TY - JOUR A1 - Teng, Jun A1 - Tang, De-Hui A1 - Zhang, Xiao A1 - Hu, Wei-Hua A1 - Said, Samir A1 - Rohrmann, Rolf G. T1 - Automated modal analysis for tracking structural change during construction and operation phases T2 - Sensors N2 - 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. PB - MDPI AG CY - Basel, Switzerland KW - Automated Modal Analysis for Tracking Structural Change during Construction and Operation Phases PY - 2019 UR - https://opus4.kobv.de/opus4-bam/frontdoor/index/index/docId/47511 AN - OPUS4-47511 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-475116 UR - https://www.mdpi.com/1424-8220/19/4/927/pdf SN - 1424-8220 VL - 19 IS - 4 SP - 927, 1 EP - 23 AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany