基于数据挖掘的电力设备状态诊断系统建模

The Modeling of the Power Equipment Condition Diagnostic System Based on Data Mining

以电力公司的业务需求为背景,为实现电力设备的状态诊断,以数据挖掘技术中的粗糙集和决策树算法为依据,采用粗糙集和决策树相结合的数据处理模型对电力设备的各属性数据进行了分析处理。综合运用粗糙集和决策树两种数据挖掘算法,通过粗糙集技术进行属性约简,并运用决策树的ID3算法对约简后的数据进行分枝、减枝得到规则集,实现对电力设备工作状态的快速、高效诊断,并根据其工作状态提供决策支持。

The system uses the business needs of a power company as the background. For the realization of the state testing of electrical equipment, rough sets and decision tree algorithm belonging to data mining technology is used as the basis. The paper proposes a data processing model combining rough sets with decision tree to realize for power each attribute the data analysis and processing equipment for power each attribute of electrical equipment. Rough sets and decision tree are used in this paper synthetically. Through rough set technology attribute reduction can be realized in this paper. Data which has been reduced is branched and cut branches by the use of the ID3 decision tree algorithm, and then rules in order can be got. At last, the working status of electrical equipment can be diagnosed rapidly and effi-ciently and the decision support is provided according to their work status.