Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems

Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems PDF

Author: Rui Yang

Publisher: CRC Press

Published: 2022-06-16

Total Pages: 87

ISBN-13: 1000594939

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This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods. Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems discusses how to formulate and solve precision compensation and fault diagnosis problems. The book includes experimental results on hardware equipment used as practical examples throughout the book. Machine learning and deep learning methods used in intelligent precision compensation and intelligent fault diagnosis are introduced. Applications to deal with relevant problems concerning CNC machining and rotating machinery in industrial engineering systems are provided in detail along with applications used in precision motion systems. Methods, applications, and concepts offered in this book can help all professional engineers and students across many areas of engineering and operations management that are involved in any part of Industry 4.0 transformation.

Fault Diagnosis

Fault Diagnosis PDF

Author: Józef Korbicz

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 936

ISBN-13: 3642186157

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This comprehensive work presents the status and likely development of fault diagnosis, an emerging discipline of modern control engineering. It covers fundamentals of model-based fault diagnosis in a wide context, providing a good introduction to the theoretical foundation and many basic approaches of fault detection.

Filter-Based Fault Diagnosis and Remaining Useful Life Prediction

Filter-Based Fault Diagnosis and Remaining Useful Life Prediction PDF

Author: Yong Zhang

Publisher: CRC Press

Published: 2023-02-09

Total Pages: 290

ISBN-13: 1000835944

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This book unifies existing and emerging concepts concerning state estimation, fault detection, fault isolation and fault estimation on industrial systems with an emphasis on a variety of network-induced phenomena, fault diagnosis and remaining useful life for industrial equipment. It covers state estimation/monitor, fault diagnosis and remaining useful life prediction by drawing on the conventional theories of systems science, signal processing and machine learning. Features: Unifies existing and emerging concepts concerning robust filtering and fault diagnosis with an emphasis on a variety of network-induced complexities. Explains theories, techniques, and applications of state estimation as well as fault diagnosis from an engineering-oriented perspective. Provides a series of latest results in robust/stochastic filtering, multidate sample, and time-varying system. Captures diagnosis (fault detection, fault isolation and fault estimation) for time-varying multi-rate systems. Includes simulation examples in each chapter to reflect the engineering practice. This book aims at graduate students, professionals and researchers in control science and application, system analysis, artificial intelligence, and fault diagnosis.

Diagnostic Techniques in Industrial Engineering

Diagnostic Techniques in Industrial Engineering PDF

Author: Mangey Ram

Publisher: Springer

Published: 2017-10-20

Total Pages: 247

ISBN-13: 3319654977

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This book presents the most important tools, techniques, strategy and diagnostic methods used in industrial engineering. The current widely accepted methods of diagnosis and their properties are discussed. Also, the possible fruitful areas for further research in the field are identified.

Knowledge-Driven Board-Level Functional Fault Diagnosis

Knowledge-Driven Board-Level Functional Fault Diagnosis PDF

Author: Fangming Ye

Publisher: Springer

Published: 2016-08-19

Total Pages: 147

ISBN-13: 3319402102

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This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design. • Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing;• Demonstrates techniques based on industrial data and feedback from an actual manufacturing line;• Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development.

Fault Detection and Diagnosis in Engineering Systems

Fault Detection and Diagnosis in Engineering Systems PDF

Author: Janos Gertler

Publisher: Routledge

Published: 2017-11-22

Total Pages: 307

ISBN-13: 1351448781

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Featuring a model-based approach to fault detection and diagnosis in engineering systems, this book contains up-to-date, practical information on preventing product deterioration, performance degradation and major machinery damage.;College or university bookstores may order five or more copies at a special student price. Price is available upon request.

Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems

Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems PDF

Author: Weihua Li

Publisher: Springer Nature

Published: 2023-09-10

Total Pages: 474

ISBN-13: 9819935377

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Based on AI and machine learning, this book systematically presents the theories and methods for complex electro-mechanical system fault prognosis, intelligent diagnosis, and health state assessment in modern industry. The book emphasizes feature extraction, incipient fault prediction, fault classification, and degradation assessment, which are based on supervised-, semi-supervised-, manifold-, and deep learning; machinery degradation state tracking and prognosis by phase space reconstruction; and complex electro-mechanical system reliability assessment and health maintenance based on running state info. These theories and methods are integrated with practical industrial applications, which can help the readers get into the field more smoothly and provide an important reference for their study, research, and engineering practice.

Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems

Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems PDF

Author: Yaguo Lei

Publisher: Springer Nature

Published: 2022-10-19

Total Pages: 292

ISBN-13: 9811691312

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This book presents systematic overviews and bright insights into big data-driven intelligent fault diagnosis and prognosis for mechanical systems. The recent research results on deep transfer learning-based fault diagnosis, data-model fusion remaining useful life (RUL) prediction, etc., are focused on in the book. The contents are valuable and interesting to attract academic researchers, practitioners, and students in the field of prognostics and health management (PHM). Essential guidelines are provided for readers to understand, explore, and implement the presented methodologies, which promote further development of PHM in the big data era. Features: Addresses the critical challenges in the field of PHM at present Presents both fundamental and cutting-edge research theories on intelligent fault diagnosis and prognosis Provides abundant experimental validations and engineering cases of the presented methodologies

Fault Diagnosis of Induction Motors

Fault Diagnosis of Induction Motors PDF

Author: Jawad Faiz

Publisher: IET

Published: 2017-08-29

Total Pages: 535

ISBN-13: 1785613286

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This book is a comprehensive, structural approach to fault diagnosis strategy. The different fault types, signal processing techniques, and loss characterisation are addressed in the book. This is essential reading for work with induction motors for transportation and energy.

Model-based Fault Diagnosis Techniques

Model-based Fault Diagnosis Techniques PDF

Author: Steven X. Ding

Publisher: Springer Science & Business Media

Published: 2008-02-23

Total Pages: 479

ISBN-13: 354076304X

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The objective of this book is to introduce basic model-based FDI schemes, advanced analysis and design algorithms, and the needed mathematical and control theory tools at a level for graduate students and researchers as well as for engineers. This is a textbook with extensive examples and references. Most methods are given in the form of an algorithm that enables a direct implementation in a programme. Comparisons among different methods are included when possible.