Jonathan Huntley is Professor of Applied Mechanics within the School of Mechanical and Manufacturing Engineering at Loughborough University, UK. He received a BA in Physics and Theoretical Physics from Cambridge University in 1983, and then pursued research leading to a PhD at the Cavendish Laboratory, Cambridge, from 1983 - 1987. Following a Royal Society research fellowship at the Cavendish, he moved to Loughborough in 1994, first as Reader and then as Professor from 1999 onwards. He is a Fellow of the Institute of Physics (IoP) and received the IoP Paterson Medal and Prize in 2005 for his work on laser speckle interferometry, phase unwrapping algorithms and applications of positron emission. In 2002 he co-founded the spinout company Phase Vision Ltd, which manufactures 3D sensors based on the projected fringe technique, and which now has 14 full-time employees.
“Advances in projected fringe metrology”
The projected fringe technique has many attractive features for the measurement of freeform surfaces compared to traditional mechanical coordinate measurement machines, including lack of sample contact and up to five orders of magnitude higher coordinate sampling rate. The talk will summarize some of the significant developments in this technique from the past few years. These include temporal phase unwrapping for unambiguous determination of range on a pixelwise basis, and use of orthogonal projected fringe patterns which allows the introduction of photogrammetric calibration techniques. Fast 3-D Hough transforms have been developed to identify known geometrical features on a calibration artefact, which then provide the input data to a bundle adjustment algorithm. As a result, multiple sensors can be calibrated in a common global coordinate system, without the errors associated with stitching point clouds from individual sensors' local coordinate systems. The combination of projected fringes with digital image correlation has also been developed for structural testing applications. This provides 3-D displacement field data, in addition to the usual shape data, with no additional hardware requirements. Finally, a novel strategy to reduce the influence of spatial variations in the sample's surface reflectivity will be described. The talk will be illustrated with practical applications of the technique in the aerospace and automotive fields.