基于模拟退火的火灾烟颗粒粒径反演

Inversion of Size Distribution of Fire Smoke Particles Based on Simulated Annealing

火灾烟颗粒粒径分布的反演是一个典型的病态问题,容易因为陷入局部最小值而丢失全局最优解。在详细分析了随机噪声对烟颗粒群光散射Mueller矩阵元随角度分布的影响之后,采用全局搜索能力很强的模拟退火算法,实现了对球形模型下单分散系和对数正态分布系的粒径反演,在有相对强度为信号最大值3%的随机噪声干扰下,反演结果的误差都小于0.3%。然后使用该反演程序对烟颗粒分形凝团的散射光数据进行反演,得出了不同分形维数的火灾烟颗粒分形凝团在球形模型下的光学等效半径,并且火灾烟颗粒分形凝团的回转半径与光学等效半径之间具有近似线性关系。

Inversion of the size distribution of fire smoke particles is an ill-conditioning problem, and it tends to lose global optimal solutions on account of being trapped into local minimum. Under spherical model, the inversion of monodisperse systems and lognormal distribution systems have been performed by simulated annealing algorithm which has a powerful ability in global searching. Before that, the interference of random noise on the angular distribution of Mueller matrixs in the light scattering of fire smoke particles has been analyzed in detail. Errors of inversional results are less than 0.3% when signal mixed with 3% stochastic noise. Then, the optical equivalent radius of smoke particle clusters with different fractal dimensions could be calculated when the program is used to fit the scattering light of the clusters. Furthermore, it has an approximatively linear relationship with radius of gyration of the clusters.