内河航道数字孪生技术研究进展、关键技术与前景

梁才; 李文勇; 王长海; 申威; 周晓琴; 罗任童

doi:10.19818/j.cnki.1671-1637.2026.083

内河航道数字孪生技术研究进展、关键技术与前景

doi: 10.19818/j.cnki.1671-1637.2026.083

梁才^{1, 2, 3,},
李文勇^{1, 3, 4},
王长海^5, ,,
申威^{2, 3},
周晓琴^{3, 6},
罗任童^{2, 3}

1.
石家庄铁道大学交通运输学院, 河北石家庄 050043
2.
广西交通设计集团有限公司, 广西南宁 530029
3.
广西基础设施三维数字孪生工程研究中心, 广西南宁 530023
4.
桂林电子科技大学建筑与交通工程学院, 广西桂林 541004
5.
华中科技大学电子信息与通信学院, 湖北武汉 430074
6.
广西交通职业技术学院智能建造与低空技术学院, 广西南宁 530000

基金项目:

广西科技重大专项 AA23062053

广西科技基地和人才专项 AD25069109

详细信息

作者简介:
梁才(1987-)，男，湖南涟源人，正高级工程师，E-mail: 87350461@qq.com

通讯作者:
王长海(1981-)，男，安徽巢湖人，正高级工程师，E-mail: 15078888596@163.com

中图分类号: U611
计量
- 文章访问数: 49
- HTML全文浏览量: 32
- PDF下载量: 8
- 被引次数: 0
出版历程
- 收稿日期: 2025-05-28
- 录用日期: 2025-11-27
- 修回日期: 2025-10-02
- 刊出日期: 2026-04-28

Research progress, key technologies, and prospects of digital twin technology for inland waterway

LIANG Cai^{1, 2, 3
,},
LI Wen-yong^{1, 3, 4},
WANG Chang-hai^{5
, ,},
SHEN Wei^{2, 3},
ZHOU Xiao-qin^{3, 6},
LUO Ren-tong^{2, 3}

1.
School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang 050043, Hebei, China
2.
Guangxi Communications Design Group Co., Ltd., Nanning 530029, Guangxi, China
3.
Guangxi Infrastructure 3D Digital Twin Engineering Research Center, Nanning 530023, Guangxi, China
4.
School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541004, Guangxi, China
5.
School of Electronic Information and Communication, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
6.
College of Intelligent Construction and Low Altitude Technology, Guangxi Transport Vocational and Technical College, Nanning 530000, Guangxi, China

Funds:

Guangxi Science and Technology Major Project AA23062053

Guangxi Science and Technology Base and Talent Special Project AD25069109

More Information

Corresponding author: WANG Chang-hai, professor of engineering, E-mail: 15078888596@163.com

Article Text (Baidu Translation)

摘要

摘要: 为厘清航道数字孪生的概念内涵、关键技术及发展趋势，推进内河航道向全生命周期精细化与智能化管理转型升级，采用文献计量与文本挖掘相结合的研究方法，系统梳理了2000~2025年间相关的中英文文献，总结并分析了航道领域数字孪生的研究现状及关键特征，辨析与对比航道数字孪生的定义及相关概念；针对内河航道工程的特征，建立以数字孪生技术作为核心驱动的内河航道全生命周期管理范式，打通了从航道设计、建造到运维、管理、服务全过程数据；进一步提出基于工程分解结构(EBS)的跨阶段数据映射机制与面向全生命周期的内河航道数字孪生系统架构，涵盖数据底座、基础支撑平台、算法模型平台、应用服务平台等核心要素，并介绍了平陆运河工程应用案例；探讨了航道数字孪生应用现状、挑战、未来发展前景。研究结果表明：当前航道数字孪生面临全面精准感知体系并未形成、多源数据融合与治理难、模型仿真与交互能力不足、应用成效与智能化水平不足等诸多挑战，未来将朝着空-天-地-水一体化智能感知、全生命周期管控、实时计算与仿真推演、AI自主决策与智能控制、多行业融合等方向发展，通过数字孪生系统建设和技术应用驱动航道实现全流程建设管控、全方位智能运维业务变革，支撑航道管理实现更智能、高效的转型升级。
- 内河航道 /
- 数字孪生 /
- 综述 /
- 智慧航道 /
- 数据底座 /
- 发展趋势
Abstract: To clarify the conceptual connotation, key technologies, and development trends of digital twins for waterways and to promote the transformation and upgrading of inland waterways towards refined and intelligent management throughout the full lifecycle, a research method combining bibliometrics and text mining was adopted. Relevant Chinese and English literatures from 2000 to 2025 were systematically reviewed. The research status and key characteristics of digital twins in the waterway field were summarized and analyzed, and the definition and related concepts of waterway digital twins were discriminated and compared. In view of the characteristics of inland waterway projects, a full lifecycle management paradigm for inland waterways driven by digital twin technology as the core was established, and the data of the whole process from waterway design and construction to operation, maintenance, management, and service were connected. Furthermore, a cross-stage data mapping mechanism based on engineering breakdown structure (EBS) and a digital twin system architecture for inland waterways oriented to the full lifecycle were proposed, covering core elements such as data foundation, basic support platform, algorithm model platform, and application service platform. The application case of the Pinglu Canal project was introduced. The application status, challenges, and future development prospects of waterway digital twins were discussed. Research results show that current waterway digital twins face many challenges, such as the unformed comprehensive and precise perception system, difficult multi-source data fusion and governance, insufficient model simulation and interaction capabilities, and insufficient application effectiveness and intelligence level. In the future, it will develop towards the directions of space-air-ground-water integrated intelligent perception, full lifecycle management and control, real-time computing and simulation deduction, AI autonomous decision-making and intelligent control, and multi-industry integration. Through the construction of digital twin systems and technology applications, the whole-process construction management and control of waterways and the transformation of all-round intelligent operation and maintenance business are driven, supporting the smarter and more efficient transformation and upgrading of waterway management.
- inland waterway /
- digital twin /
- review /
- smart waterway /
- data foundation /
- development trend

HTML全文

图 1 近年来中国交通领域和航道领域数字孪生发文数量对比(截至2025年7月)

Figure 1. Comparison of the number of digital twin publications in the field of transportation and waterways in China in recent years (end in July 2025)

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图 2 2000~2025年国内外航道数字孪生发文统计(截至2025年7月)

Figure 2. Statistical analysis of digital twins in domestic and international navigation channels from 2000 to 2025 (end in July 2025)

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图 3 不同国家航道数字孪生发文量对比

Figure 3. Comparison of digital twin publications in different countries' waterways

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图 4 中文文献关键词共现聚类图谱

Figure 4. Keyword co-occurrence cluster map of Chinese literature

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图 5 英文文献关键词共现聚类图谱

Figure 5. Keyword co-occurrence cluster map of English literature

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图 6 航道数字孪生总体框架及其维度

Figure 6. Overall architecture and dimensions of waterway digital twins

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图 7 航道FDT架构

Figure 7. Federated digital twin architecture for waterways

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图 8 航道全生命周期数据映射与传递架构

Figure 8. Architecture for mapping and transmitting full life-cycle data of waterways

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图 9 面向全生命周期的航道数字孪生系统架构

Figure 9. Architecture of waterway digital twin system for the whole life-cycle

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图 10 航道数字孪生应用生态

Figure 10. Application ecosystem of waterway digital twin technology

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图 11 平陆运河建设期数字孪生系统架构

Figure 11. Digital twin system architecture of Pinglu Canal

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图 12 航道数字孪生技术与应用发展图景

Figure 12. Development vision of waterway digital twin technology and applications

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表 1 2000~2025年中英文航道数字孪生领域期刊文献排名

Table 1. Ranking of journal Chinese and English literatures in the field of digital twin of navigation from 2000 to 2025

排名	英文期刊	中文期刊
1	Ocean Engineering	《中国水运》
2	IFAC-PapersOnLine	《水道港口》
3	Transportation Research Procedia	《水运工程》
4	Heliyon	《江苏水利》
5	Science of the Total Environment	《中国工程科学》

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表 2 数字孪生航道与其他相关航道的对比

Table 2. Comparison between digital twin waterways and other related waterways

对比维度	数字孪生航道^{[16, 26]}	传统航道^{[3-4, 27]}	信息化航道^[28-29]	数字化航道^[9]	智慧航道^[30-31]
概念内涵	物理航道的数字镜像，实现实时感知、仿真分析、智能决策，是智慧航道的关键支撑技术	侧重于航道的建设与管理，缺乏与数字世界的深度融合	利用信息技术实现航道信息的采集、存储、管理与共享，提升管理效率	实现航道物理实体的数字化映射，构建航道数字模型	利用新一代信息技术实现航道的全面感知、智能分析与优化决策
建模方法	高精度数字模型，融合BIM、GIS、物联网等技术，动态更新、实时同步	物理模型试验、经验模型，精度低、周期长、成本高	信息管理系统、电子航道图等，侧重信息管理，缺乏深度建模	利用BIM、GIS等技术构建静态数字模型，缺乏动态仿真能力	强调数据驱动和模型应用，可结合数字孪生模型应用
模型精度	高精度、多维度、动态更新，实时反映物理航道状态	精度受限，难以反映复杂环境和动态变化	侧重信息管理，模型精度和动态性不足	静态数字化表达，缺乏动态仿真和实时更新能力	可结合数字孪生提升模型精度和动态性
数据采集与更新	物联网传感器实时采集，数据驱动模型动态更新	人工测量为主，数据更新周期长	信息采集和共享，缺乏实时性和动态更新能力	数字化表达，缺乏实时数据采集和动态更新机制	可实现数据采集和智能分析
智能化水平	高度智能化，支持智能感知、仿真分析、优化决策	管理方式粗放，智能化水平低	信息管理为主，智能化决策能力较弱	缺乏智能化决策和动态仿真能力	强调智能化应用与决策
虚实交互能力	强调虚实交互和闭环优化，数字模型与物理实体实时同步	缺乏虚实交互机制	缺乏虚实交互和闭环优化能力	缺乏虚实交互和动态仿真能力	可利用数字孪生航道进行虚实交互
应用场景	航道规划、设计、建设、运行管理、航运服务等全生命周期	主要用于航道建设与基本运行管理	信息查询、管理与共享，提升管理效率	航道数字建模、静态数据管理	智能化决策支持、优化管理策略
技术集成性	集成BIM、GIS、物联网、大数据、人工智能等技术	传统测量与监控技术，技术集成性低	侧重信息技术应用，技术集成性有限	数字化技术集成，缺乏智能化和动态仿真能力	强调新一代信息技术融合，需结合数字孪生提升集成深度
价值创造	提升航道管理水平和服务能力，支撑精细化、智能化管理	满足基本航运需求，难以适应精细化管理要求	提升信息管理效率，解决信息孤岛问题	提升数据获取和管理能力，为管理提供数字基础	提升智能化水平，优化管理决策和服务质量

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表 3 数字模型、数字阴影及数字孪生对比

Table 3. Comparison of digital model, digital shadow and digital twins

特性	数字模型	数字阴影	数字孪生
定义	物理对象或系统的静态虚拟表示	物理对象在数字空间中的实时数据映射，反映当前运行状态	物理对象的数字表示，具有物理与数字之间的双向实时数据流
数据流向	无自动数据流	单向，物理到数字	双向
实时性	无实时性，手动更新	具有实时性，自动反映物理对象的当前状态	高度实时性，数字对象与物理对象同步变化
交互性	静态或有限	单向反映，无控制	双向实时控制
应用场景	设计、仿真和分析	监控、历史分析	实时监控、预测、优化、控制

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表 4 航道数字孪生研究进展

Table 4. Research progress on digital twin of waterways

研究热点	年份	参考文献	研究进展
航道数字孪生框架	2020	[46]	提出了基于工业4.0参考架构模型(RAMI4.0)的通用数字孪生架构，将数字孪生体划分为类型层、实例层和执行层，并与RAMI4.0的信息技术层级进行了对齐
	2020	[12]	提出了加莱运河数字孪生框架，旨在利用数字孪生技术辅助运河管理者进行决策。该框架通过回放历史场景和快速仿真预测性管理策略，为管理者提供决策支持
	2024	[26]	从内河航道数字化转型的角度，构建了内河航道数字孪生框架体系。该框架体系主要包括3个部分：数据底座、引擎及知识库、数字孪生应用。该框架在苏州内河干线航道通扬线高邮段等航道的实际应用表明其科学合理
		[16]	从数字孪生航道工程实际应用出发，构建了包含物理实体航道、航道时空数据、孪生驱动引擎、数字虚体航道、场景应用服务在内的五维架构，全面地描述了数字孪生航道的组成要素和功能
		[47]	提出了数字孪生航道总体技术架构，并基于该架构设计与实现了长江通航安全保障系统。该技术架构强调多源数据融合治理，实现了通航安全信息的实时获取及监测预警，为通航保障服务提供了技术支撑
数据底座	2020	[48]	着重于通过融合多种公共数据集，推动内河水运在多式联运中的应用。利用AIS等数据，构建了详细的内河可导航水道网络模型，并通过与车载GPS数据的融合，分析运输流量区域，为未来的基础设施投资优先级提供支持
	2021	[49]	结合无人机倾斜摄影技术，快速、高精度地采集了内河航道的三维几何数据，并在数字孪生与安全管理结合的研究中，展示了基于3D视频融合的数字孪生应用框架
	2022	[50]	研究了多波束技术在智慧航道建设中的应用，指出多波束测深系统可以提供详细的水下地形数据，该技术能够高效、精准地采集航道水下地形数据，是构建高精度航道数字模型的重要数据来源
	2023	[51]	构建了集成AIS、视频监控和激光雷达的监测系统，实现了多维感知和数据融合，提升了数据收集的准确性
	2024	[52]	利用特征点匹配法与迭代最近点法，实现了无人机和水下多波束采集等多源数据融合，构建多细节层次构建三维可视化模型支撑航道建设及养护应用
	2025	[53]	探讨了物联网技术在智慧航道建设中的应用。通过在关键航道部署传感器网络，收集水位、流速、水质、气象、船舶动态数据，实现了航道的实时监控与管理
仿真模拟与分析	2022	[54]	提出了一种实时数字孪生模型，通过整合传感器数据和船舶动态模型实现实时仿真，用于预测船舶在波浪中的操作行为，优化航道导航和风险管理
	2023	[55]	采用数字孪生技术构建了涵盖内陆航运系统的多层级虚拟模型，模拟不同减排措施和管理干预措施对系统的影响，全面评估零排放策略的效果
	2024	[56]	提出了“几何-物理-行为-规则”的沿海航道全要素数字孪生体构建方法，实现了物理航道向数字航道的多维映射。该方法从几何、物理、行为和规则4个维度，全面地描述了航道数字孪生的组成要素和特征
		[57]	在信江航道中开展了通航仿真与滩道分析，通航仿真技术可以通过模拟航行过程，评估航道通航能力和安全性，滩道分析可以用于分析航道滩道的冲淤变化规律，为航道维护和整治提供科学依据
		[58]	通过实时数据流和仿真环境，构建了虚拟航道模型，利用数字孪生模拟船舶在复杂环境(如码头和狭窄通道)中的导航行为，该数字孪生模型能够准确预测船舶轨迹和潜在碰撞风险，显著提高了ASV在狭窄航道中的导航安全性

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表 5 航道数字孪生图形引擎对比

Table 5. Comparison of waterway digital twin graphics engines

引擎名称	引擎类型	架构	技术特点	航道适用性
Cesium^[87]	开源WebGL引擎	B/S架构	专注于地理空间渲染，支持大场景三维渲染	适用于航道大场景规划设计、建设管理
Three.js^[88]	开源WebGL引擎	B/S架构	轻量级、灵活，但对大场景的支持还需优化	适合中小型航道场景的快速开发
Unity^[81]	商业游戏引擎	C/S架构+ 像素流	跨平台，支持PhysX物理引擎，动态调度，渲染效果好	偏向于视觉要求高的中小型场景数字孪生，适用于航道运营场景
Unreal Engine^[79-80]	商业游戏引擎	C/S架构+ 像素流	高性能，支持物理渲染、全局光照、光线追踪，渲染效果好，硬件要求高	偏向于视觉要求极高的中小型场景数字孪生，适用于航道运营场景
OGRE	开源底层引擎	C/S架构	高度定制化渲染，跨平台，但开发难度高	适合科研或需要底层优化的航道仿真系统
SuperMap/ArcGIS	商用GIS开发平台	混合架构	GIS功能完善，支持三维空间分析，支持大场景三维渲染	适合需要深度GIS分析的航道地理空间数字孪生

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表 6 内河航道数字孪生典型应用

Table 6. Typical application of digital twin in inland waterways

文献	应用阶段/ 场景	应用形式	实际应用类型	应用地点	算法类型	结果/应用价值
[111]	规划设计	三维可视化展示、参数化设计	DM	河南沱浍河航道	空间分析、工程算量	提高设计效率和精度
[30]	建设管理	多源数据整合、数字化映射及管理、安全监测及预警、遥感监测分析、应急调度	DT	广西平陆运河	水文水动力模型、安全性动态仿真	提升运河工程规建管养全过程的一体化管控能，提升建设进度、安全、质量、绿色管控能力，为后续的运营期提供了数据基础
[112]	运河改扩建	数字建模、仿真分析、指标预测	DM	巴拿马运河	离散事件模型、系统动力学模型、神经网络、支持向量回归(SVR)	提前预测巴拿马运河扩建后的运营情况，评估潜在的环境影响，为运河的扩建和运营提供科学依据
[108]	建设及运营管理	二维视频与三维场景融合	DS	未提及	视频图像拼接匹配、虚拟场景构建	提高水路交通监控的效率和准确性，提升应急响应能力和历史事件追溯能力
[113]	运营服务	数字化建模、实时监控、动态交互、决策支撑	DT	俄罗斯南北运河、北海运输走廊	数据处理、仿真评估、机器学习	提高运输效率、降低运营成本、增强运输安全性
[114]	技术探索/ 安全管理	建模和仿真、运行模拟、船员培训	DS	长江航道	数据分析、可视化分析	提高长江航运的安全性和管理效率
[78]	航道运营维护	数字化建模、数据交互、模拟仿真、优化预测	DT	长江航道	数据治理、大数据分析、机器学习	提升长江航运安全性和运行效率，降低维护成本，增强环境保护能力
[115]	运营管理	数据整合、数字化映射及管理、水情预报、调度预演	DT	长江三峡	大数据分析、智能识别模型、水文学和水动力学算法模型	提升三峡工程的预报、预警、预演、预案“四预”智慧化水平，增强工程的综合管理和协同能力
[47]	运营安全保障	多源数据整合、要素数字化映射、实时监测及分析	DT	长江航道	数据治理、水流动力学模型、船舶运动模型、安全分析预警	提升长江航道的通航效率与安全性
[116]	运营维护	概率模型和专家知识库构建、不确定性分析及预测	DS	欧洲杜罗河航道	贝叶斯网络算法	提高内河运输系统的韧性，优化运输过程，为决策提供科学依据
[117]	运营管理	运行状态模拟、预测、优化控制	DT	法国加莱运河	模型预测控制、移动视界估计、线性离散时间模型	减少因潮汐变化和降雨导致的洪水风险，降低运营成本，提高水资源利用效率
[104]	运营服务	需求分析、数据汇聚分析、云平台建设	DS	长江航道	需求识别模型，层次分析法、云计算服务	精准识别不同用户群体的信息需求，优化内河航道信息服务的提供，提高服务质量和效率

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