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首页> 外文期刊>IEEE Transactions on Instrumentation and Measurement >Affine Projection Algorithm-Based High-Order Error Power for Partial Discharge Denoising in Power Cables
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Affine Projection Algorithm-Based High-Order Error Power for Partial Discharge Denoising in Power Cables

机译:基于仿射投影算法的高阶误差功率在电力电缆中的局部放电降噪

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摘要

The onsite partial discharge (PD) detection of cable insulation is of great importance for power system maintenance. To preserve more basic features of denoised PD signal, in this paper, a PD denoising by a new class of affine projection algorithm (APA) is proposed based on the high-order error power (HOEP) criterion. We propose a new affine projection least mean absolute third algorithm (APLMATA), which exploits the HOEP criterion (p = 3) and can achieve reliable performance under Gaussian interference. We further develop a modified APLMATA (MAPLMATA) to reduce the misadjustment with moderate computational burden. Analytical models are derived for MAPLMATA for Gaussian signals. To enhance the stability of the algorithm in generalized Gaussian noise scenarios, an affine project least mean pth power algorithm (APLMPA) that includes the pth power dependence on the error is presented. In particular, we apply the proposed APA-based algorithms to suppress the noise from PD signal in power cables. Simulation and experimental results demonstrate the effectiveness of the proposed algorithms for system identification and PD denoising.
机译:电缆绝缘的局部局部放电(PD)检测对于电力系统维护非常重要。为了保留去噪PD信号的更多基本特征,本文提出了一种基于高阶误差功率(HOEP)准则的新型仿射投影算法(APA)去噪PD。我们提出了一种新的仿射投影最小均值绝对绝对第三算法(APLMATA),该算法利用HOEP准则(p = 3)并在高斯干扰下可以实现可靠的性能。我们进一步开发了改进的APLMATA(MAPLMATA),以减少适度的计算负担的错误调整。推导了针对高斯信号的MAPLMATA的分析模型。为了提高算法在广义高斯噪声场景中的稳定性,提出了一种仿射投影最小均方pth幂算法(APLMPA),该算法包括对误差的pth幂依赖性。特别是,我们应用了基于APA的算法来抑制电力电缆中PD信号产生的噪声。仿真和实验结果证明了所提出算法对系统识别和局部放电降噪的有效性。

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