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文章摘要
直流电能表计量信号自适应降噪方法
Adaptive noise reduction method for metering signal of direct current electricity meter
Received:September 07, 2023  Revised:February 16, 2024
DOI:10.19753/j.issn1001-1390.2024.06.024
中文关键词: 直流电能计量  自适应降噪  变分模态分解  小波阈值去噪  参数优化
英文关键词: direct current energy metering, adaptive noise reduction, variational mode decomposition, wavelet threshold de-noising, parameter optimization
基金项目:国家电网公司科技资助项目(项目编号)
Author NameAffiliationE-mail
ZHONGLihua Metrology Center of Guangdong Power Grid Co., Ltd. 463695442@qq.com 
PAN Feng* Metrology Center of Guangdong Power Grid Co., Ltd. pf6601@163.com 
YANG Yuyao Metrology Center of Guangdong Power Grid Co., Ltd. 2157098004@qq.com 
LI Jinli Metrology Center of Guangdong Power Grid Co., Ltd. laing_in_ps@163.com 
QI Shuzhe Metrology Center of Guangdong Power Grid Co., Ltd. 1814411416@qq.com 
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中文摘要:
      直流用电负荷包含DC/DC变换器等电力电子器件,非线性特性显著,导致直流输出端电压、电流信号存在大量纹波,需通过滤波降噪处理提升直流电能计量的准确性。针对现有的滤波降噪方法参数设置缺乏优化、滤波降噪效果尚待提升问题,提出了基于自适应变分模态分解与小波阈值去噪相结合的直流电能表计量信号降噪方法。建立输出端直流电压、电流信号变分模态分解的参数最优化模型,并联合互信息分析,实现原始信号的有效模态分量与噪声模态分量的自适应区分。在此基础上,建立以信噪比、均方根误差、平滑度、相关系数复合评价指标最优的小波阈值去噪参数最优化模型,实现噪声模态分量的最优滤波降噪。通过实测数据计算分析,验证所提方法的有效性。
英文摘要:
      DC load contains DC/DC converters and other power electronic devices, which is featured with significant nonlinear characteristics, resulting in a large number of ripple signals in DC output voltage and current signals. It is necessary to improve the accuracy of DC energy measurement by filtering and noise reduction. Aiming at the problem that the parameter setting of the existing filter de-noising method is not optimized and the effect of filter de-noising needs to be improved, this paper proposes an adaptive noise reduction method for metering signal of direct current electricity meter based on adaptive variational mode decomposition and wavelet threshold de-noising. The parameter optimization model of variational mode decomposition of DC voltage and current signal is established, and the mutual information analysis is combined to realize the adaptive differentiation between the effective mode component and the noise mode component of the original signal. On this basis, the optimization model of wavelet threshold de-noising parameters is established with the composite evaluation indices of signal-to-noise ratio, root-mean-square error, smoothness and correlation coefficient, and the optimal filtering of noise modal components is realized. The validity of the proposed method is verified by calculating and analyzing the measured data.
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