基于红外技术的人体异常热源的探测研究

Thermal Detection of Abnormal Heat Source Inside Body based on Infrared Technology

采用红外测温技术及改进蚁群算法求解导热反问题中的内热源强度及表面换热系数。通过建立含有内热源的二维稳态导热反问题实验模型,用红外热像仪测量试件的表面温度,并选用若干点温度作为求解反问题的补充条件,来反演热源强度及表面换热系数,并讨论了测点布置方式对反演结果的影响。计算结果表明:采用红外热像仪测温,结合改进蚁群算法可准确地对热源强度和表面换热系数进行反演识别。在整个边界上均匀布置测点的个数越多,则反演时计算步数越少,反演结果越精确;在测点个数相同时,在整个边界上均匀布置测点比在部分边界上均匀布置测点,更容易反演计算出准确的结果。

To search the intensity of heat source and convective heat transfer coefficient in IHCP adopting experiment and Ant colony algorithm. A two-dimensional steady-state heat conduction model with internal heat source was established,the experimental measuring point temperature,which was measured from the surface temperature by infrared camera,was combined with the Ant colony algorithm to inversely calculat the heat source information. The influence of different arrangement of measuring points was also discussed. The results indicated that using thermal infrared imager measuring temperature with the Ant colony algorithm could effectively identify the intensity of heat source and convective heat transfer coefficient. The more number of measuring point on the boundary was,the steps in inverse problem calculation was less,the inversion results were more accurate. Under the condition of the same number of measuring points,measuring points on the whole border points makes it easier for the inverse problem of thermal conductivity inversion to calculate the accurate results than on the part of the border.