Aller au contenu principal
Accès ouvert déclaré 2025 article

Advanced Algorithms of Mitigating Undermatched Systematic Error in DIC

4Citations signalées, ce qui n’est pas une note de qualité
2Institutions déclarées
2Pays d’affiliation déclarés

Rattachement africain : us, cn. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

Abstract Background In complex deformation measurements, systematic errors caused by undermatched shape functions are the primary source of errors in Digital Image Correlation (DIC). There are two important ones among the current undermatched systematic error mitigation methods, Recovery method and Improved Quasi-Gauss Point (IQGP) method, that have shown effectiveness in mitigating such errors, though each has its own inherent limitations. The Recovery method is derived based on first-order shape function, while the IQGP method is setup under the assumption of the second-order displacement field in subset. Objective This study aims to extend and improve both the Recovery method and IQGP method respectively to address these limitations and enhance their applicability while comparing the performance between themselves and with other current methods. Methods As for the Recovery method, the effectiveness in mitigating undermatched systematic errors for second-order shape functions is deduced and verified, which broadens its applicability. As for the IQGP method, a new method called Zero-Error Point (ZEP) method is proposed based on the similar principles while accepting the third-order displacement assumption which basically leads to better and wider adaptability compared to the IQGP method. Other classic undermatched systematic error mitigation method and deconvolution method are also involved into analysis and discussion here. Results The extended Recovery method can now mitigate the undermatched error of second-order shape functions compare to the original one just for the first-order shape function, and the improved IQGP method based on the third-order displacement field can achieve an accuracy improvement of nearly 0.4 pixels compared to the traditional IQGP according to experiment results. Conclusion These advancements enhance the performance of undermatched systematic errors algorithms of DIC, thus improving the ability of DIC in deformation characterization under inhomogeneous deformation.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Advanced Algorithms of Mitigating Undermatched Systematic Error in DIC
Date Crossref
04/11/2025
Éditeur
Springer Science and Business Media LLC
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Où se fait cette recherche

  • Michigan State University pays non établi dans la notice
    Université ou école supérieure
  • University of Science and Technology of China CAS Key Laboratory of Mechanical Behavior and Design of Materials pays non établi dans la notice
    Université ou école supérieure
  • College of Engineering Nondestructive Evaluation Laboratory (NDEL) pays non établi dans la notice
    Université ou école supérieure

Michigan State University, CAS Key Laboratory of Mechanical Behavior and Design of Materials — University of Science and Technology of China et Nondestructive Evaluation Laboratory (NDEL) — College of Engineering.

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Optical measurement and interference techniquesStatistical and numerical algorithmsSatellite Image Processing and Photogrammetry

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.