Damage detection (DD) is one of the primary goals of health monitoring of civil structures. Vibration-based techniques aim to identify the modal properties (or vibration characteristics) of structures and are one of the most popular approaches for structural damage detection. The use of vibration characteristics (natural frequencies, damping ratios, and mode shapes) for DD purposes is based on the premise that these characteristics change when the structure suffers damage, since the modal properties depend on the physical properties (mass, stiffness, and damping) of the structure. The use of output-only measurements (e.g., ambient vibration or AV) is the most popular approach for damage detection of civil structures. AV data recorded before and after the structure has potentially suffered damage can be used for DD. However, application of vibration-based DD using AV requires an accurate and reliable estimation of the modal properties and their variability (or uncertainty) in order to genuinely determine the existence of damage. This study presents a comprehensive statistical analysis of the identified modal properties of a full-scale five-story reinforced concrete building using AV data. The building specimen was tested on the NHERI@UCSD shake table in base-isolated and fixed-base configurations. On April 6, 2012, about two weeks before the start of the seismic tests in the base-isolated configuration, a dense array of twenty accelerometers was deployed on the structure and AV data were recorded continuously until May 18, 2012, three days after completion of the seismic tests in the fixed-base configuration. In its fixed-base configuration, the building was subjected to a sequence of six earthquake motions that progressively damaged the structure. Two popular methods of operational modal analysis are used to automatically identify the modal properties of the fixed-base building at different damage states using the recorded AV data. A statistical analysis of the identified modal parameters is performed to investigate the statistical variability and accuracy of the system identification results. The variability of the identified modal parameters due to environmental conditions is also investigated.
Bibliographical noteFunding Information:
The BNCS project was a collaboration between four academic institutions (University of California, San Diego, San Diego State University, Howard University, and Worcester Polytechnic Institute) and was funded by NSF-NEESR program , grant number CMMI-0936505 , the Englekirk Advisory Board , the Charles Pankow Foundation , and the California Seismic Safety Commission , and over 40 industry partners. A list of project participants may be found on the project website: http://chei.ucsd.edu/bncs/index.html . R. Astroza acknowledges the financial support from the Chilean National Agency for Research and Development (ANID) , FONDECYT research grant No. 11160009 . Opinions and findings in this study are those of the authors and do not necessarily reflect the views of the sponsors.
© 2022 Elsevier Ltd
- Operational modal analysis
- Shake table testing
- System identification