2023
DOI: 10.1108/ec-12-2022-0747
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A weakly supervised pairwise comparison learning approach for bearing health quantitative evaluation and remaining useful life prediction

Fanshu Zhao,
Jin Cui,
Mei Yuan
et al.

Abstract: PurposeThe purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.Design/methodology/approachBased on the principle that bearing health degrades with the increase of service time, a weak label qualitative pairing comparison dataset for bearing health is extracted from the original time series monitoring data of bearing. A bearing health indicator (HI) quantitative evaluation model is obtained by traini… Show more

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