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基于改进VMD与特征融合的直流配电系统接地故障精准定位

Accurate Location of Ground Faults in DC Distribution Systems Based on Improved VMD and Feature Fusion

  • 摘要: 针对直流配电系统接地故障定位精度与识别效率低等问题,提出一种基于改进VMD与多域特征融合的精准定位方法。通过多尺度排列熵自适应确定模态数,建立惩罚因子动态调整机制,从时域、频域和时频域提取故障特征,采用Relief-F算法筛选关键特征,并设计浅层加权融合与深层神经网络相结合的融合策略,利用支持向量机实现故障区段识别,最后结合双端行波测距和误差补偿模型完成精准定位。仿真结果表明,该方法在不同过渡电阻条件下的平均定位误差控制在10 m以内,总耗时为119.83 ms,满足实时性要求。

     

    Abstract: A precise positioning method based on improved variational mode decomposition and multi domain feature fusion is proposed to address the low accuracy and recognition efficiency of grounding fault location in DC distribution systems. By adaptively determining the number of modes through multi-scale permutation entropy and establishing a dynamic adjustment mechanism for penalty factors, fault features are extracted from the time domain, frequency domain, and time-frequency domain. Relief-F algorithm is used to screen key features, and a fusion strategy combining shallow weighted fusion and deep neural network is designed. Support vector machine is used to identify fault sections, and accurate positioning is achieved by combining dual and traveling wave ranging and error compensation models. The simulation results show that the average positioning error of this method is controlled within 10 m under different transition resistance conditions, with a total time of 119.83 ms, meeting the real-time requirements.

     

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