摘要
传统输电线路暂态故障测距方法未对点云数据进行分类和分割,存在误差叠加问题,使得测距算法应用于整个数据集时,无法准确识别出线路相关的特征点,从而引入大量干扰和错误信息,导致测距结果的相对误差增大。为此,提出了基于机载激光点云的输电线路暂态故障测距方法。采集机载激光点云数据,建立输电线路模型,得到线路的三维结构和特征信息;根据粗提取和精提取技术对点云数据进行分类和分割,实现输出波形故障信息判定,找到可能存在故障的区域;通过分析故障波形的特征,采用小波系数提取线路故障中的暂态分量,根据不同的小波系数进行故障测距。为验证方法性能,设计仿真实验,分别使用设计的故障测距方法和传统的基于行波分析故障测距方法进行测试。实验结果表明:在改变故障分支、故障类型以及过渡电阻的实验条件下,该方法得到的测距结果相对误差平均为0.436%,验证了方法的有效性。
The traditional transient fault location method for transmission lines does not classify and segment point cloud data,resulting in the problem of error superposition.When the distance measurement algorithm is applied to the entire dataset,it cannot accurately identify the characteristic points related to the line,which introduces a large amount of interference and error information,leading to an increase in the relative error of the distance measurement results.Therefore,a transient fault location method for transmission lines based on airborne laser point cloud is proposed.It collects airborne laser point cloud data,establishes a transmission line model,and obtains the threedimensional structure and feature information of the line,classifies and segments point cloud data using coarse and fine extraction techniques to determine output waveform fault information and identify potential fault areas.By analyzing the characteristics of fault waveforms,wavelet coefficients are used to extract transient components in line faults,and fault location is carried out based on different wavelet coefficients.To verify the performance of the method,simulation experiments are designed and tested using both the designed fault location method and the traditional fault location method based on traveling wave analysis.The experimental results show that under the experimental conditions of changing the fault branch,fault type,and transition resistance,the average relative error of the distance measurement results obtained by the design method is 0.436%,which verifies the effectiveness of the method.
作者
郑金杯
张镇源
赵宇
卢敏杰
ZHENG Jinbei;ZHANG Zhenyuan;ZHAO Yu;LU Minjie(Foshan Power Supply Bureau of Guangdong Power Grid Co.,Ltd.,Foshan 528000,Shandong,China;Dongfang Electronics Co.,Ltd.,Yantai 264000,Shandong,China)
出处
《自动化技术与应用》
2026年第4期40-44,共5页
Techniques of Automation and Applications
基金
广东省科技项目(0306002023030103SJ00014)。
关键词
机载激光点云
输电线路
故障测距
机器学习算法
三维点云数据
小波系数
airborne laser point cloud
transmission lines
fault distance measurement
machine learning algorithms
three-dimensional point cloud data
wavelet coefficient
