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Authors: Jin Yan (Iowa State University) , Simon Laflamme (Iowa State University) , An Chen (Iowa State University) , Austin Downey (University of South Carolina) , Xiaosong Du (Iowa State University) , Leifur Leifsson (Iowa State University) , Chao Hu (Iowa State University)
The use of sensor networks for structural health monitoring purposes has gained popularity due to advances in electronics enabling the deployment of cost-effective solutions. However, linking signal to condition evaluation is still a difficult task, and metrics must be developed to validate the performance of a given sensor network at conducting its as-designed structural health monitoring task. In this paper, we present a model-assisted sensor network validation strategy. The strategy consists of constructing a physical surrogate model to perform numerical investigations of sensor network performance under uncertainty. The update of the physical surrogate provides spatiotemporal data enabling condition evaluation. A metric inspired by probability of detection theory is developed to quantify performance. We demonstrate the methodology to validate the performance of a novel strain-based sensor network.
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How to Cite: Yan, J. . , Laflamme, S. . , Chen, A. . , Downey, A. . , Du, X. . , Leifsson, L. . & Hu, C. . (2019) “Surface sensing-based technique for nondestructive evaluation”, Review of Progress in Quantitative Nondestructive Evaluation.(0).