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Deep Learning Based Machinery Fault Diagnostics
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Book Synopsis Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems by : Rui Yang
Download or read book Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems written by Rui Yang and published by CRC Press. This book was released on 2022-06-16 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Deep Learning-Based Machinery Fault Diagnostics by : Hongtian Chen
Download or read book Deep Learning-Based Machinery Fault Diagnostics written by Hongtian Chen and published by Mdpi AG. This book was released on 2022-09-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a compilation for experts, scholars, and researchers to present the most recent advancements, from theoretical methods to the applications of sophisticated fault diagnosis techniques. The deep learning methods for analyzing and testing complex mechanical systems are of particular interest. Special attention is given to the representation and analysis of system information, operating condition monitoring, the establishment of technical standards, and scientific support of machinery fault diagnosis.
Book Synopsis Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery by : Yaguo Lei
Download or read book Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery written by Yaguo Lei and published by Butterworth-Heinemann. This book was released on 2016-11-02 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Fault Diagnosis of Induction Motors by : Jawad Faiz
Download or read book Fault Diagnosis of Induction Motors written by Jawad Faiz and published by IET. This book was released on 2017-08-29 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods by : Chris Aldrich
Download or read book Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods written by Chris Aldrich and published by Springer Science & Business Media. This book was released on 2013-06-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.
Book Synopsis Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems by : Rui Yang
Download or read book Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems written by Rui Yang and published by CRC Press. This book was released on 2022-06-16 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems by : Ruqiang Yan
Download or read book Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems written by Ruqiang Yan and published by CRC Press. This book was released on 2024-06-06 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to highlight the potential of deep learning (DL)-enabled methods in intelligent fault diagnosis (IFD), along with their benefits and contributions. The authors first introduce basic applications of DL-enabled IFD, including auto-encoders, deep belief networks, and convolutional neural networks. Advanced topics of DL-enabled IFD are also explored, such as data augmentation, multi-sensor fusion, unsupervised deep transfer learning, neural architecture search, self-supervised learning, and reinforcement learning. Aiming to revolutionize the nature of IFD, Deep Neural Networks-Enabled Intelligent Fault Diangosis of Mechanical Systems contributes to improved efficiency, safety, and reliability of mechanical systems in various industrial domains. The book will appeal to academic researchers, practitioners, and students in the fields of intelligent fault diagnosis, prognostics and health management, and deep learning.
Book Synopsis Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 by : Yaxin Bi
Download or read book Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 written by Yaxin Bi and published by Springer. This book was released on 2017-08-22 with total page 1084 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings of the SAI Intelligent Systems Conference 2016 (IntelliSys 2016) offer a remarkable collection of papers on a wide range of topics in intelligent systems, and their applications to the real world. Authors hailing from 56 countries on 5 continents submitted 404 papers to the conference, attesting to the global importance of the conference’s themes. After being reviewed, 222 papers were accepted for presentation, and 168 were ultimately selected for these proceedings. Each has been reviewed on the basis of its originality, novelty and rigorousness. The papers not only present state-of-the-art methods and valuable experience from researchers in the related research areas; they also outline the field’s future development.
Book Synopsis Predictive Method for Machinery Fault Detection Using Deep Learning and Vibration Images by : Carlos Alberto Alves Viana
Download or read book Predictive Method for Machinery Fault Detection Using Deep Learning and Vibration Images written by Carlos Alberto Alves Viana and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present work brings the study of different approaches for identification of faults in rotating machines using different classes of faults provided by the MaFaulDa database. The use of fault identification tools is of vital importance in the industrial scenario to predict machine problems before they happen, reducing costs and equipment downtime. In the context of Machine Learning, different models were used for this task. Initially, CNN neural network models were tested for classification, where the inputs were the unprocessed vibration graphs (acceleration in time, acceleration in frequency and acceleration orbits of radial x tangential cross components). A greater global accuracy, in the order of 89.4%, was observed when acceleration graphs in the frequency domain were utilized. The approach of extracting statistical parameters from the model was also tested, resulting in an overall accuracy of 60.5%. Then, a new approach was proposed in an unprecedented way: the use of the vibration images technique with signals in the frequency domain. The proposed solution resulted in a very good classification accuracy of 99.4%, even greater than when the same approach was applied to signals in the time domain (97.0%). Finally, the method was tested on incipient faults, where a new database with the lowest fault intensities was used for testing purpose. Even in such a challenging scenario for fault prediction, both resulting accuracies in the time and frequency domains were satisfactory, respectively 84.3% and 94.0%. The proposed method indicated a promising fault classification capacity, being indicated for implementation in predictive maintenance routines in the context of Industry 4.0, IoT and online machinery monitoring, due to its excellent computational cost-benefit.
Book Synopsis Condition Monitoring with Vibration Signals by : Hosameldin Ahmed
Download or read book Condition Monitoring with Vibration Signals written by Hosameldin Ahmed and published by John Wiley & Sons. This book was released on 2020-01-07 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring Clear and concise throughout, this accessible book is the first to be wholly devoted to the field of condition monitoring for rotating machines using vibration signals. It covers various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance. Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines starts by introducing readers to Vibration Analysis Techniques and Machine Condition Monitoring (MCM). It then offers readers sections covering: Rotating Machine Condition Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal processing in the time-frequency domain, methods for linear subspace learning, and the basic principles of the learning method Artificial Neural Network (ANN). They will also discover recent trends of deep learning in the field of machine condition monitoring, new feature learning frameworks based on compressive sampling, subspace learning techniques for machine condition monitoring, and much more. Covers the fundamental as well as the state-of-the-art approaches to machine condition monitoringguiding readers from the basics of rotating machines to the generation of knowledge using vibration signals Provides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs Features learning algorithms that can be used for fault diagnosis and prognosis Includes previously and recently developed dimensionality reduction techniques and classification algorithms Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.
Book Synopsis Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis by : Ruqiang Yan
Download or read book Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis written by Ruqiang Yan and published by Elsevier. This book was released on 2023-11-10 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Vibration-based Condition Monitoring by : Robert Bond Randall
Download or read book Vibration-based Condition Monitoring written by Robert Bond Randall and published by John Wiley & Sons. This book was released on 2011-03-25 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Without doubt the best modern and up-to-date text on the topic, wirtten by one of the world leading experts in the field. Should be on the desk of any practitioner or researcher involved in the field of Machine Condition Monitoring" Simon Braun, Israel Institute of Technology Explaining complex ideas in an easy to understand way, Vibration-based Condition Monitoring provides a comprehensive survey of the application of vibration analysis to the condition monitoring of machines. Reflecting the natural progression of these systems by presenting the fundamental material and then moving onto detection, diagnosis and prognosis, Randall presents classic and state-of-the-art research results that cover vibration signals from rotating and reciprocating machines; basic signal processing techniques; fault detection; diagnostic techniques, and prognostics. Developed out of notes for a course in machine condition monitoring given by Robert Bond Randall over ten years at the University of New South Wales, Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications is essential reading for graduate and postgraduate students/ researchers in machine condition monitoring and diagnostics as well as condition monitoring practitioners and machine manufacturers who want to include a machine monitoring service with their product. Includes a number of exercises for each chapter, many based on Matlab, to illustrate basic points as well as to facilitate the use of the book as a textbook for courses in the topic. Accompanied by a website www.wiley.com/go/randall housing exercises along with data sets and implementation code in Matlab for some of the methods as well as other pedagogical aids. Authored by an internationally recognised authority in the area of condition monitoring.
Book Synopsis Introduction of Intelligent Machine Fault Diagnosis and Prognosis by : O-Suk Yang
Download or read book Introduction of Intelligent Machine Fault Diagnosis and Prognosis written by O-Suk Yang and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Condition monitoring, fault diagnosis and prognosis of machinery have received considerable attention in recent years and they are increasingly becoming important in industry because of the need to increase reliability and decrease possible loss of production due to the fault of equipments. Early fault detection, diagnosis and prognosis can increase equipment availability and performance, reduce consequential damage, prolong machine life and reduce spare parts inventories and break down maintenance. With the development of the artificial intelligence techniques, many intelligent systems have been employed to assist the maintenance management task to correctly interpret the fault data. The book is very easy to study; even if the reader is a beginner in the fault diagnosis area, they do not need special prerequisite knowledge to understand the contents of this book. The book is equipped with software under MATLAB and offers many examples which are related to fault diagnosis processes. It will be very useful to readers who want to study feature-based intelligent machine fault diagnosis and prognosis techniques. The book is dedicated to graduate students of mechanical and electrical engineering, computer science and for practising engineers.
Book Synopsis Genetic and Evolutionary Computing by : Jeng-Shyang Pan
Download or read book Genetic and Evolutionary Computing written by Jeng-Shyang Pan and published by Springer Nature. This book was released on 2020-03-12 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers papers presented at the 13th International Conference on Genetic and Evolutionary Computing (ICGEC 2019), which was held in Qingdao, China, from 1st to 3rd, November 2019. Since it was established, in 2006, the ICGEC conference series has been devoted to new approaches with a focus on evolutionary computing. Today, it is a forum for the researchers and professionals in all areas of computational intelligence including evolutionary computing, machine learning, soft computing, data mining, multimedia and signal processing, swarm intelligence and security. The book appeals to policymakers, academics, educators, researchers in pedagogy and learning theory, school teachers, and other professionals in the learning industry, and further and continuing education.
Book Synopsis Filter-Based Fault Diagnosis and Remaining Useful Life Prediction by : Yong Zhang
Download or read book Filter-Based Fault Diagnosis and Remaining Useful Life Prediction written by Yong Zhang and published by CRC Press. This book was released on 2023-02-10 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data-Driven Cognitive Manufacturing - Applications in Predictive Maintenance and Zero Defect Manufacturing by : Dimitris Kiritsis
Download or read book Data-Driven Cognitive Manufacturing - Applications in Predictive Maintenance and Zero Defect Manufacturing written by Dimitris Kiritsis and published by Frontiers Media SA. This book was released on 2021-03-10 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems by : Weihua Li
Download or read book Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems written by Weihua Li and published by Springer Nature. This book was released on 2023-09-10 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
