Conference proceeding
A vision-based technique for damage assessment of reinforced concrete structures
HEALTH MONITORING OF STRUCTURAL AND BIOLOGICAL SYSTEMS 2014, v 9064, pp 90642H-90642H-9
01 Jan 2014
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The most common damage assessment technique for concrete structures is visual inspection (VI). Condition assessed by VI is subjective in nature, meaning it depends on the experience, knowledge, expertise, measurement accuracy, mental attention, and judgment of the inspector carrying out the assessment. In many post-event assessments, cracks data including width and pattern provide the most indicative information about the health or damage state of the structure. Residual cracks are sometimes the only available data for VI. However, due to adjacent elastic members, earthquake displacement spectrum, or re-centering systems, these measurements may lead to erroneous decisions. To overcome this problem, this paper proposes a novel damage index based upon Fractal Dimension (FD) analysis of residual cracks as a complementary method for VI. FD can quantify crack patterns and enhance the routine inspection procedure by establishing a crack pattern recognition system. This algorithm was validated through an experimental study on a large scale reinforced concrete shear wall (RCSW). The results demonstrate the novel technique as a quite accurate estimator for damage grades and stiffness loss of the wall.
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Details
- Title
- A vision-based technique for damage assessment of reinforced concrete structures
- Creators
- Alireza Farhidzadeh - University at Buffalo, State University of New YorkArvin Ebrahimkhanlou - University at Buffalo, State University of New YorkSalvatore Salamone - University at Buffalo, State University of New York
- Contributors
- T Kundu (Editor)
- Publication Details
- HEALTH MONITORING OF STRUCTURAL AND BIOLOGICAL SYSTEMS 2014, v 9064, pp 90642H-90642H-9
- Series
- Proceedings of SPIE
- Publisher
- Spie-Int Soc Optical Engineering
- Number of pages
- 9
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000348027200064
- Scopus ID
- 2-s2.0-84902001286
- Other Identifier
- 991021890012704721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Biomedical
- Engineering, Civil
- Optics