基于BASEGRAIN软件的卵石粒径自动识别应用研究  

Application study on the automated grain sizing based on BASEGRAIN software

作　　者：黄科翰 张晨笛[1] 徐梦珍[1] 林永鹏 HUANG Ke-han;ZHANG Chen-di;XU Meng-zhen;LIN Yong-peng(State Key Laboratory of Hydroscience and Engineering,Tsinghua University,Beijing 100084,China)

机构地区：[1]清华大学水沙科学与水利水电工程国家重点实验室,北京100084

出　　处：《泥沙研究》2020年第2期44-51,共8页Journal of Sediment Research

基　　金：国家自然科学基金委重大项目课题(41790434);国家自然科学基金面上项目(51779120)。

摘　　要：粒径是表征卵石床面特征的重要参数,对水沙计算、河床演变及栖息地评价等课题具有重要意义。基于图像处理软件BASEGRAIN可自动识别卵石床面粒径并可视化计算结果,能够大幅提高卵石床面粒径获取效率。为评价基于BASEGRAIN的粒径自动识别效果,标准化其使用流程,对BASEGRAIN的主要参数进行敏感性分析和多元回归分析,并通过水槽实测结果分析误差特征。结果表明:BASEGRAIN的主要参数有4个,其中第一灰度阈值(fac1)对结果起控制作用,超过上限值后无法通过调节其他参数缩小误差。BASEGRAIN提取的级配曲线及特征粒径略小于实际情况,相对误差不超过20%,且随特征粒径增大而减小。单个石块粒径的提取结果总体可靠,但离散性较强,粗颗粒的提取精度较低。最后提出BASEGRAIN的标准化使用流程。Grain size is an important parameter of the gravel bed surface.Based on image processing method,BASEGRAIN software can automatically identify the grain size of gravel bed and visualize the results,which can improve the acquisition efficiency of grain size information.In order to evaluate the automated grain size method based on BASEGRAIN,and standardize the workflow,sensitivity tests and multiple regression analysis were conducted on the main parameters of BASEGRAIN.The error features were analyzed by the flume measurements.Results demonstrated that BASEGRAIN had four main parameters,among which the first gray threshold(fac1) controlled the result with an upper limit.The extraction error could not be reduced by adjusting other parameters once the upper limit of fac1 was reached.The grading curve and characteristic grain sizes obtained by BASEGRAIN were slightly underestimated with a relative error less than 20%,and the error decreased for larger characteristic sizes.The extraction of single grains confirmed the reliability of BASEGRAIN results,although the data showed a large variability.The extraction accuracy for coarse grains was relatively low.A standard workflow of BASEGRAIN was proposed at last.

关 键 词：卵石河床 粒径 级配曲线 图像处理 误差分析 

分 类 号：P332.5[天文地球—水文科学]