基于SPSO算法的粒子群粒径分布反演

Particles Size Distribution Inversion Based on Stochastic Particle Swarm Optimization Algorithm

针对粒径分布反演传统算法收敛精度不高、易陷入局部最优的缺点,根据粒子群的激光透射模型,提出一种基于随机微粒群算法(SPSO)反演粒子系粒径分布的快速有效方法,对于非独立模式下的R-R分布、正态分布、对数正态分布等粒子粒径分布情况进行了反演计算,获得了合理的粒径分布。该方法概念简单,易于编程实现,同时对优化目标函数无需连续、可微等苛刻的条件,具有较强的鲁棒性和适应性,提高了粒径分布反演的可靠性和灵敏性。

To resolve the problems that the traditional algorithm of particle size distribution inversion has no good convergence accuracy and is apt to be trapped in local optima, a stochastic particle swarm optimizer（SPSO） algorithm, which is based on laser transmitting model,is proposed to estimate the size distribution of particles. The novel SPSO- based method is proved to be available to retrieve the reasonable particle size distribution such as R-R distribution, normal distribution and lognormal distribution for the independent model. The algorithm is simple, easy to implement and unnecessary the optimization objective function＇s continuity and differentiability. Additionally, It has strong robustness and adaptation to improve the reliability and sensitivity of the inversion of particle size distribution.