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Proceedings Paper

Algorithm for decomposition of additive strain from dense network of thin film sensors
Author(s): Hussam Saleem; Austin Downey; Simon Laflamme
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Paper Abstract

The authors have developed a capacitive-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. The measurement principle is based on a measurable change in capacitance provoked by strain. In the case of bi-directional in-plane strain, the sensor output contains the additive measurement of both principal strain components. In this paper, we present an algorithm for retrieving the directional strain from measurements. The algorithm leverages the dense network application of the thin film sensor to reconstruct the surface strain map. A bi-directional shape function is assumed, and it is differentiated to obtain expressions for planar strain. A least square estimator (LSE) is used to reconstruct the planar strain map from the sensors measurement’s, after the system’s boundary conditions have been enforced in the model. The coefficients obtained by the LSE can be used to reconstruct the estimated strain map or the deflection shape directly. Results from numerical simulations and experimental investigations show good performance of the algorithm, in particular for monitoring surface strain on cantilever plates.

Paper Details

Date Published: 27 March 2015
PDF: 11 pages
Proc. SPIE 9435, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015, 94351N (27 March 2015); doi: 10.1117/12.2084369
Show Author Affiliations
Hussam Saleem, Iowa State Univ. (United States)
Austin Downey, Iowa State Univ. (United States)
Simon Laflamme, Iowa State Univ. (United States)


Published in SPIE Proceedings Vol. 9435:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015
Jerome P. Lynch, Editor(s)

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