Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Title
Intelligent fault diagnosis and health assessment for complex electro-mechanical systems / Weihua Li, Xiaoli Zhang, Ruqiang Yan.
ISBN
9789819935376 (electronic bk.)
9819935377 (electronic bk.)
9789819935369
9819935369
Published
Singapore : Springer, 2023.
Language
English
Description
1 online resource (xi, 467 pages) : illustrations (some color)
Other Standard Identifiers
10.1007/978-981-99-3537-6 doi
Call Number
TA169.6
Dewey Decimal Classification
620/.00452
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed September 19, 2023).
Chapter 1 Introduction
Chapter 2 Supervised SVM based intelligent fault diagnosis methods
Chapter 3 Semi-supervised Learning Based Intelligent Fault Diagnosis Methods
Chapter 4 Manifold learning based intelligent fault diagnosis and prognostics
Chapter 5 Deep learning based machinery fault diagnosis
Chapter 6 Phase space reconstruction based on machinery system degradation tracking and fault prognostics
Chapter 7 Complex electro-mechanical system operational reliability assessment and health maintenance.
