长江科学院院报 ›› 2017, Vol. 34 ›› Issue (7): 144-148.DOI: 10.11988/ckyyb.20160234

• 仪器设备与测试技术 • 上一篇    下一篇

一种改进的粒子图像测速混合算法研究

王 甜1, 房红兵1, 黄海龙2, 王 驰2   

  1. 1.南京理工大学 电子工程与光电技术学院,南京 210094;
    2.南京水利科学研究院,南京 210024
  • 收稿日期:2016-03-16 出版日期:2017-07-01 发布日期:2017-07-10
  • 作者简介:王 甜(1992-),女,江苏泰州人,硕士研究生,主要从事粒子图像测速方面的研究,(电话)13770327829(电子信箱)wt1179363754@163.com。
  • 基金资助:
    中央级公益性科研院所基本科研业务费专项基金(2011YQ070055)

An Improved Hybrid Algorithm for Particle Image Velocimetry

WANG Tian1, FANG Hong-bing1, HUANG Hai-long2, WANG Chi2   

  1. 1.School of Electronic and Optical Engineering,Nanjing University of Science & Technology, Nanjing 210094,China;
    2.Nanjing Hydraulic Research Institute,Nanjing 210024,China
  • Received:2016-03-16 Online:2017-07-01 Published:2017-07-10

摘要: 粒子图像测速技术作为一种新的流场测速方法能够在不干扰流场的情况下获得整个流场的速度信息。粒子图像测速技术最关键的步骤在于粒子匹配。针对粒子密度分布不均匀、流场不同等实际情况,提出了混合算法,即结合互相关和松弛算法能够更准确地搜索粒子,进而对粒子进行匹配。对3种匹配算法的匹配概率进行比较分析,发现混合算法能更准确地分析粒子的运动状态,减少错误矢量的产生;另外,对松弛算法进行改进,通过优化筛选加权因子发现改进的松弛算法在运行速度上相比原始算法有了较大提高,匹配率与原始算法基本一致。

关键词: 流场速度, 粒子图像测速, 混合算法, 超松弛迭代粒子追踪, 粒子匹配, 匹配概率

Abstract: As a new method of flow velocity measurement, particle image velocimetry (PIV) could obtain velocity information of the whole flow field without disturbing the flow field. The most critical step in PIV is particle matching. A hybrid algorithm combining cross-correlation algorithm and relaxation algorithm is proposed in view of the actual conditions of uneven distribution of particle density and different flow fields. The hybrid algorithm could search the particles more accurately so as to match the particles. The matching probabilities of three matching algorithms are compared and results suggest that the hybrid algorithm can analyze the motion state of particles more accurately and reduce the generation of error vectors. In addition, the relaxation algorithm is improved in this paper. By optimizing weighting factor, the running speed of the improved relaxation algorithm has greatly improved compared with the original algorithm, while the matching rate is basically consistent with the original algorithm.

Key words: velocity of flow field, particle image velocimetry, hybrid algorithm, particle tracking based on successive over relaxation, particle matching, matching probability

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