University of Nottingham
Development of an optimised close-range photogrammetry measurement system for coordinate metrology
Close-range photogrammetry offers many benefits over competing coordinate metrology techniques; it is non-contact, offers fast data acquisition with high surface coverage, and requires relatively inexpensive hardware. However, it is highly operator dependant and can be slow at the data-processing stage.
We present the development of a measurement system that seeks to overcome and mitigate against the issues stated above. Hardware designed by Taraz Metrology in collaboration with the Manufacturing Metrology Team allows the system to implement a range of smart approaches to allow for fully automated and optimised data acquisition and processing. These approaches include a smart view planning algorithm to minimise the number of images acquired while maintaining surface coverage and point density, and a background removal algorithm that reduces noise and background matches, reducing data processing time and improving part point density.
We show some initial data collected with the system and discuss future work to further refine the measurement system and procedure.
Joe Eastwood is a researcher from the Manufacturing Metrology Team at the University of Nottingham specialising in the application of machine learning for the optimisation and automation of optical coordinate metrology.