Partial Discharge Ultrasound Localization Method Based on SRLMSGCC Algorithm

Time difference estimation is an important part of partial discharge localization. Existing algorithms are limited by the sampling rate of sampling equipment, which can generate significant system errors and result in excessive localization errors. To address the aforementioned issues, this paper proposes the Super Resolution Least Mean Square Generalized Cross Correlation (SR-LMS-GCC) algorithm, which breaks through the limitation of sampling rate and can more accurately estimate the time difference between two signals. This paper first improves the generalized cross-correlation of discrete-time signals by expanding the spectrum through frequency adjustment, which can effectively improve the time resolution of time difference estimation. To solve the problem of real time difference overflow time difference estimation interval, a multi-level cross correlator framework is proposed, and combined with the adaptive generalized cross-correlation time difference estimation method, the SR-LMS-GCC algorithm is proposed. The setting rules of algorithm parameters are discussed through simulation. Finally, through experimental verification, the SR-LMS-GCC algorithm has improved time difference estimation and positioning accuracy by about 90% compared to traditional resolution limited algorithms.