Power Plant Surveillance and Diagnostics

Lieferzeit: Lieferbar innerhalb 14 Tagen

160,49 

Applied Research with Artificial Intelligence, Power Systems

ISBN: 3642077544
ISBN 13: 9783642077548
Herausgeber: Da Ruan/Paolo F Fantoni
Verlag: Springer Verlag GmbH
Umfang: xiii, 386 S.
Erscheinungsdatum: 06.12.2010
Auflage: 1/2002
Produktform: Kartoniert
Einband: KT

Edited book reporting recent results of AI research in power plant surveillance and diagnosticsHigh quality and applicability of the contributions through a thorough peer-reviewing processCondition monitoring and early fault detection both provide efficient energy systems at lower costs

Artikelnummer: 1563679 Kategorie:

Beschreibung

Edited book reporting recent results in AI research in power plant surveillance and diagnostics. High quality and applicability of the contributions through a thorough peer-reviewing process. Condition Monitoring and Early Fault Detection provide for better efficiency of energy systems, at lower costs. Inhalt Featured Topics: Analysis of important issues relating to specification, development and use of systems for computer-assisted plant surveillance and diagnosis.- Empirical and analytical methods for on-line calibration monitoring and data reconciliation.- Noise analysis methods for early fault detection, condition monitoring, leak detection and loose part monitoring.- Predictive maintenance and condition monitoring techniques.- Empirical and analytical methods for fault detection and recognition.

Inhaltsverzeichnis

Featured Topics: Analysis of important issues relating to specification, development and use of systems for computer-assisted plant surveillance and diagnosis.- Empirical and analytical methods for on-line calibration monitoring and data reconciliation.- Noise analysis methods for early fault detection, condition monitoring, leak detection and loose part monitoring.- Predictive maintenance and condition monitoring techniques.- Empirical and analytical methods for fault detection and recognition.

Autorenporträt

Inhaltsangabe1 Modern Approaches and Advanced Applications for Plant Surveillance and Diagnostics: An Overview.- 2 Regulatory Treatment of On-line Surveillance and Diagnostic Systems.- 3 Optimized Maintenance and Management of Ageing of Critical Equipment in Nuclear Power Plants.- 4 Overview of Recent KFM AEKI Activities in the Field of Plant Surveillance and Diagnostics.- 5 Adaptive Model-Based Control of Non-linear Plants Using Soft Computing Techniques.- 6 Bayesian Networks in Decision Support.- 7 Hidden Markov Model Based Transient Identification in NPPs.- 8 Expert System-Based Implementation of Failure Detection.- 9 Detection of Incipient Signal or Process Faults in a Co-Generation Plant Using the Plant ECM System.- 10 On-Line Determination of the MTC (Moderator Temperature Coefficient) by Neutron Noise and Gamma-Thermometer Signals.- 11 Detecting Impacting of BWR Instrument Tubes by Wavelet Analysis.- 12 Development of Advanced Core Noise Monitoring System for a Boiling Water Reactor.- 13 Diagnosis of Measuring Systems Using Cluster Analysis Applied to Hydrostatic Water Level Measurement.- 14 A Hybrid Fuzzy-Fractal Approach for Time Series Analysis and Prediction and Its Applications to Plant Monitoring.- 15 Failure Detection Using a Fuzzy Neural Network with an Automatic Input Selection Algorithm.- 16 Artificial Neural Networks Modeling as a Diagnostic and Decision Making Tool.- 17 A New Approach for Transient Identification with "Don't Know" Response Using Neural Networks.- 18 Planning Surveillance Test Policies Through Genetic Algorithms.- 19 A Possibilistic Approach for Transient Identification with "Don't Know" Response Capability Optimized by Genetic Algorithm.- 20 Regularization of Ill-Posed Surveillance and Diagnostic Measurements.- 21 Application of Neuro-Fuzzy Logic for Early Detection and Diagnostics in Gas Plants and Combustion Chambers at ENEA.- 22 ALADDIN: Event Recognition & Fault Diagnosis for Process & Machine Condition Monitoring.- 23 PEANO and On-Line Monitoring Techniques for Calibration Reduction of Process Instrumentation in Power Plants.

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