摘要
模拟高炉内衬条件 ,利用实验室小型半干法喷补机进行喷补试验 ,测试了喷射压力、喷射距离、配水量和炉温等因素对喷补附着率及喷补层与残衬粘结强度的影响规律。利用模式识别和人工神经网络技术对影响喷补效果的工艺参数进行了优化与预报 ,找到了目标优化区。试验发现适宜的喷补工艺参数为 :喷补料配水量 10 %～ 14 % ;喷射压力 0 .4 MPa;喷射距离 0 .95～ 1.0 5 m;炉温 2 98～ 5 73K。随着炉温的升高 ,配水量应随之适量增加。
The gunning process of blast furnace has been simulated in laboratory. The adhesive ratio and binding strength have been experimentally measured at different gunning pressure, gunning distance, water content and furnace temperature. The pattern recognition and artificial neural network have been employed to analyze the experimental results and the optimized parameters have been worked out. The experimental results show that the optimized gunning parameters are: water content 10 %~14 %, gunning pressure 0.4 MPa, gunning distance 0.95~1.05 m and furnace temperature 298~573 K. As the furnace temperature increases, the water content should be increased too.
出处
《钢铁》
CAS
CSCD
北大核心
2003年第12期9-12,共4页
Iron and Steel
基金
国家自然科学基金资助项目 (批准号 :5 0 1740 2 6)
