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Modal parameter based structural identification using input-output data: Minimal instrumentation and global identifiability issues

机译:使用输入-输出数据的基于模态参数的结构识别:最小化仪器和全局可识别性问题

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摘要

It is of interest to the modal testing and structural health monitoring community to be able to identify the mass and stiffness parameters of a system from its vibration response measurements. On the other hand, incomplete instrumentation of the monitored system results in measured mode shapes which are incomplete and may lead to non-unique identification results. In this study, the problem of mass normalized mode shape expansion, and subsequent physical parameter identification, for shear-type structural systems with input-output measurements is investigated. While developing a mode shape expansion algorithm, the issue of global identifiability of the system is also addressed vis-a-vis instrumentation set-ups. Several possible minimal and near-minimal instrumentation set-ups which guarantee a unique estimation of the unmeasured mode shape components from the measured components are identified for various experimental designs. An input-output balance approach, applicable to any general structural model, is proposed to mass normalize the mode shape components observed at the instrumented degrees of freedom. Using the proposed mode shape expansion and the input-output balance procedures, along with the modal orthogonality relations, the mass and stiffness matrices of the system can be estimated. The advantage of the algorithm lies in its ability to obtain a reliably accurate identification using the minimal necessary instrumentation with no a priori mass or stiffness information. The performance of the proposed algorithm is finally discussed through numerical simulations of forced vibration experiments on a 7 degree of freedom shear-type system.
机译:模态测试和结构健康监测界感兴趣的是,能够从系统的振动响应测量中识别出系统的质量和刚度参数。另一方面,对被监视系统的不完整检测会导致测量模式的形状不完整,并可能导致识别结果不唯一。在这项研究中,研究了具有输入-输出测量结果的剪切型结构系统的质量归一化模式形状扩展和随后的物理参数识别问题。在开发模式形状扩展算法时,还针对仪器设置解决了系统的全局可识别性问题。针对各种实验设计,确定了几种可能的最小和接近最小的仪器设置,这些设置可确保从测量的分量中对未测量的模式形状分量进行唯一估计。提出了一种适用于任何通用结构模型的输入-输出平衡方法,以对在仪器自由度上观察到的模态形状分量进行质量归一化。使用所提出的模式形状扩展和输入输出平衡程序以及模态正交关系,可以估计系统的质量和刚度矩阵。该算法的优势在于它能够使用最小的必要仪器获得可靠的准确识别,而无需先验质量或刚度信息。最后,通过在7自由度剪切型系统上进行强迫振动实验的数值模拟,讨论了所提出算法的性能。

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