The accurate identification of modal parameters is a critical issue in the determination of features of civil structures. In this paper, a novel method based on the multisynchrosqueezing transform (MSST) is proposed to identify modal parameters, including natural frequencies, damping ratios and mode shapes of civil structures. The MSST consists of multiple operations of a synchrosqueezing transform so that the time-frequency representation of an analyzed signal becomes more concentrated, which allows more accurate decomposition of the signal. To identify modal parameters based on the MSST, first, the natural extraction technique is used to obtain a free vibration response from a measured ambient vibration response. Second, the free vibration response is decomposed into several modes by using the MSST, and mode shape vectors can be obtained from the decomposed modes for all measurements. Then, instantaneous phases and instantaneous amplitudes of the modes are obtained by using the Hilbert transform. Finally, a least-squares curve fitting technique is performed on the instantaneous phases and instantaneous amplitudes to extract natural frequencies and damping ratios. Two numerical examples, a 3-degree-of-freedom free vibration response signal and a four-story frame steel structure subjected to environmental vibration, are used to demonstrate the applicability of the MSST-based method. In addition, an experimental validation based on a pedestrian overpass, located in Tufts University, United States, is conducted. Case analyses indicate that the MSST-based method can easily identify high-quality natural frequencies and damping ratios from measurements of structures.

模态参数的准确识别是确定土木结构特征的关键问题。在本文中，提出了一种基于多同步压缩变换（MSST）的新方法来识别土木结构的模态参数，包括固有频率、阻尼比和模态振型。MSST 由同步压缩变换的多个操作组成，以便分析信号的时频表示变得更加集中，从而可以更准确地分解信号。为了基于 MSST 识别模态参数，首先，使用自然提取技术从测量的环境振动响应中获得自由振动响应。其次，使用 MSST 将自由振动响应分解为几种模式，可以从所有测量的分解模式中获得模式形状向量。然后，利用希尔伯特变换获得模态的瞬时相位和瞬时幅度。最后，对瞬时相位和瞬时振幅执行最小二乘曲线拟合技术以提取固有频率和阻尼比。两个数值例子，一个 3 自由度自由振动响应信号和一个四层框架钢结构受到环境振动，用于证明基于 MSST 的方法的适用性。此外，还进行了基于位于美国塔夫茨大学的行人天桥的实验验证。