Intelligent Fault Diagnosis And Remaining Useful Life Prediction Of Rotating Machinery
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Intelligent Fault Diagnosis And Remaining Useful Life Prediction Of Rotating Machinery
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Author : Yaguo Lei
language : en
Publisher: Butterworth-Heinemann
Release Date : 2016-11-02
Intelligent Fault Diagnosis And Remaining Useful Life Prediction Of Rotating Machinery written by Yaguo Lei and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-02 with Technology & Engineering categories.
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
Intelligent Fault Diagnosis And Prognosis For Engineering Systems
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Author : George Vachtsevanos
language : en
Publisher: Wiley
Release Date : 2006-09-29
Intelligent Fault Diagnosis And Prognosis For Engineering Systems written by George Vachtsevanos and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-29 with Technology & Engineering categories.
Expert guidance on theory and practice in condition-based intelligent machine fault diagnosis and failure prognosis Intelligent Fault Diagnosis and Prognosis for Engineering Systems gives a complete presentation of basic essentials of fault diagnosis and failure prognosis, and takes a look at the cutting-edge discipline of intelligent fault diagnosis and failure prognosis technologies for condition-based maintenance. It thoroughly details the interdisciplinary methods required to understand the physics of failure mechanisms in materials, structures, and rotating equipment, and also presents strategies to detect faults or incipient failures and predict the remaining useful life of failing components. Case studies are used throughout the book to illustrate enabling technologies. Intelligent Fault Diagnosis and Prognosis for Engineering Systems offers material in a holistic and integrated approach that addresses the various interdisciplinary components of the field--from electrical, mechanical, industrial, and computer engineering to business management. This invaluably helpful book: * Includes state-of-the-art algorithms, methodologies, and contributions from leading experts, including cost-benefit analysis tools and performance assessment techniques * Covers theory and practice in a way that is rooted in industry research and experience * Presents the only systematic, holistic approach to a strongly interdisciplinary topic
Big Data Driven Intelligent Fault Diagnosis And Prognosis For Mechanical Systems
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Author : Yaguo Lei
language : en
Publisher: Springer Nature
Release Date : 2022-10-19
Big Data Driven Intelligent Fault Diagnosis And Prognosis For Mechanical Systems written by Yaguo Lei and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-19 with Technology & Engineering categories.
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
Machine Learning Based Fault Diagnosis For Industrial Engineering Systems
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Author : Rui Yang
language : en
Publisher: CRC Press
Release Date : 2022-06-16
Machine Learning Based Fault Diagnosis For Industrial Engineering Systems written by Rui Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-16 with Technology & Engineering categories.
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.
Smart Monitoring Of Rotating Machinery For Industry 4 0
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Author : Fakher Chaari
language : en
Publisher: Springer Nature
Release Date : 2021-08-20
Smart Monitoring Of Rotating Machinery For Industry 4 0 written by Fakher Chaari and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-20 with Technology & Engineering categories.
This book offers an overview of current methods for the intelligent monitoring of rotating machines. It describes the foundations of smart monitoring, guiding readers to develop appropriate machine learning and statistical models for answering important challenges, such as the management and analysis of a large volume of data. It also discusses real-world case studies, highlighting some practical issues and proposing solutions to them. The book offers extensive information on research trends, and innovative strategies to solve emerging, practical issues. It addresses both academics and professionals dealing with condition monitoring, and mechanical and production engineering issues, in the era of industry 4.0.
Transfer Learning For Rotary Machine Fault Diagnosis And Prognosis
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Author : Ruqiang Yan
language : en
Publisher: Elsevier
Release Date : 2023-11-10
Transfer Learning For Rotary Machine Fault Diagnosis And Prognosis written by Ruqiang Yan and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Business & Economics categories.
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
Sensor Signal And Information Processing Iii
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Author : Wai Lok Woo
language : en
Publisher: MDPI
Release Date : 2021-02-05
Sensor Signal And Information Processing Iii written by Wai Lok Woo and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-05 with Technology & Engineering categories.
In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem-solving. These algorithms have the capacity to generalize and discover knowledge for themselves and to learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves the mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topics range from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspired filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensor signal processing.
New Generation Artificial Intelligence Driven Diagnosis And Maintenance Techniques
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Author : Guangrui Wen
language : en
Publisher: Springer
Release Date : 2024-06-06
New Generation Artificial Intelligence Driven Diagnosis And Maintenance Techniques written by Guangrui Wen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-06 with Computers categories.
The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance. This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools. The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance.
Intelligent Fault Diagnosis And Health Assessment For Complex Electro Mechanical Systems
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Author : Weihua Li
language : en
Publisher: Springer Nature
Release Date : 2023-09-10
Intelligent Fault Diagnosis And Health Assessment For Complex Electro Mechanical Systems written by Weihua Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-10 with Technology & Engineering categories.
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.
Multicriteria And Optimization Models For Risk Reliability And Maintenance Decision Analysis
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Author : Adiel Teixeira de Almeida
language : en
Publisher: Springer Nature
Release Date : 2022-06-28
Multicriteria And Optimization Models For Risk Reliability And Maintenance Decision Analysis written by Adiel Teixeira de Almeida and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-28 with Business & Economics categories.
This book considers a broad range of areas from decision making methods applied in the contexts of Risk, Reliability and Maintenance (RRM). Intended primarily as an update of the 2015 book Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis, this edited work provides an integration of applied probability and decision making. Within applied probability, it primarily includes decision analysis and reliability theory, amongst other topics closely related to risk analysis and maintenance. In decision making, it includes multicriteria decision making/aiding (MCDM/A) methods and optimization models. Within MCDM, in addition to decision analysis, some of the topics related to mathematical programming areas are considered, such as multiobjective linear programming, multiobjective nonlinear programming, game theory and negotiations, and multiobjective optimization. Methods related to these topics have been applied to the context of RRM. In MCDA, several other methods are considered, such as outranking methods, rough sets and constructive approaches. The book addresses an innovative treatment of decision making in RRM, improving the integration of fundamental concepts from both areas of RRM and decision making. This is accomplished by presenting current research developments in decision making on RRM. Some pitfalls of decision models on practical applications on RRM are discussed and new approaches for overcoming those drawbacks are presented.