Automated measurement of moving grains on bed deposits

作     者：Amir H.N.CHEGINI Simon TAIT 

作者机构：Lecturer of Civil Engineering DepartmentFaculty of EngineeringUniversity of GuilanMain CampusI.R.of Iran School of EngineeringDesign and TechnologyUniversity of BradfordBradfordBD7 1DPUK. 

出 版 物：《International Journal of Sediment Research》 (国际泥沙研究(英文版))

年 卷 期：2011年第26卷第3期

页      面：304-317页

核心收录：

学科分类：08[工学] 081501[工学-水文学及水资源] 0815[工学-水利工程] 

主　　题：Uniform flow Bed load Sediment transport Measurement Image processing 

摘      要：The performance of gravel bedload predictor equations is particularly poor.A key reason for this situation is the current poor understanding of the physical mechanisms that are involved in the entrainment of grains from water-worked sediment *** has been caused,in part,by a lack of detailed data on the behaviour of moving sediment *** this study,observations of the entrainment, transport and deposition of many particles from a gravel bed has been collected and studied using an image-based *** system was used to measure the motion of hundreds of gravel particles moving as *** paper describes the development of the image-based system and the data processing methods used to provide the automated measurement of particle *** system was adapted from commercially available PIV equipment and was configured to obtain simultaneously data for the analysis of the moving grains and the near-bed flow *** techniques developed are relatively sensitive to sediment colour and shape by using related image processing algorithms and so could be applied to natural gravel *** results(image data)obtained from the techniques developed are amended in a program by using two functions(commands)of image processing called Label2RGB,and RegionProps which distinguish the colour and shape of moving sediment grains *** data processing provided information that identified individual grain entrainments,*** accurately traced the motion of some,but not all,*** show that the system was able to estimate grain entrainment rates and indicate locations of preferential entrainment and deposition from data on hundreds of individual moving grains.