Hydrogel FDM Molding Process,Performance And Process Monitoring Technology

At present,hydrogels as tissue reconstructing substrates in the field of biological manufacturing have become a research hotspot of scholars at home and abroad.Many experts use FDM molding process to print hydrogel material into biological scaffold structure,mainly focusing on the printing performance of the printing ink and the rheological and physical properties of the synthetic hydrogel,but little attention has been paid to the effect of printing process parameters on the molding of biological printer.At the same time,hydrogel FDM molding process is prone to forming problems,such as printing broken wire and printing object collapse phenomenon occurs from time to time.Therefore,it is usually necessary for the experimenter to stay near the printing equipment for a long time to observe the printing situation.However,due to the long printing time,it is a waste of time and manpower.Based on the bio-3d printing technology,this paper USES the self-made sodium alginate and gelatin mixed solution as the bio-printing ink,and USES its physical and chemical cross-linking properties to realize the bio-printing.The physical properties of hydrogels were enhanced by adding nanocellulose.The flow rate,line width,mechanical properties and rate of change of the nozzle were analyzed and tested in terms of nozzle type,air pressure and solution formulation.The results show that adding nano-cellulose into the experimental material can effectively enhance the mechanical properties of the printing material.Material viscosity,printing pressure,nozzle diameter and printing height are the main factors that affect the molding.The optimum parameters of the material used in the experiment were set as nozzle diameter 0.31mm,printing pressure 7KPa and printing height 0.5-0.9mm.In the actual printing,the size of the bracket needed for printing should be enlarged by about 10%,so that the finished product after crosslinking shrinkage can better meet the needs of printing.On the other hand,a real-time monitoring system for hydrogel FDM molding was designed by using computer vision technology and convolutional neural network technology.Through the establishment of a data set for the situation in the printing process,the structure of the neural network is modified and optimized by using the convenience of Caffe framework,and the network model is obtained through the training of the data set.Then,the detection and recognition rates of the network model under four conditions of "normal","broken wire","collapse" and "block" were verified.Experiments show that the accuracy of the model is 78%on average.In addition,this experiment USES PyQt5 software to design the human-computer interaction interface for the system through Python language,and realizes data visualization.