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.
