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Power Plant Surveillance and Diagnostics

Applied Research with Artificial Intelligence

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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

1 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 ofNeuro-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.

Produktdetails

Erscheinungsdatum
12. Juni 2019
Sprache
englisch
Auflage
1st ed. 2002
Seitenanzahl
386
Dateigröße
37,94 MB
Reihe
Power Systems
Herausgegeben von
Da Ruan, Paolo F. Fantoni
Kopierschutz
mit Wasserzeichen versehen
Produktart
EBOOK
Dateiformat
PDF
ISBN
9783662049457

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