节点文献
基于BP神经网络固相流量的在线检测
Measurement of Solid-phase Mass Flow Rate of Two-phase Flow by Using Neural Networks Method
【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。
【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.
【关键词】 气固两相流;
在线测量;
神经网络;
BP算法;
【Key words】 gas-solid two-phase flow; on-line measurement; neural networks; BP algorithm;
【Key words】 gas-solid two-phase flow; on-line measurement; neural networks; BP algorithm;
- 【文献出处】 计算机测量与控制 ,Computer Automated Measurement & Control , 编辑部邮箱 ,2005年05期
- 【分类号】TP274.4
- 【被引频次】13
- 【下载频次】131