Abstract: Aiming at the overfilling at the corner and underfilling at the start in the silicone extrusion additive manufacturing process, this study proposes a silicone extrusion defect optimization method based on visual feedback. Firstly, a silicone extrusion additive manufacturing experimental platform is set up, and the visual sensor is used to monitor the printing process and obtain the printing images. Then the corresponding image processing algorithm is designed for the printed line images in the experiment, and the line widths of the printed lines are obtained according to this algorithm. In order to study the relationship between the printed line width and process parameters, a set of orthogonal experiments are designed, the printed line width data under different printing parameters (layer thickness h, nozzle moving speed $ v_{t} $, and nozzle extrusion speed $ v_{d} $) are gotten, and the line width data are fitted using least squares method to get the mathematical model of the line width. The extrusion speed change rule of the nozzle at the corner and the start of printing in the silicone extrusion process is analyzed through the line width model, the extrusion speed change model of the nozzle is established, and the G code of the printing model is optimized by using the extrusion speed change model of the nozzle and the line width model, so as to make the moving speed and extrusion speed of the nozzle maintain a certain matching relationship at the corner and the start of printing, thus improving the overfilling and underfilling defects of the silicone extrusion. Finally, silicone extrusion printing experiments verify the effectiveness of the optimization method.
Keywords: silicone; additive manufacturing; image processing; extrusion defects; off-line optimization
合肥工业大学学报自科版