Optimizing VMD and Improving Residual Network Research on Gearbox Fault Diagnosis
In order to improve the accuracy of gearbox fault diagnosis,this paper adopts a gearbox fault identification method combining VMD(Variational mode decomposition)and 1D-Resnet(One-dimensional residual network).Firstly,the krill swarm algorithm is used to optimize the penalty factor α and the number of decomposition layers K in the VMD.Secondly,the VMD is used to decompose the fault signal to generate several IMF(Intrinsic mode functions),and the correlation coefficient is used to screen the IMF component.Finally,the screened component is used as the input data of the improved residual network for network training and testing,and the fault identification result is obtained.Through the horizontal comparison with the average accuracy of VMD-random forest,VMD-CNN and other methods,the results show that the method in this paper is more accurate for identifying gearboxfault types.
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