Fault Diagnosis of Rotating Machinery Based on Dynamic Weighted Integrated DAE
In order to improve the robustness and generalization,and consider the complementary performance of various depth automatic encoders,a fault diagnosis method of rotating machinery based on dynamic weighting integrated depth automatic en-coder was proposed.Combined with sparse depth automatic encoder,noise reduction depth automatic encoder and shrinking depth automatic encoder,the integrated depth automatic encoder was constructed to improve the ability of processing redundant infor-mation,noise damage and signal disturbance.In order to enhance the recognition performance,a dynamic weighted average meth-od was proposed to aggregate learning features.The experimental verification is carried out on the data sets of centrifugal pump and motor bearing,and the results show that the test accuracy of the proposed method is 100％,99.69％ and 99.92％ respectively.Compared with other methods,the effectiveness of the proposed fault diagnosis method is proved.
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