Fault diagnosis of high speed ball bearing based on elastic kernel convex hull tensors

In order to improve the fault diagnosis accuracy of mechanical transmission system, a fault diagnosis method of high-speed ball bearing based on elastic kernel convex hull tensor was designed. The time-frequency distribution is established by using the continuous wavelet transform method with mature technology, and then the feature set is established according to the data of the gray co-occurrence matrix of the time-frequency graph, from which the accurate texture features of the time-frequency graph are calculated. The model of training elastic kernel convex hull tensor is used to identify test set samples and realize fast fault diagnosis. The research results show that the proposed method can obtain higher accuracy than the initial elastic convex hull classification method, and the texture features of time-frequency maps achieve higher accuracy than the traditional time-frequency features. The elastic kernel convex hull tensor has excellent generalization performance and achieves the optimal classification accuracy. The training set and test set were divided by the ratio of 8∶2, and the elastic kernel convex hull tensor was used to achieve the highest accuracy. The elastic kernel convex hull tensor showed better anti-noise and robustness. The research can be applied to other mechanical transmission systems and has a good value for practical promotion.