Computational Intelligence in Fault Diagnosis

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Publisher : Springer Science & Business Media
ISBN 13 : 184628631X
Total Pages : 374 pages
Book Rating : 4.15/5 ( download)

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Book Synopsis Computational Intelligence in Fault Diagnosis by : Vasile Palade

Download or read book Computational Intelligence in Fault Diagnosis written by Vasile Palade and published by Springer Science & Business Media. This book was released on 2006-12-22 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most recent concerns and research results in industrial fault diagnosis using intelligent techniques. It focuses on computational intelligence applications to fault diagnosis with real-world applications used in different chapters to validate the different diagnosis methods. The book includes one chapter dealing with a novel coherent fault diagnosis distributed methodology for complex systems.

Fault Diagnosis

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Publisher : Springer Science & Business Media
ISBN 13 : 3642186157
Total Pages : 936 pages
Book Rating : 4.58/5 ( 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.

Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

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Publisher : Springer
ISBN 13 : 3319015478
Total Pages : 196 pages
Book Rating : 4.77/5 ( download)

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Book Synopsis Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis by : Marcin Mrugalski

Download or read book Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis written by Marcin Mrugalski and published by Springer. This book was released on 2013-08-04 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practical applications.

Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

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Publisher : Springer Science & Business Media
ISBN 13 : 1447151852
Total Pages : 388 pages
Book Rating : 4.52/5 ( download)

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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.

Computational Intelligence in Emerging Technologies for Engineering Applications

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Publisher : Springer Nature
ISBN 13 : 3030344096
Total Pages : 301 pages
Book Rating : 4.92/5 ( download)

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Book Synopsis Computational Intelligence in Emerging Technologies for Engineering Applications by : Orestes Llanes Santiago

Download or read book Computational Intelligence in Emerging Technologies for Engineering Applications written by Orestes Llanes Santiago and published by Springer Nature. This book was released on 2020-02-14 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores applications of computational intelligence in key and emerging fields of engineering, especially with regard to condition monitoring and fault diagnosis, inverse problems, decision support systems and optimization. These applications can be beneficial in a broad range of contexts, including: water distribution networks, manufacturing systems, production and storage of electrical energy, heat transfer, acoustic levitation, uncertainty and robustness of infinite-dimensional objects, fatigue failure prediction, autonomous navigation, nanotechnology, and the analysis of technological development indexes. All applications, mathematical and computational tools, and original results are presented using rigorous mathematical procedures. Further, the book gathers contributions by respected experts from 22 different research centers and eight countries: Brazil, Cuba, France, Hungary, India, Japan, Romania and Spain. The book is intended for use in graduate courses on applied computation, applied mathematics, and engineering, where tools like computational intelligence and numerical methods are applied to the solution of real-world problems in emerging areas of engineering.

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 : 4.35/5 ( 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.

A Hybrid Approach for Power Plant Fault Diagnostics

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Publisher : Springer
ISBN 13 : 3319718711
Total Pages : 283 pages
Book Rating : 4.12/5 ( download)

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Book Synopsis A Hybrid Approach for Power Plant Fault Diagnostics by : Tamiru Alemu Lemma

Download or read book A Hybrid Approach for Power Plant Fault Diagnostics written by Tamiru Alemu Lemma and published by Springer. This book was released on 2017-12-30 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a hybrid approach to fault detection and diagnostics. It presents a detailed analysis related to practical applications of the fault detection and diagnostics framework, and highlights recent findings on power plant nonlinear model identification and fault diagnostics. The effectiveness of the methods presented is tested using data acquired from actual cogeneration and cooling plants (CCPs). The models presented were developed by applying Neuro-Fuzzy (NF) methods. The book offers a valuable resource for researchers and practicing engineers alike.

Photovoltaic Systems

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Publisher : CRC Press
ISBN 13 : 100054589X
Total Pages : 164 pages
Book Rating : 4.90/5 ( download)

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Book Synopsis Photovoltaic Systems by : K.Mohana Sundaram

Download or read book Photovoltaic Systems written by K.Mohana Sundaram and published by CRC Press. This book was released on 2022-03-07 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive insight into the fault detection techniques implemented for photovoltaic (PV) panels. It includes studies related to predictive maintenance needed to improve the performance of the solar PV systems using Artificial Intelligence (AI) techniques. The readers gain knowledge on the fault identification algorithm and the significance of all such algorithms in real-time power system applications. Gives detailed overview of fundamental concepts of fault diagnosis algorithm for solar PV system Explains AC and DC side of the solar PV system-based electricity generation with real-time examples Covers effective extraction of the energy from solar radiation Illustrates artificial intelligence techniques for detecting the faults occurring in the solar PV system Includes MATLAB® based simulations and results on fault diagnosis including case studies This book is aimed at researchers, professionals and graduate students in electrical engineering, artificial intelligence, control algorithms, energy engineering, photovoltaic systems, industrial electronics.

Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 3540798714
Total Pages : 223 pages
Book Rating : 4.12/5 ( download)

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Book Synopsis Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes by : Krzysztof Patan

Download or read book Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes written by Krzysztof Patan and published by Springer Science & Business Media. This book was released on 2008-06-24 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e?ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re?ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti?c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available.

Power System Fault Diagnosis

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Author :
Publisher : Elsevier
ISBN 13 : 032388430X
Total Pages : 430 pages
Book Rating : 4.03/5 ( download)

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Book Synopsis Power System Fault Diagnosis by : Md Shafiullah

Download or read book Power System Fault Diagnosis written by Md Shafiullah and published by Elsevier. This book was released on 2022-01-14 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Power System Fault Diagnosis: A Wide Area Measurement Based Intelligent Approach is a comprehensive overview of the growing interests in efficient diagnosis of power system faults to reduce outage duration and revenue losses by expediting the restoration process.This book illustrates intelligent fault diagnosis schemes for power system networks, at both transmission and distribution levels, using data acquired from phasor measurement units. It presents the power grid modeling, fault modeling, feature extraction processes, and various fault diagnosis techniques, including artificial intelligence techniques, in steps. The book also incorporates uncertainty associated with line parameters, fault information (resistance and inception angle), load demand, renewable energy generation, and measurement noises. Provides step-by-step modeling of power system networks (distribution and transmission) and faults in MATLAB/SIMULINK and real-time digital simulator (RTDS) platforms Presents feature extraction processes using advanced signal processing techniques (discrete wavelet and Stockwell transforms) and an easy-to-understand optimal feature selection method Illustrates comprehensive results in the graphical and tabular formats that can be easily reproduced by beginners Highlights various utility practices for fault location in transmission networks, distribution systems, and underground cables.