GA-BP algorithm based prediction of solids circulation rate in a dual fluidized bed with conical gas distributor

CHEN Hongwei; WU Jing; HE Junpeng; LI Yan

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GA-BP algorithm based prediction of solids circulation rate in a dual fluidized bed with conical gas distributor

Thermal Power Generation Vol. 44, Issue 2, Pages: 90-95(2015)

更新时间：2025-09-28

- GA-BP algorithm based prediction of solids circulation rate in a dual fluidized bed with conical gas distributor
- 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：

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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