12 edition of Computational Intelligence in Fault Diagnosis (Advanced Information and Knowledge Processing) found in the catalog.
Published
August 9, 2006
by Springer
.
Written in English
Edition Notes
Contributions | Vasile Palade (Editor), Cosmin Danut Bocaniala (Editor), Lakhmi Jain (Editor) |
The Physical Object | |
---|---|
Format | Hardcover |
Number of Pages | 362 |
ID Numbers | |
Open Library | OL8962560M |
ISBN 10 | 1846283434 |
ISBN 10 | 9781846283437 |
The Hybrid Computational Intelligence for Pattern Analysis series aims to provide insights into the latest trends in hybrid intelligent algorithms and architectures. It also focuses on the application perspectives of these hybrids intelligent techniques to . Advanced Information and Knowledge Processing Series Editors Professor Lakhmi Jain @ Professor Xindong Wu [email protected] Also in .
Computational Intelligence in Microelectronics Manufacturing, Gary S. May Monitoring and Diagnosing Manufacturing Processes Using Fuzzy Set Theory, R. Du and Yangsheng Xu Fuzzy Neural Network and Wavelet for Tool Condition Monitoring, Xiaoli Li QUALITY ASSURANCE AND FAULT DIAGNOSIS. Application of Artificial Intelligence to Gearbox Fault Diagnosis: A Review: /ch Gearboxes are employed in a wide variety of applications, ranging from small domestic appliances to the rather gigantic power plants and marine propulsionAuthor: Anand Parey, Amandeep Singh Ahuja.
Computational Intelligence In Manufacturing Handbook. Back to book. chapter 2. 28 Pages. and fault diagnosis. This paper presents a survey of existing neural network applications to intelligent manufacturing. Covering the whole spectrum of neural network applications to manufacturing, this chapter provides a comprehensive review of the. An approach to robust fault diagnosis in mechanical systems using computational intelligence Article in Journal of Intelligent Manufacturing July with 80 Reads How we measure 'reads'.
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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 : Vasile Palade.
Computational Intelligence in Fault Diagnosis presents the most recent concerns and research results in industrial fault diagnosis using intelligent techniques, and will be of interest to application engineers/technologists, graduates and researchers wishing to apply these techniques, enhance their knowledge, as well as build up a foundation for further : $ Computational Intelligence in Fault Diagnosis presents the most recent concerns and research results in industrial fault diagnosis using intelligent techniques, and will be of interest to application engineers/technologists, graduates and researchers wishing to apply these techniques, enhance their knowledge, as well as build up a foundation for further study.
Presenting the latest developments and research results on fault diagnosis approaches using computational intelligence methodologies, this book opens with a review of the state-of-the-art before focusing on various theoretical aspects of computational intelligence methodologies applied to real-world fault diagnosis rs deal with topics such as fuzzy sets applications to fault diagnosis, neural network based fault diagnosis applications and neuro-fuzzy techniques for fault.
Presenting the newest developments and analysis outcomes on fault analysis approaches utilizing computational intelligence methodologies, this book opens with a assessment of the state-of-the-artwork earlier than specializing in numerous theoretical points of computational intelligence methodologies utilized to actual-world fault analysis issues.
This first chapter of the book introduces the reader to the area of computational intelligence techniques and to their significant and abundant applications to fault diagnosis.
Fault diagnosis represents an important contemporary research field, due to the ever-increasing need for safety, maintainability and reliability of industrial by: This book explores computational intelligence in engineering, especially concerning condition monitoring and fault diagnosis, inverse problems, decision support systems, and optimization.
It is intended for graduate courses on applied computation, applied mathematics, and engineering. 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.
In this chapter, selected aspects of the fault diagnosis problem for control systems have been considered with special attention paid to fault detection and, to a lesser extent, fault isolation.
In particular, the robustness problem of FDI with respect to the requirement to maximise sensitivity to faults while minimising (or decoupling) the effect of uncertain effects through unknown inputs Cited by: Summary: An overview of the state of the art in the development of computational intelligence techniques pertaining to fault diagnosis.
Covering all computational intelligence techniques, the book gradually exposes the reader to these various methods in its eleven chapters. (not yet rated) 0 with reviews - Be the first. Buy Computational Intelligence in Fault Diagnosis Books online at best prices in India from Buy Computational Intelligence in Fault Diagnosis online of India’s Largest Online Book Store, Only Genuine Products.
Lowest price and Replacement Guarantee. Cash On Delivery Available. Summary: An overview of the state of the art in the development of computational intelligence techniques pertaining to fault diagnosis.
Covering all computational intelligence techniques, the book gradually exposes the reader to these various methods in its eleven chapters. Combined computational intelligence and analytical methods in fault diagnosis p.
– (44) In this chapter, selected aspects of the fault diagnosis problem for control systems have been considered with special attention paid to fault detection and, to a lesser extent, fault isolation. Fault Diagnosis Using Computational Intelligence Fault diagnosis combining fault mechanism and detection techniques; it is a subject based on the theory of signal processing and pattern recognition.
Various algorithms based on computational intelligence for fault diagnosis are presented in this by: 2 Fault Diagnosis Using Computational Intelligence Fault diagnosis combining fault mechanism and detection techniques; it is a subject based on the theory of signal processing and pattern recognition.
Various algorithms based on computational intelligence for fault diagnosis are presented in this section. Fig. 1 shows the taxonomy of theCited by: This paper attempts to present a comprehensive review of AI algorithms in rotating machinery fault diagnosis, from both the views of theory background and industrial applications.
A brief introduction of different AI algorithms is presented first, including the following methods: k -nearest neighbour, naive Bayes, support vector machine, artificial neural network and deep by: Fault diagnosis of rotating machinery plays a significant role for the reliability and safety of modern industrial systems.
As an emerging field in industrial applications and an effective solution for fault recognition, artificial intelligence (AI) techniques have been receiving increasing attention from academia and by: Presenting the latest developments and research results on fault diagnosis approaches using computational intelligence methodologies, this book opens with a.
Computational Intelligence in Fault Diagnosis Presenting the latest developments and research results on fault diagnosis approaches using computational intelligence methodologies, this book opens with a review of.
Computational Intelligence in Fault Diagnosis by cosmin danut. : Computational Intelligence in Fault Diagnosis. Assessment of computational intelligence and conventional dissolved gas analysis methods for transformer fault diagnosis Abstract: Transformers are vital components of power systems as they are situated between energy generation and consumers and their failure disrupts the use of electrical by: 9.
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.Principal Component Analysis for Fault Detection and Diagnosis.
Experience with a pilot plant Thamara Villegas method of fault detection and diagnosis is based on the definition Advances in Computational Intelligence, Man-Machine Systems and Cybernetics ISBN: S = 1.Dynamic deep learning algorithm based on incremental compensation for fault diagnosis model Authors Jing Liu 1, 2, 3, [email protected] @, Yacheng An 1, Runliang Dou 4*, [email protected], Haipeng Ji 3, 5, [email protected]: Jing Liu, Yacheng An, Runliang Dou, Haipeng Ji.