测绘通报 ›› 2022, Vol. 0 ›› Issue (10): 118-123.doi: 10.13474/j.cnki.11-2246.2022.0305

• 技术交流 • 上一篇    下一篇

利用无人船测量系统检测钱塘江护岸工程水下块石

毕继鑫1, 刘强1,2, 吴文超1, 占晓明1   

  1. 1. 浙江华东测绘与工程安全技术有限公司, 浙江 杭州 310014;
    2. 中国海洋大学工程学院, 山东 青岛 266110
  • 收稿日期:2022-01-19 修回日期:2022-08-24 发布日期:2022-11-02
  • 作者简介:毕继鑫(1994-),男,硕士,工程师,现主要从事工程测量及安全监测方面的研究。E-mail:bijixin7317@163.com
  • 基金资助:
    浙江华东测绘与工程安全技术有限公司科技项目(ZKY2022-CA-02-01;HDC&A-KJ-2021-05)

Detection of underwater block stone in Qiantang River revetment engineering based on unmanned ship measurement system

BI Jixin1, LIU Qiang1,2, WU Wenchao1, ZHAN Xiaoming1   

  1. 1. Zhejiang Huadong Mapping and Engineering Safety Technology Co., Ltd., Hangzhou 310014, China;
    2. College of Engineering, Ocean University of China, Qingdao 266110, China
  • Received:2022-01-19 Revised:2022-08-24 Published:2022-11-02

摘要: 水下块石检测与识别作为钱塘江海塘护岸工程的关键环节,对保障板桩施工工效至关重要。本文首先在研究无人船测量系统岸基通信、数据采集核心技术基础上,推导了NORBIT多波束声呐分辨率估计模型及附加块石粒径约束条件的最大波束开角、最小数据更新率、最大航速间的关系式和推荐值;然后结合钱塘江水下多波束扫测点云数据三维特性,对区域生长算法进行改进,以实现块石点云识别和提取。工程实践结果表明,优化的无人船测量系统多波束声呐参数可实现水下细小块石精准检测,能如实反映水下块石及周边微地形地貌真实情况,改进的区域生长算法能从众多河床点云数据中高效提取水下块石点云,为板桩施工提供准确的块石分布情况,具有很好的工程应用意义。

关键词: 护岸工程, 无人船测量系统, 水下块石, 多波束, 参数优化, 区域生长算法

Abstract: As the key link of Qiantang River seawall revetment engineering, the detection and identification of underwater block stone is very important to ensure the construction efficiency of sheet piles. Based on the research on the core technology of shore-based communication and data acquisition of the unmanned ship measurement system, the NORBIT multi-beam sonar resolution estimation model and the maximum beam opening angle, the minimum data update rate and the maximum speed of the additional rock particle size constraints are derived. The relationship and recommended value of,combined with the three-dimensional characteristics of the Qiantang River underwater multi-beam scanning point cloud data, the region growing algorithm is improved to realize the identification and extraction of the boulder point cloud. The engineering practice results show that the optimized multi-beam sonar parameters of the unmanned ship measurement system can achieve accurate detection of small underwater rocks, and can faithfully reflect the real situation of underwater block stone and surrounding micro-topography. The point cloud of underwater block stone is extracted from the point cloud data of many riverbeds to provide accurate distribution of boulders for sheet pile construction, which has good engineering application significance.

Key words: revetment engineering, unmanned ship measurement system, underwater block stone, multi-beam, parameter optimization, regional growth algorithm

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