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Proceedings Paper

A low-cost digital image correlation based constitutive sensor
Author(s): Gun-Jin Yun; Shen Shang; Shilpa Kunchum; Joan Carletta; Si-Byung Nam
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Paper Abstract

In this paper, a low-cost digital image correlation-based constitutive sensor with a novel identification algorithm that is deployable and scalable in the field is proposed. The term 'constitutive sensor' is coined herein to describe a sensor that is capable of determining the target material constitutive parameters. The proposed method is different from existing identification methods in that it does not need to solve boundary value problems of the target materials using updated parameters. Since the development of the digital image correlation (DIC) technique in the 1980s, the DIC technique has been broadly evaluated and improved for measuring full-field displacements of test specimens, mainly in laboratory settings. Although its potential in damage and mechanical identification is immense, the high cost of current commercial DIC systems makes it difficult to apply the DIC technique to in-field health monitoring of structures. To realize a first ever application of DIC in the field, a prototypical low-cost sensing unit consisting of a high performance embedded microprocessor board, a low-cost web camera, and a communication module is suggested. In the proposed constitutive sensor, DIC displacement fields considered as true values are used in computing stress fields satisfying the equilibrium condition and strain fields using finite element concepts. The unknown constitutive law is initially assumed to be fully anisotropic and linear elastic. A steady state genetic algorithm is utilized to search for the material parameters by minimizing a cost function that measures energy residuals. The main features that allow the sensor to be deployable in the field are introduced, and a validation of the proposed constitutive sensor concept using synthetic data is presented.

Paper Details

Date Published: 8 April 2010
PDF: 10 pages
Proc. SPIE 7648, Smart Sensor Phenomena, Technology, Networks, and Systems 2010, 76480H (8 April 2010); doi: 10.1117/12.848184
Show Author Affiliations
Gun-Jin Yun, The Univ. of Akron (United States)
Shen Shang, The Univ. of Akron (United States)
Shilpa Kunchum, The Univ. of Akron (United States)
Joan Carletta, The Univ. of Akron (United States)
Si-Byung Nam, Kangwon National Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 7648:
Smart Sensor Phenomena, Technology, Networks, and Systems 2010
Kara J. Peters; Wolfgang Ecke; Theodore E. Matikas, Editor(s)

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