Journal
SENSORS
Volume 19, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/s19040927
Keywords
automated modal analysis (AMA); system model order; density-based spatial clustering of applications with noise (DBSCAN); continuous dynamic monitoring; temperature effect
Funding
- National Natural Science Foundation of China [51878226]
- Research Project of Knowledge Innovation Plan in Shenzhen [JCYJ20160531193340540]
- Guangdong Provincial Natural Science Foundation [2017A030313292]
- Fundamental Research Funds for the Central Universities
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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.
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