首页 | 本学科首页   官方微博 | 高级检索  
     检索      

移动最小二乘法在 PIV迭代过程中的应用
引用本文:陈波,李万平.移动最小二乘法在 PIV迭代过程中的应用[J].华中科技大学学报(自然科学版),2012,40(1):104-107,112.
作者姓名:陈波  李万平
作者单位:华中科技大学土木工程与力学学院,湖北武汉,430074
基金项目:国家自然科学基金资助项目(10372033);西部灾害与环境力学教育部重点实验室开放基金资助项目
摘    要:提出了一种增强粒子图像测速(PIV)技术中图片变形迭代查询算法稳定性的方法,在迭代计算过程中用移动最小二乘法(MLS)来拟合互相关计算得到的位移场.合成图片的评估显示:MLS能很好地增强算法的稳定性,并且有很好的空间分辨率特性,在一定程度上改善了算法的精度.真实流场的评估也显示MLS能增强算法的稳定性.同时MLS的加入不会明显增加计算时间.

关 键 词:粒子图像测速  互相关  迭代  移动最小二乘法  稳定性

Application of moving least square filter to iterative image deformation method in PIV
Chen Bo Li Wanping.Application of moving least square filter to iterative image deformation method in PIV[J].JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE,2012,40(1):104-107,112.
Authors:Chen Bo Li Wanping
Institution:Chen Bo Li Wanping(School of Civil Engineering and Mechanics,Huazhong University of Science and Technology,Wuhan 430074,China)
Abstract:A method to increase the stability of the iterative procedure of the image deformation method for the particle image velocimetry(PIV) was proposed.The moving least square(MLS) method was used to filter the vector field during the iterative process.The assessment of synthetic images shows that the MLS can enhance the stability of the iterative procedure accompanied with well accuracy and spatial resolution.The real flow field results also show that the MLS can enhance the stability of the algorithm.MLSs accession will not significantly increase the computing time,and adapt to different types of flow field.
Keywords:particle image velocimetry (PIV)  cross-correlation  iterative~ moving least square(MLS)  stability
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号