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＜電子ブック＞
Process Monitoring and Fault Diagnosis Based on Multivariable Statistical Analysis / by Xiangyu Kong, Jiayu Luo, Xiaowei Feng
(Engineering Applications of Computational Methods. ISSN:26623374 ; 19)

版	1st ed. 2024.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2024
本文言語	英語
大きさ	XXXIII, 300 p. 138 illus., 131 illus. in color : online resource
著者標目	*Kong, Xiangyu author Luo, Jiayu author Feng, Xiaowei author SpringerLink (Online service)
件　名	LCSH:Mathematical models LCSH:Industrial Management LCSH:Control engineering FREE:Mathematical Modeling and Industrial Mathematics FREE:Industrial Management FREE:Control and Systems Theory
一般注記	Chapter 1 Introduction -- Chapter 2 An Overview of Conventional MSPC Methods -- Chapter 3 System-wide Process Monitoring and Fault Diagnosis -- Chapter 4 Quality-Related Time-Varying Process Monitoring -- Chapter 5 Quality-Related Dynamic Process Monitoring: Part I -- Chapter 6 Quality-Related Dynamic Process Monitoring: Part II -- Chapter 7 Quality-Related Complex Nonlinear Process Monitoring -- Chapter 8 Quality-Related Fault Subspace Extraction for Fault Diagnosis -- Chapter 9 Non-Gaussian Process Monitoring and Fault Diagnosis -- Chapter 10 Hybrid Gaussian/Non-Gaussian Quality-Related Nonlinear Process Monitoring -- Chapter 11 Conclusions and Future Work This book reports recent developments of the multivariate statistical process control (MSPC) methods for industrial process monitoring and fault diagnosis. Specifically, this book gives an overview of recently developed methods in different aspects, namely system-wide process monitoring, quality-related time-varying process monitoring, quality-related dynamic process monitoring, quality-related complex nonlinear process monitoring, and quality-related fault subspace extraction for fault diagnosis, non-Gaussian process monitoring and fault diagnosis, etc. In order to help readers understand and master the new methods, before presenting each new method in each chapter, a specialized section is provided to review the closely related several basis models. Throughout the book, detailed steps of new methods are provided, and all new algorithms or methods proposed by us are tested and verified by numerical simulations or Tennessee Eastman benchmark chemical process. Readers find illustrative demonstration examples on a range of industrial processes to study and the present deficiency and recent developments of the MSPC methods for industrial processes monitoring and fault diagnosis, by learning from the authors’ latest achievements or new methods around the practical industrial needs. This book is assimilated by advanced undergraduates and graduate students, as well as industrial and process engineering researchers and practitioners HTTP:URL=https://doi.org/10.1007/978-981-99-8775-7

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