GA-BP algorithm based prediction of solids circulation rate in a dual fluidized bed with conical gas distributor
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GA-BP algorithm based prediction of solids circulation rate in a dual fluidized bed with conical gas distributor
Thermal Power GenerationVol. 44, Issue 2, Pages: 90-95(2015)
作者机构:
华北电力大学电站设备状态监测与控制教育部重点实验室
作者简介:
基金信息:
DOI:
CLC:TK229.66
Published:2015
稿件说明:
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CHEN Hongwei, WU Jing, HE Junpeng, et al. GA-BP algorithm based prediction of solids circulation rate in a dual fluidized bed with conical gas distributor[J]. Thermal power generation, 2015, 44(2): 90-95.
DOI:
CHEN Hongwei, WU Jing, HE Junpeng, et al. GA-BP algorithm based prediction of solids circulation rate in a dual fluidized bed with conical gas distributor[J]. Thermal power generation, 2015, 44(2): 90-95.DOI:
GA-BP algorithm based prediction of solids circulation rate in a dual fluidized bed with conical gas distributor
摘要
为了合理地控制锥形布风板双流化床的颗粒循环流率
在自行搭建的冷态实验台上
研究了一些参数对颗粒循环流率的影响。结果显示
颗粒循环流率分别随着气化室风速、提升管风速、床料重量的增加而增加
随着颗粒粒径的增加而减小
随着锥形布风板角度的增加而增加。建立了GA-BP神经网络模型
利用预测值与实际值的最大相对误差和均方差来评价模型优劣
通过比较
找到了模型的最优参数设置
其预测结果的最大相对误差仅为0.108 7
均方差为0.002 0。
Abstract
In order to control solids circulation rate in dual fluidized bed with conical gas distributor properly
a cold test bench was built up to investigate the influence of several parameters on solids circulation rate.The results show that
the solids circulation rate increased with the gas velocities(to the gasification chamber or the riser)and bed material weight
while decreases with the increasing particle size.It grew with the angle of the conical gas distributor.The GA-BP neural network model was established to predict the circulation rate
and the maximum relative error and mean square error were defined to evaluate the models.By comparison
the optimal parameters of the model were found.The maximum relative error is only 0.108 7and the mean square error is 0.002.
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