冷凝器污垢的灰色预测  

Gray theory based prediction for condenser fouling

作　　者：樊绍胜[1] 

机构地区：[1]长沙理工大学电气与信息工程学院,湖南长沙410076

出　　处：《电力科学与技术学报》2007年第2期12-15,共4页Journal of Electric Power Science And Technology

基　　金：湖南省自然科学基金资助项目(06JJ2011)

摘　　要：提出一种基于灰色理论的冷凝器污垢预测方法.将污垢分解为软垢和硬垢两部分,并采用灰色模型分别描述其变化趋势,进而通过二者的结合获得较为精确的污垢预测.试验结果表明:该方法能够有效地预测冷凝器的周期性结垢现象,并能适应冷凝器工况参数的动态变化,取得比常规渐近模型更好的预测精度.A novel gray theory based prediction method for condenser fouling is proposed in this paper. The overall fouling is separated into two parts： hard fouling and soft fouling. Their variation trends are approximated by two gray models respectively. And a more accurate prediction is developed by synthesizing the two gray models outputs. Condenser testing results show that the method can predict the periodic fouling effectively, and it can be applied in the conditions with condenser parameters dynamically varying. It can achieve more accurate fouling prediction than traditional asymptotic fouling model.

关 键 词：冷凝器 污垢预测 周期性结垢 灰色模型 

分 类 号：TK268[动力工程及工程热物理—动力机械及工程] TP212.9[自动化与计算机技术—检测技术与自动化装置]