Abstract: In view of the difficulty of locating power cables quickly and accurately when faults occur due to the fact that power cables are laid underground, a locating method for power cable faults based on wavelet transform and genetic algorithm back propagation(GA-BP) neural network is proposed. On the basis of analyzing and comparing the energy concentration degree and frequency of fluctuations of each wavelet, the Daubechies wavelet 6(Db6) is selected as the wavelet basis function. The wavelet decomposition is carried out on the α mode component of the forward fault traveling wave collected at each fault location. The maximum value of the mode under d1 scale is taken as the characteristic value, and the fault distance is taken as the label value. Using the population evolution and global optimal searching ability of genetic algorithm(GA) to improve the error back propagation(BP) network's sensitivity to initial weight. The optimized weights and thresholds of the BP neural network are given for re-training and prediction. Finally, the proposed method is compared with the two-ended traveling wave positioning algorithm, BP algorithm and particle swarm optimization-BP(PSO-BP) algorithm to prove its excellent ranging performance.