关键词: 故障诊断, 递归图, 递归定量分析, GG模糊聚类

Abstract:

A fault diagnosis method of rolling bearings based on RQA and GG clustering was put forward. The parameters of the RQA which were able to characterize the degree of divergence of the signal-determinism and laminarity were used to consist the fault feature vector. Combined with the GG fuzzy clustering, it could achieve the fault pattern recognition of rolling bearings. The analyses of the actual fault data show that the method is able to identify different degrees of damage of rolling bearing faults and to complete different parts of the bearing fault diagnosis. It provides an efficient and intuitionistic new way for the identification of rolling bearing faults.

Key words: fault diagnosis;recurrence plot, recurrence quantification analysis(RQA);GG fuzzy clustering