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Data Driven And Model Based Methods For Fault Detection And Diagnosis

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Data Driven and Model Based Methods for Fault Detection and Diagnosis

Data Driven and Model Based Methods for Fault Detection and Diagnosis Book
Author : Majdi Mansouri,Mohamed-Faouzi Harkat,Hazem N Nounou,Mohamed N Nounou
Publisher : Elsevier
Release : 2020-02-28
ISBN : 9780128191644
Language : En, Es, Fr & De

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Book Description :

The main objective of Data-Driven and Model-Based Methods for Fault Detection and Diagnosis is to develop techniques that improve the quality of fault detection and then utilize these developed techniques to enhance monitoring various chemical and environmental processes. The book provides both the theoretical framework and technical solutions. It starts with reviewing relevant literature, proceeds with a detailed description of developed methodologies, followed by a discussion of the results of developed methodologies, and ends with major conclusions reached from the analysis of simulation and experimental studies. The book is an indispensable resource for researchers in academia and industry and practitioners working in chemical and environmental engineering to do their work safely. Outlines latent variable based hypothesis testing fault detection techniques to enhance monitoring processes represented by linear or nonlinear input-space models (such as PCA) or input-output models (such as PLS) Explains multiscale latent variable based hypothesis testing fault detection techniques using multiscale representation to help deal with uncertainty in the data and minimize its effect on fault detection Includes interval PCA (IPCA) and interval PLS (IPLS) fault detection methods to enhance the quality of fault detection Provides model-based detection techniques for improvement of monitoring processes using state estimation-based fault detection approaches Demonstrates the effectiveness of the proposed strategies by conducting simulation and experimental studies on synthetic data

Data Driven and Model Based Methods for Fault Detection and Diagnosis

Data Driven and Model Based Methods for Fault Detection and Diagnosis Book
Author : Majdi Mansouri,Mohamed-Faouzi Harkat,Hazem N. Nounou,Mohamed N. Nounou
Publisher : Elsevier
Release : 2020-02-05
ISBN : 0128191651
Language : En, Es, Fr & De

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Book Description :

Data-Driven and Model-Based Methods for Fault Detection and Diagnosis covers techniques that improve the quality of fault detection and enhance monitoring through chemical and environmental processes. The book provides both the theoretical framework and technical solutions. It starts with a review of relevant literature, proceeds with a detailed description of developed methodologies, and then discusses the results of developed methodologies, and ends with major conclusions reached from the analysis of simulation and experimental studies. The book is an indispensable resource for researchers in academia and industry and practitioners working in chemical and environmental engineering to do their work safely. Outlines latent variable based hypothesis testing fault detection techniques to enhance monitoring processes represented by linear or nonlinear input-space models (such as PCA) or input-output models (such as PLS) Explains multiscale latent variable based hypothesis testing fault detection techniques using multiscale representation to help deal with uncertainty in the data and minimize its effect on fault detection Includes interval PCA (IPCA) and interval PLS (IPLS) fault detection methods to enhance the quality of fault detection Provides model-based detection techniques for the improvement of monitoring processes using state estimation-based fault detection approaches Demonstrates the effectiveness of the proposed strategies by conducting simulation and experimental studies on synthetic data

Data Driven Fault Detection for Industrial Processes

Data Driven Fault Detection for Industrial Processes Book
Author : Zhiwen Chen
Publisher : Springer Vieweg
Release : 2017-01-12
ISBN : 9783658167554
Language : En, Es, Fr & De

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Book Description :

Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed.

Fault Detection and Diagnosis in Industrial Systems

Fault Detection and Diagnosis in Industrial Systems Book
Author : L.H. Chiang,E.L. Russell,R.D. Braatz
Publisher : Springer Science & Business Media
Release : 2012-12-06
ISBN : 1447103475
Language : En, Es, Fr & De

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Book Description :

Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs. This book presents the theoretical background and practical techniques for data-driven process monitoring. It demonstrates the application of all the data-driven process monitoring techniques to the Tennessee Eastman plant simulator, and looks at the strengths and weaknesses of each approach in detail. A plant simulator and problems allow readers to apply process monitoring techniques.

Advanced methods for fault diagnosis and fault tolerant control

Advanced methods for fault diagnosis and fault tolerant control Book
Author : Steven X. Ding
Publisher : Springer Nature
Release : 2021-08-01
ISBN : 3662620049
Language : En, Es, Fr & De

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Book Description :

Download Advanced methods for fault diagnosis and fault tolerant control book written by Steven X. Ding, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Model based and Data driven Techniques and Their Application to Fault Detection and Diagnosis in Engineering Systems and Information Retrieval

Model based and Data driven Techniques and Their Application to Fault Detection and Diagnosis in Engineering Systems and Information Retrieval Book
Author : Setu Madhavi Namburu
Publisher : Unknown
Release : 2006
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Model based and Data driven Techniques and Their Application to Fault Detection and Diagnosis in Engineering Systems and Information Retrieval book written by Setu Madhavi Namburu, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Data driven Design of Fault Diagnosis and Fault tolerant Control Systems

Data driven Design of Fault Diagnosis and Fault tolerant Control Systems Book
Author : Steven X. Ding
Publisher : Springer Science & Business Media
Release : 2014-04-12
ISBN : 1447164105
Language : En, Es, Fr & De

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Book Description :

Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems presents basic statistical process monitoring, fault diagnosis, and control methods and introduces advanced data-driven schemes for the design of fault diagnosis and fault-tolerant control systems catering to the needs of dynamic industrial processes. With ever increasing demands for reliability, availability and safety in technical processes and assets, process monitoring and fault-tolerance have become important issues surrounding the design of automatic control systems. This text shows the reader how, thanks to the rapid development of information technology, key techniques of data-driven and statistical process monitoring and control can now become widely used in industrial practice to address these issues. To allow for self-contained study and facilitate implementation in real applications, important mathematical and control theoretical knowledge and tools are included in this book. Major schemes are presented in algorithm form and demonstrated on industrial case systems. Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems will be of interest to process and control engineers, engineering students and researchers with a control engineering background.

Data driven Methods for Fault Detection and Diagnosis in Chemical Processes

Data driven Methods for Fault Detection and Diagnosis in Chemical Processes Book
Author : Evan L. Russell,Leo H. Chiang,Richard D. Braatz
Publisher : Springer Science & Business Media
Release : 2012-12-06
ISBN : 1447104099
Language : En, Es, Fr & De

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Book Description :

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.

Data Driven Design of Fault Diagnosis Systems

Data Driven Design of Fault Diagnosis Systems Book
Author : Adel Haghani Abandan Sari
Publisher : Springer Vieweg
Release : 2014-05-06
ISBN : 9783658058067
Language : En, Es, Fr & De

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Book Description :

In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development of model-based monitoring approaches and it sometimes becomes unrealistic for modern large-scale processes. The main objective of Adel Haghani Abandan Sari is to study efficient fault diagnosis techniques for complex industrial systems using process historical data and considering the nonlinear behavior of the process. To this end, different methods are presented to solve the fault diagnosis problem based on the overall behavior of the process and its dynamics. Moreover, a novel technique is proposed for fault isolation and determination of the root-cause of the faults in the system, based on the fault impacts on the process measurements.

Advanced methods for fault diagnosis and fault tolerant control

Advanced methods for fault diagnosis and fault tolerant control Book
Author : Steven X. Ding
Publisher : Springer
Release : 2020-11-24
ISBN : 9783662620038
Language : En, Es, Fr & De

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Book Description :

The major objective of this book is to introduce advanced design and (online) optimization methods for fault diagnosis and fault-tolerant control from different aspects. Under the aspect of system types, fault diagnosis and fault-tolerant issues are dealt with for linear time-invariant and time-varying systems as well as for nonlinear and distributed (including networked) systems. From the methodological point of view, both model-based and data-driven schemes are investigated.To allow for a self-contained study and enable an easy implementation in real applications, the necessary knowledge as well as tools in mathematics and control theory are included in this book. The main results with the fault diagnosis and fault-tolerant schemes are presented in form of algorithms and demonstrated by means of benchmark case studies. The intended audience of this book are process and control engineers, engineering students and researchers with control engineering background.

Data driven Detection and Diagnosis of Faults in Traction Systems of High speed Trains

Data driven Detection and Diagnosis of Faults in Traction Systems of High speed Trains Book
Author : Hongtian Chen,Bin Jiang,Ningyun Lu,Wen Chen
Publisher : Springer Nature
Release : 2020-04-25
ISBN : 3030462633
Language : En, Es, Fr & De

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Book Description :

This book addresses the needs of researchers and practitioners in the field of high-speed trains, especially those whose work involves safety and reliability issues in traction systems. It will appeal to researchers and graduate students at institutions of higher learning, research labs, and in the industrial R&D sector, catering to a readership from a broad range of disciplines including intelligent transportation, electrical engineering, mechanical engineering, chemical engineering, the biological sciences and engineering, economics, ecology, and the mathematical sciences.

Statistical Process Monitoring Using Advanced Data Driven and Deep Learning Approaches

Statistical Process Monitoring Using Advanced Data Driven and Deep Learning Approaches Book
Author : Fouzi Harrou,Ying Sun,Amanda S. Hering,Muddu Madakyaru,abdelkader Dairi
Publisher : Elsevier
Release : 2020-07-03
ISBN : 0128193662
Language : En, Es, Fr & De

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Book Description :

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

Data Driven Design of Fault Diagnosis Systems

Data Driven Design of Fault Diagnosis Systems Book
Author : Adel Haghani Abandan Sari
Publisher : Springer Science & Business
Release : 2014-04-22
ISBN : 3658058072
Language : En, Es, Fr & De

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Book Description :

In many industrial applications early detection and diagnosis of abnormal behavior of the plant is of great importance. During the last decades, the complexity of process plants has been drastically increased, which imposes great challenges in development of model-based monitoring approaches and it sometimes becomes unrealistic for modern large-scale processes. The main objective of Adel Haghani Abandan Sari is to study efficient fault diagnosis techniques for complex industrial systems using process historical data and considering the nonlinear behavior of the process. To this end, different methods are presented to solve the fault diagnosis problem based on the overall behavior of the process and its dynamics. Moreover, a novel technique is proposed for fault isolation and determination of the root-cause of the faults in the system, based on the fault impacts on the process measurements.

Dynamic Modeling of Complex Industrial Processes Data driven Methods and Application Research

Dynamic Modeling of Complex Industrial Processes  Data driven Methods and Application Research Book
Author : Chao Shang
Publisher : Springer
Release : 2018-02-22
ISBN : 9811066779
Language : En, Es, Fr & De

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Book Description :

This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial production contexts. The thesis reveals the slowly varying nature of industrial production processes under feedback control, and integrates it with process data analytics to offer powerful prior knowledge that gives rise to statistical methods tailored to industrial data. It addresses several issues of immediate interest in industrial practice, including process monitoring, control performance assessment and diagnosis, monitoring system design, and product quality prediction. In particular, it proposes a holistic and pragmatic design framework for industrial monitoring systems, which delivers effective elimination of false alarms, as well as intelligent self-running by fully utilizing the information underlying the data. One of the strengths of this thesis is its integration of insights from statistics, machine learning, control theory and engineering to provide a new scheme for industrial process modeling in the era of big data.

Parallel and Distributed Computing Applications and Technologies

Parallel and Distributed Computing  Applications and Technologies Book
Author : Jong Hyuk Park,Hong Shen,Yunsick Sung,Hui Tian
Publisher : Springer
Release : 2019-02-07
ISBN : 9811359075
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 19th International Conference on CParallel and Distributed Computing, Applications and Technologies, PDCAT 2018, held in Jeju Island, South Korea, in August 2018. The 35 revised full papers presented along with the 14 short papers and were carefully reviewed and selected from 150 submissions. The papers of this volume are organized in topical sections on wired and wireless communication systems, high dimensional data representation and processing, networks and information security, computing techniques for efficient networks design, electronic circuits for communication systems.

Process Control Performance Assessment

Process Control Performance Assessment Book
Author : Andrzej Ordys,Damien Uduehi,Michael A Johnson
Publisher : Springer Science & Business Media
Release : 2007-05-19
ISBN : 1846286247
Language : En, Es, Fr & De

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Book Description :

This book is a practical guide to the application of control benchmarking to real, complex, industrial processes. The variety of industrial case studies gives the benchmarking ideas presented a robust real-world attitude. The book deals with control engineering principles and economic and management aspects of benchmarking. It shows the reader how to avoid common problems in benchmarking and details the benefits of effective benchmarking.

Electro Mechanical Actuators for the More Electric Aircraft

Electro Mechanical Actuators for the More Electric Aircraft Book
Author : Mirko Mazzoleni
Publisher : Springer Nature
Release : 2021-08-01
ISBN : 3030617998
Language : En, Es, Fr & De

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Book Description :

Download Electro Mechanical Actuators for the More Electric Aircraft book written by Mirko Mazzoleni, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Introduction to Process Control Second Edition

Introduction to Process Control  Second Edition Book
Author : Jose A. Romagnoli,Ahmet Palazoglu
Publisher : CRC Press
Release : 2016-04-19
ISBN : 1439854874
Language : En, Es, Fr & De

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Book Description :

Introduction to Process Control, Second Edition provides a bridge between the traditional view of process control and the current, expanded role by blending conventional topics with a broader perspective of more integrated process operation, control, and information systems. Updating and expanding the content of its predecessor, this second edition addresses issues in today’s teaching of process control. Teaching & Learning Principles Presents a concept first followed by an example, allowing students to grasp theoretical concepts in a practical manner Uses the same problem in each chapter, culminating in a complete control design strategy Includes 50 percent more exercises Content Defines the traditional and expanded roles of process control in modern manufacturing Introduces the link between process optimization and process control (optimizing control), including the effect of disturbances on the optimal plant operation, the concepts of steady-state and dynamic backoff as ways to quantify the economic benefits of control, and how to determine an optimal transition policy during a planned production change Incorporates an introduction to the modern architectures of industrial computer control systems with real case studies and applications to pilot-scale operations Discusses the expanded role of process control in modern manufacturing, including model-centric technologies and integrated control systems Integrates data processing/reconciliation and intelligent monitoring in the overall control system architecture Web Resource The book’s website offers a user-friendly software environment for interactively studying the examples in the text. The site contains the MATLAB® toolboxes for process control education as well as the main simulation examples from the book. Access the site through the authors’ websites at www.pseonline.net and www.chms.ucdavis.edu/research/web/pse/ahmet/ Drawing on the authors’ combined 50 years of teaching experiences, this classroom-tested text is designed for chemical engineering students but is also suitable for industrial practitioners who need to understand key concepts of process control and how to implement them. The authors help readers see how traditional process control has evolved into an integrated operational environment used to run modern manufacturing facilities.

Applications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering Book
Author : Jingzheng Ren,Weifeng Shen,Yi Man,Lichun DOng
Publisher : Elsevier
Release : 2021-06-05
ISBN : 012821743X
Language : En, Es, Fr & De

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Book Description :

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering