| Title |
A Study on High Impedance Fault Detection using Wavelet Transform and Neural -Network |
| Authors |
홍대승(Hong, Dae-Seung) ; 유창완(Ryu, Chang-Wan) ; 임화영(Yim, Wha-Yeong) |
| Keywords |
High impedance fault ; High impedance fault detector ; Wavelet Transform ; Backpropagation |
| Abstract |
The research presented in this paper focuses on a method for the detection of High Impedance Fault(HIF). The method will use the wavelet transform and neural network system. HIF on the multi-grounded three-phase four-wires primary distribution power system cannot be detected effectively by existing over current sensing devices. These paper describes the application of discrete wavelet transform to the various HIF data. These data were measured in actual 22-9kV distribution system. Wavelet transform analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate HIF from the normal status by a gradient descent method. The proposed method performed very well by proving the right state when it was applied staged fault data and normal load mimics HIF, such as arc-welder. |