Vibration-based condition identification of bolted connections can benefit the effective maintenance and operation of steel structures. Existing studies show that modal parameters are not sensitive to such damage as loss of preload. In contrast, structural responses in the time domain contain all the information regarding a structural system. Therefore, this study aims to exploit time-domain data directly for condition identification of bolted connection. Finite element model updating is carried out based on the vibration test data of a steel frame, with various combinations of bolts with loss of preload, representing different damage scenarios. It is shown that the match between the numerically simulated and measured acceleration responses of the steel frame cannot be achieved. The reason is that time-dependent nonlinearity is generated in bolted connections during dynamic excitation of the steel frame. To capture the nonlinearity, a virtual viscous damper is proposed. By using the proposed damper alongside the updated system matrices of the finite element model, the time-domain acceleration responses are estimated with great consistency with the measured responses. The results demonstrate that the proposed virtual damper is not only effective in estimating the time-domain acceleration responses in each damage case, but also has the potential for condition identification of bolted connections with such small damage as just one bolt with loss of preload. It can also be applied to other challenging scenarios of condition identification, where modal parameters are not sensitive to the damage.

基于振动的螺栓连接状态识别有助于钢结构的有效维护和运行。现有研究表明，模态参数对预紧力损失等损坏不敏感。相比之下，时域中的结构响应包含有关结构系统的所有信息。因此，本研究旨在直接利用时域数据进行螺栓连接的状态识别。有限元模型更新是基于钢框架的振动试验数据进行的，具有预紧力损失的螺栓的各种组合，代表不同的损坏场景。结果表明，钢框架的数值模拟和实测加速度响应无法匹配。原因是在钢框架的动态激励过程中，螺栓连接中会产生与时间相关的非线性。为了捕捉非线性，提出了一种虚拟粘性阻尼器。通过将所提出的阻尼器与有限元模型的更新系统矩阵一起使用，估计时域加速度响应与测量响应具有很大的一致性。结果表明，所提出的虚拟阻尼器不仅可以有效地估计每种损坏情况下的时域加速度响应，而且还具有识别螺栓连接的条件，这种螺栓连接的损坏很小，例如只有一个螺栓失去预紧力。它还可以应用于其他具有挑战性的条件识别场景，其中模态参数对损坏不敏感。