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Article
Reconstruction of in-plane strain maps using hybrid dense sensor network composed of sensing skin
Measurement Science and Technology
  • Austin R.J. Downey, Iowa State University
  • Simon Laflamme, Iowa State University
  • Filippo Ubertini, University of Perugia
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
11-1-2016
DOI
10.1088/0957-0233/27/12/124016
Abstract
The authors have recently developed a soft-elastomeric capacitive (SEC)-based thin film sensor for monitoring strain on mesosurfaces. Arranged in a network configuration, the sensing system is analogous to a biological skin, where local strain can be monitored over a global area. Under plane stress conditions, the sensor output contains the additive measurement of the two principal strain components over the monitored surface. In applications where the evaluation of strain maps is useful, in structural health monitoring for instance, such signal must be decomposed into linear strain components along orthogonal directions. Previous work has led to an algorithm that enabled such decomposition by leveraging a dense sensor network configuration with the addition of assumed boundary conditions. Here, we significantly improve the algorithm's accuracy by leveraging mature off-the-shelf solutions to create a hybrid dense sensor network (HDSN) to improve on the boundary condition assumptions. The system's boundary conditions are enforced using unidirectional RSGs and assumed virtual sensors. Results from an extensive experimental investigation demonstrate the good performance of the proposed algorithm and its robustness with respect to sensors' layout. Overall, the proposed algorithm is seen to effectively leverage the advantages of a hybrid dense network for application of the thin film sensor to reconstruct surface strain fields over large surfaces.
Comments

This is an author-created, un-copyedited version of an article accepted for publication/published in Measurement Science and Technology. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at doi: 10.1088/0957-0233/27/12/124016 ”. Posted with permission.

Copyright Owner
IOP Publishing Ltd
Language
en
File Format
application/pdf
Citation Information
Austin R.J. Downey, Simon Laflamme and Filippo Ubertini. "Reconstruction of in-plane strain maps using hybrid dense sensor network composed of sensing skin" Measurement Science and Technology Vol. 27 Iss. 12 (2016)
Available at: http://works.bepress.com/simon_laflamme/42/