Data Driven and Model Based Methods for Fault Detection and Diagnosis Book

Data Driven and Model Based Methods for Fault Detection and Diagnosis


  • Author : Majdi Mansouri
  • Publisher : Elsevier
  • Release Date : 2020-02-05
  • Genre: Technology & Engineering
  • Pages : 322
  • ISBN 10 : 9780128191651

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Data Driven and Model Based Methods for Fault Detection and Diagnosis Excerpt :

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

Diagnosis and Fault tolerant Control 1 Book

Diagnosis and Fault tolerant Control 1


  • Author : Vicenc Puig
  • Publisher : John Wiley & Sons
  • Release Date : 2022-01-06
  • Genre: Business & Economics
  • Pages : 288
  • ISBN 10 : 9781789450583

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Diagnosis and Fault tolerant Control 1 Excerpt :

This book presents recent advances in fault diagnosis strategies for complex dynamic systems. Its impetus derives from the need for an overview of the challenges of the fault diagnosis technique, especially for those demanding systems that require reliability, availability, maintainability and safety to ensure efficient operations. Moreover, the need for a high degree of tolerance with respect to possible faults represents a further key point, primarily for complex systems, as modeling and control are inherently challenging, and maintenance is both expensive and safety-critical. Diagnosis and Fault-tolerant Control 1 also presents and compares different diagnosis schemes using established case studies that are widely used in related literature. The main features of this book regard the analysis, design and implementation of proper solutions for the problems of fault diagnosis in safety critical systems. The design of the considered solutions involves robust data-driven, model-based approaches.

Data driven Methods for Fault Detection and Diagnosis in Chemical Processes Book

Data driven Methods for Fault Detection and Diagnosis in Chemical Processes


  • Author : Evan L. Russell
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • Genre: Science
  • Pages : 192
  • ISBN 10 : 9781447104094

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Data driven Methods for Fault Detection and Diagnosis in Chemical Processes Excerpt :

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 Fault Detection for Industrial Processes Book

Data Driven Fault Detection for Industrial Processes


  • Author : Zhiwen Chen
  • Publisher : Springer
  • Release Date : 2017-01-02
  • Genre: Technology & Engineering
  • Pages : 112
  • ISBN 10 : 9783658167561

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Data Driven Fault Detection for Industrial Processes Excerpt :

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.

Data driven Design of Fault Diagnosis and Fault tolerant Control Systems Book

Data driven Design of Fault Diagnosis and Fault tolerant Control Systems


  • Author : Steven X. Ding
  • Publisher : Springer Science & Business Media
  • Release Date : 2014-04-12
  • Genre: Technology & Engineering
  • Pages : 300
  • ISBN 10 : 9781447164104

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Data driven Design of Fault Diagnosis and Fault tolerant Control Systems Excerpt :

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 and Model Based Methods for Fault Detection and Diagnosis Book

Data Driven and Model Based Methods for Fault Detection and Diagnosis


  • Author : Majdi Mansouri
  • Publisher : Elsevier
  • Release Date : 2020-02-28
  • Genre: Uncategoriezed
  • Pages : 412
  • ISBN 10 : 0128191643

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Data Driven and Model Based Methods for Fault Detection and Diagnosis Excerpt :

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 Design of Fault Diagnosis Systems Book

Data Driven Design of Fault Diagnosis Systems


  • Author : Adel Haghani Abandan Sari
  • Publisher : Springer Science & Business
  • Release Date : 2014-04-22
  • Genre: Technology & Engineering
  • Pages : 136
  • ISBN 10 : 9783658058074

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Data Driven Design of Fault Diagnosis Systems Excerpt :

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.

Fault Detection and Diagnosis in Industrial Systems Book
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Fault Detection and Diagnosis in Industrial Systems


  • Author : L.H. Chiang
  • Publisher : Springer Science & Business Media
  • Release Date : 2000-12-11
  • Genre: Technology & Engineering
  • Pages : 279
  • ISBN 10 : 1852333278

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Fault Detection and Diagnosis in Industrial Systems Excerpt :

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.

Diagnosis and Fault tolerant Control 1 Book

Diagnosis and Fault tolerant Control 1


  • Author : Vicenc Puig
  • Publisher : John Wiley & Sons
  • Release Date : 2021-12-01
  • Genre: Computers
  • Pages : 288
  • ISBN 10 : 9781119882312

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Diagnosis and Fault tolerant Control 1 Excerpt :

This book presents recent advances in fault diagnosis strategies for complex dynamic systems. Its impetus derives from the need for an overview of the challenges of the fault diagnosis technique, especially for those demanding systems that require reliability, availability, maintainability and safety to ensure efficient operations. Moreover, the need for a high degree of tolerance with respect to possible faults represents a further key point, primarily for complex systems, as modeling and control are inherently challenging, and maintenance is both expensive and safety-critical. Diagnosis and Fault-tolerant Control 1 also presents and compares different diagnosis schemes using established case studies that are widely used in related literature. The main features of this book regard the analysis, design and implementation of proper solutions for the problems of fault diagnosis in safety critical systems. The design of the considered solutions involves robust data-driven, model-based approaches.

Model Based Fault Diagnosis Techniques Book

Model Based Fault Diagnosis Techniques


  • Author : Steven X. Ding
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-20
  • Genre: Technology & Engineering
  • Pages : 504
  • ISBN 10 : 9781447147992

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Model Based Fault Diagnosis Techniques Excerpt :

Guaranteeing a high system performance over a wide operating range is an important issue surrounding the design of automatic control systems with successively increasing complexity. As a key technology in the search for a solution, advanced fault detection and identification (FDI) is receiving considerable attention. This book introduces basic model-based FDI schemes, advanced analysis and design algorithms, and mathematical and control-theoretic tools. This second edition of Model-Based Fault Diagnosis Techniques contains: • new material on fault isolation and identification and alarm management; • extended and revised treatment of systematic threshold determination for systems with both deterministic unknown inputs and stochastic noises; • addition of the continuously-stirred tank heater as a representative process-industrial benchmark; and • enhanced discussion of residual evaluation which now deals with stochastic processes. Model-based Fault Diagnosis Techniques will interest academic researchers working in fault identification and diagnosis and as a text it is suitable for graduate students in a formal university-based course or as a self-study aid for practising engineers working with automatic control or mechatronic systems from backgrounds as diverse as chemical process and power engineering.

Fault Detection and Diagnosis in Industrial Systems Book

Fault Detection and Diagnosis in Industrial Systems


  • Author : L.H. Chiang
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • Genre: Technology & Engineering
  • Pages : 279
  • ISBN 10 : 9781447103479

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Fault Detection and Diagnosis in Industrial Systems Excerpt :

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.

Data Driven Fault Detection and Reasoning for Industrial Monitoring Book

Data Driven Fault Detection and Reasoning for Industrial Monitoring


  • Author : Jing Wang
  • Publisher : Springer
  • Release Date : 2022-01-04
  • Genre: Technology & Engineering
  • Pages : 264
  • ISBN 10 : 9811680434

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Data Driven Fault Detection and Reasoning for Industrial Monitoring Excerpt :

This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.

Advanced methods for fault diagnosis and fault tolerant control Book

Advanced methods for fault diagnosis and fault tolerant control


  • Author : Steven X. Ding
  • Publisher : Springer
  • Release Date : 2020-11-24
  • Genre: Technology & Engineering
  • Pages : 658
  • ISBN 10 : 3662620030

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Advanced methods for fault diagnosis and fault tolerant control Excerpt :

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.

Model based Fault Diagnosis in Dynamic Systems Using Identification Techniques Book

Model based Fault Diagnosis in Dynamic Systems Using Identification Techniques


  • Author : Silvio Simani
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-11-11
  • Genre: Technology & Engineering
  • Pages : 282
  • ISBN 10 : 9781447138297

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Model based Fault Diagnosis in Dynamic Systems Using Identification Techniques Excerpt :

Safety in industrial process and production plants is a concern of rising importance but because the control devices which are now exploited to improve the performance of industrial processes include both sophisticated digital system design techniques and complex hardware, there is a higher probability of failure. Control systems must include automatic supervision of closed-loop operation to detect and isolate malfunctions quickly. A promising method for solving this problem is "analytical redundancy", in which residual signals are obtained and an accurate model of the system mimics real process behaviour. If a fault occurs, the residual signal is used to diagnose and isolate the malfunction. This book focuses on model identification oriented to the analytical approach of fault diagnosis and identification covering: choice of model structure; parameter identification; residual generation; and fault diagnosis and isolation. Sample case studies are used to demonstrate the application of these techniques.