Simulation and measured analysis of the influence of sampling parameters on clustering results of partial discharge

Zhao Guang Du; Ding Qian Yang; Fei Zhang; Long Fei Li; Jia Bao Du

doi:10.1117/12.2639125

19 October 2022 Simulation and measured analysis of the influence of sampling parameters on clustering results of partial discharge

Zhao Guang Du, Ding Qian Yang, Fei Zhang, Long Fei Li, Jia Bao Du

Author Affiliations +

Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 122940N (2022) https://doi.org/10.1117/12.2639125
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China

Abstract

Discrete sampling is broadly utilized in the measurement system of wide-band partial discharge (PD) , and collection parameters of discrete sampling have a significant impact on the PD pulse sequence. Stationary noise originating from vertical resolution of oscilloscope is a feature of sampling signal, which always exists when digital acquisition system is used. In the wide band partial discharge measurement system, sampling frequency F_s, sampling time T_s, sampling bits and other parameters will lead to steady noise changes from oscilloscope, which can be quantified by signal to noise ratio (SNR). With the development of wide-band PD measurement system, clustering graph is the tool that can be used to analyze PD pulse in actual time, and apply clustering technology to PD source separation. By drawing classification diagram with equivalent time T_eq and equivalent frequency F_eq, characteristics of partial discharge pulses can be extracted and clustered, so as to realize the classification of sources. In the paper, a series of simulation analysis and measurements in laboratory are used to evaluate the impact of sampling parameters on T_eq and F_eq results. The results show that clustering outcomes are greatly influenced by the number of sampling bits, and the impact on the classification map will be reduced by the appropriate number of sampling bits.

Citation Download Citation

Zhao Guang Du, Ding Qian Yang, Fei Zhang, Long Fei Li, and Jia Bao Du "Simulation and measured analysis of the influence of sampling parameters on clustering results of partial discharge", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 122940N (19 October 2022); https://doi.org/10.1117/12.2639125

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KEYWORDS

Signal to noise ratio

Interference (communication)

Time-frequency analysis

Signal processing

Oscilloscopes

Americium

Data modeling

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