Abstract
Reinforced concrete shear walls are critical structural components in gravity and lateral force resisting systems. The objective of this work is to design and validate a monitoring system capable of rapid and automated damage assessment of reinforced concrete shear walls. The proposed system is based on a sparse array of piezoelectric transducers to receive acoustic emissions distributed across the wall and a statistical pattern recognition algorithm capable of identifying critical structural conditions to inform decision makers on the need for repair to ensure safe operation of the structure. The proposed system was validated on a full-scale reinforced concrete shear wall subjected to quasi-static cyclic loading.
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