The Proceedings of The Computational Mechanics Conference
Online ISSN : 2424-2799
2023.36
Session ID : OS-0402
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Identification of Cracks Using Crack Shape as Prior Information and Digital Image Correlation Method
*Norihiko HanaMasaki UmedaMasao AkiyoshiKenji Amaya
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Abstract

A new crack identification method that estimates the cracks in invisible locations based on the surface deformation measured by digital image correlation (DIC) is developed. An inverse problem is setup to estimate such invisible cracks from surface deformations. The inverse problem has an ill-condition because of noise contained in surface deformations. Our proposed regularization method uses prior information and Expectation a Posteriori (EAP) estimation. Prior information includes candidate crack shapes and surface deformations due to cracks. The candidate crack shapes are created by determining a crack's starting point and propagating it based on the force at its perimeter (ligament). A prior distribution is the surface deformations due to the candidate crack shapes. The likelihood distribution is a surface deformation measured by the DIC method. A posterior distribution is defined from the prior and likelihood distributions. In this study, the estimated result is the expected value of the posterior distribution. The validation test was performed, and the result shows that the proposed method superior to the conventional L1-norm regularization method.

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© 2023 The Japan Society of Mechanical Engineers
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