In order to improve the accuracy of transmission line fault diagnosis

a power system fault diagnosis of multi-support vector machine（SVM） model based on the fault information characteristics of electrical quantity is proposed

where the synchronous monitoring information of the wide area measurement system is used. Firstly

the fault information feature is extracted by the symmetrical component method for the synchronous monitoring information

and the feature set is established. Secondly

the genetic algorithm（GA） is used to optimize the model parameters and build the diagnosis model. Finally

the D-S evidence theory is used to fuse the diagnosis results from different diagnosis models and obtain the final diagnosis results. The simulation results show that the accuracy of the diagnosis model based on the fault features can reach up to 97%

and this diagnosis model has advantages of improving accuracy and reducing complexity of model structural. Compared with the traditional methods

the multi-support vector machine diagnostic model can accurately identify the fault features

and can effectively improve the diagnosis accuracy by more than 4%

thus it has higher accuracy and effectiveness.