泥沙研究2025，Vol.50Issue(5)：42-49,8.DOI:10.16239/j.cnki.0468-155x.2025.05.006
基于卡尔曼滤波的推移质颗粒运动轨迹跟踪算法研究
Study on the trajectory tracking algorithm for bedload particle movement based on Kalman filter
摘要
Abstract
To address the accuracy limitations of the traditional image tracking algorithms in capturing the dynamic motion of multiple bedload particles,a motion trajectory tracking algorithm based on Kalman filter has been proposed.Experimental results from five flume tests under varying flow intensities(0.012 to 0.02)show that the improved algorithm improves the trajectory recognition rate up to 100％,the relative error and the coef-ficient of variation in particle coordinate identification can be decreased by 70％and 66％respectively,com-pared to traditional method.Bed load particle's instantaneous velocity exhibits an"acceleration-deceleration-acceleration"periodic pattern with notable local fluctuations.As flow intensity increases,particle trajectories become to smoothness from winding,the streamwise fluctuation intensity significantly rises,while transverse fluctuation intensity shows minor increase.关键词
推移质/卡尔曼滤波/颗粒识别/运动轨迹/水流强度/脉动强度Key words
bed load/Kalman filter/particle identification/particle trajectory tracking/flow intensity/fluctua-tion intensity分类
建筑与水利引用本文复制引用
刘鑫,邓敬宏,肖毅..基于卡尔曼滤波的推移质颗粒运动轨迹跟踪算法研究[J].泥沙研究,2025,50(5):42-49,8.基金项目
国家自然科学基金项目(52179059) （52179059）
