This paper deals with the application of wavelet based alienation technique for the detection and classification of faults on transmission lines. The three phase current signals of both the ends are synchronized with the help of Global Positioning System clock. These signals are decomposed with Haar wavelet to obtain approximate coefficients over a moving window of half cycle. Approximate Coefficients obtained over a half cycle are compared with the previous half cycle of same polarity to compute alienation coefficients at each end. A Fault Index, computed by adding alienation coefficients of local and remote end, is compared with the threshold to detect and classify the faults. The proposed algorithm has been tested successfully for various types of faults at different fault locations and different fault incidence angles. © 2015 IEEE.