激光粒度仪自适应算法研究
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摘要
基于衍射原理的激光粒度仪是在颗粒测量领域应用最为广泛的仪器之一。在激光粒度测试中,反演算法各有其适用条件和适用范围,对于不同粒径和粒度分布宽度的粒子群进行反演,求解结果可能出现较大偏差。本文在研究不同粒子群光能分布特点的基础上,使用相似度原理预测了粒子群的粒度分布,并根据预测结果自适应选取步长调整因子,将得到的最优步长调整因子应用于Projection算法求解粒子群粒度分布。
本文的主要工作及创新性如下:
1、在分析粒子群的粒径、分布宽度及混合粒子群与光能分布关系的基础上,借鉴基于测距相似度原理的粒度分布预测方法,预测粒子群的粒度分布。
2、在分析基于Projection算法的几种反演方法优缺点的基础上,提出根据粒子群的预测粒度分布计算步长调整因子的自适应Projection算法,并对该算法的收敛阈值的选取进行了讨论。
3、采用自适应Projection算法对标准粒子板和国家标准物质进行测量实验,并与已有的改进下降因子的Projection算法、引入渐变下降因子的Projection算法的实验结果进行了比对。通过对实验结果的分析,验证了自适应Projection算法的有效性。
Laser particle sizer which based on the principle of laser diffraction is one of the most widely used in particle size measurement.In laser particle size analyzing,each algorithm has its inversion condition and application scope.The results may have been solved deviation when measuring different size and different width of the particles.According to the characteristics of particle light distribution,this paper has used of similarity theory to predict the distribution of particle size.The adaptive step adjustment coefficient has been calculated based on the predicted distribution which will be used in Projection algorithm to measure the distribution of particle size.
Main work and innovation are as follows:
1. This paper has researched the relationship of particle size, particle width and hybrid particle to the light distribution .Using a method to predict the distribution of particle size which based on similatity.
2. Research the advantages and disadvantages of Projection algorithm and some other non-mode inversion algorithms which based on Projection algorithm. The adaptive Projection algorithm which calculate the step adjustment coefficient based on the predicted distribution has been proposed. Finally, the algorithm threshold for convergence is discussed.
3. Using adaptive Projection algorithm to measure the standard particle board and national standard material, compared the result with improved Projection algorithm which introducing an increasing fine coefficient and Projection algorithm which introducing an improved fall coefficient. The results show that the adaptive Projection algorithm is effective.
本文的主要工作及创新性如下:
1、在分析粒子群的粒径、分布宽度及混合粒子群与光能分布关系的基础上,借鉴基于测距相似度原理的粒度分布预测方法,预测粒子群的粒度分布。
2、在分析基于Projection算法的几种反演方法优缺点的基础上,提出根据粒子群的预测粒度分布计算步长调整因子的自适应Projection算法,并对该算法的收敛阈值的选取进行了讨论。
3、采用自适应Projection算法对标准粒子板和国家标准物质进行测量实验,并与已有的改进下降因子的Projection算法、引入渐变下降因子的Projection算法的实验结果进行了比对。通过对实验结果的分析,验证了自适应Projection算法的有效性。
Laser particle sizer which based on the principle of laser diffraction is one of the most widely used in particle size measurement.In laser particle size analyzing,each algorithm has its inversion condition and application scope.The results may have been solved deviation when measuring different size and different width of the particles.According to the characteristics of particle light distribution,this paper has used of similarity theory to predict the distribution of particle size.The adaptive step adjustment coefficient has been calculated based on the predicted distribution which will be used in Projection algorithm to measure the distribution of particle size.
Main work and innovation are as follows:
1. This paper has researched the relationship of particle size, particle width and hybrid particle to the light distribution .Using a method to predict the distribution of particle size which based on similatity.
2. Research the advantages and disadvantages of Projection algorithm and some other non-mode inversion algorithms which based on Projection algorithm. The adaptive Projection algorithm which calculate the step adjustment coefficient based on the predicted distribution has been proposed. Finally, the algorithm threshold for convergence is discussed.
3. Using adaptive Projection algorithm to measure the standard particle board and national standard material, compared the result with improved Projection algorithm which introducing an increasing fine coefficient and Projection algorithm which introducing an improved fall coefficient. The results show that the adaptive Projection algorithm is effective.
引文
[1]郁可,粉体粒度分布的分形研究,材料科学与工程,1995,1( 13):30~34
[2]周臻,刘亮,王艳玲,煤粉粒径对燃烧特性影响的试验研究,热力发电,2007,1(3),35~39
[3] Roland Hütt1, Hochleistungsbeton-Beispiel S urerest-enz, BFT, 2000,(1):52~60
[4]黄宁,周湘玲,张永刚,粒度测试及激光衍射粒度测试法在涂料工业中的应用,涂料工业,2006,36(9): 43~46
[5] Lee M. Nagao, Svetlana Lyapustina, Melinda K. Munos, et al., Aspects of particle science and regulation in pharmaceutical inhalation drug products, Crystal Growth & Design, 2005,5(6): 2261-2267
[6]邓东,周华,杨华勇,舰船用高压单相流细水雾灭火系统,工兵学报,2006,27(4): 716~720
[7]管建,陈霞,杨洋,测试装置对冶金喷嘴压力一流量特性测量的影响及分析,中国计量,2007,2(4) : 78~79
[8]王乃宁,颗粒粒径的光学测量技术及应用,北京:原子能出版社,2000
[9] Swithenbank J, Beer J M, Taylor D S, A laser diagnostic technique for the measurement of droplet and particle size distribution, Prog. Astronaut. Aeronaut, 1977, 53: 421~447
[10]马尔文MS2000激光粒度分析仪使用手册,郑州:黄河水利出版社,2001
[11]岛津SALD-7101型激光粒度分析仪使用手册,郑州:黄河水利出版社,2001
[12]栾志超,激光粒度仪的无模式数据处理算法研究,硕士论文,天津;天津大学,2005
[13]魏永杰,基于组合频谱技术的激光粒度仪研制,博士论文,天津;天津大学,2008
[14]李文超,激光粒度仪自动对中系统研制,硕士论文,天津;天津大学,2009
[15]王素华,颗粒粒径分布光散射问题的迭代正则化算法,硕士论文,天津;河北工业大学,2007
[16]尹吉婷,基于颗粒粒度极值分布函数的遗传反演算法的研究,硕士论文,南京;南京理工大学,2005
[17]韩一平,光散射法测量颗粒尺寸和浓度的实验研究,硕士论文,西安;西安电子科技大学,2007
[18]周雯,基于shifrin变换反演粒度分布的理论分析,光散射学报,2007,19(3):236~241
[19] M. T. Chahine, Determination of the Temperature profile in an atmosphere from its outgoing radiance, J. Opt. Soc. Am., 1968.1634~1637
[20]王清华,光散射法颗粒大小与形状分析,博士论文,南京;南京工业大学,2003
[21] B. L. Phillips, A Technique for the numerical solution of certain integral equations of the first kind, J. Assoc. Comput. Mach., 1962, 9: 84~97
[22] S. Twomey, On the numerical solution of Fredholm integral equations of the first kind by the inversion of linear system produced by quadrature, J. Assoc. Comput. Mach., 1963,10: 97~101
[23]王燕民,陈琪星,潘志东,激光粒度测量的综合反演及参数选择,2009,17(9):2120~2127
[24]梁国标,王燕民,李新衡,由Mie散射光强反演颗粒粒度分布的一种改进正则化法,光电工程,2006,33(12):44~49
[25]喻雷寿,杨冠玲,何振江,颗粒粒径测量中约束正则CONTN算法分析,激光生物学报,2007,16(1): 74~78
[26]张宇、刘雨东,计钊,向量相似度测度方法,声学技术,2009,28(4):532~536
[27]李中,苑津莎,杨宏,一种向量间相似度的计算方法,华北电力大学,专利号: 200910073836,2009
[28]王建萍,激光粒度测试系统的模块化研究,博士论文,天津;天津大学,1999
[29] Francisco Pedocchi,Marcelo H.Garcia, Noise-resolution trade-off in projection algorithms for laser diffraction particle sizing, APPLIED OPTICS,2006,45(15),3620~3628
[2]周臻,刘亮,王艳玲,煤粉粒径对燃烧特性影响的试验研究,热力发电,2007,1(3),35~39
[3] Roland Hütt1, Hochleistungsbeton-Beispiel S urerest-enz, BFT, 2000,(1):52~60
[4]黄宁,周湘玲,张永刚,粒度测试及激光衍射粒度测试法在涂料工业中的应用,涂料工业,2006,36(9): 43~46
[5] Lee M. Nagao, Svetlana Lyapustina, Melinda K. Munos, et al., Aspects of particle science and regulation in pharmaceutical inhalation drug products, Crystal Growth & Design, 2005,5(6): 2261-2267
[6]邓东,周华,杨华勇,舰船用高压单相流细水雾灭火系统,工兵学报,2006,27(4): 716~720
[7]管建,陈霞,杨洋,测试装置对冶金喷嘴压力一流量特性测量的影响及分析,中国计量,2007,2(4) : 78~79
[8]王乃宁,颗粒粒径的光学测量技术及应用,北京:原子能出版社,2000
[9] Swithenbank J, Beer J M, Taylor D S, A laser diagnostic technique for the measurement of droplet and particle size distribution, Prog. Astronaut. Aeronaut, 1977, 53: 421~447
[10]马尔文MS2000激光粒度分析仪使用手册,郑州:黄河水利出版社,2001
[11]岛津SALD-7101型激光粒度分析仪使用手册,郑州:黄河水利出版社,2001
[12]栾志超,激光粒度仪的无模式数据处理算法研究,硕士论文,天津;天津大学,2005
[13]魏永杰,基于组合频谱技术的激光粒度仪研制,博士论文,天津;天津大学,2008
[14]李文超,激光粒度仪自动对中系统研制,硕士论文,天津;天津大学,2009
[15]王素华,颗粒粒径分布光散射问题的迭代正则化算法,硕士论文,天津;河北工业大学,2007
[16]尹吉婷,基于颗粒粒度极值分布函数的遗传反演算法的研究,硕士论文,南京;南京理工大学,2005
[17]韩一平,光散射法测量颗粒尺寸和浓度的实验研究,硕士论文,西安;西安电子科技大学,2007
[18]周雯,基于shifrin变换反演粒度分布的理论分析,光散射学报,2007,19(3):236~241
[19] M. T. Chahine, Determination of the Temperature profile in an atmosphere from its outgoing radiance, J. Opt. Soc. Am., 1968.1634~1637
[20]王清华,光散射法颗粒大小与形状分析,博士论文,南京;南京工业大学,2003
[21] B. L. Phillips, A Technique for the numerical solution of certain integral equations of the first kind, J. Assoc. Comput. Mach., 1962, 9: 84~97
[22] S. Twomey, On the numerical solution of Fredholm integral equations of the first kind by the inversion of linear system produced by quadrature, J. Assoc. Comput. Mach., 1963,10: 97~101
[23]王燕民,陈琪星,潘志东,激光粒度测量的综合反演及参数选择,2009,17(9):2120~2127
[24]梁国标,王燕民,李新衡,由Mie散射光强反演颗粒粒度分布的一种改进正则化法,光电工程,2006,33(12):44~49
[25]喻雷寿,杨冠玲,何振江,颗粒粒径测量中约束正则CONTN算法分析,激光生物学报,2007,16(1): 74~78
[26]张宇、刘雨东,计钊,向量相似度测度方法,声学技术,2009,28(4):532~536
[27]李中,苑津莎,杨宏,一种向量间相似度的计算方法,华北电力大学,专利号: 200910073836,2009
[28]王建萍,激光粒度测试系统的模块化研究,博士论文,天津;天津大学,1999
[29] Francisco Pedocchi,Marcelo H.Garcia, Noise-resolution trade-off in projection algorithms for laser diffraction particle sizing, APPLIED OPTICS,2006,45(15),3620~3628