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Investigation on the damage identification of bridges using distributed long-gauge dynamic macrostrain response under ambient excitation

机译:环境激励下基于分布式大应变动力大应变响应的桥梁损伤识别研究

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摘要

In this study, an output-only method for extraction of modal macrostrain and damage identification of bridges under ambient excitation is presented. It is theoretically proved that the modal macrostrain within the gauge length of a long-gauge macrostrain sensor is uniquely determined by the peak value of the power spectral density (PSD) of dynamic macrostrain response. Then damage occurred within the gauge length of a sensor can be identified by the ratio change between the peak value of PSD of this sensor response and that of the reference sensor response. The damage extent has also been verified to have corresponding relationship with the ratio change. Numerical simulation was carried out to confirm the feasibility of the proposed method. Analysis results of the numerical simulation reveal that the maximum error of the identified modal macrostrain relative to that of the modal analysis is 3%. Results of simulation show that the proposed PSD-based method can not only accurately localize the damage but also assess the damage extent. The influence of several typical excitations on real bridges was also investigated that further proves the robustness of the method. It is worth mentioning that only the first-order mode is necessary for the method to identify damage. Finally, the proposed method is employed for condition assessment of a real bridge located in New Jersey, wherein 17 long-gauge macrostrain sensors with the gauge length of I m were distributedly arranged along the critical region of the girder. Analysis results of the field measurements further verify that the PSD-based method can be utilized to assess the damage state of structures under ambient excitation.
机译:在这项研究中,提出了一种仅输出的模态大应变的提取方法,并在环境激励下识别桥梁的损伤。从理论上证明,长规格宏应变传感器的标距内的模态宏应变是由动态宏应变响应的功率谱密度(PSD)的峰值唯一确定的。然后,可以通过该传感器响应的PSD峰值与参考传感器响应的PSD峰值之间的比率变化来识别在传感器的标距内发生的损坏。损坏程度也已被验证与比率变化具有对应关系。数值模拟证实了该方法的可行性。数值模拟分析结果表明,所识别的模态大应变相对于模态分析的最大误差为3%。仿真结果表明,所提出的基于PSD的方法不仅可以准确地定位损伤,而且可以评估损伤程度。还研究了几种典型激励对真实桥梁的影响,进一步证明了该方法的鲁棒性。值得一提的是,识别损坏的方法只需要一阶模式。最后,将所提出的方法用于新泽西州一座真实桥梁的状态评估,其中沿梁的关键区域分布了17个标距为I m的长尺寸宏应变传感器。现场测量的分析结果进一步验证了基于PSD的方法可用于评估环境激发下结构的损伤状态。

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