Safety in industrial process and production plants is a concern of rising importance but because the control devices which are now exploited to improve the performance of industrial processes include both sophisticated digital system design techniques and complex hardware, there is a higher probability of failure. Control systems must include automatic supervision of closed-loop operation to detect and isolate malfunctions quickly. A promising method for solving this problem is "analytical redundancy", in which residual signals are obtained and an accurate model of the system mimics real process behaviour. If a fault occurs, the residual signal is used to diagnose and isolate the malfunction. This book focuses on model identification oriented to the analytical approach of fault diagnosis and identification covering: choice of model structure; parameter identification; residual generation; and fault diagnosis and isolation. Sample case studies are used to demonstrate the application of these techniques.
Annotation This is Volume 1 of five volumes that comprise the proceedings of the June 2002 conference, sponsored by the International Gas Turbine Institute (IGTI), a technical institute of the American Society of Mechanical Engineers. The purpose of the conference was to facilitate international exchange and development of educational and technical information related to the design, application, manufacture, operation, maintenance, and environmental impact of all types of gas engines. With an emphasis upon the need for more efficient, cleaner, and more reliable gas turbines, the approximately 130 articles cover various technical aspects of aircraft engines; coal, biomass, and alternative fuels; combustion and fuels; education; electric power; and vehicular and small turbomachines. There is no subject index. Annotation c. Book News, Inc., Portland, OR (booknews.com).
This book investigates observer-fault estimation techniques in detail, while also highlighting recent research and findings regarding fault estimation. Many practical control systems are subject to possible malfunctions, which may cause significant performance loss or even system instability. To improve the reliability, performance and safety of dynamical systems, fault diagnosis techniques are now receiving considerable attention, both in research and applications, and have been the subject of intensive investigations. Fault detection – the essential first step in fault diagnosis – is a binary decision-making process used to determine whether or not a fault has occurred. In turn, fault isolation is used to identify the location of the faulty component, while fault estimation is used to identify the size of the fault online. Compared with the problems involved in fault detection and isolation, fault estimation is considerably more challenging.