Measurement of pulverized coal mass flow with double-bend method based on BPNN

ZHAO Yanjun; ZHANG Xu; HUANG Xiaofei

doi:10.19666/j.rlfd.201706057

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Measurement of pulverized coal mass flow with double-bend method based on BPNN

更新时间：2025-09-28

- Measurement of pulverized coal mass flow with double-bend method based on BPNN
- Thermal Power Generation Vol. 47, Issue 2, Pages: 92-96(2018)
- 作者机构：
  
  华北理工大学电气工程学院
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.201706057
  CLC： TB937
- Published Online：31 January 2018，
  
  Published：2018
- 稿件说明：
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ZHAO Yanjun, ZHANG Xu, HUANG Xiaofei. Measurement of pulverized coal mass flow with double-bend method based on BPNN[J]. Thermal power generation, 2018, 47(2): 92-96.
DOI：

ZHAO Yanjun, ZHANG Xu, HUANG Xiaofei. Measurement of pulverized coal mass flow with double-bend method based on BPNN[J]. Thermal power generation, 2018, 47(2): 92-96. DOI： 10.19666/j.rlfd.201706057.

摘要

煤粉质量流量是气力输送煤粉中的一个重要参数

对燃煤热力发电具有重要意义。本文在双弯管法测量的基础上建立了新的数学测量模型

并在煤粉输送实验平台上得到了大量的实验数据。利用人工神经网络强大的非线性逼近能力

在新数学模型下建立了BP神经网络(BPNN)。结果表明

利用BPNN能很好地实现双弯管法煤粉质量流量在线测量

相对误差最大不超过7%

是新的数学模型下的一种很好的测量方法。

Abstract

The mass flow of pulverized coal is an important parameter in its pneumatic conveying

which is of great significance for thermal power generation. In this study

a new mathematical measurement model was established on the basis of double-elbow method. Then

in the experimental platform of pulverized coal transportation

a large amount of experimental data were obtained. By using the powerful nonlinear approximation ability of artificial neural network

BP neural network was established based on the new mathematical model. The results showed that

the BP neural network can well realize the online measurement of the pulverized coal quality in double-pipe method

and the relative error was no more than 7%

which is a good measurement method based on the new mathematical model.

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