INTELLIGENT FAULT DIAGNOSIS AND PROGNOSIS FOR INDUSTRIAL SYSTEMS: CROSS-DOMAIN, ZERO-SAMPLE, AND DEGRADATION...

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Hongpeng Yin, PhD (Chongqing University, China) Li Cai, B.E. (Chongqing University, China)

INTELLIGENT FAULT DIAGNOSIS AND PROGNOSIS FOR INDUSTRIAL SYSTEMS

Name: INTELLIGENT FAULT DIAGNOSIS AND PROGNOSIS FOR INDUSTRIAL SYSTEMS
Price: 262.95 AUD
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ISBN: 9780443442919

CROSS-DOMAIN, ZERO-SAMPLE, AND DEGRADATION MODELING METHODS

Hongpeng Yin, PhD (Chongqing University, China), Li Cai, B.E. (Chongqing University, China), Peng Zhang, B.E. (Chongqing University, China)

$262.95

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English

Elsevier - Health Sciences Division
01 February 2026

Engineering: general

Industrial Fault Diagnosis and Remaining Useful Life Prediction

By: Hongpeng Yin PhD (Chongqing University China), Li Cai, B.E. (Chongqing University, China), Peng Zhang, B.E. (Chongqing University, China)
Imprint: Elsevier - Health Sciences Division
Country of Publication: United States
Dimensions: Height: 229mm, Width: 152mm,
Weight: 450g
ISBN: 9780443442919
ISBN 10: 0443442916
Pages: 222
Publication Date: 01 February 2026
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

1. Introduction 2. Basic theories and methods of intelligent fault diagnosis and health prediction 3. Multi-attribute learning framework for zero-sample fault detection in machinery 4. Generalized zero-sample industrial fault diagnosis with domain bias 5. Generalized zero-sample industrial fault diagnosis under cross-domain scenarios 6. Learning across multisource domains for generalized zero-sample industrial fault diagnosis 7. Federated generalized zero-sample industrial fault diagnosis across multisource domains 8. A multi-phase Wiener process-based degradation model with imperfect maintenance activities

Professor Hongpeng Yin is based at the School of Automation, Chongqing University in China. His current research interests mainly include data-driven process monitoring and fault diagnosis, pattern recognition, and data mining Li Cai received the B.E. degree from the School of Physics and Electronic Engineering from Hainan Normal University in 2019. He is currently undertaking a Ph.D. degree at the School of Automation, Chongqing University, China. His major research interests include data-driven fault detection and diagnosis, fault prediction, remaining useful life prediction, and (generalized) zero-shot learning Peng Zhang received the B.E. degree from College of Automation, Hangzhou Dianzi University, China in 2021. He is currently working towards a Ph.D. degree in the College of Automation, Chongqing University, China. His research interests include data mining, fault diagnosis and machine learning