In order to solve the problem of high measurement error in the condition of high concentration particles in surface velocity image measurement, the nearest neighbor matching algorithm is improved. The particle matching algorithm of multi-frame regression analysis, a particle matching algorithm for surface flow field based on regression analysis is presented. This algorithm takes the particle distance, the motion-trajectory and the movement trends into account. A linear regression analysis is applied to the coordinates of the particle center and the particle matching is accomplished through calculating the correlation coefficient to achieve the best homologous particle tracking. An improved large-scale particle image velocimetry(ILSPIV)was developed with multi-frame regression particle matching algorithm, which had been applied to the Baguazhou Island physical model. The measurement results of the distribution shape and value of for the average vertical velocity between ILSPIV and propeller-type current meter were basically the same, indicating that the particle matching algorithm of multi-frame regression analysis can improve the precision of surface velocity measurement in the condition of high concentration particles and can better meet the needs of engineering practice research.
陈红,周国梁,闫静,等.基于回归分析的表面流场粒子匹配算法[J].水利水电科技进展,2020,40(1):32-36.(CHEN Hong, ZHOU Guoliang, YAN Jing, et al. Study on particle matching algorithm for surface flow field based on regression analysis[J]. Advances in Science and Technology of Water Resources,2020,40(1):32-36.(in Chinese))复制