A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Vibration-Based Damage Identification of a Steel Frame Using an Output-Only Algorithm
There are various approaches used by different research groups to identify structures and structural changes, and the success of a certain methodology may depend on the context in which it is applied. Therefore, it is crucial to verify promising methodologies by testing them on different structures and damage cases. The objective of this study is to investigate a statistical pattern recognition-based method of Structural Health Monitoring (SHM) using a laboratory structure. Sophisticated finite element models and traditional modal parameters are not used in the implementation of the statistical pattern recognition techniques, as they require significant user interaction. Instead, the statistical approaches presented in this paper are solely based on the signal analysis of the measured vibration data. This makes this approach attractive for the development of an automated health monitoring system. A large-scale laboratory structure was constructed at the Qatar University structures laboratory, and a large dataset of vibration signals was obtained under several structural damage scenarios. This paper suggests a statistical moments-based technique to identify damage using the vibration signals. The method does not require labor-intensive supervised learning, and only acceleration sensor data is required to detect damage. Overall, the proposed approach has the potential to be a cost-effective and efficient solution for SHM of various infrastructures.
Vibration-Based Damage Identification of a Steel Frame Using an Output-Only Algorithm
There are various approaches used by different research groups to identify structures and structural changes, and the success of a certain methodology may depend on the context in which it is applied. Therefore, it is crucial to verify promising methodologies by testing them on different structures and damage cases. The objective of this study is to investigate a statistical pattern recognition-based method of Structural Health Monitoring (SHM) using a laboratory structure. Sophisticated finite element models and traditional modal parameters are not used in the implementation of the statistical pattern recognition techniques, as they require significant user interaction. Instead, the statistical approaches presented in this paper are solely based on the signal analysis of the measured vibration data. This makes this approach attractive for the development of an automated health monitoring system. A large-scale laboratory structure was constructed at the Qatar University structures laboratory, and a large dataset of vibration signals was obtained under several structural damage scenarios. This paper suggests a statistical moments-based technique to identify damage using the vibration signals. The method does not require labor-intensive supervised learning, and only acceleration sensor data is required to detect damage. Overall, the proposed approach has the potential to be a cost-effective and efficient solution for SHM of various infrastructures.
Vibration-Based Damage Identification of a Steel Frame Using an Output-Only Algorithm
Lecture Notes in Civil Engineering
Alam, M. Shahria (editor) / Hasan, G. M. Jahid (editor) / Billah, A. H. M. Muntasir (editor) / Islam, Kamrul (editor) / Sakib, Nazmuz (author) / Rana, Shohel (author)
International Conference on Advances in Civil Infrastructure and Construction Materials ; 2023 ; Dhaka, Bangladesh
2024-08-31
11 pages
Article/Chapter (Book)
Electronic Resource
English
Structural health monitoring , Statistical pattern recognition , Vibration signals , Laboratory structures , Damage identification , Automated system , Statistical moment analysis Engineering , Construction Management , Structural Materials , Building Construction and Design , Geoengineering, Foundations, Hydraulics , Geotechnical Engineering & Applied Earth Sciences
Damage Localization of Output-Only Frame Systems Using Stochastic Subspace Identification
| British Library Conference Proceedings | 2012
Vibration Based Damage Assessment of a Steel Frame Structure Using Support Vector Machine Algorithm
| Springer Verlag | 2025
Output-only substructural identification for local damage detection
| British Library Conference Proceedings | 2010
Damage Assessment Using Stiffness Matrix Decomposition and Output-Only Modal Identification
| Springer Verlag | 2021
| British Library Conference Proceedings | 2002