Fault diagnosis of planetary gearbox based on improved composite multi-scale sample entropy
In view of the fact that the multi-scale sample entropy is greatly affected by the sample length,the coarse graining process is relatively rough,and the shortage of effective information may be easily ignored,based on the composite multi-scale sample entropy,the energy distribution between sampling points was used as the weight for coarse graining calculation,and an improved composite multi-scale sample entropy was proposed and applied to the fault diagnosis of planetary gearbox.The influences of different parameters and noise characteristics on the improved composite multi-scale sample entropy algorithm were studied through simulation signals.The stability of the improved algorithm was verified by comparing it with multi-scale sample entropy,generalized multi-scale sample entropy and composite multi-scale sample entropy.Combined with variational mode decomposition,principal component analysis and support vector machine,the fault diagnosis of planetary gearbox experimental signals was carried out.The comparison results showed that the method can effectively realize the common fault diagnosis of the sun gear of the planetary gearbox under different working conditions and structures,and the fault identification rate was more than 95%,with certain effectiveness.