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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
ISBN: 1000594939
Category : Technology & Engineering
Languages : en
Pages : 87

Book Description
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.

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
ISBN: 1000594939
Category : Technology & Engineering
Languages : en
Pages : 87

Book Description
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
ISBN: 3642186157
Category : Computers
Languages : en
Pages : 922

Book Description
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
ISBN: 1000835944
Category : Technology & Engineering
Languages : en
Pages : 290

Book Description
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.

Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems

Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems PDF Author: Hamid Reza Karimi
Publisher: Elsevier
ISBN: 0128224738
Category : Technology & Engineering
Languages : en
Pages : 419

Book Description
Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems gives a systematic description of the many facets of envisaging, designing, implementing, and experimentally exploring emerging trends in fault diagnosis and failure prognosis in mechanical, electrical, hydraulic and biomedical systems. The book is devoted to the development of mathematical methodologies for fault diagnosis and isolation, fault tolerant control, and failure prognosis problems of engineering systems. Sections present new techniques in reliability modeling, reliability analysis, reliability design, fault and failure detection, signal processing, and fault tolerant control of engineering systems. Sections focus on the development of mathematical methodologies for diagnosis and prognosis of faults or failures, providing a unified platform for understanding and applicability of advanced diagnosis and prognosis methodologies for improving reliability purposes in both theory and practice, such as vehicles, manufacturing systems, circuits, flights, biomedical systems. This book will be a valuable resource for different groups of readers - mechanical engineers working on vehicle systems, electrical engineers working on rotary machinery systems, control engineers working on fault detection systems, mathematicians and physician working on complex dynamics, and many more. Presents recent advances of theory, technological aspects, and applications of advanced diagnosis and prognosis methodologies in engineering applications Provides a series of the latest results, including fault detection, isolation, fault tolerant control, failure prognosis of components, and more Gives numerical and simulation results in each chapter to reflect engineering practices

Fault Diagnosis of Induction Motors

Fault Diagnosis of Induction Motors PDF Author: Jawad Faiz
Publisher: IET
ISBN: 1785613286
Category : Business & Economics
Languages : en
Pages : 535

Book Description
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.

Knowledge-Driven Board-Level Functional Fault Diagnosis

Knowledge-Driven Board-Level Functional Fault Diagnosis PDF Author: Fangming Ye
Publisher: Springer
ISBN: 3319402102
Category : Technology & Engineering
Languages : en
Pages : 147

Book Description
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.

Diagnostic Techniques in Industrial Engineering

Diagnostic Techniques in Industrial Engineering PDF Author: Mangey Ram
Publisher: Springer
ISBN: 3319654977
Category : Technology & Engineering
Languages : en
Pages : 247

Book Description
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.

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
ISBN: 9811691312
Category : Technology & Engineering
Languages : en
Pages : 292

Book Description
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

Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery

Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery PDF Author: Yaguo Lei
Publisher: Butterworth-Heinemann
ISBN: 0128115351
Category : Technology & Engineering
Languages : en
Pages : 376

Book Description
Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery provides a comprehensive introduction of intelligent fault diagnosis and RUL prediction based on the current achievements of the author's research group. The main contents include multi-domain signal processing and feature extraction, intelligent diagnosis models, clustering algorithms, hybrid intelligent diagnosis strategies, and RUL prediction approaches, etc. This book presents fundamental theories and advanced methods of identifying the occurrence, locations, and degrees of faults, and also includes information on how to predict the RUL of rotating machinery. Besides experimental demonstrations, many application cases are presented and illustrated to test the methods mentioned in the book. This valuable reference provides an essential guide on machinery fault diagnosis that helps readers understand basic concepts and fundamental theories. Academic researchers with mechanical engineering or computer science backgrounds, and engineers or practitioners who are in charge of machine safety, operation, and maintenance will find this book very useful. Provides a detailed background and roadmap of intelligent diagnosis and RUL prediction of rotating machinery, involving fault mechanisms, vibration characteristics, health indicators, and diagnosis and prognostics Presents basic theories, advanced methods, and the latest contributions in the field of intelligent fault diagnosis and RUL prediction Includes numerous application cases, and the methods, algorithms, and models introduced in the book are demonstrated by industrial experiences

Model-based Fault Diagnosis in Dynamic Systems Using Identification Techniques

Model-based Fault Diagnosis in Dynamic Systems Using Identification Techniques PDF Author: Silvio Simani
Publisher: Springer Science & Business Media
ISBN: 1447138295
Category : Technology & Engineering
Languages : en
Pages : 294

Book Description
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.