摘要
基于裂纹萌生与扩展的机制及金属部件疲劳损伤的各种主要因素,结合模具行业的特点和需求,开发了一种基于深度学习的寿命预测模型。仿真结果表明,该模型在预测模具金属部件的寿命方面具有较高的精度和可靠性。这对于模具制造和运行企业而言,不仅有助于他们更深入地理解金属部件的疲劳损伤行为,更能帮助他们准确预测部件的寿命,从而进行更为合理的工程设计和优化。
The article first introduces the particularity and importance of fatigue damage in the mold industry,clarifies the mechanism of crack initiation and propagation,and further analyzes various main factors affecting fatigue damage of mold metal components.On this basis,a deep learning based life prediction model is elaborated,which closely combines the characteristics and needs of the mold industry.Through a series of simulation studies,the article found that the model has high accuracy and reliability in predicting the life of mold metal components,and can effectively reveal the fatigue damage mechanism of these components.For mold manufacturing and operation enterprises,this not only helps them to have a deeper understanding of the fatigue damage behavior of metal components,but also helps them accurately predict the lifespan of components,so as to carry out more reasonable engineering design and optimization.
作者
程丽琴
万茸
程艳
刘楠
CHENG Liqin;WAN Rong;CHENG Yan;LIU Nan(Xi'an High-Tech University,Xi'an 713700,Shaanxi,China;The Hi-Tech College of Xi'an University of Technology,Xi'an 713700,Shaanxi,China)
出处
《模具技术》
2024年第3期1-7,共7页
Die and Mould Technology
基金
《颗粒增强高铬铸铁耐磨件及离心复合铸造工艺的关键技术》(编号:18JK1050)。
关键词
金属机械部件
疲劳损伤机制
寿命预测模型
深度学习
metal mechanical components
fatigue damage mechanism
life prediction model
deep learning
