Bridge damage analysis under joint environmental and operational variability

One of the main challenges for bridge damage identification using monitoring data is to acquire sensitive damage features but insensitive to operational and environmental effects as well as noise. Specifically, the temperature as part of environmental variability can mask structural damages in bridg...

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Detalhes bibliográficos
Autores: Delgadillo, Rick M., Tenelema, Fernando J., Casas, Joan R.
Formato: artículo
Fecha de publicación:2023
País:Perú
Recursos:Universidad Peruana de Ciencias Aplicadas
Repositorio:UPC-Institucional
Idioma:inglés
OAI Identifier:oai:repositorioacademico.upc.edu.pe:10757/669631
Acesso em linha:https://doi.org/10.1080/15732479.2023.2243248
http://hdl.handle.net/10757/669631
Access Level:acceso embargado
Palavra-chave:Bridges
damage detection
environmental conditions
Hilbert-Huang transform
instantaneous phase difference
modal frequency
principal component analysis
temperature effect
variational mode decomposition
https://purl.org/pe-repo/ocde/ford#2.01.00
Descrição
Resumo:One of the main challenges for bridge damage identification using monitoring data is to acquire sensitive damage features but insensitive to operational and environmental effects as well as noise. Specifically, the temperature as part of environmental variability can mask structural damages in bridges. Principal Component Analysis (PCA) has been applied here as a well-known and robust technique for removing environmental variability and obtain damage-sensitive indices. As a first aim, PCA is used considering only ambient vibrations and the natural frequencies are considered as damage indicators. As a second objective, PCA in conjunction with Hilbert Huang Transform (HHT) and Variational Mode Decomposition (VMD) are applied to eliminate the environmental influence in transient vibrations due to traffic. The combined methodology is applied to the case of a numerical benchmark by using the Instantaneous Phase Difference (IPD) as novel vibration damage feature in the case of non-stationary vibrations. The results show that the proposed strategy to use the non-stationary vibration due to traffic instead of ambient vibration seems a promising tool for damage identification and, therefore, its capabilities in real bridge applications are worth exploring further when experimental data from real bridges will become available.