热力发电2018，Vol.47Issue(2)：56-62,7.DOI:10.19666/j.rlfd.201705042
双循环流化床颗粒循环流率实验研究
Experimental study on particle circulating rate of double-circulating fluidized bed
摘要
Abstract
In order to realize reasonable control of particle circulating flow rate,the effects of control parameters on circulating flow rate were analyzed on a self-built double-circulating fluidized bed cold system,such as the wind speed of the bubbling bed,total wind speed and air distribution ratio of the fast bed,static bed height of the bubling bed,and the average particle size.Moreover,on the basis of three different weight optimization algorithms,like the additional momentum method,Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA),the BP neural network model was established,and the errors between the model predicted values and experimental values were compared.The results show that,the particle circulating flow rate was less influenced by the wind speed in bubbling bed,it increased with the primary air ratio and total wind speed of the fast bed and the static height of the bubling bed,but decreased with the increasing average particle size.The average error between the test sample and the one predicted by the GA-optimized BP neural network was 0.436 5％,the standard deviation was 0.064 1.The predicted values agreed well with the experimental values,indicating the BP neural network model was suitable.关键词
双循环流化床/循环流率/控制参数/权值优化/BP神经网络模型/遗传算法/AM算法/LM算法Key words
double-circulating fluidized bed/flow rate of particles/control parameters/weight optimization/BP neural network model/genetic algorithm/AM algorithm/LM algorithm分类
能源科技引用本文复制引用
陈鸿伟,杨新,贾建东,麻哲瑞,赵振虎,孙超..双循环流化床颗粒循环流率实验研究[J].热力发电,2018,47(2):56-62,7.基金项目
河北省青年基金项目(QN2016204)Youth Foundation of Hebei Province (QN2016204) （QN2016204）
