【摘要】：采用原位電阻測(cè)試法、金相顯微鏡觀察、掃描電鏡觀察、透射電鏡觀察和拉伸測(cè)試技術(shù)研究固溶條件對(duì)Al-Zn-Mg-Cu合金顯微組織和拉伸性能的影響�；趯�(shí)驗(yàn)數(shù)據(jù)建立人工神經(jīng)網(wǎng)絡(luò)模型,將該模型用于預(yù)測(cè)實(shí)驗(yàn)合金在固溶過(guò)程中的電阻率變化。結(jié)果表明,所建立的模型能很好地預(yù)測(cè)合金在固溶過(guò)程中的電阻率變化。預(yù)測(cè)結(jié)果與實(shí)驗(yàn)值的相關(guān)系數(shù)為0.9958,相對(duì)誤差為0.33%。采用預(yù)測(cè)數(shù)據(jù)可以建立一種新型的"固溶-電阻率"物理圖形。該圖形顯示,實(shí)驗(yàn)合金的最佳固溶溫度區(qū)間為465~475℃,保溫時(shí)間為50~60 min;在該區(qū)間內(nèi)第二相的溶解與再結(jié)晶對(duì)合金性能的影響將達(dá)到平衡。
[Abstract]:The effect of solution conditions on the microstructure and tensile properties of Al-Zn-Mg-Cu alloy was investigated by in-situ resistance test, metallographic microscope, scanning electron microscopy, transmission electron microscopy and tensile test. An artificial neural network model was established based on the experimental data, and the model was used to predict the resistivity change of the experimental alloy during the solution process. The results show that the model can well predict the resistivity change of the alloy during the solution process. The correlation coefficient between the predicted results and the experimental values is 0.9958, and the relative error is 0.33. A new physical pattern of solid solution-resistivity can be established by using prediction data. The figure shows that the optimum solution temperature range is 465 鈩，

本文編號(hào)：2192073