基于SVM与GA参数优化的齿轮箱断齿故障诊断方法研究 - 张星辉; 康建设; 曹端超; 孙磊; 滕红智 (Jixie chuandong)
A new method of gearbox fault diagnosis based on SVM（Support vector machine） and GA（Genetic algorithm）which is used to optimize parameters is presented.Firstly,the raw vibration signal is preprocessed by Time Synchronous Average algorithm.Then,the signal wavelet packet decomposition is carried out,standard deviation of wavelet packet coefficients of the signals is considered as the fault feature vector,and the normalization process of the fault feature vector is carried out.In the end,the fault feature vector is used as the input of SVM.In this process,the Daubechies order,wavelet packet decomposition level,c and g of SVM are optimized by GA.After that,the optimized parameter is used in training model which will be used for fault diagnosis.The experimental result shows that SVM and GA can be used to effectively diagnose faults of gearbox.