Weihua L. Intelligent Fault Diagnosis and Health Assessment...Systems 2023

Textbook in PDF format

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.
Preface
Introduction
Supervised SVM Based Intelligent Fault Diagnosis Methods
Semi-supervised Learning Based Intelligent Fault Diagnosis Methods
Manifold Learning Based Intelligent Fault Diagnosis and Prognosis
Deep Learning Based Machinery Fault Diagnosis
Phase Space Reconstruction Based on Machinery System Degradation Tracking and Fault Prognostics
Complex Electro-Mechanical System Operational Reliability Assessment and Health Maintenance