井下电力电缆故障定位研究

Research on fault positioning of underground power cable

针对传统井下电力电缆故障定位方法依赖主观参数选择和抗噪性能较差,无法满足强噪声背景下井下电力电缆故障精确定位要求的问题,提出了一种基于樽海鞘群算法(SSA)优化变分模态分解(VMD)并结合改进型Teager能量算子(NTEO)的井下电力电缆故障定位方法。针对VMD在信号分解上存在的模态混叠、过分解和欠分解问题,采用SSA以模糊熵为适应度函数对VMD模态数K和惩罚因子α2个参数进行优化,得到更能反映故障特征信息的本征模态函数;采用NTEO对本征模态函数进行首波波头标定,得到首末两端的波头到达时刻,根据双端测距法得出故障位置。采用PSCAD/EMTDC进行井下电力电缆故障仿真,模拟具有强背景噪声的井下故障信号,结果表明:①在理想电流信号中加入9,12 dB噪声后,SSA-VMD的信噪比最低,皮尔逊相关系数最大,说明SSA-VMD在最大程度降噪的同时,能很好地保留信号的特征信息。②在不同过渡电阻下,SSA-VMD-NTEO的定位精度较高。③在不同故障相角下,SSA-VMD-NTEO在采样点上出现不同,但定位位置没有改变,依旧保持较高的定位精度。④在不同故障距离下,SSA-VMD-NTEO均能保证较高的定位精度。⑤在井下较大噪声和10 MHz采样频率下,SSA-VMD-NTEO较小波模极大值和VMD+NTEO 2种方法的定位精度具有明显优势。

The traditional underground power cable fault positioning method relies on subjective parameter selection and noise resistance is poor.It cannot meet the accurate fault positioning requirements of underground power cable under strong noise background.In order to solve the above problems,a fault positioning method of underground power cable based on salp swarm algorithm(SSA)optimizing variational mode decomposition(VMD)combined with novel Teager energy operator(NTEO)is proposed.In response to the problem of modal aliasing,over decomposition,and under decomposition in signal decomposition of VMD,SSA is used to optimize the modal number K and penalty factorαof VMD parameters using fuzzy entropy as the fitness function.The intrinsic modal function that better reflects the fault feature information is obtained.NTEO is used to calibrate the first wave head to obtain the arrival time of the wave heads at both ends.The fault position is determined based on the dual end distance measurement method.PSCAD/EMTDC is used for underground power cable fault simulation.It simulates underground fault signals with strong background noise.The results show the following points.①After adding 9 dB and 12 dB noise to the ideal current signal,the signal-to-noise ratio of SSA-VMD is the lowest,and the Pearson correlation coefficient is the highest.It indicates that SSA-VMD can effectively preserve the characteristic information of the signal while minimizing noise.②Under different transition resistances,the positioning precision of SSA-VMD-NTEO is relatively high.③Under different fault phase angles,although SSA-VMD-NTEO may have different sampling points,the positioning position remains unchanged and still maintains high precision.④SSA-VMD-NTEO can ensure high positioning precision at different fault distances.⑤Under high underground noise and a sampling frequency of 10 MHz,SSA-VMDNTEO has significant advantages in positioning precision compared to wavelet modulus maximum and VMD+NTEO methods.