期刊
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
卷 23, 期 2, 页码 387-394出版社
POLISH MAINTENANCE SOC
DOI: 10.17531/ein.2021.2.19
关键词
predictive maintenance; failure prognostics; performance degradation; maintenance cost
资金
- Natural Science Foundation of China [61873122, 62020106003]
- China Scholarship Council [202006830060]
This paper presents a novel data-driven predictive maintenance strategy that achieves accurate failure prognosis through degradation feature selection and degradation prognostic modeling modules, outperforming traditional maintenance strategies.
Maintenance is fundamental to ensure the safety, reliability and availability of engineering systems, and predictive maintenance is the leading one in maintenance technology. This paper aims to develop a novel data-driven predictive maintenance strategy that can make appropriate maintenance decisions for repairable complex engineering systems. The proposed strategy includes degradation feature selection and degradation prognostic modeling modules to achieve accurate failure prognostics. For maintenance decision-making, the perfect time for taking maintenance activities is determined by evaluating the maintenance cost online that has taken into account of the failure prognostic results of performance degradation. The feasibility and effectiveness of the proposed strategy is confirmed using the NASA data set of aero-engines. Results show that the proposed strategy outperforms the two benchmark maintenance strategies: classical periodic maintenance and emerging dynamic predictive maintenance.
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