基于故障群-征兆群对子的变电站故障诊断

The Fault Diagnosis for Substation Based on Couples of Fault-Masses and Symptom-Masses

为处理好变电站故障诊断问题中故障源和故障征兆间因果关系的不确定性 ,本文提出了基于故障群组合优化的故障诊断方法。在建立保护配合的 Petri网模型的基础上 ,用状态转移方程分析模型的动态特性 ,从中获取所有故障群 -征兆群对子。创建故障群组合匹配已知故障征兆的适应度函数 ,并用遗传算法搜索出最优诊断解。实验证明 :该方法不仅能有效地辨识出故障源 ,而且能提供保护装置拒动、断路器装置拒动、信号传输错误等信息 。

In view of the uncertainties of the causalities from fault sources to fault symptoms in the fault diagnosis for substation,a new fault diagnosis method based on optimizing the combination of fault masses is proposed in this paper.The protection schemes are described as Petri net models,and all couples of fault masses and symptom masses are obtained in the process of analyzing the dynamic characteristics of the models with the help of the transferring state equation.A new fitness function is presented to evaluate the feasibility that the combination of fault masses matches the known fault symptoms,and the genetic algorithm is employed to search out the optimal answers.The trials prove that the developed methodology is effective and can supply detailed diagnosis results:fault sources,protective device non operations,circuit breaker non operations and missing signals.It is beneficial for the operators to confirm broken down components quickly.