A wavelet multiresolution analysis approach to fault detection and classification in transmission lines

Abstract A real-time wavelet multiresolution analysis (MRA)-based fault detection and classification algorithm is proposed in this paper. The first stage MRA detail signals extracted from the original signals are used as the criteria for this problem. By measuring the sharp variation values of the MRA detail signals, faults in the power system can be detected. The fault type is then identified by the comparison of the three-phase MRA sharp variations. The effects of the fault distance, fault inception angle and fault impedance are examined, and the fault classification routine is designed to overcome their effects. Simulation results show that this algorithm is effective and robust, and it is promising in high impedance fault detection.