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Experimental and operational modal analysis of a bio-composite pedestrian bridge

  • With the aim of reducing the carbon footprint of the construction industry, three pedestrian bridges, are currently being developed as Smart Circular Bridges (SCB). The bridges innovate through the use of a novel bio-composite material and by incorporating Structural Health Monitoring (SHM) technology, consisting of accelerometers and embedded optical strain sensors. This paper discusses the SHM setup and gives initial results from the first installed SCB. Analysis from a controlled test, consisting of an experimental modal analysis when the bridge was still in the factory, is compared to results found from a field test during the first months of operational use. Here, the acceleration data is processed using automated operational modal analysis. The effect of environmental variables on tracked frequencies and a strategy for simplifying datanormalization of the dynamic properties are detailed. Finally, alternative machine learning strategies could be used to detect anomalies in theWith the aim of reducing the carbon footprint of the construction industry, three pedestrian bridges, are currently being developed as Smart Circular Bridges (SCB). The bridges innovate through the use of a novel bio-composite material and by incorporating Structural Health Monitoring (SHM) technology, consisting of accelerometers and embedded optical strain sensors. This paper discusses the SHM setup and gives initial results from the first installed SCB. Analysis from a controlled test, consisting of an experimental modal analysis when the bridge was still in the factory, is compared to results found from a field test during the first months of operational use. Here, the acceleration data is processed using automated operational modal analysis. The effect of environmental variables on tracked frequencies and a strategy for simplifying datanormalization of the dynamic properties are detailed. Finally, alternative machine learning strategies could be used to detect anomalies in the spectrum or detect events occurring on the bridge from SHM data only.…show moreshow less

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Metadaten
Author:M. Weil, Y. Bel-Hadj, Adelmo Fernandes, W. Weijtjens, C. Devriendt
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/102097
URL:http://past.isma-isaac.be/downloads/isma2022/proceedings/Contribution_524_proceeding_3.pdf
ISBN:9789082893151OPAC
Parent Title (English):ISMA 2022 - International Conference on Noise and Vibration Engineering, Leuven, Belgium, 12-14 September 2022
Publisher:KU Leuven, Departement Werktuigkunde (LMSD)
Place of publication:Leuven
Type:Conference Proceeding
Language:English
Date of Publication (online):2023/02/15
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2023/02/15
First Page:1436
Last Page:1449
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management / Professur für Mechanical Engineering
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten

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