{'fraction_non_alphanumeric': 0.025660964230171075, 'fraction_numerical': 0.0023328149300155523, 'mean_word_length': 5.128571428571429, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Multi-Resolution Generalized S-Transform Denoising for Precise Localization of Partial Discharge in Substations

Denoising is a crucial step in the localization of partial discharge (PD) in a substation. In this paper, a novel multi-resolution generalized S-transform (GST) denoising algorithm for precise localization of PD in substations is proposed. The algorithm denoises the PD signal received by the ultra-high frequency (UHF) sensor in two steps. First, the GST with the high frequency resolution is used to analyze the PD signal, and a GST filter is designed to filter out periodic narrowband noises. Then, the S-transform (a particular case of GST) is applied to analyze the PD signal, and the white Gaussian noise is suppressed according to the statistical characteristic difference between the noise and effective signal. Finally, the denoised PD signal is obtained and applied to PD localization. The simulations results show that the proposed algorithm can effectively suppress noise and can extract accurate time delay data from the denoised PD signal. The experiment results show that, compared with the wavelet transform, the localization error of the proposed algorithm is the smallest, which is 1.59m. The proposed algorithm can realize the precise localization of PD.