Filter Based Fault Diagnosis And Remaining Useful Life Prediction
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Filter-Based Fault Diagnosis and Remaining Useful Life Prediction
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.
Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery
Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery provides a comprehensive introduction of intelligent fault diagnosis and RUL prediction based on the current achievements of the author's research group. The main contents include multi-domain signal processing and feature extraction, intelligent diagnosis models, clustering algorithms, hybrid intelligent diagnosis strategies, and RUL prediction approaches, etc. This book presents fundamental theories and advanced methods of identifying the occurrence, locations, and degrees of faults, and also includes information on how to predict the RUL of rotating machinery. Besides experimental demonstrations, many application cases are presented and illustrated to test the methods mentioned in the book. This valuable reference provides an essential guide on machinery fault diagnosis that helps readers understand basic concepts and fundamental theories. Academic researchers with mechanical engineering or computer science backgrounds, and engineers or practitioners who are in charge of machine safety, operation, and maintenance will find this book very useful. - Provides a detailed background and roadmap of intelligent diagnosis and RUL prediction of rotating machinery, involving fault mechanisms, vibration characteristics, health indicators, and diagnosis and prognostics - Presents basic theories, advanced methods, and the latest contributions in the field of intelligent fault diagnosis and RUL prediction - Includes numerous application cases, and the methods, algorithms, and models introduced in the book are demonstrated by industrial experiences
Proceedings of the TEPEN International Workshop on Fault Diagnostic and Prognostic
This book gathers the latest advances, innovations, and applications in the field of efficiency and performance engineering, as presented by leading international researchers and engineers at the TEPEN International Workshop on Fault Diagnostics and Prognostics (TEPEN-IWFDP), held in Qingdao, China on May 8–11, 2024. Topics include machine and structural health monitoring, non-destructive testing and fault detection, diagnostic and prognostic for both operational and manufacturing processes, maintenance optimization and asset management, smart metamaterials and metastructures, artificial intelligence, and machine learning. The contributions, which were selected through a rigorous international peer-review process, share exciting ideas that will spur novel research directions and foster new multidisciplinary collaborations.