Simulation Research On Predictive Control Of Sintering Point Temperature In Selective Laser Sintering

Selective Laser Sintering(SLS)is one of the most important additive manufacturing technologies.The Selective Laser Sintering(SLS)has many advantages,such as wide selection of materials,no support,high forming speed and the ability to form complex parts.It has a wide application prospect.In SLS process,stable sintering point temperature is an important factor to ensure the quality of forming parts.At present,direct feedback control is mainly used to maintain the temperature stability of sintering point,but the actual effect is not ideal.In this paper,the predictive control method of sintering point temperature in SLS is proposed.In order to realize this method,the finite element analysis of SLS temperature field of coated sand is carried out,and the predictive control model of sintering point temperature based on GA-BP neural network is established.Based on this model,the simulation and experiment of predictive control of sintering point temperature are carried out.Specific research contents are as follows:Using finite element software ANSYS APDL SLS temperature field simulation model is established,moving gauss heat source are adopted to simulate the continuous laser scanning,considering the material parameters in thermal and physical properties under different temperature,the analysis leads to the inner mechanism of the SLS sintering temperature distribution,and the forming process parameters are discussed in detail and the relationship between the sintering temperature.The SLS temperature detection platform based on the infrared thermal imager is built,and the temperature acquisition experiment is carried out.The simulation results are consistent with the experimental results,which verifies the correctness of the finite element model.On the basis of a large number of numerical simulation experiments,the prediction model of sintering point temperature and the laser power control model were established by using GA-BP neural network.The temperature prediction model can predict the temperature distribution of sintering point of different size models under different forming process parameters.The GA-BP prediction results are compared with the standard BP neural network prediction results.The GABP model has a higher prediction accuracy.The power control model can calculate the corresponding laser power of each sintering point when the sintering point temperature is stable at the target value.The simulation results of power control are verified in ANSYS,and the temperature of each sintering point is kept near the target value.The predictive control software of SLS sintering point temperature was developed based on GA-BP temperature predictive control model.The software was used to predict the sintering point temperature of cuboid and triangular cylinder parts in the process of constant laser power SLS forming.The accuracy of the prediction of sintering point temperature was proved by the experiments of constant laser power SLS forming.Application of this software for rectangle,triangle,cylinder parts sintering temperature simulation prediction control,calculate the dynamic changes of the sintering point of the laser power,applied to calculate the different sintering point of the laser power variable power SLS forming experiments,the results show that the sintering temperature can remain stable,sintering temperature is verified the correctness of the predictive control method.