Abstract
Robust elimination of the environmental and operational variability from monitored vibration properties is essential for accurate vibration-based damage detection in civil engineering structures. This study uses the two-story wooden frame model of a shear building placed in real ambient conditions to extract natural frequencies of the structure by means of automated operational modal analysis. Further, inputoutput and output-only environmental models based on multiple linear regression and principal component analysis are developed to remove environmental influences from the identified frequency time series. This study aims to assess the robustness and performance of those methods in detecting damage and structural changes in civil structures exposed to highly variable environmental and operational conditions. The initial results show the superiority of the principal component analysis for modelling environmental effects and damage detection under challenging environments
| Original language | English |
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| Title of host publication | Proceedings of the 9th International Operational Modal Analysis Conference (IOMAC) |
| Editors | Carlos E. Ventura, Mehrtash Motamedi, Alexander Mendler, Manuel Aenlle-Lopez |
| Publisher | International Operational Modal Analysis Conference (IOMAC) |
| Publication date | 2022 |
| Pages | 286-293 |
| ISBN (Electronic) | 978-84-09-44336-9 |
| Publication status | Published - 2022 |
| Event | 9th International Operational Modal Analysis Conference - Vancouver, Canada Duration: 3 Jul 2022 → 6 Jul 2022 |
Conference
| Conference | 9th International Operational Modal Analysis Conference |
|---|---|
| Country/Territory | Canada |
| City | Vancouver |
| Period | 03/07/2022 → 06/07/2022 |
| Sponsor | HBK, Ommatidia LiDAR S.L., Structural Engineers Association (SEA), Structural Vibration Solutions A/S |
Keywords
- Vibration-based monitoring
- Operational and environmental factors
- Damage detection