| Citation: | LI Jiesong, LIU Tao, WU Xing. Rolling bearing RUL prediction based on Pearson correlation coefficient statistical features[J]. Journal of Aerospace Power, 2025, 40（7）：20230630 doi: 10.13224/j.cnki.jasp.20230630
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To obtain health indicators that can accurately describe the degradation process, a new health indicator based on envelope spectrum statistical features and Pearson correlation coefficient was proposed for remaining useful life prediction. Firstly, a first prediction time identification method was proposed based on the Boostrap sampling method and the 3 sigma principle to obtain a suitable full-life degradation threshold. Secondly, the envelope spectrum probability distributions at different time points were calculated and the health index was obtained based on the Pearson correlation coefficient. Finally, the remaining useful life of bearing was predicted by a hybrid model of exponential and linear regression. The experimental results showed that the proposed health index can effectively reflect the bearing degradation trend, and the prediction accuracy of the hybrid exponential and linear regression model was improved by 23.7% compared with other prediction models.
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