多角度动态光散射粒度分布递归非负Phillips-Twomey算法

Besides the advantages such as the fast response speed ,non-contact measurement and so on, the multiangle dynamic light scattering(MDLS) can give better particle-size distribution(PSD) because it can get more information about scattering light which can reflect the characteristic parameter of particles. And the improvement of the accuracy of MDLS depends largely on appropriate PSD inversion methods. Based on Phillips- Twomey algorithm, we proposed the Recursion Nonnegative Phillips-Twomey (RNNPT) algorithm , which use the MR-L-curve to estimate the regularization parameter, recursion algorithm to obtain the weighting coefficients and is added the nonnegative constraint. Through the exact determination of the weighting coefficients, the RNNPT algorithm can improve the accuracy of MDLS PSD inversion algorithm. Measured at the light intensity autocorrelation function noise range is between 0.01% and 1%, the results show that the inverted PSDs of the two unimodal distribution and the bimodal distribution are comparatively desired, while the noise level is under 0.1%. In contrast to Recursion Phillips-Twomey (RPT) and the existing Recursion Tikhonov (RT) algorithm, the results show that the weighting coefficient ratio is minimum and the inverted PSD is closest to theoretical one, which is obtained from RNNPT algorithm.