Fault Location in Power Transmission Lines Using a Second Generation Wavelet Analysis

A novel but effective signal processing tool-second generation wavelet (SGW) analysis-is proposed to extract the features of fault-generated transient waves: the maxima of amplitude fluctuation and polarities. The transient current signals observed at each end of the power transmission line are firstly transformed into an aerial mode current signal when fault occurs. The original data of transient current signal is split into the approximation signal and the detail signal. The approximation signal is updated using the information contained in the detail signal. Meanwhile, The detail signal is predicted using information contained in the updated approximation signal. The updated approximation signal represents the steady component of signal and the updated detail signal contains the high-frequency component only and is exploited to extract the transient features. The maxima of the detail signal are recognized to identify the time-tags and the polarities of these time-tags are easy to determine. Finally, with reference to the maxima and their polarities derived from the high-frequency component of the aerial modal signals, the distance to the fault can be obtained. The simulation results have demonstrated that the proposed SGW analysis scheme is capable of extracting the transient features more effectively than the recently developed multi-resolution morphology gradient method