半干法烟气脱硫工艺中绝热饱和温差的软测量  

Research on soft-sensing of approach to adiabatic saturation temperature in semi-dry flue gas desulfurization process

作　　者：范丽婷[1] 李鸿儒[2] 王福利[2] 何大阔[1] 

机构地区：[1]东北大学流程工业综合自动化教育部重点实验室,沈阳110004 [2]东北大学信息科学与工程学院,沈阳110004

出　　处：《仪器仪表学报》2009年第7期1384-1389,共6页Chinese Journal of Scientific Instrument

基　　金：国家自然科学基金(60674063);辽宁省自然科学基金(20062024)资助项目

摘　　要：针对半干法烟气脱硫工艺中绝热饱和温差的测量难题,提出一种基于混合策略的绝热饱和温差软测量模型,该混合策略既考虑了绝热增湿降温过程的机理,同时又利用了相关的过程数据信息。在分析烟气绝热增湿降温机理的基础上,指出实际工业过程中原有测量方案存在的不足,增加出口烟气湿度作为辅助变量以提高绝热饱和温差的估计精度,为克服湿度不易测量的问题,采用RBF人工神经网络作为湿度估计器。仿真结果分析表明,与工业脱硫过程的原有方案相比,基于混合策略的软测量模型的精度有很大提高,只需在脱硫塔入口安装湿度传感器即可比较准确地的估计出绝热饱和温差,保证脱硫系统高效安全稳定运行。A soft-sensing hybrid model is presented to solve the on-line measurement problem of approach to adiabatic saturation temperature in the semi-dry flue gas desulfurization process. The hybrid strategy combines the physical knowledge with the data information of the desulfurization process. Based on the analysis of the adiabatic humidification process, the inaccuracy of traditional measurement is pointed out, and the flue gas humidity at outlet is selected as the secondary variable to improve the estimation accuracy. An RBF artificial neural network is proposed as the humidity estimator because humidity is not easy to measure accurately under high particle concentration condition. Simulation result shows that the estimation accuracy is greatly improved compared with those using traditional methods. Just installing a humidity sensor at inlet will ensure the desulfurizaiton equipment running efficiently and safely.

关 键 词：半干法 烟气脱硫 绝热饱和温差 软测量 

分 类 号：TK221[动力工程及工程热物理—动力机械及工程]