Process Control System Fault Diagnosis: A Bayesian Approach

by Fei Qi, Biao Huang, Ruben Gonzalez

Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc., Canada Biao Huang, University of Alberta, Canada Data-driven Inferential Solutions for Control System Fault Diagnosis A typical modern process system consists of hundreds or even thousands of control loops, which are overwhelming for plant personnel to monitor. The main objectives of this book are to establish a new framework for control system fault diagnosis, to synthesize observations of different monitors with a prior knowledge, and to pinpoint possible abnormal sources on the basis of Bayesian theory. Process Control System Fault Diagnosis: A Bayesian Approach consolidates results developed by the authors, along with the fundamentals, and presents them in a systematic way. The book provides a comprehensive coverage of various Bayesian methods for control system fault diagnosis, along with a detailed tutorial. The book is useful for graduate students and researchers as a monograph and as a reference for state-of-the-art techniques in control system performance monitoring and fault diagnosis. Since several self-contained practical examples are included in the book, it also provides a place for practicing engineers to look for solutions to their daily monitoring and diagnosis problems. Key features: * A comprehensive coverage of Bayesian Inference for control system fault diagnosis. * Theory and applications are self-contained. * Provides detailed algorithms and sample Matlab codes. * Theory is illustrated through benchmark simulation examples, pilot-scale experiments and industrial application. Process Control System Fault Diagnosis: A Bayesian Approach is a comprehensive guide for graduate students, practicing engineers, and researchers who are interests in applying theory to practice.

• Format: Hardcover
• Language: English
• ISBN: 1118770617
• ISBN13: 9781118770610
• Release Date: September 2016
• Publisher: Wiley
• Length: 360 Pages
• Weight: 1.50 lbs.
• Dimensions: 0.9" x 6.6" x 9.6"