Fault Diagnosis of Gearbox based on Multi-fractal and PSO-SVM - Li Sha; Pan Hongxia; Zhang Jundong; Zhao Weiwei (Jixie chuandong)
Aiming at the non-stationary and nonlinear of gearbox vibration signals,a fault diagnosis method based on the multi-fractal and particle swarm optimization support vector machine（PSO-SVM）is put forward.Firstly,the fractal filter with short-time fractal dimension as fuzzy control parameters is used to filtering noise reduction the gearbox vibration signals with bigger background noises.Secondly,the multi-fractal spectrum algorithm is applied to analyze the signal after filtering,the results show that the characteristic parameters:Δa（q）、f（a（q））maxand box dimensions Dbcan give a good presentation for gearbox working condition.Finally,the particle swarm optimization（PSO）is applied to optimize the parameters of support vector machine（SVM）.Taking the multi-fractal characteristic vectors as input parameters of PSO-SVM and SVM to recognize the fault types of the gearbox.The results show that SVM based on particle swarm optimization can improve the classification accuracy.Meanwhile,the validity of gearbox fault diagnosis based on muti-fractal and PSO-SVM is proved.