Identification and Quantification of Non-Spherical Particles  

非球形粒子的检测与识别(英文)

作　　者：曾周末[1] 张宝明[1] 杨庆[1] 

机构地区：[1]天津大学精密测试技术与仪器国家重点实验室,天津300072

出　　处：《Transactions of Tianjin University》2002年第2期75-78,共4页天津大学学报（英文版）

基　　金：NationalNaturalScienceFoundationofChina(No.60 1 750 0 3);KeyYoungTeacherFundofEducationMinistryofChina

摘　　要：In commercial applications of phase Doppler anemometry (PDA), the effectiveness of non sphericity of particles is present and the response of PDA system deviates from the theoretical prediction. In this paper, the statistic characteristics of PDA signal related to irregular particles is analyzed and a method of statistic classification of irregular particles is proposed.It proves that the parameter of PDA signal for irregular particles is an unbiased estimation for spherical ones, the mean of the phase difference is in direct proportion to the mean diameter of particles and the standard deviation of the phase difference increases linearly with the standard deviation of irregular particles. As an application of the identification of irregular objects, fuzzy patterns and similarities of haemocytes are used to recognize and quantify cell samples.The statistic classification of particles is more significant in practice.激光相位多普勒技术 (PDA)是目前公认有效的多参数粒子测量技术之一 ,但是PDA对粒子的非球形特性极为敏感 .本文分析了粒子的非球形特性对PDA的影响 ,明确了PDA信号参数与粒子非球形特性的关系 ,表明非球形粒子条件下的PDA信号相位差是理想粒子条件下PDA信号相位差的无偏估计 .提出了基于对象分类识别的非球形粒子的检测方法 ,利用模糊模式识别中的群体识别技术 ,计算对象特性与参照物特性的贴近度 ,根据择近原则判断对象的类别及数量 .实验表明 。

关 键 词：particle measurement phase Doppler anemometry statistic classification pattern recognition 

分 类 号：O235[理学—运筹学与控制论]