基于高分辨率ECOMAC的桥梁结构损伤识别∗
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马宏伟,男,1966年4月生,博士、教授。主要研究方向为结构冲击动力学、结构安全与预警。E-mail: mahongwei@dgut.edu.cn

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TN911.6;TU312+.3

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广东省重点领域研发计划资助项目(2019B111106001);国家自然科学基金资助项目(52178289);广东省普通高校机器人与智能装备重点实验室资助项目(2017KSYS009);东莞理工学院机器人与智能装备创新中心资助项目(KCYCXPT2017006)


Damage Identification of Bridge Structure Based on High‑Resolution Enhanced Coordinated Modal Assurance Criterion
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    摘要:

    为了达到精确定位损伤的目的,提出了利用少量传感器信息进行桥梁高分辨率全模态振型识别,获得高分辨率的全桥协调模态置信因子(enhanced coordinate modal assurance criteria,简称ECOMAC)这一动力指纹参数的方法。利用特征正交分解直接分析移动车辆荷载作用下桥梁上的少量传感器所测位移响应,获得主成分矩阵,将主成分矩阵通过低通滤波即可获得高分辨率的模态振型。利用高分辨率模态振型获得高分辨率的协调模态置信因子,并作为损伤指标进行损伤定位。为了验证该方法的有效性,对一梁桥进行数值仿真和实验。数值模拟和实验结果均表明,基于少量传感器下利用高分辨率的协调模态置信因子能够精确识别损伤。

    Abstract:

    A method to identify the high-resolution full modal shapes of the bridge with a limited number of sensors is proposed. Then the high-resolution dynamic fingerprint parameter, enhanced coordinate modal assurance criteria (ECOMAC), of the whole bridge can be obtained, so as to achieve the purpose of damage localization. In this method, the displacement responses measured by a limited number of sensors on the bridge under a moving vehicle load are analyzed by proper orthogonal decomposition, leading to obtaining the principal component matrix. The high-resolution modal shapes can be obtained by using the low-pass filter on the principal component matrix. Then the high-resolution enhanced coordinate modal assurance criterion can be obtained by using the identified high-resolution modal shapes, which can be used as the damage index for damage localization. In order to verify the effectiveness of the method, a simple beam bridge is simulated and test in the lab. The numerical and experimental results show that the damage can be identified with the proposed method.

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历史
  • 收稿日期:2022-09-16
  • 最后修改日期:2022-10-27
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  • 在线发布日期: 2023-03-09
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