Abstract
The automated modal analysis (AMA) technique has attracted significant interest over the last few years, because it can track variations in modal parameters and has the potential to detect structural changes. In this paper, an improved density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean the abnormal poles in a stabilization diagram. Moreover, the optimal system model order is also discussed to obtain more stable poles. A numerical simulation and a full-scale experiment of an arch bridge are carried out to validate the effectiveness of the proposed algorithm. Subsequently, the continuous dynamic monitoring system of the bridge and the proposed algorithm are implemented to track the structural changes during the construction phase. Finally, the artificial neural network (ANN) is used to remove the temperature effect on modal frequencies so that a health index can be constructed under operational conditions.
Highlights
The status monitoring of full-scale structures by applying operational modal analysis (OMA) has become more attractive because it can characterize the structural behavior under operational conditions [1]
Though the key algorithm of the OMA technique, such as the subspace stochastic identification (SSI) method [3], can be automated in order to track the evolution of modal parameters and detect structural changes under operational conditions [10,11,12,13], some obstacles still exist for a fully automated modal analysis (AMA) procedure
This may partially result from the fact that some of the significant information identification results spread gradually due to the effect of noise
Summary
The status monitoring of full-scale structures by applying operational modal analysis (OMA) has become more attractive because it can characterize the structural behavior under operational conditions [1]. Though the key algorithm of the OMA technique, such as the subspace stochastic identification (SSI) method [3], can be automated in order to track the evolution of modal parameters and detect structural changes under operational conditions [10,11,12,13], some obstacles still exist for a fully automated modal analysis (AMA) procedure. They are summarized as follows: Regarding the SSI method, the modal parameters are identified by interpreting the stabilization diagram. The remaining residuals are used to construct the damage sensitive indices
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