基于热波阻抗法建立了多层介质的一维光热模型,从样品表面调制光热信号出发,采用粒子群优化(PSO)算法和总变差(TV)正则化方法对多层介质的热物性予以深度剖面重构。该方法将多层介质离散成一系列厚度相同的虚拟层,并将待重构的热物性深度剖面以粒子表示,再让粒子在解空间进行优化搜索。数值模拟的结果证明了该方法的有效性和实用性,适合用来重构层数未知的多层介质的热导率和热扩散率剖面。对噪声背景下光热信号的重构结果亦证实了算法的稳定性和可靠性。此外,数值结果也表明上述方法可用于热导率和热扩散率深度剖面的同步重构。 Based on the thermo-wave impedance method, a one-dimensional photothermal model of multi-layered media is established. Based on the modulation of light and heat signals on the surface of the sample, particle swarm optimization (PSO) algorithm and TV variation regularization Physical properties of the deep profile reconstruction. In this method, the multi-layered medium is discretized into a series of virtual layers of the same thickness, and the thermal physical depth profile to be reconstructed is represented by particles, and the particles are searched optimally in the solution space. The numerical simulation results show the effectiveness and practicability of the proposed method and are suitable for reconstructing the thermal conductivity and thermal diffusivity profiles of multilayer media with unknown layer number. The reconstructed results of photothermal signals under noise background also confirm the stability and reliability of the algorithm. In addition, numerical results also show that the above method can be used for the simultaneous reconstruction of thermal conductivity and thermal diffusivity depth profiles.