Droplet Deposition Model And Iterative Learning Control For 3D Printing

3D inkjet printing uses an inkjet printing head to spray droplets to the predetermined position of the substrate,and multi-layers are superimposed to form a specific three-dimensional structure.The shape,size and impact point error of droplets become the key problems that restrict the improvement of forming accuracy.The method of improving the surface quality of parts in three-dimensional inkjet printing is studied in this paper.Firstly,a drop deposition model based on material characteristics is established,which can predict the defects such as the collapse of parts edge in 3D inkjet printing,which lays the foundation for feedback control of 3D inkjet printing.In this paper,the principle of droplet spreading is studied,and the process of droplet spreading is calculated by energy method,and the relationship between material characteristics and droplet spreading is obtained.on this basis,the droplet model is simplified and the droplet fusion model is obtained,and the optimal overprinting rate of droplet printing is obtained.Finally,the deposition model of droplets is obtained by superposition principle.The model can predict the edge collapse of parts in 3D inkjet printing.Secondly,a p-type closed-loop iterative learning control algorithm with initial value correction is proposed,which solves the problem of different initial state in the process of3 D inkjet printing.In view of the repeatability of 3D inkjet printing,a closed-loop iterative learning control algorithm is proposed.In view of the different initial state of each layer,the algorithm is generalized,and a p-type closed-loop iterative learning control algorithm with initial value correction is proposed;The simulation model shows that the expected root mean square error of parts is reduced by 69.3% after the iterative learning control algorithm is adopted.Thirdly,the solution of random offset and greedy algorithm are proposed,which solves the problem that the plug of the orifice will affect the compensation.In this scheme,the data of plug holes are sprayed with other normal holes through position transformation.the experimental results show that the surface roughness of the parts is reduced by 66.3% after using random offset solution.Finally,a compensation control printing system is developed to realize the feedback control and compensation of 3D inkjet printing.The equipment is used to print the parts,and the effectiveness of the algorithm is verified.After adopting the iterative learning control algorithm,the surface roughness of the parts is reduced by 89.5%.