节点文献
高炉炉壁侵蚀状态预测的神经网络分析法
THE NEURAL NETWORK METHOD FOR PREDICTING EROSION OF BLAST FURNACE WALL
【摘要】 采用二维简化的炉壁模型 ,用ANSYS软件进行热传导仿真计算 ;同时在MATLSAB环境中建立BP网络模型 ,并利用炉壳外部测点的温度值识别炉壁侵蚀线 ,从而证明了神经网络方法在高炉炉壁侵蚀状态预测中应用的可行性。
【Abstract】 Based on a simple two-dimension blast furnace wall model,the heat exchange status is calculated by ANSYS software.A BP neural network model is made in MATLSAB,The eroding line of blast furnace wall is emulated through the temperature values of the special points in blast furnace shell.The example shows that it is feasible for the neural network method to be used in predicting erosion of blast furnace wall.
【关键词】 高炉侵蚀;
神经网络;
仿真;
热传导;
【Key words】 blast furnace erosion; neural network; emulation; heat exchange;
【Key words】 blast furnace erosion; neural network; emulation; heat exchange;
- 【文献出处】 四川冶金 ,Metallurgy of Sichuan , 编辑部邮箱 ,2004年04期
- 【分类号】TF548
- 【被引频次】4
- 【下载频次】81