Research on Bearing Fault Diagnosis of Motor Based on Chaotic Firefly Algorithm
In order to improve the fault signal diagnosis efficiency of industrial robot bearings,a chaotic optimization Firefly parameter(CFA)fault signal diagnosis method was designed and its corresponding control flow was established.Based on the fault test platform of industrial robot bearing,the vibration signal processing analysis is carried out.The results show that the modal component signals have achieved accurate separation of synthetic signals and achieved ideal separation performance,which is helpful to extract the fault signal frequency from the signal envelope spectrum.The accuracy of fault diagnosis obtained by chaotic firefly method is increased significantly,which is close to 99％.Compared with other methods,chaos optimization firefly method has the best accuracy,showing high accuracy.
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