首页|期刊导航|电力工程技术|基于改进SSTDR的XLPE电缆抗干扰故障定位仿真

基于改进SSTDR的XLPE电缆抗干扰故障定位仿真OA

An anti-interference fault location simulation for XLPE cables based on improved SSTDR

中文摘要英文摘要

随着交联聚乙烯(cross-linked polyethylene,XLPE)电力电缆在现代电网中的广泛应用,其复杂的敷设环境及外界电磁干扰对电缆故障定位精度造成了较大影响.为解决现有电缆故障定位方法在高噪声环境中故障定位精度较低的问题,文中提出一种基于扩展频谱时域反射(spread spectrum time domain reflectometry,SSTDR)改进的电缆故障定位方法.首先,引入M序列多周期信号建模方法,结合加窗滤波与自适应小波去噪方法对反射信号进行优化处理;然后,采用基于平滑相关变换(smoothed coherence transform,SCOT)加权函数的二次互相关加权方法,处理每个周期的入射信号与滤波后的反射信号,得到每个周期的相关系数,并通过算术平均得到最终的定位信息;最后,采用高斯平滑滤波方法增强故障位置的峰值特征,并通过峰值检测算法确定故障的位置信息.基于MATLAB/Simulink平台的仿真实验表明,在-20 dB低信噪比条件下,文中方法对不同位置的短路、开路故障以及多支路故障的平均定位误差均小于 0.062 m,平均相对误差低于 0.25%.与传统方法和现有技术相比,文中方法在低信噪比条件下能够实现有效定位,且定位相对误差至少提高 0.01%.实验结果进一步验证了文中方法具有良好的抗噪声故障定位性能.

Complex laying environments and external electromagnetic interference have significantly impacted the accuracy of cable fault location,particularly in modern power grids with the widespread application of cross-linked polyethylene(XLPE)power cables.In order to solve the low accuracy of existing fault location methods in high-noise environments,an improved fault positioning method based on spread spectrum time domain reflectometry(SSTDR)is proposed.Firstly,by introducing a multi-period signal modeling method using M-sequences,combined with windowed filtering and adaptive wavelet denoising,the reflected signals are optimized.Subsequently,a quadratic cross-correlation weighting method based on the smoothed coherence transform(SCOT)weighting function is employed to process the incident signals and the filtered reflected signals for each period,obtaining the correlation coefficients for each period.The final location information is derived through arithmetic averaging.Finally,Gaussian smoothing filtering is applied to enhance the peak characteristics of the fault location,and the fault position is determined using a peak detection algorithm.Simulation experiments conducted on the MATLAB/Simulink platform demonstrate that under a low signal-to-noise ratio of-20 dB,the average location error for short-circuit,open-circuit faults at different positions,and multi-branch faults is less than 0.062 m,with an average relative error below 0.25%.Compared to traditional methods and existing methods,the proposed method exhibits effective localization under low signal-to-noise ratio conditions,with the relative localization error improving by at least 0.01%.Furthermore,the experimental results validate that the method proposed in this paper has robust noise-resistant fault localization performance.

王毅;赖国鹏;罗樟;何家骏;陈权峰;花之蕾

重庆邮电大学通信与信息工程学院,重庆 400065||重庆邮电大学移动通信技术重庆市重点实验室,重庆 400065重庆邮电大学通信与信息工程学院,重庆 400065国网重庆市电力公司营销服务中心,重庆 400014国网重庆市电力公司营销服务中心,重庆 400014国网重庆市电力公司营销服务中心,重庆 400014华北电力大学扬中智能电气研究中心,江苏 镇江 212200

信息技术与安全科学

电缆故障定位扩展频谱时域反射(SSTDR)M序列多周期信号建模小波去噪高斯平滑滤波峰值检测

cable fault locationspread spectrum time domain reflectometry(SSTDR)M-sequencemulti-period signal modelingwavelet denoisingGaussian smoothing filterpeak detection

《电力工程技术》 2026 (3)

46-56,11

重庆市技术创新与应用发展专项重点项目"基于边缘计算的局部放电多通道智能在线监测技术研究与应用"(CSTB2022TIAD-KPX0040) 本文得到扬中市社会发展科技计划项目(YS202305),扬中市微网群优化运行智能技术示范项目资助,谨此致谢!

10.12158/j.2096-3203.2026.03.006

评论