Diagnose of electronic circuits of the driver controller based on VPCA-BRB model

The controller of railway vehicle is the main command control electric appliance which controls the operation of railway vehicle. Any fault of the electronic circuit of the controller will cause the safety accident of railway vehicle. Aiming at the problem of low accuracy in fault diagnosis of controller electronic circuits caused by fuzzy meaning in feature extraction, a fault diagnosis method based on maximum variance rotating principal component analysis and confidence rule base was proposed. Firstly, the dimensionality of the data was reduced by the principal component analysis of the maximum variance rotation to improve the explan ability of the factors after dimensionality reduction. Then the belief rule base reasoning method based on evidence reasoning was used to diagnose the fault, and the CMA-E algorithm was used to optimize the initial parameters of the established model, so as to improve the accuracy of fault diagnosis of electronic circuit of railway vehicle. The effectiveness of the proposed method is verified by simulation and experiment.