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陈兴惠, 张洪申. 基于主成分及灰色关联度分析的5083铝合金FSW接头工艺参数优化[J]. 焊接学报, 2023, 44(5): 62-69. DOI: 10.12073/j.hjxb.20220623001
引用本文: 陈兴惠, 张洪申. 基于主成分及灰色关联度分析的5083铝合金FSW接头工艺参数优化[J]. 焊接学报, 2023, 44(5): 62-69. DOI: 10.12073/j.hjxb.20220623001
CHEN Xinghui, ZHANG Hongshen. Process parameters optimization of 5083 aluminum alloy FSW joint based on principal component analysis and grey correlation analysis[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(5): 62-69. DOI: 10.12073/j.hjxb.20220623001
Citation: CHEN Xinghui, ZHANG Hongshen. Process parameters optimization of 5083 aluminum alloy FSW joint based on principal component analysis and grey correlation analysis[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(5): 62-69. DOI: 10.12073/j.hjxb.20220623001

基于主成分及灰色关联度分析的5083铝合金FSW接头工艺参数优化

Process parameters optimization of 5083 aluminum alloy FSW joint based on principal component analysis and grey correlation analysis

  • 摘要: 针对铝合金搅拌摩擦焊接工艺参数优化问题,对5083铝合金板材进行研究,开展其在不同搅拌摩擦焊工艺参数下的力学性能探索,运用主成分分析和灰色关联度分析法对试验结果进行探索,得出焊接接头最优工艺参数,并建立基于GRG的工艺参数二阶预测模型.结果表明,均值极差法得出最优工艺参数组合为转速1 400 r/min,焊接速度1 mm/s,下压量0.3 mm,接头抗拉强度最大达到225.5 MPa,达到了母材的95.4%,失效位移为10.6 mm. 在试验工艺参数范围内,影响接头抗拉强度的主要因素次序为下压量、焊接速度、转速;模型预测值与计算值无显著差异,回归模型与试验数据的吻合度好,说明预测模型可靠度高,此回归模型可作为其预测模型.

     

    Abstract: Aim at optimizing the friction stir welding (FSW) process parameters of aluminum alloy, 5083 aluminum alloy plate was selected as the research object in this study. The mechanical properties of 5083 aluminum alloy plate under different FSW process parameters were explored. Principal component analysis (PCA) and grey relational degree (GRG) analysis were employed to analyze the test results. The optimal process parameters were obtained, and a second-order prediction model of process parameters based on GRG was established. The results show that the optimal combination of process parameters is a rotation speed of 1400 r/min, welding speed of 1 mm/s and plunge depth of 0.3 mm. The maximum tensile strength of the joint reaches 225.5 MPa, 95.4% of the base metal, and the failure displacement is 10.6 mm. Among the tested process parameters, the main factors influencing the tensile strength of the joint are plunge depth of shoulder, welding speed and rotation speed in sequence. Besides, there is no significant difference between the predicted value of the model and the calculated value. The good agreement between the regression model and the experimental data indicates that the prediction model has high reliability. The regression model can be used as the prediction model.

     

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