AN IMPROVED PTV SYSTEM FOR LARGE-SCALE PHYSICAL RIVER MODEL  

作　　者：TANG Hong-wu CHEN Cheng CHEN Hong HUANG Jian-tong 

机构地区：[1]College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China

出　　处：《Journal of Hydrodynamics》2008年第6期669-678,共10页水动力学研究与进展B辑（英文版）

基　　金：Project supported by the National Natural Science Foundation of China (Grant Nos. 50479068, 50779014);the Technological Innovation Project of Graduate students in Jiangsu Province (Grant No.1306014);the Project of "Six Talent Peak" of Jiangsu Province (Grant No. 07-A-006).

摘　　要：To measure the surface flow in a physical river model, an improved system of Large-Scale Particle Tracking Velocimetry （LSPTV） was proposed and the elements of the PTV system were described. Usually the tracer particles of a PTV system seeded on water surface tend to form conglomerates due to surface tension of water. In addition, they can not float on water surface when water flow is shallow. Ellipsoid particles were used to avoid the above problems. Another important issue is particle recognition. In order to eliminate the influence of noise, particles were recognized by the processing of multi-frame images. The kernel of the improved PTV system is the algorithm for particle tracking. A new 3-frame PTV algorithm was developed. The performance of this algorithm was compared with the conventional 4-frame PTV algorithm and 2-frame PTV algorithm by means of computer simulation using synthetically generated images. The results show that the new 3-frame PTV algorithm can recover more velocity vectors and have lower relative error. In addition, in order to attain the whole flow field from individual flow fields, the method of stitching individual flow fields by obvious marks was worked out. Then the improved PTV system was applied to the measurement of surface flow field in Model Yellow River and shows good performance.To measure the surface flow in a physical river model, an improved system of Large-Scale Particle Tracking Velocimetry （LSPTV） was proposed and the elements of the PTV system were described. Usually the tracer particles of a PTV system seeded on water surface tend to form conglomerates due to surface tension of water. In addition, they can not float on water surface when water flow is shallow. Ellipsoid particles were used to avoid the above problems. Another important issue is particle recognition. In order to eliminate the influence of noise, particles were recognized by the processing of multi-frame images. The kernel of the improved PTV system is the algorithm for particle tracking. A new 3-frame PTV algorithm was developed. The performance of this algorithm was compared with the conventional 4-frame PTV algorithm and 2-frame PTV algorithm by means of computer simulation using synthetically generated images. The results show that the new 3-frame PTV algorithm can recover more velocity vectors and have lower relative error. In addition, in order to attain the whole flow field from individual flow fields, the method of stitching individual flow fields by obvious marks was worked out. Then the improved PTV system was applied to the measurement of surface flow field in Model Yellow River and shows good performance.

关 键 词：Large-Scale Particle Tracking Velocimetry （LSPTV） PARTICLE 3-frame PTV physical fiver model 

分 类 号：TV131.2[水利工程—水力学及河流动力学]