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张子豪, 曾凯, 张洪申, 邢保英, 丁燕芳, 田海. 基于球形底模的铝合金自冲铆接工艺多元回归模型[J]. 焊接学报. DOI: 10.12073/j.hjxb.20230715003
引用本文: 张子豪, 曾凯, 张洪申, 邢保英, 丁燕芳, 田海. 基于球形底模的铝合金自冲铆接工艺多元回归模型[J]. 焊接学报. DOI: 10.12073/j.hjxb.20230715003
ZHANG Zihao, ZENG Kai, ZHANG Hongshen, XING Baoying, DING Yanfang, TIAN Hai. Multiple regression model of process for aluminum alloy self-piercing riveting based on ball-shaped die[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION. DOI: 10.12073/j.hjxb.20230715003
Citation: ZHANG Zihao, ZENG Kai, ZHANG Hongshen, XING Baoying, DING Yanfang, TIAN Hai. Multiple regression model of process for aluminum alloy self-piercing riveting based on ball-shaped die[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION. DOI: 10.12073/j.hjxb.20230715003

基于球形底模的铝合金自冲铆接工艺多元回归模型

Multiple regression model of process for aluminum alloy self-piercing riveting based on ball-shaped die

  • 摘要: 针对低延展性铝合金薄板材料自冲铆接成形过程易出现裂纹问题,提出了一种基于球形底模的自冲铆连接工艺.针对7075铝合金材料,采用Box-Behnken Design响应面试验方法,开展自冲铆接头工艺试验研究,确定最优工艺参数.以铆钉长度,冲头速度和冲头行程作为输入变量,接头的失效载荷和能量吸收值为响应值,建立基于球形底模的自冲铆接工艺多元非线性回归模型,并进行试验验证.结果表明,采用球形底模在保证接头强度下有效抑制自冲铆接头机械内锁区裂纹的产生;应用回归模型得到的理论预测值与试验值之间的相对误差较低,回归模型具有较高的可靠性;同时,单因素分析表明,铆钉长度对接头静力学性能的影响最大;交互作用分析中,铆钉长度和冲头行程的交互作用对失效载荷和能量吸收值的影响最为显著.最后通过NSGA-II遗传算法确定最优工艺参数组合.

     

    Abstract: The self-piercing riveting (SPR) technology based on ball-shaped die is proposed to solve the problem of cracks in the SPR process of aluminum alloy sheet materials with low ductility. The Box-Behnken Design (BBD) response surface experimental method was used to study the SPR joint process for 7075 aluminum alloy material, and the optimal process parameters were determined. Taking rivet length, punch speed and punch stroke as input variables and joint failure load and energy absorption as response values, a multiple nonlinear regression model for SPR process based on ball-shaped die was established and verified by experiments. The results show that the use of ball-shaped die can effectively restrain the crack in the mechanical inner locking zone of the SPR joint under the guarantee of joint strength. The relative error between the theoretical predicted value obtained by the regression model and the experimental value is low, and the regression model has high reliability. Meanwhile, single factor analysis shows that the rivet length has the greatest influence on the static mechanical property of the joint. In the interaction analysis, the interaction of rivet length and punch stroke has the most significant influence on the failure load and energy absorption value. Finally, NSGA-II genetic algorithm was used to determine the optimal process parameter combination.

     

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