| 引用本文: | 颜楠楠,傅正财,李俊峰,王常飞.雷电流在线监测系统中噪声干扰的处理方法[J].电力自动化设备,2012,32(9): |
| YAN Nannan,FU Zhengcai,LI Junfeng,WANG Changfei.Noise interference processing of lightning current monitoring system[J].Electric Power Automation Equipment,2012,32(9): |
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| 摘要: |
| 针对雷电流在线监测系统中的噪声干扰，提出一种基于模糊神经系统的雷电流波形处理方法。利用所提方法对噪声频率在0.001～10 MHz间变化的雷电流波形进行仿真测试， 消噪后雷电流波形的峰值误差小于0.06 %，说明所提方法具有很强的抑噪能力。分别用曲线拟合法、小波分析法和所提方法对设备实测波形消噪，分析结果表明，所提方法具有更好的非线性快速逼近性能，得到的波形匹配度高，参数误差最小。 |
| 关键词: 雷电 监测 雷电流 波形分析 噪声消除 模糊神经系统 波形参数 |
| DOI： |
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| Noise interference processing of lightning current monitoring system |
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YAN Nannan1, FU Zhengcai1, LI Junfeng2, WANG Changfei2
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1.Key Laboratory of Control of Power Transmission and Conversion，Ministry of Education，Department of Electrical Engineering，Shanghai Jiao Tong University，Shanghai 200240，China;2.Henan Electric Power Transmission & Transformation Construction Company，Zhengzhou 450052，China
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| Abstract: |
| A noise interference processing method based on fuzzy neural system model is proposed for the lightning current online monitoring system. Simulation and test are carried out for the lightning current with the noises varying between 0.001 MHz and 10 MHz，and results indicate that，the peak value error of denoised lightning current waveform is below 0.06 %，showing the excellent denoising capability of the proposed method. The measured lightning current with noises is processed by the curve fitting，wavelet analysis and the proposed method respectively，and the analysis shows that，the proposed method has faster nonlinear approaching property，higher waveform matching degree and smaller parameter error. |
| Key words: lightning monitoring lightning current waveform analysis denoising fuzzy neural system waveform parameter |
