Fault diagnosis method for bearing clearance of reciprocating compressor based on MFO-VMD and GMFE
Based on the nonlinear,unstable and feature-coupled characteristics of bearing clearance faults of reciprocating compressors,a new fault diagnosis method for bearing clear-ance faults of reciprocating compressors based on MFO optimization and generalized multi-scale fuzzy entropy(GMFE)is proposed in this paper.Firstly,the MFO algorithm is used to optimize the two parameters of the mode number k and penalty factor α of the VMD method,and the optimal parameter combination[k,α]is obtained.Then the optimized VMD method is used to decompose the vibration signal of the bearing clearance,and the reconstruction analysis of the vibration signal is carried out.Then,the GMFE entropy algorithm is used to extract fault features from the reconstructed signal,and the required fault feature vector set is obtained.Finally,the extracted fault feature vector set is input into intelligent classifica-tion algorithm support vector machine for fault classification and diagnosis.The results show that the fault diagnosis method proposed in this paper can effectively improve the accuracy of diagnosis and has the advantages of better fault feature extraction.
万方数据
维普
