多尺度视角下桥梁损伤检测与服役性能评估研究综述OA
Multi-scale perspective on bridge damage detection and service performance evaluation research:a review
桥梁检测与服役性能评估是保障桥梁安全运营的核心.基于多尺度视角,系统梳理桥梁损伤检测与评估领域的研究进展及未来趋势,并从宏观、中观及亚微观尺度展开探讨.在宏观尺度上,深入剖析桥梁特征检测方法的演变,揭示其向基于车辆响应的快速检测技术转型的趋势;在中观及亚微观尺度上,鉴于桥梁表观损伤的复杂性,现有研究重点聚焦基计算机视觉的识别方法.在服役性能评估方面,归纳了现有桥梁短期状态评估与长期状态预测的方法.综合分析表明,当前桥梁检测技术在识别桥梁损伤特征上已具成效,但未来仍需聚焦基车辆响应的宏观损伤识别与基于计算机视觉的中观及亚微观损伤识别,这两大方向均展现出巨大的应用潜力.未来的研究应进一步优化车-桥耦合响应模型,提升其在不同宏观尺度损伤形式下的适用性;深入研究中观及亚微观损伤图像与桥梁力学特征的映射关系;加强多尺度损伤相关性研究,以提高检测准确性;从工程实际出发,探索更具实用性的桥梁服役性能评估方法.
Bridge inspection and service performance evaluation are critical technologies for ensuring the safe operation of bridges.Utilising a multi-scale perspective,the paper systematically reviews the academic progress and future trends in the field of bridge damage detection and assessment.The research is explored from three different scales:macro,meso,and sub-micro.A thorough analysis of the evolution of bridge feature detection methods is presented at the macro level,illuminating the trend of transformation toward rapid detection technologies based on vehicle responses.At the meso-and sub-micro scales,the complexity of bridge surface damage has resulted in research focusing on recognition methods based on computer vision.In terms of service performance evaluation,the extant methods for short-term bridge condition assessment and long-term condition prediction are summarized.The comprehensive analysis shows that the current bridge inspection technology has been effective in identifying bridge damage features.However,future research should still focus on two directions:macro damage identification based on vehicle response and meso-and sub-micro damage identification based on computer vision.Both directions have shown great application potential.Future research should further optimize vehicle-bridge coupled response models and improve their applicability to different forms of macro-scale damage;Study the mapping relationships between meso-and sub-micro-scale damage images and bridge mechanical characteristics;conduct research on multi-scale damage correlation to improve detection accuracy;and explore more practical evaluation methods for bridge service performance based on engineering practice.
李泽伟;杨永清;谢明志;黄胜前;郑小刚;余华丽;邹凌晨
西南交通大学 土木工程学院,成都 610031||西南交通大学 桥梁智能与绿色建造全国重点实验室,成都 610031西南交通大学 土木工程学院,成都 610031||西南交通大学 桥梁智能与绿色建造全国重点实验室,成都 610031西南交通大学 土木工程学院,成都 610031||西南交通大学 桥梁智能与绿色建造全国重点实验室,成都 610031西南交通大学 土木工程学院,成都 610031四川交大工程检测咨询有限公司,成都 610031四川交大工程检测咨询有限公司,成都 610031中北大学 经济与管理学院,太原 030051
交通工程
桥梁检测服役性能评估多尺度损伤车桥耦合计算机视觉
bridge inspectionservice performance assessmentmulti-scale damagevehicle-bridge couplingcomputer vision
《土木与环境工程学报(中英文)》 2026 (4)
154-169,16
国家自然科学基金(52322811)四川省科技计划(2020YJ0081)四川交大工程检测咨询有限公司科研项目(KYL202305-0143) National Natural Science Foundation of China(No.52322811)Sichuan Science and Technology Program(No.2020YJ0081)Scientific Program of Sichuan Jiaoda Engineering Testing Consulting Co.,Ltd.(No.KYL202305-0143)
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