.png){kind=icon}
Return
Adaptive undermatched systematic error mitigation algorithm considering spatial continuity in digital image correlation
.png){kind=icon}
PRE
AI
DOI：10.1088/2051-672X/ade7a4.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In the measurement of inhomogeneous complex deformations using the digital image correlation (DIC) method, systematic errors arising from undermatched shape functions are a significant source of inaccuracy, often surpassing the effects of other errors like random noise and grey-level interpolation errors. This study focuses primarily on mitigating these undermatched systematic errors. In this work, the traditional model corresponding to such errors is extended to analyse the entire subset region comprehensively. Based on this model, a novel mitigation method is proposed, which incorporates spatial continuity considerations. By averaging the recalculated displacement results for each pixel, this approach significantly minimizes potential errors introduced during calculation and achieves more accurate estimations of actual displacements when dealing with complex deformation characterization.
Keywords:
digital image correlation
undermatched shape function
systematic errors
inhomogeneous deformation
Journal
S
IF:
2.4
Papers:
77
Citations:
0
Organization
Cited Papers
.png){kind=icon}
ShareSaveParameter identification of a phase-field fracture model using integrated digital image correlation
OAAI
OAAIShareSaveShareSaveShareSave
ShareSaveShareSaveShareSave
View more