control. Children's knowledge self-assessment correlated with question delegation, and older children showed greater IH than younger children. Greater IH was associated with higher intelligence but not with social cognition or motivational framework. ERN related to self-assessment, whereas Pe related to question delegation. Thus, children show separable epistemic and social components of IH that may differentially contribute to metacognition and learning. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

  11. Intelligent monitoring and fault diagnosis for ATLAS TDAQ: a complex event processing solution

    CERN Document Server

    Magnoni, Luca; Luppi, Eleonora

    Effective monitoring and analysis tools are fundamental in modern IT infrastructures to get insights on the overall system behavior and to deal promptly and effectively with failures. In recent years, Complex Event Processing (CEP) technologies have emerged as effective solutions for information processing from the most disparate fields: from wireless sensor networks to financial analysis. This thesis proposes an innovative approach to monitor and operate complex and distributed computing systems, in particular referring to the ATLAS Trigger and Data Acquisition (TDAQ) system currently in use at the European Organization for Nuclear Research (CERN). The result of this research, the AAL project, is currently used to provide ATLAS data acquisition operators with automated error detection and intelligent system analysis. The thesis begins by describing the TDAQ system and the controlling architecture, with a focus on the monitoring infrastructure and the expert system used for error detection and automated reco...

  12. Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring

    Directory of Open Access Journals (Sweden)

    Zhaozhuo Xu

    2016-01-01

    Full Text Available Wireless sensor networks are proved to be effective in long-time localized torrential rain monitoring. However, the existing widely used architecture of wireless sensor networks for rain monitoring relies on network transportation and back-end calculation, which causes delay in response to heavy rain in localized areas. Our work improves the architecture by applying logistic regression and support vector machine classification to an intelligent wireless sensor node which is created by Raspberry Pi. The sensor nodes in front-end not only obtain data from sensors, but also can analyze the probabilities of upcoming heavy rain independently and give early warnings to local clients in time. When the sensor nodes send the probability to back-end server, the burdens of network transport are released. We demonstrate by simulation results that our sensor system architecture has potentiality to increase the local response to heavy rain. The monitoring capacity is also raised.

  13. A multi-agent approach to intelligent monitoring in smart grids

    Science.gov (United States)

    Vallejo, D.; Albusac, J.; Glez-Morcillo, C.; Castro-Schez, J. J.; Jiménez, L.

    2014-04-01

    In this paper, we propose a scalable multi-agent architecture to give support to smart grids, paying special attention to the intelligent monitoring of distribution substations. The data gathered by multiple sensors are used by software agents that are responsible for monitoring different aspects or events of interest, such as normal voltage values or unbalanced intensity values that can end up blowing fuses and decreasing the quality of service of end consumers. The knowledge bases of these agents have been built by means of a formal model for normality analysis that has been successfully used in other surveillance domains. The architecture facilitates the integration of new agents and can be easily configured and deployed to monitor different environments. The experiments have been conducted over a power distribution network.

  14. Construction and application of an intelligent air quality monitoring system for healthcare environment.

    Science.gov (United States)

    Yang, Chao-Tung; Liao, Chi-Jui; Liu, Jung-Chun; Den, Walter; Chou, Ying-Chyi; Tsai, Jaw-Ji

    2014-02-01

    Indoor air quality monitoring in healthcare environment has become a critical part of hospital management and policy. Manual air sampling and analysis are cost-inhibitive and do not provide real-time air quality data and response measures. In this month-long study over 14 sampling locations in a public hospital in Taiwan, we observed a positive correlation between CO(2) concentration and population, total bacteria, and particulate matter concentrations, thus monitoring CO(2) concentration as a general indicator for air quality could be a viable option. Consequently, an intelligent environmental monitoring system consisting of a CO(2)/temperature/humidity sensor, a digital plug, and a ZigBee Router and Coordinator was developed and tested. The system also included a backend server that received and analyzed data, as well as activating ventilation and air purifiers when CO(2) concentration exceeded a pre-set value. Alert messages can also be delivered to offsite users through mobile devices.

  15. Modern techniques for condition monitoring of railway vehicle dynamics

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  16. Integrated system of structural health monitoring and intelligent management for a cable-stayed bridge.

    Science.gov (United States)

    Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

    2014-01-01

    It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

  17. Integrated System of Structural Health Monitoring and Intelligent Management for a Cable-Stayed Bridge

    Directory of Open Access Journals (Sweden)

    Bin Chen

    2014-01-01

    Full Text Available It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province. The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

  18. 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 ·   ...

  19. [Intelligent watch system for health monitoring based on Bluetooth low energy technology].

    Science.gov (United States)

    Wang, Ji; Guo, Hailiang; Ren, Xiaoli

    2017-08-01

    According to the development status of wearable technology and the demand of intelligent health monitoring, we studied the multi-function integrated smart watches solution and its key technology. First of all, the sensor technology with high integration density, Bluetooth low energy (BLE) and mobile communication technology were integrated and used in develop practice. Secondly, for the hardware design of the system in this paper, we chose the scheme with high integration density and cost-effective computer modules and chips. Thirdly, we used real-time operating system FreeRTOS to develop the friendly graphical interface interacting with touch screen. At last, the high-performance application software which connected with BLE hardware wirelessly and synchronized data was developed based on android system. The function of this system included real-time calendar clock, telephone message, address book management, step-counting, heart rate and sleep quality monitoring and so on. Experiments showed that the collecting data accuracy of various sensors, system data transmission capacity, the overall power consumption satisfy the production standard. Moreover, the system run stably with low power consumption, which could realize intelligent health monitoring effectively.

  20. MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring

    Science.gov (United States)

    Saeed, M.; Lieu, C.; Raber, G.; Mark, R. G.

    2002-01-01

    Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.

  1. Radiation Monitoring System in Advanced Spent Fuel Conditioning Process Facility

    Energy Technology Data Exchange (ETDEWEB)

    You, Gil Sung; Kook, D. H.; Choung, W. M.; Ku, J. H.; Cho, I. J.; You, G. S.; Kwon, K. C.; Lee, W. K.; Lee, E. P

    2006-09-15

    The Advanced spent fuel Conditioning Process is under development for effective management of spent fuel by converting UO{sub 2} into U-metal. For demonstration of this process, {alpha}-{gamma} type new hot cell was built in the IMEF basement . To secure against radiation hazard, this facility needs radiation monitoring system which will observe the entire operating area before the hot cell and service area at back of it. This system consists of 7 parts; Area Monitor for {gamma}-ray, Room Air Monitor for particulate and iodine in both area, Hot cell Monitor for hot cell inside high radiation and rear door interlock, Duct Monitor for particulate of outlet ventilation, Iodine Monitor for iodine of outlet duct, CCTV for watching workers and material movement, Server for management of whole monitoring system. After installation and test of this, radiation monitoring system will be expected to assist the successful ACP demonstration.

  2. Radiation Monitoring System in Advanced Spent Fuel Conditioning Process Facility

    International Nuclear Information System (INIS)

    You, Gil Sung; Kook, D. H.; Choung, W. M.; Ku, J. H.; Cho, I. J.; You, G. S.; Kwon, K. C.; Lee, W. K.; Lee, E. P.

    2006-09-01

    The Advanced spent fuel Conditioning Process is under development for effective management of spent fuel by converting UO 2 into U-metal. For demonstration of this process, α-γ type new hot cell was built in the IMEF basement . To secure against radiation hazard, this facility needs radiation monitoring system which will observe the entire operating area before the hot cell and service area at back of it. This system consists of 7 parts; Area Monitor for γ-ray, Room Air Monitor for particulate and iodine in both area, Hot cell Monitor for hot cell inside high radiation and rear door interlock, Duct Monitor for particulate of outlet ventilation, Iodine Monitor for iodine of outlet duct, CCTV for watching workers and material movement, Server for management of whole monitoring system. After installation and test of this, radiation monitoring system will be expected to assist the successful ACP demonstration

  3. Monitoring machining conditions by infrared images

    Science.gov (United States)

    Borelli, Joao E.; Gonzaga Trabasso, Luis; Gonzaga, Adilson; Coelho, Reginaldo T.

    2001-03-01

    During machining process the knowledge of the temperature is the most important factor in tool analysis. It allows to control main factors that influence tool use, life time and waste. The temperature in the contact area between the piece and the tool is resulting from the material removal in cutting operation and it is too difficult to be obtained because the tool and the work piece are in motion. One way to measure the temperature in this situation is detecting the infrared radiation. This work presents a new methodology for diagnosis and monitoring of machining processes with the use of infrared images. The infrared image provides a map in gray tones of the elements in the process: tool, work piece and chips. Each gray tone in the image corresponds to a certain temperature for each one of those materials and the relationship between the gray tones and the temperature is gotten by the previous of infrared camera calibration. The system developed in this work uses an infrared camera, a frame grabber board and a software composed of three modules. The first module makes the image acquisition and processing. The second module makes the feature image extraction and performs the feature vector. Finally, the third module uses fuzzy logic to evaluate the feature vector and supplies the tool state diagnostic as output.

  4. Cognitive Artificial Intelligence Method for Interpreting Transformer Condition Based on Maintenance Data

    Directory of Open Access Journals (Sweden)

    Karel Octavianus Bachri

    2017-07-01

    Full Text Available A3S(Arwin-Adang-Aciek-Sembiring is a method of information fusion at a single observation and OMA3S(Observation Multi-time A3S is a method of information fusion for time-series data. This paper proposes OMA3S-based Cognitive Artificial-Intelligence method for interpreting Transformer Condition, which is calculated based on maintenance data from Indonesia National Electric Company (PLN. First, the proposed method is tested using the previously published data, and then followed by implementation on maintenance data. Maintenance data are fused to obtain part condition, and part conditions are fused to obtain transformer condition. Result shows proposed method is valid for DGA fault identification with the average accuracy of 91.1%. The proposed method not only can interpret the major fault, it can also identify the minor fault occurring along with the major fault, allowing early warning feature. Result also shows part conditions can be interpreted using information fusion on maintenance data, and the transformer condition can be interpreted using information fusion on part conditions. The future works on this research is to gather more data, to elaborate more factors to be fused, and to design a cognitive processor that can be used to implement this concept of intelligent instrumentation.

  5. Intelligent low-level RF system by non-destructive beam monitoring device for cyclotrons

    Science.gov (United States)

    Sharifi Asadi Malafeh, M. S.; Ghergherehchi, M.; Afarideh, H.; Chai, J. S.; Yoon, Sang Kim

    2016-04-01

    The project of a 10 MeV PET cyclotron accelerator for medical diagnosis and treatment was started at Amirkabir University of Technology in 2012. The low-level RF system of the cyclotron accelerator is designed to stabilize acceleration voltage and control the resonance frequency of the cavity. In this work an Intelligent Low Level Radio Frequency Circuit or ILLRF, suitable for most AVF cyclotron accelerators, is designed using a beam monitoring device and narrow band tunable band-pass filter. In this design, the RF phase detection does not need signal processing by a microcontroller.

  6. Using the motor to monitor pump conditions

    Energy Technology Data Exchange (ETDEWEB)

    Casada, D. [Oak Ridge National Lab., TN (United States)

    1996-12-01

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

  7. Using the motor to monitor pump conditions

    International Nuclear Information System (INIS)

    Casada, D.

    1996-01-01

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

  8. Vibration-based condition monitoring industrial, aerospace and automotive applications

    CERN Document Server

    Randall, Robert Bond

    2010-01-01

    ""Without doubt the best modern and up-to-date text on the topic, wirtten by one of the world leading experts in the field. Should be on the desk of any practitioner or researcher involved in the field of Machine Condition Monitoring"" Simon Braun, Israel Institute of Technology Explaining complex ideas in an easy to understand way, Vibration-based Condition Monitoring provides a comprehensive survey of the application of vibration analysis to the condition monitoring of machines. Reflecting the natural progression of these systems by presenting the fundamental material

  9. Automated Intelligent Monitoring and the Controlling Software System for Solar Panels

    Science.gov (United States)

    Nalamwar, H. S.; Ivanov, M. A.; Baidali, S. A.

    2017-01-01

    The inspection of the solar panels on a periodic basis is important to improve longevity and ensure performance of the solar system. To get the most solar potential of the photovoltaic (PV) system is possible through an intelligent monitoring & controlling system. The monitoring & controlling system has rapidly increased its popularity because of its user-friendly graphical interface for data acquisition, monitoring, controlling and measurements. In order to monitor the performance of the system especially for renewable energy source application such as solar photovoltaic (PV), data-acquisition systems had been used to collect all the data regarding the installed system. In this paper the development of a smart automated monitoring & controlling system for the solar panel is described, the core idea is based on IoT (the Internet of Things). The measurements of data are made using sensors, block management data acquisition modules, and a software system. Then, all the real-time data collection of the electrical output parameters of the PV plant such as voltage, current and generated electricity is displayed and stored in the block management. The proposed system is smart enough to make suggestions if the panel is not working properly, to display errors, to remind about maintenance of the system through email or SMS, and to rotate panels according to a sun position using the Ephemeral table that stored in the system. The advantages of the system are the performance of the solar panel system which can be monitored and analyzed.

  10. Health monitoring and rehabilitation of a concrete structure using intelligent materials

    Science.gov (United States)

    Song, G.; Mo, Y. L.; Otero, K.; Gu, H.

    2006-04-01

    This paper presents the concept of an intelligent reinforced concrete structure (IRCS) and its application in structural health monitoring and rehabilitation. The IRCS has multiple functions which include self-rehabilitation, self-vibration damping, and self-structural health monitoring. These functions are enabled by two types of intelligent (smart) materials: shape memory alloys (SMAs) and piezoceramics. In this research, Nitinol type SMA and PZT (lead zirconate titanate) type piezoceramics are used. The proposed concrete structure is reinforced by martensite Nitinol cables using the method of post-tensioning. The martensite SMA significantly increases the concrete's damping property and its ability to handle large impact. In the presence of cracks due to explosions or earthquakes, by electrically heating the SMA cables, the SMA cables contract and close up the cracks. In this research, PZT patches are embedded in the concrete structure to detect possible cracks inside the concrete structure. The wavelet packet analysis method is then applied as a signal-processing tool to analyze the sensor signals. A damage index is defined to describe the damage severity for health monitoring purposes. In addition, by monitoring the electric resistance change of the SMA cables, the crack width can be estimated. To demonstrate this concept, a concrete beam specimen with reinforced SMA cables and with embedded PZT patches is fabricated. Experiments demonstrate that the IRC has the ability of self-sensing and self-rehabilitation. Three-point bending tests were conducted. During the loading process, a crack opens up to 0.47 inches. Upon removal of the load and heating the SMA cables, the crack closes up. The damage index formed by wavelet packet analysis of the PZT sensor data predicts and confirms the onset and severity of the crack during the loading. Also during the loading, the electrical resistance value of the SMA cable changes by up to 27% and this phenomenon is used to

  11. An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

    Science.gov (United States)

    Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

    2012-01-01

    This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

  12. An Intelligent Knowledge-Based and Customizable Home Care System Framework with Ubiquitous Patient Monitoring and Alerting Techniques

    Directory of Open Access Journals (Sweden)

    Yen-Lin Chen

    2012-08-01

    Full Text Available This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

  13. Condition monitoring a key component in the preventive maintenance

    International Nuclear Information System (INIS)

    Isar, C.

    2006-01-01

    The preventive maintenance programs are necessary to ensure that nuclear safety significant equipment will function when it is supposed to. Diesel generator, pumps, motor operated valves and air operated control valves are typically operated every three months. When you drive a car, you depend on lot of sounds, the feel of the steering wheel and gauges to determine if the car is running correctly. Similarly with operating equipment for a power plant - sounds or vibration of the equipment or the gauges and test equipment indicate a problem or degradation, actions are taken to correct the deficiency. Due to safety and economical reason diagnostic and monitoring systems are of growing interest in all complex industrial production. Diagnostic systems are requested to detect, diagnose and localize faulty operating conditions at an early stage in order to prevent severe failures and to enable predictive and condition oriented maintenance. In this context it is a need for using various on-line and off-line condition monitoring and diagnostics, non-destructive inspection techniques and surveillance. The condition monitoring technique used in nuclear power plant Cernavoda are presented in this paper. The selection of components and parameters to be monitored, monitoring and diagnostics techniques used are incorporated into a preventive maintenance program. Modern measurement technique in combination with advanced computerized data processing and acquisition show new ways in the field of machine surveillance. The diagnostic capabilities of predictive maintenance technologies have increased recently year with advances made in sensor technologies. The paper will focus on the following condition monitoring technique: - oil analysis - acoustic leakage monitoring - thermography - valve diagnostics: motor operated valve, air operated valve and check valve - motor current signature - vibration monitoring and rotating machine monitoring and diagnostics For each condition monitoring

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

    Science.gov (United States)

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

    2009-01-01

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

  15. Non-stationary condition monitoring through event alignment

    DEFF Research Database (Denmark)

    Pontoppidan, Niels Henrik; Larsen, Jan

    2004-01-01

    We present an event alignment framework which enables change detection in non-stationary signals. change detection. Classical condition monitoring frameworks have been restrained to laboratory settings with stationary operating conditions, which are not resembling real world operation....... In this paper we apply the technique for non-stationary condition monitoring of large diesel engines based on acoustical emission sensor signals. The performance of the event alignment is analyzed in an unsupervised probabilistic detection framework based on outlier detection with either Principal Component...... Analysis or Gaussian Processes modeling. We are especially interested in the true performance of the condition monitoring performance with mixed aligned and unaligned data, e.g. detection of fault condition of unaligned examples versus false alarms of aligned normal condition data. Further, we expect...

  16. Monitoring and operational support on nuclear power plants using an artificial intelligence system

    International Nuclear Information System (INIS)

    Bianchi, P.H.; Baptista Filho, B.D.

    2009-01-01

    The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

  17. Monitoring and operational support on nuclear power plants using an artificial intelligence system

    Energy Technology Data Exchange (ETDEWEB)

    Bianchi, Paulo H.; Baptista Filho, Benedito D., E-mail: phbianchi@gmail.co, E-mail: bdbfilho@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2009-07-01

    The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

  18. Design of a real-time tax-data monitoring intelligent card system

    Science.gov (United States)

    Gu, Yajun; Bi, Guotang; Chen, Liwei; Wang, Zhiyuan

    2009-07-01

    To solve the current problem of low efficiency of domestic Oil Station's information management, Oil Station's realtime tax data monitoring system has been developed to automatically access tax data of Oil pumping machines, realizing Oil-pumping machines' real-time automatic data collection, displaying and saving. The monitoring system uses the noncontact intelligent card or network to directly collect data which can not be artificially modified and so seals the loopholes and improves the tax collection's automatic level. It can perform real-time collection and management of the Oil Station information, and find the problem promptly, achieves the automatic management for the entire process covering Oil sales accounting and reporting. It can also perform remote query to the Oil Station's operation data. This system has broad application future and economic value.

  19. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

    1996-01-01

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NN ds ) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

  20. SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis

    Science.gov (United States)

    Lawson, Denise L.; James, Mark L.

    1989-01-01

    The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

  1. Transformer ageing modern condition monitoring techniques and their interpretations

    CERN Document Server

    Purkait, Prithwiraj

    2017-01-01

    This book is a one-stop guide to state-of-the-art research in transformer ageing, condition monitoring and diagnosis. It is backed by rigorous research projects supported by the Australian Research Council in collaboration with several transmission and distribution companies. Many of the diagnostic techniques and tools developed in these projects have been applied by electricity utilities and would appeal to both researchers and practicing engineers. Important topics covered in this book include transformer insulation materials and their ageing behaviour, transformer condition monitoring techniques and detailed diagnostic techniques and their interpretation schemes. It also features a monitoring framework for smart transformers as well as a chapter on biodegradable oil.

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

    Science.gov (United States)

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

    2014-12-01

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

  3. Beam conditions monitors at CMS and LHC using diamond sensors

    Energy Technology Data Exchange (ETDEWEB)

    Hempel, Maria; Lohmann, Wolfgang [Desy-Zeuthen, Platanenallee 6, 15738 Zeuthen (Germany); Brandenburgische Technische Universitaet Cottbus, Konrad-Wachsmann-Allee 1, 03046 Cottbus (Germany); Castro-Carballo, Maria-Elena; Lange, Wolfgang; Novgorodova, Olga [Desy-Zeuthen, Platanenallee 6, 15738 Zeuthen (Germany); Walsh, Roberval [Desy-Hamburg, Notkestrasse 85, 22607 Hamburg (Germany)

    2012-07-01

    The Fast Beam Conditions Monitor (BCM1F) is a particle detector based on diamonds. Eight modules comprising a single crystal diamond, front-end electronics and an optical link are installed on both sides of the interaction point inside the tracker of the CMS detector. The back-end uses ADCs, TDCs and scalers to measure the amplitudes, arrival time and rates of beam-halo particles and collision products. These data are used to protect the inner tracker from adverse beam conditions, perform a fast monitoring of the luminosity and e.g. beam-gas interactions. Recently two additional BCM1F modules have been installed at other positions of the LHC to supplement the beam-loss monitors by a flux measurement with nanosecond time resolution. In the talk essential parameters of the system are presented and examples of beam conditions monitoring are reported.

  4. Intelligent Monitoring System with High Temperature Distributed Fiberoptic Sensor for Power Plant Combustion Processes

    Energy Technology Data Exchange (ETDEWEB)

    Kwang Y. Lee; Stuart S. Yin; Andre Boehman

    2006-09-26

    The objective of the proposed work is to develop an intelligent distributed fiber optical sensor system for real-time monitoring of high temperature in a boiler furnace in power plants. Of particular interest is the estimation of spatial and temporal distributions of high temperatures within a boiler furnace, which will be essential in assessing and controlling the mechanisms that form and remove pollutants at the source, such as NOx. The basic approach in developing the proposed sensor system is three fold: (1) development of high temperature distributed fiber optical sensor capable of measuring temperatures greater than 2000 C degree with spatial resolution of less than 1 cm; (2) development of distributed parameter system (DPS) models to map the three-dimensional (3D) temperature distribution for the furnace; and (3) development of an intelligent monitoring system for real-time monitoring of the 3D boiler temperature distribution. Under Task 1, we have set up a dedicated high power, ultrafast laser system for fabricating in-fiber gratings in harsh environment optical fibers, successfully fabricated gratings in single crystal sapphire fibers by the high power laser system, and developed highly sensitive long period gratings (lpg) by electric arc. Under Task 2, relevant mathematical modeling studies of NOx formation in practical combustors have been completed. Studies show that in boiler systems with no swirl, the distributed temperature sensor may provide information sufficient to predict trends of NOx at the boiler exit. Under Task 3, we have investigated a mathematical approach to extrapolation of the temperature distribution within a power plant boiler facility, using a combination of a modified neural network architecture and semigroup theory. Given a set of empirical data with no analytic expression, we first developed an analytic description and then extended that model along a single axis.

  5. Research on intelligent monitor for 3D power distribution of reactor core

    International Nuclear Information System (INIS)

    Xia, Hong; Li, Bin; Liu, Jianxin

    2014-01-01

    Highlights: • Core power distribution of ex-core measurement system has been reconstructed. • Building up an artificial intelligence model for 3-D core power distribution. • Error of the experiments has been reduced to 0.76%. • Methods for improving the accuracy of the model have been obtained. - Abstract: A real-time monitor for 3D reactor power distribution is critical for nuclear safety and high efficiency of NPP’s operation as well as for optimizing the control system, especially when the nuclear power plant (NPP) works at a certain power level or it works in load following operation. This paper was based on analyzing the monitor for 3D reactor power distribution technologies used in modern NPPs. Furthermore, considering the latest research outcomes, the paper proposed a method based on using an ex-core neutron detector system and a neural network to set up a real time monitor system for reactor’s 3D power distribution supervision. The results of the experiments performed on a reactor simulation machine illustrated that the new monitor system worked very well for a certain burn-up range during the fuel cycle. In addition, this new model could reduce the errors associated with the fitting of the distribution effectively, and several optimization methods were also obtained to improve the accuracy of the simulation model

  6. Development of an Intelligent Monitoring System for Geological Carbon Sequestration (GCS) Systems

    Science.gov (United States)

    Sun, A. Y.; Jeong, H.; Xu, W.; Hovorka, S. D.; Zhu, T.; Templeton, T.; Arctur, D. K.

    2016-12-01

    To provide stakeholders timely evidence that GCS repositories are operating safely and efficiently requires integrated monitoring to assess the performance of the storage reservoir as the CO2 plume moves within it. As a result, GCS projects can be data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, and accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. How to correlate anomaly detected by a certain sensor to events observed by other devices to verify leakage incidents? How to optimally allocate resources for task-oriented monitoring if reservoir integrity is in question? These are issues that warrant further investigation before real integration can take place. In this work, we are building a web-based, data integration, assimilation, and learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS will be an intelligent monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in high-throughput database, complex event processing, data assimilation, and machine learning technologies. Results will be demonstrated using realistic data and model derived from a GCS site.

  7. Pump failure leads to alternative vertical pump condition monitoring technique

    International Nuclear Information System (INIS)

    DeVilliers, Adriaan; Glandon, Kevin

    2011-01-01

    Condition monitoring and detecting early signs of potential failure mechanisms present particular problems in vertical pumps. Most often, the majority of the pump assembly is not readily accessible for visual or audible inspection or conventional vibration monitoring techniques using accelerometers and/or proximity sensors. The root cause failure analysis of a 2-stage vertical centrifugal service-water pump at a nuclear power generating facility in the USA is presented, highlighting this long standing challenge in condition monitoring of vertical pumps. This paper will summarize the major findings of the root cause analysis (RCA), highlight the limitations of traditional monitoring techniques, and present an expanded application of motor current monitoring as a means to gain insight into the mechanical performance and condition of a pump. The 'real-world' example of failure, monitoring and correlation of the monitoring technique to a detailed pump disassembly inspection is also presented. This paper will explain some of the reasons behind well known design principles requiring natural frequency separation from known forcing frequencies, as well as explore an unexpected submerged brittle fracture failure mechanism, and how such issues may be avoided. (author)

  8. Muscular condition monitoring system using fiber bragg grating sensors

    International Nuclear Information System (INIS)

    Kim, Heon Young; Lee, Jin Hyuk; Kim, Dae Hyun

    2014-01-01

    Fiber optic sensors (FOS) have advantages such as electromagnetic interference (EMI) immunity, corrosion resistance and multiplexing capability. For these reasons, they are widely used in various condition monitoring systems (CMS). This study investigated a muscular condition monitoring system using fiber optic sensors (FOS). Generally, sensors for monitoring the condition of the human body are based on electro-magnetic devices. However, such an electrical system has several weaknesses, including the potential for electro-magnetic interference and distortion. Fiber Bragg grating (FBG) sensors overcome these weaknesses, along with simplifying the devices and increasing user convenience. To measure the level of muscle contraction and relaxation, which indicates the muscle condition, a belt-shaped FBG sensor module that makes it possible to monitor the movement of muscles in the radial and circumferential directions was fabricated in this study. In addition, a uniaxial tensile test was carried out in order to evaluate the applicability of this FBG sensor module. Based on the experimental results, a relationship was observed between the tensile stress and Bragg wavelength of the FBG sensors, which revealed the possibility of fabricating a muscular condition monitoring system based on FBG sensors.

  9. Muscular condition monitoring system using fiber bragg grating sensors

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Heon Young; Lee, Jin Hyuk; Kim, Dae Hyun [Seoul National University of Technology, Seoul (Korea, Republic of)

    2014-10-15

    Fiber optic sensors (FOS) have advantages such as electromagnetic interference (EMI) immunity, corrosion resistance and multiplexing capability. For these reasons, they are widely used in various condition monitoring systems (CMS). This study investigated a muscular condition monitoring system using fiber optic sensors (FOS). Generally, sensors for monitoring the condition of the human body are based on electro-magnetic devices. However, such an electrical system has several weaknesses, including the potential for electro-magnetic interference and distortion. Fiber Bragg grating (FBG) sensors overcome these weaknesses, along with simplifying the devices and increasing user convenience. To measure the level of muscle contraction and relaxation, which indicates the muscle condition, a belt-shaped FBG sensor module that makes it possible to monitor the movement of muscles in the radial and circumferential directions was fabricated in this study. In addition, a uniaxial tensile test was carried out in order to evaluate the applicability of this FBG sensor module. Based on the experimental results, a relationship was observed between the tensile stress and Bragg wavelength of the FBG sensors, which revealed the possibility of fabricating a muscular condition monitoring system based on FBG sensors.

  10. Integrated reliability condition monitoring and maintenance of equipment

    CERN Document Server

    Osarenren, John

    2015-01-01

    Consider a Viable and Cost-Effective Platform for the Industries of the Future (IOF) Benefit from improved safety, performance, and product deliveries to your customers. Achieve a higher rate of equipment availability, performance, product quality, and reliability. Integrated Reliability: Condition Monitoring and Maintenance of Equipment incorporates reliable engineering and mathematical modeling to help you move toward sustainable development in reliability condition monitoring and maintenance. This text introduces a cost-effective integrated reliability growth monitor, integrated reliability degradation monitor, technological inheritance coefficient sensors, and a maintenance tool that supplies real-time information for predicting and preventing potential failures of manufacturing processes and equipment. The author highlights five key elements that are essential to any improvement program: improving overall equipment and part effectiveness, quality, and reliability; improving process performance with maint...

  11. Condition Monitoring Of Operating Pipelines With Operational Modal Analysis Application

    OpenAIRE

    Mironov Aleksey; Doronkin Pavel; Priklonsky Aleksander; Kabashkin Igor

    2015-01-01

    In the petroleum, natural gas and petrochemical industries, great attention is being paid to safety, reliability and maintainability of equipment. There are a number of technologies to monitor, control, and maintain gas, oil, water, and sewer pipelines. The paper focuses on operational modal analysis (OMA) application for condition monitoring of operating pipelines. Special focus is on the topicality of OMA for definition of the dynamic features of the pipeline (frequencies and mode shapes) i...

  12. Wireless pilot monitoring system for extreme race conditions.

    Science.gov (United States)

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

    2012-01-01

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

  13. Condition Monitoring Of Operating Pipelines With Operational Modal Analysis Application

    Directory of Open Access Journals (Sweden)

    Mironov Aleksey

    2015-12-01

    Full Text Available In the petroleum, natural gas and petrochemical industries, great attention is being paid to safety, reliability and maintainability of equipment. There are a number of technologies to monitor, control, and maintain gas, oil, water, and sewer pipelines. The paper focuses on operational modal analysis (OMA application for condition monitoring of operating pipelines. Special focus is on the topicality of OMA for definition of the dynamic features of the pipeline (frequencies and mode shapes in operation. The research was conducted using two operating laboratory models imitated a part of the operating pipeline. The results of finite-element modeling, identification of pipe natural modes and its modification under the influence of virtual failure are discussed. The work considers the results of experimental research of dynamic behavior of the operating pipe models using one of OMA techniques and comparing dynamic properties with the modeled data. The study results demonstrate sensitivity of modal shape parameters to modification of operating pipeline technical state. Two strategies of pipeline repair – with continuously condition-based monitoring with proposed technology and without such monitoring, was discussed. Markov chain reliability models for each strategy were analyzed and reliability improvement factor for proposed technology of monitoring in compare with traditional one was evaluated. It is resumed about ability of operating pipeline condition monitoring by measuring dynamic deformations of the operating pipe and OMA techniques application for dynamic properties extraction.

  14. Guiding rules for development of intelligent monitoring system of nuclear power plants

    International Nuclear Information System (INIS)

    Kitamura, M.; Furukawa, H.; Kozma, R.; Washio, T.

    1996-01-01

    General frameworks and major component techniques for intelligent monitoring of nuclear power plants are presented. The key concept, diversity-based design, is to provide advisory information through consensus of multiple agents, each performing operational decision-making by focusing on mutually different information obtained from the plant. The multi-agent design scheme allows to attain high credibility and tolerance against sensor failure in fault detection and causal reasoning. The advantage of the proposed scheme realized by multiple neural networks was clearly demonstrated through numerical experiments with anomalies in a pressurized water reactor. Relevant techniques are also introduced for diagnostic information evaluation in specified symptoms, and for remedial procedure synthesis. A new architecture for future implementation of the proposed scheme, worm-type multi-agent system, is also proposed as a promising candidate. (author)

  15. Artificial intelligence system for the monitoring of natural gas production systems; Intelligente Ueberwachung von Erdgasfoerderanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Tschaetsch, H.U.

    2001-02-01

    The article explains a novel, artificial intelligence-based system called HISS (Human Interface Supervision System) which has been installed as a prototype for the monitoring of a natural gas production site at Thoense near Hannover/Germany. The system is capable to perform audio-visual and smelling functions, analogous to the human sensory perception. (orig./CB) [German] Die Aufrechterhaltung eines einwandfreien Betriebszustandes von technischen Anlagen durch staendige Kontrollen und regelmaessige Wartungsarbeiten ist haeufig eine aufwendige und kostspielige Angelegenheit. Gleichwohl ist sie - sowohl was die Frage der Sicherheit als auch des Umweltschutzes anbelangt - unentbehrlich. Die Erdgasfoerderanlage Thoense bei Hannover wird von einem intelligenten Ueberwachungssystem, HISS - Human Interface Supervision System, kontrolliert, das die menschlichen Eigenschaften sehen, hoeren und riechen beherrscht. (orig.)

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  17. Workshop on power plant cable condition monitoring: Proceedings

    International Nuclear Information System (INIS)

    Del Valle, L.

    1988-07-01

    A three-day workshop on cable condition monitoring was held in San Francisco on Fegruary 16--18, 1988. The workshop was cosponsored by the Nuclear Power, Electrical Systems, and Coal Combustion Systems Divisions of the Electric Power Research Institute. The primary objective of the workshop was to identify the state-of-the-art for cable condition monitoring. Twenty-five technical papers as well as EPRI research programs were presented at the technical sessions. Four working group sessions and one general session were held on each of two days. Each group session provided a forum for participants to exchange ideas and to discuss in more depth research for cable condition monitoring, existing and innovative testing technology, and utility and NRC needs for testing. Recommendations from the working groups were summarized and presented at the end of the workshop

  18. Wind Turbine Gearbox Oil Filtration and Condition Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Sheng, Shuangwen

    2015-10-25

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

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

    Science.gov (United States)

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

    1999-03-01

    place the condition monitoring program in perspective); (11) Use of procedures for Predictive, Condition Monitoring and maintenance in general (To get consistent results); (12) Developing a scheme for predictive, condition monitoring personnel qualification and certification (To provide a career path and incentive to advance skill level and value to the company); (13) Analyst Assignment to Technologies and Related Duties (To make intelligent use of the skills of individuals assigned); (14) Condition Monitoring Analyst Selection Criteria (Key attributes for success are mentioned.); (15) Design and Modification to Support Monitoring (For old and new machinery to facilitate data acquisition); (16) Establishment of a Museum of Components and Samples Pulled from Service for Cause (For orientation and awareness training of operators and managers and exchange of information between analysts); (17) Goals (To promote a proactive program approach for machinery condition improvement).

  20. 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

  1. Towards artificial intelligence based diesel engine performance control under varying operating conditions using support vector regression

    Directory of Open Access Journals (Sweden)

    Naradasu Kumar Ravi

    2013-01-01

    Full Text Available Diesel engine designers are constantly on the look-out for performance enhancement through efficient control of operating parameters. In this paper, the concept of an intelligent engine control system is proposed that seeks to ensure optimized performance under varying operating conditions. The concept is based on arriving at the optimum engine operating parameters to ensure the desired output in terms of efficiency. In addition, a Support Vector Machines based prediction model has been developed to predict the engine performance under varying operating conditions. Experiments were carried out at varying loads, compression ratios and amounts of exhaust gas recirculation using a variable compression ratio diesel engine for data acquisition. It was observed that the SVM model was able to predict the engine performance accurately.

  2. Monitoring and analysis of an absorption air-conditioning system

    Energy Technology Data Exchange (ETDEWEB)

    Perez de Vinaspre, M.; Bourouis, M.; Coronas, A. [Centro de Innovacion Tecnologica en Revalorizacion Energetica y Refrigeracion, Tarragona (Spain); Garcia, A.; Soto, V.; Pinazo, J.M. [E.T.S. Ingenieros Industriales, Valencia (Spain)

    2004-09-01

    In the last few years, high-energy consumption due to air-conditioning has led to a growing interest in the efficient use of energy in buildings. Although simulation programs have always been the main tools for analyzing energy in buildings, the reliability of their results is often compromised by a lack of certainty to reflect real conditions. The aim of this work is to monitorize and analyze the thermal behavior of an absorption-based air-conditioning installation of a university building in Tarragona, Spain. The existing monitoring system of the installation has been improved by implementing additional sensors and flow meters. The data has been stored during summer 2002 and used to assess the energy balance of the air-conditioning installation and the operational regime of the absorption chiller. [Author].

  3. Nonlinear Cointegration Approach for Condition Monitoring of Wind Turbines

    Directory of Open Access Journals (Sweden)

    Konrad Zolna

    2015-01-01

    Full Text Available Monitoring of trends and removal of undesired trends from operational/process parameters in wind turbines is important for their condition monitoring. This paper presents the homoscedastic nonlinear cointegration for the solution to this problem. The cointegration approach used leads to stable variances in cointegration residuals. The adapted Breusch-Pagan test procedure is developed to test for the presence of heteroscedasticity in cointegration residuals obtained from the nonlinear cointegration analysis. Examples using three different time series data sets—that is, one with a nonlinear quadratic deterministic trend, another with a nonlinear exponential deterministic trend, and experimental data from a wind turbine drivetrain—are used to illustrate the method and demonstrate possible practical applications. The results show that the proposed approach can be used for effective removal of nonlinear trends form various types of data, allowing for possible condition monitoring applications.

  4. Three State-of-the-Art Methods for Condition Monitoring

    NARCIS (Netherlands)

    Grimmelius, H.T.; Meiler, P.P.; Maas, H.L.M.M.; Bonnier, B.; Grevink, J.S.; Kuilenburg, R.F. van

    1999-01-01

    This paper describes and compares three different state-of-the-art condition monitoring techniques: first principles, feature extraction, and neural networks. The focus of the paper is on the application of the techniques, not on the underlying theory. Each technique is described briefly and is

  5. Groundwater detection monitoring system design under conditions of uncertainty

    NARCIS (Netherlands)

    Yenigül, N.B.

    2006-01-01

    Landfills represent a wide-spread and significant threat to groundwater quality. In this thesis a methodology was developed for the design of optimal groundwater moni-toring system design at landfill sites under conditions of uncertainty. First a decision analysis approach was presented for optimal

  6. The Effect of Multicultural Experience in Conflicts Management Styles: Mediation of Cultural Intelligence and Self-Monitoring

    Directory of Open Access Journals (Sweden)

    Gabriela Gonçalves

    2015-03-01

    Full Text Available Conflict is an inevitable reality both in personal and in organizational life. For being inevitable, the conflict must be managed Defined as a process that occurs when one party feels adversely affected by another (e.g., De Dreu, 1997 the conflict management styles can be analysed as a function of personality variables. In this respect the cultural intelligence, self-monitoring and self-interdependent seem to be relevant variables, since characterised by flexibility and interest in other aspects present in conflict management styles. In this study, we propose that cultural intelligence, associated with the self-interdependent and self-monitoring, can have a positive impact on the choice of most effective interpersonal conflict resolution styles. Being cultural intelligence an attribute of extreme importance, we still sought to determine how the quantity and quality of intercultural contact and self-interdependent present themselves as predictors of it. With a sample of 399 individuals, the proposed model suggests that high levels of cultural intelligence mediated by a high self-monitoring and selfinterdependent positively affect and predict the conflict resolution styles adopted. Given the need to develop abilities aimed at increasing the skills of conflict resolution, this study adds to the existing literature new predictors, contributing to the welfare and performance of human resources, and consequently to success and organizational effectiveness.

  7. A digital filter-based approach to the remote condition monitoring of railway turnouts

    International Nuclear Information System (INIS)

    Garcia Marquez, Fausto Pedro; Schmid, Felix

    2007-01-01

    Railway operations in Europe have changed dramatically since the early 1990s, partly as a result of new European Union Directives. Performance targets have become more and more exacting, due to reductions in state support for railways and the need to increasing traffic. More intensive operations also place greater demands on the hardware of the railway. This is true for both rolling stock and infrastructure subsystems and components, particularly so in the case of the latter where the time available for maintenance is being reduced. The authors of this paper focus on the railway infrastructure, and more specifically on points. These are critical elements whose reliability is key to the operation of the whole system. Using intelligent monitoring systems, it is possible to predict problems and enable quick recovery before component failures disrupt operations. The authors have studied the application of remote condition monitoring to point mechanisms and their operation, and have identified algorithms which may be used to identify incipient failures. In this paper, the authors propose a Kalman filter for the linear discrete data filtering problem encountered when using current sensor data in a point condition monitoring system. The reason for applying Kalman filtering in this study was to increase the reliability of the model presented to the rule-based decision mechanism

  8. Development of intelligent monitoring purifier for indoor PM 2.5

    Science.gov (United States)

    Lou, Guanting; Zhu, Rong; Guo, Jiangwei; Wei, Yongqing

    2018-03-01

    The particulate matter 2.5 (PM2.5) refers to tiny particles or droplets in the air that are two and one half microns or less in width. PM2.5 is an air pollutant that is a concern for people’s health when levels in air are high. The intelligent monitoring purifier was developed to detect indoor PM2.5 concentration before and after purification and the monitoring data could be displayed on the LCD screen, displaying different color patterns according to the concentrations. Through the Bluetooth transport module, real-time values could also display on the mobile phone and voice broadcast PM2.5 concentration level in the air. When PM2.5 concentration is higher than the setting threshold, the convection fan rotation and the speed can be remote controlled with mobile phone through the Bluetooth transport. Therefore, the efficiency and scope of the purification could be enhanced and further better air quality could be achieved.

  9. Towards an Intelligent Monitoring System for Patients with Obstrusive Sleep Apnea

    Directory of Open Access Journals (Sweden)

    Xavier Rafael-Palou

    2017-12-01

    Full Text Available Due to the growing incidence of chronic diseases and aging populations, the pressure to control costs and the expectations of continuous improvements in the quality of service have increased the need to understand how healthcare is provided and to determine whether cost-effective improvements to care practices can be made. In the case of people suffering Obstructive Sleep Apnea, patients using self-administer nasal Continuous Positive Airway Pressure (CPAP may receive information on the treatment only once they go to a visit with the lung specialist. In this paper, we propose an IoT-based Intelligent Monitoring System that relies on machine learning to achieve a threefold goal: (1 it is aimed at early detecting compliance in order to predict CPAP usage; (2 it monitors the actual adherence degree to the treatment to keep informed both the patient and the lung specialists; and (3 it sends recommendations to the patient to empower her/him and to better follow up.

  10. Condition monitoring and maintenance of nuclear power plant concrete structures

    International Nuclear Information System (INIS)

    Orr, R.; Prasad, N.

    1988-01-01

    Nuclear power plant concrete structures are potentially subject to deterioration due to several environmental conditions, including weather exposure, ground water exposure, and sustained high temperature and radiation levels. The nuclear power plant are generally licensed for a term of 40 years. In order to maximize the return from the existing plants, feasibility studies are in progress for continued operation of many of these plants beyond the original licensed life span. This paper describes a study that was performed with an objective to define appropriate condition monitoring and maintenance procedures. A timely implementation of a condition monitoring and maintenance program would provide a valuable database and would provide justification for extension of the plant's design life. The study included concrete structures such as the containment buildings, interior structures, basemats, intake structures and cooling towers. Age-related deterioration at several operating power plants was surveyed and the potential degradation mechanisms have been identified

  11. Integrated online condition monitoring system for nuclear power plants

    International Nuclear Information System (INIS)

    Hashemian, Hashem M.

    2010-01-01

    Online condition monitoring or online monitoring (OLM) uses data acquired while a nuclear power is operating to continuously assess the health of the plant's sensors, processes, and equipment; to measure the dynamic performance of the plant's process instrumentation; to verify in-situ the calibration of the process instrumentation; to detect blockages, voids, and leaks in the pressure sensing lines; to identify core flow anomalies; to extend the life of neutron detectors and other sensors; and to measure the vibration of reactor internals. Both the steady-state or DC output of plant sensors and their AC signal or noise output can be used to assess sensor health, depending on whether the application is monitoring a rapidly changing (e.g., core barrel motion) or a slowly changing (e.g., sensor calibration) process. The author has designed, developed, installed, and tested OLM systems (comprised of software/hardware-based data acquisition and data processing modules) that integrate low-frequency (1 mHz to 1 Hz) techniques such as RTD cross-calibration, pressure transmitter calibration monitoring, and equipment condition monitoring and high-frequency (1 Hz to 1 kHz) techniques such as the noise analysis technique. The author has demonstrated the noise analysis technique's effectiveness for measuring the dynamic response-time of pressure transmitters and their sensing lines; for performing predictive maintenance on reactor internals; for detecting core flow anomalies; and for extending neutron detector life. Integrated online condition monitoring systems can combine AC and DC data acquisition and signal processing techniques, can use data from existing process sensors during all modes of plant operation, including startup, normal operation, and shutdown; can be retrofitted into existing PWRs, BWRs, and other reactor types and will be integrated into next-generation plants. (orig.)

  12. Integrated online condition monitoring system for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Hashemian, Hashem M. [Analysis and Measurement Services Corporation, Knoxville, TN (United States). AMS Technology Center

    2010-09-15

    Online condition monitoring or online monitoring (OLM) uses data acquired while a nuclear power is operating to continuously assess the health of the plant's sensors, processes, and equipment; to measure the dynamic performance of the plant's process instrumentation; to verify in-situ the calibration of the process instrumentation; to detect blockages, voids, and leaks in the pressure sensing lines; to identify core flow anomalies; to extend the life of neutron detectors and other sensors; and to measure the vibration of reactor internals. Both the steady-state or DC output of plant sensors and their AC signal or noise output can be used to assess sensor health, depending on whether the application is monitoring a rapidly changing (e.g., core barrel motion) or a slowly changing (e.g., sensor calibration) process. The author has designed, developed, installed, and tested OLM systems (comprised of software/hardware-based data acquisition and data processing modules) that integrate low-frequency (1 mHz to 1 Hz) techniques such as RTD cross-calibration, pressure transmitter calibration monitoring, and equipment condition monitoring and high-frequency (1 Hz to 1 kHz) techniques such as the noise analysis technique. The author has demonstrated the noise analysis technique's effectiveness for measuring the dynamic response-time of pressure transmitters and their sensing lines; for performing predictive maintenance on reactor internals; for detecting core flow anomalies; and for extending neutron detector life. Integrated online condition monitoring systems can combine AC and DC data acquisition and signal processing techniques, can use data from existing process sensors during all modes of plant operation, including startup, normal operation, and shutdown; can be retrofitted into existing PWRs, BWRs, and other reactor types and will be integrated into next-generation plants. (orig.)

  13. Predicting speech intelligibility in adverse conditions: evaluation of the speech-based envelope power spectrum model

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    conditions by comparing predictions to measured data from [Kjems et al. (2009). J. Acoust. Soc. Am. 126 (3), 1415-1426] where speech is mixed with four different interferers, including speech-shaped noise, bottle noise, car noise, and cafe noise. The model accounts well for the differences in intelligibility......The speech-based envelope power spectrum model (sEPSM) [Jørgensen and Dau (2011). J. Acoust. Soc. Am., 130 (3), 1475–1487] estimates the envelope signal-to-noise ratio (SNRenv) of distorted speech and accurately describes the speech recognition thresholds (SRT) for normal-hearing listeners...... observed for the different interferers. None of the standardized models successfully describe these data....

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

    International Nuclear Information System (INIS)

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

    2001-01-01

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

  15. A design condition for incorporating human judgement into monitoring systems

    International Nuclear Information System (INIS)

    Tanaka, K.; Klir, G.J.

    1999-01-01

    In safety monitoring, there exists an uncertainty situation in which the sensor cannot detect whether or not the monitored object is in danger. For the uncertainty zone identified by a non-homogeneous safety monitoring system that utilizes two types of sensors with different thresholds, operators or experts are expected to judge whether the real state is safe or dangerous on the basis of additional information from a detailed inspection or other related sensors output. However, the activities for inspection performed by relevant humans may require additional cost and introduce inspection errors. The present article proposes two types of an automatic monitoring system not involving any human inspection or a human-machine (H-M) cooperative monitoring system with inspection. In order to compare the systems, an approach based on the Dempster-Shafer theory is proposed as uncertainty analysis by this theory (it is simpler than by the traditional Bayesian approach). By comparing their expected losses as a result of failed dangerous failures or failed safe failures as well as the inspection errors, the condition is determined under which H-M cooperative systems incorporating human judgements are more effective than automatic monitoring systems

  16. Fast beam condition monitor for CMS. Performance and upgrade

    International Nuclear Information System (INIS)

    Leonard, Jessica L.; Bell, Alan; Burtowy, Piotr

    2014-05-01

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

  17. Fast Beam Condition Monitor for CMS: performance and upgrade

    CERN Document Server

    INSPIRE-00009152; Bell, Alan; Burtowy, Piotr; Dabrowski, Anne; Hempel, Maria; Henschel, Hans; Lange, Wolfgang; Lohmann, Wolfgang; Odell, Nathaniel; Penno, Marek; Pollack, Brian; Przyborowski, Dominik; Ryjov, Vladimir; Stickland, David; Walsh, Roberval; Warzycha, Weronika; Zagozdzinska, Agnieszka

    2014-11-21

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

  18. Intelligent MONitoring System for antiviral pharmacotherapy in patients with chronic hepatitis C (SiMON-VC

    Directory of Open Access Journals (Sweden)

    Luis Margusino-Framiñán

    2017-01-01

    Full Text Available Two out of six strategic axes of pharmaceutical care in our hospital are quality and safety of care, and the incorporation of information technologies. Based on this, an information system was developed in the outpatient setting for pharmaceutical care of patients with chronic hepatitis C, SiMON-VC, which would improve the quality and safety of their pharmacotherapy. The objective of this paper is to describe requirements, structure and features of Si- MON-VC. Requirements demanded were that the information system would enter automatically all critical data from electronic clinical records at each of the visits to the Outpatient Pharmacy Unit, allowing the generation of events and alerts, documenting the pharmaceutical care provided, and allowing the use of data for research purposes. In order to meet these requirements, 5 sections were structured for each patient in SiMON-VC: Main Record, Events, Notes, Monitoring Graphs and Tables, and Follow-up. Each section presents a number of tabs with those coded data needed to monitor patients in the outpatient unit. The system automatically generates alerts for assisted prescription validation, efficacy and safety of using antivirals for the treatment of this disease. It features a completely versatile Indicator Control Panel, where temporary monitoring standards and alerts can be set. It allows the generation of reports, and their export to the electronic clinical record. It also allows data to be exported to the usual operating systems, through Big Data and Business Intelligence. Summing up, we can state that SiMON-VC improves the quality of pharmaceutical care provided in the outpatient pharmacy unit to patients with chronic hepatitis C, increasing the safety of antiviral therapy.

  19. The Use of Hidden Markov Models for Anomaly Detection in Nuclear Core Condition Monitoring

    Science.gov (United States)

    Stephen, Bruce; West, Graeme M.; Galloway, Stuart; McArthur, Stephen D. J.; McDonald, James R.; Towle, Dave

    2009-04-01

    Unplanned outages can be especially costly for generation companies operating nuclear facilities. Early detection of deviations from expected performance through condition monitoring can allow a more proactive and managed approach to dealing with ageing plant. This paper proposes an anomaly detection framework incorporating the use of the Hidden Markov Model (HMM) to support the analysis of nuclear reactor core condition monitoring data. Fuel Grab Load Trace (FGLT) data gathered within the UK during routine refueling operations has been seen to provide information relating to the condition of the graphite bricks that comprise the core. Although manual analysis of this data is time consuming and requires considerable expertise, this paper demonstrates how techniques such as the HMM can provide analysis support by providing a benchmark model of expected behavior against which future refueling events may be compared. The presence of anomalous behavior in candidate traces is inferred through the underlying statistical foundation of the HMM which gives an observation likelihood averaged along the length of the input sequence. Using this likelihood measure, the engineer can be alerted to anomalous behaviour, indicating data which might require further detailed examination. It is proposed that this data analysis technique is used in conjunction with other intelligent analysis techniques currently employed to analyse FGLT to provide a greater confidence measure in detecting anomalous behaviour from FGLT data.

  20. Development of an integrated condition monitoring system for meeting license renewal criteria

    International Nuclear Information System (INIS)

    Jarrell, D.B.; Stratton, R.C.

    1991-01-01

    A project for developing a methodology that facilitates an artificial intelligence (AI) approach to the integration of component condition monitoring, fault diagnostics, and component failure root cause analysis is in progress at PNL. Using model-based reasoning with an object oriented schematic representation, these combined elements provide a real-time interactive means to systematically investigate, understand and auto-document the mitigation of age-related component degradation. A common Data Acquisition System contains component parameter and machinery history data as well as a knowledge of the plant system configuration. The unique aspect of this system is that it integrates this component parametric, diagnostic, and failure history knowledge to determine a more complete computerized specification of the component condition than was previously possible. This condition specification is then compared to degradation process models for behavioral similitude, thereby identifying the active degradation mechanism. Based on the monitored trends and the degradation model, an accurate estimate of projected equipment service life can then be projected. (author)

  1. Condition monitoring through advanced sensor and computational technology

    International Nuclear Information System (INIS)

    Kim, Jung Taek; Hur, S.; Seong, S. H.; Hwang, Il Soon; Lee, Joon Hyun; You, Jun; Lee, Sang Jung

    2004-01-01

    In order to successfully implement the extended-life operation plan of the nuclear power plant (NPP), predictive maintenance based on on-line monitoring of deteriorated components becomes highly important. In this work, we present progresses in the development of an advanced monitoring system to detect the health condition on check valve failures and pipe wall-thinning phenomena. The failures of check valves have resulted in significant maintenance efforts, on occasion, have resulted in water hammer, over-pressurization of low-pressure systems, and damage to flow system components. Pipe wall-thinning is usually caused by Flow-Accelerated Corrosion (FAC) under the undesirable combination of water chemistry, flow velocity and material composition. A piping elbow in the moisture separator/reheater drain line on the secondary waterside of a PWR is chosen as a monitoring target

  2. Artificial intelligence applications in fixed area monitor for TRIGA reactor building and service building

    International Nuclear Information System (INIS)

    Talpalariu, C.; Talpalariu, J.; Vaja, N.; Matei, C.

    2008-01-01

    This system is intended for the protection of personnel working in those areas of the Reactor Building and Service Building where high gamma radiation fields are expected. A detector, sensitive to gamma radiation, is installed in each of the areas to be monitored. The detector will send a signal, proportional to the radiation level in the area, to a corresponding electronic module (Alarm Unit), where the signal will be amplified and checked against alarm set points for possible alarming conditions. In case the field exceeds the alarm set values, the Alarm Unit will produce a signal that will trigger the field alarms (Horn and Beacon) located in the area where the condition occurred. Each Alarm Unit will send a numerical input to central computer command. he system is required to accomplish the following tasks: - Monitors the level of gamma radiation in those areas of the Station where high radiation fields are expected; - Provides a continuous and centralized display of the radiation level in each of the monitored areas. The display shall be in exposure rate units (R/h); - Provides a visual and audible alarm in each monitored areas; Allows the control room operator to check at any time the radiation levels and alarm conditions in each of the monitored areas; - Control room operator shall be alerted of any alarm conditions that occurs in the Station. A typical monitoring loop is composed of the following components: Detector Assembly type: CI-MA - 522 two channels, two ranges; Horn and Beacon Assembly; Remote Indicating Meter with Warning Lights; Central computer; common equipment for all 40 loops. (authors)

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

    Science.gov (United States)

    Sun, LiMin; Sun, Shouwang

    2011-04-01

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

  4. Wire system aging assessment and condition monitoring (WASCO)

    International Nuclear Information System (INIS)

    Fantoni, P.F.

    2007-04-01

    Nuclear facilities rely on electrical wire systems to perform a variety of functions for successful operation. Many of these functions directly support the safe operation of the facility; therefore, the continued reliability of wire systems, even as they age, is critical. Condition Monitoring (CM) of installed wire systems is an important part of any aging program, both during the first 40 years of the qualified life and even more in anticipation of the license renewal for a nuclear power plant. This report contains some test results of a method for wire system condition monitoring, developed at the Halden Reactor Project, called LIRA (LIne Resonance Analysis), which can be used on-line to detect any local or global changes in the cable electrical parameters as a consequence of insulation faults or degradation. (au)

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

    Energy Technology Data Exchange (ETDEWEB)

    Ueno, K. [Building Science Corporation, Westford, MA (United States)

    2015-03-01

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

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

    Science.gov (United States)

    Alan E. Watson

    1990-01-01

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

  7. Monitoring the Microcirculation in Critical Conditions: Possibilities and Limitations

    Directory of Open Access Journals (Sweden)

    T. O. Tokmakova

    2012-01-01

    Full Text Available The paper provides an analytical review of the references on the role of microcirculatory disorders in the development of critical conditions, the significance of circulatory monitoring, specifically, to make a presumptive prognosis of multiple organ dysfunction. It defines main directions in the diagnosis and correction of microcirculatory disorders as direct (infusion therapy and indirect (influence on the components of a systemic inflammatory response, by extending to microcirculatory correction microcirculatory exposures. Key words: critical conditions, multiple organ dysfunction, procedures to evaluate and correct microcirculation.

  8. Luminosity measurement and beam condition monitoring at CMS

    Energy Technology Data Exchange (ETDEWEB)

    Leonard, Jessica Lynn [DESY, Zeuthen (Germany)

    2015-07-01

    The BRIL system of CMS consists of instrumentation to measure the luminosity online and offline, and to monitor the LHC beam conditions inside CMS. An accurate luminosity measurement is essential to the CMS physics program, and measurement of the beam background is necessary to ensure safe operation of CMS. In expectation of higher luminosity and denser proton bunch spacing during LHC Run II, many of the BRIL subsystems are being upgraded and others are being added to complement the existing measurements. The beam condition monitor (BCM) consists of several sets of diamond sensors used to measure online luminosity and beam background with a single-bunch-crossing resolution. The BCM also detects when beam conditions become unfavorable for CMS running and may trigger a beam abort to protect the detector. The beam halo monitor (BHM) uses quartz bars to measure the background of the incoming beams at larger radii. The pixel luminosity telescope (PLT) consists of telescopes of silicon sensors designed to provide a CMS online and offline luminosity measurement. In addition, the forward hadronic calorimeter (HF) will deliver an independent luminosity measurement, making the whole system robust and allowing for cross-checks of the systematics. Data from each of the subsystems will be collected and combined in the BRIL DAQ framework, which will publish it to CMS and LHC. The current status of installation and commissioning results for the BRIL subsystems are given.

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

    Directory of Open Access Journals (Sweden)

    Siegfried Hohmann

    2015-05-01

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

  10. Intelligent system for pilot and astronaut Psychophysiological status monitoring and recuperating.

    Science.gov (United States)

    Janicki, Andrzej; -Bogumila Pecyna, S. Maria

    called intelligent computations, and their methodology is called “computational intelligence”. The absence of gravity which causes significant physiological stress with broad biomedical changes generated key problems for researchers and practitioners of aviations and space flight. Following previous experiences we had on the matter, some current results achieved on the bases of FlexComp Infinity/Biograph Infiniti, V6.1™ of Thought Technology ltd. [Janicki, Pecyna, 2014] are underlined. A particular emphasis has been placed on the ability of the distributed parallel computations connected with the sophisticated application of the NASA Autogenic Feedback Training AFTE [PS Cowings, 2011] method combined biofeedback and Autogenic Therapy exercises [WIML-NASA, 2011]. The present paper reports on the results of a serious preliminary experiments addressed especially to space disorientation and/or awareness of reality problem. Keywords: pilot’s decision making process; intelligent a agent; coherency; psychophysiological pilot status; remote monitoring; remote training; synthetic indicators; scientific information system; three-factor utility function; space disorientation;Near-Infrared Hemoencephalography; References: A.Janicki “three-factor utility function” in LabTSI™ Modeling and Simulation Platform, KUL Univ. publication 2011 - in polish, page 95-103 M.B. Pecyna and M. Pokorski "Near-Infrared Hemoencephalography for Monitoring Blood Oxygenation in Prefrontal Cortical Areas in diagnosis and Therapy of Developmental Dyslexia" in "Neurobiology of Respiration" Springer Science+Business Media Dordrecht 2013 page 175 - 180. NASA-WIML Workshop on 2011, Psychophysiological Aspects of Flight Safety In Aerospace Operations, WIML 2011

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

    Energy Technology Data Exchange (ETDEWEB)

    Bartelmus, W.; Zimroz, R. [Wroclaw University of Technology, Wroclaw (Poland)

    2009-01-15

    The paper shows that for condition monitoring of planetary gearboxes it is important to identify the external varying load condition. In the paper, systematic consideration has been taken of the influence of many factors on the vibration signals generated by a system in which a planetary gearbox is included. These considerations give the basis for vibration signal interpretation, development of the means of condition monitoring, and for the scenario of the degradation of the planetary gearbox. Real measured vibration signals obtained in the industrial environment are processed. The signals are recorded during normal operation of the diagnosed objects, namely planetary gearboxes, which are a part of the driving system used in a bucket wheel excavator, used in lignite mines. It has been found that the most important factor of the proper planetary gearbox condition is connected with perturbation of arm rotation, where an arm rotation gives rise to a specific vibration signal whose properties are depicted by a short-time Fourier transform (STFT) and Wigner-Ville distribution presented as a time-frequency map. The paper gives evidence that there are two dominant low-frequency causes that influence vibration signal modulation, i.e. the varying load, which comes from the nature of the bucket wheel digging process, and the arm/carrier rotation. These two causes determine the condition of the planetary gearboxes considered.

  12. Monitoring machining conditions by analyzing cutting force vibration

    Energy Technology Data Exchange (ETDEWEB)

    Piao, Chun Guang; Kim, Ju Wan; Kim, Jin Oh; Shin, Yoan [Soongsl University, Seoul (Korea, Republic of)

    2015-09-15

    This paper deals with an experimental technique for monitoring machining conditions by analyzing cutting-force vibration measured at a milling machine. This technique is based on the relationship of the cutting-force vibrations with the feed rate and cutting depth as reported earlier. The measurement system consists of dynamic force transducers and a signal amplifier. The analysis system includes an oscilloscope and a computer with a LabVIEW program. Experiments were carried out at various feed rates and cutting depths, while the rotating speed was kept constant. The magnitude of the cutting force vibration component corresponding to the number of cutting edges multiplied by the frequency of rotation was linearly correlated with the machining conditions. When one condition of machining is known, another condition can be identified by analyzing the cutting-force vibration.

  13. Monitoring machining conditions by analyzing cutting force vibration

    International Nuclear Information System (INIS)

    Piao, Chun Guang; Kim, Ju Wan; Kim, Jin Oh; Shin, Yoan

    2015-01-01

    This paper deals with an experimental technique for monitoring machining conditions by analyzing cutting-force vibration measured at a milling machine. This technique is based on the relationship of the cutting-force vibrations with the feed rate and cutting depth as reported earlier. The measurement system consists of dynamic force transducers and a signal amplifier. The analysis system includes an oscilloscope and a computer with a LabVIEW program. Experiments were carried out at various feed rates and cutting depths, while the rotating speed was kept constant. The magnitude of the cutting force vibration component corresponding to the number of cutting edges multiplied by the frequency of rotation was linearly correlated with the machining conditions. When one condition of machining is known, another condition can be identified by analyzing the cutting-force vibration

  14. Artificial intelligence techniques coupled with seasonality measures for hydrological regionalization of Q90 under Brazilian conditions

    Science.gov (United States)

    Beskow, Samuel; de Mello, Carlos Rogério; Vargas, Marcelle M.; Corrêa, Leonardo de L.; Caldeira, Tamara L.; Durães, Matheus F.; de Aguiar, Marilton S.

    2016-10-01

    Information on stream flows is essential for water resources management. The stream flow that is equaled or exceeded 90% of the time (Q90) is one the most used low stream flow indicators in many countries, and its determination is made from the frequency analysis of stream flows considering a historical series. However, stream flow gauging network is generally not spatially sufficient to meet the necessary demands of technicians, thus the most plausible alternative is the use of hydrological regionalization. The objective of this study was to couple the artificial intelligence techniques (AI) K-means, Partitioning Around Medoids (PAM), K-harmonic means (KHM), Fuzzy C-means (FCM) and Genetic K-means (GKA), with measures of low stream flow seasonality, for verification of its potential to delineate hydrologically homogeneous regions for the regionalization of Q90. For the performance analysis of the proposed methodology, location attributes from 108 watersheds situated in southern Brazil, and attributes associated with their seasonality of low stream flows were considered in this study. It was concluded that: (i) AI techniques have the potential to delineate hydrologically homogeneous regions in the context of Q90 in the study region, especially the FCM method based on fuzzy logic, and GKA, based on genetic algorithms; (ii) the attributes related to seasonality of low stream flows added important information that increased the accuracy of the grouping; and (iii) the adjusted mathematical models have excellent performance and can be used to estimate Q90 in locations lacking monitoring.

  15. An Intelligent and Secure Health Monitoring Scheme Using IoT Sensor Based on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Jin-Xin Hu

    2017-01-01

    Full Text Available Internet of Things (IoT is the network of physical objects where information and communication technology connect multiple embedded devices to the Internet for collecting and exchanging data. An important advancement is the ability to connect such devices to large resource pools such as cloud. The integration of embedded devices and cloud servers offers wide applicability of IoT to many areas of our life. With the aging population increasing every day, embedded devices with cloud server can provide the elderly with more flexible service without the need to visit hospitals. Despite the advantages of the sensor-cloud model, it still has various security threats. Therefore, the design and integration of security issues, like authentication and data confidentiality for ensuring the elderly’s privacy, need to be taken into consideration. In this paper, an intelligent and secure health monitoring scheme using IoT sensor based on cloud computing and cryptography is proposed. The proposed scheme achieves authentication and provides essential security requirements.

  16. Hopfield neural network and optical fiber sensor as intelligent heart rate monitor

    Science.gov (United States)

    Mutter, Kussay Nugamesh

    2018-01-01

    This paper presents a design and fabrication of an intelligent fiber-optic sensor used for examining and monitoring heart rate activity. It is found in the literature that the use of fiber sensors as heart rate sensor is widely studied. However, the use of smart sensors based on Hopfield neural networks is very low. In this work, the sensor is a three fibers without cladding of about 1 cm, fed by laser light of 1550 nm of wavelength. The sensing portions are mounted with a micro sensitive diaphragm to transfer the pulse pressure on the left radial wrist. The influenced light intensity will be detected by a three photodetectors as inputs into the Hopfield neural network algorithm. The latter is a singlelayer auto-associative memory structure with a same input and output layers. The prior training weights are stored in the net memory for the standard recorded normal heart rate signals. The sensors' heads work on the reflection intensity basis. The novelty here is that the sensor uses a pulse pressure and Hopfield neural network in an integrity approach. The results showed a significant output measurements of heart rate and counting with a plausible error rate.

  17. Intelligent, net or wireless enabled fluorosensors for high throughput monitoring of assorted crops

    International Nuclear Information System (INIS)

    Barócsi, Attila

    2013-01-01

    Phenotypic characterization of assorted crops of different genotypes requires large data sets of diverse types for statistical reliability. Temporal monitoring of plant fluorescence is able to capture the dynamics of the photosynthesis process that is summarized in a number of parameters for which the genotypic heritability can be calculated. In this paper, an intelligent sensor system is presented that is capable of high-throughput production of baseline-corrected temporal fluorescence curves with many feature points. These are obtained by integrating several (direct and modulated) measurement methods applied at different wavelengths. Simultaneously, temporal change of the sample's emission and the ambient reference temperatures are recorded. Multiple sensors can be deployed easily in large span greenhouse environments with centralized data collection over wired or wireless infrastructure. The unique features of the sensors are a compact, embedded signal guiding fibre optic system, instrument-standard variable tubular detector and source modules, net or wireless enabling for remote control and fast, quasi real-time data collection. Along with the instrumentation, some representative phenotyping data are also presented that were taken on a subset of pepper recombinant inbred line population. It is also demonstrated that transient fluorescence feature points yield high heritability, offering a high confidence level for distinguishing the pepper genotypes. (paper)

  18. Monitoring of operation with artificial intelligence methods; Betriebsueberwachung mit Verfahren der Kuenstlichen Intelligenz

    Energy Technology Data Exchange (ETDEWEB)

    Bruenninghaus, H. [DMT-Gesellschaft fuer Forschung und Pruefung mbH, Essen (Germany). Geschaeftsbereich Systemtechnik

    1999-03-11

    Taking the applications `early detection of fires` and `reduction of burst of messages` as an example, the usability of artificial intelligence (AI) methods in the monitoring of operation was checked in a R and D project. The contribution describes the concept, development and evaluation of solutions to the specified problems. A platform, which made it possible to investigate different AI methods (in particular artificial neuronal networks), had to be creaated as a basis for the project. At the same time ventilation data had to be acquired and processed by the networks for the classification. (orig.) [Deutsch] Am Beispiel der Anwendungsfaelle `Brandfrueherkennung` und `Meldungsschauerreduzierung` wurde im Rahmen eines F+E-Vorhabens die Einsetzbarkeit von Kuenstliche-Intelligenz-Methoden (KI) in der Betriebsueberwachung geprueft. Der Beitrag stellt Konzeption, Entwicklung und Bewertung von Loesungsansaetzen fuer die genannten Aufgabenstellungen vor. Als Grundlage fuer das Vorhaben wurden anhand KI-Methoden (speziell: Kuenstliche Neuronale Netze -KNN) auf der Grundlage gewonnener und aufbereiteter Wetterdaten die Beziehungen zwischen den Wettermessstellen im Laufe des Wetterwegs klassifiziert. (orig.)

  19. Unmanned Aerial Vehicles (UAVs and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

    Directory of Open Access Journals (Sweden)

    Luis F. Gonzalez

    2016-01-01

    Full Text Available Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV, artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

  20. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

    Science.gov (United States)

    Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

    2016-01-14

    Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

  1. The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

    International Nuclear Information System (INIS)

    Kazarov, A; Miotto, G Lehmann; Magnoni, L

    2012-01-01

    to centralize all communication between modules. The result is an intelligent system able to extract and compute relevant information from the flow of operational data to provide real-time feedback to human experts who can promptly react when needed. The paper presents the design and implementation of the AAL project, together with the results of its usage as automated monitoring assistant for the ATLAS data taking infrastructure.

  2. The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

    Science.gov (United States)

    Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

    2012-06-01

    to centralize all communication between modules. The result is an intelligent system able to extract and compute relevant information from the flow of operational data to provide real-time feedback to human experts who can promptly react when needed. The paper presents the design and implementation of the AAL project, together with the results of its usage as automated monitoring assistant for the ATLAS data taking infrastructure.

  3. Infant Long-Term Memory for a Conditioned Response and Intelligence Test Performance at 2 Years of Age.

    Science.gov (United States)

    Fagen, Jeffrey W.; And Others

    To find predictive relations between measures taken in infancy and later scores on intelligence tests, a study was made that measured in the infant those cognitive processes examined later in life. Operant conditioning tasks were employed which required 3-, 7-, and 11-month-old infants to execute some response to produce an environmental…

  4. Intelligent monitoring system for real-time geologic CO2 storage, optimization and reservoir managemen

    Science.gov (United States)

    Dou, S.; Commer, M.; Ajo Franklin, J. B.; Freifeld, B. M.; Robertson, M.; Wood, T.; McDonald, S.

    2017-12-01

    Archer Daniels Midland Company's (ADM) world-scale agricultural processing and biofuels production complex located in Decatur, Illinois, is host to two industrial-scale carbon capture and storage projects. The first operation within the Illinois Basin-Decatur Project (IBDP) is a large-scale pilot that injected 1,000,000 metric tons of CO2 over a three year period (2011-2014) in order to validate the Illinois Basin's capacity to permanently store CO2. Injection for the second operation, the Illinois Industrial Carbon Capture and Storage Project (ICCS), started in April 2017, with the purpose of demonstrating the integration of carbon capture and storage (CCS) technology at an ethanol plant. The capacity to store over 1,000,000 metric tons of CO2 per year is anticipated. The latter project is accompanied by the development of an intelligent monitoring system (IMS) that will, among other tasks, perform hydrogeophysical joint analysis of pressure, temperature and seismic reflection data. Using a preliminary radial model assumption, we carry out synthetic joint inversion studies of these data combinations. We validate the history-matching process to be applied to field data once CO2-breakthrough at observation wells occurs. This process will aid the estimation of permeability and porosity for a reservoir model that best matches monitoring observations. The reservoir model will further be used for forecasting studies in order to evaluate different leakage scenarios and develop appropriate early-warning mechanisms. Both the inversion and forecasting studies aim at building an IMS that will use the seismic and pressure-temperature data feeds for providing continuous model calibration and reservoir status updates.

  5. Intelligent mobile sensor system for drum inspection and monitoring: Phase 1

    International Nuclear Information System (INIS)

    1993-06-01

    The objective of this project was to develop an operational system for monitoring and inspection activities for waste storage facility operations at several DOE sites. Specifically, the product of this effort is a robotic device with enhanced intelligence and maneuverability capable of conducting routine inspection of stored waste drums. The device is capable of operating in narrow aisles and interpolating the free aisle space between rows of stacked drums. The system has an integrated sensor suite for leak detection, and is interfaced with a site database both for inspection planning and for data correlation, updating, and report generation. The system is capable of departing on an assigned mission, collecting required data, recording which positions of its mission had to be aborted or modified due to environmental constraints, and reporting back when the mission is complete. Successful identification of more than 90% of all drum defects has been demonstrated in a high fidelity waste storage facility mockup. Identified anomalies included rust spots, rust streaks, areas of corrosion, dents, and tilted drums. All drums were positively identified and correlated with the site database. This development effort is separated into three phases of which phase one is now complete. The first phase has demonstrated an integrated system for monitoring and inspection activities for waste storage facility operations. This demonstration system was quickly fielded and evaluated by leveraging technologies developed from previous NASA and DARPA contracts and internal research. The second phase will demonstrate a prototype system appropriate for operational use in an actual storage facility. The prototype provides an integrated design that considers operational requirements, hardware costs, maintenance, safety, and robustness. The final phase will demonstrate commercial viability using the prototype vehicle in a pilot waste operations and inspection project

  6. Condition Management of Marine Lube Oil and the Role of Intelligent Sensor Systems in Diagnostics

    International Nuclear Information System (INIS)

    Knowles, M; Baglee, D

    2012-01-01

    Failures in marine diesel engines can be costly and can cause extreme inconvenience when they result in ships becoming stranded. Lubricating oil is a crucial component in maintaining engine reliability and so monitoring its condition is essential. Furthermore the lubricating oil offers early indication of various other engine faults. Current approaches to oil-based condition monitoring involve samples being sent for land based testing which involves considerable delay during which the situation could deteriorate further. Furthermore there is a substantial risk of contamination. The POSSEIDON project aimed to address this by developing a system involving real-time condition monitoring sensors observing the properties of the lubricating oil. Novel sensors were developed which address the specific issues associated with the marine environment. Furthermore, to complement the sensor system outputs, specific monitoring and diagnosis software has been developed to support the operation of onboard personnel with specific advice. On-line management of engine and lubricant condition aboard the ship may thus be achieved. In this paper we will describe the progress achieved in this area by the recently completed POSSEIDON project, outline the opportunities for ongoing development in this area and describe the roadmap for future development. The Reliability Centered Maintenance (RCM) paradigm will be applied to identify critical aspects of oil condition and prioritize parameters for measurement. The critical issues for development of the prototype unit into a viable commercial unit will be discussed including hardware design constraints, sensor miniaturization and display optimization. Issues such onboard connectivity, ship to shore communications will also be addressed.

  7. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2012-01-01

    Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

  8. Condition monitoring of rotormachinery in nuclear power plants

    International Nuclear Information System (INIS)

    Suedmersen, U.; Runkel, J.; Vortriede, A.; Reimche, W.; Stegemann, D.

    1996-01-01

    Due to safety and economical reasons diagnostic and monitoring systems are of growing interest in nuclear power plants and other complex industrial productions. Key components of NPP's are rotating machineries of the primary and secondary loops like PWR main coolant pumps, BWR recirculation pumps, turbines, fresh water pumps and feed water pumps. Diagnostic systems are requested which detect, diagnose and localize faulty operation conditions at an early stage in order to prevent severe failures and to enable predictive and condition oriented maintenance. The knowledge of characteristical machine signatures and their time dependent behaviour are the basis of efficient condition monitoring of rotating machines. The performance of reference measurements are of importance for fault detection during operation by trend settings. The comparison with thresholds given by norms and standards is only a small section of available possibilities. Therefore, for each machinery own thresholds should be determined using statistical time values, spectra comparison, cepstrum analysis and correlation analysis for source localization corresponding to certain machine operation conditions. (author). 14 refs, 15 figs

  9. ASSESSMENT OF CABLE AGING USING CONDITION MONITORING TECHNIQUES

    International Nuclear Information System (INIS)

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

    2000-01-01

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

  10. Condition monitoring of rotormachinery in nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Suedmersen, U; Runkel, J; Vortriede, A; Reimche, W; Stegemann, D [University of Hannover, Hannover (Germany). Inst. of Nuclear Engineering and Nondestructive Testing

    1997-12-31

    Due to safety and economical reasons diagnostic and monitoring systems are of growing interest in nuclear power plants and other complex industrial productions. Key components of NPP`s are rotating machineries of the primary and secondary loops like PWR main coolant pumps, BWR recirculation pumps, turbines, fresh water pumps and feed water pumps. Diagnostic systems are requested which detect, diagnose and localize faulty operation conditions at an early stage in order to prevent severe failures and to enable predictive and condition oriented maintenance. The knowledge of characteristical machine signatures and their time dependent behaviour are the basis of efficient condition monitoring of rotating machines. The performance of reference measurements are of importance for fault detection during operation by trend settings. The comparison with thresholds given by norms and standards is only a small section of available possibilities. Therefore, for each machinery own thresholds should be determined using statistical time values, spectra comparison, cepstrum analysis and correlation analysis for source localization corresponding to certain machine operation conditions. (author). 14 refs, 15 figs.

  11. Condition Monitoring Through Advanced Sensor and Computational Technology

    International Nuclear Information System (INIS)

    Kim, Jung Taek; Park, Won Man; Kim, Jung Soo; Seong, Soeng Hwan; Hur, Sub; Cho, Jae Hwan; Jung, Hyung Gue

    2005-05-01

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

  12. Wireless condition monitoring for the RA-6 research reactor

    International Nuclear Information System (INIS)

    Garcia Peyrano, O.; Calzeta, O.; Rico, N.; Damiani, H.; Coutsiers, E.

    1999-01-01

    The vibration laboratory at C.A.B. has a great experience with the analysis and diagnostic of symptoms of failures in the rotating equipment of the R-6 research reactor and in our longest NPP (CANDU 600 Mw), located in Embalse town, Cordoba City, Argentina. Objective: The standard condition monitoring instrumentation system were designed for large equipment operating under different environmental conditions and sensitivities. The signal processing is not flexible and the diagnostic is an expensive method for the small poll type research reactors. This papers describes the research and development which are related whit the new concept, cheaper and flexible condition monitoring instrumentation system. Implementing a vibration analysis measurements technique with a sensor inside (in the pool) of the nuclear reactor RA-6, and mainly based on fft signal processing, an extensive program for vibration source identification was done. Different nuclear power conditions were monitored as full power and in zero power, also. This zero power shows the best acoustical environmental, because the cooling pumps are stop, and the core is cooling by natural convection. Two sensors were mainly used as the detector's subsystem. One of these detectors was an accelerometer attached to the top of the fine control rod and the other one was a water resistant omnidirectional microphone which was located underwater at different distances from the nuclear core. All the signal measurement by this two sensors were recorded and then was processed. Both signal was acquired at the same time for correlation analysis purposes. The analysis was composed by a 'Spectral Dynamics SD380' connected to a P.C. with dedicated post processing software. On the other hand, some calibration and sensitivity comparison was done using an SKFCM40, dual channel data collector and analyzer. (author)

  13. The Impact of Emotional Intelligence on Conditions of Trust Among Leaders at the Kentucky Department for Public Health

    Directory of Open Access Journals (Sweden)

    Jennifer Redmond Knight

    2015-03-01

    Full Text Available There has been limited leadership research on emotional intelligence and trust in governmental public health settings. The purpose of this study was to identify and seek to understand the relationship between trust and elements of emotional intelligence, including stress management, at the Kentucky Department for Public Health. The Kentucky Department for Public Health (KDPH serves as Kentucky’s state governmental health department. KDPH is led by a Commissioner and composed of seven primary divisions and 25 branches within those divisions. The study was a non-randomized cross-sectional study utilizing electronic surveys that evaluated conditions of trust among staff members and emotional intelligence among supervisors. Pearson correlation coefficients and corresponding p-values are presented to provide the association between emotional intelligence scales and the conditions of trust. Significant positive correlations were observed between supervisors' stress management and the staff members' trust or perception of supervisors' loyalty(r=0.6, p=0.01, integrity(r=0.5, p=0.03, receptivity(r=0.6, p=0.02, promise fulfillment(r=0.6, p=0.02 and availability (r=0.5, p=0.07. This research lays the foundation for emotional intelligence and trust research and leadership training in other governmental public health settings, such as local, other state, national or international organizations. This original research provides metrics to assess the public health workforce with attention to organizational management and leadership constructs. The survey tools could be used in other governmental public health settings in order to develop tailored training opportunities related to emotional intelligence and trust organizations.

  14. Ionization beam profile monitor for operation under hard environmental conditions

    International Nuclear Information System (INIS)

    Teterev, Yu.G.; Kaminski, G.; Phi Thanh Huong; Kaminski, G.; Kozik, E.

    2010-01-01

    The design and the performance of the Ionization Beam Profile Monitor (IBPM) operating on the residual gas ionization principle are described. The main advantage of the constructed device is the non-contact measuring method. Operating under hard environmental conditions it delivers the information about the primary beam position, profile and intensity in 'on-line' regime. It was found out that the device is capable to operate in vacuum in the range of 10 -6 /10 -3 mbar without the loss of the resolution power at the beam current as low as a few nA. The IBPM is prospective for beam profile monitoring due to long time. Emergency situations do not lead to decrease of its operability.

  15. Cable condition monitoring in a pressurized water reactor environment

    International Nuclear Information System (INIS)

    Al-Hussaini, T.J.

    1988-01-01

    Oconee Nuclear Station is the first nuclear plant designed, engineered and constructed by Duke Power Company. Even though the accelerated aging method was available to determine the life expectancy of the cable used in the reactor building, no natural aging data was available at that time. In order to be able to verify the condition of the reactor building cable over the life of the plant, an on-going cable monitoring plan was instituted. Various types of cable were selected to be monitored, and they were installed in cable life evaluation circuits in the reactor building. At five year intervals over the life of the plant, cable samples would be removed from these cable life evaluation circuits and tested to determine the effects of the reactor building environment on the integrity of the cable. A review of the cable life evaluation circuits and the results of the evaluation program to date is presented

  16. Research on Land Ecological Condition Investigation and Monitoring Technology

    Science.gov (United States)

    Lv, Chunyan; Guo, Xudong; Chen, Yuqi

    2017-04-01

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

  17. Condition monitoring of pumps with co-relating field observations

    International Nuclear Information System (INIS)

    Mishra, S.K.; Prasad, V.; Sharma, R.B.

    1994-01-01

    The maintenance of 40 MWth research reactor, Cirus has been carried out for over 30 years following the time based maintenance schedule. With the commissioning of indigenously built 100 MWth nuclear research reactor Dhruva in the year 1985, a systematic work on condition monitoring has been commissioned. Apart from process parameters, which are recorded on hourly basis, vibration, noise, temperature, kurtosis etc. are measured for assessment of condition of pumps. The bearings of flywheel assembly of main pumps, Dhruva broke down almost abruptly during the initial years after first commissioning. The regular measurements of vibration level and kurtosis have greatly helped in avoiding breakdown. In a recent case one newly procured herringbone gear box (300 hp, 1475/1760 rpm) for the primary coolant pump was showing high vibration. In further checking using Fast Fourier Transform (FFT) analyser in a time domain plot the gear teeth damage was indicated. The pump was shut down for inspection and when the gear box was dismantled teeth were found broken. An attempt has been made in this paper to discuss a few interesting field experiences with condition monitoring and correlating field observations on pumps. (author). 3 figs

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

    Energy Technology Data Exchange (ETDEWEB)

    Sheng, S.

    2012-07-01

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

  19. Mechanical Seal Opening Condition Monitoring Based on Acoustic Emission Technology

    Directory of Open Access Journals (Sweden)

    Erqing Zhang

    2014-06-01

    Full Text Available Since the measurement of mechanical sealing film thickness and just-lift-off time is very difficult, the sealing film condition monitoring method based on acoustic emission signal is proposed. The mechanical seal acoustic emission signal present obvious characteristics of time-varying nonlinear and pulsating. In this paper, the acoustic emission signal is used to monitor the seal end faces just-lift-off time and friction condition. The acoustic emission signal is decomposed by empirical mode decomposition into a series of intrinsic mode function with independent characteristics of different time scales and different frequency band. The acoustic emission signal only generated by end faces friction is obtained by eliminating the false intrinsic mode function components. The correlation coefficient of acoustic emission signal and Multi-scale Laplace Wavelet is calculated. It is proved that the maximum frequency (8000 Hz of the correlation coefficient is appeared at the spindle speed of 300 rpm. And at this time (300 rpm the end faces have just lifted off. By a set of mechanical oil seal running test, it is demonstrated that this method could accurately identify mechanical seal end faces just-lift-off time and friction condition.

  20. Optimization of Remediation Conditions using Vadose Zone Monitoring Technology

    Science.gov (United States)

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

    2010-12-01

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

  1. Guaranteeing robustness of structural condition monitoring to environmental variability

    Science.gov (United States)

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

    2017-01-01

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

  2. The application of artificial intelligence on the optimal solution of the operating conditions of continuous casting; Aplicacao da inteligencia artificial na solucao otima das condicoes operacionais do lingotamento continuo

    Energy Technology Data Exchange (ETDEWEB)

    Spim Junior, J.A.; Ierardi, M.C.F.; Garcia, A. [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica

    1995-12-31

    This work presents the development of a software that incorporates artificial intelligence techniques, directly applied to the metallurgical industry, particularly to those using the continuous casting process for ingot production. The essential parts of the continuous casting equipment which must be subjected to monitoring are presented, and a methodology of physical settlements in each cooling region as well. The modification performed by the intelligent program taking into account the critical rules conducting to an efficient solidification, are compared with real time simulation of ingot surface temperatures. The efficiency of the intelligent system is assured by final product quality parameters. This approach is applied to the real dimension of a slab continuous caster under real operation conditions, demonstrating that very good results can be attained by using an heuristic search 11 refs., 4 figs., 4 tabs.

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

    Science.gov (United States)

    Crutchfield, J.

    2016-12-01

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

  4. Optical Communication System for Remote Monitoring and Adaptive Control of Distributed Ground Sensors Exhibiting Collective Intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Cameron, S.M.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-11-01

    Comprehensive management of the battle-space has created new requirements in information management, communication, and interoperability as they effect surveillance and situational awareness. The objective of this proposal is to expand intelligent controls theory to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and interoperative global optimization for sensor fusion and mission oversight. By using a layered hierarchal control architecture to orchestrate adaptive reconfiguration of autonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecks. In this concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a covert laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelli- gence opens up a new class of remote-sensing applications in which small single-function autono- mous observers at the local level can collectively optimize and measure large scale ground-level signals. AS the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandwidth requirements within the net. A system of the type described in this proposal will be capable of sensitively detecting, tracking, and mapping spatial distributions of measurement signatures which are non-stationary or obscured by clutter and inter- fering obstacles by virtue of adaptive reconfiguration. This methodology could be used, for example, to field an adaptive ground-penetrating radar for detection of underground structures in

  5. Upgraded Fast Beam Conditions Monitor for CMS online luminosity measurement

    CERN Document Server

    Leonard, Jessica Lynn; Hempel, Maria; Henschel, Hans; Karacheban, Olena; Lange, Wolfgang; Lohmann, Wolfgang; Novgorodova, Olga; Penno, Marek; Walsh, Roberval; Dabrowski, Anne; Guthoff, Moritz; Loos, R; Ryjov, Vladimir; Burtowy, Piotr; Lokhovitskiy, Arkady; Odell, Nathaniel; Przyborowski, Dominik; Stickland, David P; Zagozdzinska, Agnieszka

    2014-01-01

    The CMS beam condition monitoring subsystem BCM1F during LHC Run I consisted of 8 individual diamond sensors situated around the beam pipe within the tracker detector volume, for the purpose of fast monitoring of beam background and collision products. Effort is ongoing to develop the use of BCM1F as an online bunch-by-bunch luminosity monitor. BCM1F will be running whenever there is beam in LHC, and its data acquisition is independent from the data acquisition of the CMS detector, hence it delivers luminosity even when CMS is not taking data. To prepare for the expected increase in the LHC luminosity and the change from 50 ns to 25 ns bunch separation, several changes to the system are required, including a higher number of sensors and upgraded electronics. In particular, a new real-time digitizer with large memory was developed and is being integrated into a multi-subsystem framework for luminosity measurement. Current results from Run II preparation will be discussed, including results from the January 201...

  6. Monitoring of lubrication conditions in journal bearing by acoustic emission

    International Nuclear Information System (INIS)

    Yoon, Dong Jin; Kwon, Oh Yang; Jung, Min Hwa

    1993-01-01

    Systems with journal bearings generally operate in large scale and under severe loading conditions such as steam generator turbines and internal combustion engines, in contrast to the machinery using rolling element bearings. Failure of the bearings in these machinery can result in the system breakdown. To avoid the time consuming repair and considerable economic loss, the detection of incipient failure in journal bearings becomes very important. In this experimental approach, acoustic emission monitoring is employed to the detection of incipient failure caused by intervention of foreign particles most probable in the journal bearing systems. It has been known that the intervention of foreign materials, insufficient lubrication and misassembly etc. are principal factors to cause bearing failure and distress. The experiment was conducted under such designed conditions as inserting alumina particles to the lubrication layer in the simulated journal bearing system. The results showed that acoustic emission could be an effective tool to detect the incipient failure in journal bearings.

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

    Science.gov (United States)

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

    2013-12-01

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

  8. The influence of gender on personality variables conditioning learning: Emotional intelligence and academic procrastination

    Directory of Open Access Journals (Sweden)

    Mercè Clariana,

    2011-10-01

    Full Text Available This research analyses the relationship between academic procrastination and emotional intelligence taking also into account the gender and age influence. Psychology undergraduates from the UAB (Universitat Autónoma de Barcelona, Spain and the UIB (Universitat de les Illes Balears, Spain, 45 males and 147 females constituted the sample of the study. Academic procrastination was assessed by means of the D scale (CLARIANA & MARTÍN, 2008 and emotional intelligence by means of the EQ–i (BAR–ON, 1997. The results show that academic procrastination has a significant negative relationship with intrapersonal intelligence, emotional quotient and mood. Moreover, female students scored significantly higher than males both in intrapersonal and interpersonal Intelligence while males obtained higher scores in both stress management and adaptability.

  9. Condition monitoring of machinery using motor current signature analysis

    International Nuclear Information System (INIS)

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

    1989-01-01

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

  10. Wire system aging assessment and condition monitoring (WASCO)

    Energy Technology Data Exchange (ETDEWEB)

    Fantoni, P.F. [Institutt for energiteknikk (Norway); Nordlund, A. [Chalmers Univ. of Technology (Sweden)

    2006-04-15

    Nuclear facilities rely on electrical wire systems to perform a variety of functions for successful operation. Many of these functions directly support the safe operation of the facility; therefore, the continued reliability of wire systems, even as they age, is critical. Condition Monitoring (CM) of installed wire systems is an important part of any aging program, both during the first 40 years of the qualified life and even more in anticipation of the license renewal for a nuclear power plant. This report describes a method for wire system condition monitoring, developed at the Halden Reactor Project, which is based on Frequency Domain Reflectometry. This method resulted in the development of a system called LIRA (LIne Resonance Analysis), which can be used on-line to detect any local or global changes in the cable electrical parameters as a consequence of insulation faults or degradation. LIRA is composed of a signal generator, a signal analyser and a simulator that can be used to simulate several failure/degradation scenarios and assess the accuracy and sensitivity of the LIRA system. Chapter 5 of this report describes an complementary approach based on positron measurement techniques, used widely in defect physics due to the high sensitivity to micro defects, in particular open volume defects. This report describes in details these methodologies, the results of field experiments and the proposed future work. (au)

  11. Wire system aging assessment and condition monitoring (WASCO)

    International Nuclear Information System (INIS)

    Fantoni, P.F.; Nordlund, A.

    2006-04-01

    Nuclear facilities rely on electrical wire systems to perform a variety of functions for successful operation. Many of these functions directly support the safe operation of the facility; therefore, the continued reliability of wire systems, even as they age, is critical. Condition Monitoring (CM) of installed wire systems is an important part of any aging program, both during the first 40 years of the qualified life and even more in anticipation of the license renewal for a nuclear power plant. This report describes a method for wire system condition monitoring, developed at the Halden Reactor Project, which is based on Frequency Domain Reflectometry. This method resulted in the development of a system called LIRA (LIne Resonance Analysis), which can be used on-line to detect any local or global changes in the cable electrical parameters as a consequence of insulation faults or degradation. LIRA is composed of a signal generator, a signal analyser and a simulator that can be used to simulate several failure/degradation scenarios and assess the accuracy and sensitivity of the LIRA system. Chapter 5 of this report describes an complementary approach based on positron measurement techniques, used widely in defect physics due to the high sensitivity to micro defects, in particular open volume defects. This report describes in details these methodologies, the results of field experiments and the proposed future work. (au)

  12. Thermal Analysis for Condition Monitoring of Machine Tool Spindles

    International Nuclear Information System (INIS)

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

    2012-01-01

    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.

  13. SIM2PeD– Intelligent monitoring system for prevention of diabetic foot

    African Journals Online (AJOL)

    Tuoyo Aghomotsegin

    2016-10-12

    Oct 12, 2016 ... integrated with a mobile device to capture individuals' data, entitled Mobile ... Key words: Intelligent module, diabetes, application, diabetic foot. ..... treatment of 575 diabetic foot ulcers at home, Ph.D. thesis, University.

  14. Mimic sensor to monitor condition of human health; Mimic sensor wo riyoshita taicho monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Nagata, Y. [Mechanical Engineering Lab., Tokyo (Japan)

    2000-04-01

    In the aging society where the birth rate decreases and the number of nuclear families increases, it is very important to inquire after the aged or physically handicapped people, to monitor their physical conditions, and to take steps to keep them healthy. As for the in-home physical measurement for the aged or physically handicapped people and the work of health management for them based on such measurement, it is feared that under the present conditions the invalid themselves or their family members or nurses will inevitably have to bear the burden and that nobody can deny the difficulty of continuing such nursing care. If daily physical condition measurement and related data collection are automatically carried out, however, interested people' burden will lessen and in-home heath management will become actually feasible. In this paper, a mimic sensor for realizing such a situation is described, which will measure physical conditions without interfering with the daily life of interested people. Serving as the mimic sensor is a blood flow sensor embedded in a telephone receiver, and changes in the blood flow during telephone conversation and changes in the gaps between peeks will be monitored. The feasibility is shown of continual collection of information necessary for the measurement of physical conditions of the aged or physically handicapped persons. (NEDO)

  15. Equipment monitoring and diagnosis of their mechanical condition

    International Nuclear Information System (INIS)

    Morel, J.; Monnier, B.

    1994-01-01

    The main objectives of reactor monitoring are reviewed and the three monitoring types are described: reception controls and alarms, periodical controls, and specific monitoring. The monitoring process is then presented: information acquisition, dysfunction detection and diagnosis, risk analysis and maintenance action determination. Diagnosis assistance is now automated with expert systems such as DIVA (shaft vibration diagnosis) and DIAPO (primary pump diagnosis). Several application examples at EDF are described: SEXTEN reactor containment tightness monitoring, large and small-size turbo-machine monitoring, reactor inner structure monitoring, loose part detection in the primary circuit. All these informations will be centralized in a general monitoring and diagnosis assistance station. 3 fig

  16. Condition monitoring of electrical equipment in nuclear power plants

    International Nuclear Information System (INIS)

    Sugarman, A.

    1986-01-01

    Condition monitoring (CM) is a subset of maintenance testing. It is a quantitative, predictive technique for assessing the effects of all types of aging (environmental, cyclic, operational, etc) on the ''health'' of the equipment. A difference between CM and maintenance testing is that the latter is neither quantitative (i.e., measures the relative condition of the component or material as opposed to merely verifying that its condition is acceptable) nor predictive (i.e., makes judgments, on the ability of the component to perform at a future time). A common example of the principle of CM can be illustrated with the automobile which has a lifetime that is small enough to observe all the periods (break in, random failure, wear out) that occur throughout aging. There are several weak link components in the car (e.g., water hoses, contacts in the distributor, generator, spark plug cables, solenoid, etc) which if they fail will cause failure of the automobile to either start or run. From the day the car is put on the road and is subjected to heat and vibration, significant aging of these components occurs. Degradation in the water hoses, for example is manifested by the elastomeric casing becoming brittle and cracking

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

    Science.gov (United States)

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

    2016-05-01

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

  18. Expert System for Diagnostics and Status Monitoring of NPP Water Chemistry Condition

    International Nuclear Information System (INIS)

    Shvedova, M.N.; Kritski, V.G.; Zakharova, S.V.; Nikolaev, F.V.; Benediktov, V.B.

    2002-01-01

    Water chemistry condition (WCC) has been the subject of constant study and improvement up to the present day. It is connected with the presence of a direct relationship between the violation of water chemistry regulation on the one hand and components reliability of the circuit's equipment and cost-effectiveness of their operation on the other. It dictates the necessity to apply different optimization methods in the field of monitoring and use of information - analytical and diagnostic systems to assess WCC quality, control and support. By now NPP experts have broad experience in revealing and removing the causes of WCC disturbances. However this knowledge is often of an intuitive, non-classified nature, scattered among various working documents, which makes their transfer difficult. Based on what has been mentioned above, special attention is currently being paid to the problem of creating expert diagnostic systems for supporting the optimum WCC. The existing developments in this field (DIWA, Smart chem Works, the water quality control system at the Onagava NPP etc. [1,3,4,5] are based on wide use of experts' knowledge. Such expert diagnostic systems for supporting WCC refer to the new generation of intellectual control methods, which allow the incorporation of the latest achievements both in the field of water chemistry simulation and in the field of artificial intelligence and computer technologies. LI 'VNIPIET' employees have, for several years, been developing an expert diagnostic system for supporting WCC and status monitoring of RBMK - reactor NPPs [2]. This system has not only conveniently organized the traditional functions of information acquisition and storage, a complete presentation of information in the form of tables, graphs of a dynamical changes of parameters and formation regular reports, diagnostic functions and issuing recommendations on WCC correction, but it also allows the assessment of confidence in the diagnosis made, relying on a wide

  19. Gearbox Fatigue Load Estimation for Condition Monitoring of Wind Turbines

    DEFF Research Database (Denmark)

    Perisic, Nevena; Pedersen, Bo Juul; Kirkegaard, Poul Henning

    2012-01-01

    control and data acquisition (SCADA) system. Estimated loads can be further used for prediction of remaining operating lifetime of turbine components, detection of high stress level or fault detection. An augmented Kalman filter is chosen as the fatigue load estimator because its characteristics well suit......The focus of the paper is on a design of a fatigue load estimator for predictive condition monitoring systems (CMS) of wind turbines. In order to avoid high-price measurement equipment required for direct load measuring, an indirect approach is suggested using only measurements from supervisory...... for the real time application. This paper presents results of the estimation of the gearbox fatigue load, often called shaft torque, using simulated data of wind turbine. Noise sensitivity of the algorithm is investigated by assuming different levels of measurement noise. Shaft torque estimations are compared...

  20. Maintenance Planning of Offshore Wind Turbine using Condition Monitoring Information

    DEFF Research Database (Denmark)

    Ramírez, José G. Rangel; Sørensen, John Dalsgaard

    2009-01-01

    Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To "control" this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and control...... the deterioration in structures such as offshore wind turbines (OWT). Besides these methods, the integration of condition monitoring information (CMI) can optimize the mitigation activities as an updating tool. In this paper, a framework for risk-based inspection and maintenance planning (RBI) is applied for OWT....... With the integration of CMI by means Bayesian inference, a slightly change of first inspection times are coming up, influenced by the reduction of the uncertainty and harsher or milder external agents....

  1. Condition monitoring with Mean field independent components analysis

    DEFF Research Database (Denmark)

    Pontoppidan, Niels Henrik; Sigurdsson, Sigurdur; Larsen, Jan

    2005-01-01

    We discuss condition monitoring based on mean field independent components analysis of acoustic emission energy signals. Within this framework it is possible to formulate a generative model that explains the sources, their mixing and also the noise statistics of the observed signals. By using...... a novelty approach we may detect unseen faulty signals as indeed faulty with high precision, even though the model learns only from normal signals. This is done by evaluating the likelihood that the model generated the signals and adapting a simple threshold for decision. Acoustic emission energy signals...... from a large diesel engine is used to demonstrate this approach. The results show that mean field independent components analysis gives a better detection of fault compared to principal components analysis, while at the same time selecting a more compact model...

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

    Science.gov (United States)

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

    2017-08-01

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

  3. Speech intelligibility for normal hearing and hearing-impaired listeners in simulated room acoustic conditions

    DEFF Research Database (Denmark)

    Arweiler, Iris; Dau, Torsten; Poulsen, Torben

    Speech intelligibility depends on many factors such as room acoustics, the acoustical properties and location of the signal and the interferers, and the ability of the (normal and impaired) auditory system to process monaural and binaural sounds. In the present study, the effect of reverberation...... on spatial release from masking was investigated in normal hearing and hearing impaired listeners using three types of interferers: speech shaped noise, an interfering female talker and speech-modulated noise. Speech reception thresholds (SRT) were obtained in three simulated environments: a listening room......, a classroom and a church. The data from the study provide constraints for existing models of speech intelligibility prediction (based on the speech intelligibility index, SII, or the speech transmission index, STI) which have shortcomings when reverberation and/or fluctuating noise affect speech...

  4. Proportional monitoring of the acoustic emission in crypto-conditions

    Directory of Open Access Journals (Sweden)

    Petr Dostál

    2011-01-01

    Full Text Available The work is aimed at studying corrosion and fatigue properties of aluminum alloys by means of acoustic emission (AE. During material degradation are acoustic events scanned and evaluated. The main objective of the article is a description of behavior of aluminum alloys degraded in specific conditions and critical degradation stages determination. The first part of the article describes controlled degradation of the material in the crypto–conditions. The acoustic emission method is used for process analyzing. This part contains the AE signals assessment and comparing aluminium alloy to steel. Then the specimens are loaded on high-cyclic loading apparatus for fatigue life monitoring. Also, the synergy of fatigue and corrosion processes is taken into account.The aim is the description of fatigue properties for aluminum alloys that have already been corrosion-degraded. Attention is also focused on the structure of fatigue cracks. The main part of the article is aimed at corrosion degradation of aluminium alloys researched in real time by means of AE. The most important benefit of AE detection/recording is that it provides information about the process in real time. Using this measurement system is possible to observe the current status of the machines/devices and to prevent serious accidents.

  5. Abnormal condition detector for a local power range monitor

    International Nuclear Information System (INIS)

    Akiyama, Takao.

    1976-01-01

    Object: to permit determination of abnormal condition by a number of local power range monitors (LPRM) to be quickly made through precise estimation of the ratio between the true rate of change in neutron flux and true change in the neutron flux by making use of the fact that the status of the neutron distribution does not widely change with a change in the core flow rate for a short period of time. Structure: While carrying out power control according to the core flow rate, detection values from LPRM which are disposed in a three-dimensional fashion within the reactor core are indicated on an indicator. The average value of rates of change in the indicated values for a group of LPRM under substantially the same fluid dynamic condition as that for each LPRM is determined while measuring time-wise change rate in the indicated value of each of the LPRM. The average value is successively divided by the rate of change in the indicated value for each LPRM and the amplifier gain thereof to obtain the reference value. When the difference between the average value and reference value obtained in this way exceeds a prescribed value, the corresponding LPRM is determined to be defective. (Moriyama, K.)

  6. A modern diagnostic approach for automobile systems condition monitoring

    Science.gov (United States)

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

    2012-05-01

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

  7. A modern diagnostic approach for automobile systems condition monitoring

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  8. Condition monitoring of rotor blades of modern wind power systems; Ueberwachung mit Hertz. Condition Monitoring von Rotorblaettern moderner Windenergieanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Fecht, Nikolaus

    2010-06-15

    With seven wind turbines, the Austrian wind farm ''Sternwald'' is the biggest wind farm in Upper Austria. It is the only wind farm in a forest, and all turbines are therefore equipped with automatic fire fighting equipment. The mountain range on which the wind farm is located is about 1000 m high, with strong wind and much ice and snow in the winter season. For this reason, the owner decided to instal a condition monitoring system with ice detectors. The piezoelectric sensors are mounted directly on the rotor blades as measurements on the nacelle will always be incorrect. Installation on the rotor blades, on the other hand, makes high demands on the fastenings and sensors as the velocity of the blade tips may be up to 250 km per hour. (orig.)

  9. Cultures, Conditions, and Cognitive Closure: Breaking Intelligence Studies’ Dependence on Security Studies

    Directory of Open Access Journals (Sweden)

    Matthew Crosston

    2015-09-01

    Full Text Available This paper is about how the conceptualization of ‘culture’ in intelligence studies has taken on too powerful a role, one that has become too restrictive in its impact on thinking about other intelligence communities, especially non-Western ones. This restriction brings about unintentional cognitive closure that damages intelligence analysis. The argument leans heavily in many ways on the fine work of Desch and Johnston in the discipline of Security Studies, who cogently brought to light over fifteen years ago how ultra-popular cultural theories were best utilized as supplements to traditional realist approaches, but were not in fact capable of supplanting or replacing realist explanations entirely. The discipline of Intelligence Studies today needs a similar ‘intellectual intervention’ as it has almost unknowingly advanced in the post-Cold War era on the coattails of Security Studies but has largely failed to apply the same corrective measures. This effort may be best accomplished by going back to Snyder in the 1970s who warned that culture should be used as the explanation of last resort for Security Studies.

  10. Use of Local Intelligence to Reduce Energy Consumption of Wireless Sensor Nodes in Elderly Health Monitoring Systems

    Directory of Open Access Journals (Sweden)

    Thomas J. Lampoltshammer

    2014-03-01

    Full Text Available The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL, which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors’ by use of local sensors’ intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units.

  11. Use of Local Intelligence to Reduce Energy Consumption of Wireless Sensor Nodes in Elderly Health Monitoring Systems

    Science.gov (United States)

    Lampoltshammer, Thomas J.; de Freitas, Edison Pignaton; Nowotny, Thomas; Plank, Stefan; da Costa, João Paulo Carvalho Lustosa; Larsson, Tony; Heistracher, Thomas

    2014-01-01

    The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors' by use of local sensors' intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units. PMID:24618777

  12. An Ambient Intelligent Agent Model for Relapse and Recurrence Monitoring in Unipolar Depression

    NARCIS (Netherlands)

    Aziz, A.A.; Klein, M.C.A.; Treur, J.; Combi, C.; Shahar, Y.; Abu-Hanna, A.

    2009-01-01

    Mental healthcare is a prospective area for applying AI techniques. For example, a computerized system could support individuals with a history of depression in maintaining their well-being throughout their lifetime. In this paper, the design of an ambient intelligent agent to support these

  13. SIM2PeD– Intelligent monitoring system for prevention of diabetic foot

    African Journals Online (AJOL)

    Individuals receive alerts regarding care according to their location and activity directly from their smartphones. After capturing, the information is passed to the expert system (Intelligent module) that generates recommendations from the answers. The developed system presents a model of alerts as the best architecture, ...

  14. Physical working conditions as covered in European monitoring questionnaires

    Directory of Open Access Journals (Sweden)

    Tore Tynes

    2017-06-01

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

  15. Overnight non-contact continuous vital signs monitoring using an intelligent automatic beam-steering Doppler sensor at 2.4 GHz.

    Science.gov (United States)

    Batchu, S; Narasimhachar, H; Mayeda, J C; Hall, T; Lopez, J; Nguyen, T; Banister, R E; Lie, D Y C

    2017-07-01

    Doppler-based non-contact vital signs (NCVS) sensors can monitor heart rates, respiration rates, and motions of patients without physically touching them. We have developed a novel single-board Doppler-based phased-array antenna NCVS biosensor system that can perform robust overnight continuous NCVS monitoring with intelligent automatic subject tracking and optimal beam steering algorithms. Our NCVS sensor achieved overnight continuous vital signs monitoring with an impressive heart-rate monitoring accuracy of over 94% (i.e., within ±5 Beats-Per-Minute vs. a reference sensor), analyzed from over 400,000 data points collected during each overnight monitoring period of ~ 6 hours at a distance of 1.75 meters. The data suggests our intelligent phased-array NCVS sensor can be very attractive for continuous monitoring of low-acuity patients.

  16. Development of Beam Conditions Monitor for the ATLAS experiment

    CERN Document Server

    Dolenc Kittelmann, Irena; Mikuž, M

    2008-01-01

    If there is a failure in an element of the accelerator the resulting beam losses could cause damage to the inner tracking devices of the experiments. This thesis presents the work performed during the development phase of a protection system for the ATLAS experiment at the LHC. The Beam Conditions Monitor (BCM) system is a stand-alone system designed to detect early signs of beam instabilities and trigger a beam abort in case of beam failures. It consists of two detector stations positioned at z=±1.84m from the interaction point. Each station comprises four BCM detector modules installed symmetrically around the beam pipe with sensors located at r=55 mm. This structure will allow distinguishing between anomalous events (beam gas and beam halo interactions, beam instabilities) and normal events due to proton-proton interaction by measuring the time-of-flight as well as the signal pulse amplitude from detector modules on the timescale of nanoseconds. Additionally, the BCM system aims to provide a coarse instan...

  17. Condition Monitoring of Sensors in a NPP Using Optimized PCA

    Directory of Open Access Journals (Sweden)

    Wei Li

    2018-01-01

    Full Text Available An optimized principal component analysis (PCA framework is proposed to implement condition monitoring for sensors in a nuclear power plant (NPP in this paper. Compared with the common PCA method in previous research, the PCA method in this paper is optimized at different modeling procedures, including data preprocessing stage, modeling parameter selection stage, and fault detection and isolation stage. Then, the model’s performance is greatly improved through these optimizations. Finally, sensor measurements from a real NPP are used to train the optimized PCA model in order to guarantee the credibility and reliability of the simulation results. Meanwhile, artificial faults are sequentially imposed to sensor measurements to estimate the fault detection and isolation ability of the proposed PCA model. Simulation results show that the optimized PCA model is capable of detecting and isolating the sensors regardless of whether they exhibit major or small failures. Meanwhile, the quantitative evaluation results also indicate that better performance can be obtained in the optimized PCA method compared with the common PCA method.

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

    Science.gov (United States)

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

    2001-06-01

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

  19. A Novel Strain-Based Method to Estimate Tire Conditions Using Fuzzy Logic for Intelligent Tires

    Directory of Open Access Journals (Sweden)

    Daniel Garcia-Pozuelo

    2017-02-01

    Full Text Available The so-called intelligent tires are one of the most promising research fields for automotive engineers. These tires are equipped with sensors which provide information about vehicle dynamics. Up to now, the commercial intelligent tires only provide information about inflation pressure and their contribution to stability control systems is currently very limited. Nowadays one of the major problems for intelligent tire development is how to embed feasible and low cost sensors to obtain reliable information such as inflation pressure, vertical load or rolling speed. These parameters provide key information for vehicle dynamics characterization. In this paper, we propose a novel algorithm based on fuzzy logic to estimate the mentioned parameters by means of a single strain-based system. Experimental tests have been carried out in order to prove the suitability and durability of the proposed on-board strain sensor system, as well as its low cost advantages, and the accuracy of the obtained estimations by means of fuzzy logic.

  20. Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

    Science.gov (United States)

    Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

    2012-01-01

    In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

  1. Conditional standard errors of measurement for composite scores on the Wechsler Preschool and Primary Scale of Intelligence-Third Edition.

    Science.gov (United States)

    Price, Larry R; Raju, Nambury; Lurie, Anna; Wilkins, Charles; Zhu, Jianjun

    2006-02-01

    A specific recommendation of the 1999 Standards for Educational and Psychological Testing by the American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education is that test publishers report estimates of the conditional standard error of measurement (SEM). Procedures for calculating the conditional (score-level) SEM based on raw scores are well documented; however, few procedures have been developed for estimating the conditional SEM of subtest or composite scale scores resulting from a nonlinear transformation. Item response theory provided the psychometric foundation to derive the conditional standard errors of measurement and confidence intervals for composite scores on the Wechsler Preschool and Primary Scale of Intelligence-Third Edition.

  2. A Novel and Intelligent Home Monitoring System for Care Support of Elders with Cognitive Impairment.

    Science.gov (United States)

    Lazarou, Ioulietta; Karakostas, Anastasios; Stavropoulos, Thanos G; Tsompanidis, Theodoros; Meditskos, Georgios; Kompatsiaris, Ioannis; Tsolaki, Magda

    2016-10-18

    Assistive technology, in the form of a smart home environment, is employed to support people with dementia. To propose a system for continuous and objective remote monitoring of problematic daily living activity areas and design personalized interventions based on system feedback and clinical observations for improving cognitive function and health-related quality of life. The assistive technology of the proposed system, including wearable, sleep, object motion, presence, and utility usage sensors, was methodically deployed at four different home installations of people with cognitive impairment. Detection of sleep patterns, physical activity, and activities of daily living, based on the collected sensor data and analytics, was available at all times through comprehensive data visualization solutions. Combined with clinical observation, targeted psychosocial interventions were introduced to enhance the participants' quality of life and improve their cognitive functions and daily functionality. Meanwhile, participants and their caregivers were able to visualize a reduced set of information tailored to their needs. Overall, paired-sample t-test analysis of monitored qualities revealed improvement for all participants in neuropsychological assessment. Moreover, improvement was detected from the beginning to the end of the trial, in physical condition and in the domains of sleep. Detecting abnormalities via the system, for example in sleep quality, such as REM sleep, has proved to be critical to assess current status, drive interventions, and evaluate improvements in a reliable manner. It has been proved that the proposed system is suitable to support clinicians to reliably drive and evaluate clinical interventions toward quality of life improvement of people with cognitive impairment.

  3. Intelligent environmental sensing

    CERN Document Server

    Mukhopadhyay, Subhas

    2015-01-01

    Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

  4. Development of condition monitoring and diagnosis system for standby diesel generator

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Kwang Hee; Park, Jong Hyuck; Park, Jong Eun [Korea Electric Power Research Institute, Daejeon (Korea, Republic of)

    2009-05-15

    The emergency diesel generator (EDG) of the nuclear power plant is designed to supply the power to the nuclear on Station Black Out (SBO) condition. The operation reliability of onsite emergency diesel generator should be ensured by a condition monitoring system designed to monitor and analysis the condition of diesel generator. For this purpose, we have developed the online condition monitoring and diagnosis system for the wolsong unit 3 and 4 standby diesel generator including diesel engine performance. In this paper, technologies of condition monitoring and diagnosis system (SDG MDS) for the wolsong standby diesel generator are described. By using the condition monitoring module of the SDG MDS, performance monitoring function for major operating parameters of EDG reliability program required by Reg. guide 1.155 can be operated as on line monitoring system.

  5. Development of condition monitoring and diagnosis system for standby diesel generator

    International Nuclear Information System (INIS)

    Choi, Kwang Hee; Park, Jong Hyuck; Park, Jong Eun

    2009-01-01

    The emergency diesel generator (EDG) of the nuclear power plant is designed to supply the power to the nuclear on Station Black Out (SBO) condition. The operation reliability of onsite emergency diesel generator should be ensured by a condition monitoring system designed to monitor and analysis the condition of diesel generator. For this purpose, we have developed the online condition monitoring and diagnosis system for the wolsong unit 3 and 4 standby diesel generator including diesel engine performance. In this paper, technologies of condition monitoring and diagnosis system (SDG MDS) for the wolsong standby diesel generator are described. By using the condition monitoring module of the SDG MDS, performance monitoring function for major operating parameters of EDG reliability program required by Reg. guide 1.155 can be operated as on line monitoring system

  6. Intelligent poly (vinyl alcohol)-chitosan nanoparticles-mulberry extracts films capable of monitoring pH variations.

    Science.gov (United States)

    Ma, Qianyun; Liang, Tieqiang; Cao, Lele; Wang, Lijuan

    2018-03-01

    The aim of this study was to prepare a visually responsive intelligent film based on poly (vinyl alcohol) (PVA), chitosan nanoparticles (CHNPs) and mulberry extracts (MBE). CHNPs were first prepared by using ionotropic gelation method to enhance the mechanical properties of PVA based films. The morphology, particle size, zeta potential and crystallinity of CHNPs were measured. The resultant CHNPs were spherical with a diameter of 381.2nm, with high stability and a zeta potential of 49.1±1.33mV. The film with 6% CHNPs (P-C6) had the highest tensile strength (∼73.43MPa). MBE was incorporated into the P-C6 film. The film containing 20% MBE had the highest tensile strength and showed visible color responses to variations across pH 1-13. The film was tested by monitoring the spoilage of fish. The color of the film changed from red to green as the fish spoiled. Therefore, the pH responsive intelligent film developed here can be used as a package label to detect food spoilage. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Systems and method for lagrangian monitoring of flooding conditions

    KAUST Repository

    Claudel, Christian G.; Shamim, Atif; Farooqui, Muhammad Fahad

    2015-01-01

    A traffic monitoring system and method for mapping traffic speed and density while preserving privacy. The system can include fixed stations that make up a network and mobile probes that are associated with vehicles. The system and method do

  8. Structural damage monitoring of harbor caissons with interlocking condition

    Energy Technology Data Exchange (ETDEWEB)

    Huynh, Thanh Canh; Lee, So Young; Nauyen, Khac Duy; Kim, Jeong Tae [Pukyong National Univ., Busan (Korea, Republic of)

    2012-12-15

    The objective of this study is to monitor the health status of harbor caissons which have potential foundation damage. To obtain the objective, the following approaches are performed. Firstly, a structural damage monitoring(SDM) method is designed for interlocked multiple caisson structures. The SDM method utilizes the change in modal strain energy to monitor the foundation damage in a target caisson unit. Secondly, a finite element model of a caisson system which consists of three caisson units is established to verify the feasibility of the proposed method. In the finite element simulation, the caisson units are constrained each other by shear key connections. The health status of the caisson system against various levels of foundation damage is monitored by measuring relative modal displacements between the adjacent caissons.

  9. Structural damage monitoring of harbor caissons with interlocking condition

    International Nuclear Information System (INIS)

    Huynh, Thanh Canh; Lee, So Young; Nauyen, Khac Duy; Kim, Jeong Tae

    2012-01-01

    The objective of this study is to monitor the health status of harbor caissons which have potential foundation damage. To obtain the objective, the following approaches are performed. Firstly, a structural damage monitoring(SDM) method is designed for interlocked multiple caisson structures. The SDM method utilizes the change in modal strain energy to monitor the foundation damage in a target caisson unit. Secondly, a finite element model of a caisson system which consists of three caisson units is established to verify the feasibility of the proposed method. In the finite element simulation, the caisson units are constrained each other by shear key connections. The health status of the caisson system against various levels of foundation damage is monitored by measuring relative modal displacements between the adjacent caissons

  10. MONITORING OF THE FINANCIAL CONDITION OF THE COMPANY

    Directory of Open Access Journals (Sweden)

    V. E. Gladkova

    2015-01-01

    Full Text Available Topic: nowadays, many companies are on the market of high competition and are in need of new methods of needs assessment in the market in their products. In this study the methodology of calculation of the breakeven point and its projection of the dynamics of changes in the time lag will allow new businesses to forecast and take into account seasonal fl uctuations in demand for their products.Goals/objectives: the Authors of this publication have set ourselves three main goals: to improve the classical method of determining the breakeven point; to identify the dynamics and patterns of basic mathematical relations that determine the interdependence between the volume of sales (income and total costs; the possibility of applying this methodology economists in production to implement predict the future costs of production.Methodology: the Authors used the conventional scientifi c approaches and methods to analyse and identify mathematical relationships that take into account the specifi c economic and industry conditions and can be further used as template functions to predict the break-even point at a certain time lag.Results: the study authors derived a mathematical relation of volume of sales and total costs, which allows the maximization of the profi ts of Russian companies [1, 2].Discussion/application (if any: explores options graphs break-even point. Revealed that some products have a life cycle with two break-even point (at the fi rst point shows the future profi tability of the enterprise, and in the second point shows the beginning of a losing period and the need to remove product from production.Conclusions/signifi cance: Further research allowed for the monitoring of break-even point in time for which the article demonstrates the possibility of charting the break-even point in three-dimensional space that allows you to track the profi tability of the enterprise and to avoid a possible bankruptcy at a certain time lag.

  11. Through Wall Wireless Intelligent Sensor and Health Monitoring (TWall-ISHM) System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA's strategic needs include those related to flexible instrumentation capable of monitoring remote or inaccessible measurement locations within Stennis Space...

  12. PROBLEMS OF CREATION THE MONITORING SYSTEM CONCERNING THE CONDITION OF INFORMATIZATION OF THE GENERAL EDUCATION INSTITUTIONS

    Directory of Open Access Journals (Sweden)

    Valeriy Yu. Bykov

    2010-08-01

    Full Text Available In the article the problems, which appear under the creation of monitoring systems concerning the condition of informatization of general educational institutions, such as definition of monitoring object and list of parameters that will be traced during the monitoring, technologies of obtaining and actualization of data parameters, that are to be monitored, formats of data submission and ways of its processing, monitoring time period etc. are considered. In the article some decision of these problems are offered. Here is also mentioned the data of some characteristics and possibilities of the creation of monitoring systems concerning the condition of informatization of general educational institutions in Ukraine.

  13. Intelligent Mobile Sensor System for drum inspection and monitoring - Volume 2. Final report, October 1, 1993 - April 22, 1995

    International Nuclear Information System (INIS)

    1995-01-01

    The objective of the Intelligent Mobile Sensor System (IMSS) project was to develop an operational system for monitoring and inspection activities for waste storage facility operations at several DOE sites. Specifically, the product of this effort was a robotic device with enhanced intelligence and maneuverability capable of conducting routine inspection of stored waste drums. The system has an integrated sensor suite for problem-drum detection, and creates and maintains a site database both for inspection planning and for data correlation, updating, and report generation. The system is capable of departing on an assigned mission, collecting required data, recording which portions of its mission had to be aborted or modified due to environmental constraints, and reporting back when the mission is complete. Successful identification of more than 96% of drum defects has been demonstrated in a high fidelity waste storage facility mockup. Identified anomalies included rust spots, rust streaks, areas of corrosion, dents, and tilted drums. All drums were positively identified and correlated with the site database. This development effort was separated into three phases of which phase three is now complete. The first phase demonstrated an integrated system (maturity level IVa) for monitoring and inspection activities for waste storage facility operations. The second phase demonstrated a prototype system appropriate for operational use in an actual storage facility. The prototype employed an integrated design that considered operational requirements, hardware costs, maintenance, safety, and robustness. The final phase has demonstrated the commercial viability of the vehicle in operating waste storage facilities at Fernald, Ohio and the Idaho National Engineering Laboratory (INEL). This report summarizes the system upgrades performed in phase 3 and the evaluation of the IMSS Phase 3 system and vehicle

  14. Intelligent Mobile Sensor System for drum inspection and monitoring - Volume 1. Final report, October 1, 1993 - April 22, 1995

    International Nuclear Information System (INIS)

    1995-01-01

    The objective of the Intelligent Mobile Sensor System (IMSS) project is to develop an operational system for monitoring and inspection activities for waste storage facility operations at several DOE sites. Specifically, the product of this effort is a robotic device with enhanced intelligence and maneuverability capable of conducting routine inspection of stored waste drums. The device is capable of operating in the narrow free aisle space between rows of stacked drums. The system has an integrated sensor suite for problem-drum detection, and is linked to a site database both for inspection planning and for data correlation, updating, and report generation. The system is capable of departing on an assigned mission, collecting required data, recording which portions of its mission had to be aborted or modified due to environmental constraints, and reporting back when the mission is complete. Successful identification of more than 96% of drum defects has been demonstrated in a high fidelity waste storage facility mockup. Identified anomalies included rust spots, rust streaks, areas of corrosion, dents, and tilted drums. All drums were positively identified and correlated with the site database. This development effort is separated into three phases of which phase two is now complete. The first phase demonstrated an integrated system (maturity level IVa) for monitoring and inspection activities for waste storage facility operations. The second phase demonstrated a prototype system appropriate for operational use in an actual storage facility. The prototype provides an integrated design that considers operational requirements, hardware costs, maintenance, safety, and robustness. The final phase will demonstrate commercial viability using the prototype vehicle in a pilot waste operations and inspection project. This report summarizes the design and evaluation of the new IMSS Phase 2 system and vehicle

  15. Real-time personal exposure and health condition monitoring system

    Energy Technology Data Exchange (ETDEWEB)

    Saitou, Isamu; Kanda, Hiroaki; Asai, Akio; Takeishi, Naoki; Ota, Yoshito [Hitachi Aloka Medical, Ltd., Measuring Systems Engineering Dept., Tokyo (Japan); Hanawa, Nobuhiro; Ueda, Hisao; Kusunoki, Tsuyoshi; Ishitsuka, Etsuo; Kawamura, Hiroshi [Japan Atomic Energy Agency, Oarai Research and Development Center, Oarai, Ibaraki (Japan)

    2012-03-15

    JAEA (Japan Atomic Energy Agency) and HAM (Hitachi Aloka Medical, Ltd) have proposed novel monitoring system for workers of nuclear facility. In these facilities, exposure management for workers is mainly used access control and personal exposure recordings. This system is currently only for reports management but is not confirmative for surveillance when work in progress. Therefore, JAEA and HAM integrate access control and personal exposure recordings and two real-time monitoring systems which are position sensing and vital sign monitor. Furthermore change personal exposure management to real-time management, this system integration prevents workers from risk of accidents, and makes possible take appropriate action quickly. This novel system is going to start for tentative operation, using position sensing and real-time personal dosimeter with database in Apr. 2012. (author)

  16. A study on the condition monitoring for safety-related electric cables

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chul Hwan; Ahn, S. P.; Yeo, S. M.; Kang, Y. S.; Ahn, S. M.; Kim, I. S.; Kim, D. S.; Kang, J. S. [Sungkyunkwan Univ., Suwon (Korea, Republic of)

    2002-03-15

    In this report, we have studied compositions and characteristics of various types of insulation material for cables in Nuclear Power Plant. We arrange relationship with condition monitoring methods. Also, we propose new condition monitoring method using third harmonic frequency. We test the proposed method with CV cables. We also describe about feature of condition monitoring such as application, theory, characteristic, thereby other engineer can confirm to advantage and disadvantage for each method, and possibly choice adequate condition monitoring method for various types of cables.

  17. Systems and method for lagrangian monitoring of flooding conditions

    KAUST Repository

    Claudel, Christian G.

    2015-12-17

    A traffic monitoring system and method for mapping traffic speed and density while preserving privacy. The system can include fixed stations that make up a network and mobile probes that are associated with vehicles. The system and method do not gather, store, or transmit any unique or identifying information, and thereby preserves the privacy of members of traffic. The system and method provide real-time traffic density and speed mapping. The system and method can further be integrated with a complementary flood monitoring system and method.

  18. An artificial intelligence approach to onboard fault monitoring and diagnosis for aircraft applications

    Science.gov (United States)

    Schutte, P. C.; Abbott, K. H.

    1986-01-01

    Real-time onboard fault monitoring and diagnosis for aircraft applications, whether performed by the human pilot or by automation, presents many difficult problems. Quick response to failures may be critical, the pilot often must compensate for the failure while diagnosing it, his information about the state of the aircraft is often incomplete, and the behavior of the aircraft changes as the effect of the failure propagates through the system. A research effort was initiated to identify guidelines for automation of onboard fault monitoring and diagnosis and associated crew interfaces. The effort began by determining the flight crew's information requirements for fault monitoring and diagnosis and the various reasoning strategies they use. Based on this information, a conceptual architecture was developed for the fault monitoring and diagnosis process. This architecture represents an approach and a framework which, once incorporated with the necessary detail and knowledge, can be a fully operational fault monitoring and diagnosis system, as well as providing the basis for comparison of this approach to other fault monitoring and diagnosis concepts. The architecture encompasses all aspects of the aircraft's operation, including navigation, guidance and controls, and subsystem status. The portion of the architecture that encompasses subsystem monitoring and diagnosis was implemented for an aircraft turbofan engine to explore and demonstrate the AI concepts involved. This paper describes the architecture and the implementation for the engine subsystem.

  19. Intelligent software solution for reliable high efficiency/low false alarm border monitoring

    International Nuclear Information System (INIS)

    Rieck, W.; Iwatschenko, M.

    2001-01-01

    Full text: Radioactivity Monitoring at border stations requires detection systems that are reliably operating under special conditions such as: different types and shapes of vehicles; different velocities; stop and go traffic. ESM has developed a solution that achieves under all such conditions the lowest possible detection limit and avoids false alarms generated by naturally occurring radioactive material (NORM). NBR (Natural Background Reduction) data evaluation - One of the main reasons for the success of the ESM gate monitors is the unique and proprietary NBR-technology of instantaneous discrimination of artificial and natural gamma radiation using large area plastic scintillators. Thus the FHT 1388 gate monitors show 2 unique features: Possible setting of different alarm levels for NORM and artificial gamma sources; Self adjusting compensation of the background shielding of the truck in respect to the detection of artificial sources. Both properties are a preposition for the highly sensitive detection of artificial gamma sources. While at scrap yards and steel mills usually all radioactivity (including NORM) must be detected, the main object of interest in respect to the measuring task at border stations, airports or harbours is clearly the detection of even very small signals of artificial radioactivity. The reliable rejection of the influence of natural radioactivity is of special importance in the case of detection of illicit trafficking, since construction material, fertilisers or soil often lead to much higher detector signals than the alarming levels for dangerous sources of interest. Beside the varying content of natural radioactivity in the load of a truck, different loads and trucks show different influence on the reduction of the ambient radiation due to the passing vehicle. Thus software approaches assuming a specific reduction of the background count rate (regarding relative magnitude and shape) must fail when trucks of different shape and load

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

    Science.gov (United States)

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

  1. Robot dispatching Scenario for Accident Condition Monitoring of NPP

    International Nuclear Information System (INIS)

    Kim, Jongseog

    2013-01-01

    In March of 2011, unanticipated big size of tsunami attacks Fukushima NPP, this accident results in explosion of containment building. Tokyo electric power of Japan couldn't dispatch a robot for monitoring of containment inside. USA Packbot robot used for desert war in Iraq was supplied to Fukushima NPP for monitoring of high radiation area. Packbot also couldn't reach deep inside of Fukushima NPP due to short length of power cable. Japanese robot 'Queens' also failed to complete a mission due to communication problem between robot and operator. I think major reason of these robot failures is absence of robot dispatching scenario. If there was a scenario and a rehearsal for monitoring during or after accident, these unanticipated obstacles could be overcome. Robot dispatching scenario studied for accident of nuclear power plant was described herein. Study on scenario of robot dispatching is performed. Flying robot is regarded as good choice for accident monitoring. Walking robot with arm equipped is good for emergency valve close. Short time work and shift work by several robots can be a solution for high radiation area. Thin and soft cable with rolling reel can be a good solution for long time work and good communication

  2. Monitoring operational conditions of vehicle tyre pressure levels and ...

    African Journals Online (AJOL)

    Compliance with vehicle tyre inflation pressure and tread depth standard specifications and legal requirements were monitored by survey study in Kumasi Metropolis, Ghana. The survey covered 400 vehicles, comprising cars (28 %), medium buses (25 %), large capacity buses (15 %) and trucks (32 %). There were wide ...

  3. Internet-based intelligent information processing systems

    CERN Document Server

    Tonfoni, G; Ichalkaranje, N S

    2003-01-01

    The Internet/WWW has made it possible to easily access quantities of information never available before. However, both the amount of information and the variation in quality pose obstacles to the efficient use of the medium. Artificial intelligence techniques can be useful tools in this context. Intelligent systems can be applied to searching the Internet and data-mining, interpreting Internet-derived material, the human-Web interface, remote condition monitoring and many other areas. This volume presents the latest research on the interaction between intelligent systems (neural networks, adap

  4. Monitoring parameters of technical condition and safety of aircraft using control charts

    Directory of Open Access Journals (Sweden)

    В.І. Чепіженко

    2007-03-01

    Full Text Available  The opportunity of control cards use for monitoring of a technical condition parameters and reliability of aviation techniques is considered at its operation on a technical condition.

  5. Study on sampling conditions for the monitoring of waste air

    International Nuclear Information System (INIS)

    Moeller, T.J.; Buetefisch, K.A.

    1998-01-01

    The technical codes for radiological monitoring of the waste air released from a radwaste repository demand that sampling for determination of aerosol-borne radioactivity is to be made with a screener equipped with a suitable number of measuring probes extending over the entire cross-sectional surface of the vent. Another requirement is to ensure that the waste air stream passing through the measuring channel is representative, containing the typical, operation-induced distribution of aerosols across the surface to be scanned. The study reported was intended to determine in a scaled-down model (1:10) of a repository ventilating duct the typical spatial distribution of aerosols (3D particulate density) in order to establish information on the type of typical distributions of aerosols, to be used for optimisation of the measuring site and monitoring instruments. (orig./CB) [de

  6. Condition Monitoring of a Process Filter Applying Wireless Vibration Analysis

    Directory of Open Access Journals (Sweden)

    Pekka KOSKELA

    2011-05-01

    Full Text Available This paper presents a novel wireless vibration-based method for monitoring the degree of feed filter clogging. In process industry, these filters are applied to prevent impurities entering the process. During operation, the filters gradually become clogged, decreasing the feed flow and, in the worst case, preventing it. The cleaning of the filter should therefore be carried out predictively in order to avoid equipment damage and unnecessary process downtime. The degree of clogging is estimated by first calculating the time domain indices from low frequency accelerometer samples and then taking the median of the processed values. Nine different statistical quantities are compared based on the estimation accuracy and criteria for operating in resource-constrained environments with particular focus on energy efficiency. The initial results show that the method is able to detect the degree of clogging, and the approach may be applicable to filter clogging monitoring.

  7. Upgraded Fast Beam Conditions Monitor for CMS online luminosity measurement

    CERN Document Server

    Leonard, Jessica Lynn

    2014-01-01

    The CMS beam and radiation monitoring subsystem BCM1F during LHC Run I consisted of 8 individual diamond sensors situated around the beam pipe within the tracker detector volume, for the purpose of fast monitoring of beam background and collision products. Effort is ongoing to develop the use of BCM1F as an online bunch-by-bunch luminosity monitor. BCM1F will be running whenever there is beam in LHC, and its data acquisition is independent from the data acquisition of the CMS detector, hence it delivers luminosity even when CMS is not taking data. To prepare for the expected increase in the LHC luminosity and the change from 50 ns to 25 ns bunch separation, several changes to the system are required, including a higher number of sensors and upgraded electronics. In particular, a new real-time digitizer with large memory was developed and is being integrated into a multi-subsystem framework for luminosity measurement. Current results from Run II preparation will be shown, including results from the January 201...

  8. Recent trends in the condition monitoring of transformers theory, implementation and analysis

    CERN Document Server

    Chakravorti, Sivaji; Chatterjee, Biswendu

    2013-01-01

    Recent Trends in the Condition Monitoring of Transformers reflects the current interest in replacing traditional techniques used in power transformer condition monitoring with non-invasive measures such as polarization/depolarization current measurement, recovery voltage measurement, frequency domain spectroscopy and frequency response analysis. The book stresses the importance of scrutinizing the condition of transformer insulation which may fail under present day conditions of intensive use with the resulting degradation of dielectric properties causing functional failure of the transformer.

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

    Science.gov (United States)

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

    2005-07-01

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

  10. Gamma-ray detectors for intelligent, hand-held radiation monitors

    International Nuclear Information System (INIS)

    Fehlau, P.E.

    1983-01-01

    Small radiation detectors based on HgI 2 , bismuth germanate (BGO), plastic, or NaI(Tl) detector materials were evaluated for use in small, lighweight radiation monitors. The two denser materials, HgI 2 and BGO, had poor resolution at low-energy and thus performed less well than NaI(Tl) in detecting low-energy gamma rays from bare, enriched uranium. The plastic scintillator, a Compton recoil detector, also performed less well at low gamma-ray energy. Two small NaI(Tl) detectors were suitable for detecting bare uranium and sheilded plutonium. One became part of a new lightweight hand-held monitor and the other found uses as a pole-mounted detector for monitoring hard-to-reach locations

  11. New intelligent monitor for tritium in air measurements - an experimental model

    International Nuclear Information System (INIS)

    Purghel, Lidia; Calin, Marian Romeo; Bartos, Daniel; Serbina, Leonardo; Lupu, Adrian; Lupu, Dan

    2003-01-01

    The statistical discrimination method is an original one, developed and patented in IFIN - HH Bucharest, Magurele, Romania. In frame of the National Research and Development Program MENER, the research for manufacturing and certifying a portable monitor was financed. The method is based on the dependence of the resulting k - factor on the relative values of the ionization current components in a mixed radiation field. The instrumentation consists of a gas flowing ionization chamber (integrated in a sampling circuit), a preamplifier, a data acquisition system and a microcomputer. A special designed software allows for running the monitor on tritium gas (vapors of tritiated water) and on the associated radiation field (i.e. natural radiation background or gamma-ray field). Some performances of the monitor concerning the tritium in relative strong gamma-ray fields are tested and the results reported. (authors)

  12. Monitoring fate and behaviour of Nanoceria under relevant environmental conditions

    CSIR Research Space (South Africa)

    Tancu, Y

    2014-11-01

    Full Text Available ). The results revealed significant tendency of nCeO¬2 to undergo aggregation, agglomeration and certain degree of deagglomeration processes under different environmental conditions. Moreover, the findings suggested that both electrostatic and steric interactions...

  13. Intelligent mobile sensor system for drum inspection and monitoring: Topical report, October 1, 1993--April 22, 1995

    International Nuclear Information System (INIS)

    1997-01-01

    The objective of the Intelligent Mobile Sensor System (IMSS) project is to develop an operational system for monitoring and inspection activities for waste storage facility operations at several DOE sites. Specifically, the product of this effort is a robotic device with enhanced intelligence and maneuverability capable of conducting routine inspection of stored waste drums. The system has an integrated sensor suite for problem-drum detection, and is linked to a site database both for inspection planning and for data correlation, updating, and report generation. The system is capable of departing on an assigned mission, collecting required data, recording which portions of its mission had to be aborted or modified due to environmental constraints, and reporting back when the mission is complete. Successful identification of more than 96% of drum defects has been demonstrated in a high fidelity waste storage facility mockup. Identified anomalies included rust spots, rust streaks, areas of corrosion, dents, and tilted drums. All drums were positively identified and correlated with the site database. This development effort is separated into three phases of which phase two is now complete. The second phase demonstrated a prototype system appropriate for operational use in an actual storage facility. The prototype provides an integrated design that considers operational requirements, hardware costs, maintenance, safety, and robustness. The final phase will demonstrate commercial viability using the prototype vehicle in a pilot waste operations and inspection project. This report summarizes the design and evaluation of the new IMSS Phase 2 system and vehicle. Several parts of the IMSS Phase 1 Topical (Final) Report, which describes the requirements, design guidelines, and detailed design of the Phase 1 IMSS vehicle, are incorporated here, with modifications to reflect the changes in the design and the new elements added during the Phase 2 work

  14. An artificial intelligence-based structural health monitoring system for aging aircraft

    Science.gov (United States)

    Grady, Joseph E.; Tang, Stanley S.; Chen, K. L.

    1993-01-01

    To reduce operating expenses, airlines are now using the existing fleets of commercial aircraft well beyond their originally anticipated service lives. The repair and maintenance of these 'aging aircraft' has therefore become a critical safety issue, both to the airlines and the Federal Aviation Administration. This paper presents the results of an innovative research program to develop a structural monitoring system that will be used to evaluate the integrity of in-service aerospace structural components. Currently in the final phase of its development, this monitoring system will indicate when repair or maintenance of a damaged structural component is necessary.

  15. Analysis of acoustic data from the PFR SGU condition monitor

    International Nuclear Information System (INIS)

    Rowley, R.; Airey, J.

    1990-01-01

    This paper gives an outline description of an acoustic monitoring system which has been installed on the SGU of the Prototype Fast Reactor (PFR) at Dounreay with the objective of giving early warning of any change in noise output which could be related to potentially damaging vibrations within the units. Data obtained from this PFR monitoring system is playing an important part in the development of acoustic instrumentation for leak detection although this had not been the primary objective of this particular installation. The PFR has three secondary circuits each containing an evaporator, a superheater and a reheater giving a total of nine SGUs. Although the design of the units is different from that intended for EFR, the measurements provide a valuable source of information on the character and amplitude of acoustic background noise in operational steam generator units. The vibration monitoring system uses the waveguides originally installed during reactor commissioning for leak detection studies. Twelve acoustic waveguides are fitted to the shell of each of the units. The superheaters and reheaters have three waveguides at each of four axial levels, while the evaporators have four waveguides at each of three axial levels. In addition the evaporators have a small number of waveguides attached to the top flange of the unit. Each waveguide is fitted with an accelerometer to record the acoustic signal from the SGU. Tape recordings of the acoustic noise from each unit are made on a regular basis and the tapes analysed on an automated analysis system which has been developed to extract and store in a database about 20 characteristic features from the data. The paper gives examples of the background noise from the SGU. The data demonstrates the use of location techniques to identify prominent acoustic source. 8 figs

  16. Fundamentals for remote condition monitoring of offshore wind turbines

    DEFF Research Database (Denmark)

    McGugan, Malcolm; Larsen, Gunner Chr.; Sørensen, Bent F.

    In the future, large wind turbines will be placed offshore in considerable numbers. Since access will be difficult and costly, it is preferable to use monitoring systems to reduce the reliance on manual inspection. The motivation for the effort reported here is to create the fundamental basis...... of the wind turbine blades that can integrate with existing SCADA tools to improve management of large offshore wind farms, and optimise the manual inspection/maintenance effort. Various sensor types, which have previously been identified as technically (and economically) capable of detecting the early...

  17. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  18. Condition Monitoring for DC-link Capacitors Based on Artificial Neural Network Algorithm

    DEFF Research Database (Denmark)

    Soliman, Hammam Abdelaal Hammam; Wang, Huai; Gadalla, Brwene Salah Abdelkarim

    2015-01-01

    hardware will reduce the cost, and therefore could be more promising for industry applications. A condition monitoring method based on Artificial Neural Network (ANN) algorithm is therefore proposed in this paper. The implementation of the ANN to the DC-link capacitor condition monitoring in a back......In power electronic systems, capacitor is one of the reliability critical components . Recently, the condition monitoring of capacitors to estimate their health status have been attracted by the academic research. Industry applications require more reliable power electronics products...... with preventive maintenance. However, the existing capacitor condition monitoring methods suffer from either increased hardware cost or low estimation accuracy, being the challenges to be adopted in industry applications. New development in condition monitoring technology with software solutions without extra...

  19. On the use of temperature for online condition monitoring of geared systems - A review

    Science.gov (United States)

    Touret, T.; Changenet, C.; Ville, F.; Lalmi, M.; Becquerelle, S.

    2018-02-01

    Gear unit condition monitoring is a key factor for mechanical system reliability management. When they are subjected to failure, gears and bearings may generate excessive vibration, debris and heat. Vibratory, acoustic or debris analyses are proven approaches to perform condition monitoring. An alternative to those methods is to use temperature as a condition indicator to detect gearbox failure. The review focuses on condition monitoring studies which use this thermal approach. According to the failure type and the measurement method, it exists a distinction whether it is contact (e.g. thermocouple) or non-contact temperature sensor (e.g. thermography). Capabilities and limitations of this approach are discussed. It is shown that the use of temperature for condition monitoring has a clear potential as an alternative to vibratory or acoustic health monitoring.

  20. Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards.

    Science.gov (United States)

    da Costa, Cristiano André; Pasluosta, Cristian F; Eskofier, Björn; da Silva, Denise Bandeira; da Rosa Righi, Rodrigo

    2018-06-02

    Large amounts of patient data are routinely manually collected in hospitals by using standalone medical devices, including vital signs. Such data is sometimes stored in spreadsheets, not forming part of patients' electronic health records, and is therefore difficult for caregivers to combine and analyze. One possible solution to overcome these limitations is the interconnection of medical devices via the Internet using a distributed platform, namely the Internet of Things. This approach allows data from different sources to be combined in order to better diagnose patient health status and identify possible anticipatory actions. This work introduces the concept of the Internet of Health Things (IoHT), focusing on surveying the different approaches that could be applied to gather and combine data on vital signs in hospitals. Common heuristic approaches are considered, such as weighted early warning scoring systems, and the possibility of employing intelligent algorithms is analyzed. As a result, this article proposes possible directions for combining patient data in hospital wards to improve efficiency, allow the optimization of resources, and minimize patient health deterioration. It is concluded that a patient-centered approach is critical, and that the IoHT paradigm will continue to provide more optimal solutions for patient management in hospital wards. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Monitoring stanja kroz testove analize ulja / Condition monitoring through oil analysis tests

    Directory of Open Access Journals (Sweden)

    Sreten R. Perić

    2010-10-01

    : neutralization number (TAN-total acid number, total base number (TBN, oxidation stabillity, chemical and thermal stabillity, corrodibillity, ash content and carbon residue, water content, compatibility, toxicity, etc. Diagnostics of the tribomechanical system of an internal combustion engine The diagnostics is based on the prediction (recognition of damage and/or failure through characteristic diagnostic parameters. This allows prevention of delays and increases reliability, cost-effectiveness, and usage life. The diagnostics of the tribomechanical system can provide verification of the system condition, working capacity and functionality, and can point out the place, form and cause of a failure. The diagnostics is carried out through the detection of symptoms, determining the value of the characteristic parameters and their comparison with the limit values. If the engine assemblies are considered from the aspect of tribomechanical systems (e. g. piston-piston ring-cylinder, cam-valve lifter, bearing journal bearing defined by tribological processes, it can be shown that the determination of the content of wear products, content of contaminants, state of lubricants and lubrication conditions have a significant influence on the implementation of maintenance of these systems. We should emphasize the importance of monitoring oil for lubrication of tribomechanical engine assemblies, which provides identification of potential causes and phenomena leading to damage and failure in the early stages of the functioning of the system. Prediction, i.e. detection of potential and/or current damage and failures in the system, checking the functionality of oil and determination of usage life are the main factors of the implementation of oil monitoring. Since mobile components of tribomechanical system engines are necessarily exposed to wear and contaminants and wear products deposit in the lubrication oil, it is necessary to monitor changes in fluid properties during exploitation, because the

  2. An intelligent stand-alone ultrasonic device for monitoring local structural damage: implementation and preliminary experiments

    International Nuclear Information System (INIS)

    Pertsch, Alexander; Kim, Jin-Yeon; Wang, Yang; Jacobs, Laurence J

    2011-01-01

    Continuous structural health monitoring has the potential to significantly improve the safety management of aged, in-service civil structures. In particular, monitoring of local damage growth at hot-spot areas can help to prevent disastrous structural failures. Although ultrasonic nondestructive evaluation (NDE) has proved to be effective in monitoring local damage growth, conventional equipment and devices are usually bulky and only suitable for scheduled human inspections. The objective of this research is to harness the latest developments in embedded hardware and wireless communication for developing a stand-alone, compact ultrasonic device. The device is directed at the continuous structural health monitoring of civil structures. Relying on battery power, the device possesses the functionalities of high-speed actuation, sensing, signal processing, and wireless communication. Integrated with contact ultrasonic transducers, the device can generate 1 MHz Rayleigh surface waves in a steel specimen and measure response waves. An envelope detection algorithm based on the Hilbert transform is presented for efficiently determining the peak values of the response signals, from which small surface cracks are successfully identified

  3. Intelligent packaging for monitoring food quality: a case study on fresh fish

    NARCIS (Netherlands)

    Heising, J.K.

    2014-01-01

    Background

    Foods are prone to quality degradation in the whole supply chain, but the possibilities for monitoring the quality of foods inside the package are limited. When sensors of quality indicators are included into the package of a food, the package can become an

  4. Significance of Operating Environment in Condition Monitoring of Large Civil Structures

    Directory of Open Access Journals (Sweden)

    Sreenivas Alampalli

    1999-01-01

    Full Text Available Success of remote long-term condition monitoring of large civil structures and developing calibrated analytical models for damage detection, depend significantly on establishing accurate baseline signatures and their sensitivity. Most studies reported in the literature concentrated on the effect of structural damage on modal parameters without emphasis on reliability of modal parameters. Thus, a field bridge structure was studied for the significance of operating conditions in relation to baseline signatures. Results indicate that in practice, civil structures should be monitored for at least one full cycle of in-service environmental changes before establishing baselines for condition monitoring or calibrating finite-element models. Boundary conditions deserve special attention.

  5. Condition Monitoring and Fault Diagnosis for an Antifalling Safety Device

    Directory of Open Access Journals (Sweden)

    Guangxiang Yang

    2015-01-01

    Full Text Available There is a constant need for the safe operation and reliability of antifalling safety device (AFSD of an elevator. This paper reports an experimental study on rotation speed and catching torque monitoring and fault diagnosis of an antifalling safety device in a construction elevator. Denoising the signal using wavelet transform is presented in this paper. Based on the denoising effects for several types of wavelets, the sym8 wavelet basis, which introduces the high order approximation and an adaptive threshold, is employed for denoising the signal. The experimental result shows a maximum data error reduction of 7.5% is obtained and SNRs (signal-to-noise ratio of rotation speed and catching torque are improved for 3.9% and 6.4%, respectively.

  6. A global condition monitoring system for wind turbines

    DEFF Research Database (Denmark)

    Schlechtingen, Meik

    the output signal is entirely reconstructed by using other correlated signals. Benefits in fault visibility and lead-time to failure estimatesare observed. A very important signal to monitor contained in the SCADA data is the wind turbine power output. The power output has a direct influence on the revenue...... proposed method to separate discrete (e.g. originating from gears) from random (e.g. originating from bearings) signal components is applied and validated in this research. This state of the art method named“signal pre-whitening” enhances the fault pattern visibility in the envelope spectra in a very...... developed leading to fully automated fault diagnosis. For this purpose a frequency content identifier is developed extracting the frequency content from the envelope spectrum building the basis for automated diagnosis. A modified parameter, namely the Kurtosis of the Amplitude Envelope Spectrum (KEAS...

  7. Time domain spectroscopy to monitor the condition of cable insulation

    International Nuclear Information System (INIS)

    Mopsik, F.I.; Martzloff, F.D.

    1989-01-01

    The use of Time Domain Spectroscopy, the measurement of dielectric constant and loss using time-domain response, the monitoring the aging of reactor cable insulation is examined. The method is presented, showing its sensitivity, accuracy and wide frequency range. The method's ability to acquire a great deal of information in a short time and its superiority to conventional single frequency data is shown. Different cable samples are examined before and after exposure to radiation and changes with exposure are clearly seen to occur. Also it is shown that a wide range of behavior can be found in different insulation systems. The requirements for performing valid measurements is presented. The need for controlled samples and correlation with other criteria for aging is discussed. 14 refs., 9 figs

  8. Physical working conditions as covered in European monitoring questionnaires

    NARCIS (Netherlands)

    Tynes, T.; Aagestad, C.; Vester Thorsen, S.; Andersen, L.L.; Perkio-Makela, M.; García, F.J.P.; Blanco, L..; Vermeylen, G.; Parent-Thirion, A.; Hooftman, W.; Houtman, I.L.D.; Liebers, F.; Burr, H.; Formazin, M.

    2017-01-01

    Background. The prevalence of workers with demanding physical working conditions in the European work force remains high, and occupational physical exposures are considered important risk factors for musculoskeletal disorders (MSD), a major burden for both workers and society. Exposures to physical

  9. Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design.

    Science.gov (United States)

    Hall, Travis; Lie, Donald Y C; Nguyen, Tam Q; Mayeda, Jill C; Lie, Paul E; Lopez, Jerry; Banister, Ron E

    2017-11-15

    It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients' long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient's vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF) non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the subject is sleeping

  10. The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

    CERN Document Server

    Kazarov, A; The ATLAS collaboration; Magnoni, L

    2011-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for filtering and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The huge flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This require strong competence and experience in understanding and discovering problems and root causes, and often the meaningful in...

  11. The AAL project: Automated monitoring and intelligent AnaLysis for the ATLAS data taking infrastructure

    CERN Document Server

    Magnoni, L; The ATLAS collaboration; Kazarov, A

    2011-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for filtering and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The huge flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This require strong competence and experience in understanding and discovering problems and root causes, and often the meaningful in...

  12. An Intelligent Sensor System for Monitoring Fatigue Damage in Welded Steel Components

    Science.gov (United States)

    Fernandes, B.; Gaydecki, P.; Burdekin, F. Michael

    2005-04-01

    A system for monitoring fatigue damage in steel components is described. The sensor, a thin steel sheet with a pre-crack in it, is attached to the component. Its crack length increases by fatigue in service and is recorded using a microcontroller. Measurement is accomplished using conductive tracks in a circuit whose output voltage changes when the crack propagates past a track. Data stored in memory can be remotely downloaded using Bluetooth™ technology to a PC.

  13. An Intelligent Sensor System for Monitoring Fatigue Damage in Welded Steel Components

    International Nuclear Information System (INIS)

    Fernandes, B.; Gaydecki, P.; Burdekin, F. Michael

    2005-01-01

    A system for monitoring fatigue damage in steel components is described. The sensor, a thin steel sheet with a pre-crack in it, is attached to the component. Its crack length increases by fatigue in service and is recorded using a microcontroller. Measurement is accomplished using conductive tracks in a circuit whose output voltage changes when the crack propagates past a track. Data stored in memory can be remotely downloaded using Bluetooth TM technology to a PC

  14. Non-stationary Condition Monitoring of large diesel engines with the AEWATT toolbox

    DEFF Research Database (Denmark)

    Pontoppidan, Niels Henrik; Larsen, Jan; Sigurdsson, Sigurdur

    2005-01-01

    We are developing a specialized toolbox for non-stationary condition monitoring of large 2-stroke diesel engines based on acoustic emission measurements. The main contribution of this toolbox has so far been the utilization of adaptive linear models such as Principal and Independent Component Ana......, the inversion of those angular timing changes called “event alignment”, has allowed for condition monitoring across operation load settings, successfully enabling a single model to be used with realistic data under varying operational conditions-...

  15. Condition monitoring approach for permanent magnet synchronous motor drives based on the INFORM method

    OpenAIRE

    Arellano-Padilla, J.; Sumner, M.; Gerada, C.

    2016-01-01

    This paper proposes a monitoring scheme based on saliency tracking to assess the health condition of PMSM drives operating under non stationary conditions. The evaluated scheme is based on the INFORM methodology, which is associated to the accurate sensorless control of PM drives without zero speed limitation. The result is a monitoring scheme that is able to detect faults that would be very difficult to evaluate under nonstationary conditions. A relevant aspect of the proposed scheme is that...

  16. Modeling air concentration over macro roughness conditions by Artificial Intelligence techniques

    Science.gov (United States)

    Roshni, T.; Pagliara, S.

    2018-05-01

    Aeration is improved in rivers by the turbulence created in the flow over macro and intermediate roughness conditions. Macro and intermediate roughness flow conditions are generated by flows over block ramps or rock chutes. The measurements are taken in uniform flow region. Efficacy of soft computing methods in modeling hydraulic parameters are not common so far. In this study, modeling efficiencies of MPMR model and FFNN model are found for estimating the air concentration over block ramps under macro roughness conditions. The experimental data are used for training and testing phases. Potential capability of MPMR and FFNN model in estimating air concentration are proved through this study.

  17. Adaptive Artificial intelligence based fuzzy logic MPPTcontrol for stande-alone photovoltaic system under different atmospheric conditions

    Directory of Open Access Journals (Sweden)

    Zaghba Layachi

    2015-08-01

    Full Text Available there is an increased need for analysing the effect of atmospheric variables on photovoltaic (PV production and performance. The outputs from the different PV cells in different atmospheric conditions, such as irradiation and temperature , differ from each other evidencing knowledge deficiency in PV systems [14]. Maximum power point tracking (MPPT methods are used to maximize the PV array output power by tracking continuously the maximum power point (MPP. Among all MPPT methods existing in the literature, perturb and observe (P&O is the most commonly used for its simplicity and ease of implementation; however, it presents drawbacks such as slow response speed, oscillation around the MPP in steady state, and even tracking in wrong way under rapidly changing atmospheric conditions. In order to allow a functioning around the optimal point Mopt, we have inserted a DC-DC converter (Buck–Boost for a better matching between the PV and the load. This paper, we study the Maximum power point tracking using adaptive Intelligent fuzzy logic and conventional (P&O control for stande-alone photovoltaic Array system .In particular, the performances of the controllers are analyzed under variation weather conditions with are constant temperature and variable irradiation. The proposed system is simulated by using MATLAB-SIMULINK. According to the results, fuzzy logic controller has shown better performance during the optimization.

  18. Compact polarimetric synthetic aperture radar for monitoring soil moisture condition

    Science.gov (United States)

    Merzouki, A.; McNairn, H.; Powers, J.; Friesen, M.

    2017-12-01

    Coarse resolution soil moisture maps are currently operationally delivered by ESA's SMOS and NASA's SMAP passive microwaves sensors. Despite this evolution, operational soil moisture monitoring at the field scale remains challenging. A number of factors contribute to this challenge including the complexity of the retrieval that requires advanced SAR systems with enhanced temporal revisit capabilities. Since the launch of RADARSAT-2 in 2007, Agriculture and Agri-Food Canada (AAFC) has been evaluating the accuracy of these data for estimating surface soil moisture. Thus, a hybrid (multi-angle/multi-polarization) retrieval approach was found well suited for the planned RADARSAT Constellation Mission (RCM) considering the more frequent relook expected with the three satellite configuration. The purpose of this study is to evaluate the capability of C-band CP data to estimate soil moisture over agricultural fields, in anticipation of the launch of RCM. In this research we introduce a new CP approach based on the IEM and simulated RCM CP mode intensities from RADARSAT-2 images acquired at different dates. The accuracy of soil moisture retrieval from the proposed multi-polarization and hybrid methods will be contrasted with that from a more conventional quad-pol approach, and validated against in situ measurements by pooling data collected over AAFC test sites in Ontario, Manitoba and Saskatchewan, Canada.

  19. Real-time well condition monitoring in extended reach wells

    Energy Technology Data Exchange (ETDEWEB)

    Kucs, R.; Spoerker, H.F. [OMV Austria Exploration and Production GmbH, Gaenserndorf (Austria); Thonhauser, G. [Montanuniversitaet Leoben (Austria)

    2008-10-23

    Ever rising daily operating cost for offshore operations make the risk of running into drilling problems due to torque and drag developments in extended reach applications a growing concern. One option to reduce cost related to torque and drag problems can be to monitor torque and drag trends in real time without additional workload on the platform drilling team. To evaluate observed torque or drag trends it is necessary to automatically recognize operations and to have a 'standard value' to compare the measurements to. The presented systematic approach features both options - fully automated operations recognition and real time analysis. Trends can be discussed between rig- and shore-based teams, and decisions can be based on up to date information. Since the system is focused on visualization of real-time torque and drag trends, instead of highly complex and repeated simulations, calculation time is reduced by comparing the real-time rig data against predictions imported from a commercial drilling engineering application. The system allows reacting to emerging stuck pipe situations or developing cuttings beds long before the situations become severe enough to result in substantial lost time. The ability to compare real-time data with historical data from the same or other wells makes the system a valuable tool in supporting a learning organization. The system has been developed in a joint research initiative for field application on the development of an offshore heavy oil field in New Zealand. (orig.)

  20. Crown condition assessment at the CONECOFOR Permanent Monitoring Plots

    Directory of Open Access Journals (Sweden)

    Renzo NIBBI

    2002-09-01

    Full Text Available A detailed crown condition assessment is currently being carried out at the CONECOFOR (CONtrollo ECOsistemi FORestali, Control of Forest Ecosystems plots. The assessment began in 1996, and during the first two years (1996 and 1997 an assessment form based on previous regional experience was used; in 1998 the new official EU form was adopted. The resulting loss of comparability means that only a few indices can be used in the temporal series 1996-1999. Much effort was devoted to Quality Assurance (QA procedures. The QA program is structured as follows: (i specific field manuals have been adopted and are continuously updated; (ii a national training and intercalibration course (NT&IC is undertaken yearly before beginning the assessment campaign;( iii field checks are carried out yearly on a large number of plots. The results of the QA program have shown that for several indices the quality objectives were not reached, but the quality of the data is improving with time. To express the change in crown conditions in each area, a complex index (CCI = Crown Condition Index was adopted. This index is the result of the sum of the relativized values of all the common indices used during the four years. The following parameters were used: transparency, ramification type, leaf colour alteration extension, leaf damage extension, alteration of leaf distension extension. The range within which the CCI fluctuates was evaluated taking into account all the observations carried out at a given plot throughout the years. The number of cases over a given threshold (outliers was calculated for each year. The threshold for outliers was calculated as the median value plus 2 times the range of the interquartile value. All individual cases exceeding this value are considered outliers. The results are presented for all the areas in which the data set is complete for the four years. The yearly fluctuations are discussed and related to possible causes.

  1. The "Haptic Finger"- a new device for monitoring skin condition.

    Science.gov (United States)

    Tanaka, Mami; Lévêque, Jean Luc; Tagami, Hachiro; Kikuchi, Katsuko; Chonan, Seifi

    2003-05-01

    Touching the skin is of great importance for the Clinician for assessing roughness, softness, firmness, etc. This type of clinical assessment is very subjective and therefore non-reproducible from one Clinician to another one or even from time to time for the same Clinician. In order to objectively monitor skin texture, we developed a new sensor, placed directly on the Clinician's finger, which generate some electric signal when slid over the skin surface. The base of this Haptic Finger sensor is a thin stainless steel plate on which sponge rubber, PVDF foil, acetate film and gauze are layered. The signal generated by the sensor was filtered and digitally stored before processing. In a first in vitro experiment, the sensor was moved over different skin models (sponge rubber covered by silicon rubber) of varying hardness and roughness. These experiments allowed the definition of two parameters characterizing textures. The first parameter is variance of the signal processed using wavelet analysis, representing an index of roughness. The second parameter is dispersion of the power spectrum density in the frequency domain, corresponding to hardness. To validate these parameters, the Haptic Finger was used to scan skin surfaces of 30 people, 14 of whom displayed a skin disorder: xerosis (n = 5), atopic dermatitis (n = 7), and psoriasis (n = 2). The results obtained by means of the sensor were compared with subjective, clinical evaluations by a Clinician who scored both roughness and hardness of the skin. Good agreement was observed between clinical assessment of the skin and the two parameters generated using the Haptic Finger. Use of this sensor could prove extremely valuable in cosmetic research where skin surface texture (in terms of tactile properties) is difficult to measure.

  2. Nuclear Energy Research Initiative (NERI): On-Line Intelligent Self-Diagnostic Monitoring for Next Generation Nuclear Plants - Phase I Annual Report

    Energy Technology Data Exchange (ETDEWEB)

    L. J. Bond; S. R. Doctor; R. W. Gilbert; D. B. Jarrell; F. L. Greitzer; R. J. Meador

    2000-09-01

    OAK-B135 This OSTI ID belongs to an IWO and is being released out of the system. The Program Manager Rebecca Richardson has confirmed that all reports have been received. The objective of this project is to design and demonstrate the operation of the real-time intelligent self-diagnostic and prognostic system for next generation nuclear power plant systems. This new self-diagnostic technology is titled, ''On-Line Intelligent Self-Diagnostic Monitoring System'' (SDMS). This project provides a proof-of-principle technology demonstration for SDMS on a pilot plant scale service water system, where a distributed array of sensors is integrated with active components and passive structures typical of next generation nuclear power reactor and plant systems. This project employs state-of-the-art sensors, instrumentation, and computer processing to improve the monitoring and assessment of the power reactor system and to provide diagnostic and automated prognostics capabilities.

  3. Nuclear Energy Research Initiative (NERI): On-Line Intelligent Self-Diagnostic Monitoring for Next Generation Nuclear Plants - Phase I Annual Report

    International Nuclear Information System (INIS)

    Bond, L.G.; Doctor, S.R.; Gilbert, R.W.; Jarrell, D.B.; Greitzer, F.L.; Meador, R.J.

    2000-01-01

    OAK-B135 This OSTI ID belongs to an IWO and is being released out of the system. The Program Manager Rebecca Richardson has confirmed that all reports have been received. The objective of this project is to design and demonstrate the operation of the real-time intelligent self-diagnostic and prognostic system for next generation nuclear power plant systems. This new self-diagnostic technology is titled, ''On-Line Intelligent Self-Diagnostic Monitoring System'' (SDMS). This project provides a proof-of-principle technology demonstration for SDMS on a pilot plant scale service water system, where a distributed array of sensors is integrated with active components and passive structures typical of next generation nuclear power reactor and plant systems. This project employs state-of-the-art sensors, instrumentation, and computer processing to improve the monitoring and assessment of the power reactor system and to provide diagnostic and automated prognostics capabilities

  4. Computational intelligence in nuclear engineering

    International Nuclear Information System (INIS)

    Uhrig, Robert E.; Hines, J. Wesley

    2005-01-01

    Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several Changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations

  5. Intelligent mobile sensor system for drum inspection and monitoring: Phase 1. Topical report, October 1, 1992--June 8, 1993

    Energy Technology Data Exchange (ETDEWEB)

    1993-06-01

    The objective of this project was to develop an operational system for monitoring and inspection activities for waste storage facility operations at several DOE sites. Specifically, the product of this effort is a robotic device with enhanced intelligence and maneuverability capable of conducting routine inspection of stored waste drums. The device is capable of operating in narrow aisles and interpolating the free aisle space between rows of stacked drums. The system has an integrated sensor suite for leak detection, and is interfaced with a site database both for inspection planning and for data correlation, updating, and report generation. The system is capable of departing on an assigned mission, collecting required data, recording which positions of its mission had to be aborted or modified due to environmental constraints, and reporting back when the mission is complete. Successful identification of more than 90% of all drum defects has been demonstrated in a high fidelity waste storage facility mockup. Identified anomalies included rust spots, rust streaks, areas of corrosion, dents, and tilted drums. All drums were positively identified and correlated with the site database. This development effort is separated into three phases of which phase one is now complete. The first phase has demonstrated an integrated system for monitoring and inspection activities for waste storage facility operations. This demonstration system was quickly fielded and evaluated by leveraging technologies developed from previous NASA and DARPA contracts and internal research. The second phase will demonstrate a prototype system appropriate for operational use in an actual storage facility. The prototype provides an integrated design that considers operational requirements, hardware costs, maintenance, safety, and robustness. The final phase will demonstrate commercial viability using the prototype vehicle in a pilot waste operations and inspection project.

  6. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  7. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Directory of Open Access Journals (Sweden)

    Ke Li

    2016-01-01

    Full Text Available A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF and Diagnostic Bayesian Network (DBN is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO. To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA is proposed to evaluate the sensitiveness of symptom parameters (SPs for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  8. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

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

    International Nuclear Information System (INIS)

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

    2000-01-01

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

  10. An intelligent portal monitor for fast suppression of false positives due to radiopharmaceuticals

    International Nuclear Information System (INIS)

    Johnson, M.W.; Butterfield, K.B.

    1985-01-01

    Monitoring the movement of radioactive material through secure or sensitive areas may be complicated by the existence of unanticipated sources of radiation carried by individuals passing through the area. Typical of such sources are radiopharmaceuticals prescribed for a medical procedure. The authors report here on an apparatus designed to quickly discriminate between in-vivo radiopharmaceuticals and other nuclear materials, based on a pattern-recognition algorithm and microcomputer. Principles of operation are discussed, and the data base for the pattern-recognition algorithms is displayed. Operating experience with the apparatus in a trial location is also discussed. The apparatus correctly identifies in-vivo radiopharmaceuticals in over 80% of all trials; challenges with radioisotopes other than radiopharmaceuticals have led the apparatus, without exception, to reject the challenge isotope as incompatible with medical practice. The apparatus thus rapidly discriminates between individuals bearing radiopharmaceuticals and those bearing illicit sources, such as special nuclear materials

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

    Science.gov (United States)

    Turán, Ján.; Ovseník, Łuboš

    2016-12-01

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

  12. Performance Evaluation of an Intelligent Sensor Platform for Radiation Monitoring Applications

    Energy Technology Data Exchange (ETDEWEB)

    Nakazawa, Dante; Herman, Cedric; Russ, Bill; Huckins, Robert [Canberra Industries, 800 Research Parkway, Meriden, CT 06450 (United States)

    2015-07-01

    Accurate, rugged, and reliable radiation detection systems are important for area and environmental monitoring applications. The desire for spectroscopic capability has increased in monitoring aspects of the nuclear fuel cycle to provide fast characterization of the radiation profile of a situation, such as the planned or unplanned release of material. The reduction or elimination of having to conduct sampling for laboratory analysis can result in significant cost savings for an industry, government agency, or regulatory body. A new system, comprised of a NaI:Tl scintillator and a G-M tube, has been designed and tested, taking into account the following end-user requirements: ease-of-use, capability to network and supervise multiple units, compact form factor, low power consumption, versatility, and stability. The detector sizes were selected to accommodate a dose rate up to 1 Sv/hr. Several algorithms and analysis routines have been developed to incorporate these key needs without sacrificing on accuracy, dynamic range, nuclide identification, and sensitivity. This presentation will introduce the major hardware and software components of the platform, as well as the user interface and data analysis workflow. Key features of the hardware include an environmentally robust housing, low power signal processing electronics, patented LED-based gain stabilization, and an embedded processor for unattended instrument management and data analysis. New and improved algorithms for determining scintillator gamma dose rates, total integrated dose, and nuclide identification will be introduced. The two detector elements were modeled with MCNP and validated experimentally. The results of the radiological testing shall be presented including energy resolution, throughput, dose response, and minimum detectable activities. The dose response has been evaluated in simulations and with measurements to ensure accurate response with respect to energy spectrum of the dose field and

  13. Complex data management for landslide monitoring in emergency conditions

    Science.gov (United States)

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

    2017-04-01

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

  14. Condition monitoring: a study on ageing in Inconel 718

    International Nuclear Information System (INIS)

    Acharya, Vidhi; Murthy, G.V.S.

    2015-01-01

    The development of contemporary high temperature materials is needed to enable the successful introduction of cleaner and more efficient next generation power plants. Due to inherent limitations in steels, new high temperature materials must be selected for a change in operating parameters. Inconel-718 is currently considered to be one of the leading materials for use in high temperature applications. Due to its excellent high-temperature mechanical properties, Inconel-718 is believed to be a contender for forged components of Advanced Ultra-Supercritical (A-USC) power plants. The A-USC power plant with steam conditions of 700°C/35 MPa, is expected to have greater efficiency. Thus the microstructural stability and its impact on the mechanical properties of this alloy at elevated temperatures will certainly be a crucial factor that influences the reliability of the power plants. Therefore it is of imminent importance to study the microstructural evolution of components made out of Inconel-718 preferably by Non-destructive methods

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

    Science.gov (United States)

    2010-01-01

    ... external and internal occupational dose. Each licensee shall monitor exposures to radiation and radioactive... 10 Energy 1 2010-01-01 2010-01-01 false Conditions requiring individual monitoring of external and internal occupational dose. 20.1502 Section 20.1502 Energy NUCLEAR REGULATORY COMMISSION STANDARDS FOR...

  16. 4th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations

    CERN Document Server

    Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed

    2016-01-01

    The book provides readers with a snapshot of recent research and technological trends in the field of condition monitoring of machinery working under a broad range of operating conditions. Each chapter, accepted after a rigorous peer-review process, reports on an original piece of work presented and discussed at the 4th International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO 2014, held on December 15-16, 2014, in Lyon, France. The contributions have been grouped into three different sections according to the main subfield (signal processing, data mining, or condition monitoring techniques) they are related to. The book includes both theoretical developments as well as a number of industrial case studies, in different areas including, but not limited to: noise and vibration; vibro-acoustic diagnosis; signal processing techniques; diagnostic data analysis; instantaneous speed identification; monitoring and diagnostic systems; and dynamic and fault modeling. This book no...

  17. Performance and perspectives of the diamond based Beam Condition Monitor for beam loss monitoring at CMS

    CERN Document Server

    AUTHOR|(CDS)2080862

    2015-01-01

    At CMS, a beam loss monitoring system is operated to protect the silicon detectors from high particle rates, arising from intense beam loss events. As detectors, poly-crystalline CVD diamond sensors are placed around the beam pipe at several locations inside CMS. In case of extremely high detector currents, the LHC beams are automatically extracted from the LHC rings.Diamond is the detector material of choice due to its radiation hardness. Predictions of the detector lifetime were made based on FLUKA monte-carlo simulations and irradiation test results from the RD42 collaboration, which attested no significant radiation damage over several years.During the LHC operational Run1 (2010 â?? 2013), the detector efficiencies were monitored. A signal decrease of about 50 times stronger than expectations was observed in the in-situ radiation environment. Electric field deformations due to charge carriers, trapped in radiation induced lattice defects, are responsible for this signal decrease. This so-called polarizat...

  18. On-line condition monitoring of nuclear systems via symbolic time series analysis

    International Nuclear Information System (INIS)

    Rajagopalan, V.; Ray, A.; Garcia, H. E.

    2006-01-01

    This paper provides a symbolic time series analysis approach to fault diagnostics and condition monitoring. The proposed technique is built upon concepts from wavelet theory, symbolic dynamics and pattern recognition. Various aspects of the methodology such as wavelet selection, choice of alphabet and determination of depth of D-Markov Machine are explained in the paper. The technique is validated with experiments performed in a Machine Condition Monitoring (MCM) test bed at the Idaho National Laboratory. (authors)

  19. Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods

    OpenAIRE

    Peng Guo; Nan Bai

    2011-01-01

    Condition Monitoring (CM) of wind turbines can greatly reduce the maintenance costs for wind farms, especially for offshore wind farms. A new condition monitoring method for a wind turbine gearbox using temperature trend analysis is proposed. Autoassociative Kernel Regression (AAKR) is used to construct the normal behavior model of the gearbox temperature. With a proper construction of the memory matrix, the AAKR model can cover the normal working space for the gearbox. When the gearbox has a...

  20. Intelligent portal monitor for fast suppression of false positives due to radiopharmaceuticals

    International Nuclear Information System (INIS)

    Johnson, M.W.; Butterfield, K.B.

    1985-01-01

    Monitoring the movement of radioactive material through secure or sensitive areas may be complicated by the existence of unanticipated sources of radiation carried by individuals passing through the area. Typical of such sources are radiopharmaceuticals prescribed for a medical procedure. We report here on an apparatus designed to quickly discriminate between in-vivo radiopharmaceuticals and other nuclear materials, based on a pattern-recognition algorithm and a microcomputer. Principles of operation are discussed, and the data base for the pattern-recognition algorithm is displayed. Operating experience with the apparatus in a trial location is also discussed. Our apparatus correctly identifies in-vivo radiopharmaceuticals in over 80% of all trials; challenges with radioisotopes other than radiopharmaceuticals have led the apparatus, without exception, to reject the challenge isotope as incompatible with medical practice. The apparatus thus rapidly discriminates between individuals bearing radiopharmaceuticals and those bearing illicit sources, such as special nuclear materials. Examples of applications are presented. 7 refs., 4 figs., 1 tab

  1. A vision-based system for intelligent monitoring: human behaviour analysis and privacy by context.

    Science.gov (United States)

    Chaaraoui, Alexandros Andre; Padilla-López, José Ramón; Ferrández-Pastor, Francisco Javier; Nieto-Hidalgo, Mario; Flórez-Revuelta, Francisco

    2014-05-20

    Due to progress and demographic change, society is facing a crucial challenge related to increased life expectancy and a higher number of people in situations of dependency. As a consequence, there exists a significant demand for support systems for personal autonomy. This article outlines the vision@home project, whose goal is to extend independent living at home for elderly and impaired people, providing care and safety services by means of vision-based monitoring. Different kinds of ambient-assisted living services are supported, from the detection of home accidents, to telecare services. In this contribution, the specification of the system is presented, and novel contributions are made regarding human behaviour analysis and privacy protection. By means of a multi-view setup of cameras, people's behaviour is recognised based on human action recognition. For this purpose, a weighted feature fusion scheme is proposed to learn from multiple views. In order to protect the right to privacy of the inhabitants when a remote connection occurs, a privacy-by-context method is proposed. The experimental results of the behaviour recognition method show an outstanding performance, as well as support for multi-view scenarios and real-time execution, which are required in order to provide the proposed services.

  2. A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context

    Directory of Open Access Journals (Sweden)

    Alexandros Andre Chaaraoui

    2014-05-01

    Full Text Available Due to progress and demographic change, society is facing a crucial challenge related to increased life expectancy and a higher number of people in situations of dependency. As a consequence, there exists a significant demand for support systems for personal autonomy. This article outlines the vision@home project, whose goal is to extend independent living at home for elderly and impaired people, providing care and safety services by means of vision-based monitoring. Different kinds of ambient-assisted living services are supported, from the detection of home accidents, to telecare services. In this contribution, the specification of the system is presented, and novel contributions are made regarding human behaviour analysis and privacy protection. By means of a multi-view setup of cameras, people’s behaviour is recognised based on human action recognition. For this purpose, a weighted feature fusion scheme is proposed to learn from multiple views. In order to protect the right to privacy of the inhabitants when a remote connection occurs, a privacy-by-context method is proposed. The experimental results of the behaviour recognition method show an outstanding performance, as well as support for multi-view scenarios and real-time execution, which are required in order to provide the proposed services.

  3. Environment monitoring and residents health condition monitoring of nuclear power plant Bohunice region

    International Nuclear Information System (INIS)

    Letkovicova, M.; Rehak, R.; Stehlikova, B.; Celko, M.; Hraska, S.; Klocok, L.; Kostial, J.; Prikazsky, V.; Vidovic, J.; Zirko, M.; Beno, T.; Mitosinka, J.

    1998-01-01

    The report contents final environment evaluation and selected characteristic of residents health physics of nuclear power plant Bohunice region. Evaluated data were elaborated during analytical period 1993-1997.Task solving which results are documented in this final report was going on between 1996- 1998. The report deals in individual stages with the following: Information obtaining and completing which characterize demographic situation of the area for the 1993-1997 period; Datum obtaining and completing which contain selected health physics characteristics of the area residents; Database structures for individual data archiving from monitoring and collection; Brief description of geographic information system for graphic presentation of evaluation results based on topographic base; Digital mapping structure description; Results and evaluation of radionuclide monitoring in environment performed by Environmental radiation measurements laboratory by the nuclear power plant Bohunice for the 1993-1997 period. Demographic situation evaluation and selected health physics characteristics of the area of nuclear power plant residents for the 1993-1997 period are summarized in the final part of the document. Monitoring results and their evaluation is processed in graph, table, text description and map output forms. Map outputs are processed in the geographic information system Arc View GIS 3.0a environment

  4. Influence factor analysis of atmospheric electric field monitoring near ground under different weather conditions

    International Nuclear Information System (INIS)

    Wan, Haojiang; Wei, Guanghui; Cui, Yaozhong; Chen, Yazhou

    2013-01-01

    Monitoring of atmospheric electric field near ground plays a critical role in atmospheric environment detecting and lightning warning. Different environmental conditions (e.g. buildings, plants, weather, etc.) have different influences on the data's coherence in an atmospheric electric field detection network. In order to study the main influence factors of atmospheric electric field monitoring under different weather conditions, with the combination of theoretical analysis and experiments, the electric field monitoring data on the ground and on the top of a building are compared in fair weather and thunderstorm weather respectively in this paper. The results show that: In fair weather, the field distortion due to the buildings is the main influence factor on the electric field monitoring. In thunderstorm weather, the corona ions produced from the ground, besides the field distortion due to the buildings, can also influence the electric field monitoring results.

  5. Monitoring and diagnosis of vegetable growth based on internet of things

    Science.gov (United States)

    Zhang, Qian; Yu, Feng; Fu, Rong; Li, Gang

    2017-10-01

    A new condition monitoring method of vegetable growth was proposed, which was based on internet of things. It was combined remote environmental monitoring, video surveillance, intelligently decision-making and two-way video consultation together organically.

  6. Implementation strategies and tools for condition based monitoring at nuclear power plants

    International Nuclear Information System (INIS)

    2007-05-01

    There is now an acute need to optimize maintenance to improve both reliability and competitiveness of nuclear power plant operation. There is an increasing tendency to move from the preventive (time based) maintenance concept to one dependent on plant and component conditions. In this context, various on-line and off-line condition monitoring and diagnostics, nondestructive inspection techniques and surveillance are used. Component selection for condition based maintenance, parameter selection for monitoring condition, evaluation of condition monitoring results are issues influencing the effectiveness of condition based maintenance. All these selections of components and parameters to be monitored, monitoring and diagnostics techniques to be used, acceptance criteria and trending for condition evaluation, and the economic aspect of predictive maintenance and condition monitoring should be incorporated into an integrated, effective condition based maintenance programme, which is part of the plant's overall maintenance optimization programme. This publication collects and analyses proven condition based maintenance strategies and techniques (engineering and organizational) in Member States. It includes selected papers on maintenance optimization presented during its preparation. This report was prepared under IAEA project on integrated NPP life cycle management including decommissioning. The main objective of an integrated life cycle management programme is to enable NPP's to compete, without compromising safety, successfully in the changing energy markets throughout their service life and to facilitate life extension and eventual decommissioning through improved engineering, technological, economic and managerial actions. The technical working group on NPP life management and other advisory groups nominated by the Member States provide recommendations on high priority needs of Member States in this area

  7. Life cycle management. Condition monitoring of wind power plants; Life-cycle-management. Zustandsueberwachung von Windenergieanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Wolff, R. [cmc GmbH, Kiel (Germany)

    2013-06-01

    The author of the contribution under consideration reports on maintenance strategies and condition monitoring in the field of wind energy. Beside the components in the drive train of wind turbines under consideration, the condition monitoring of the hardware systems and their software is explained. A brief overview of the field of machinery diagnosis and an explanation of the transmission of the measured data follow. Additional sensors such as sensors for the rotor blade monitoring, oil particles counter or oil quality sensors are described. In the field of diagnostic certainty, special follow-up studies such as video endoscopy, analysis of oil or grease, filter testing and material testing are discussed. The information from these thematic fields is used in the life-cycle management database for operationally relevant evaluations and considerations of economy of condition monitoring systems.

  8. Economic analysis of condition monitoring systems for offshore wind turbine sub-systems

    DEFF Research Database (Denmark)

    May, Allan; MacMillan, David; Thöns, Sebastian

    2015-01-01

    The use of condition monitoring systems on offshore wind turbines has increased dramatically in recent times. However, their use is mostly restricted to vibration based monitoring systems for the gearbox, generator and drive train. A survey of commercially available condition monitoring systems...... year life cycle. The model uses Hidden Markov Models to represent both the actual system state and the observed condition monitoring state. The CM systems are modelled to include reduced failure types, false alarms, detection rates and 6 month failure warnings. The costs for system failures are derived...... and their associated costs has been completed for the blades, drive train, tower and foundation. This paper considers what value can be obtained from integrating these additional systems into the maintenance plan. This is achieved by running simulations on an operations and maintenance model for a wind farm over a 20...

  9. A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

    Science.gov (United States)

    Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

    2014-01-01

    This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.

  10. Novel activity classification and occupancy estimation methods for intelligent HVAC (heating, ventilation and air conditioning) systems

    International Nuclear Information System (INIS)

    Rana, Rajib; Kusy, Brano; Wall, Josh; Hu, Wen

    2015-01-01

    Reductions in HVAC (heating, ventilation and air conditioning) energy consumption can be achieved by limiting heating in the winter or cooling in the summer. However, the resulting low thermal comfort of building occupants may lead to an override of the HVAC control, which revokes its original purpose. This has led to an increased interest in modeling and real-time tracking of location, activity, and thermal comfort of building occupants for HVAC energy management. While thermal comfort is well understood, it is difficult to measure in real-time environments where user context changes dynamically. Encouragingly, plethora of sensors available on smartphone unleashes the opportunity to measure user contexts in real-time. An important contextual information for measuring thermal comfort is Metabolism rate, which changes based on current physical activities. To measure physical activity, we develop an activity classifier, which achieves 10% higher accuracy compared to Support Vector Machine and k-Nearest Neighbor. Office occupancy is another contextual information for energy-efficient HVAC control. Most of the phone based occupancy estimation techniques will fail to determine occupancy when phones are left at desk while sitting or attending meetings. We propose a novel sensor fusion method to detect if a user is near the phone, which achieves more than 90% accuracy. Determining activity and occupancy our proposed algorithms can help maintaining thermal comfort while reducing HVAC energy consumptions. - Highlights: • We propose activity and occupancy detection for efficient HVAC control. • Activity classifier achieves 10% higher accuracy than SVM and kNN. • For occupancy detection we propose a novel sensor fusion method. • Using Weighted Majority Voting we fuse microphone and accelerometer data on phone. • We achieve more than 90% accuracy in detecting occupancy.

  11. Condition Monitoring

    DEFF Research Database (Denmark)

    Avenas, Yvan; Dupont, Laurent; Baker, Nick

    2015-01-01

    Power conversion systems are dependent on the performance and reliability of static converters. However, they are subject to frequent functional and environmental strains, which can induce failures. The anticipation of these failures is difficult but important so the operation of a system can be ...

  12. The use of condition monitoring information for maintenance planning and decision-making

    Energy Technology Data Exchange (ETDEWEB)

    Laakso, K.; Rosqvist, T. [VTT Industrial Systems (Finland); Paulsen, J.L. [Risoe National Lab., Roskilde (Denmark)

    2002-12-01

    A survey is presented outlining the use of condition monitoring information in three Nordic nuclear power plants. The questions of the survey relate to the role of condition monitoring in strategic, as well as operative, maintenance planning and decision-making. The survey indicates that condition monitoring is increasingly implemented at nuclear power plants, but very selectively and in a rather slow pace for predictive maintenance. A combined strategy of condition based maintenance and predetermined preventive maintenance is applied for important equipment such as main circulation pumps and steam turbines. A realistic aim is to reduce the number of costly or error prone maintenance and disassembling inspection activities by condition monitoring given that the approach enables a good diagnosis and prediction. Systematic follow-up and analysis of such condition monitoring information followed by a case-specific planning and decision making of timely and rightly directed maintenance actions can justify an extension of the intervals of a number of predetermined inspection, maintenance or periodic testing tasks. (au)

  13. Catalogue of systems for the monitoring of working conditions relating to health and safety

    NARCIS (Netherlands)

    Prins, R.; Verboon, F.

    1991-01-01

    In this Catalogue a number of systems or instruments for Monitoring Working Conditions and workers Health and Safety have been described. The general aim of the project was three-fold: - to obtain an overall assessment of the existing instruments for identifying risk factors and working conditions

  14. Condition Monitoring of Machinery in Non-Stationary Operations : Proceedings of the Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations"

    CERN Document Server

    Bartelmus, Walter; Chaari, Fakher; Zimroz, Radoslaw; Haddar, Mohamed

    2012-01-01

    Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 – 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers...

  15. Artificial Intelligence in Autonomous Telescopes

    Science.gov (United States)

    Mahoney, William; Thanjavur, Karun

    2011-03-01

    Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

  16. New oil condition monitoring system, Wearsens® enables continuous, online detection of critical operating conditions and wear damage

    Directory of Open Access Journals (Sweden)

    Manfred Mauntz

    2015-12-01

    Full Text Available A new oil sensor system is presented for the continuous, online measurement of the wear in turbines, industrial gears, generators, hydraulic systems and transformers. Detection of change is much earlier than existing technologies such as particle counting, vibration measurement or recording temperature. Thus targeted, corrective procedures and/or maintenance can be carried out before actual damage occurs. Efficient machine utilization, accurately timed preventive maintenance, increased service life and a reduction of downtime can all be achieved. The presented sensor system effectively controls the proper operation conditions of bearings and cogwheels in gears. The online diagnostics system measures components of the specific complex impedance of oils. For instance, metal abrasion due to wear debris, broken oil molecules, forming acids or oil soaps, result in an increase of the electrical conductivity, which directly correlates with the degree of contamination of the oil. For additivated lubricants, the stage of degradation of the additives can also be derived from changes in the dielectric constant. The determination of impurities or reduction in the quality of the oil and the quasi continuous evaluation of wear and chemical aging follow the holistic approach of a real-time monitoring of an alteration in the condition of the oil-machine system. Once the oil condition monitoring sensors are installed on the wind turbine, industrial gearbox and test stands, the measuring data can be displayed and evaluated elsewhere. The signals are transmitted to a web-based condition monitoring system via LAN, WLAN or serial interfaces of the sensor unit. Monitoring of the damage mechanisms during proper operation below the tolerance limits of the components enables specific preventive maintenance independent of rigid inspection intervals.

  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)

    1998-12-31

    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. 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.)

  19. Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design

    Science.gov (United States)

    Hall, Travis; Nguyen, Tam Q.; Mayeda, Jill C.; Lie, Paul E.; Lopez, Jerry; Banister, Ron E.

    2017-01-01

    It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients’ long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF) non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the subject is

  20. Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design

    Directory of Open Access Journals (Sweden)

    Travis Hall

    2017-11-01

    Full Text Available It has been the dream of many scientists and engineers to realize a non-contact remote sensing system that can perform continuous, accurate and long-term monitoring of human vital signs as we have seen in many Sci-Fi movies. Having an intelligible sensor system that can measure and record key vital signs (such as heart rates and respiration rates remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a sensor system can also effectively help physicians and patients making better informed decisions when patients’ long-term vital signs data is available. Therefore, there has been a lot of research activities on developing a non-contact sensor system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Doppler-based radio-frequency (RF non-contact vital signs (NCVS monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor any contact-based sensors involved so the subjects may not be even aware of the ubiquitous monitoring. In this paper, we will provide a brief review on some latest development on NCVS sensors and compare them against a few novel and intelligent phased-array Doppler-based RF NCVS biosensors we have built in our labs. Some of our NCVS sensor tests were performed within a clutter-free anechoic chamber to mitigate the environmental clutters, while most tests were conducted within the typical Herman-Miller type office cubicle setting to mimic a more practical monitoring environment. Additionally, we will show the measurement data to demonstrate the feasibility of long-term NCVS monitoring. The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring intelligently and robustly, especially for situations where the

  1. Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

    2013-03-01

    The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.

  2. Overview of condition monitoring and operation control of electric power conversion systems in direct-drive wind turbines under faults

    Science.gov (United States)

    Huang, Shoudao; Wu, Xuan; Liu, Xiao; Gao, Jian; He, Yunze

    2017-09-01

    Electric power conversion system (EPCS), which consists of a generator and power converter, is one of the most important subsystems in a direct-drive wind turbine (DD-WT). However, this component accounts for the most failures (approximately 60% of the total number) in the entire DD-WT system according to statistical data. To improve the reliability of EPCSs and reduce the operation and maintenance cost of DD-WTs, numerous researchers have studied condition monitoring (CM) and fault diagnostics (FD). Numerous CM and FD techniques, which have respective advantages and disadvantages, have emerged. This paper provides an overview of the CM, FD, and operation control of EPCSs in DD-WTs under faults. After introducing the functional principle and structure of EPCS, this survey discusses the common failures in wind generators and power converters; briefly reviewed CM and FD methods and operation control of these generators and power converters under faults; and discussed the grid voltage faults related to EPCSs in DD-WTs. These theories and their related technical concepts are systematically discussed. Finally, predicted development trends are presented. The paper provides a valuable reference for developing service quality evaluation methods and fault operation control systems to achieve high-performance and high-intelligence DD-WTs.

  3. Improvements in valve reliability due to implementation of effective condition monitoring programs

    International Nuclear Information System (INIS)

    Hale, Stan

    2003-01-01

    Modern diagnostic systems for motor-operated valves, pneumatic control valves and checkvalves have facilitated a shift in the maintenance philosophy for valves and actuators in nuclear power plants from schedule based to condition-based maintenance (CBM). This shift enables plant management to focus resources and schedule priority on the plant equipment that warrants attention thereby not wasting resources or increasing the human factors risk on equipment that has not degraded. The most recent initiatives combine condition monitoring with risk/safety insights to focus attention and resonances on the right equipment at the right time consistent with each component's safety-significance. The activities of the ASME working groups responsible for nuclear O and M codes have kept pace with the technology and process improvements necessary to maximize the technical and economic benefits of condition based and risk informed maintenance. This paper discusses adoption of valve condition monitoring in the nuclear power industry, changes to ASME codes and standards during the 90's to facilitate adoption of condition monitoring technology for in-service testing and recent efforts to combine risk insights with condition monitoring strategies to achieve the highest level of valve reliability and nuclear safety without over inflating maintenance cost. (author)

  4. Priority target conditions for algorithms for monitoring children's growth: Interdisciplinary consensus.

    Directory of Open Access Journals (Sweden)

    Pauline Scherdel

    Full Text Available Growth monitoring of apparently healthy children aims at early detection of serious conditions through the use of both clinical expertise and algorithms that define abnormal growth. Optimization of growth monitoring requires standardization of the definition of abnormal growth, and the selection of the priority target conditions is a prerequisite of such standardization.To obtain a consensus about the priority target conditions for algorithms monitoring children's growth.We applied a formal consensus method with a modified version of the RAND/UCLA method, based on three phases (preparatory, literature review, and rating, with the participation of expert advisory groups from the relevant professional medical societies (ranging from primary care providers to hospital subspecialists as well as parent associations. We asked experts in the pilot (n = 11, reading (n = 8 and rating (n = 60 groups to complete the list of diagnostic classification of the European Society for Paediatric Endocrinology and then to select the conditions meeting the four predefined criteria of an ideal type of priority target condition.Strong agreement was obtained for the 8 conditions selected by the experts among the 133 possible: celiac disease, Crohn disease, craniopharyngioma, juvenile nephronophthisis, Turner syndrome, growth hormone deficiency with pituitary stalk interruption syndrome, infantile cystinosis, and hypothalamic-optochiasmatic astrocytoma (in decreasing order of agreement.This national consensus can be used to evaluate the algorithms currently suggested for growth monitoring. The method used for this national consensus could be re-used to obtain an international consensus.

  5. Fast beam conditions monitor BCM1F for the CMS experiment

    International Nuclear Information System (INIS)

    Bell, A.; Castro, E.; Hall-Wilton, R.

    2009-10-01

    The CMS Beam Conditions and Radiation Monitoring System, BRM, will support beam tuning, protect the CMS detector from adverse beam conditions, and measure the accumulated dose close to or inside all sub-detectors. It is composed of different sub-systems measuring either the particle flux near the beam pipe with time resolution between nano- and microseconds or the integrated dose over longer time intervals. This paper presents the Fast Beam Conditions Monitor, BCM1F, which is designed for fast flux monitoring measuring both beam halo and collision products. BCM1F is located inside the CMS pixel detector volume close to the beam-pipe. It uses sCVD diamond sensors and radiation hard front-end electronics, along with an analog optical readout of the signals. The commissioning of the system and its successful operation during the first beams of the LHC are described. (orig.)

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

    Science.gov (United States)

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

    2017-07-01

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

  7. Fast beam conditions monitor BCM1F for the CMS experiment

    Energy Technology Data Exchange (ETDEWEB)

    Bell, A. [CERN, Geneva (Switzerland); Geneva Univ. (Switzerland); Castro, E. [DESY Zeuthen (Germany); Hall-Wilton, R. [CERN, Geneva (Switzerland); Wisconsin Univ., Madison, WI (US)] (and others)

    2009-10-15

    The CMS Beam Conditions and Radiation Monitoring System, BRM, will support beam tuning, protect the CMS detector from adverse beam conditions, and measure the accumulated dose close to or inside all sub-detectors. It is composed of different sub-systems measuring either the particle flux near the beam pipe with time resolution between nano- and microseconds or the integrated dose over longer time intervals. This paper presents the Fast Beam Conditions Monitor, BCM1F, which is designed for fast flux monitoring measuring both beam halo and collision products. BCM1F is located inside the CMS pixel detector volume close to the beam-pipe. It uses sCVD diamond sensors and radiation hard front-end electronics, along with an analog optical readout of the signals. The commissioning of the system and its successful operation during the first beams of the LHC are described. (orig.)

  8. Data support system for controlling decentralised nuclear power industry facilities through uninterruptible condition monitoring

    Directory of Open Access Journals (Sweden)

    Povarov Vladimir

    2018-01-01

    Full Text Available The article describes the automated uninterruptible multi-parameter system for monitoring operational vulnerability of critical NPP components, which differs from existing ones by being universally applicable for analysing mechanical damage of nuclear power unit components. The system allows for performing routine assessment of metal structures. The assessment of strained condition of a deteriorating component is based on three-dimensional finite element simulation with calculations adjusted with reference to in-situ measurements. A program for calculation and experimental analysis of maximum load and durability of critical area forms the core of uninterruptible monitoring system. The knowledge base on performance of the monitored components in different operating conditions and the corresponding comprehensive analysis of strained condition and deterioration rates compose the basis of control system data support, both for operating nuclear power units and robotic maintenance and repair systems.

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  10. A Review of the Condition Monitoring of Capacitors in Power Electronic Converters

    DEFF Research Database (Denmark)

    Soliman, Hammam Abdelaal Hammam; Wang, Huai; Blaabjerg, Frede

    2015-01-01

    Capacitor is one of the reliability critical components in power electronic systems. In the last two decades, many efforts in the academic research have been devoted to the condition monitoring of capacitors to estimate their health status. Industry applications demand more reliable power...... electronics products with preventive maintenance. Nevertheless, most of the developed capacitor condition monitoring technologies are rarely adopted by industry due to the complexity, increased cost and other relevant issues. An overview of the prior-art research in this area is therefore needed to justify....... Therefore, this paper firstly classifies the capacitor condition monitoring methods into three categories, then the respective technology evolution from 1993 to 2015 is summarized. Remarks on the state-of-the-art research and the future opportunities targeting for practical industry applications are given....

  11. A Review of the Condition Monitoring of Capacitors in Power Electronic Converters

    DEFF Research Database (Denmark)

    Soliman, Hammam Abdelaal Hammam; Wang, Huai; Blaabjerg, Frede

    2016-01-01

    Capacitors are one type of reliability-critical components in power electronic systems. In the last two decades, many efforts in academic research have been devoted to the condition monitoring of capacitors to estimate their health status. Industry applications are demanding more reliable power...... electronics products with preventive maintenance. Nevertheless, most of the developed capacitor condition monitoring technologies are rarely adopted by industry due to the complexity, increased cost, and other relevant issues. An overview of the prior-art research in this area is therefore needed to justify......, this paper first classifies the capacitor condition monitoring methods into three categories, then the respective technology evolution in the last two decades is summarized. Finally, the state-of-the-art research and the future opportunities targeting for industry applications are given....

  12. A real time study on condition monitoring of distribution transformer using thermal imager

    Science.gov (United States)

    Mariprasath, T.; Kirubakaran, V.

    2018-05-01

    The transformer is one of the critical apparatus in the power system. At any cost, a few minutes of outages harshly influence the power system. Hence, prevention-based maintenance technique is very essential. The continuous conditioning and monitoring technology significantly increases the life span of the transformer, as well as reduces the maintenance cost. Hence, conditioning and monitoring of transformer's temperature are very essential. In this paper, a critical review has been made on various conditioning and monitoring techniques. Furthermore, a new method, hot spot indication technique, is discussed. Also, transformer's operating condition is monitored by using thermal imager. From the thermal analysis, it is inferred that major hotspot locations are appearing at connection lead out; also, the bushing of the transformer is the very hottest spot in transformer, so monitoring the level of oil is essential. Alongside, real time power quality analysis has been carried out using the power analyzer. It shows that industrial drives are injecting current harmonics to the distribution network, which causes the power quality problem on the grid. Moreover, the current harmonic limit has exceeded the IEEE standard limit. Hence, the adequate harmonics suppression technique is need an hour.

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

    Directory of Open Access Journals (Sweden)

    Yong Li

    2014-01-01

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

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

    International Nuclear Information System (INIS)

    Meng Qinghu; Meng Qingfeng; Feng Wuwei

    2012-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  16. Development of wall conditioning and impurity monitoring systems in Versatile Experiment Spherical Torus (VEST)

    Energy Technology Data Exchange (ETDEWEB)

    Lee, H.Y., E-mail: brbbebbero@snu.ac.kr [Seoul National University, Seoul (Korea, Republic of); Yang, J.; Kim, Y.G.; Yang, S.M.; Kim, Y.S.; Lee, K.H. [Seoul National University, Seoul (Korea, Republic of); An, Y.H. [National Fusion Research Institute, Daejon (Korea, Republic of); Chung, K.J.; Na, Y.S. [Seoul National University, Seoul (Korea, Republic of); Hwang, Y.S., E-mail: yhwang@snu.ac.kr [Seoul National University, Seoul (Korea, Republic of)

    2016-11-01

    Highlights: • The baking for partial wall heating and H{sub 2}/He GDC systems are developed in VEST. • The RGA and OES systems for monitoring impurities are constructed in VEST. • The partial baking and He GDC show limited effects on plasma characteristics. • H{sub 2} GDC above 4 h enables the longer plasma current duration up to ∼15 ms. • After H{sub 2} GDC, the discharge should be conducted within 3 h from treatment. - Abstract: Wall conditioning and impurity monitoring systems are developed in Versatile Experiment Spherical Torus (VEST). As a wall conditioning system, a baking system covering the vacuum vessel wall partially and a glow discharge cleaning (GDC) system using two electrodes with dc and 50 kHz power supplies are installed. The GDC system operates with hydrogen and helium gases for both chemical and physical desorption. The impurity monitoring system with residual gas analyzer (RGA), operating at <10{sup −5} Torr with a differential pumping system, is installed along with the optical emission spectroscopy (OES) system to monitor the hydrogen and impurity radiation lines. Effects of these wall conditioning techniques are investigated with the impurity monitoring system for ohmic discharges of VEST. The partial baking and He GDC show limited effects on plasma characteristics but sufficient H{sub 2} GDC above 4 h enables the longer plasma current duration up to ∼15 ms within 3 h from the end of treatment.

  17. Development of wall conditioning and impurity monitoring systems in Versatile Experiment Spherical Torus (VEST)

    International Nuclear Information System (INIS)

    Lee, H.Y.; Yang, J.; Kim, Y.G.; Yang, S.M.; Kim, Y.S.; Lee, K.H.; An, Y.H.; Chung, K.J.; Na, Y.S.; Hwang, Y.S.

    2016-01-01

    Highlights: • The baking for partial wall heating and H_2/He GDC systems are developed in VEST. • The RGA and OES systems for monitoring impurities are constructed in VEST. • The partial baking and He GDC show limited effects on plasma characteristics. • H_2 GDC above 4 h enables the longer plasma current duration up to ∼15 ms. • After H_2 GDC, the discharge should be conducted within 3 h from treatment. - Abstract: Wall conditioning and impurity monitoring systems are developed in Versatile Experiment Spherical Torus (VEST). As a wall conditioning system, a baking system covering the vacuum vessel wall partially and a glow discharge cleaning (GDC) system using two electrodes with dc and 50 kHz power supplies are installed. The GDC system operates with hydrogen and helium gases for both chemical and physical desorption. The impurity monitoring system with residual gas analyzer (RGA), operating at <10"−"5 Torr with a differential pumping system, is installed along with the optical emission spectroscopy (OES) system to monitor the hydrogen and impurity radiation lines. Effects of these wall conditioning techniques are investigated with the impurity monitoring system for ohmic discharges of VEST. The partial baking and He GDC show limited effects on plasma characteristics but sufficient H_2 GDC above 4 h enables the longer plasma current duration up to ∼15 ms within 3 h from the end of treatment.

  18. Significance of Operating Environment in Condition Monitoring of Large Civil Structures

    OpenAIRE

    Alampalli, Sreenivas

    1999-01-01

    Success of remote long-term condition monitoring of large civil structures and developing calibrated analytical models for damage detection, depend significantly on establishing accurate baseline signatures and their sensitivity. Most studies reported in the literature concentrated on the effect of structural damage on modal parameters without emphasis on reliability of modal parameters. Thus, a field bridge structure was studied for the significance of operating conditions in relation to bas...

  19. Tools and techniques for ageing predictions in nuclear reactors through condition monitoring

    International Nuclear Information System (INIS)

    Verma, R.M.P.

    1994-01-01

    To operate the nuclear reactors beyond their design predicted life is gaining importance because of huge replacement and decommissioning costs. But experience shows that nuclear plant safety and reliability may decline in the later years of plant life due to ageing degradation. Ageing of nuclear plant components, structures and systems, if unmitigated reduces their safety margins provided in the design and thus increases risks to public health and safety. These safety margins must be monitored throughout plant service life including any extended life. Condition monitoring of nuclear reactor components/equipment and systems can be done to study the effect of ageing, status of safety margins and effect of corrective and mitigating actions taken. The tools and techniques of condition monitoring are also important in failure trending, predictive maintenance, evaluation of scheduled maintenance, in mitigation of ageing, life extension and reliability studies. (author). 1 fig., 1 annexure

  20. A contemporary method for monitoring indoor radon and environmental conditions at a remote test site

    International Nuclear Information System (INIS)

    Renken, K.J.; Coursin, S.

    1996-01-01

    A state-of-the-art method for automatically monitoring indoor radon and environmental conditions at a remote test site is described. A Wisconsin home that exhibited elevated radon levels has been installed with automated PC-data acquisition system (PC-DAS) that includes: a laptop PC, a data acquisition cardcage, a commercial data acquisition software program plus sensors to measure radon gas concentrations, differential pressures, indoor air quality and meteorological conditions. The isolated PC-DAS is connected to a PC in a university laboratory via a modem and a communications software package. Experimental data is monitored and saved by the remote PC in real time and then automatically downloaded to the lab computer at selected intervals. An example of the formatted field results is presented and analysed. This documentation of the set-up, the off-the-shelf computer hardware and software, and the procedures should assist investigations requiring flexible remote long-term radon and environmental monitoring. (Author)

  1. Online calibration method for condition monitoring of nuclear reactor instrumentations based on electrical signature analysis

    International Nuclear Information System (INIS)

    Syaiful Bakhri

    2013-01-01

    Electrical signature analysis currently becomes an alternative in condition monitoring in nuclear power plants not only for stationary components such as sensors, measurement and instrumentation channels, and other components but also for dynamic components such as electric motors, pumps, generator or actuators. In order to guarantee the accuracy, the calibration of monitoring system is a necessary which practically is performed offline, under limited schedules and certain tight procedures. This research aims to introduce online calibration technique for electrical signature condition monitoring in order that the accuracy can be maintained continuously which in turn increases the reactor safety as a whole. The research was performed step by stepin detail from the conventional technique, online calibration using baseline information and online calibration using differential gain adjustment. Online calibration based on differential gain adjustment provides better results than other techniques even tough under extreme gain insertion as well as external disturbances such as supply voltages. (author)

  2. Condition Monitoring for Roller Bearings of Wind Turbines Based on Health Evaluation under Variable Operating States

    Directory of Open Access Journals (Sweden)

    Lei Fu

    2017-10-01

    Full Text Available Condition monitoring (CM is used to assess the health status of wind turbines (WT by detecting turbine failure and predicting maintenance needs. However, fluctuating operating conditions cause variations in monitored features, therefore increasing the difficulty of CM, for example, the frequency-domain analysis may lead to an inaccurate or even incorrect prediction when evaluating the health of the WT components. In light of this challenge, this paper proposed a method for the health evaluation of WT components based on vibration signals. The proposed approach aimed to reduce the evaluation error caused by the impact of the variable operating condition. First, the vibration signal was decomposed into a set of sub-signals using variational mode decomposition (VMD. Next, the sub-signal energy and the probability distribution were obtained and normalized. Finally, the concept of entropy was introduced to evaluate the health condition of a monitored object to provide an effective guide for maintenance. In particular, the health evaluation for CM was based on a performance review over a range of operating conditions, rather than at a certain single operating condition. Experimental investigations were performed which verified the efficiency of the evaluation method, as well as a comparison with the previous method.

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

    Science.gov (United States)

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

    2016-03-01

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

  4. Assessment of Augmented Electronic Fuel Controls for Modular Engine Diagnostics and Condition Monitoring

    Science.gov (United States)

    1978-12-01

    removal of the horoscope . Diagnostic Conoctor - E4 Th10 E4 23-pin connoctor on the electrical control unit Is provided for ground- checking electrical...confidenou in engine condition monitoring * 1min general. Thi9 has boon especially true in~ eases where fUse signal s have c~aused engine shutdowns. Where ECWI

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-10-01

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

  6. A new oil debris sensor for online condition monitoring of wind turbine gearboxes

    DEFF Research Database (Denmark)

    Wang, Chao; Liu, Hui; Liu, Xiao

    2015-01-01

    Online Condition Monitoring (CM) is a key technology for the Operation and Maintenance (O&M) of wind turbines. Lubricating oil is the blood of the wind turbine gearbox. Metal debris in lubricating oil contains abundant information regarding the ageing and wear/damage of mechanical transmission sy...

  7. 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 This paper proposes a novel framework for monitoring the condition of a rotating machine (for example a gearbox or a bearing) that may be subject to load and speed fluctuations. The methodology is especially relevant in situations where no (or only...

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

    Science.gov (United States)

    Torous, John; Friedman, Rohn; Keshavan, Matcheri

    2014-01-21

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

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

    NARCIS (Netherlands)

    Formazin, M.; Burr, H.; Aagestad, C.; Tynes, T.; Thorsen, S.V.; Perkio-Makela, M.; Díaz Aramburu, C.I.; Pinilla García, F.J.; Galiana Blanco, L.; Vermeylen, G.; Parent-Thirion, A.; Hooftman, W.; Houtman, I.L.D.

    2014-01-01

    Background.In most countries in the EU, national surveys are used to monitor working conditions and health. Since the development processes behind the various surveys are not necessarily theoretical, but certainly practical and political, the extent of similarity among the dimensions covered in

  10. Long-term monitoring of sea ice conditions in the Kerch Strait by remote sensing data

    Science.gov (United States)

    Lavrova, Olga Yu.; Mityagina, Marina I.; Bocharova, Tatiana Yu.; Kostianoy, Andrey G.

    2017-10-01

    The results of multi-year satellite monitoring of ice conditions in the Kerch Strait connecting the Black and Azov Seas are discussed. The issue gained importance in view of the ongoing construction of the Crimean Bridge across the strait. Our monitoring has been based on the whole variety of available satellite data including visible and radar data over the past 17 years. Every year the Azov Sea becomes fully or partially covered by ice during the cold season. In severe winters, ice often is carried to the Kerch Strait and even the Black Sea. An analysis of ice drift hydrometeorological conditions is presented. The ice conditions of 2017 are under special consideration. Everyday satellite monitoring of the Kerch Strait, including the construction area of the Crimean Bridge, revealed ice formation and drift features on the way from the Azov Sea through the Kerch Strait as well as ice interaction with the piers of the main and technological bridges under construction. It was found that, even under strong northeast winds, ice can pass neither through the piers, nor via the widest shipway. At present, it is hard to discern the impacts of the two bridges on floating ice, nevertheless when the construction is over and the technological bridge is gone, by all appearances the main bridge will strongly affect ice conditions in the Kerch Strait. This perspective calls for continuous satellite monitoring of the area that is enabled by cutting-edge systems and technologies.

  11. Building and application of the plant condition monitoring system for nuclear power plants

    International Nuclear Information System (INIS)

    Ono, S.

    2013-01-01

    To achieve the stable operation of nuclear power plants, we developed the plant condition monitoring system based on the heat and mass balance calculation. This system has adopted the heat balance model based on the actual plant data to find the symptoms of the disorder of the equipment by heat balance changes in the turbine system. (author)

  12. Development and application of the plant condition monitoring system for nuclear power plants

    International Nuclear Information System (INIS)

    Ono, S.

    2014-01-01

    To achieve the stable operation of nuclear power plants, we developed the plant condition monitoring system based on the heat and mass balance calculation. In this system, it is a significant feature to adopt the sophisticated heat balance model based on the actual plant data to find the symptoms of anomalies in the turbine system from heat balance changes. (author)

  13. Photovoltaic Array Condition Monitoring Based on Online Regression of Performance Model

    DEFF Research Database (Denmark)

    Spataru, Sergiu; Sera, Dezso; Kerekes, Tamas

    2013-01-01

    regression modeling, from PV array production, plane-of-array irradiance, and module temperature measurements, acquired during an initial learning phase of the system. After the model has been parameterized automatically, the condition monitoring system enters the normal operation phase, where...

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

    Science.gov (United States)

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

    2010-01-01

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

  15. 77 FR 24228 - Condition Monitoring Techniques for Electric Cables Used in Nuclear Power Plants

    Science.gov (United States)

    2012-04-23

    ... Used in Nuclear Power Plants AGENCY: Nuclear Regulatory Commission. ACTION: Regulatory guide; issuance... guide, (RG) 1.218, ``Condition Monitoring Techniques for Electric Cables Used in Nuclear Power Plants... of electric cables for nuclear power plants. RG 1.218 is not intended to be prescriptive, instead it...

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

    Science.gov (United States)

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

    2005-01-01

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

  17. Online condition monitoring to enable extended operation of nuclear power plants

    International Nuclear Information System (INIS)

    Meyer, Ryan Michael; Bond, Leonard John; Ramuhalli, Pradeep

    2012-01-01

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

  18. Monitoring Conditions Leading to SCC/Corrosion of Carbon Steel in Fuel Grade Ethanol

    Science.gov (United States)

    2011-02-11

    This is the draft final report of the project on field monitoring of conditions that lead to SCC in ethanol tanks and piping. The other two aspects of the consolidated program, ethanol batching and blending effects (WP#325) and source effects (WP#323...

  19. Vibro-acoustic condition monitoring of Internal Combustion Engines: A critical review of existing techniques

    Science.gov (United States)

    Delvecchio, S.; Bonfiglio, P.; Pompoli, F.

    2018-01-01

    This paper deals with the state-of-the-art strategies and techniques based on vibro-acoustic signals that can monitor and diagnose malfunctions in Internal Combustion Engines (ICEs) under both test bench and vehicle operating conditions. Over recent years, several authors have summarized what is known in critical reviews mainly focused on reciprocating machines in general or on specific signal processing techniques: no attempts to deal with IC engine condition monitoring have been made. This paper first gives a brief summary of the generation of sound and vibration in ICEs in order to place further discussion on fault vibro-acoustic diagnosis in context. An overview of the monitoring and diagnostic techniques described in literature using both vibration and acoustic signals is also provided. Different faulty conditions are described which affect combustion, mechanics and the aerodynamics of ICEs. The importance of measuring acoustic signals, as opposed to vibration signals, is due since the former seem to be more suitable for implementation on on-board monitoring systems in view of their non-intrusive behaviour, capability in simultaneously capturing signatures from several mechanical components and because of the possibility of detecting faults affecting airborne transmission paths. In view of the recent needs of the industry to (-) optimize component structural durability adopting long-life cycles, (-) verify the engine final status at the end of the assembly line and (-) reduce the maintenance costs monitoring the ICE life during vehicle operations, monitoring and diagnosing system requests are continuously growing up. The present review can be considered a useful guideline for test engineers in understanding which types of fault can be diagnosed by using vibro-acoustic signals in sufficient time in both test bench and operating conditions and which transducer and signal processing technique (of which the essential background theory is here reported) could be

  20. Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

    Science.gov (United States)

    Varatharajah, Yogatheesan; Berry, Brent; Cimbalnik, Jan; Kremen, Vaclav; Van Gompel, Jamie; Stead, Matt; Brinkmann, Benjamin; Iyer, Ravishankar; Worrell, Gregory

    2018-08-01

    An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between 90 min and 2 h are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-12-31

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

  2. Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring.

    Science.gov (United States)

    Wei, Peng; Ning, Zhi; Ye, Sheng; Sun, Li; Yang, Fenhuan; Wong, Ka Chun; Westerdahl, Dane; Louie, Peter K K

    2018-01-23

    The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂), and oxidants (O x ) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO₂ and ozone on a newly introduced oxidant sensor.

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

    Science.gov (United States)

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

    2017-05-18

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

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

    Directory of Open Access Journals (Sweden)

    Jie Liu

    2017-05-01

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

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

    International Nuclear Information System (INIS)

    Naumenko, A P; Kostyukov, V N

    2012-01-01

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

  6. Cost-Effective Shaft Torque Observer for Condition Monitoring of Wind Turbines

    DEFF Research Database (Denmark)

    Perisic, Nevena; Kirkegaard, Poul Henning; Pedersen, Bo Juul

    2015-01-01

    Improvement of condition monitoring (CM) systems for wind turbines (WTs) and reduction of the cost of wind energy are possible if knowledge about the condition of different WT components is available. CM based on the WT drive train shaft torque signal can give a better understanding of the gearbox...... of the augmented Kalman filter with fading memory (AKFF) is compared with the augmented Kalman filter (AKF) using simulated data of theWT for different load conditions, measurement noise levels andWT fault scenarios. A multiple-model algorithm, based on a set of different Kalman filters, is designed for practical...

  7. 3rd International Conference on Condition Monitoring of Machinery in Non-Stationary Operations

    CERN Document Server

    Rubini, Riccardo; D'Elia, Gianluca; Cocconcelli, Marco; Chaari, Fakher; Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed

    2014-01-01

    This book presents the processings of the third edition of the Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO13) which was held in Ferrara, Italy. This yearly event merges an international community of researchers who met – in 2011 in Wroclaw (Poland) and in 2012 in Hammamet (Tunisia) – to discuss issues of diagnostics of rotating machines operating in complex motion and/or load conditions. The growing interest of the industrial world on the topics covered by the CMMNO13 involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition.The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. Signals acquired from machines often contain contributions from several different components as well as noise. Therefore, the major challenge of condition monitoring is to po...

  8. Condition monitoring of a motor-operated valve using estimated motor torque

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  9. An online condition monitoring system implemented an internet connectivity and FTP for low speed slew bearing

    Science.gov (United States)

    Caesarendra, W.; Kosasih, B.; Tjahjowidodo, T.; Ariyanto, M.; Daryl, LWQ; Pamungkas, D.

    2018-04-01

    Rapid and reliable information in slew bearing maintenance is not trivial issue. This paper presents the online monitoring system to assist maintenance engineer in order to monitor the bearing condition of low speed slew bearing in sheet metal company. The system is able to pass the vibration information from the place where the bearing and accelerometer sensors are attached to the data center; and from the data center it can be access by opening the online monitoring website from any place and by any person. The online monitoring system is built using some programming languages such as C language, MATLAB, PHP, HTML and CSS. Generally, the flow process is start with the automatic vibration data acquisition; then features are calculated from the acquired vibration data. These features are then sent to the data center; and form the data center, the vibration features can be seen through the online monitoring website. This online monitoring system has been successfully applied in School of Mechanical, Materials and Mechatronic Engineering, University of Wollongong.

  10. Intelligence and treaty ratification

    International Nuclear Information System (INIS)

    Sojka, G.L.

    1990-01-01

    What did the intelligence community and the Intelligence Committee di poorly in regard to the treaty ratification process for arms control? We failed to solve the compartmentalization problem/ This is a second-order problem, and, in general, analysts try to be very open; but there are problems nevertheless. There are very few, if any, people within the intelligence community who are cleared for everything relevant to our monitoring capability emdash short of probably the Director of Central Intelligence and the president emdash and this is a major problem. The formal monitoring estimates are drawn up by individuals who do not have access to all the information to make the monitoring judgements. This paper reports that the intelligence community did not present a formal document on either Soviet incentives of disincentives to cheat or on the possibility of cheating scenarios, and that was a mistake. However, the intelligence community was very responsive in producing those types of estimates, and, ultimately, the evidence behind them in response to questions. Nevertheless, the author thinks the intelligence community would do well to address this issue up front before a treaty is submitted to the Senate for advice and consent

  11. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  12. Wind turbine condition monitoring based on SCADA data using normal behavior models

    DEFF Research Database (Denmark)

    Schlechtingen, Meik; Santos, Ilmar; Achiche, Sofiane

    2013-01-01

    This paper proposes a system for wind turbine condition monitoring using Adaptive Neuro-Fuzzy Interference Systems (ANFIS). For this purpose: (1) ANFIS normal behavior models for common Supervisory Control And Data Acquisition (SCADA) data are developed in order to detect abnormal behavior...... the applicability of ANFIS models for monitoring wind turbine SCADA signals. The computational time needed for model training is compared to Neural Network (NN) models showing the strength of ANFIS in training speed. (2) For automation of fault diagnosis Fuzzy Interference Systems (FIS) are used to analyze...

  13. Information support of monitoring of technical condition of buildings in construction risk area

    Science.gov (United States)

    Skachkova, M. E.; Lepihina, O. Y.; Ignatova, V. V.

    2018-05-01

    The paper presents the results of the research devoted to the development of a model of information support of monitoring buildings technical condition; these buildings are located in the construction risk area. As a result of the visual and instrumental survey, as well as the analysis of existing approaches and techniques, attributive and cartographic databases have been created. These databases allow monitoring defects and damages of buildings located in a 30-meter risk area from the object under construction. The classification of structures and defects of these buildings under survey is presented. The functional capabilities of the developed model and the field of it practical applications are determined.

  14. Model-Based Sensor Placement for Component Condition Monitoring and Fault Diagnosis in Fossil Energy Systems

    Energy Technology Data Exchange (ETDEWEB)

    Mobed, Parham [Texas Tech Univ., Lubbock, TX (United States); Pednekar, Pratik [West Virginia Univ., Morgantown, WV (United States); Bhattacharyya, Debangsu [West Virginia Univ., Morgantown, WV (United States); Turton, Richard [West Virginia Univ., Morgantown, WV (United States); Rengaswamy, Raghunathan [Texas Tech Univ., Lubbock, TX (United States)

    2016-01-29

    Design and operation of energy producing, near “zero-emission” coal plants has become a national imperative. This report on model-based sensor placement describes a transformative two-tier approach to identify the optimum placement, number, and type of sensors for condition monitoring and fault diagnosis in fossil energy system operations. The algorithms are tested on a high fidelity model of the integrated gasification combined cycle (IGCC) plant. For a condition monitoring network, whether equipment should be considered at a unit level or a systems level depends upon the criticality of the process equipment, its likeliness to fail, and the level of resolution desired for any specific failure. Because of the presence of a high fidelity model at the unit level, a sensor network can be designed to monitor the spatial profile of the states and estimate fault severity levels. In an IGCC plant, besides the gasifier, the sour water gas shift (WGS) reactor plays an important role. In view of this, condition monitoring of the sour WGS reactor is considered at the unit level, while a detailed plant-wide model of gasification island, including sour WGS reactor and the Selexol process, is considered for fault diagnosis at the system-level. Finally, the developed algorithms unify the two levels and identifies an optimal sensor network that maximizes the effectiveness of the overall system-level fault diagnosis and component-level condition monitoring. This work could have a major impact on the design and operation of future fossil energy plants, particularly at the grassroots level where the sensor network is yet to be identified. In addition, the same algorithms developed in this report can be further enhanced to be used in retrofits, where the objectives could be upgrade (addition of more sensors) and relocation of existing sensors.

  15. Business Intelligence

    OpenAIRE

    Petersen, Anders

    2001-01-01

    Cílem této bakalářské práce je seznámení s Business Intelligence a zpracování vývojového trendu, který ovlivňuje podobu řešení Business Intelligence v podniku ? Business Activity Monitoring. Pro zpracování tohoto tématu byla použita metoda studia odborných pramenů, a to jak v českém, tak v anglickém jazyce. Hlavním přínosem práce je ucelený, v českém jazyce zpracovaný materiál pojednávající o Business Activity Monitoring. Práce je rozdělena do šesti hlavních kapitol. Prvních pět je věnováno p...

  16. Laboratory versus industrial cutting force sensor in tool condition monitoring system

    International Nuclear Information System (INIS)

    Szwajka, K

    2005-01-01

    Research works concerning the utilisation of cutting force measures in tool condition monitoring usually present results and deliberations based on laboratory sensors. These sensors are too fragile to be used in industrial practice. Industrial sensors employed on the factory floor are less accurate, and this must be taken into account when creating a tool condition monitoring strategy. Another drawback of most of these works is that constant cutting parameters are used for the entire tool life. This does not reflect industrial practice where the same tool is used at different feeds and depths of cut in sequential passes. This paper presents a comparison of signals originating from laboratory and industrial cutting force sensors. The usability of the sensor output was studied during a laboratory simulation of industrial cutting conditions. Instead of building mathematical models for the correlation between tool wear and cutting force, an FFBP artificial neural network was used to find which combination of input data would provide an acceptable estimation of tool wear. The results obtained proved that cross talk between channels has an important influence on cutting force measurements, however this input configuration can be used for a tool condition monitoring system

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

    Science.gov (United States)

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

    2016-08-01

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

  18. Are We Tracking the Dragon? Ensuring the Intelligence Community is Properly Postured to Monitor an Emerging China

    Science.gov (United States)

    2008-03-01

    franchise conferred by secrets is at the root of why U.S. intelligence made puzzle solving its principal Cold War business….For the mysteries…information...Enterprises (SOEs). As a corollary, local entrepreneurship has been emphasized. There has also been a growing application of market forces, and the...decentralize the economy and encourage entrepreneurship on the part of local leaders has robbed the center of much of its ability to force environmental

  19. Panorama Image Processing for Condition Monitoring with Thermography in Power Plant

    Energy Technology Data Exchange (ETDEWEB)

    Jeon, Byoung Joon; Kim, Tae Hwan; Kim, Soon Geol; Mo, Yoon Syub [UNETWARE, Seoul (Korea, Republic of); Kim, Won Tae [Kongju National University, Gongju (Korea, Republic of)

    2010-04-15

    In this paper, imaging processing study obtained from CCD image and thermography image was performed in order to treat easily thermographic data without any risks of personnel who conduct the condition monitoring for the abnormal or failure status occurrable in industrial power plants. This imaging processing is also applicable to the predictive maintenance. For confirming the broad monitoring, a methodology producting single image from the panorama technique was developed no matter how many cameras are employed, including fusion method for discrete configuration for the target. As results, image fusion from quick realtime processing was obtained and it was possible to save time to track the location monitoring in matching the images between CCTV and thermography

  20. Panorama Image Processing for Condition Monitoring with Thermography in Power Plant

    International Nuclear Information System (INIS)

    Jeon, Byoung Joon; Kim, Tae Hwan; Kim, Soon Geol; Mo, Yoon Syub; Kim, Won Tae

    2010-01-01

    In this paper, imaging processing study obtained from CCD image and thermography image was performed in order to treat easily thermographic data without any risks of personnel who conduct the condition monitoring for the abnormal or failure status occurrable in industrial power plants. This imaging processing is also applicable to the predictive maintenance. For confirming the broad monitoring, a methodology producting single image from the panorama technique was developed no matter how many cameras are employed, including fusion method for discrete configuration for the target. As results, image fusion from quick realtime processing was obtained and it was possible to save time to track the location monitoring in matching the images between CCTV and thermography

  1. Using modular neural networks to monitor accident conditions in nuclear power plants

    International Nuclear Information System (INIS)

    Guo, Z.

    1992-01-01

    Nuclear power plants are very complex systems. The diagnoses of transients or accident conditions is very difficult because a large amount of information, which is often noisy, or intermittent, or even incomplete, need to be processed in real time. To demonstrate their potential application to nuclear power plants, neural networks axe used to monitor the accident scenarios simulated by the training simulator of TVA's Watts Bar Nuclear Power Plant. A self-organization network is used to compress original data to reduce the total number of training patterns. Different accident scenarios are closely related to different key parameters which distinguish one accident scenario from another. Therefore, the accident scenarios can be monitored by a set of small size neural networks, called modular networks, each one of which monitors only one assigned accident scenario, to obtain fast training and recall. Sensitivity analysis is applied to select proper input variables for modular networks

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

    Energy Technology Data Exchange (ETDEWEB)

    Ramuhalli, Pradeep [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hirt, Evelyn H. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Coles, Garill A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bonebrake, Christopher A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ivans, William J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wootan, David W. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Mitchell, Mark R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-07-18

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

  3. An Information Theoretic Framework and Self-organizing Agent- based Sensor Network Architecture for Power Plant Condition Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Loparo, Kenneth [Case Western Reserve Univ., Cleveland, OH (United States); Kolacinski, Richard [Case Western Reserve Univ., Cleveland, OH (United States); Threeanaew, Wanchat [Case Western Reserve Univ., Cleveland, OH (United States); Agharazi, Hanieh [Case Western Reserve Univ., Cleveland, OH (United States)

    2017-01-30

    A central goal of the work was to enable both the extraction of all relevant information from sensor data, and the application of information gained from appropriate processing and fusion at the system level to operational control and decision-making at various levels of the control hierarchy through: 1. Exploiting the deep connection between information theory and the thermodynamic formalism, 2. Deployment using distributed intelligent agents with testing and validation in a hardware-in-the loop simulation environment. Enterprise architectures are the organizing logic for key business processes and IT infrastructure and, while the generality of current definitions provides sufficient flexibility, the current architecture frameworks do not inherently provide the appropriate structure. Of particular concern is that existing architecture frameworks often do not make a distinction between ``data'' and ``information.'' This work defines an enterprise architecture for health and condition monitoring of power plant equipment and further provides the appropriate foundation for addressing shortcomings in current architecture definition frameworks through the discovery of the information connectivity between the elements of a power generation plant. That is, to identify the correlative structure between available observations streams using informational measures. The principle focus here is on the implementation and testing of an emergent, agent-based, algorithm based on the foraging behavior of ants for eliciting this structure and on measures for characterizing differences between communication topologies. The elicitation algorithms are applied to data streams produced by a detailed numerical simulation of Alstom’s 1000 MW ultra-super-critical boiler and steam plant. The elicitation algorithm and topology characterization can be based on different informational metrics for detecting connectivity, e.g. mutual information and linear correlation.

  4. A case study of remaining storage life prediction using stochastic filtering with the influence of condition monitoring

    International Nuclear Information System (INIS)

    Wang, Zhaoqiang; Hu, Changhua; Wang, Wenbin; Zhou, Zhijie; Si, Xiaosheng

    2014-01-01

    Some systems may spend most of their time in storage, but once needed, must be fully functional. Slow degradation occurs when the system is in storage, so to ensure the functionality of these systems, condition monitoring is usually conducted periodically to check the condition of the system. However, taking the condition monitoring data may require putting the system under real testing situation which may accelerate the degradation, and therefore, shorten the storage life of the system. This paper presents a case study of condition-based remaining storage life prediction for gyros in the inertial navigation system on the basis of the condition monitoring data and the influence of the condition monitoring data taking process. A stochastic-filtering-based degradation model is developed to incorporate both into the prediction of the remaining storage life distribution. This makes the predicted remaining storage life depend on not only the condition monitoring data but also the testing process of taking the condition monitoring data, which the existing prognostic techniques and algorithms did not consider. The presented model is fitted to the real condition monitoring data of gyros testing using the maximum likelihood estimation method for parameter estimation. Comparisons are made with the model without considering the process of taking the condition monitoring data, and the results clearly demonstrate the superiority of the newly proposed model

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

    Science.gov (United States)

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

    2017-08-10

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

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

    Directory of Open Access Journals (Sweden)

    Cunji Zhang

    2015-12-01

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

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

    Science.gov (United States)

    Zhang, Cunji; Yao, Xifan; Zhang, Jianming

    2015-01-01

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

  8. Software for Intelligent System Health Management

    Science.gov (United States)

    Trevino, Luis C.

    2004-01-01

    This viewgraph presentation describes the characteristics and advantages of autonomy and artificial intelligence in systems health monitoring. The presentation lists technologies relevant to Intelligent System Health Management (ISHM), and some potential applications.

  9. Verification of the machinery condition monitoring technology by fault simulation tests

    International Nuclear Information System (INIS)

    Maehara, Takafumi; Watanabe, Yukio; Osaki, Kenji; Higuma, Koji; Nakano, Tomohito

    2009-01-01

    This paper shows the test items and equipments introduced by Japan Nuclear Energy Safety Organization to establish the monitoring technique for machinery conditions. From the result of vertical pump simulation tests, it was confirmed that fault analysis was impossible by measuring the accelerations on both motor and pump column pipes, however, was possible by measuring of pump shaft vibrations. Because hydraulic whirls by bearing wear had significant influences over bearing misalignments and flow rates, the monitoring trends must be done under the same condition (on bearing alignments and flow rates). We have confirmed that malfunctions of vertical pumps can be diagnosed using measured shaft vibration by ultrasonic sensors from outer surface of pump casing on the floor. (author)

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

    Science.gov (United States)

    Sinitsin, Vladimir V.; Shestakov, Aleksandr L.

    2017-09-01

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

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

    Science.gov (United States)

    Widerszal-Bazyl, M; Cieślak, R

    2000-01-01

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

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

    International Nuclear Information System (INIS)

    Sinitsin, Vladimir V; Shestakov, Aleksandr L

    2017-01-01

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

  13. Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation

    DEFF Research Database (Denmark)

    Soliman, Hammam Abdelaal Hammam; Wang, Huai; Gadalla, Brwene Salah Abdelkarim

    2015-01-01

    challenges. A capacitance estimation method based on Artificial Neural Network (ANN) algorithm is therefore proposed in this paper. The implemented ANN estimated the capacitance of the DC-link capacitor in a back-toback converter. Analysis of the error of the capacitance estimation is also given......In power electronic converters, reliability of DC-link capacitors is one of the critical issues. The estimation of their health status as an application of condition monitoring have been an attractive subject for industrial field and hence for the academic research filed as well. More reliable...... solutions are required to be adopted by the industry applications in which usage of extra hardware, increased cost, and low estimation accuracy are the main challenges. Therefore, development of new condition monitoring methods based on software solutions could be the new era that covers the aforementioned...

  14. A Two-Stage Diagnosis Framework for Wind Turbine Gearbox Condition Monitoring

    Directory of Open Access Journals (Sweden)

    Janet M. Twomey

    2013-01-01

    Full Text Available Advances in high performance sensing technologies enable the development of wind turbine condition monitoring system to diagnose and predict the system-wide effects of failure events. This paper presents a vibration-based two stage fault detection framework for failure diagnosis of rotating components in wind turbines. The proposed framework integrates an analytical defect detection method and a graphical verification method together to ensure the diagnosis efficiency and accuracy. The efficacy of the proposed methodology is demonstrated with a case study with the gearbox condition monitoring Round Robin study dataset provided by the National Renewable Energy Laboratory (NREL. The developed methodology successfully picked five faults out of seven in total with accurate severity levels without producing any false alarm in the blind analysis. The case study results indicated that the developed fault detection framework is effective for analyzing gear and bearing faults in wind turbine drive train system based upon system vibration characteristics.

  15. Condition monitoring of a check valve for nuclear power plants by means of acoustic emission technique

    International Nuclear Information System (INIS)

    Lee, M. R.; Lee, J. H.; Kim, J. T.; Kim, J. S.; Luk, V. K.

    2003-01-01

    This work performed in support of the International Nuclear Energy Research Institute (INERI) program, which was to develop and demonstrate advanced sensor and computational technology for on-line monitoring of the condition of components, structures, and systems in advanced and next-generation nuclear power plants (NPPs). This primary object of this work is to investigate advanced condition monitoring systems based on acoustic emission detection that can provide timely detection of check valve degeneration and service aging so that maintenance/replacement could be preformed prior to loss safety function. The research is focused on the capability of AE technique to provide diagnostic information useful in determining check valve aging and degradation check valve failure and undesirable operating modes. This work also includes the investigation and adaptation of several advanced sensor technologies such as accelerometer and advanced ultrasonic technique. In addition, this work will develop advanced sophisticated signal processing, noise reduction, and pattern recognition techniques and algorithms from check valve degradation.

  16. Development Of A Sensor Network Test Bed For ISD Materials And Structural Condition Monitoring

    International Nuclear Information System (INIS)

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

    2011-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-07-06

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

  18. Autonomous monitoring of control hardware to predict off-normal conditions using NIF automatic alignment systems

    International Nuclear Information System (INIS)

    Awwal, Abdul A.S.; Wilhelmsen, Karl; Leach, Richard R.; Miller-Kamm, Vicki; Burkhart, Scott; Lowe-Webb, Roger; Cohen, Simon

    2012-01-01

    Highlights: ► An automatic alignment system was developed to process images of the laser beams. ► System uses processing to adjust a series of control loops until alignment criteria are satisfied. ► Monitored conditions are compared against nominal values with an off-normal alert. ► Automated health monitoring system trends off-normals with a large image history. - Abstract: The National Ignition Facility (NIF) is a high power laser system capable of supporting high-energy-density experimentation as a user facility for the next 30 years. In order to maximize the facility availability, preventive maintenance enhancements are being introduced into the system. An example of such an enhancement is a camera-based health monitoring system, integrated into the automated alignment system, which provides an opportunity to monitor trends in measurements such as average beam intensity, size of the beam, and pixel saturation. The monitoring system will generate alerts based on observed trends in measurements to allow scheduled pro-active maintenance before routine off-normal detection stops system operations requiring unscheduled intervention.

  19. Autonomous monitoring of control hardware to predict off-normal conditions using NIF automatic alignment systems

    Energy Technology Data Exchange (ETDEWEB)

    Awwal, Abdul A.S., E-mail: awwal1@llnl.gov [Lawrence Livermore National Laboratory, Livermore, CA 94550 (United States); Wilhelmsen, Karl; Leach, Richard R.; Miller-Kamm, Vicki; Burkhart, Scott; Lowe-Webb, Roger; Cohen, Simon [Lawrence Livermore National Laboratory, Livermore, CA 94550 (United States)

    2012-12-15

    Highlights: Black-Right-Pointing-Pointer An automatic alignment system was developed to process images of the laser beams. Black-Right-Pointing-Pointer System uses processing to adjust a series of control loops until alignment criteria are satisfied. Black-Right-Pointing-Pointer Monitored conditions are compared against nominal values with an off-normal alert. Black-Right-Pointing-Pointer Automated health monitoring system trends off-normals with a large image history. - Abstract: The National Ignition Facility (NIF) is a high power laser system capable of supporting high-energy-density experimentation as a user facility for the next 30 years. In order to maximize the facility availability, preventive maintenance enhancements are being introduced into the system. An example of such an enhancement is a camera-based health monitoring system, integrated into the automated alignment system, which provides an opportunity to monitor trends in measurements such as average beam intensity, size of the beam, and pixel saturation. The monitoring system will generate alerts based on observed trends in measurements to allow scheduled pro-active maintenance before routine off-normal detection stops system operations requiring unscheduled intervention.

  20. Indicators for monitoring of safety operation and condition of nuclear power stations

    International Nuclear Information System (INIS)

    Manova, D.

    2001-01-01

    A common goal of all employees in the nuclear power field is safety operation of nuclear power stations. The evaluation and control of NPP safety operation are a part of the elements of safety management. The present report is related only to a part of the total assessment and control of the plant safety operation, namely - the indicator system for monitoring of Kozloduy NPP operation and condition. (author)

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

    Energy Technology Data Exchange (ETDEWEB)

    Ueno, K. [Building Science Corporation, Westford, MA (United States)

    2015-03-01

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

  2. Remote support services using condition monitoring and online sensor data for offshore oilfield

    OpenAIRE

    Du, Baoli

    2013-01-01

    Master's thesis in Offshore technology Based on advanced technology in condition monitoring and online sensor data, a new style of operation and maintenance management called remote operation and maintenance support services has been created to improve oil and gas E&P performance. This master thesis will look into how the remote support service is conducted including the concept, design, technology and management philosophies; the current implementation of remote support services in China,...

  3. A STUDY OF CONDITION MONITORING IN WATER PIPE USING VIBRATION SENSOR

    OpenAIRE

    角田, 裕紀

    2013-01-01

    This paper describes a study of condition monitoring in water pipe using vibration sensor. The vibration sensor composed of condenser microphone is placed at water pipe. This sensor picks up vibration by water flow. We estimate of flow rate from the output voltage waveform. It is high cost that any conventional flowmeter which use at outside pipe such as ultrasonic flowmeter. We develop a lower cost system and make measurement of flow rate in water pipe easier. The validity of sensing pipe vi...

  4. Investigation into the effect of fixturing systems on the design of condition monitoring for machining operations

    OpenAIRE

    Abbas, JK

    2013-01-01

    The global market competition has drawn the manufacturer’s attention on automated manufacturing processes using condition monitoring systems. These systems have been used for improving product quality, eliminating inspection, and enhancing manufacturing productivity. Fixtures are essential devices in machining processes to hold the tool or workpiece, hence they are influenced directly by the stability of the cutting tool. Therefore, tool and fixturing faults play an important part in the inac...

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

    Science.gov (United States)

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

    2011-01-01

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

  6. Energy-efficient strain gauges for the wireless condition monitoring systems in mechanical engineering

    Energy Technology Data Exchange (ETDEWEB)

    Berndt, Michael; Fellner, Thomas; Zeiser, Roderich; Wilde, Juergen [Freiburg Univ. (Germany). Dept. for Microsystems Engineering (IMTEK)

    2012-07-01

    This work focuses on the development of novel strain gauges, which are suited for the operation in autonomous wireless condition monitoring systems. For this purpose, capacitive as well as highly resistive strain gauges were designed and fabricated. The C- and R-sensors were utilised in combination with demonstration circuits, which integrate the circuits for instrumentation, A/D-conversion and furthermore comprise a microcontroller with a wireless transceiver system, all on a small separate printed wiring board. (orig.)

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

    Energy Technology Data Exchange (ETDEWEB)

    Zeigler, Kristine E.; Ferguson, Blythe A. [Savannah River National Laboratory, Aiken, South Carolina 29808 (United States)

    2012-07-01

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

  8. Monitoring growth condition of spring maize in Northeast China using a process-based model

    Science.gov (United States)

    Wang, Peijuan; Zhou, Yuyu; Huo, Zhiguo; Han, Lijuan; Qiu, Jianxiu; Tan, Yanjng; Liu, Dan

    2018-04-01

    Early and accurate assessment of the growth condition of spring maize, a major crop in China, is important for the national food security. This study used a process-based Remote-Sensing-Photosynthesis-Yield Estimation for Crops (RS-P-YEC) model, driven by satellite-derived leaf area index and ground-based meteorological observations, to simulate net primary productivity (NPP) of spring maize in Northeast China from the first ten-day (FTD) of May to the second ten-day (STD) of August during 2001-2014. The growth condition of spring maize in 2014 in Northeast China was monitored and evaluated spatially and temporally by comparison with 5- and 13-year averages, as well as 2009 and 2013. Results showed that NPP simulated by the RS-P-YEC model, with consideration of multi-scattered radiation inside the crop canopy, could reveal the growth condition of spring maize more reasonably than the Boreal Ecosystem Productivity Simulator. Moreover, NPP outperformed other commonly used vegetation indices (e.g., Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) for monitoring and evaluating the growth condition of spring maize. Compared with the 5- and 13-year averages, the growth condition of spring maize in 2014 was worse before the STD of June and after the FTD of August, and it was better from the third ten-day (TTD) of June to the TTD of July across Northeast China. Spatially, regions with slightly worse and worse growth conditions in the STD of August 2014 were concentrated mainly in central Northeast China, and they accounted for about half of the production area of spring maize in Northeast China. This study confirms that NPP is a good indicator for monitoring and evaluating growth condition because of its capacity to reflect the physiological characteristics of crops. Meanwhile, the RS-P-YEC model, driven by remote sensing and ground-based meteorological data, is effective for monitoring crop growth condition over large areas in a near real

  9. The condition monitoring system of turbine system components for nuclear power plants

    International Nuclear Information System (INIS)

    Ono, Shigetoshi

    2013-01-01

    The thermal and nuclear power plants have been imposed a stable supply of electricity. To certainly achieve this, we built the plant condition monitoring system based on the heat and mass balance calculation. If there are some performance changes on the turbine system components of their power plants, the heat and mass balance of the turbine system will change. This system has ability to detect the abnormal signs of their components by finding the changes of the heat and mass balance. Moreover we note that this system is built for steam turbine cycle operating with saturated steam conditions. (author)

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

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2014-11-01

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

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

    Science.gov (United States)

    Potočnik, Primož; Govekar, Edvard

    2017-09-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

  13. Run II performance of luminosity and beam condition monitors at CMS

    Energy Technology Data Exchange (ETDEWEB)

    Leonard, Jessica Lynn [DESY, Hamburg (Germany)

    2016-07-01

    The BRIL (Beam Radiation Instrumentation and Luminosity) system of CMS consists of instrumentation to measure the luminosity online and offline, and to monitor the LHC beam conditions inside CMS. An accurate luminosity measurement is essential to the CMS physics program, and measurement of the beam background is necessary to ensure safe operation of CMS. Many of the BRIL subsystems have been upgraded and others have been added for LHC Run II to complement the existing measurements. The beam condition monitor (BCM) consists of several sets of diamond sensors used to measure online luminosity and beam background with a single-bunch-crossing resolution. The BCM also detects when beam conditions become unfavorable for CMS running and may trigger a beam abort to protect the detector. The beam halo monitor (BHM) uses quartz bars to measure the background of the incoming beams at larger radii. The pixel luminosity telescope (PLT) consists of telescopes of silicon sensors designed to provide a CMS online and offline luminosity measurement. In addition, the forward hadronic calorimeter (HF) delivers an independent luminosity measurement, making the whole system robust and allowing for cross-checks of the systematics. An overview of the performance during 2015 LHC running for the new/updated BRIL subsystems will be given, including the uncertainties of the luminosity measurements.

  14. Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods

    Directory of Open Access Journals (Sweden)

    Peng Guo

    2011-11-01

    Full Text Available Condition Monitoring (CM of wind turbines can greatly reduce the maintenance costs for wind farms, especially for offshore wind farms. A new condition monitoring method for a wind turbine gearbox using temperature trend analysis is proposed. Autoassociative Kernel Regression (AAKR is used to construct the normal behavior model of the gearbox temperature. With a proper construction of the memory matrix, the AAKR model can cover the normal working space for the gearbox. When the gearbox has an incipient failure, the residuals between AAKR model estimates and the measurement temperature will become significant. A moving window statistical method is used to detect the changes of the residual mean value and standard deviation in a timely manner. When one of these parameters exceeds predefined thresholds, an incipient failure is flagged. In order to simulate the gearbox fault, manual temperature drift is added to the initial Supervisory Control and Data Acquisitions (SCADA data. Analysis of simulated gearbox failures shows that the new condition monitoring method is effective.

  15. Results of Recent DOE Research on Development of Cable Condition Monitoring and Aging Management Technologies

    International Nuclear Information System (INIS)

    Campbell, C.J.; McConkey, J.B.; Hashemian, H.M.; Sexton, C.D.; Cummins, D.S.

    2012-01-01

    Analysis and Measurement Services (AMS) Corporation has been conducting two research projects focused on understanding cable aging and developing cable condition monitoring technologies for nuclear power plants. The goal of the first project is to correlate cable faults with testing techniques that can identify and locate the faults whether they are in the cable, conductor, or the insulation. This project involves laboratory experiments using low and medium voltage cable types typically installed in nuclear power plants. The second project is focused on development of an integrated cable condition monitoring system for nuclear facilities. This system integrates a number of cable testing and cable condition monitoring techniques, such as the time domain reflectometry (TDR), frequency domain reflectometry (FDR), inductance, capacitance, resistance (LCR), reverse TDR (RTDR), current-to-voltage (IV) for testing of nuclear instrumentation sensors, insulation resistance (IR) and other techniques. The purpose of the project is to combine all proven technologies into one system to detect and pinpoint problems in cable circuits as well as cable insulation, shield, or jacket material. (author)

  16. Demonstration of TEG-powered wireless autonomous transducer solution for condition monitoring in industrial environment

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Ziyang; Patrascu, Mihai; Su, Jiale; Vullers, Ruud J.M. [imec the Netherlands, Eindhoven (Netherlands)

    2011-07-01

    Imec/Holst Centre focuses on the development of wireless autonomous transducer solution, which is poised to bring about huge impact in the sectors of health care, machinery, transportation and energy, etc. In this paper, we first showcase a TEG-powered demonstration for condition monitoring in industrial environment. Composing of sensor-actuator, front-end interface, digital signal processing unit and radio, the developed wireless sensor node can monitor the changing operating condition, i.e. the loading on a rolling-element bearing, on a rotating shaft. The use of a specially designed TEG, working in tandem with an energy storage device, can significantly improve the energy autonomy of the condition monitoring system as a whole. The different components in the demonstration are presented. Subsequently, the experimental results of vibration signature analysis are exhibited. On one hand, the presented demonstration sheds light on the huge potential of thermoelectric energy harvesting to achieve energy autonomy. On the other hand, it also points to the aspects that are in need of further development, namely miniaturization and cost reduction of energy harvesters. Aimed at the delivery of cost-effective miniaturized thermoelectric harvesting devices, imec/Holst Centre has been tackling with the relevant challenges by resorting to, but not limited to, its expertise in micromachining. An update on the latest research results is subsequently given with regard to various micromachined thermoelectric devices, fully fledged wearable TEGs with custom designed package and thermoelectric material property optimization. (orig.)

  17. Intelligent robotic tracker

    Science.gov (United States)

    Otaguro, W. S.; Kesler, L. O.; Land, K. C.; Rhoades, D. E.

    1987-01-01

    An intelligent tracker capable of robotic applications requiring guidance and control of platforms, robotic arms, and end effectors has been developed. This packaged system capable of supervised autonomous robotic functions is partitioned into a multiple processor/parallel processing configuration. The system currently interfaces to cameras but has the capability to also use three-dimensional inputs from scanning laser rangers. The inputs are fed into an image processing and tracking section where the camera inputs are conditioned for the multiple tracker algorithms. An executive section monitors the image processing and tracker outputs and performs all the control and decision processes. The present architecture of the system is presented with discussion of its evolutionary growth for space applications. An autonomous rendezvous demonstration of this system was performed last year. More realistic demonstrations in planning are discussed.

  18. Modelling and measurement of wear particle flow in a dual oil filter system for condition monitoring

    DEFF Research Database (Denmark)

    Henneberg, Morten; Eriksen, René Lynge; Fich, Jens

    2016-01-01

    . The quantity of wear particles in gear oil is analysed with respect to system running conditions. It is shown that the model fits the data in terms of startup “particle burst” phenomenon, quasi-stationary conditions during operation, and clean-up filtration when placed out of operation. In order to establish...... boundary condition for particle burst phenomenon, the release of wear particles from a pleated mesh filter is measured in a test rig and included in the model. The findings show that a dual filter model, with startup phenomenon included, can describe trends in the wear particle flow observed in the gear...... particle generation is made possible by model parameter estimation and identification of an unintended lack of filter change. The model may also be used to optimise system and filtration performance, and to enable continuous condition monitoring....

  19. Assessment of monitored energy use and thermal comfort conditions in mosques in hot-humid climates

    Energy Technology Data Exchange (ETDEWEB)

    Al-Homoud, Mohammad S.; Abdou, Adel A.; Budaiwi, Ismail M. [Architectural Engineering Department, KFUPM, Dhahran 31261 (Saudi Arabia)

    2009-06-15

    In harsh climatic regions, buildings require air-conditioning in order to provide an acceptable level of thermal comfort. In many situations buildings are over cooled or the HVAC system is kept running for a much longer time than needed. In some other situations thermal comfort is not achieved due to improper operation practices coupled with poor maintenance and even lack it, and consequently inefficient air-conditioning systems. Mosques represent one type of building that is characterized by their unique intermittent operating schedule determined by prayer times, which vary continuously according to the local solar time. This paper presents the results of a study designed to monitor energy use and thermal comfort conditions of a number of mosques in a hot-humid climate so that both energy efficiency and the quality of thermal comfort conditions especially during occupancy periods in such intermittently operated buildings can be assessed accurately. (author)

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

    Science.gov (United States)

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

    2015-07-01

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

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

    International Nuclear Information System (INIS)

    Strączkiewicz, M; Barszcz, T; Jabłoński, A

    2015-01-01

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

  2. Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring

    Directory of Open Access Journals (Sweden)

    Peng Wei

    2018-01-01

    Full Text Available The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series for carbon monoxide (CO, nitric oxide (NO, nitrogen dioxide (NO2, and oxidants (Ox were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor.

  3. Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring

    Science.gov (United States)

    Ning, Zhi; Ye, Sheng; Sun, Li; Yang, Fenhuan; Wong, Ka Chun; Westerdahl, Dane; Louie, Peter K. K.

    2018-01-01

    The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidants (Ox) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor. PMID:29360749

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-09-17

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

  5. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  6. Intelligent tecnology of information analysis and quantitative evaluation of condition with preliminary and inaccurate data of current observations

    Directory of Open Access Journals (Sweden)

    Yu. Savva

    1999-08-01

    Full Text Available The article presents an approach to design of data processing systems of ecological monitoring based on modern information technologies: data mining, genetic algorithms and geoinformatics.

  7. Intelligent mechatronics; Intelligent mechatronics

    Energy Technology Data Exchange (ETDEWEB)

    Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

    1995-10-01

    Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

  8. Condition monitoring of oil-impregnated paper bushings using extension neural network, Gaussian mixture and hidden Markov models

    CSIR Research Space (South Africa)

    Miya, WS

    2008-10-01

    Full Text Available was performed in MATLAB simulation environment with an IntelTM CoreTM2 Duo computer operating at a processor speed of 3 GHz. ENN simulation procedures entail the use of optimal learning rate, a minimum number of epochs (also used as a training.... Intelligent Transformer Monitoring System Utilizing Neuro-Fuzzy Technique Approach http://www.pserc.org/cgipserc/getbig/publicati/reports/2004report/shures hi_smart_sensor_final_report.pdf, Last accessed 27 September 2007. [3] Wang M H. Extension Neural...

  9. Real Time In-circuit Condition Monitoring of MOSFET in Power Converters

    Directory of Open Access Journals (Sweden)

    Shakeb A. Khan

    2015-03-01

    Full Text Available Abstract:This paper presents simple and low-cost, real time in-circuit condition monitoring of MOSFET in power electronic converters. Design metrics requirements like low cost, small size, high power factor, low percentage of total harmonic distortion etc. requires the power electronic systems to operate at high frequencies and at high power density. Failures of power converters are attributed largely by aging of power MOSFETs at high switching frequencies. Therefore, real time in-circuit prognostic of MOSFET needs to be done before their selection for power system design. Accelerated aging tests are performed in different circuits to determine the wear out failure of critical components based on their parametric degradation. In this paper, the simple and low-cost test beds are designed for real time in-circuit prognostics of power MOSFETs. The proposed condition monitoring scheme helps in estimating the condition of MOSFETs at their maximum rated operating condition and will aid the system designers to test their reliability and benchmark them before selecting in power converters.

  10. Nurse occupational burnout and patient-rated quality of care: The boundary conditions of emotional intelligence and demographic profiles.

    Science.gov (United States)

    Chao, Minston; Shih, Chih-Ting; Hsu, Shu-Fen

    2016-01-01

    Most previous studies on the relationship between occupational burnout and the quality of care among nurses have used self-reported data on the quality of care from nurses, thus rendering evaluating the relationship between burnout and the quality of care difficult. Hospitals increasingly hire contract nurses and high turnover rates remain a concern. Little is known about whether nurses' emotional intelligence and demographic factors such as contract status, tenure, and marital status affect the quality of care when burnout occurs. This study investigated the relationship between burnout and patient-rated quality of care and investigated the moderating role of emotional intelligence and demographic variables. Hierarchical moderated regression was used to analyze 98 sets of paired data obtained from nurses and their patients at a teaching hospital in northern Taiwan. The results suggest that occupational burnout has a less unfavorable effect on the quality of care from permanent, married, and senior nurses. Nursing management should pay particular attention to retaining permanent, married, and senior nurses. To ensure a sustainable nursing workforce in the future, newly graduated registered nurses should have access to permanent positions and opportunities for long-term professional development. In addition, married nurses should be provided with flexible work-family arrangements to ensure their satisfaction in the nursing profession. © 2015 Japan Academy of Nursing Science.

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

    Directory of Open Access Journals (Sweden)

    Tharoeun Thap

    2016-04-01

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

  12. RECREATION MONITORING OF RESOURCE CONDITIONS IN THE KRONOTSKY STATE NATURAL BIOSPHERE PRESERVE (KAMCHATKA: AN INITIAL ASSESSMENT

    Directory of Open Access Journals (Sweden)

    Anna Zavadskaya

    2011-01-01

    Full Text Available The paper describes assessment and monitoring program which has been designed and initiated for monitoring recreational impacts in some wildernesses areas of Kamchatka. The framework of the recreational assessment was tested through its application in a case study conducted during the summer 2008 in the Kronotsky State Natural Biosphere Preserve (the Kamchatka peninsula, Russia. The overall objective of the case study was to assess the existing campsite and trail recreation impacts and to establish a network of key sites for the subsequent long-term impact monitoring. The detailed assessment of different components of natural complexes of the Kronotsky State Natural Preserve and the obtained maps of their ecological conditions showed that some sites had been highly disturbed. The results of these works have given rise to a concern that the intensive use of these areas would make an unacceptable impact on the nature. Findings of our initial work corroborate the importance of founding wilderness management programs on knowledge about the trail and campsite impacts and emphasize the necessity of adopting the recreational assessment and monitoring framework to the practice of decision-making.

  13. Monitoring and analysis of air emissions based on condition models derived from process history

    Directory of Open Access Journals (Sweden)

    M. Liukkonen

    2016-12-01

    Full Text Available Evaluation of online information on operating conditions is necessary when reducing air emissions in energy plants. In this respect, automated monitoring and control are of primary concern, particularly in biomass combustion. As monitoring of emissions in power plants is ever more challenging because of low-grade fuels and fuel mixtures, new monitoring applications are needed to extract essential information from the large amount of measurement data. The management of emissions in energy boilers lacks economically efficient, fast, and competent computational systems that could support decision-making regarding the improvement of emission efficiency. In this paper, a novel emission monitoring platform based on the self-organizing map method is presented. The system is capable, not only of visualizing the prevailing status of the process and detecting problem situations (i.e. increased emission release rates, but also of analyzing these situations automatically and presenting factors potentially affecting them. The system is demonstrated using measurement data from an industrial circulating fluidized bed boiler fired by forest residue as the primary fuel and coal as the supporting fuel.

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

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jung-Taek (Korea Atomic Energy Research Institute, Daejon, Korea); Luk, Vincent K.

    2005-05-01

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

  15. Wind Turbine Condition Monitoring Strategy through Multiway PCA and Multivariate Inference

    Directory of Open Access Journals (Sweden)

    Francesc Pozo

    2018-03-01

    Full Text Available This article states a condition monitoring strategy for wind turbines using a statistical data-driven modeling approach by means of supervisory control and data acquisition (SCADA data. Initially, a baseline data-based model is obtained from the healthy wind turbine by means of multiway principal component analysis (MPCA. Then, when the wind turbine is monitorized, new data is acquired and projected into the baseline MPCA model space. The acquired SCADA data are treated as a random process given the random nature of the turbulent wind. The objective is to decide if the multivariate distribution that is obtained from the wind turbine to be analyzed (healthy or not is related to the baseline one. To achieve this goal, a test for the equality of population means is performed. Finally, the results of the test can determine that the hypothesis is rejected (and the wind turbine is faulty or that there is no evidence to suggest that the two means are different, so the wind turbine can be considered as healthy. The methodology is evaluated on a wind turbine fault detection benchmark that uses a 5 MW high-fidelity wind turbine model and a set of eight realistic fault scenarios. It is noteworthy that the results, for the presented methodology, show that for a wide range of significance, α ∈ [ 1 % , 13 % ] , the percentage of correct decisions is kept at 100%; thus it is a promising tool for real-time wind turbine condition monitoring.

  16. 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.

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

    Science.gov (United States)

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

    2014-04-01

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

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

    International Nuclear Information System (INIS)

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

    1998-05-01

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

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

    International Nuclear Information System (INIS)

    Roe, S.; Mba, D.

    2009-01-01

    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

  20. Intelligent Structured Intermittent Auscultation (ISIA): evaluation of a decision-making framework for fetal heart monitoring of low-risk women

    Science.gov (United States)

    2014-01-01

    Background Research-informed fetal monitoring guidelines recommend intermittent auscultation (IA) for fetal heart monitoring for low-risk women. However, the use of cardiotocography (CTG) continues to dominate many institutional maternity settings. Methods A mixed methods intervention study with before and after measurement was undertaken in one secondary level health service to facilitate the implementation of an initiative to encourage the use of IA. The intervention initiative was a decision-making framework called Intelligent Structured Intermittent Auscultation (ISIA) introduced through an education session. Results Following the intervention, medical records review revealed an increase in the use of IA during labour represented by a relative change of 12%, with improved documentation of clinical findings from assessments, and a significant reduction in the risk of receiving an admission CTG (RR 0.75, 95% CI, 0.60 – 0.95, p = 0.016). Conclusion The ISIA informed decision-making framework transformed the practice of IA and provided a mechanism for knowledge translation that enabled midwives to implement evidence-based fetal heart monitoring for low risk women. PMID:24884597