A data-driven identification technique is used to implement an effective change detection approach for uncertain multi-degree-of-freedom chainlike systems. The information about mass properties of system is not required in the process of identification, but only the excitation information and the corresponding structural dynamic response are needed to obtain a stochastic representation of estimated changes in stiffness-like and damping-like structural coefficients. The validity and reliability of the data-driven technique in uncertain chain-like systems are further verified by using shaking table experimental data from a five-floor shear structure. The results of this study show that this method can not only accurately detect the existence of physical structural changes but also accurately locate the region of the changes and determine the degree of structural changes. Additionally, a finite element model of the test shear structure was developed and simulated to verify the effectiveness of this change-detection approach.

中文翻译：

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链状不确定性嵌入结构的数据驱动系统参数变化检测

数据驱动的识别技术用于实现不确定的多自由度链状系统的有效变化检测方法。在辨识过程中不需要系统的质量特性信息，只需要激励信息和相应的结构动力响应，即可获得类刚度和类阻尼结构系数估计变化的随机表示。通过使用来自五层剪力结构的振动台实验数据，进一步验证了数据驱动技术在不确定链状系统中的有效性和可靠性。研究结果表明，该方法不仅可以准确检测物理结构变化的存在，而且可以准确定位变化的区域，判断结构变化的程度。此外，还开发并模拟了测试剪切结构的有限元模型，以验证这种变化检测方法的有效性。