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.

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.