期刊
IEEE TRANSACTIONS ON RELIABILITY
卷 65, 期 2, 页码 718-735出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TR.2015.2500681
关键词
Kernel smoothing; model-based prognostics; online prognostics performance assessment; particle filter; turbine blade creeping
类别
资金
- China Scholarship Council (CSC) [201206110018]
- China NSFC [71231001]
- European Union Project INNovation through Human Factors in risk analysis and management (INNHF) - 7th framework program FP7-PEOPLE- Initial Training Network: Marie-Curie Action
In this paper, we propose a method for online assessing the performance of a prognostic approach in situations of very poor knowledge on the degradation process. In particular, we deal with cases in which the entire degradation process, from the beginning of the operation until failure, has never been observed and, thus, the traditional offline performance metrics cannot be applied. The proposed method is applied on a prognostic approach based on a particle filter and optimized tuning kernel smoothing (PF-OTKS). Case studies regarding the degradation of turbine blade and aluminum electrolytic capacitor are considered.
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