# Insulator Partial Discharge Localization Based on Improved Wavelet Packet Threshold Denoising and Gxx−β Generalized Cross-Correlation Algorithm

## TL;DR

This paper introduces a new method to locate partial discharges in insulators using improved signal processing techniques and a specialized algorithm for better accuracy in noisy environments.

## Contribution

The novel contribution is the combination of improved wavelet packet denoising and a modified Gxx−β generalized cross-correlation algorithm for PD localization.

## Key findings

- The improved wavelet packet denoising algorithm effectively separates PD signals from noise with low distortion.
- The modified Gxx−β weighting function significantly improves the accuracy of time difference estimation between sensors.

## Abstract

Partial discharge (PD) in insulators will not only lead to the gradual degradation of insulation performance but even cause power system failure in serious cases. Because there is strong noise interference in the field, it is difficult to accurately locate the position of the PD source. Therefore, this paper proposes a three-dimensional spatial localization method of the PD source with a four-element ultra-high-frequency (UHF) array based on improved wavelet packet dynamic threshold denoising and the Gxx−β generalized cross-correlation algorithm. Firstly, considering the field noise interference, the PD signal is decomposed into sub-signals with different frequency bands by the wavelet packet, and the corresponding wavelet packet coefficients are extracted. By using the improved threshold function to process the wavelet packet coefficients, the PD signal with low distortion rate and high signal-to-noise ratio (SNR) is reconstructed. Secondly, in order to solve the problem that the amplitude of the first wave of the PD signal is small and the SNR is low, an improved weighting function, Gxx−β, is proposed, which is based on the self-power spectral density of the signal and is adjusted by introducing an exponential factor to improve the accuracy of the first wave arrival time and time difference calculation. Finally, the influence of different sensor array shapes and PD source positions on the localization results is analyzed, and a reasonable arrangement scheme is found. In order to verify the performance of the proposed method, simulation and experimental analysis are carried out. The results show that the improved wavelet packet denoising algorithm can effectively realize the separation of PD signal and noise and improve the SNR of the localization signal with low distortion rate. The improved Gxx−β weighting function significantly improves the estimation accuracy of the time difference between UHF sensors. With the sensor array designed in this paper, the relative localization error is 3.46%, and the absolute error is within 6 cm, which meets the requirements of engineering applications.