基于图像识别的推移质输沙率检测技术研究  

Study of real-time detection of bedload transport rate using image recognition technology

作　　者：孙东坡[1] 高昂[1] 刘明潇[2] 王鹏涛[1] 马腾飞[1] 赵亚飞[1] 

机构地区：[1]华北水利水电大学水力学及河流研究所,郑州450045 [2]西安理工大学水利水电学院,西安710048

出　　处：《水力发电学报》2015年第9期85-91,共7页Journal of Hydroelectric Engineering

基　　金：国家自然科学基金重点资助项目(51039004);华北水利水电大学大学生创新计划资助项目

摘　　要：鉴于传统推移质输沙率测量方法难以进行实时动态检测,本文将图像识别理论与推移质输移特点结合,提出了基于图像识别的推移质输沙率检测技术,给出了相应的推移质颗粒组成确定方法与推移质输沙率计算方法。水槽试验表明,基于图像识别的推移质输沙率的确定方法具有较好的可靠度。实时动态检测表明小粒径泥沙输移具有较好的连续性,而大粒径泥沙输移则具有明显的阵发性特点。这种非接触式的检测方法可以实现对非均匀推移质输移过程的动态监测,实时获取推移质颗粒组成以及分粒径组和分条带输沙率,在推求确定输沙率时还可以降低拟合曲线的病态特征程度,丰富了推移质测量的内容,有利于对非均匀推移质输移规律的深入研究。In this paper, we describe a new approach to real-time detection of bedload transport rate using image recognition technology, based on the characteristics of bedload transport. This method can be used to determine the particle composition of bedload and its transport rate of each compositional component, and thus the dynamic transport rate, which is difficult to measure by the traditional methods, can be directly measured in real-time. The flume experiment indicates that the method of bedload transport rate measurement based on image recognition has good reliability. Application to real-time dynamic detection shows that the transport of fine particles is stable with continuous variation while the transport of coarse particles is characterized by obvious intermittency. The non-contact detecting method presented herein can achieve dynamic monitoring on the transport process of non-uniform bedload, real-time tracking of the particle composition and each component＇s transport rate, and tracking of the strip transport rate. It can also lower the ill conditions of curve fitting in calculation of transport rate. Thus, the method would enrich bedload measurement and help the study of non-uniform bedload transport.

关 键 词：图像识别 推移质输沙率 非均匀沙 实时监测 OPENCV 波动性 

分 类 号：TV149[水利工程—水力学及河流动力学]