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

Author(s): (Institute for Automation and Applied Informatics (IAI), Karlsruhe Institute of Technology (KIT), 76344 Karlsruhe, Germany)
ORCID (Institute for Automation and Applied Informatics (IAI), Karlsruhe Institute of Technology (KIT), 76344 Karlsruhe, Germany)
(Büro für Strukturmechanik, 96450 Coburg, Germany)
(Büro für Strukturmechanik, 96450 Coburg, Germany)
(Institute of Photogrammetry and Remote Sensing (IPF), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)
ORCID (Institute for Automation and Applied Informatics (IAI), Karlsruhe Institute of Technology (KIT), 76344 Karlsruhe, Germany)
Medium: journal article
Language(s): English
Published in: Infrastructures, , n. 4, v. 8
Page(s): 72
DOI: 10.3390/infrastructures8040072
Abstract:

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.

Copyright: © 2023 the Authors. Licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10722699
  • Published on:
    22/04/2023
  • Last updated on:
    10/05/2023
 
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