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Small-Sample Reliability Assessment of Electromagnetic Relays: Storage Reliability Analysis and Lifetime Prediction of Electromagnetic Relays Under Small-Sample Conditions - Softcover
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The work presented in this book was supported by Jiangsu University of Science and Technology. As critical components in electrical control systems, electromagnetic relays are particularly vulnerable to contact degradation and failure, which may ultimately lead to system-level malfunctions. Accordingly, reliability assessment based on Remaining Useful Life (RUL) prediction has become an important research topic. However, relay degradation is inherently governed by coupled multi-physical processes and is characterized by highly nonlinear and uncertain failure mechanisms. In addition, the high cost and long duration of life testing severely limit the availability of complete degradation datasets, giving rise to a typical small-sample problem. Furthermore, conventional data-driven methods generally assume parameter independence or linear relationships and fail to capture latent, time-varying nonlinear dependencies, thereby restricting prediction accuracy and robustness.
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Über die Autorin bzw. den Autor
Zhaobin Wang joined Jiangsu University of Science and Technology in 2007 and is currently an Assistant Professor. He received the Ph.D. degree in Electric Machines and Electric Apparatus from Harbin Institute of Technology. His research interest includes storage reliability, testing technique and life-prediction of electrical apparatus.
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Small-Sample Reliability Assessment of Electromagnetic Relays
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Small-Sample Reliability Assessment of Electromagnetic Relays : Storage Reliability Analysis and Lifetime Prediction of Electromagnetic Relays Under Small-Sample Conditions
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The work presented in this book was supported by Jiangsu University of Science and Technology. As critical components in electrical control systems, electromagnetic relays are particularly vulnerable to contact degradation and failure, which may ultimately lead to system-level malfunctions. Accordingly, reliability assessment based on Remaining Useful Life (RUL) prediction has become an important research topic. However, relay degradation is inherently governed by coupled multi-physical processes and is characterized by highly nonlinear and uncertain failure mechanisms. In addition, the high cost and long duration of life testing severely limit the availability of complete degradation datasets, giving rise to a typical small-sample problem. Furthermore, conventional data-driven methods generally assume parameter independence or linear relationships and fail to capture latent, time-varying nonlinear dependencies, thereby restricting prediction accuracy and robustness. Bestandsnummer des Verkäufers 9786630263527
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Small-Sample Reliability Assessment of Electromagnetic Relays | Storage Reliability Analysis and Lifetime Prediction of Electromagnetic Relays Under Small-Sample Conditions
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Taschenbuch. Zustand: Neu. Small-Sample Reliability Assessment of Electromagnetic Relays | Storage Reliability Analysis and Lifetime Prediction of Electromagnetic Relays Under Small-Sample Conditions | Zhaobin Wang | Taschenbuch | Englisch | 2026 | Scholars' Press | EAN 9786630263527 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 136790969
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The work presented in this book was supported by Jiangsu University of Science and Technology. As critical components in electrical control systems, electromagnetic relays are particularly vulnerable to contact degradation and failure, which may ultimately lead to system-level malfunctions. Accordingly, reliability assessment based on Remaining Useful Life (RUL) prediction has become an important research topic. However, relay degradation is inherently governed by coupled multi-physical processes and is characterized by highly nonlinear and uncertain failure mechanisms. In addition, the high cost and long duration of life testing severely limit the availability of complete degradation datasets, giving rise to a typical small-sample problem. Furthermore, conventional data-driven methods generally assume parameter independence or linear relationships and fail to capture latent, time-varying nonlinear dependencies, thereby restricting prediction accuracy and robustness. 212 pp. Englisch. Bestandsnummer des Verkäufers 9786630263527
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