process control system fault de gonzalez ruben (17 resultados)

Condición: New. pp. 368.

Condición: New. pp. 368.

Condición: New. pp. 368.

Condición: New.

Hardcover. Condición: new. Hardcover. 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. Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: New. In.

Hardcover. Condición: New.

Hardback. Condición: New. New copy - Usually dispatched within 4 working days. 598.

Condición: New. Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc. Series: Wiley Series in Dynamics and Control of Electromechanical Systems. Num Pages: 360 pages, illustrations. BIC Classification: TDCB; TGP; TJ. Category: (P) Professional & Vocational. Dimension: 249 x 175 x 22. Weight in Grams: 714. . 2016. 1st Edition. Hardcover. . . . .

Hardcover. Condición: new. Hardcover. 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. Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condición: Brand New. 331 pages. 9.50x6.75x0.75 inches. In Stock.

Gebunden. Condición: New. Ruben Gonzalez completed his Bachelor s degree in chemical engineering in 2008 at the University of New Brunswick. Under the supervision of Dr. Biao Huang, he completed his Master s degree in 2010 and his Doctorate in 2014, both in chemical engineering, at .

Condición: New. Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc. Series: Wiley Series in Dynamics and Control of Electromechanical Systems. Num Pages: 360 pages, illustrations. BIC Classification: TDCB; TGP; TJ. Category: (P) Professional & Vocational. Dimension: 249 x 175 x 22. Weight in Grams: 714. . 2016. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Condición: As New. Unread book in perfect condition.

Hardcover. Condición: Like New. Like New. Ships from Multiple Locations. book.

Buch. Condición: Neu. Neuware - Process Control System Fault Diagnosis: A Bayesian ApproachRuben T. Gonzalez, University of Alberta, CanadaFei Qi, Suncor Energy Inc., CanadaBiao Huang, University of Alberta, CanadaData-driven Inferential Solutions for Control System Fault DiagnosisA 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.

Hardcover. Condición: new. Hardcover. 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. Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.