基于图像信息熵与多元变分模态分解的电缆局放信号去噪方法  

A Denoising Algorithm for Cable Partial Discharge Signals Based on Image Information Entropy and Multivariate Variational Mode Decomposition

作　　者：王晓卫 王雪[1] 王毅钊 张志华 梁振锋[1] Wang Xiaowei;Wang Xue;Wang Yizhao;Zhang Zhihua;Liang Zhenfeng(School of Electrical Engineering Xi’an University of Technology,Xi’an 710048,China;Institute of Electric Power Research of Shaanxi Electric Power Company,Xi’an 710100,China)

机构地区：[1]西安理工大学电气工程学院,西安710048 [2]国网陕西省电力有限公司电力科学研究院,西安710100

出　　处：《电工技术学报》2024年第13期4100-4115,4152,共17页Transactions of China Electrotechnical Society

基　　金：国家自然科学基金项目(52177114,61403127);国网陕西省电力有限公司科技项目(5226KY220006)资助。

摘　　要：局部放电(PD)检测是评估交联聚乙烯(XLPE)电缆绝缘状态的主要手段。针对电缆终端与中间接头局部放电现场检测时存在白噪声、周期性窄带干扰,以及去噪过程中自适应性较弱的问题,该文提出了一种基于图像信息熵与新型自适应多元变分模态分解的去噪方法。首先,对信号进行多元变分模态分解,重组信号并转换成灰度图像,进而计算图像一维信息熵。在考虑算法执行效率的同时,将Pearson相关系数与图像信息熵优化算法的模态参数相结合。其次,通过计算各本征模态分量的峭度来判定其主导分量的性质特征,利用峭度对噪声敏感的特性区分PD特征信息与噪声干扰分量,进而对噪声干扰分量进行3σ准则滤波。最后,通过新型改进小波阈值算法得到去噪信号。利用该方法对PD信号进行去噪,并与基于Spearman的变分模态分解(S-VMD)法、自适应集合经验模态分解(NAEEMD)法、短时傅里叶变换-奇异值分解(STFTSVD)法进行对比分析。结果表明,该方法对现场PD信号具有良好的抑噪性能,且耗时少、执行效率高、工程应用价值高。In recent years,cross-linked polyethylene cables have been developed in transmission lines and urban distribution networks due to their advantages,lightweight,high-temperature resistance,and high transmission power.With the increase in the number of XLPE power cables put into operation and the extension of cable lines,silicone rubber insulated prefabricated intermediate joints are widely used in XLPE power cables due to their excellent high-voltage shielding performance,overall prefabricated design,reliable grounding,large voltage margin,and convenient on-site installation.The intermediate cable joint is usually installed and formed on the laying site,which can quickly leave a hidden danger of cable operation failure.Because it comprises multi-layer solid composite structures with different dielectric properties,the probability of accidents is much higher than that of the cable body.Partial discharge(PD)detection is the main means of evaluating the insulation status of XLPE cables and the manufacturing and installation defects of cables.A PD denoising method based on image information entropy and novel adaptive multivariate variational mode decomposition(MVMD)is proposed to address the issues of white noise,periodic narrowband interference,and poor adaptability in on-site detection of PD at cable terminals and intermediate joints.Firstly,optimize the parameters of the MVMD algorithm by integrating multiple factors,and then,based on parameter optimization,perform modal decomposition on the noisy PD signal.Secondly,the kurtosis of each eigenmode component is calculated,and the kurtosis of the sine signal and double exponential decay signal at the signal-to-noise ratio of 0dB is calculated by using the characteristic that kurtosis is sensitive to noise to distinguish the PD characteristic information from the noise interference component.Then,the 3σcriterion is used to filter white noise with normal distribution.Finally,based on the improved new wavelet threshold function,the reconstructed PD signal is denoised to

关 键 词：多元变分模态分解 局部放电 图像信息熵 峭度 电力电缆 

分 类 号：TM77[电气工程—电力系统及自动化]