局部放电特高频检测装置抗电磁干扰性能的量化评估方法研究

doi:10.19595/j.cnki.1000-6753.tces.190502

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Abstract The existence of electromagnetic interference in substations seriously affects the sensitivity of on-site partial discharge detection and the accuracy of defect diagnosis. It is one of the key technical bottlenecks for partial discharge state detection. In this paper, the source of interference and its influence on partial discharge detection are studied, and a relatively complete database of partial discharge samples is accumulated. Based on this, a high performance arbitrary waveform generator is proposed to restore the typical partial discharge. A platform of quantitative evaluation for the anti-electromagnetic interference capability of the partial discharge UHF detection device is established by means of interference real-time simulation. Based on the principle of signal-to-noise ratio, a method for quantitative evaluation of the anti-electromagnetic interference capability of UHF detection devices is proposed for the first time. The evaluation method proposed in this paper has a practical value for improving the quantitative evaluation of the anti-interference performance of the partial discharge detection device and perfecting the partial discharge state detection technology standard.

Key words： Partial discharge ultra high frequency anti-interference cluster analysis

Received: 29 April 2019

PACS:

TM930.1

Fund:国家电网公司总部科技资助项目,局部放电带电检测仪器功能检验对比方法研究与应用（52182018000K）

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	Articles by authors
	Zou Yang
	Zhou Qiukuan
	Liu Mingjun
	Tang Zhiguo
	Zhang Da

Cite this article:

Zou Yang,Zhou Qiukuan,Liu Mingjun等. Research on Quantitative Evaluation on Anti-Electromagnetic Interference Capability of Ultra High Frequency Partial Discharge Detection Instrument[J]. Transactions of China Electrotechnical Society, 2020, 35(10): 2275-2282.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.190502 OR https://dgjsxb.ces-transaction.com/EN/Y2020/V35/I10/2275

[1] 齐歌, 郭俊, 吴广宁, 等. 局部放电检测技术的现状和发展[J]. 电工技术学报, 2005, 20(2): 29-35.
Qi Ge, Guo Jun, Wu Guangning, et al.Current status and development of partial discharge detection technology[J]. Transactions of China Electrotechnical Society, 2005, 20(2): 29-35.
[2] 黎慧明, 张志磊. GIS局部放电测试案例分析[J]. 电气技术, 2018, 19(11): 111-114.
Li Huiming, Zhang Zhilei.A case study of GIS partial discharge test[J]. Electrical Engineering, 2018, 19(11): 111-114.
[3] 卢启付, 李端姣, 唐志国, 等. 局部放电特高频检测技术[M]. 北京: 中国电力出版社, 2017.
[4] Dey D, Chatterjee B, Chakravorti S, et al.Cross- wavelet transform as a new paradigm for feature extraction from noisy partial discharge pulses[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2010, 17(1): 157-165.
[5] 刘宇舜, 周文俊, 李鹏飞, 等. 基于广义S变换模时频矩阵的局部放电特高频信号去噪方法[J]. 电工技术学报, 2017, 32(9): 211-220.
Liu Yushun, Zhou Wenjun, Li Pengfei, et al.Denoising method of partial discharge UHF signal based on generalized S-transform mode time- frequency matrix[J]. Transactions of China Electro- technical Society, 2017, 32(9): 211-220.
[6] 刘宇舜, 程登峰, 夏令志, 等. 基于单通道盲源分离算法的局部放电特高频信号去噪方法[J]. 电工技术学报, 2018, 33(23): 5625-5636.
Liu Yushun, Cheng Dengfeng, Xia Lingzhi, et al.Denoising method of partial discharge UHF signal based on single channel blind source separation algorithm[J]. Transactions of China Electrotechnical Society, 2018, 33(23): 5625-5636.
[7] 王彩雄, 唐志国, 常文治, 等. 局部放电超高频检测抗干扰与多源放电信号分离方法[J]. 电网技术, 2012, 36(3): 46-50.
Wang Caixiong, Tang Zhiguo, Chang Wenzhi, et al.Partial discharge ultra-high frequency detection anti- interference and multi-source discharge signal separation method[J]. Power Grid Technology, 2012, 36(3): 46-50.
[8] 国家能源局. 气体绝缘金属封闭开关设备局部放电特高频检测技术规范[S]. 北京: 中国电力出版社, 2017.
[9] 国家能源局. 变电设备在线监测装置技术规范第4部分: 气体绝缘金属封闭开关设备局部放电特高频在线监测装置[S]. 北京: 中国电力出版社, 2017.
[10] 国家能源局. 电力设备带电检测仪器技术规范[S]. 北京: 国家电网公司标准, 2016.
[11] 国家电网公司. 气体绝缘金属封闭开关设备特高频法局部放电在线监测装置技术规范[S]. 北京: 国家电网公司标准, 2015.
[12] 国家电网公司. 变电设备在线监测装置检验规范[S]. 北京: 国家电网公司标准, 2015.
[13] 国家电网公司. 气体绝缘开关设备局部放电带电测试技术现场应用导则[S]. 北京: 国家电网公司标准, 2014.
[14] 唐志国, 蒋佟佟, 叶会生, 等. 变电站局放检测中的电磁干扰统计特性研究[J]. 高电压技术, 2017, 43(9): 2998-3006.
Tang Zhiguo, Jiang Dongdong, Ye Huisheng, et al.Statistical characteristics of electromagnetic inter- ference in substation partial discharge detection[J]. High Voltage Technology, 2017, 43(9): 2998-3006.
[15] 李端姣, 唐志国. GIS局部放电特高频检测系统标定研究[J]. 高电压技术, 2015, 41(10): 3348-3354.
Li Duanjiao, Tang Zhiguo.Study on calibration of GIS partial discharge UHF detection system[J]. High Voltage Engineering, 2015, 41(10): 3348-3354.
[16] 李臻, 罗林根, 盛戈皞, 等. 基于压缩感知的特高频局部放电定位法[J]. 电工技术学报, 2018, 33(1): 202-208.
Li Zhen, Luo Lingen, Sheng Gehao, et al.Ultra-high frequency partial discharge localization method based on compressed sensing[J]. Transactions of China Electrotechnical Society, 2018, 33(1): 202-208.
[17] Christoph Herold, Simon Wenig, Thomas Leibfried.Advanced de-noising of power cable partial discharge signals by empirical mode decomposition[C]//2010 20th Australasian Universities Power Engineering Conference, Christchurch, New Zealand, 2010: 1-5.
[18] Cavallini A, Montanari G C.A new methodology for the identification of PD in electrical apparatus: properties and applications[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2005, 12(2): 203-214.
[19] 李正明, 钱露先, 李加彬. 基于统计特征与概率神经网络的变压器局部放电类型识别[J]. 电力系统保护与控制, 2018, 46(13): 55-60.
Li Zhengming, Qian Luxian, Li Jiabin.Partial discharge type identification of transformer based on statistical features and probabilistic neural net- works[J]. Power System Protection and Control, 2018, 46(13): 55-60.
[20] 杨丽君, 孙才新, 廖瑞金, 等. 采用等效时频分析及模糊聚类法识别混合局部放电源[J]. 高电压技术, 2010, 36(7): 1710-1716.
Yang Lijun, Sun Caixin, Liao Ruijin, et al.Identifi- cation of hybrid local discharge power source by equivalent time-frequency analysis and fuzzy clustering method[J]. High Voltage Technology, 2010, 36(7): 1710-1716.