长江科学院院报 ›› 2017, Vol. 34 ›› Issue (1): 1-5.DOI: 10.11988/ckyyb.20150831

• 江湖泥沙与治理 • 上一篇    下一篇

图像处理技术在推移质运动颗粒参数提取中的应用

许琳娟1,2, 曹文洪1, 刘春晶1, 鲁婧1   

  1. 1.中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室,北京 100048;
    2.黄河水利委员会 黄河水利科学研究院,郑州 450003
  • 收稿日期:2015-10-04 出版日期:2017-01-01 发布日期:2017-01-01
  • 作者简介:许琳娟(1984-),女,河南巩义人,博士,工程师,主要从事水力学及河流动力学方面的研究,(电话)15810176865(电子信箱)282957173@qq.com。
  • 基金资助:
    中国水科院科研专项(泥基本科研KY1646);国家自然科学基金项目(11472310);国家国际科技合作专项(2015DFR70980);国家科技支撑计划课题(2013BAB12B01)

Application of Image Processing Technology to Extracting Parameters of Bedload Motion Particles

XU Lin-juan1,2, CAO Wen-hong1, LIU Chun-jing1, LU Jing1   

  1. 1.State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China;
    2.Yellow River Institute of Hydraulic Research,Yellow River Conservancy Commission, Zhengzhou 450003, China
  • Received:2015-10-04 Published:2017-01-01 Online:2017-01-01

摘要: 非均匀推移质颗粒运动规律一直是泥沙研究领域的难点,提取非均匀推移质颗粒的参数信息则是推进该难点研究的基础性工作。通过进行粗化床面非均匀沙水槽试验,拍摄了大量的泥沙颗粒运动视频,选取其中部分视频进行处理和研究:先通过图像转换软件将拍摄的视频转化为图片;然后利用图像处理技术对泥沙颗粒运动图像的空间变化特征进行识别,对转化后的图片进行畸形矫正和背景除噪;最后通过选取合理阈值将图片上泥沙颗粒提取出来,并计算泥沙颗粒粒径、体积等相关参数信息。研究成果可为获取推移质颗粒输沙运动基本信息提供基础,为非均匀推移质输沙机理研究提供更科学、完善、可靠的数据。

关键词: 水质预测, 神经网络模型, 耦合动态方程, 机理性先验知识, Mackey-Glass混沌系统

Abstract: The motion regularity of non-uniform bedload particles has been a difficulty in sediment research, and extracting the parameters of non-uniform bedload particles is a basic work to overcome the difficulty. Through flume experiment of non-uniform bedload on rough bed, a large amount of videos of particle motion were obtained, and some of the videos were selected for processing and research: firstly the video shot was converted into images by image conversion software, and then the deformity was corrected and the background noise was removed of the converted images by spatial transformation and cutting; lastly the sediment particle contours were extracted by selecting a reasonable threshold. Furthermore, parameters inclusive of particle size and particle volume were calculated to provide basis for obtaining the basic information of bed load particles motion. The research offers scientific and improved, reliable data for researching the transport mechanism of non-uniform bed load sediment.

Key words: water quality prediction, neural network model, dynamic equation, mechanism priori knowledge, Mackey-Glass chaotic system

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