摘要
冷却壁工作过程中的温度高低直接影响其使用寿命。以铸钢冷却壁的传热为研究对象,根据热态试验结果,提出简化传热关系式,并将其与神经网络技术相结合,形成冷却壁热面温度预测仿真模型。与试验值相比,仿真输出值的最大相对误差不足2%,说明这种智能模型准确、可靠。同时采用的研究方法在冷却壁的研究中具有参考价值。
Temperature of cooling stave under working condition directly affects stave campaign life. Heat transfer of cast steel cooling stave is the research object, and simplified heat transfer formula is proposed based on thermal state test results. Then the simplified mode is combined with artificial neural network to form a prediction model of cooling stave hot surface temperature. Maximum relative error of simulation outputs compared with experiment data is less than 2%, indicating that such an intelligent model is accurate and reliable. In addition, the research method of this paper is quoteworthy for research on cooling stave.
出处
《钢铁研究学报》
CAS
CSCD
北大核心
2007年第5期103-106,共4页
Journal of Iron and Steel Research
关键词
冷却壁
传热
热面温度
神经网络
智能仿真
cooling stave
heat transfer
hot surface temperature
neural network
intelligent simulation
