摘要
采用人工神经网络的方法,研究了固溶时效工艺参数对AlSi7MgBe合金半固态挤压成形件热处理性能的影响,建立了AlSi7MgBe合金半固态挤压成形件热处理工艺制度的人工神经网络模型,并对热处理工艺进行了优化,结果表明,当545℃固溶4h,178℃时效10h,成形件具有最优力学性能Rm=325MPa,A5=14.6%。
The effects of solid solution and ageing process parameters on the properties of semi-solid extruded parts of AlSi7MgBe alloy were studied with the artificial neural network. An artificial neural network model for the heat treatment process of semi-solid extruded parts of AlSi7MgBe alloy was constructed and the process parameters of heat treatment were optimized. The result showed that properties of the part will be the best with the solid solution temperature at 545 ℃ in 4 hours and ageing at 178 ℃ in 10 hours. The tensile strength is 325 MPa, and elongation rate is 14.6%.
出处
《铸造》
EI
CAS
CSCD
北大核心
2007年第11期1160-1163,共4页
Foundry
基金
教育部科学技术研究重点项目(106058)
教育部博士点基金资助项目(20050145007)
国家教育部新世纪优秀人才支持计划资助(NCET-04-0279)
