基于数字孪生的海底悬浮物时空变化可视化技术实现与应用

乔玥; 单红仙; 王宏威; 朱超祁; 孙志文; 贾永刚

doi:10.12284/hyxb2023082

基于数字孪生的海底悬浮物时空变化可视化技术实现与应用

doi: 10.12284/hyxb2023082

乔玥^1,,
单红仙^{1, 2},
王宏威¹,
朱超祁^{1, 2, 3},
孙志文¹,
贾永刚^{1, 2, ,}

1.
中国海洋大学山东省海洋环境地质工程重点实验室，山东青岛 266100
2.
中国海洋大学海洋环境与生态教育部重点实验室，山东青岛 266100
3.
中国海洋大学海底科学与探测技术教育部重点实验室，山东青岛 266100

基金项目: 国家自然科学基金重点项目（41831280）；国家自然科学基金面上项目（41877223）；国家自然科学基金青年项目（42207173）。

详细信息

作者简介:
乔玥（1998-），女，江苏省徐州市人，研究方向为基于数字孪生技术的海底地质灾害监测预警。E-mail: jay0127@qq.com

通讯作者:
贾永刚（1965-），男，吉林省伊通满族自治县人，教授，博士，研究方向为海洋工程地质与环境。E-mail: yonggang@ouc.edu.cn

中图分类号: P751；P734.2⁺3
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- 被引次数: 0
出版历程
- 收稿日期: 2022-12-08
- 修回日期: 2023-03-08
- 网络出版日期: 2023-08-16
- 刊出日期: 2023-08-31

Implementation and application of digital twin-based visualization technology for spatial and temporal variation of seafloor suspensions

Qiao Yue^1
,,
Shan Hongxian^{1, 2},
Wang Hongwei¹,
Zhu Chaoqi^{1, 2, 3},
Sun Zhiwen¹,
Jia Yonggang^{1, 2
, ,}

1.
Shandong Provincial Key Laboratory of Marine Environment and Geological Engineering, Ocean University of China, Qingdao 266100, China
2.
Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, China
3.
Key Laboratory of Submarine Geosciences and Prospecting Techniques, Ministry of Education, Ocean University of China, Qingdao 266100, China

摘要

摘要: 数字孪生技术构建的虚拟海洋平台，能够进一步实现海底环境监测数据的三维可视化分析。本文基于深海底长期原位监测数据，使用Unity3D技术构建出多模型融合的虚拟海洋环境，初步建立海洋工程地质环境数字孪生系统；结合MATLAB、ArcGIS数据分析技术实现智能监测、数据分析、人机交互、辅助决策等功能；研究进一步构建虚拟环境粒子系统，对南海北部陆坡神狐海域近底层悬浮物浓度升高事件进行了三维可视化分析，结果表明：在虚拟环境粒子系统中悬浮物浓度、粒子数量与聚集程度具有较大的时空差异。特别是悬浮物浓度维持在较高水平时，发现粒子间相互碰撞、重叠，并在空间中衍生了密集程度更高的微团，当悬浮物浓度进一步升至峰值时，微团数量增加并占据空间大部分体积，形成悬浮颗粒高度聚集，覆盖范围更广的悬浮物聚合体。本文基于图像分析技术，将可视化分析结果与真实海底摄像进行对比，相对误差在0.16%～2.80%范围内，具有较高的可行性。
- 数字孪生 /
- 悬浮物浓度 /
- 可视化分析 /
- 虚拟粒子系统 /
- 深海原位长期监测
Abstract: The virtual ocean platform constructed by digital twin technology can further realize the 3D visualization and analysis of seabed environmental monitoring data. Based on the long-term in-situ monitoring data of the deep seabed, this paper uses Unity3D technology to build a virtual marine environment with multi-model fusion, and initially establishes a digital twin system for marine engineering geological environment; combines MATLAB and ArcGIS data analysis technology to realize intelligent monitoring, data analysis, human-computer interaction and auxiliary decision-making; the study further constructs a virtual environment particle system to conduct a 3D visualization and analysis of the near-bottom suspended sediment concentration elevation event in the northern part of the South China Sea. The results show that there are large spatial and temporal differences in suspended matter concentration, particle number and aggregation degree in the virtual environmental particle system. In particular, when the suspended matter concentration is maintained at a high level, particles are found to collide and overlap with each other, and the denser microclusters are derived in space. When the suspended matter concentration rises further to the peak, the number of microclusters increases and occupies most of the volume of space, forming a highly aggregated suspended matter aggregate with a wider coverage of suspended particles. This paper is based on image analysis techniques and compares the visualization results with real seafloor cameras with relative errors in the range of 0.16%–2.80%, which is highly feasible.
- digital twins /
- concentration of suspended solids /
- visual analysis /
- virtual particle system /
- in situ long-term monitoring of deep sea

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图 1 海洋工程地质环境数字孪生系统框架

Fig. 1 Framework for a digital twin system for the marine engineering geological environment

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图 2 SEEGeo工作模式

Fig. 2 SEEGeo working mode

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图 3 虚拟层场景实现过程

Fig. 3 Virtual layer scenario realisation process

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图 4 设备虚拟仿真模型

Fig. 4 Virtual simulation models of equipment

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图 5 海底地形模型

Fig. 5 Submarine terrain model

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图 6 海洋环境仿真模型

Fig. 6 Marine environment simulation model

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图 7 虚拟现实模型实现框架

Fig. 7 Virtual reality model implementation framework

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图 8 智能监测功能

Fig. 8 Intelligent monitoring functions

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图 9 数据分析功能

Fig. 9 Data analysis functions

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图 10 研究区位置

Fig. 10 Location of the study area

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图 11 浊度随时间变化关系

Fig. 11 Relationship between turbidity and time

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图 12 浊度与悬浮物颗粒浓度之间的线性关系

Fig. 12 Linear relationship between turbidity and suspended particle concentration

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图 13 悬浮颗粒物粒径的垂直分布及中值曲线

Fig. 13 Vertical distribution and median curves of suspended particulate matter particle sizes

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图 14 悬浮物浓度时间变化曲线及对应数字孪生虚拟粒子系统可视化分析图

Fig. 14 Temporal variation curve of suspended matter concentration and corresponding digital twin virtual particle system visualisation

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图 15 ROV海底摄像影片和数字孪生虚拟粒子系统可视化分析对比图

Fig. 15 Comparison of ROV subsea camera film and digital twin virtual particle system visualisation analysis

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表 1 近底层悬浮物颗粒虚拟仿真粒子信息表

Tab. 1 Virtual simulation particle information sheet for near-bottom suspended particles

虚拟仿真参数名称	参数信息
悬浮物平均粒径	30 μm
悬浮物体积	14 130 μm³
悬浮物平均密度	1.48 g/cm³
悬浮物体积（1 mg/L）	3 943 mm³
悬浮物数量（1 m³）	279 021 059
传感器有效探测范围	125 cm³
空间体积放大比例	1∶4 096 000
空间体积	512 m³
单个粒子体积放大比例	1∶621 378 370
粒子体积	8 780 mm³

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