数据挖掘的电力自动化系统故障自动诊断系统设计

Design of automatic fault diagnosis system for power automation system based on data mining

以进一步提升电力自动化系统故障诊断精度为出发点,设计数据挖掘的电力自动化系统故障自动诊断系统。系统操作者的需求通过应用表现层传递至业务处理层,业务处理层是系统的核心,包含故障自动诊断与故障追踪等主要功能,利用基于数据挖掘的故障自动诊断算法通过挖掘电力自动化系统状态参量关联规则,根据支持度与可信度最高的关联规则判断电力自动化系统故障类型;基于故障类型诊断结果,利用数据挖掘技术分析故障信息,通过决策树对故障信息实施反向追踪,确定故障原因,实现故障诊断。系统数据层为业务处理层提供数据服务。测试分析结果显示,该系统可自动、准确诊断电力自动化系统的各种故障。

In order to further improve the fault diagnosis accuracy of the power automation system as the starting point,the power automation system fault automatic diagnosis system based on data mining is designed.The requirements of system operators are transferred to the business processing layer through the application presentation layer,which is the core of the system,including the main functions of automatic fault diagnosis and fault tracking.The automatic fault diagnosis algorithm based on data mining is used to mine the association rules of state parameters of power automation system,and judge the power automation system according to the association rules with the highest support and reliability Based on the results of fault type diagnosis,the data mining technology is used to analyze fault information,and the decision tree is used to track the fault information in reverse to determine the cause of fault and realize fault diagnosis.The system data layer provides data services for the business processing layer.The test and analysis results show that the system can automatically and accurately diagnose various faults in power automation system.