Improved projection algorithm for measuring distribution of particle sizes

GE Bao-zhen; MA Yun-feng; WEI Yao-lin

doi:10.3788/OPE.20122001.0197

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Improved projection algorithm for measuring distribution of particle sizes

Article | 更新时间：2020-08-12

- Improved projection algorithm for measuring distribution of particle sizes
- Optics and Precision Engineering Vol. 20, Issue 1, Pages: 197-203(2012)
- 作者机构：
  
  天津大学精密仪器与光电子工程学院光电信息技术教育部重点实验室天津,300072
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20122001.0197
  CLC： TP391.4
- Received：14 April 2011，
  
  Revised：30 July 2011，
  
  Published Online：25 January 2012，
  
  Published：25 January 2012
- 稿件说明：
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葛宝臻, 马云峰, 魏耀林. 求解粒子群粒度分布的改进Projection算法[J]. 光学精密工程, 2012,20(1): 197-203

GE Bao-zhen, MA Yun-feng, WEI Yao-lin. Improved projection algorithm for measuring distribution of particle sizes[J]. Editorial Office of Optics and Precision Engineering, 2012,20(1): 197-203
葛宝臻, 马云峰, 魏耀林. 求解粒子群粒度分布的改进Projection算法[J]. 光学精密工程, 2012,20(1): 197-203 DOI： 10.3788/OPE.20122001.0197.

GE Bao-zhen, MA Yun-feng, WEI Yao-lin. Improved projection algorithm for measuring distribution of particle sizes[J]. Editorial Office of Optics and Precision Engineering, 2012,20(1): 197-203 DOI： 10.3788/OPE.20122001.0197.

摘要

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。

Abstract

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.

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references

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