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Verification of real sensor motion for a high-dynamic 3D measurement inspection system

: Breitbarth, A.; Correns, M.; Zimmermann, M.; Zhang, C.; Rosenberger, M.; Schambach, J.; Notni, G.


Lehmann, Peter H. (Ed.) ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Optical Measurement Systems for Industrial Inspection X : Munich, Germany; 25 June 2017
Bellingham, WA: SPIE, 2017 (Proceedings of SPIE 10329)
ISBN: 978-1-5106-1103-0
Paper 103290O
Conference "Optical Measurement Systems for Industrial Inspection" <10, 2017, Munich>
Fraunhofer IOF ()

Inline three-dimensional measurements are a growing part of optical inspection. Considering increasing production capacities and economic aspects, dynamic measurements under motion are inescapable. Using a sequence of different pattern, like it is generally done in fringe projection systems, relative movements of the measurement object with respect to the 3d sensor between the images of one pattern sequence have to be compensated.
Based on the application of fully automated optical inspection of circuit boards at an assembly line, the knowledge of the relative speed of movement between the measurement object and the 3d sensor system should be used inside the algorithms of motion compensation. Optimally, this relative speed is constant over the whole measurement process and consists of only one motion direction to avoid sensor vibrations. The quantified evaluation of this two assumptions and the error impact on the 3d accuracy are content of the research project described by this paper.
For our experiments we use a glass etalon with non-transparent circles and transmitted light. Focused on the circle borders, this is one of the most reliable methods to determine subpixel positions using a couple of searching rays. The intersection point of all rays characterize the center of each circle. Based on these circle centers determined with a precision of approximately 1=50 pixel, the motion vector between two images could be calculated and compared with the input motion vector. Overall, the results are used to optimize the weight distribution of the 3d sensor head and reduce non-uniformly vibrations. Finally, there exists a dynamic 3d measurement system with an error of motion vectors about 4 micrometer. Based on this outcome, simulations result in a 3d standard deviation at planar object regions of 6 micrometers. The same system yields a 3d standard deviation of 9 µm without the optimization of weight distribution.