Key Laboratory of Photoelectric Measurement & Control and Optical Information Transfer Technology, Changchun University of Science and Technology, 7089 Weixing Road, Changchun 130022, China.
Opt Lett. 2013 Jun 1;38(11):1757-9. doi: 10.1364/OL.38.001757.
Conventional methods for estimating particle size distribution (PSD) based on the computed field autocorrelation function (ACF) of dynamic light scattering data are prone to baseline error and random measurement errors. To reduce the effects of the errors efficiently and automatically, we propose a penalized nonlinear nonnegative least squares (NNLS) method based on the measured photon ACF that simultaneously determines the PSD and the unknown baseline. In simulations and experiments, the proposed method was able to estimate the PSD more accurately than the existing NNLS method using the computed field ACF.
基于动态光散射数据的计算域自相关函数(ACF)来估算颗粒粒径分布(PSD)的传统方法容易受到基线误差和随机测量误差的影响。为了有效且自动地降低误差的影响,我们提出了一种基于测量光子 ACF 的惩罚非线性非负最小二乘法(NNLS)方法,该方法同时确定 PSD 和未知基线。在模拟和实验中,与使用计算域 ACF 的现有 NNLS 方法相比,所提出的方法能够更准确地估计 PSD。