航空钣金热成形模具损伤多目标评估与寿命预测研究OA

This article focuses on the damage assessment and life prediction of aviation sheet metal hot forming molds,aiming to solve key problems such as rapid mold wear,short life,and large surface quality fluctuations of formed parts under high temperature conditions.As the core process for achieving"shape property coordinated control"of lightweight and high-strength aviation sheet metal components,hot forming technology can effectively overcome the bottleneck of poor formability at room temperature,but its high temperature and high pressure characteristics exacerbate mold damage,restricting process stability and economy.Therefore,based on the modified Archard wear model and the DeForm-3D simulation platform,this article systematically simulates the wear depth distribution and evolution of hot-stamping dies for sheet metal components during the thermoforming process,revealing the coupling mechanisms among the temperature field,stress field,and wear behavior.Furthermore,by integrating the BP neural network(BPNN)algorithm,an intelligent prediction model was constructed with material performance parameters,stress levels,and process conditions as input variables,and the remaining life of the mold as the output objective.The simulation results show that this method can not only quantitatively evaluate the degree of damage in multiple areas of the mold,but also achieve low error life prediction.