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基于人工神经网络的6063铝合金时效工艺的研究

Study on Ageing Regime for 6063 Aluminium Alloys Based on Artificial Neural Network

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【作者】 左秀荣井元伟

【Author】 ZUO Xiu-rong,JING Yuan-wei (School of Information Science and Engineering,Northeastern University,Shenyang 110004,China)

【机构】 东北大学信息科学与工程学院

【摘要】 采用人工神经元网络对时效硬度进行预测,并对两阶段时效工艺参数对时效硬度的影响规律进行研究.研究结果表明:在本研究的温度时间范围内,第2阶段时效温度对时效硬度的影响非常显著,而第1阶段时效温度和时间及第2阶段时效时间对时效硬度的影响不太明显,这与正交试验结果相同.人工神经网络与正交试验分析方法相结合,确定的最优时效工艺参数为170℃×70 min+210℃×50 min.

【Abstract】 Ageing hardness for 6063 Aluminium alloys has been predicted,and the effects of ageing process parameters on ageing hardness have been studied by means of artificial neural network.The results show: in the range of temperature and time of this study,the temperature and time of the first-staged ageing process and the time of the second-staged ageing process have less influence on ageing hardness,but the temperature of the second-staged ageing process has obvious influence on ageing hardness.This result accords with that of orthogonal experiment.Through combining artificial neural network and orthogonal experiment,the optimum two-staged ageing process parameters are 170 ℃ for 70 mins and 210 ℃ for 50 mins.

  • 【文献出处】 中北大学学报(自然科学版) ,Journal of North University of China(Natural Science Edition) , 编辑部邮箱 ,2009年01期
  • 【分类号】TG166.3
  • 【被引频次】2
  • 【下载频次】150
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