Abstract
The problem of output-only stochastic identification of a Time-Varying (TV) laboratory structure is considered for the first time via a Functional Series Time-Dependent AutoRegressive Moving Average (FS-TARMA) approach. The approach is based on the modelling of a single non-stationary vibration response via a non-stationary parametric FS-TARMA model. The steps and facets of the identification procedure are presented, and the obtained model is used for structural characteristics recovery and vibration signal analysis. For purposes of comparison, multiple “frozen-configuration” stationary experiments are also carried out and a sequence of “frozen” stationary models are identified. The results of the study demonstrate the applicability, effectiveness, and high accuracy of the non-stationary FS-TARMA approach in capturing and analyzing the TV structural dynamics.
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