Partial discharge ultrasound localization based on super-resolution generalized cross-correlation estimation algorithm

The ultrasonic localization method for partial discharge based on the arrival time difference method is widely used in the detection of partial discharge in power equipment. However, existing methods suffer from limited time resolution of time difference estimation algorithms under low sampling rates, which leads to divergence of localization algorithms. To overcome the constraints imposed by sampling rates, a super-resolution generalized cross-correlation algorithm was introduced. In the algorithm, the signals were preprocessed to reduce the impact of noise on time difference estimation accuracy, exponentiation was performed in the frequency domain within the framework of generalized cross-correlation to enhance time resolution, an iterative estimation method was employed to search for precise time difference estimates, and kurtosis analysis was conducted on the apparent images after each iteration to determine the termination criteria. Through simulation analysis, the feasibility, performance under different weighting functions, and noise robustness of this method were verified. Finally, through experimental verification, compared to traditional generalized cross-correlation algorithms, the positioning accuracy of our method has been significantly improved at various sampling rates. © 2024 Editorial Department of Electric Machines and Control. All rights reserved.