Fault Traveling Wavefront Detection Method Based on GLCT-TEO

To address the challenge of traveling wavefront detection in distribution networks, this paper proposes a novel detection method based on the General Linear Chirplet Transform and Teager Energy Operator (GLCT-TEO). The GLCT is first employed to achieve high-resolution time-frequency characterization, enabling precise capture of the time-varying frequency components in traveling waves. By selecting the most identifiable frequency components through kurtosis and subsequently enhancing transient energy features using the TEO's sensitivity to abrupt signal changes, a joint time-frequency and energy detection framework is established to precisely identify wavefront arrival instants. Simulation results demonstrate that the proposed method effectively detects fault-induced traveling waves under strong noise conditions, significantly improving fault location accuracy in distribution networks.