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 bidirectional in-plane strain, the sensor output contains the additive measurement of both principal strain components. In this paper, we present an algorithm for retrieving unidirectional strain from the bidirectional measurements of the capacitive-based thin film sensor when place in a hybrid dense sensor network with state-of-the-art unidirectional strain sensors. The algorithm leverages the advantages of a hybrid dense network for application of the thin film sensor to reconstruct the surface strain maps. A bidirectional shape function is assumed, and it is differentiated to obtain expressions for planar strain. A least squares estimator (LSE) is used to reconstruct the planar strain map from the networks measurements, 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. Results from numerical simulations and experimental investigations show good performance of the algorithm.
Austin Downey, Simon Laflamme, and Filippo Ubertini, "Distributed thin film sensor array for damage detection and localization," Proc. SPIE 9803, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2016, 98030R (Presented at SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring: March 21, 2016; Published: 20 April 2016); https://doi.org/10.1117/12.2219301.
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