ZHANG Yuetong, CHEN Wenliang, WANG Xiangjun, LIU Feng, WANG Meiyi. FDM printing trajectory measurement and quality evaluation method based on infrared imaging[J]. Journal of Applied Optics, 2024, 45(5): 1008-1018. DOI: 10.5768/JAO202445.0503003
Citation: ZHANG Yuetong, CHEN Wenliang, WANG Xiangjun, LIU Feng, WANG Meiyi. FDM printing trajectory measurement and quality evaluation method based on infrared imaging[J]. Journal of Applied Optics, 2024, 45(5): 1008-1018. DOI: 10.5768/JAO202445.0503003

FDM printing trajectory measurement and quality evaluation method based on infrared imaging

  • Fused deposition modeling (FDM) is a hot working process, the research on temperature and motion accuracy in the printing process are independent directions, and the shape of the high temperature filament in the infrared image is usually not concerned, making it impossible to detect the operating status and temperature of the printer at the same time. An FDM printing trajectory measurement and quality evaluation method based on infrared imaging was proposed. The method adopted infrared camera to continuously monitor the FDM printing process, and established the pose solution model of the printer coordinate system and the camera world coordinate system, as well as the global camera motion pose solution model matching the infrared features between dynamic frames. The real time measurement of the running position of the end nozzle was realized, and the accurate print trajectory information was obtained. On this basis, the object image mapping relationship between the spatial print trajectory and the high temperature filament in the infrared image was established, and the quality of the printing process and typical defects were evaluated in the image domain. The average time of image processing was 25.9 ms, and the reprojection error of infrared camera posture measurement was 0.7 pixel. Under normal printing conditions, the average IoU between the ideal print trajectory calculated by the system and the high temperature region in the infrared image is 0.61. The experimental results show that the proposed method can accurately identify the typical problems such as model dislocation and abnormal extruding in the printing process, which provides a new solution for the related research of online print quality evaluation.
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