射流稀疏颗粒图像PIV算法应用  

Comparative study of three PIV algorithms for sparse particle images of jet flow

作　　者：虞建[1] 李荣先[1] 周力行[1] 

机构地区：[1]清华大学航天航空学院,北京100084

出　　处：《化工学报》2005年第7期1206-1208,共3页CIESC Journal

基　　金：国家重点基础研究发展规划项目(G1999022106).~~

摘　　要：A comparison of three PIV algorithms: FFT-based cross-correlation (FFT-CC) method, direct cross-correlation (DCC) method, and minimum quadratic difference (MQD) method was performed by applying these methods to low number density PIV images obtained by the Japan Visualization Society.Raw results of the MQD method were better than those of the FFT-CC, but validated results of the FFT-CC method were better than those of the MQD method. Results of the DCC method were the worst.There was discrepancy between results of the same algorithm with different sizes of the interrogation window.It mainly resulted from various amounts of matched particles of sub images.This study could provide good reference to the selection of the algorithm and its parameters.(A comparison of three PIV algorithms： FFT-based cross-correlation （FFT-CC） method, direct cross-correlation （DCC） method, and minimum quadratic difference （MQD） method was performed by applying these methods to low number density PIV images obtained by the Japan Visualization Society.Raw results of the MQD method were better than those of the FFT-CC, but validated results of the FFT-CC method were better than those of the MQD method. Results of the DCC method were the worst.There was discrepancy between results of the same algorithm with different sizes of the interrogation window. It mainly resulted from various amounts of matched particles of sub images. This study could provide good reference to the selection of the algorithm and its parameters.

关 键 词：颗粒图像测速(PIV) 最小平方差 FFT互相关 直接计算相关系数 射流稀疏颗粒图像 

分 类 号：O359[理学—流体力学]