摘要
随着高压输电线路长度不断增加,高压输电电缆故障在线识别成为当前的研究热点。文中针对高压输电电缆故障监测与识别的不足,提出了一种基于灰色关联度分析的高压电缆故障利萨如图形识别方法。该方法包含基于利萨如图形的信号分析方法和基于灰色关联度的模式识别方法,通过采集高压电缆首末端环流并构建二维利萨如图形,分析获取图形特征参数包括长轴、短轴、离心率、倾斜角及其变化率并作为输入特征向量,通过求解未知故障类型的输入特征向量与已知故障类型参数组成的样本空间向量的嫡值、嫡权值、关联系数等得到相应的关联度,最终实现故障的准确识别。最后以实际线路为参考搭建了仿真模型并结合实例分析验证了该方法的准确性,为高压输电电缆故障识别提供了新思路。
With the ever increase of length of high-voltage(HV)transmission lines,the on-line identification on the fault of high-voltage transmission cable becomes into the current research hotspot.Aiming at the deficiency of fault monitoring and identification of high-voltage transmission cable in this paper,a kind of Lissajous pattern identification method on the fault of high-voltage cable based on grey relation analysis is proposed.This method includes a signal analysis method based on Lissajous pattern and a pattern recognition method based on grey relation.The head and end circulating current of the high-voltage cable is collected and a two-dimensional Lissajous pattern is con-structed to analyze and obtain such graphical feature parameters as long axis,short axis,eccentricity and tilt angle and its variation rate,which are used as input feature vectors.The corresponding degree of correlation is obtained through solving entropy value,entropy weight and correlation coefficient of the sample space vector which is consisted of input feature vector of unknown type of fault and the parameters of the known types of fault and,eventually,the accurate identification of the fault is achieved.Finally,the simulation model is set up with the actual line as the reference and the accuracy of the method is analyzed and verified in combination with example,which provides a new idea for fault identification of high-voltage transmission cable.
作者
夏向阳
赵威
刘炎
李明德
郭长春
李旭
XIA Xiangyang;ZHAO Wei;LIU Yan;LI Mingde;GUO Changchun;LI Xu(College of Electrical and Information Engineering,Changsha University of Science&Technology,Changsha 410114,China;Hengyang City Commodity Quality Supervision and Inspection,Hunan Hengyang 421000,China;Changlan Electric Technology Co.,Ltd.,Changsha 410007,China)
出处
《高压电器》
CAS
CSCD
北大核心
2021年第11期124-130,共7页
High Voltage Apparatus
基金
湖南省自然科学基金(2018JJ4025)。
关键词
高压电缆
利萨如图形
灰色关联度
关联系数
故障识别
high-voltage cable
Lissajous pattern
grey relation
correlation coefficient
fault identification