Translator Disclaimer
27 March 2015 Algorithm for decomposition of additive strain from dense network of thin film sensors
Author Affiliations +
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hussam Saleem, Austin Downey, and Simon Laflamme "Algorithm for decomposition of additive strain from dense network of thin film sensors", Proc. SPIE 9435, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015, 94351N (27 March 2015);

Back to Top