Dokument-ID Dokumenttyp Autoren/innen Persönliche Herausgeber/innen Haupttitel Abstract Auflage Verlagsort Verlag Herausgeber (Institution) Erscheinungsjahr Titel des übergeordneten Werkes Jahrgang/Band ISBN Veranstaltung Veranstaltungsort Beginndatum der Veranstaltung Enddatum der Veranstaltung Ausgabe/Heft Erste Seite Letzte Seite URN DOI Lizenz Datum der Freischaltung OPUS4-47511 Zeitschriftenartikel Teng, Jun; Tang, De-Hui; Zhang, Xiao; Hu, Wei-Hua; Said, Samir; Rohrmann, Rolf G. Automated modal analysis for tracking structural change during construction and operation phases 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. Basel, Switzerland MDPI AG 2019 Sensors 19 4 927, 1 23 urn:nbn:de:kobv:b43-475116 10.3390/s19040927 https://creativecommons.org/licenses/by/4.0/deed.de 2019-03-11