基于SVD与小波变换的反高频脉冲磁场窃电方法

An electricity stealing method of anti-high-frequency pulsed magnetic field based on SVD and wavelet transform

中文关键词: 脉冲磁场  窃电  FFT 功率谱  奇异值分解  小波变换

英文关键词: pulsed magnetic field  electricity stealing  FFT power spectrum  singular value decomposition  wavelet transform

中文摘要:

      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 modedecomposition，EMD）法对比，所提方法抑制效果更突出。

英文摘要:

      Faced with the more insidious electricity stealing methods of high-frequency pulsed magnetic field, anti-theft detection 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 separate stolen electricity signal in detection. Firstly, the noisy magnetic field mixed signal is transformed by FFT to obtain the power spectrum, and the classical threshold is introduced to determine the number of narrow-band noises and the effective rank order of the SVD.Then the mixed signal is SVD decomposed, the singular value corresponding to the narrow-band noise is reset to zero, and then the signal 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.