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Dynamic Reconstruction of In-plane Strain Maps using a Two-dimensional Sensing Skin

AUSTIN DOWNEY, JIN YAN, SIMON LAFLAMME, AN CHEN

Abstract


Damage detection and localization in large-scale systems requires the detection of local faults over a typically very large geometry. This can be done through the deployment of twodimensional sensor arrays capable of discreetly monitoring local changes over a structure’s global area. The authors have previously developed a soft-elastomeric capacitor (SEC) thin film sensor capable of measuring the additive strain components over a surface along its two principal directions. For applications to structural health monitoring, it is useful to decompose the signal into strain components along these principal directions. When deployed in a dense sensor network configuration, the principal strain components can be extracted from the measured additive strain using a previously developed algorithm that used assumptions on the boundary conditions. The introduction of mature off-the-shelf solutions, for the purpose of boundary condition updating, has been shown to significantly improve the algorithm’s accuracy. The newly created hybrid dense sensor network (HDSN), consisting of SECs and resistive strain gauges, is capable of producing orthogonal strain maps over the structure’s surface. Previous studies were conducted using static loads. Here, the authors report on the capability of the HDSN-based technique to reconstruct dynamic strain maps for a component exposed to dynamic loads. Results demonstrate that the hybrid dense sensor network can efficiently reconstruct dynamic in-plane strain maps. These dynamic strain maps can then be used for the reconstruction of dynamic deflection shapes or, in combination with other damage detection algorithms, to detect, localize and quantify damage.


DOI
10.12783/shm2017/14019

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