Introduction of Intelligent Machine Fault Diagnosis and Prognosis

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Publisher :
ISBN 13 : 9781606922637
Total Pages : 0 pages
Book Rating : 4.9/5 (226 download)

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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.

Introduction of Intelligent Machine Fault Diagnosis and Prognosis

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (723 download)

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Book Synopsis Introduction of Intelligent Machine Fault Diagnosis and Prognosis by :

Download or read book Introduction of Intelligent Machine Fault Diagnosis and Prognosis written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Intelligent Fault Diagnosis and Prognosis for Engineering Systems

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Publisher : Wiley
ISBN 13 : 9780471729990
Total Pages : 0 pages
Book Rating : 4.7/5 (299 download)

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Book Synopsis Intelligent Fault Diagnosis and Prognosis for Engineering Systems by : George Vachtsevanos

Download or read book Intelligent Fault Diagnosis and Prognosis for Engineering Systems written by George Vachtsevanos and published by Wiley. This book was released on 2006-09-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery

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Publisher : Butterworth-Heinemann
ISBN 13 : 0128115351
Total Pages : 376 pages
Book Rating : 4.1/5 (281 download)

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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

Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems

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Publisher : Springer Nature
ISBN 13 : 9811691312
Total Pages : 292 pages
Book Rating : 4.8/5 (116 download)

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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

Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems

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Publisher : Elsevier
ISBN 13 : 0128224738
Total Pages : 419 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems by : Hamid Reza Karimi

Download or read book Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems written by Hamid Reza Karimi and published by Elsevier. This book was released on 2021-06-14 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis

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Publisher : Elsevier
ISBN 13 : 0323914233
Total Pages : 314 pages
Book Rating : 4.3/5 (239 download)

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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

Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems

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Publisher : Springer Nature
ISBN 13 : 9819935377
Total Pages : 474 pages
Book Rating : 4.8/5 (199 download)

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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.

Fault Detection, Diagnosis and Prognosis

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Publisher : BoD – Books on Demand
ISBN 13 : 1789842131
Total Pages : 177 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis Fault Detection, Diagnosis and Prognosis by : Fausto Pedro García Márquez

Download or read book Fault Detection, Diagnosis and Prognosis written by Fausto Pedro García Márquez and published by BoD – Books on Demand. This book was released on 2020-02-05 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime. Advances in mathematics, modeling, computational techniques, dynamic analysis, etc. are employed analytically. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support the analysis of prognostic problems with defined constraints and requirements. The book is intended for graduate students and professionals in industrial engineering, business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying maintenance or needing to solve large, specific, and complex maintenance management problems as part of their jobs. The work will also be of interest to researches from academia.

Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems

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Publisher : CRC Press
ISBN 13 : 1000594939
Total Pages : 87 pages
Book Rating : 4.0/5 (5 download)

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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.

Fault Diagnosis

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Publisher : Springer Science & Business Media
ISBN 13 : 3642186157
Total Pages : 936 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Fault Diagnosis by : Józef Korbicz

Download or read book Fault Diagnosis written by Józef Korbicz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems

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Publisher : CRC Press
ISBN 13 : 1040026591
Total Pages : 217 pages
Book Rating : 4.0/5 (4 download)

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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.

A Remote Machine Condition Monitoring Framework for Intelligent Fault Diagnosis and Prognosis

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Publisher :
ISBN 13 :
Total Pages : 500 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis A Remote Machine Condition Monitoring Framework for Intelligent Fault Diagnosis and Prognosis by : Muhammad Farrukh Yaqub

Download or read book A Remote Machine Condition Monitoring Framework for Intelligent Fault Diagnosis and Prognosis written by Muhammad Farrukh Yaqub and published by . This book was released on 2012 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate remote equipment health monitoring systems can improve the efficiency of theagile processes e.g. agile manufacturing facilities, processing, mining and utilities etc. Theimpairments in industrial equipment are inevitable over the time. These impairments couldbe due to continuous meshing of the mechanical components, environment issues or nonidealisticoperating conditions such as contaminated electrical supplies etc. Despite ofdeterioration in the industrial equipment, in order to ensure reliable process operation, arobust online condition monitoring system becomes need of the hour.An efficient online condition monitoring system can provide predictive repairmaintenance schedule well ahead of the breakdown instances. In this research work, aframework for remote machine condition monitoring is presented to address the challengesin reliable data acquisition, inchoate fault diagnosis under varying industrial conditions andfault prognosis in terms of residual life prediction to minimise unplanned outages.Reliable and flexible data acquisition is necessary for continuous equipment monitoringin agile systems. In this thesis, wireless data acquisition, in the presence of co-existingnetworks, has been investigated for agile processes, e.g., shop floors of manufacturingfacility where the underlying processes are prone to change both in orientation and type,due to new market trends.The problem of fault diagnosis essentially deals with categorizing the type of the faultarising in the machine, using the fault signatures captured from the wireless dataacquisition unit. The fault diagnostic module comprises of signal processing, featureextraction and fault detection. The proposed framework optimally and adaptively tunesthese constituents, particularly for inchoate, severity invariant machine fault diagnosis andmultiple points-defect modelling.Fault prognosis demands continuous monitoring of the fault propagation to estimate theseverity of the fault and hence, the residual life prediction of the equipment accordingly.The proposed residual life prediction scheme helps in achieving an optimized schedulingof maintenance to meet industrial demands, challenges and commitments.Proposed remote equipment health monitoring framework is flexible; and can beapplied to industries e.g., mining, petroleum, utilities, transport, agriculture, space and building etc.

Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives

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Publisher : John Wiley & Sons
ISBN 13 : 1119722780
Total Pages : 448 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives by : Elias G. Strangas

Download or read book Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives written by Elias G. Strangas and published by John Wiley & Sons. This book was released on 2021-11-19 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives An insightful treatment of present and emerging technologies in fault diagnosis and failure prognosis In Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives, a team of distinguished researchers delivers a comprehensive exploration of current and emerging approaches to fault diagnosis and failure prognosis of electrical machines and drives. The authors begin with foundational background, describing the physics of failure, the motor and drive designs and components that affect failure and signals, signal processing, and analysis. The book then moves on to describe the features of these signals and the methods commonly used to extract these features to diagnose the health of a motor or drive, as well as the methods used to identify the state of health and differentiate between possible faults or their severity. Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives discusses the tools used to recognize trends towards failure and the estimation of remaining useful life. It addresses the relationships between fault diagnosis, failure prognosis, and fault mitigation. The book also provides: A thorough introduction to the modes of failure, how early failure precursors manifest themselves in signals, and how features extracted from these signals are processed A comprehensive exploration of the fault diagnosis, the results of characterization, and how they used to predict the time of failure and the confidence interval associated with it A focus on medium-sized drives, including induction, permanent magnet AC, reluctance, and new machine and drive types Perfect for researchers and students who wish to study or practice in the rea of electrical machines and drives, Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives is also an indispensable resource for researchers with a background in signal processing or statistics.

Artificial Intelligence

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Publisher : BoD – Books on Demand
ISBN 13 : 178923364X
Total Pages : 466 pages
Book Rating : 4.7/5 (892 download)

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Book Synopsis Artificial Intelligence by : Marco Antonio Aceves-Fernandez

Download or read book Artificial Intelligence written by Marco Antonio Aceves-Fernandez and published by BoD – Books on Demand. This book was released on 2018-06-27 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is taking an increasingly important role in our society. From cars, smartphones, airplanes, consumer applications, and even medical equipment, the impact of AI is changing the world around us. The ability of machines to demonstrate advanced cognitive skills in taking decisions, learn and perceive the environment, predict certain behavior, and process written or spoken languages, among other skills, makes this discipline of paramount importance in today's world. Although AI is changing the world for the better in many applications, it also comes with its challenges. This book encompasses many applications as well as new techniques, challenges, and opportunities in this fascinating area.

Fault Diagnosis of Dynamic Systems

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Publisher : Springer
ISBN 13 : 3030177289
Total Pages : 462 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Fault Diagnosis of Dynamic Systems by : Teresa Escobet

Download or read book Fault Diagnosis of Dynamic Systems written by Teresa Escobet and published by Springer. This book was released on 2019-06-22 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault Diagnosis of Dynamic Systems provides readers with a glimpse into the fundamental issues and techniques of fault diagnosis used by Automatic Control (FDI) and Artificial Intelligence (DX) research communities. The book reviews the standard techniques and approaches widely used in both communities. It also contains benchmark examples and case studies that demonstrate how the same problem can be solved using the presented approaches. The book also introduces advanced fault diagnosis approaches that are currently still being researched, including methods for non-linear, hybrid, discrete-event and software/business systems, as well as, an introduction to prognosis. Fault Diagnosis of Dynamic Systems is valuable source of information for researchers and engineers starting to work on fault diagnosis and willing to have a reference guide on the main concepts and standard approaches on fault diagnosis. Readers with experience on one of the two main communities will also find it useful to learn the fundamental concepts of the other community and the synergies between them. The book is also open to researchers or academics who are already familiar with the standard approaches, since they will find a collection of advanced approaches with more specific and advanced topics or with application to different domains. Finally, engineers and researchers looking for transferable fault diagnosis methods will also find useful insights in the book.

Intelligent Diagnosis and Prognosis of Industrial Networked Systems

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Publisher : CRC Press
ISBN 13 : 1439840598
Total Pages : 332 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Intelligent Diagnosis and Prognosis of Industrial Networked Systems by : Chee Khiang Pang

Download or read book Intelligent Diagnosis and Prognosis of Industrial Networked Systems written by Chee Khiang Pang and published by CRC Press. This book was released on 2017-07-28 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified perspectives in system analysis and design for engineering applications. Intelligent Diagnosis and Prognosis of Industrial Networked Systems proposes linear mathematical tool sets that can be applied to realistic engineering systems. The book offers an overview of the fundamentals of vectors, matrices, and linear systems theory required for intelligent diagnosis and prognosis of industrial networked systems. Building on this theory, it then develops automated mathematical machineries and formal decision software tools for real-world applications. The book includes portable tool sets for many industrial applications, including: Forecasting machine tool wear in industrial cutting machines Reduction of sensors and features for industrial fault detection and isolation (FDI) Identification of critical resonant modes in mechatronic systems for system design of R&D Probabilistic small-signal stability in large-scale interconnected power systems Discrete event command and control for military applications The book also proposes future directions for intelligent diagnosis and prognosis in energy-efficient manufacturing, life cycle assessment, and systems of systems architecture. Written in a concise and accessible style, it presents tools that are mathematically rigorous but not involved. Bridging academia, research, and industry, this reference supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students in the field.