ABSTRACT Digital Image Correlation (DIC) is a popular camera‐based, non‐contacting method to obtain full‐field displacement and strain measurements. In a vibration‐based fatigue test, DIC is desirable because DIC can continue to monitor strain after a strain gage would have failed. When applied to vibration‐based testing, one of the major challenges of DIC is maintaining sufficient lighting. Large out‐of‐plane displacements necessitate small apertures for improved depth of field while high frequency oscillation requires short exposure times to reduce motion blur. In this work, the tradeoffs in aperture, exposure time, gain, and external lighting are examined. First, a Design of Experiment (DOE) response surface test matrix is generated for each light source and aperture size. Second, strains are estimated using a laser vibrometer for which there is a pre‐determined relationship between its measured displacement and the strains measured by a strain gauge at lower amplitudes. Third, strains are additionally measured by fitting an analytical solution to full‐field deformation obtained using DIC. Further, a Monte Carlo Method uncertainty propagation was performed to determine the uncertainty between the two strain measurements. The strobe lights provided the most accurate and stable strain measurements while the ring lights provided the smallest tolerance range. In most cases, the use of Gain was found to be relatively harmless, which runs counter to the common wisdom that it should be generally avoided in DIC. In some extreme cases, Gain even produced less error than leaving the Gain as zero, but there are also counter‐examples for which increased Gain produced worse outcomes. Thus, although in some situations Gain may be the least‐worst option based on the needs of the experiment, DIC users should be cautioned not to over‐rely on Gain without careful consideration of other lighting methods.
Building similarity graph...
Analyzing shared references across papers
Loading...
Rigby et al. (Tue,) studied this question.
synapsesocial.com/papers/69fd7e5cbfa21ec5bbf06a0e — DOI: https://doi.org/10.1111/str.70035
Jacob Rigby
Utah State University
Brandon A. Furman
Utah State University
Jeffrey M. Wagner
Utah State University
Strain
Utah State University
Building similarity graph...
Analyzing shared references across papers
Loading...