A Typical Fault Diagnosis Method for Axial Piston Pump Based on CEEMDAN and t-SNE
The hydraulic driving system of the tunneling machine is subjected to strong impact load when it runs in non-uniform soil condition,which is easy to cause the failure of its core power source hydraulic pump.For the characteristic separation,extraction and identification classification of typical wear faults in axial piston pump,a time-frequency domain feature extraction method of fault vibration signals based on CEEMDAN method was proposed.The vibration signals collected from pump shell were decomposed in time-frequency domain,and 70 dimensions'feature space was constructed to characterize the state features.Through the feature dimension reduction fusion strategy,t-SNE was used for analytic fusion of high-dimensional features,which reduced the dimension of 70-dimensional feature space to 2-dimensional space,and significantly improved the training efficiency and classification accuracy of the classifier.The SVM method was used to train the classifier model for three types of typical wear faults,and through the test set verification,the identification accuracy of the model reached 96.7％,which was significantly better than the high-dimensional classifier identification model was not processed by dimensionality reduction.
万方数据
维普
