
Filter-Based Fault Diagnosis and Remaining Useful Life Prediction
CRC Press
1st Edition
Published on 8. October 2024
Book
Paperback/Softback
262 pages
978-1-032-36254-0 (ISBN)
Description
This book unifies existing and emerging concepts concerning state estimation, fault detection, fault isolation and fault estimation on industrial systems with an emphasis on a variety of network-induced phenomena, fault diagnosis and remaining useful life for industrial equipment. It covers state estimation/monitor, fault diagnosis and remaining useful life prediction by drawing on the conventional theories of systems science, signal processing and machine learning.
Features:
Unifies existing and emerging concepts concerning robust filtering and fault diagnosis with an emphasis on a variety of network-induced complexities.
Explains theories, techniques, and applications of state estimation as well as fault diagnosis from an engineering-oriented perspective.
Provides a series of latest results in robust/stochastic filtering, multidate sample, and time-varying system.
Captures diagnosis (fault detection, fault isolation and fault estimation) for time-varying multi-rate systems.
Includes simulation examples in each chapter to reflect the engineering practice.
This book aims at graduate students, professionals and researchers in control science and application, system analysis, artificial intelligence, and fault diagnosis.
Features:
Unifies existing and emerging concepts concerning robust filtering and fault diagnosis with an emphasis on a variety of network-induced complexities.
Explains theories, techniques, and applications of state estimation as well as fault diagnosis from an engineering-oriented perspective.
Provides a series of latest results in robust/stochastic filtering, multidate sample, and time-varying system.
Captures diagnosis (fault detection, fault isolation and fault estimation) for time-varying multi-rate systems.
Includes simulation examples in each chapter to reflect the engineering practice.
This book aims at graduate students, professionals and researchers in control science and application, system analysis, artificial intelligence, and fault diagnosis.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Academic
Illustrations
110 s/w Abbildungen, 10 s/w Photographien bzw. Rasterbilder, 100 s/w Zeichnungen, 39 s/w Tabellen
39 Tables, black and white; 100 Line drawings, black and white; 10 Halftones, black and white; 110 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 16 mm
Weight
445 gr
ISBN-13
978-1-032-36254-0 (9781032362540)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Yong Zhang | Zidong Wang | Ye Yuan
Filter-Based Fault Diagnosis and Remaining Useful Life Prediction
E-Book
02/2023
1st Edition
CRC Press
€64.49
Available for download

Yong Zhang | Zidong Wang | Ye Yuan
Filter-Based Fault Diagnosis and Remaining Useful Life Prediction
Book
02/2023
1st Edition
CRC Press
€186.50
Shipment within 10-20 days

Yong Zhang | Zidong Wang | Ye Yuan
Filter-Based Fault Diagnosis and Remaining Useful Life Prediction
E-Book
02/2023
1st Edition
CRC Press
€64.49
Available for download
Persons
Author
Wuhan Univ. of Science & Tech., China
Brunel Uni, UK
Huazhong Univ. of Science & Tech., China
Content
1. Introduction . 2. Filter/Estimator Design of Networked Multirate Sampled Systems with Network-induced Phenomena. 3. Fault Detection of Networked Multirate Systems with Filter-based Methods. 4. Fault Diagnosis of Multirate Time-varying Systems with Filter-based Methods. 5. Fault Diagnosis of Modular Multilevel Converters with Machine Learning Methods. 6. Remaining Useful Life Prediction of Industrial Components with Filterbased Methods. 7. Remaining Useful Life Prediction of Industrial Components with Machine Learning Methods. 8. Conclusions and Future Topics.