Model Based Fault Diagnosis In Dynamic Systems Using Identification Techniques

Download or read book Model-based Fault Diagnosis in Dynamic Systems Using Identification Techniques written by Silvio Simani and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.