BP neural network bearing
no vote
Bearing fault feature extraction is closely related to the accuracy of diagnosis, and its methods are constantly improving, such as traditional indicators, talaf and Thika indicators. In this paper, the kernel principal component analysis (KPCA) feature extraction method based on particle swarm optimization (PSO) is used.