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16 July 2019 Mass production quality control of welds based on image processing and deep learning in safety components industry
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Proceedings Volume 11172, Fourteenth International Conference on Quality Control by Artificial Vision; 111720L (2019) https://doi.org/10.1117/12.2520578
Event: Fourteenth International Conference on Quality Control by Artificial Vision, 2019, Mulhouse, France
Abstract
In capital goods industry, there are some components that are employed for safety purposes and, due to this fact, parts are subjected to high quality control demands. This is especially relevant for the case safety components that contain welds because of the inherent complex process and the likelihood of defects appearance. In this context, this work presents a machine vision system that was employed for replacing costly quality control procedures based on visual inspection. This was possible thanks to the proper design of all the machine vision system components including the image processing algorithm. As a special feature of the system, it has to be highlighted the low cycle time of the production process (<2s), which stablished some requirements on the image processing algorithms. During the inspection system development, the main efforts were concentrated for obtaining a reliable and balanced database of defective and non-defective parts images useful to train the classification model. At this respect, the main contributions consisted of image analysis software development and visual curation of data. As a result, tailor made filters were developed that allowed together with color information the identification of common flaws, as Lacks of Fusion (LoF). Due to the high amount of inspected samples, a preliminary deep learning based model was developed that included these filters with the aim of increasing defect detection accuracy.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ander Muniategui, Aitor García de la Yedra, Jon Ander del Barrio, Manuel Masenlle, Xabier Angulo, and Ramón Moreno "Mass production quality control of welds based on image processing and deep learning in safety components industry", Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 111720L (16 July 2019); https://doi.org/10.1117/12.2520578
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