Summarization of Remaining Life Prediction Methods for Special Power Plants
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Published:2023-08-18
Issue:16
Volume:13
Page:9365
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Liang Weige1,
Li Chi1ORCID,
Zhao Lei1,
Yan Xiaojia1,
Sun Shiyan1
Affiliation:
1. College of Weaponry Engineering, Naval University of Engineering, Wuhan 430033, China
Abstract
With continuous improvements in integration, totalization and automation, remaining useful life predictions of mechanical equipment have become a key feature of technology and core element of equipment prediction and health management. The traditional method based on degradation mechanisms is not fully capable of predicting remaining useful life, especially for special power plants that use industrial transmissions, barrel launchers, etc. The expected service requirements are higher for condition monitoring and remaining service life prediction. The effective prediction of the remaining useful life of such special power plants is a major challenge and technical bottleneck in the industrial field and national defense equipment construction. This paper analyzes and expands on the research on the remaining life prediction methods for special power plants and analyzes the remaining life prediction methods of existing dynamic models, as well as data-driven and data–model fusion drives, and specific ideas for future research and development in four aspects, including remaining useful life prediction tests supplemented with soft measurements. Additionally, future research directions for the remaining life prediction of special power plants are provided.
Funder
National Natural Science Foundation of China
Hubei Provincial Natural Science Foundation
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference107 articles.
1. Summary of machine learning-based device RUL prediction methods;Fei;J. Mech. Eng.,2019
2. Advanced design and manufacturing technology frontier: The reliability guarantee of important equipment column preface;Tu;J. Mech. Eng.,2021
3. Review on condition-based equipment RUL prediction and preventive maintenance scheduling;Meng;J. Vib. Shock.,2011
4. Retrospect and prospect on century-long research of structural fatigue;Xuan;J. Mech. Eng.,2021
5. Survey of vibration fault diagnosis of rotational machinery;Feng;J. Vib. Shock,2001
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