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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 376 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 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 2021 7th International Conference on Control, Automation and Robotics (ICCAR) by : IEEE Staff
Download or read book 2021 7th International Conference on Control, Automation and Robotics (ICCAR) written by IEEE Staff and published by . This book was released on 2021-04-23 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 2021 The 7th International Conference on Control, Automation and Robotics (ICCAR 2021) will take place at Singapore during April 23 26, 2021 On the theoretical side, this conference features papers focusing on intelligent systems engineering, distributed intelligence systems, multi level systems, intelligent control, multi robot systems, cooperation and coordination of unmanned vehicle systems, etc On the application side, it emphasizes autonomous systems, industrial robotic systems, multi robot systems, aerial vehicles, underwater robots and sensor based control For the first time ever, ICCAR affords the delegates unparalleled opportunities to interact and network with qualified professionals from throughout the world We are looking forward to welcoming you at the garden City Singapore
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 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 272 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 Domain Adaptation in Computer Vision Applications by : Gabriela Csurka
Download or read book Domain Adaptation in Computer Vision Applications written by Gabriela Csurka and published by Springer. This book was released on 2018-05-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive text/reference presents a broad review of diverse domain adaptation (DA) methods for machine learning, with a focus on solutions for visual applications. The book collects together solutions and perspectives proposed by an international selection of pre-eminent experts in the field, addressing not only classical image categorization, but also other computer vision tasks such as detection, segmentation and visual attributes. Topics and features: surveys the complete field of visual DA, including shallow methods designed for homogeneous and heterogeneous data as well as deep architectures; presents a positioning of the dataset bias in the CNN-based feature arena; proposes detailed analyses of popular shallow methods that addresses landmark data selection, kernel embedding, feature alignment, joint feature transformation and classifier adaptation, or the case of limited access to the source data; discusses more recent deep DA methods, including discrepancy-based adaptation networks and adversarial discriminative DA models; addresses domain adaptation problems beyond image categorization, such as a Fisher encoding adaptation for vehicle re-identification, semantic segmentation and detection trained on synthetic images, and domain generalization for semantic part detection; describes a multi-source domain generalization technique for visual attributes and a unifying framework for multi-domain and multi-task learning. This authoritative volume will be of great interest to a broad audience ranging from researchers and practitioners, to students involved in computer vision, pattern recognition and machine learning.
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 Performance Optimization of Fault Diagnosis Methods for Power Systems by : Dinghui Wu
Download or read book Performance Optimization of Fault Diagnosis Methods for Power Systems written by Dinghui Wu and published by Springer Nature. This book was released on 2022-09-18 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the performance optimization of fault diagnosis methods for power systems including both model-driven ones, such as the linear parameter varying algorithm, and data-driven ones, such as random matrix theory. Studies on fault diagnosis of power systems have long been the focus of electrical engineers and scientists. Pursuing a holistic approach to improve the accuracy and efficiency of existing methods, the underlying concepts toward several algorithms are introduced and then further applied in various situations for fault diagnosis of power systems in this book. The primary audience for the book would be the scholars and graduate students whose research topics including the control theory, applied mathematics, fault detection, and so on.
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 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 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.
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 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE) by : IEEE Staff
Download or read book 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE) written by IEEE Staff and published by . This book was released on 2021-03-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The topics related to reporting applied big data, artificial intelligence and internet of things engineering,etc will be pondered on, through the interactions between academic researchers from different regions and cultures Timely research topics will be discussed via presentations of the latest progresses and developments of applied big data, artificial intelligence and internet of things engineering for solving social problems
Book Synopsis Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems by : Yaguo Lei
Download or read book Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems written by Yaguo Lei and published by Springer Nature. This book was released on 2022-10-19 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
