基于数据挖掘及SIS的工况划分方法研究  

Research on condition identification based on data mining and SIS

作　　者：刘宝玲[1] 何钧[2] 

机构地区：[1]南昌工程学院电气与电子工程系,江西南昌330099 [2]江西省电力科学研究院,江西南昌330006

出　　处：《南昌工程学院学报》2009年第6期36-39,共4页Journal of Nanchang Institute of Technology

基　　金：江西省教育厅科学技术研究项目(GJJ09368);南昌工程学院青年基金项目(2008KJ019)

摘　　要：数据挖掘技术是目前人工智能领域的研究热点,基于SIS系统中存储的海量数据探讨了一种基于数据挖掘的工况划分方法,经现场检验,此方法可以高效准确地获取电厂正常运行时的各个典型工况,通过机组"实际可达的最优工况"从而设置目标值,达到电厂各种运行工况进行有效划分的目的.Data mining technology has become a very active research focus in the field of artificial intelligence.In this paper,a method of working condition analysis based on data mining and the massive data from SIS is explored.The typical working conditions in the normal operation can be obtained efficiently and accurately by this way.The result illustrates that setting the target value through the actual optimal working conditions can provide the good guidance to the operation and valuable promotion.

关 键 词：数据挖掘 厂级信息监控系统 聚类分析 工况划分 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]