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Power Plant Surveillance and Diagnostics - Herausgegeben:Ruan, Da; Fantoni, Paolo F.
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Herausgegeben:Ruan, Da; Fantoni, Paolo F.:

Power Plant Surveillance and Diagnostics - Paperback

2010, ISBN: 9783642077548

[ED: Softcover], [PU: Springer / Springer Berlin Heidelberg / Springer, Berlin], Edited book reporting recent results in AI research in power plant surveillance and diagnostics. High qual… More...

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Power Plant Surveillance and Diagnostics - Paolo F. Fantoni
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Paolo F. Fantoni:

Power Plant Surveillance and Diagnostics - Paperback

2006, ISBN: 9783642077548

[ED: Taschenbuch], [PU: Springer Berlin Heidelberg], Neuware - Edited book reporting recent results in AI research in power plant surveillance and diagnostics. High quality and applicabil… More...

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Power Plant Surveillance and Diagnostics - Ruan, Da|Fantoni, Paolo F.
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Ruan, Da|Fantoni, Paolo F.:
Power Plant Surveillance and Diagnostics - Paperback

2010

ISBN: 3642077544

[EAN: 9783642077548], Neubuch, [PU: Springer Berlin Heidelberg], BAYESIANNETWORK ARTIFICIALINTELLIGENCE ARTIFICIALNEURALNETWORK COGNITION EXPERTSYSTEM FUZZY FUZZYLOGIC GENETICALGORITHM HI… More...

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Power Plant Surveillance and Diagnostics - Ruan, Da Fantoni, Paolo F.
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Ruan, Da Fantoni, Paolo F.:
Power Plant Surveillance and Diagnostics - First edition

2010, ISBN: 9783642077548

Paperback

[ED: Kartoniert / Broschiert], [PU: Springer Berlin Heidelberg], Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Edited book reporting rec… More...

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Power Plant Surveillance and Diagnostics - Ruan, Da Fantoni, Paolo F.
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Ruan, Da Fantoni, Paolo F.:
Power Plant Surveillance and Diagnostics - First edition

2010, ISBN: 9783642077548

Paperback

[ED: Kartoniert / Broschiert], [PU: Springer Berlin Heidelberg], Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Edited book reporting rec… More...

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Bibliographic data of the best matching book

Details of the book
Power Plant Surveillance and Diagnostics: Applied Research with Artificial Intelligence (Power Systems)

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.

Details of the book - Power Plant Surveillance and Diagnostics: Applied Research with Artificial Intelligence (Power Systems)


EAN (ISBN-13): 9783642077548
ISBN (ISBN-10): 3642077544
Hardcover
Paperback
Publishing year: 2010
Publisher: Ruan, Da, Springer Berlin Heidelberg
396 Pages
Weight: 0,598 kg
Language: eng/Englisch

Book in our database since 2012-09-22T14:03:31-04:00 (New York)
Detail page last modified on 2024-02-10T14:32:12-05:00 (New York)
ISBN/EAN: 3642077544

ISBN - alternate spelling:
3-642-07754-4, 978-3-642-07754-8
Alternate spelling and related search-keywords:
Book author: fanton, fantoni
Book title: plant power, artificial intelligence, surveillance


Information from Publisher

Author: Da Ruan; Paolo F. Fantoni
Title: Power Systems; Power Plant Surveillance and Diagnostics - Applied Research with Artificial Intelligence
Publisher: Springer; Springer Berlin
386 Pages
Publishing year: 2010-12-06
Berlin; Heidelberg; DE
Printed / Made in
Language: English
160,49 € (DE)
164,99 € (AT)
177,00 CHF (CH)
POD
XIII, 386 p.

BC; Hardcover, Softcover / Technik/Elektronik, Elektrotechnik, Nachrichtentechnik; Elektrotechnik; Verstehen; Bayesian network; artificial intelligence; artificial neural network; cognition; expert system; fuzzy; fuzzy logic; genetic algorithm; hidden Markov model; modeling; neural network; Electrical Power Engineering; Mechanical Power Engineering; Renewable Energy; Artificial Intelligence; Computer-Aided Engineering (CAD, CAE) and Design; Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Energietechnik, Elektrotechnik und Energiemaschinenbau; Alternative und erneuerbare Energiequellen und -technik; Künstliche Intelligenz; Computer-Aided Design (CAD); Wahrscheinlichkeitsrechnung und Statistik; BB

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.
Edited book reporting recent results of 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 both provide efficient energy systems at lower costs

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