Buch, Englisch, 386 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1620 g
Reihe: Power Systems
Applied Research with Artificial Intelligence
Buch, Englisch, 386 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1620 g
Reihe: Power Systems
ISBN: 978-3-540-43247-0
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Energietechnik | Elektrotechnik Alternative und erneuerbare Energien
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Technische Wissenschaften Energietechnik | Elektrotechnik Windkraftanlagen, Wasserkraftanlagen
- Technische Wissenschaften Energietechnik | Elektrotechnik Planung und Betrieb von Kraftwerken
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
Weitere Infos & Material
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.
