27 March 2018 Crack detection in RC structural components using a collaborative data fusion approach based on smart concrete and large-area sensors
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Abstract
Recent advances in the fields of nanocomposite technologies have enabled the development of highly scalable, low-cost sensing solution for civil infrastructures. This includes two sensing technologies, recently proposed by the authors, engineered for their high scalability, low-cost and mechanical simplicity. The first sensor consists of a smart-cementitious material doped with multi-wall carbon nanotubes, which has been demonstrated to be suitable for monitoring its own deformations (strain) and damage state (cracks). Integrated to a structure, this smart cementitious material can be used for detecting damage or strain through the monitoring of its electrical properties. The second sensing technology consists of a sensing skin developed from a flexible capacitor that is mounted externally onto the structure. When deployed in a dense sensor network configuration, these large area sensors are capable of covering large surfaces at low cost and can monitor both strain- and crack-induced damages. This work first presents a comparison of the capabilities of both technologies for crack detection in a concrete plate, followed by a fusion of sensor data for increased damage detection performance. Experimental results are conducted on a 50 50 5 cm3 plate fabricated with smart concrete and equipped with a dense sensor network of 20 large area sensors. Results show that both novel technologies are capable of increased damage localization when used concurrently.
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Austin Downey, Austin Downey, Antonella D'Alessandro, Antonella D'Alessandro, Filippo Ubertini, Filippo Ubertini, Simon Laflamme, Simon Laflamme, "Crack detection in RC structural components using a collaborative data fusion approach based on smart concrete and large-area sensors", Proc. SPIE 10598, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018, 105983B (27 March 2018); doi: 10.1117/12.2296695; https://doi.org/10.1117/12.2296695
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