电能质量扰动信号的自适应去噪方法

发布时间：2018-05-10 20:03

本文选题：电能质量 + 基于块匹配的三维变换域联合滤波　；参考：《电力系统自动化》2016年23期

【摘要】：有效地降低电能质量信号中的噪声,是做好电能质量信号检测、识别等工作的基础。为了克服一维电能质量信号降噪的难点问题,即有效地去除噪声并完整地保留奇异点的特征,对目前图像处理领域中针对高斯等噪声降噪性能最好的基于块匹配的三维变换域联合滤波(BM3D)算法进行了改进,提出一种电能质量扰动信号的自适应去噪新方法。该方法参数较少,无需估计噪声方差,也无需人为设定滤波阈值,而是通过自适应估算较为准确的阈值实现离散余弦变换(DCT)域的滤波。通过对电压中断、电压暂降、电压暂升、脉冲暂态、振荡暂态和谐波这6种常见的电能质量信号进行降噪仿真实验,并与应用较为广泛的小波阈值去噪法进行对比分析,最后应用于实际电能质量扰动数据的降噪,验证了所述算法的有效性。
[Abstract]:Effectively reducing the noise in power quality signal is the basis of power quality signal detection and recognition. In order to overcome the difficult problem of noise reduction in one-dimensional power quality signal, that is, removing noise effectively and preserving singularity completely, In the field of image processing, a new adaptive denoising method for power quality disturbance signals is proposed, which is based on block matching in 3D transform domain joint filtering and BM3D, which has the best noise reduction performance in the field of image processing. This method has few parameters, no estimation of noise variance, and no artificial setting of filtering threshold. Instead, the discrete cosine transform (DCT) domain is filtered by adaptive estimation of a more accurate threshold. Six common power quality signals, such as voltage interruption, voltage sag, voltage surge, pulse transient, oscillation transient and harmonic, are simulated and compared with the wavelet threshold denoising method, which is widely used. Finally, the proposed algorithm is applied to the real power quality disturbance data denoising, and the effectiveness of the proposed algorithm is verified.
【作者单位】：西南交通大学电气工程学院;
【基金】：中央高校基本科研业务费专项资金资助项目(2682014RC07)~~
【分类号】：TM711

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