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基于BP神经网络固相流量的在线检测
引用本文:潘笑,韩伟.基于BP神经网络固相流量的在线检测[J].计算机测量与控制,2005,13(5):431-433.
作者姓名:潘笑  韩伟
作者单位:武汉大学,动机学院自动化系,湖北,武汉,430072;武汉大学,动机学院自动化系,湖北,武汉,430072
摘    要:气固两相流中固相流量的在线测量对气固两相流工业过程的检测和控制具有重要的意义。现以电厂煤粉气力输送的气固两相流中煤粉质量的在线测量为背景,提出基于神经网络的固相质量流量的测量方案,并对使用的BP算法进行几点改进。最后实验结果表明,这种基于神经网络的固相质量流量测量方案是行之有效的,并且具有简单易行和普遍适用的特点。

关 键 词:气固两相流  在线测量  神经网络  BP算法
文章编号:1671-4598(2005)05-0431-03
修稿时间:2004年11月12

Measurement of Solid-phase Mass Flow Rate of Two-phase Flow by Using Neural Networks Method
Pan Xiao,Han Wei.Measurement of Solid-phase Mass Flow Rate of Two-phase Flow by Using Neural Networks Method[J].Computer Measurement & Control,2005,13(5):431-433.
Authors:Pan Xiao  Han Wei
Abstract:On-line measurement of solid-phase mass has important meaning while measuring and controlling to the industrial process involving in gas-solid two-phase flow. This paper is based on the on-line measurement of coal quality while moved by gas, and proposes the plans that do it utilizing neural networks. Meanwhile, it has also improved the BP Algorithm. The result of artificial experiment shows that this plan is effectual and has easy and generally suitable characteristics.
Keywords:gas-solid two-phase flow  on-line measurement  neural networks  BP algorithm
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