| 基于神经网络的热带层流基本热流密度的计算 |
| |
| 引用本文： | 韩斌,彭良贵,王国栋,刘相华,焦景民,佘广夫,张中平. 基于神经网络的热带层流基本热流密度的计算[J]. 钢铁, 2004, 39(3): 29-33,42 |
| |
| 作者姓名： | 韩斌 彭良贵 王国栋 刘相华 焦景民 佘广夫 张中平 |
| |
| 作者单位： | 1. 轧制技术及连轧自动化国家重点实验室,东北大学,沈阳,110004
2. 攀枝花钢铁(集团)公司热轧厂,攀枝花,617062 |
| |
| 基金项目： | 国家自然科学基金资助项目 (5 0 10 40 0 4 |
| |
| 摘 要： | 利用现场的数据，采用BP神经元网络预报热连轧层流水冷区集管组内的基本热流密度，将预报的结果用于上、下集管组的热流密度的数学模型计算，进而优化层冷集管组的水冷温降计算数学模型的精度。将结果与采用多元回归方法所得到的结果作比较，表明采用BP神经元网络计算基本热流密度的精度要高于多元回归方法的计算精度，卷取温度的计算值与实测值的标准差比解析回归方法减少了近20％，说明该方法具有良好的在线应用前景。
|
| 关 键 词： | 热轧带钢 层流冷却 卷取温度 热流密度 数学模型 多元回归 BP神经网络 |
CALCULATION OF BASIC HEAT-FLUX DENSITY FOR HOT STRIP LAMINAR-COOLING SYSTEM USING ARTIFICIAL NEURAL NETWORKS |
| |
| HAN Bin ,PENG Lianggui ,WANG Guodong ,LIU Xianghua ,JIAO Jingmin ,SHE Guangfu ,ZHANG Zhongping. CALCULATION OF BASIC HEAT-FLUX DENSITY FOR HOT STRIP LAMINAR-COOLING SYSTEM USING ARTIFICIAL NEURAL NETWORKS[J]. Iron & Steel, 2004, 39(3): 29-33,42 |
| |
| Authors: | HAN Bin PENG Lianggui WANG Guodong LIU Xianghua JIAO Jingmin SHE Guangfu ZHANG Zhongping |
| |
| Affiliation: | HAN Bin 1,PENG Lianggui 1,WANG Guodong 1,LIU Xianghua 1,JIAO Jingmin 2,SHE Guangfu 2,ZHANG Zhongping 2 |
| |
| Abstract: | By use of BP neural networks the basic heat-flux density for laminar cooling system of hot strip mills was predicted on the basis of measured date,the result was then applied to calculate the top and bottom heat-flux density for cooling banks to improve the precision of calculation of temperature drop in each bank.In the mean time the basic heat-flux density was calculated by using traditional linear analytical regression program.The results showed that the calculation precision of neural networks is higher than that of analytical method,The standard deviation between the predicted and measured coiling temperature was reduced about 20 %. |
| |
| Keywords: | laminar cooling coiling temperature basic heat-flux density mathematical model analytical regression BP neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
