Research and Application of Intelligent Safety Monitoring and Early Warning System for Long-distance Water Diversion Projects

NIU Guang-li, LI Tian-yang, XUE Guang-wen, CUI Peng, QIN Peng, FANG Hao-wen

Journal of Changjiang River Scientific Research Institute ›› 2025, Vol. 42 ›› Issue (2) : 204-210.

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Journal of Changjiang River Scientific Research Institute ›› 2025, Vol. 42 ›› Issue (2) : 204-210. DOI: 10.11988/ckyyb.20240695
BASIC THEORIES AND KEY TECHNOLOGIES FOR MAJOR WATER DIVERSION PROJECTS

Research and Application of Intelligent Safety Monitoring and Early Warning System for Long-distance Water Diversion Projects

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Abstract

To ensure the safety of long-distance water diversion projects during construction and operation, it is crucial to implement intelligent safety monitoring and early warning systems based on existing engineering safety monitoring frameworks. We present a comprehensive design for an intelligent safety monitoring and early warning system tailored for long-distance water diversion projects. We expound the system’s key technical approaches, including management modes and processes, specialized analysis methods, and development technology system. We also illustrate the system’s application in major water diversion projects, such as the Pearl River Delta Water Resources Allocation Project and the Yangtze-Huaihe River Water Diversion Project. Engineering practices demonstrate that the system offers perfect functional modules and stable performance, significantly enhancing the information management, online monitoring, and early warning capabilities for long-distance water diversion projects. This provides valuable insights and guidance for developing similar systems.

Key words

long distance water diversion project / engineering safety / intelligent monitoring and early warning system / Pearl River Delta Water Resources Allocation Project / Yangtze River to Huaihe River Diversion Project

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NIU Guang-li , LI Tian-yang , XUE Guang-wen , et al . Research and Application of Intelligent Safety Monitoring and Early Warning System for Long-distance Water Diversion Projects[J]. Journal of Changjiang River Scientific Research Institute. 2025, 42(2): 204-210 https://doi.org/10.11988/ckyyb.20240695

References

[1]
中共中央, 国务院. 国家水网建设规划纲要[J]. 中国水利, 2023(11): 1-7.
Central Committee of the Communist Party of China and the State Council. The Guideline for the Construction of National Water Network[J]. China Water Resources, 2023(11): 1-7. (in Chinese))
[2]
杨启贵, 张传健, 颜天佑, 等. 长距离调水工程建设与安全运行集成研究及应用[J]. 岩土工程学报, 2022, 44(7): 1188-1210.
YANG Qi-gui, ZHANG Chuan-jian, YAN Tian-you, et al. Integrated Research and Application of Construction and Safe Operation of Long-distance Water Transfer Projects[J]. Chinese Journal of Geotechnical Engineering, 2022, 44(7): 1188-1210. (in Chinese))
[3]
蔡阳, 成建国, 曾焱, 等. 加快构建具有“四预”功能的智慧水利体系[J]. 中国水利, 2021(20):2-5.
CAI Yang, CHENG Jian-guo, ZENG Yan, et al. Accelerate to Build Smart Water System with the Function of “Four Pres”[J]. China Water Resources, 2021(20): 2-5. (in Chinese))
[4]
成建国. 数字孪生水网建设思路初探[J]. 中国水利, 2022(20):18-22,10.
CHENG Jian-guo. Preliminary Study on the Construction of Digital Twin Water Network[J]. China Water Resources, 2022(20):18-22,10. (in Chinese))
[5]
刘辉. 国家水网工程智能化建设的思考[J]. 中国水利, 2021(20): 9-10.
LIU Hui. Thought of Intelligentized Construction of National Water Network[J]. China Water Resources, 2021(20): 9-10. (in Chinese))
[6]
黄跃文, 牛广利, 李端有, 等. 大坝安全监测智能感知与智慧管理技术研究及应用[J]. 长江科学院院报, 2021, 38(10): 180-185, 198.
Abstract
水库大坝安全监测是工程安全的重要保障措施,亟需结合新一代信息技术,提升大坝安全监测能力。系统总结了长江科学院近年来在大坝安全监测智能感知与智慧管理技术方面的研究及应用工作,通过研发系列化智能传感器、智能采集单元和物联网感知平台,建设统一的大坝安全监测数据资源池,开发通用化安全监测云服务系统,搭建专业数据挖掘平台和综合可视化应用,实现了大坝安全监测数据感知、传输、管理、分析及展示全链路应用,形成了大坝安全监测全生命周期智慧解决方案。研究成果已在乌东德、溪洛渡、向家坝、大藤峡等100余项水利水电工程中成功应用,为保障工程建设及运行安全发挥了重要的支撑作用,具有很好的推广应用前景。
HUANG Yue-wen, NIU Guang-li, LI Duan-you, et al. Research and Application of Intelligent Perception and Intelligent Management Technology for Dam Safety Monitoring[J]. Journal of Yangtze River Scientific Research Institute, 2021, 38(10):180-185, 198. (in Chinese))
Monitoring on reservoir and dam safety is an important guarantee for the safe operation of project. It is urgent to improve the ability of dam safety monitoring by using the new generation of information technology. In this paper we systematically summarize the researches and applications made by Changjiang (Yangtze) River Research Institute in intelligent perception and intelligent management technology of dam safety monitoring in recent years. We built a unified data resource pool for dam safety monitoring by developing a series of intelligent sensors, intelligent acquisition units and Internet of things sensing platform, and developed a generalized safety monitoring cloud service system. We also built professional data mining platform and comprehensive visualization application to realize the full link application of data perception, transmission, management, analysis and display for dam safety monitoring, forming a full life cycle intelligent solution for dam safety monitoring. The research achievements have been applied in more than 100 water conservancy and hydropower projects, such as Wudongde, Xiluodu, Xiangjiaba and Datengxia hydropower stations, playing an important supporting role in ensuring the safety of project construction and operation.
[7]
肖彬. 长距离引水工程智慧建设管理方案研究[J]. 人民珠江, 2022, 43(2): 46-51, 69.
XIAO Bin. Study on Management Scheme about Intelligent Construction of Long-distance Water Diversion Project[J]. Pearl River, 2022, 43(2):46-51, 69. (in Chinese))
[8]
秦朋, 谭勇, 牛广利, 等. 某长距离引调水工程安全预警管理体系[J]. 广东土木与建筑, 2021, 28(11): 1-4, 11.
QIN Peng, TAN Yong, NIU Guang-li, et al. The Safety Forewarning System of a Long-distanced Water Diversion Project[J]. Guangdong Architecture Civil Engineering, 2021, 28(11):1-4, 11. (in Chinese))
[9]
郭新强, 邢阿龙, 张伟. 深埋引水隧洞安全监测数据分析[J]. 西北水电, 2024(2): 72-77.
GUO Xin-qiang, XING A-long, ZHANG Wei. Analysis on Safety Monitoring Data of Deep Diversion Tunnels[J]. Northwest Hydropower, 2024(2): 72-77. (in Chinese))
[10]
牛广利, 李天旸, 杨恒玲, 等. 数字孪生水利工程安全智能分析预警技术研究及应用[J]. 长江科学院院报, 2023, 40(3): 181-185.
Abstract
数字孪生水利工程是智慧水利建设的核心与关键。聚焦水利工程安全运行需求,有必要结合数字孪生建设,开展工程安全智能分析预警技术研究和系统开发工作,从而有效提升工程运行安全保障水平与突发事件应急处置能力。介绍了基于数字孪生平台的工程安全智能分析预警技术的总体框架,针对工程安全监测感知体系和工程安全模型库进行了详细论述,并构建了具有“四预”功能的工程安全智能业务应用。目前,研究成果已在数字孪生江垭皂市工程中获得初步应用,可为同类数字孪生工程建设提供借鉴与参考。
NIU Guang-li, LI Tian-yang, YANG Heng-ling, et al. Research and Application of Safety Intelligent Analysis and Early Warning Technology for Digital Twin Water Conservancy Project[J]. Journal of Changjiang River Scientific Research Institute, 2023, 40(3): 181-185. (in Chinese))
[11]
杨阳, 何勇军, 徐海峰, 等. 输水隧洞动态监控指标拟定方法[J]. 水利水电科技进展, 2018, 38(5): 81-85.
YANG Yang, HE Yong-jun, XU Hai-feng, et al. Determination Method of Dynamic Monitoring Indexes for Water Conveyance Tunnels[J]. Advances in Science and Technology of Water Resources, 2018, 38(5): 81-85. (in Chinese))
[12]
程德虎, 郝泽嘉, 何金平. 引调水工程渠堤运行安全监控多指标评判准则[J]. 南水北调与水利科技(中英文), 2022, 20(1): 54-61.
CHENG De-hu, HAO Ze-jia, HE Jin-ping. Multi-index Evaluation Criterion for Operation Safety of the Canal in Water Diversion Project[J]. South-to-North Water Transfers and Water Science & Technology, 2022, 20(1): 54-61. (in Chinese))
[13]
牛广利, 胡雨新, 胡蕾, 等. 工程安全综合评价模型研究及数字孪生应用[J]. 人民长江, 2024, 55(4): 239-243, 261.
NIU Guang-li, HU Yu-xin, HU Lei, et al. Comprehensive Evaluation Model of Engineering Safety and Application in Digital Twin[J]. Yangtze River, 2024, 55(4):239-243, 261. (in Chinese))
[14]
严振瑞. 珠江三角洲水资源配置工程关键技术问题思考[J]. 水利规划与设计, 2015(11): 48-51.
YAN Zhen-rui. Thoughts on Key Technical Problems of Water Resources Allocation Project in Pearl River Delta[J]. Water Resources Planning and Design, 2015(11): 48-51. (in Chinese))
[15]
胡星名. 引江济淮工程施工组织设计重难点分析[J]. 水利水电快报, 2020, 41(12): 17-21.
HU Xing-ming. Analysis of Key Points and Difficulties in Construction Organization Design of Water Diversion Project from Yangtze to Huaihe River[J]. Express Water Resources & Hydropower Information, 2020, 41(12): 17-21. (in Chinese))
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