Fault diagnosis of explosion proof motor based on SVM and RS

In view of problems that fault data acquisition of explosion proof motor in underground coal mine was difficult and fault data was clutter and nonlinear, a fault diagnosis method of explosion proof motor based on SVM and RS was proposed. Wavelet packet is used to analyze instantaneous power of stator of explosion proof motor, and extract fault feature. Redundant data of fault feature is eliminated using reduction feature of rough set, and the reduced feature is used as input sample of support vector machine, to realize rotor fault diagnosis and classification of explosion proof motor. The simulation results show that fault diagnosis accuracy of the proposed method reaches 92.857 1%.