压铸模具激光仿生强化工艺决策系统研究

发布时间：2018-08-28 11:36

【摘要】：采用激光表面仿生强化技术提高模具的使用寿命是近几年新兴的一个课题，是仿生学在模具工业领域中的重要应用，为模具行业带来了巨大的经济效益。将激光仿生强化工艺规范化更有助于其在未来的发展与推广。文中以人工神经网络理论为依据，将激光熔凝单元体形态和激光加工工艺之间存在的高度非线性关系视为“黑箱”，把熔凝单元体横截面尺寸作为神经网络的输入，激光工艺参数作为神经网络的输出，建立了激光熔凝参数反求模型。采用结构化分析方法对压铸模具激光仿生强化工艺决策系统进行了功能模块划分和结构设计。从系统总体功能出发，设计了压铸模具材料表、激光工艺参数表、熔凝结果表、仿生形态表、热疲劳性能表和摩擦磨损性能表以及表与表之间的关系，建立了压铸模具激光仿生强化工艺数据库。以Visual C++6.0为开发平台，采用模块化编程设计人机交互界面，，开发出具有自主知识产权的压铸模具激光仿生强化工艺决策系统。最后，以DIEVAR模具钢为例，从激光熔凝单元体的横截面尺寸、组织形态、显微硬度和热疲劳性能四个方面对压铸模具激光仿生强化工艺决策系统的决策精度和整体性能进行了测试。结果显示：系统稳定性良好；决策精度能够达到1.33%；经反求的激光工艺参数熔凝加工后，材料硬度提高了40-100HV，热疲劳性能也显著提高。将该系统应用于实际模具强化工艺制定中，经生产运行显示，强化后的模具寿命提高约70%。
[Abstract]:The application of laser surface bionic strengthening technology to improve the service life of mould is a new topic in recent years. It is an important application of bionics in the field of mould industry and brings great economic benefits to die industry. The standardization of laser bionic strengthening technology is helpful to its development and popularization in the future. Based on the theory of artificial neural network, the highly nonlinear relationship between the shape of laser coagulation unit and the laser processing technology is regarded as a "black box", and the cross section size of the fusion unit is regarded as the input of neural network. Laser process parameters are used as the output of neural network, and the inverse model of laser melting parameters is established. The structural analysis method is used to divide the function modules and design the structure of the process decision system for the laser bionic strengthening of die casting die. Based on the overall function of the system, the material table of die casting die, the parameter table of laser process, the result table of melting, the bionic form table, the table of thermal fatigue performance and the table of friction and wear performance, and the relationship between the table and the table are designed. The database of laser bionic strengthening process for die casting die was established. With Visual C 6.0 as the development platform, the man-machine interactive interface is designed by modular programming, and a die casting mould laser bionic strengthening process decision system with independent intellectual property rights is developed. Finally, taking DIEVAR die steel as an example, the cross section size and microstructure of laser solidifying unit are analyzed. Four aspects of microhardness and thermal fatigue performance of the die casting die laser bionic strengthening process decision-making system decision-making accuracy and overall performance were tested. The results show that the stability of the system is good, the decision accuracy can reach 1.33, and the hardness of the material is increased by 40 ~ 100 HVV, and the thermal fatigue property is also improved significantly after the reverse laser processing parameters are fused and solidified. The system is applied to the actual die strengthening process. The operation shows that the service life of the strengthened die is increased by about 70%.
【学位授予单位】：太原科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TG665;TG233.1

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