Research on Unbalanced Data Set for Transmission Fault Classification
In order to solve the fault detection problem of new transmission products,this paper presents a method of fault feature extraction by order analysis and fault classification by support vector machine(SVM) classifier.The establishment of the tw o-layer SVM discriminant model and the adjustment of the penalty factor C solve the problem of imbalance in the training sample set w hich leads to get w rong classicification results.The experimental result of field data show s that the fault identification rate and run time of the method are greatly improved than BP neural netw ork and standard SVM algorithm.