岩土工程学报2025，Vol.47Issue(10)：2003-2014,12.DOI:10.11779/CJGE20240465
智能大坝研究进展与发展路径思考
Research progress and reflection on development path of smart dams
摘要
Abstract
Climate change and strong human activities have brought new challenges to dam safety management,and traditional safety management concepts and technologies are difficult to meet the requirements of high-quality dam safety management in the new stage.The development of cloud computing,Internet of Things,big data,artificial intelligence and other new-generation information technologies provide an important opportunity for the digital,networked and intelligent transformation of dam safety management.As an important symbol of the modernization of dam safety management,smart dam is an important carrier for the development of the new quality productivity of water conservancy.How to use intelligent technology to upgrade and transform a traditional dam construction management system and effectively improve the construction management efficiency and safety guarantee margin has become the focus and difficulty of industry research.This paper comprehensively sorts out the research progress of smart dam construction,puts forward a research idea of smart dam construction and transformation,which coordinates the whole life cycle of dam planning and design,construction,impoundment and operation,and risk elimination and mitigation,and proposes the implementation path for further development of smart dam construction and management.The aim is to improve the dam safety capacity continuously and promote the transformation of the dam safety management industry from"engineering management"to"intelligent management"through the construction of smart dams.关键词
智能大坝/全生命期/智能改造/工程安全/信息技术/人工智能Key words
smart dam/whole life cycle/smart retrofit/engineering safety/information technology/artificial intelligence分类
建筑与水利引用本文复制引用
刘六宴,李宏恩,高长胜,向衍..智能大坝研究进展与发展路径思考[J].岩土工程学报,2025,47(10):2003-2014,12.基金项目
国家自然科学基金项目(U2443231) （U2443231）
国家重点研发计划项目(2022YFC3005403) （2022YFC3005403）
中央级公益性科研院所基本科研业务费专项资金项目(Y722003,Y724008,Y723007)This work was supported by National Natural Science Foundation of China(Grant No.U2443231),National Key Research and Development Program of China(Grant No.2022YFC3005403),and Fundamental Research Funds for Central-Level Non-profit Research Institutes(Grant Nos.Y722003,Y724008,Y723007). （Y722003,Y724008,Y723007）
