A study on SVM with feature selection for fault diagnosis of power systems
Yufei Wang, Chunguo Wu, Liming Wan, Yanchun Liang · 2010
When faults occur in power systems, it is hard to manually deal with the fault data reported by the system of supervisory control and data acquisition (SCADA) because of the huge amount of alarm information. In this paper, we study the problem of power system fault diagnosis by using support vector machine (SVM), and enhance the ability of fault diagnosis through optimizing support vectors. The results of simulation tests demonstrate the effectiveness of the proposed automatic fault diagnosis method.