Woodgrain Inspired 3D Printing Toolpath Planning Method Based on Image Recognition

Abstract:

Aimed at the problems of low structural efficiency and incongruity with the stress field of bearing parts in the filling of uniform isomorphic mesoscopic structures such as grid and triangle used in traditional 3D printing， and inspired by the fact that naturally growing woodgrain can improve the overall performance of wood， a woodgrain inspired 3D printing toolpath planning method based on image recognition is proposed aiming to learn from the fiber arrangement of wood to improve the mechanical properties of parts. Through wood milling layering， the woodgrain image of each layer is extracted in turn and the corresponding printing path is generated. Then， the biomimetic woodgrain specimen is printed layer by layer. The tensile test results show that the maximum tensile load of the printed specimen based on woodgrain is increased by 115.03 %， 72.89 % and 64.39 % respectively compared with the three traditional uniform isomorphic filling specimens，i.e.， grid filling， triangular filling，and rectilinear filling. It is proved that the non-uniform heterogeneous filling structure based on biomimetic woodgrain can significantly improve the tensile strength of the printed specimen.