Displacement estimation using a modified seed prediction algorithm in digital image correlation

A new model based strategy for predicting the initial guess in digital image correlation (DIC) analysis is presented. This is accomplished by integrating the physics of deformation with measurements from images using the Bayesian framework. For the purpose of illustration synthetic and experimental...

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Bibliographic Details
Published inSadhana (Bangalore) Vol. 48; no. 1
Main Authors SUPREETH, M, PANDURANGAN, V, RADHIKA, B
Format Journal Article
LanguageEnglish
Published New Delhi Springer India 09.01.2023
Subjects
Engineering
correlation criterion
Bayesian estimation
seed prediction
Digital image correlation
Kalman filter
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Summary:A new model based strategy for predicting the initial guess in digital image correlation (DIC) analysis is presented. This is accomplished by integrating the physics of deformation with measurements from images using the Bayesian framework. For the purpose of illustration synthetic and experimental data from problems of rigid body motion and finite strains are considered. The proposed algorithm is validated by comparing the predicted deformations with those obtained using the open-source software, Ncorr. The method is successful in accurately capturing the displacements and also achieved a 50% reduction in the computation time in contrast to the existing correlation based approaches. It is anticipated that the formulation presented in this paper will form the basis for developing efficient modelling based computational strategies for DIC applications.
ISSN:0973-7677
0973-7677
DOI:10.1007/s12046-022-02065-0