Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage Detection

Prestressed concrete bridges built between 1960 and 1990 no longer meet today’s requirements due to loads and increasing mileage of higher loads that have increased since the bridges were designed. Prestressed concrete bridges are representative of Germany’s existing bridges. In order to deal with t...

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Main Authors: Andreas Döring, Markus Vogelbacher, Oliver Schneider, Jacob Müller, Stefan Hinz, Jörg Matthes
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Infrastructures
Subjects:
Online Access:https://www.mdpi.com/2412-3811/8/4/72
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author Andreas Döring
Markus Vogelbacher
Oliver Schneider
Jacob Müller
Stefan Hinz
Jörg Matthes
author_facet Andreas Döring
Markus Vogelbacher
Oliver Schneider
Jacob Müller
Stefan Hinz
Jörg Matthes
author_sort Andreas Döring
collection DOAJ
description Prestressed concrete bridges built between 1960 and 1990 no longer meet today’s requirements due to loads and increasing mileage of higher loads that have increased since the bridges were designed. Prestressed concrete bridges are representative of Germany’s existing bridges. In order to deal with the large number of ageing bridges, recalculations and measurements for control as well as bridge monitoring are an important means of support. For both, it is important to find features that are damage-sensitive as well as robust against measurement noise, vehicle parameters (dynamics, geometry, weight, etc.) and environmental influences (temperature, wind, etc.). In this paper, we present features for damage detection based on the influence line, which are investigated with respect to the above requirements by using the analytical solution of the Euler–Bernoulli beam and more complex numerical bridge simulations. In this context, we restrict ourselves to the damage caused by bending stress. The features are calculated on the basis of single vehicle crossings over the bridge for the strain in the longitudinal direction as well as for the deflection of the bridge at different sensor positions. The ratio-based features are compared with raw data and natural frequencies in a classification. Additionally, the sensor positioning is considered. The investigations shows that the ratio-based integrated influence lines are equivalent to or better than the modal parameters, especially when noise and temperature changes are taken into account.
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spelling doaj.art-5fabd2fc408247048bd5085d982f768f2023-11-17T19:44:59ZengMDPI AGInfrastructures2412-38112023-04-01847210.3390/infrastructures8040072Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage DetectionAndreas Döring0Markus Vogelbacher1Oliver Schneider2Jacob Müller3Stefan Hinz4Jörg Matthes5Institute for Automation and Applied Informatics (IAI), Karlsruhe Institute of Technology (KIT), 76344 Karlsruhe, GermanyInstitute for Automation and Applied Informatics (IAI), Karlsruhe Institute of Technology (KIT), 76344 Karlsruhe, GermanyBüro für Strukturmechanik, 96450 Coburg, GermanyBüro für Strukturmechanik, 96450 Coburg, GermanyInstitute of Photogrammetry and Remote Sensing (IPF), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, GermanyInstitute for Automation and Applied Informatics (IAI), Karlsruhe Institute of Technology (KIT), 76344 Karlsruhe, GermanyPrestressed concrete bridges built between 1960 and 1990 no longer meet today’s requirements due to loads and increasing mileage of higher loads that have increased since the bridges were designed. Prestressed concrete bridges are representative of Germany’s existing bridges. In order to deal with the large number of ageing bridges, recalculations and measurements for control as well as bridge monitoring are an important means of support. For both, it is important to find features that are damage-sensitive as well as robust against measurement noise, vehicle parameters (dynamics, geometry, weight, etc.) and environmental influences (temperature, wind, etc.). In this paper, we present features for damage detection based on the influence line, which are investigated with respect to the above requirements by using the analytical solution of the Euler–Bernoulli beam and more complex numerical bridge simulations. In this context, we restrict ourselves to the damage caused by bending stress. The features are calculated on the basis of single vehicle crossings over the bridge for the strain in the longitudinal direction as well as for the deflection of the bridge at different sensor positions. The ratio-based features are compared with raw data and natural frequencies in a classification. Additionally, the sensor positioning is considered. The investigations shows that the ratio-based integrated influence lines are equivalent to or better than the modal parameters, especially when noise and temperature changes are taken into account.https://www.mdpi.com/2412-3811/8/4/72structural health monitoringanomaly detectionbridge monitoring featuresinfluence lineinfluence line-based features
spellingShingle Andreas Döring
Markus Vogelbacher
Oliver Schneider
Jacob Müller
Stefan Hinz
Jörg Matthes
Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage Detection
Infrastructures
structural health monitoring
anomaly detection
bridge monitoring features
influence line
influence line-based features
title Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage Detection
title_full Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage Detection
title_fullStr Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage Detection
title_full_unstemmed Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage Detection
title_short Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage Detection
title_sort investigations of ratio based integrated influence lines as features for bridge damage detection
topic structural health monitoring
anomaly detection
bridge monitoring features
influence line
influence line-based features
url https://www.mdpi.com/2412-3811/8/4/72
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