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.
How can prenatal testing help your patients? In utero diagnosis has undergone an amazing revolution in recent years. More tests are available; the indications for prenatal diagnosis have expanded – you can now advise your patients about disorders you could not have previously detected. Medical training for obstetricians, medical geneticists, and genetic counselors has not kept pace with these developments. Clinical exposure to common and unusual problems in prenatal diagnosis is limited. Prenatal Diagnosis: Clinical Cases and Challenges, based on the authors’ several decades of experiences, fills this gap. Real cases portray diagnostic problems as a route to the underlying biology, the available testing options, and the results that might be obtained. The authors discuss the challenges of management, interpretation, and counseling. Cases used throughout emphasize three types of clinical problems: Chromosomal abnormalities Mendelian disorders Fetal structural abnormalities The decision to enter the world of prenatal diagnosis should be very carefully considered by any prospective mother. Prenatal Diagnosis: Clinical Cases and Challenges will help you discuss the issues in an informed manner with your patients.
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