Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery

2016-11-02 Technology & Engineering

Author : Yaguo Lei
Release : 2016-11-02
Genre : Technology & Engineering
Kind : eBook
Book Rating : 351/5 ( reviews)

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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. This book was released on 2016-11-02. 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

Intelligent Fault Diagnosis and Prognosis for Engineering Systems

2006-09-29 Technology & Engineering

Author : George Vachtsevanos
Release : 2006-09-29
Genre : Technology & Engineering
Kind : eBook
Book Rating : 990/5 ( reviews)

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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. This book was released on 2006-09-29. 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

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

2022-10-19 Technology & Engineering

Author : Yaguo Lei
Release : 2022-10-19
Genre : Technology & Engineering
Kind : eBook
Book Rating : 312/5 ( reviews)

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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. This book was released on 2022-10-19. 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

Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis

2023-11-10 Business & Economics

Author : Ruqiang Yan
Release : 2023-11-10
Genre : Business & Economics
Kind : eBook
Book Rating : 233/5 ( reviews)

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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. This book was released on 2023-11-10. 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 for Rotating Machines Using Deep Learning

2019 Machine learning

Author : Jorge Chuya Sumba
Release : 2019
Genre : Machine learning
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Intelligent Fault Diagnosis for Rotating Machines Using Deep Learning by : Jorge Chuya Sumba

Download or read book Intelligent Fault Diagnosis for Rotating Machines Using Deep Learning written by Jorge Chuya Sumba. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt: The diagnosis of failures in high-speed machining centers and other rotary machines is critical in manufacturing systems, because early detection can save a representative amount of time and cost. Fault diagnosis systems generally have two blocks: feature extraction and classification. Feature extraction affects the performance of the prediction model, and essential information is extracted by identifying high-level abstract and representative characteristics. Deep learning (DL) provides an effective way to extract the characteristics of raw data without prior knowledge, compared with traditional machine learning (ML) methods. A feature learning approach was applied using one-dimensional (1-D) convolutional neural networks (CNN) that works directly with raw vibration signals. The network structure consists of small convolutional kernels to perform a nonlinear mapping and extract features; the classifier is a softmax layer. The method has achieved satisfactory performance in terms of prediction accuracy that reaches ∼99 % and ∼97 % using a standard bearings database: the processing time is suitable for real-time applications with ∼8 ms per signal, and the repeatability has a low standard deviation

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