| 摘要: |
| 为解决配电网行波波头检测困难的问题，提出一种基于随机共振-变分模态分解(SR-VMD)的行波信号检测方法。利用粒子群优化的变尺度SR对行波信号进行预处理，有效提高输出信号的信噪比。利用VMD算法将输出信号进行自适应分解，应用到故障定位中。用Teager能量算子(TEO)对行波波头进行标定，代入测距公式得到故障距离。仿真结果表明，该方法能在噪声背景下实现故障信息的提取，有效提高了故障测距的精度，尤其是高阻接地和电压过零附近接地的精度。 |
| 关键词: 变尺度随机共振 变分模态分解 Teager能量算子 行波检测 粒子群优化算法 |
| DOI：DOI: 10.19783/j.cnki.pspc.200104 |
| 投稿时间：2020-01-23修订日期：2020-03-25 |
| 基金项目:辽宁省自然基金指导计划项目资助(20180550438) |
|
| Weak fault traveling wave detection method based on SR-VMD |
| FU Hua,WANG Jingyu |
| (Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao 125105, China) |
| Abstract: |
| In order to solve the difficulty of detecting the traveling wave head in a distribution network, a method of traveling wave signal detection based on Stochastic Resonance and Variational Mode Decomposition (SR-VMD) is proposed. The traveling wave signal is preprocessed by the variable scale SR of particle swarm optimization. This can effectively improve the signal-to-noise ratio of the output signal. The output signal is decomposed adaptively by a VMD algorithm and applied to fault location. Then the traveling wave head is calibrated by a Teager Energy Operator (TEO), and the fault distance is obtained by the distance formula. The simulation results show that the method can extract fault information from the noise background, and improve the accuracy of fault location, especially the accuracy of high resistance grounding and grounding near voltage zero crossing.
This work is supported by Natural Science Guiding Program of Liaoning Province (No. 20180550438). |
| Key words: variable scale stochastic resonance variational mode decomposition Teager energy operator traveling wave detection particle swarm optimization algorithm |
