基于支持向量回归的温度场数值分析

Numerical Analysis on Temperature Field Based on Support Vector Regression

为深入分析并提取温度场的参数化特征,提出一种基于支持向量回归的温度场数值分析方法。首先利用常用的有限元分析方法建立被研究对象的温度场模型,进而抽取模型节点及温度信息数据;然后,对被研究的结构进行特征分区,并据此确定分析的敏感方向;最后借助支持向量回归方法对各分区数据进行分片回归分析,并提取温度场的参数化特征信息,获得对被研究对象整体传热性能的综合定量评价。对换热器冷却栅的仿真分析结果证明了该方法的有效性,也显示了它在过程自动化控制以及机械结构优化设计等方面具有较大的应用潜力。

To analyze and extract feature parameters of a temperature field,a support vector regression based numerical analysis method is proposed.First,the temperature field of a studied object is modeled by the finite element analysis（FEA）.Furthermore,position and temperature of every node are extracted.Then,the studied object is divided into several feature areas,by which a sensitive direction to be analyzed is determined.Finally,the support vector regression is repeatedly implemented on every feature area,and its feature coefficients are extracted.Consequently,a all-round quantitative evaluation on the heat transfer performance of the studied object is presented.In order to verify the method,a simulated analysis is made on the cooling grid of a heat exchanger.The result indicates that the proposed method is effective in numerical representing a complex temperature field,which implies its great potential in many fields such as industry process automatic control and mechanical structure optimal design,etc.