Riassunto analitico
Digital Image Correlation (DIC) is an optical metrology technique that can be used as a mean to mechanically characterize an object, correlate FEA analyses, visualize stress paths, etc. Since it is an accurate and a non-contact technique -independent of the material or dimensions of the test subject- its usage has found its way into different industries, not being motorsports an exception.
Seeking to use this technology to increase its investigation yield and complement their current testing processes, Dallara acquired a DIC system developed by Zeiss called GOM, comprised of both a camera system and a proprietary software that carries out the camera system’s calibration, as well as the data acquisition and processing from the test subjects being mechanically tested. As an initiative to optimize their current testing and data post-processing analysis, an opportunity to develop this project rose, split into two parts: the first one was focused on understanding how GOM worked and how different parameters affected its calculation modality (i.e. how acquisition frequency affected data processing capabilities and file size); the second part in turn looked to analyze and correlate between the results calculated by GOM and those predicted by FEA models.
As this thesis focused on the optimization of the test methodology, error mitigation, and FEA models’ correlation with GOM results, a more thorough description on optics’ theory and the mathematics behind DIC are contained in the Appendices of this work.
|
