Abstract：Aiming at the problem that the set of linear equations in the inversion of particle size distribution based on light diffraction was ill-posed, a self-adaptive regularization algorithm which could solve this kind of ill-posed problem effectively was proposed. The self-adaptive regularization algorithm was proposed by studying the inversion accuracy and anti-noise performance of the classical regularization algorithm and a vector similarity algorithm, studying the defects of the two algorithms and combining these two algorithms. The results show that this algorithm can make different treatments for different forms of particle size distributions. When the particle size distribution is narrow,the tiny peak is removed.Smooth treatment is made when the particle size distribution is wide. The accuracy of the inversion is improved. The effectiveness of the proposed algorithm is confirmed by a measurement of standard particles.

Keywords: inversion; particle size distribution; vector similarity; self-adaptive regularization algorithm