基于神经网络理论的煤调湿系统建模与控制
关键词： 煤调湿；神经网络；自动控制
The modeling and control of CMC system based on Neural Network theory
Abstract：The CMC technology relys both directly and indirectly on heating to make the moisture of furnace coal decrease, and controls stability. Baosteel has built the craft workshop related to CMC technology using the second generation technology of coal , and the craft makes a significant impact on energy costs in 2008. Then this article emphasizes on the analysis of the system, such as theory based on the heat balance analysis and the heat balance model. By collecting and recording running parameters, the data of the system is statistically analyzed, and it found that the main factors that affect the steam volume were the coal quantity, outlet exhaust gas temperature of coal dryer, inlet humidity caudal temperature and entrance of coal moisture. And through data analyzing, this research uses the artificial neural network to model the system. After establishing the preliminary model, the research established the preliminary model of the moisture control which is rather approximate to the practice and the theory based on the parameters, which were obtained by data packet, the Latin square design of experiment and the selections of the threshold parameter. And on this basis, the research has raised a new hypothesis of the different situations when the moisture of export coal in different values. In summary, this research uses the artificial neural network to establish the moisture control model of coal which achieves the automatic control. Through experiment, finding the method can reduce about 3kg/h/t of the unit consumption of steam a compared with manual operation.
KeyWords : the CMC technology; artificial neural network; automatic control
目录
1. 绪论 1
1.1. 煤料水分控制系统的作用 1
1.2. 煤调湿的国内外研究现状 2
1.2.1. 国外煤调湿技术的发展 2
1.2.2. 我国煤调湿技术的发展 4
1.2.3. 宝钢煤料水分控制系统的现状 5
1.2.4. 目前遇到的问题 8
1.3. 研究内容 8
1.4. 技术路线 8
2. 热平衡计算 10
2.1. 宝钢煤调湿工艺校企合作前期积累 10
2.1.1. 环境参数 10
2.1.2. 操作参数 10
2.2. 本次针对煤调湿控制系统提出热平衡计算原理 15
2.3. 煤调湿处理的热量衡算 16
2.4. 热平衡方法分析 17
3. CMC的神经网络建模 19