Data Driven and Model Based Methods for Fault Detection and Diagnosis

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  • Publisher : Elsevier
  • Release : 05 February 2020
  • ISBN : 9780128191651
  • Page : 322 pages
  • Rating : 4.5/5 from 103 voters

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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

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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
  • Author : Majdi Mansouri,Mohamed-Faouzi Harkat,Hazem Nounou,Mohamed N. Nounou
  • Publisher : Elsevier
  • Release Date : 2020-02-05
  • ISBN : 9780128191651
GET THIS BOOKData-Driven and Model-Based Methods for Fault Detection and Diagnosis

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

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

Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
  • Author : Evan L. Russell,Leo H. Chiang,Richard D. Braatz
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • ISBN : 9781447104094
GET THIS BOOKData-driven Methods for Fault Detection and Diagnosis in Chemical Processes

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

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

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
  • ISBN : 9781447164104
GET THIS BOOKData-driven Design of Fault Diagnosis and Fault-tolerant Control Systems

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

Diagnosis and Fault-tolerant Control 1

Diagnosis and Fault-tolerant Control 1
  • Author : Vicenc Puig,Silvio Simani
  • Publisher : John Wiley & Sons
  • Release Date : 2021-12-01
  • ISBN : 9781119882312
GET THIS BOOKDiagnosis and Fault-tolerant Control 1

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

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

Data-Driven and Model-Based Methods for Fault Detection and Diagnosis
  • Author : Majdi Mansouri,Mohamed-Faouzi Harkat,Hazem N Nounou,Mohamed N Nounou
  • Publisher : Elsevier
  • Release Date : 2020-02-28
  • ISBN : 0128191643
GET THIS BOOKData-Driven and Model-Based Methods for Fault Detection and Diagnosis

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

Data-Driven Design of Fault Diagnosis Systems

Data-Driven Design of Fault Diagnosis Systems
  • Author : Adel Haghani Abandan Sari
  • Publisher : Springer Science & Business
  • Release Date : 2014-04-22
  • ISBN : 9783658058074
GET THIS BOOKData-Driven Design of Fault Diagnosis Systems

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

Fault Detection and Diagnosis in Industrial Systems

Fault Detection and Diagnosis in Industrial Systems
  • Author : L.H. Chiang,E.L. Russell,R.D. Braatz
  • Publisher : Springer Science & Business Media
  • Release Date : 2000-12-11
  • ISBN : 1852333278
GET THIS BOOKFault Detection and Diagnosis in Industrial Systems

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.

Model-Based Fault Diagnosis Techniques

Model-Based Fault Diagnosis Techniques
  • Author : Steven X. Ding
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-20
  • ISBN : 9781447147992
GET THIS BOOKModel-Based Fault Diagnosis Techniques

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

Fault Detection and Diagnosis in Industrial Systems

Fault Detection and Diagnosis in Industrial Systems
  • Author : L.H. Chiang,E.L. Russell,R.D. Braatz
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • ISBN : 9781447103479
GET THIS BOOKFault Detection and Diagnosis in Industrial Systems

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.

Model- and Data-driven Approaches to Fault Detection and Isolation in Complex Systems

Model- and Data-driven Approaches to Fault Detection and Isolation in Complex Systems
  • Author : Hamed Khorasgani
  • Publisher : Unknown
  • Release Date : 2018
  • ISBN : OCLC:1101444770
GET THIS BOOKModel- and Data-driven Approaches to Fault Detection and Isolation in Complex Systems

Data-Driven Fault Detection and Reasoning for Industrial Monitoring

Data-Driven Fault Detection and Reasoning for Industrial Monitoring
  • Author : Jing Wang,Jinglin Zhou,Xiaolu Chen
  • Publisher : Springer
  • Release Date : 2022-01-04
  • ISBN : 9811680434
GET THIS BOOKData-Driven Fault Detection and Reasoning for Industrial Monitoring

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

Advanced methods for fault diagnosis and fault-tolerant control

Advanced methods for fault diagnosis and fault-tolerant control
  • Author : Steven X. Ding
  • Publisher : Springer
  • Release Date : 2020-11-24
  • ISBN : 3662620030
GET THIS BOOKAdvanced methods for fault diagnosis and fault-tolerant control

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

Model-based Fault Diagnosis in Dynamic Systems Using Identification Techniques

Model-based Fault Diagnosis in Dynamic Systems Using Identification Techniques
  • Author : Silvio Simani,Cesare Fantuzzi,Ron J. Patton
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-11-11
  • ISBN : 9781447138297
GET THIS BOOKModel-based Fault Diagnosis in Dynamic Systems Using Identification Techniques

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

Advanced methods for fault diagnosis and fault-tolerant control

Advanced methods for fault diagnosis and fault-tolerant control
  • Author : Steven X. Ding
  • Publisher : Springer Nature
  • Release Date : 2020-11-24
  • ISBN : 9783662620045
GET THIS BOOKAdvanced methods for fault diagnosis and fault-tolerant control

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

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
  • Author : Hongtian Chen,Bin Jiang,Ningyun Lu,Wen Chen
  • Publisher : Springer Nature
  • Release Date : 2020-04-25
  • ISBN : 9783030462635
GET THIS BOOKData-driven Detection and Diagnosis of Faults in Traction Systems of High-speed Trains

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.