Abstract It is important to conduct structural damage detection using only output time histories of structures under ambient excitations. Recently, an approach has been proposed for structural damage detection under ambient excitations using the synthesis of cross-correlation functions of partial structural responses and the extended Kalman filter (EKF). However, structural mass is assumed known in this approach. Although some methodologies have been presented for detecting damage due to relative structural mass and stiffness changes in chain-like systems, measurements of structural responses including acceleration, velocity, and displacement at each degree of freedom are required. This greatly limits the application of these methodologies. In this paper, without structural mass information, an algorithm is proposed to identify structural element mass and stiffness changes using only partial acceleration responses of chain-like systems under ambient excitations. First, based on the equations for cross-correlation functions of structural responses under ambient stationary excitations modeled as independent stationary white noise processes, EKF is utilized for identifying the structural element stiffness-mass coupled coefficients using only partial acceleration responses. Then, these coefficients are decoupled by cluster analysis and the least squares estimation to obtain structural element stiffness and mass changes. Furthermore, the proposed algorithm is extended for identifying chain-like structural element mass and stiffness changes under non-stationary ambient excitations assumed as time modulating white noises. The performances of the proposed algorithm are numerically investigated using the Phase I The American Society of Civil Engineers structural health monitoring benchmark building under stationary or non-stationary ambient excitations, respectively. Moreover, the experimental data with structural element mass and stiffness changes conducted at the Los Alamos National Laboratory are utilized to test the proposed algorithm.

中文翻译：

---

使用环境激励下链状系统的部分加速度响应识别结构元素质量和刚度变化

摘要 在环境激励下仅使用结构的输出时间历史进行结构损伤检测是很重要的。最近，已经提出了一种使用部分结构响应的互相关函数和扩展卡尔曼滤波器 (EKF) 的合成在环境激励下进行结构损伤检测的方法。然而，在这种方法中，假定结构质量是已知的。尽管已经提出了一些方法来检测由于链状系统中相对结构质量和刚度变化引起的损坏，但需要测量结构响应，包括每个自由度的加速度、速度和位移。这极大地限制了这些方法的应用。在本文中，在没有结构质量信息的情况下，提出了一种算法，仅使用链状系统在环境激励下的部分加速度响应来识别结构元素的质量和刚度变化。首先，基于环境静止激励下结构响应的互相关函数方程，建模为独立的静止白噪声过程，EKF 用于仅使用部分加速度响应来识别结构元件刚度-质量耦合系数。然后，通过聚类分析和最小二乘估计将这些系数解耦，以获得结构单元刚度和质量变化。此外，所提出的算法被扩展用于在假设为时间调制白噪声的非平稳环境激励下识别链状结构元件的质量和刚度变化。分别使用第一阶段美国土木工程师学会结构健康监测基准建筑物在静止或非静止环境激励下对所提出的算法的性能进行数值研究。此外，利用在洛斯阿拉莫斯国家实验室进行的结构元素质量和刚度变化的实验数据来测试所提出的算法。