In this study, two approaches are presented to detect short-circuit faults in power transmission lines. The two proposed methods are completely novel from both theoretical and technical aspects. The first approach is a soft computing method that uses discrete wavelet transform with Daubechies mother wavelets db1, db2, db3, and db4. The second approach is a hardware based method that utilizes a novel proposed two-stage finite impulse response filter with a sampling frequency of 32kHz, and a very short process time about three samples time. The two approaches are analyzed by presenting theoretical results. Simulated results obtained by simulating a three-phase 230kV, 50Hz power transmission line are given that validate the theoretical results, and explicitly verify that the filter based approach has an accuracy of 100% in presence of 10% disturbance while the accuracy of the wavelet transform based approach is maximally 97%, but it has less complication and implementation cost. Another comparative study between this work and other works shows that the two proposed methods have higher accuracy and very shorter process time compared to the other methods, especially in presence of 10% disturbance that actually occurs in power transmission lines. 
Two novel proposed discrete wavelet transform and filter based approaches for short-circuit faults detection in power transmission lines