Research on Fault Line Selection Method for Small Current Grounding System in High Noise Environment Based on IDRSN

WANG Qiang; LV Honghao; ZHOU Xiaochao; ZHANG An

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Research on Fault Line Selection Method for Small Current Grounding System in High Noise Environment Based on IDRSN

更新时间：2025-08-12

- Research on Fault Line Selection Method for Small Current Grounding System in High Noise Environment Based on IDRSN
- High Voltage Apparatus (2025)
- 作者机构：
  
  1.智慧能源技术湖北省工程研究中心,湖北省宜昌市443002
  2.三峡大学电气与新能源学院,湖北省宜昌市443002
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(52277012)
- DOI：
  CLC：
- Received：23 June 2025，
  
  Revised：14 July 2025，
  
  Accepted：30 July 2025，
- 稿件说明：
移动端阅览
WANG Qiang, LV Honghao, ZHOU Xiaochao, et al. Research on Fault Line Selection Method for Small Current Grounding System in High Noise Environment Based on IDRSN[J/OL]. High voltage apparatus, 2025.
DOI：

WANG Qiang, LV Honghao, ZHOU Xiaochao, et al. Research on Fault Line Selection Method for Small Current Grounding System in High Noise Environment Based on IDRSN[J/OL]. High voltage apparatus, 2025. DOI：

摘要

小电流接地系统发生单相接地故障时，暂态零序电流信号持续时间短、衰减快、易受电磁噪声干扰。针对现有选线方法抗噪能力不足的问题，文中提出一种基于改进深度残差收缩网络(improved deep residual shrinkage network

IDRSN)的故障选线新方法。首先，提出了一种收缩因子动态调节的改进阈值函数，以减少有效特征的损失；其次，设计了基于高效通道注意力机制的自适应阈值模块(adaptive threshold block

ATB)与自适应收缩模块(adaptive shrinkage block

ASB)，并将两者嵌入到改进的残差收缩块(improved residual shrinkage building unit

IRSBU)中。该设计实现了阈值参数与收缩因子的自适应获取、模型去噪能力的增强和计算效率的优化。为验证所提选线方法的有效性，在配网10kV辐射型线路及IEEE-34节点仿真系统上进行了多种复杂干扰场景下的测试。结果表明，所提IDRSN模型在-5 dB强噪声下，平均F1分数较DRSN提升了3.11%。

Abstract

In small current grounding systems

transient zero-sequence current signals during single-phase ground faults are characterized by short duration

fast decay

and susceptibility to electromagnetic noise interference. Addressing the insufficient noise robustness of existing line selection methods

this paper proposes a novel fault line selection method based on an Improved Deep Residual Shrinkage Network (IDRSN). Firstly

an improved threshold function with dynamically regulated shrinkage factors is proposed to reduce the loss of effective features. Secondly

an Adaptive Threshold Block (ATB) and an Adaptive Shrinkage Block (ASB)

based on an efficient channel attention mechanism

are designed. These blocks are incorporated into an Improved Residual Shrinkage Building Unit (IRSBU). This design enables the adaptive acquisition of threshold parameters and shrinkage factors

enhances the model's denoising capability

and optimizes computational efficiency. To validate the effectiveness of the proposed line selection method

tests were conducted under various complex interference scenarios on a 10kV radial distribution line system and the IEEE-34 node simulation system. The results demonstrate that the proposed IDRSN model achieves an average F1-score improvement of 3.11% compared to the DRSN model under strong noise conditions of -5 dB.

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references

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