求解粒子群粒度分布的改进Projection算法

Improved projection algorithm for measuring distribution of particle sizes

针对在激光粒度分布反演中由于迭代算法的迭代步长选取不当致使反演结果存在严重展宽和拖尾的问题,提出一种调整迭代步长的方法应用于Projection算法来提高测量精度。该方法首先基于测距相似度原理得到光能分布列向量与光能系数矩阵行向量之间的相似度曲线,经滤波和归一化处理后得到被测粒子群的预测粒度分布;然后根据预测粒度分布结果确定迭代步长的大小。使用本文提出的改进Projection算法测量国家标准物质GWB(E)120046的D50误差为-0.6%、D10误差为-1.1%、D90误差为-0.6%,测量GWB(E)120041与GWB(E)120049混合标准物质的光能对数误差为2.167。测量结果表明,该算法可有效地提高算法的抗噪声能力、测量精度和分辨率。

In consideration of the serious size distribution broadening and tailing phenomena come from improper iterative steps in inversing laser particle size distribution, this paper presents a method to select the iterative step for Projection algorithms to improve measurement accuracy. Based on the similarity theory, this method obtains the similarity between the row vector of light energy distribution and the course quantity of light energy coefficient matrix. Then, it gets the predict distribution of particle size after filtering and normalized processing. Furthermore, according to the predicted result, the iteration step can be calculated. The measurement results for national standard particles GWB（E）120046 show that the measuring errors for D50, D10, and D90 are -0.6%, -1.1% and -0.6%, respectively,and the light energy logarithm error of mix standard particles GWB（E）120041 and GWB（E）120049 is 2.167. Results demonstrate that the algorithm can effectively improve noise immunity, measurement accuracy and resolution.