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Detecting generalized dynamic inter-relationship in a frame experiment with measures of information flow and interdependence

机译:通过信息流和相互依赖性的度量在框架实验中检测广义动态相互关系

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摘要

Structural system identification, historically, has largely consisted of seeking linear relationships among vibration time series data, e.g., auto/cross-correlations, modal analysis, ARMA models, etc. This work considers how dynamical relationships may be viewed in terms of 'information flow' between different points on a structure. Information or interdependence metrics (e.g., time-delayed mutual information) are able to capture both linear and nonlinear aspects of the dynamics, including higher-order correlations. This work computes information-based metrics on a frame experiment where nonlinearity is introduced by the loosening of a bolt. Both linear and nonlinear measures of dynamical interdependence are then used to assess the degree of degradation to the joint. Results indicate clear differences in the way linear and nonlinear measures quantify the bolt loosening.
机译:从历史上看,结构系统的识别主要是在振动时间序列数据之间寻找线性关系,例如自动/互相关,模态分析,ARMA模型等。这项工作考虑了如何从“信息流”的角度看动力学关系。在结构上不同点之间。信息或相互依存性度量标准(例如,时间延迟的互信息)能够捕获动力学的线性和非线性方面,包括高阶相关性。这项工作是在框架实验中计算基于信息的指标,在​​该实验中,螺栓的松动会引入非线性。然后使用动力学相互依赖的线性和非线性度量来评估关节的退化程度。结果表明,线性和非线性措施量化螺栓松动的方式存在明显差异。

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