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高坝水下缺陷检测与诊断评估:现状与挑战

向衍 王亚坤 陈哲 戴波 陈思宇 沈光泽

水科学进展2025,Vol.36Issue(4):537-552,16.
水科学进展2025,Vol.36Issue(4):537-552,16.DOI:10.14042/j.cnki.32.1309.2025.04.001

高坝水下缺陷检测与诊断评估:现状与挑战

Underwater defect detection and diagnosis assessment for high dams:current status and challenges

向衍 1王亚坤 2陈哲 3戴波 1陈思宇 4沈光泽1

作者信息

  • 1. 南京水利科学研究院,江苏 南京 210029||水利部大坝安全管理中心,江苏 南京 210029
  • 2. 南京水利科学研究院,江苏 南京 210029
  • 3. 河海大学信息科学与工程学院,江苏 南京 210098
  • 4. 南京水利科学研究院,江苏 南京 210029||中国电建集团昆明勘测设计研究院有限公司,云南 昆明 650000
  • 折叠

摘要

Abstract

High dams and large reservoirs are critical infrastructure that support water safety and security systems.Their safe and stable operation plays a vital role in ensuring sustainable socio-economic development and public safety.However,certain defects develop beneath the water surface,rendering them difficult to detect and potentially threatening the long-term safety and reliability of these structures.This study reviews domestic and international cases of underwater distress in high dams and systematically summarizes existing defect detection methods and equipment,including optical and acoustic imaging techniques.It also highlights recent advances in underwater defect detection,damage identification,construction within deep-water digital twin frameworks,and structural health diagnosis and assessment.Key scientific challenges are identified,such as acoustic-optical fusion imaging under multi-field perturbations,high-resolution detection of deep-water defects,multi-source data fusion-based characterization,error propagation between underwater and land-based digital twin systems,and rapid defect diagnosis.The aim is to provide technological support for precise underwater detection and enhance safety assessment of high dams.

关键词

缺陷识别/高坝大库/水下检测/数字孪生/结构健康诊断

Key words

defect identification/high dams and large reservoirs/underwater inspection/digital twin/structural health monitoring

分类

建筑与水利

引用本文复制引用

向衍,王亚坤,陈哲,戴波,陈思宇,沈光泽..高坝水下缺陷检测与诊断评估:现状与挑战[J].水科学进展,2025,36(4):537-552,16.

基金项目

国家重点研发计划项目(2022YFC3005405) (2022YFC3005405)

国家自然科学基金项目(U23B20150)The study is financially supported by the National Key R&D Program of China(No.2022YFC3005405)and the National Natural Science Foundation of China(No.U23B20150). (U23B20150)

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