To achieve the diagnosis of bearing faults,this paper proposes a classification algorithm based on singular value decomposition(SVD)and one-dimensional convolutional neural network(1DCNN),which converts one-dimensional signals into two-dimensional data for reconstruction,estab-lishes a detection model,inputs the reconstructed signal and the original signal into the 1DCNN model for detection and finally evaluates the model through confusion matrix and accuracy evaluation.The re-sults show that the combination of SVD and 1DCNN model has improved the accuracy by 1.57% and 3.12% compared to the traditional 1DCNN model under different operating conditions,providing certain reference value.
维普
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