Improved OSF Method for Early Fault Identification of RV Gear Box of Industrial Robot
In order to further improve the fault diagnosis capability of RV gear box for industrial robots,a vibration signal recognition method based on adaptive Autogram improved sequential statistical filter(OSF)was designed.After OSF calculation of vibration signals,the moving average method is used to smooth the data and obtain a better envelope array.The results show that,compared with the adaptive Autogram method,no significant fault characteristic frequency is observed,which indicates that the performance of the proposed method is better than that of the filter fast spectral kurtosis method.Compared with the proposed method,the corresponding double and triple frequencies do not form obvious characteristic frequencies,and are interfered by other components.Comprehensive analysis shows that the proposed adaptive Autogram method has obvious advantages.This research is helpful to improve the ability of RV gear box of industrial robot to remove hidden faults,and can also be extended to other mechanical transmission mechanisms.