基于UP/PTV技术的明流床面颗粒状态试验观测方法研究

Experimental Method for Observing the Bed Sands Motion Regimes in Open Channel Flow Based on UP/PTV Technology

明槽流中床沙运动及随机状态转换的试验研究水平依赖于高清图像的采集与颗粒踪迹的准确获取,为了提高试验精度与效率,借助UP/PTV技术进行了测试分析新方法的研究.首先探讨了水下无干扰图像采集系统的布置与技术要求,基于PTV原理,采用动态阈值、优化算法开发了基于Matlab平台的颗粒智能识别追踪程序PTP;引入活性粒子及颤抖效应,提出了0.2D50的颗粒临界活动域;通过多重滤波筛选可以提高样本数据有效性与降低颗粒定位误差.利用系列动床水槽试验和UP/PTV技术获取的床面颗粒较为完整的踪迹数据,进行了颗粒运动特征分析;颗粒速度的PDF显示出与Lajeunesse研究一致的细尾分布特性;由于采用比以往采集颗粒踪迹长5倍以上新数据,分析颗粒单步步长的PDF规律也明显优于以往如Roseberry的研究结果,验证了新方法的科学可行.

The experimental research on the bed sands movement and the transitions of random motion regimes,has a lot to do with the obtaining of high-resolution images and particle trajectories. To improve the accuracy and availability of experiment,the new measurement and analysis methods based on UP/PTV technology are researched. First of all,the arrangement and technical requirements of underwater photography system without interference are investigated.According to PTV principle,the particle recognition and tracking program PTP based on Matlab platform is developed by adopting dynamic threshold and optimizing algorithm. Besides,new ideas of active particles and wagging effect are introduced,and the critical active area of wagging particles less than 0.2D50 is proposed. Multiple filtering is used to improve the effectiveness of sample data and to reduce the locating error of particles. Using the relatively complete data of bed sands trajectories based on series of experiments and UP/PTV technology,the Lagrange process properties of the particle movement are analyzed. The PDF of particle velocity shows a gamma function curve,which coincides with the research of Lajeunesse et al.Because of the length of the obtained trajectories is at least five times longer than former collected data,the PDF curve of step distance behaves much better than previous research including Roseberry et al. These results above indicate the reliable and scientific nature of the new experimental method.