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作 者:阙华坤 林国龙 曹云飞 冯小峰 江泽涛 李健 范竞敏 QUE Huakun;LIN Guolong;CAO Yunfei;FENG Xiaofeng;JIANG Zetao;LI Jian;FAN Jingmin(Metrology Center,Guangdong Power Grid Co.,Ltd.,Guangzhou 518049,China;School of Automation,Guangdong University of Technology,Guangzhou 510006,China)
机构地区:[1]广东电网有限责任公司计量中心,广州518049 [2]广东工业大学自动化学院,广州510006
出 处:《电力需求侧管理》2022年第3期92-97,共6页Power Demand Side Management
基 金:国家自然科学基金资助项目(62073084);中国南方电网有限责任公司科技项目(GDKJXM20185800)。
摘 要:面对更隐蔽的高频脉冲磁场窃电方式,根据磁场信号进行反窃电检测会由于噪声影响而失效。针对这个问题,提出将奇异值分解(singular value decomposition,SVD)和小波变换结合的方法应用到防窃电装置中,在检测中去除噪声分离出窃电信号。首先将带有噪声的磁场混合信号进行快速傅立叶变换(fast Fourier transform,FFT)求出功率谱,引入经典阈值判断出窄带噪声的个数,并以此确定奇异值分解的有效秩阶次。然后对混合信号SVD分解,将窄带噪声对应的的奇异值置零后重构信号,最后利用小波变换去除随机噪声的影响。仿真和实验结果表明,此方法能有效应用到窃电检测中,并通过与FFT阈值滤波法、经验模态分解(empirical mode decomposition,EMD)法对比,所提方法抑制效果更突出。Faced with the more insidious electricity stealing methods of high⁃frequency pulsed magnetic field,anti⁃theft detec⁃tion based on magnetic field signals would fail due to noise.Aiming at this problem,a method combining SVD and wavelet transform is applied to anti⁃theft devices and proposed to remove noise and sepa⁃rate stolen electricity signal in detection.Firstly,the noisy magnetic field mixed signal is transformed by FFT to obtain the power spec⁃trum,and the classical threshold is introduced to determine the num⁃ber of narrow⁃band noises and the effective rank order of the SVD.Then the mixed signal is SVD decomposed,the singular value corre⁃sponding to the narrow⁃band noise is reset to zero,and then the sig⁃nal is reconstructed.Finally,wavelet transform is used to remove the influence of random noise.Simulation and experimental results show that,this method can be effectively applied to the detection of electrical stealing.Compared with FFT threshold filtering method and EMD method,the suppression effect of the proposed method is more prominent.
关 键 词:脉冲磁场 窃电 FFT功率谱 奇异值分解 小波变换
分 类 号:TM93[电气工程—电力电子与电力传动] TM73
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