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| Research on noise reduction of local discharge signal based on adaptive ensemble empirical mode decomposition algorithm |
| SUN Cong1,2, JU Pengfei1,3, LI Dahua1,2, LI Dong1,2 |
1. School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin 300384;
2. Tianjin Advanced Mechatronic System Design and Intelligent Control Laboratory, School of Mechanical Engineering, Tianjin University of Technology, Tianjin 300384;
3. National Experimental Teaching Demonstration Center of Mechanical and Electrical Engineering, Tianjin University of Technology, Tianjin 300384 |
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Abstract High voltage switchgear is widely used in power system, so it is very important to ensure its safe and stable operation. Aiming at the problems of narrow-band interference and other noise interference in the analysis of partial discharge of high-voltage switchgear, a new noise reduction algorithm called adaptive ensemble empirical mode decomposition (AEEMD) is proposed in this paper. The core idea of the proposed algorithm is to decompose only the first-order mode after adding white noise to the original signal, and then add noise to the remaining signal for cyclic processing. The denoising process is simplified and modal aliasing is reduced. Experimental results show that the signal waveform obtained by this method is basically consistent with the measured original signal waveform, and it is superior to the other two algorithms.
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Received: 09 September 2021
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| Cite this article: |
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SUN Cong,JU Pengfei,LI Dahua等. Research on noise reduction of local discharge signal based on adaptive ensemble empirical mode decomposition algorithm[J]. Electrical Engineering, 2022, 23(2): 67-72.
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| URL: |
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http://dqjs.cesmedia.cn/EN/Y2022/V23/I2/67
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[1] 陈路易. 高压开关柜故障检测与预警系统研究[D].淮南: 安徽理工大学, 2019.
[2] 刘财明. 气体绝缘开关设备局部放电带电检测综合应用[J]. 电气技术, 2020, 21(10): 117-122.
[3] 徐兆丹. 10kV开关柜局部放电检测技术分析[J]. 电工技术, 2020(24): 102-104.
[4] 程曦. 基于TEV和超声波法的高压开关柜局部放电综合检测方法及诊断技术[D]. 北京: 华北电力大学, 2017.
[5] 孟祥海, 王文华, 彭飞. 超声波测试技术在高压开关柜局部放电检测定位中的应用[J]. 电气应用, 2019, 38(3): 108-112.
[6] 孙进, 梅凡, 陈月, 等. 声电联合检测法在开关柜局部放电事故分析中的应用[J]. 电工技术, 2020(24): 94-95.
[7] 陈磊, 唐建, 王智睿. 开关柜局部放电超高频在线监测天线的研究[J]. 电气技术, 2019, 20(5): 24-28, 32.
[8] KEDADOUCHE M, THOMAS M, TAHAN A.A com-parative study between empirical wavelet transforms and empirical mode decomposition methods: appli-cation to bearing defect diagnosis[J]. Mechanical Systems and Signal Processing, 2016, 81: 88-107.
[9] ROOSTAEE S, THOMAS M S, MEHFUZ S.Experi-mental studies on impedance based fault location for long transmission lines[J]. Protection and Control of Modern Power Systems, 2017, 2(1): 1-9.
[10] ZHU Bangzhu, MA Shujiao, XIE Rui, et al.Hilbert spectra and empirical mode decomposition: a multiscale event analysis method to detect the impact of economic crises on the European carbon market[J]. Computational Economics, 2018, 52(1): 105-121.
[11] 王永强, 李长元, 胡芳芳, 等. 基于改进EMD的GIS局部放电特高频信号降噪方法研究[J]. 电测与仪表, 2017, 54(9): 1-5, 29.
[12] 胡威. 局部放电超声信号检测与小波包变换在信号去噪中的应用[D]. 昆明: 昆明理工大学, 2016.
[13] 王异凡, 朱冠霖, 王兆强, 等. 基于改进小波阈值的GIS局部放电在线监测白噪声干扰抑制研究[J]. 高压电器, 2019, 55(3): 37-43, 50.
[14] 张彪, 焦良葆, 史塨毓, 等. 基于小波去噪的开关柜局部放电声检测方法[J]. 南京工程学院学报(自然科学版), 2018, 16(4): 55-60.
[15] 丁一, 张磐, 戚艳, 等. 基于EEMD-CCA组合去噪的新型配电开关柜局部放电抗干扰检测[J]. 电子器件, 2020, 43(6): 1335-1340.
[16] 高佳程, 田蕴卿, 朱永利, 等. 基于完全集合经验模态分解和排列熵的局部放电信号的小波包去噪方法[J]. 电力系统及其自动化学报, 2018, 30(3): 1-7.
[17] 秦金飞, 朱琦, 周玮, 等. 基于经验小波与小波变换的GIS局部放电信号去噪方法研究[J]. 高压电器, 2019, 55(7): 70-77, 86.
[18] 钱帅伟, 彭彦军, 周泽民, 等. 以提升小波包系数熵为特征值的隐马尔科夫电缆局部放电识别[J]. 电气技术, 2020, 21(10): 93-102.
[19] 马星河, 张登奎. 基于改进经验小波变换的高压电缆局部放电噪声抑制研究[J]. 电工技术学报, 2021, 36(增刊1): 353-361. |
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2022, Vol. 23 
