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Electrical impedance tomography (EIT) is recently demonstrated to be viable for damage localization over a spatial area. The algorithm reconstructs the spatial conductivity distribution within a defined boundary via boundary voltage measurements. To solve this inverse problem, a finite element model (FEM) conforming to the interrogated geometry is required. Previous studies on identifying a center crack’s propagation suggests that an FEM-updating strategy may help identify both the existence of a crack and the plastic zones formed around the crack’s tips. In this paper a data-driven algorithm is applied to automatically update the FEM. The selforganizing map algorithm is adopted to categorize the reconstructed conductivity data, tracing the boundary of the crack to be updated as material-absence. The EIT results from the updated FEM model are able to identify damage location and damage severity with desired accuracy.
Yingjun Zhao,Martin Schagerl, andChristoph Kralovec
"Updating the finite element model for electrical impedance tomography using self-organizing map", Proc. SPIE 10598, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018, 1059832 (27 March 2018); https://doi.org/10.1117/12.2296894
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Yingjun Zhao, Martin Schagerl, Christoph Kralovec, "Updating the finite element model for electrical impedance tomography using self-organizing map," Proc. SPIE 10598, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018, 1059832 (27 March 2018); https://doi.org/10.1117/12.2296894