基于多尺度变换的动态光散射粒径反演范围的自适应调整

Self-adaptive adjustment of inverse range of dynamic light scattering particle sizing based on multi-scale transform

通过多尺度变换实现了反演范围的自适应调整,使其更接近真实范围。分别采用反演范围固定算法与自适应算法对200～600 nm单峰和200～900 nm双峰分布颗粒的模拟相关函数进行了反演,结果表明:自适应算法的结果更接近理论分布,抗干扰能力更强。相对于固定算法,单峰分布颗粒最多可缩小峰值误差4.73%,缩小峰宽误差185 nm。双峰分布颗粒在0～0.001噪声水平时,峰值误差分别小于11.33%,12.45%,峰宽误差分别小于35,160 nm,而固定算法在噪声水平大于0.000 1时,难以得到合理的反演结果。反演范围自适应调整方法能够有效优化粒径反演结果。

In dynamic light scattering particle sizing, the inverse range can be self-adapted closer to the true range by multi-scale transform. The simulative autocorrelation functions(ACFs) of unimodal size distribution particles of 200~600 nm and bimodal size distribution particles of 200~900 nm were inversed by the inverse range fixed and self-adaptive algorithms. Compared to the fixed algorithm, the self-adaptive algorithm is more precise and noise-tolerant. For unimodal distribution particles, it can reduce peak value error by 4.73% and peak width error by 185 nm at most. For bimodal distribution particles, when the noise level is 0~0.001, its peak value errors are less than by 11.33%, by 12.45%, and its peak width errors are less than 35 nm, 160 nm. While, the fixed algorithm cannot get reasonable results when the noise level is greater than 0.0001. Therefore, this self-adaptive adjustment method of inverse range can effectively optimize the inverse results.