In order to make full use of the monitoring data of the mine hoist during operation and accurately diagnose the brake system,a fault diagnosis method based on Sparse Auto-Encoder(SAE)is proposed.Through the simulated failure test,the failure data is obtained,and the training set and the test set are generated after standardized processing.And add the Dropout regulariza-tion method to optimize the fault diagnosis model,and use the gradient descent method to optimize the model parameters accord-ing to the training results.Finally,the test data set is used to compare the diagnosis model before and after optimization.The re-sults show that the hoist fault diagnosis method proposed in this paper reduces the over-fitting phenomenon and the workload of obtaining label data,and the average classification accuracy of fault types can reach 96%.This method uses the monitoring data of the hoist for diagnosis,without subjective intervention of personnel,and can accurately diagnose the fault of the mine hoist.
维普
万方数据
