Cited by 60Structural Health Monitoring TechniquesInfrastructure Maintenance and MonitoringMachine Fault Diagnosis Techniques

Ensemble classification method for structural damage assessment under varying temperature

Fallahian, Milad, Khoshnoudian, Faramarz, Meruane, Viviana·2018·Structural Health Monitoring

Abstract

Vibration-based damage assessment approaches use modal parameters, such as frequency response functions, mode shapes, and natural frequencies, as indicators of structural damage. Nevertheless, these parameters are sensitive not only to damage but also to temperature variations. Most civil engineering structures are exposed to varying environmental conditions, thus hindering vibration-based damage assessment. Therefore, in this article, a new damage assessment algorithm based on pattern recognition is proposed to scrutinize the healthy state of a structure in the presence of uncertainties such as noise and temperature. The algorithm adopts a combination of couple sparse coding and deep neural network as an ensemble system to assess damage. The proposed method is validated using a numerical model of a truss bridge and experimental data of the I-40 bridge. The results demonstrate its efficiency in the localization and quantification of damages under varying temperature conditions.

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Crossref · 10.1177/1475921717717311

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Authors
Fallahian, M., Khoshnoudian, F., & Meruane, V.
Affiliations
  • Amirkabir University of Technology (IR)
  • University of Chile (CL)
Corresponding author
Khoshnoudian, Faramarz
Venue
Structural Health Monitoring
Published
2017-07-07
Volume
17
Issue
4
Pages
747-762
ISSN
  • 1475-9217 (ISSN-L)
  • 1741-3168
OpenAlex
W2748435964
Cited by
60
References
53
Citations by year
2026: 4 · 2025: 6 · 2024: 8 · 2023: 9 · 2022: 7 · 2021: 10 · 2020: 12 · 2019: 3 · 2018: 1
FWCI
4.58
Type
journal article
Language
en
Open access
closed
Locations
  • Structural Health Monitoring (publishedVersion)
  • Universidad de Chile (submittedVersion)
Topics
  • Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
  • Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
  • Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
Keywords
structural damage assessment, vibration-based damage detection, temperature variation, ensemble classification, sparse coding, deep neural network, pattern recognition, modal parameters, damage localization, damage quantification, truss bridges, noise robustness

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