Fault diagnosis of DC distribution network based on improved matrix half-tensor product Bayesian network

YU Huanan; QIU Huahua; WANG He; LI Shiqiang; WEI Bo

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Fault diagnosis of DC distribution network based on improved matrix half-tensor product Bayesian network

更新时间：2025-12-06

- Fault diagnosis of DC distribution network based on improved matrix half-tensor product Bayesian network
- Vol. 62, Issue 6, (2025)
- 作者机构：
  
  东北电力大学现代电力系统仿真控制与绿色电能新技术教育部重点实验室
- 作者简介：
- 基金信息：
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- Published：2025
- 稿件说明：
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YU Huanan, QIU Huahua, WANG He, et al. Fault diagnosis of DC distribution network based on improved matrix half-tensor product Bayesian network[J]. 2025, 62(6).
DOI：

YU Huanan, QIU Huahua, WANG He, et al. Fault diagnosis of DC distribution network based on improved matrix half-tensor product Bayesian network[J]. 2025, 62(6). DOI：

摘要

文章提出基于改进半张量积贝叶斯网络的直流配电网故障诊断算法。对基于半张量积的贝叶斯网络方法进行改进，引入了保护和断路器动作时刻可信度和动作状态可信度，提高了故障诊断精度，即使条件概率不准确时也能够对计算结果进行修正。考虑到直流配电网中保护与控制的深度融合，将反映控制状态改变的控制量与反映保护动作的保护量融合到半张量积贝叶斯网络中，使得故障诊断结果更加准确。通过算例分析，验证了所提出的诊断方法的正确性和可靠性。

Abstract

This paper proposes a fault diagnosis algorithm for DC distribution network based on improved half-tensor product Bayesian networks. The Bayesian network method based on half-tensor product is improved by introducing the protection and circuit breaker action moment confidence and action state confidence

which improves the fault diagnosis accuracy and enables to correct the calculation results even when the conditional probability is inaccurate. Considering the deep integration of protection and control in DC distribution network

the control quantity reflecting the change of control state and the protection quantity reflecting the protection action are integrated into the half-tensor product Bayesian network

which makes the fault diagnosis results more accurate. The correctness and reliability of the proposed diagnosis method are verified through the analysis of arithmetic cases.

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