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Affine Projection Algorithm based High-Order Error Power for Partial Discharge Denoising in Power Cables
IEEE Transactions on Instrumentation and Measurement ( IF 5.6 ) Pub Date : 2020-04-01 , DOI: 10.1109/tim.2019.2914710
Lu Lu , Guangya Zhu , Xiaomin Yang , Kai Zhou , Zheng Liu , Wei Wu

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 $p$ th power algorithm (APLMPA) that includes the $p$ th 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.

中文翻译:

基于仿射投影算法的电力电缆局部放电去噪高阶误差功率

电缆绝缘的现场局部放电(PD)检测对于电力系统维护具有重要意义。为了保留去噪后PD信号的更多基本特征,本文基于高阶误差功率(HOEP)准则,提出了一种新的仿射投影算法(APA)进行PD去噪。我们提出了一种新的仿射投影最小均值绝对第三算法(APLMATA),它利用了 HOEP 标准( $p=3$ ) 并且可以在高斯干扰下实现可靠​​的性能。我们进一步开发了一种改进的 APLMATA (MAPLMATA) 以减少具有适度计算负担的误调整。为高斯信号的 MAPLMATA 推导出分析模型。为了增强算法在广义高斯噪声场景中的稳定性,仿射项目最小均值 $p$ 次幂算法 (APLMPA) 包括 $p$ 给出了对误差的幂依赖性。特别是,我们应用所提出的基于 APA 的算法来抑制电力电缆中 PD 信号的噪声。仿真和实验结果证明了所提出的系统识别和局部放电去噪算法的有效性。
更新日期:2020-04-01
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