1 April 2016 Small-strain measurement in bridge connections using the digital image correlation (DIC) technique
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Abstract
Structural health monitoring (SHM) is emerging as a vital tool to help civil engineers improve the safety, maintainability, and reliability of critical structures and assists infrastructure owners with timely information for the continued safe and economic operation of their structure. SHM involves implementing a strategy that identifies and characterizes damage or undesirable performance in engineering structures. The goal of this research project was to determine the smallest strains measurable using standard digital image correlation (DIC) based SHM equipment. This practical investigation that had strong ties to the industry was motivated by damage observed in a real-world bridge, which was initially undetected. Its early detection would have led to reduced repair costs. To accomplish the aforementioned goal, tests were performed on a laboratory specimen that replicated a steel beam-to-column connection of the concerned bridge, involving progressively loading it in a manner in which it was loaded in the actual bridge, while simultaneously measuring the strains that developed in it using the aforementioned DIC-based equipment and software. Under the controlled conditions in the laboratory, the minimum resolution of the state-of-the-art system used in this investigation was determined. Due to the challenges faced in making these small-strain measurements even under highly controlled laboratory conditions, it was concluded that it is currently unrealistic to use the existing DIC technology in a real-world situation to measure strains as small as those that would need to be measured to detect the onset of damage in bridge connections. More work needs to be done in this area.
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Niranjan Desai, Niranjan Desai, } "Small-strain measurement in bridge connections using the digital image correlation (DIC) technique", Proc. SPIE 9805, Health Monitoring of Structural and Biological Systems 2016, 980530 (1 April 2016); doi: 10.1117/12.2234454; https://doi.org/10.1117/12.2234454
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