Filter-Based Fault Diagnosis and Remaining Useful Life Prediction PDF Download

Author: Yong Zhang
Publisher: CRC Press
ISBN: 1000835944
Category : Technology & Engineering
Languages : en
Pages : 290

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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.

Author: Yaguo Lei
Publisher: Butterworth-Heinemann
ISBN: 0128115351
Category : Technology & Engineering
Languages : en
Pages : 376

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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

Author: Weihua Li
Publisher: Springer Nature
ISBN: 9819935377
Category : Technology & Engineering
Languages : en
Pages : 474

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Book Description
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.

Author: Ruqiang Yan
Publisher: Elsevier
ISBN: 0323914233
Category : Business & Economics
Languages : en
Pages : 314

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Book Description
Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis introduces the theory and latest applications of transfer learning on rotary machine fault diagnosis and prognosis. Transfer learning-based rotary machine fault diagnosis is a relatively new subject, and this innovative book synthesizes recent advances from academia and industry to provide systematic guidance. Basic principles are described before key questions are answered, including the applicability of transfer learning to rotary machine fault diagnosis and prognosis, technical details of models, and an introduction to deep transfer learning. Case studies for every method are provided, helping readers apply the techniques described in their own work. Offers case studies for each transfer learning algorithm Optimizes the transfer learning models to solve specific engineering problems Describes the roles of transfer components, transfer fields, and transfer order in intelligent machine diagnosis and prognosis

Author: Faiz Ahmad
Publisher: Springer Nature
ISBN: 9811919399
Category : Technology & Engineering
Languages : en
Pages : 997

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Book Description
This book contains papers presented in the 7th International Conference on Production, Energy and Reliability (ICPER 2020) under the banner of World Engineering, Science & Technology Congress (ESTCON2020) held from 14th to 16th July 2020 at Borneo Convention Centre, Kuching, Malaysia. The conference contains papers presented by academics and industrial practitioners showcasing their latest advancements and findings in mechanical engineering areas with an emphasis on sustainability and the Industrial Revolution 4.0. The papers are categorized under the following tracks and topics of research: IoT, Reliability and Simulation Advanced Materials, Corrosion and Autonomous Production Efficient Energy Systems and Thermofluids Production, Manufacturing and Automotive

Author: Yaguo Lei
Publisher: Springer Nature
ISBN: 9811691312
Category : Technology & Engineering
Languages : en
Pages : 292

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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

Author: Yu Liu
Publisher: Springer Nature
ISBN: 3031288599
Category : Technology & Engineering
Languages : en
Pages : 642

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Book Description
This comprehensive book brings together the latest developments in reliability and maintainability methods from leading research groups globally. Covering a diverse range of subject areas, from mechanical systems to cyber-physical systems, the book offers both theoretical advancements and practical applications in various industries. With a focus on reliability modelling, reliability analysis, reliability design, maintenance optimization, warranty policy, prognostics and health management, this book appeals to academic and industrial professionals in the field of reliability engineering and beyond. It features real-world case studies from turbofan engines bearings, industrial robots, wireless networks, aircraft actuation systems, and more. This book is ideal for engineers, scientists, and graduate students in reliability, maintainability, design optimization, prognostics and health management, and applied probability and statistics.

Author: Hamid Reza Karimi
Publisher: Academic Press
ISBN: 0128224886
Category : Technology & Engineering
Languages : en
Pages : 421

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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

Author: Birgit Milius
Publisher: Springer Nature
ISBN: 3031433661
Category : Computers
Languages : en
Pages : 237

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Book Description
This book constitutes the proceedings of the 5th International Conference on Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification, RSSRail 2023, held in Berlin, Germany, during October 10–12, 2023. The 13 full papers presented in this book together with 3 keynotes were carefully reviewed and selected from 25 submissions. The papers are divided into the following topical sections: modeling for security; tooled approaches and dependability of highly automated transport systems; formal methods for safety assessment; and formal model and visual tooling.

Author: Michael G. Pecht
Publisher: John Wiley & Sons
ISBN: 1119515300
Category : Technology & Engineering
Languages : en
Pages : 800

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Book Description
An indispensable guide for engineers and data scientists in design, testing, operation, manufacturing, and maintenance A road map to the current challenges and available opportunities for the research and development of Prognostics and Health Management (PHM), this important work covers all areas of electronics and explains how to: assess methods for damage estimation of components and systems due to field loading conditions assess the cost and benefits of prognostic implementations develop novel methods for in situ monitoring of products and systems in actual life-cycle conditions enable condition-based (predictive) maintenance increase system availability through an extension of maintenance cycles and/or timely repair actions; obtain knowledge of load history for future design, qualification, and root cause analysis reduce the occurrence of no fault found (NFF) subtract life-cycle costs of equipment from reduction in inspection costs, downtime, and inventory Prognostics and Health Management of Electronics also explains how to understand statistical techniques and machine learning methods used for diagnostics and prognostics. Using this valuable resource, electrical engineers, data scientists, and design engineers will be able to fully grasp the synergy between IoT, machine learning, and risk assessment.