摘要
在介绍炉温数据的聚类方法的基础上,介绍了快速聚类法的具体步骤。以上海某电厂600MW为例,进行了机组数据聚类参数的分析和比较,得出了比较好的机组参数配额,减少了炉管超温的现象,节约了生产成本。
Based on introduction of clustering methods on boiler＇s temperature data, this paper introduced the steps of quick clustering methods. The 600 MW units＇data of clustering parameter were analysed and compared and obtained a better units quota using a Shanghai Power Plant. Quick clustering methods decreased the appearance of overtemperature on the boiler＇s tubes and saved the manufacturing cost.
出处
《吉林电力》
2005年第6期30-33,共4页
Jilin Electric Power
关键词
超高温
异常变化
聚类方法
水冷壁
overtemperature
abnormal change
clustering method
water-cooled wall
