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基于图像的河流表面测速研究综述

Review of image-based river surface velocimetry research

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【作者】 杨聃邵广俊胡伟飞刘国富梁家铭王瀚林许超

【Author】 YANG Dan;SHAO Guang-jun;HU Wei-fei;LIU Guo-fu;LIANG Jia-ming;WANG Han-lin;XU Chao;Jinshuitan Hydropower Plant of State Grid Zhejiang Electric Power Limited Company;College of Control Science and Engineering, Zhejiang University;

【机构】 国网浙江省电力有限公司紧水滩水力发电厂浙江大学控制科学与工程学院

【摘要】 为了解决洪涝灾害环境下设备难布设、流速难测量、河流难监控等问题,结合河流管控领域近10年研究情况,基于非侵入式、低成本、高效的测量手段,概述从粒子图像测速技术(PIV)到深度学习方法的一系列图像测速技术.从图像采集、图像分析、图像后处理等方面探讨河流表面测速机理及存在的问题.通过比对与总结各方法差异性,提出对现有方法的改进需求,旨在提升河流流速的测量效率.

【Abstract】 In order to solve the problems of difficult equipment deployment, velocity measurement and river monitoring in flooding environment, a series of image velocimetry techniques from particle image velocimetry(PIV)to deep learning methods were outlined based on non-invasive, low-cost and efficient measurement means in conjunction with nearly ten years of research in the field of river monitoring. The mechanism and issues of river surface velocimetry were discussed in the sections of image acquisition, image analysis, and image post-processing.By comparing and summarizing the differences of each method, the requirement of the existing methods were proposed, aiming to improve the river flow velocity measurement efficiency.

【基金】 国网浙江省电力有限公司科技项目(5211JS18001200K3100000)
  • 【文献出处】 浙江大学学报(工学版) ,Journal of Zhejiang University(Engineering Science) , 编辑部邮箱 ,2021年09期
  • 【分类号】TP391.41;P332.4
  • 【被引频次】2
  • 【下载频次】326
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