A class of mathematical model of heat conduction inverse problem is given. A new robust solving method to determine the phase change interface in inverse heat conduction problem is developed. By using PSO optimizating, the author studies the parameter optimization of adaptive particle swarm in a kind of inverse heat conduction problem on the ground of basic PSO,and the largest number of particles,particle movement speed and acceleration coefficient values are studied. The results show that in the soluting inverse heat conduction problem optimization question,PSO algorithm performs well in accuracy and speed .%给出了一类热传导反问题的数学模型，并采用粒子群优化算法对该热传导反问题进行了相变界面位置的反演求解。在标准PSO的基础上，研究了基于自适应PSO的热传导反问题的参数优化方法，并对粒子群优化算法中粒子数、粒子最大移动速度和加速系数的取值进行了讨论。仿真结果表明：在热传导反问题的优化求解中，PSO算法具有较高的精度和较好的收敛速度。
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