基于无约束非线性优化算法的光强自相关函数拟合

在光子相关光谱(PCS)颗粒测量技术中非线性累积反演方法是一种重要的算法。采用无约束非线性优化算法对反演过程中相关曲线的拟合问题进行了分析和研究, 实现了从任意初始值开始获取最优非线性拟合解, 并给出了算法的实现步骤。采用此方法对50 nm, 100 nm, 200 nm和500 nm的标准聚苯乙烯乳胶颗粒的实测光强自相关函数数据进行了拟合, 并反演了颗粒粒径, 与其他曲线拟合算法相比, 本算法不但对初始值的依赖性小, 而且得到的颗粒粒径更接近乳胶颗粒的标称直径, 测量误差更小。

Fitting of Light Autocorrelation Function Based on Unconstrained Nonlinear Optimization Algorithm

The nonlinear cumulants analysis is an important method in photon correlation spectroscopy (PCS) particle sizing technique. Using unconstrained nonlinear optimization algorithm, optimum fitting result is achieved in the nonlinear fitting process with random original value, and the implementation of the algorithm is presented. Autocorrelation functions of scattered light signal of normal polystyrene latex particles of 50 nm, 100 nm, 200 nm and 500 nm are fitted using this method, and particle sizes are inversed. Comparied with other curve fitting algorithm, this method has little dependence on original value, and the inversed particle sizes are more close to the nominal value with less measurement error.