Power Plant Surveillance and Diagnostics: Applied Research with Artificial Intelligence

Author:   Da Ruan ,  Paolo F. Fantoni
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2002 ed.
ISBN:  

9783540432470


Pages:   386
Publication Date:   01 April 2002
Format:   Hardback
Availability:   In Print   Availability explained
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Power Plant Surveillance and Diagnostics: Applied Research with Artificial Intelligence


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Overview

This edited book is directed primarily to the discussion of the most recent developments and on-going research related to all areas pertaining to plant surveillance and diagnosis. The secondary aim of this book is to identify the successful applications of already well-settled methodological tools in the field. It will highlight advantages of intelligent systems, AI techniques, and integration of soft computing tools and traditional tools, for a better service in all aspects related to power plant surveillance and diagnostics. It also reports recent research results and provides a state of the art on AI in power plant surveillance and diagnostics. The book especially focuses on theoretical and analytical solutions to the problems of real interest in AI techniques, possibly combined with other traditional computing tools.

Full Product Details

Author:   Da Ruan ,  Paolo F. Fantoni
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2002 ed.
Dimensions:   Width: 15.50cm , Height: 2.20cm , Length: 23.50cm
Weight:   1.620kg
ISBN:  

9783540432470


ISBN 10:   3540432477
Pages:   386
Publication Date:   01 April 2002
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

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.

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