Evaluation method of degradation index based on AdaBoost regression

In the field of bearing monitoring, it has always been a difficult problem in the industry to judge the performance of the degradation index. A degradation index evaluation method is proposed based on AdaBoost regression. In this method, AdaBoost regression method is used for the bearing degradation index correlation evaluation criteria. The comprehensive weighted evaluation of degradation characteristics was obtained by the combination with robustness and monotonicity. Features were optimized according to the evaluation score. The analysis of accelerated life experimental data shows that the degradation feature evaluation method based on AdaBoost regression can effectively select the degradation features with good characterization.