Process Monitoring And Fault Diagnosis Based On Multivariable Statistical Analysis
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Process Monitoring And Fault Diagnosis Based On Multivariable Statistical Analysis
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Author : Xiangyu Kong
language : en
Publisher: Springer Nature
Release Date : 2024-03-12
Process Monitoring And Fault Diagnosis Based On Multivariable Statistical Analysis written by Xiangyu Kong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-12 with Mathematics categories.
This book reports the developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering. Specifically, this book introduces the authors’ latest achievements in the past 20 years, including the recursive TLS algorithms, the approximate inverse power iteration TLS algorithm, the neural based MCA algorithm, the neural based SVD algorithm, the neural based TLS algorithm, the TLS algorithms under non-Gaussian noises, performance analysis methods of TLS algorithms, etc. In order to faster the understanding and mastering of the new methods provided by this book for readers, before presenting each new method in each chapter, a specialized section is provided to review the closely related several basis models. Throughout the book, large of procedure of new methods are provided, and all new algorithms or methods proposed by us are tested and verified by numerical simulations or actual engineering applications. Readers will find illustrative demonstration examples on a range of industrial processes to study. Readers will find out the present deficiency and recent developments of the TLS parameter estimation fields, and learn from the the authors’ latest achievements or new methods around the practical industrial needs. In my opinion, this book can be assimilated by advanced undergraduates and graduate (PH.D.) students, as well as statisticians, because of the new tools in data analysis, applied mathematics experts, because of the novel theories and techniques that we propose, engineers, above all for the applications in control, system identification, computer vision, and signal processing.
Unsupervised Process Monitoring And Fault Diagnosis With Machine Learning Methods
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Author : Chris Aldrich
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-15
Unsupervised Process Monitoring And Fault Diagnosis With Machine Learning Methods written by Chris Aldrich and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-15 with Computers categories.
This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.
Statistical Process Monitoring Using Advanced Data Driven And Deep Learning Approaches
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Author : Fouzi Harrou
language : en
Publisher: Elsevier
Release Date : 2020-07-03
Statistical Process Monitoring Using Advanced Data Driven And Deep Learning Approaches written by Fouzi Harrou and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-03 with Technology & Engineering categories.
Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. - Uses a data-driven based approach to fault detection and attribution - Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems - Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods - Includes case studies and comparison of different methods
Fault Detection And Diagnosis In Industrial Systems
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Author : L.H. Chiang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Fault Detection And Diagnosis In Industrial Systems written by L.H. Chiang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process monitoring techniques presented include: Data-driven methods - principal component analysis, Fisher discriminant analysis, partial least squares and canonical variate analysis; Analytical Methods - parameter estimation, observer-based methods and parity relations; Knowledge-based methods - causal analysis, expert systems and pattern recognition. The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process monitoring techniques to a non-trivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques. The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.
Data Driven Methods For Fault Detection And Diagnosis In Chemical Processes
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Author : Evan L. Russell
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Data Driven Methods For Fault Detection And Diagnosis In Chemical Processes written by Evan L. Russell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis. The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques. The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.
Multivariate Statistical Process Control
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Author : Zhiqiang Ge
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-28
Multivariate Statistical Process Control written by Zhiqiang Ge and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-28 with Technology & Engineering categories.
Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help operators run industrial processes efficiently at the same time as maintaining high product quality. Multivariate Statistical Process Control reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas. Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
16th European Symposium On Computer Aided Process Engineering And 9th International Symposium On Process Systems Engineering
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Author : Wolfgang Marquardt
language : en
Publisher: Elsevier
Release Date : 2006-08-02
16th European Symposium On Computer Aided Process Engineering And 9th International Symposium On Process Systems Engineering written by Wolfgang Marquardt and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-02 with Science categories.
This proceedings book contains the papers presented at the joint conference event of the 9th Symposium on Process Systems Engineering (PSE'2006) and the 16th European Symposium on Computer Aided Process Engineering (ESCAPE-16), held in Garmisch-Partenkirchen, Germany, from July 9 – July 13, 2006. The symposium follows the first joint event PSE'97 / ESCAPE-7 in Trondheim, Norway (1997). The last two venues of the ESCAPE symposia were Barcelona, Spain (2005) and Lisbon, Portugal (2004) and the most recent PSE symposia were held in Kunming, China (2003) and Keystone, Colorado, USA (2000). The purpose of both series is to bring together the international community of researchers engineers who are interested in computing-based methods in process engineering. The main objective of the symposium is to review and present the latest developments and current state in Process Systems Engineering and Computer Aided Process Engineering. The focus of PSE'2006 / ESCAPE-16 has been on Modelling and Numerical Methods, Product and Process Design, Operations and Control, Biological Systems, Infrastructure Systems, and Business decision support.* reviews and presents the latest developments and current state of Process Systems Engineering and Computer Aided Process Engineering * contains papers presented at a joint conference event * bringing together an international community of researchers and engineers interested in computing-based methods in Process Engineering
Proceedings Of The 2015 Chinese Intelligent Systems Conference
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Author : Yingmin Jia
language : en
Publisher: Springer
Release Date : 2015-12-11
Proceedings Of The 2015 Chinese Intelligent Systems Conference written by Yingmin Jia and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-11 with Technology & Engineering categories.
This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.
Fault Detection Supervision And Safety Of Technical Processes 2006
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Author : Hong-Yue Zhang
language : en
Publisher: Elsevier
Release Date : 2007-03-01
Fault Detection Supervision And Safety Of Technical Processes 2006 written by Hong-Yue Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-01 with Science categories.
The safe and reliable operation of technical systems is of great significance for the protection of human life and health, the environment, and of the vested economic value. The correct functioning of those systems has a profound impact also on production cost and product quality. The early detection of faults is critical in avoiding performance degradation and damage to the machinery or human life. Accurate diagnosis then helps to make the right decisions on emergency actions and repairs. Fault detection and diagnosis (FDD) has developed into a major area of research, at the intersection of systems and control engineering, artificial intelligence, applied mathematics and statistics, and such application fields as chemical, electrical, mechanical and aerospace engineering. IFAC has recognized the significance of FDD by launching a triennial symposium series dedicated to the subject. The SAFEPROCESS Symposium is organized every three years since the first symposium held in Baden-Baden in 1991. SAFEPROCESS 2006, the 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes was held in Beijing, PR China. The program included three plenary papers, two semi-plenary papers, two industrial talks by internationally recognized experts and 258 regular papers, which have been selected out of a total of 387 regular and invited papers submitted. * Discusses the developments and future challenges in all aspects of fault diagnosis and fault tolerant control * 8 invited and 36 contributed sessions included with a special session on the demonstration of process monitoring and diagnostic software tools
17th European Symposium On Computed Aided Process Engineering
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Author : Valentin Plesu
language : en
Publisher: Elsevier
Release Date : 2007-05-24
17th European Symposium On Computed Aided Process Engineering written by Valentin Plesu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-24 with Technology & Engineering categories.
The 17th European Symposium on Computed Aided Process Engineering contains papers presented at the 17th European Symposium of Computer Aided Process Engineering (ESCAPE 17) held in Bucharest, Romania, from 27-30 May 2007. The ESCAPE series serves as a forum for scientists and engineers from academia and industry to discuss progress achieved in the area of Computer Aided Process Engineering (CAPE). The main goal was to emphasize the continuity in research of innovative concepts and systematic design methods as well the diversity of applications emerged from the demands of sustainable development. ESCAPE 17 highlights the progresss software technology needed for implementing simulation based tools.The symposium is based on 5 themes and 27 topics, following the main trends in CAPE area: Modelling, Process and Products Design, Optimisation and Optimal Control and Operation, System Biology and Biological Processes, Process Integration and Sustainable Development. Participants from 50 countries attended and invited speakers presented 5 plenary lectures tackling broad subjects and 10 keynote lectures. Satellite events added a plus to the scientific dimension to this symposium.* All contributions are included on the CD-ROM attached to the book* Attendance from 50 countries with invited speakers presenting 5 plenary lectures tackling broad subjects and 10 keynote lectures