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
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摘要: 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。Abstract: 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 selfadaptive 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 reason
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