用反演迭代算法提高粉体粒径分段沉降测量精度

Improvement of Measurement Precision for Particle Subsection Sedimentation by Inversion Iterative Algorithm

摘要: 为了减小分段沉降法在测量粉体粒径中的误差,采用Chahine算法进行反演,并用硼酸锌粉体进行了验证性试验.结果表明:Chahine算法经过预处理改进后,所得粒径分布与自然沉降法所测结果相比,误差最大值为5.9%,平均误差为1.9%;验证试验最大误差为5.02%,平均误差为2.03%,说明该算法能很好地应用于分段沉降测量的反演过程中.

Abstract: Chahine algorithm was used to minish the error in measurement of subsection sedimentation.The results show that compared with the distribution of natural sedimentation,the maximal error of distribution after improving the algorithm was 5.9%,and the average error was 1.9%.The results of another test for validating the non-chanciness show that the maximal error was 5.02%,and the average error was 2.03%.These indicated that the Chahine algorithm can primely be used in the inversion process of subsection sedimentation.