数据挖掘在电站故障预警中的应用

Application of Data Mining in Predictive Alarm of Power Plant Failure

近年,电站企业从自动化转型为信息化、智能化的需求升高,通过对电站DCS中储存的大量数据进行分析,能够提示设备劣化状态,对电站企业提高生产效率、经济安全运行有积极的指导意义。将数据挖掘应用于电站数据分析,试图为电站安全性运行提供理论依据。介绍了数据挖掘的概念,着重研究了数据挖掘中数据预处理、聚类、回归的方法,之后将该方法应用于实际电站的预警中取得了较好的效果。

In recent years, the demand for power plant companies to transform from automation to informationization and intelligence has increased. By analyzing the large amount of data stored in the power plant’s DCS, it can prompt the deterioration of equipment, it also has positive guiding significance for power plant enterprises to improve production efficiency and economic and safe operation. The data mining is applied to power plant data analysis in an attempt to provide a theoretical basis for the safe operation of power plant. The concept of data mining is introduced, and focuses on the methods of data preprocessing, clustering and regression in data mining. After that, the method has been applied to the predictive alarm of actual power plants and achieved good results.