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材料导报  2024, Vol. 38 Issue (6): 22060206-5    https://doi.org/10.11896/cldb.22060206
  金属与金属基复合材料 |
颗粒增强粘接层结构参数对连接强度的影响及工艺优化
秦怡歆, 曾凯*, 邢保英, 张洪申, 何晓聪
昆明理工大学机电工程学院,昆明 650500
Effect of Structural Parameters of Particle Reinforced Bonding Process on Bonding Strength and Process Optimization
QIN Yixin, ZENG Kai*, XING Baoying, ZHANG Hongshen, HE Xiaocong
Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China
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摘要 基于Box-Behnken design(BBD)响应面法,开展颗粒增强粘接试验研究,构建粘接层结构参数(粘接层厚度、颗粒粒径和颗粒体积分数)与失效载荷和能量吸收值之间的多元回归模型,辨析粘接层结构参数对接头力学性能的影响规律;同时,结合多目标遗传算法,开展粘接工艺的多目标优化,并进行试验验证。结果表明:单因素分析中,颗粒体积分数对接头强度的影响最大;交互作用分析中,粘接层厚度和颗粒体积分数对接头连接强度的影响最为显著。通过Pareto解集确定的最优粘接层结构参数组合为粘接层厚度0.531 mm、颗粒粒径61.765 μm、颗粒体积分数4.099%,遗传算法的预测值与试验值之间的误差分别为5.7%(失效载荷)和0.9%(能量吸收值)。
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秦怡歆
曾凯
邢保英
张洪申
何晓聪
关键词:  颗粒增强  粘接接头  响应面法  遗传算法    
Abstract: Box-Behnken design (BBD) method was used to investigate the effect of process parameters on the mechanical properties of particle reinforced adhesive bonded joints. The multivariate regression models between structural parameters of the adhesive layer (adhesive layer thickness, particle size, and particle volume fraction) and response values (failure load, energy absorption value) were established. Meanwhile, the multi-objective genetic algorithm was used to carry out multi-objective optimization of the bonding process, and the optimized parameters were verified by experiments. The results indicate that particle volume fraction has the biggest impact on the strength of the joints in single factor analysis, and the interaction of adhesive layer thickness and particle volume fraction have the highest influence on the strength of the joints. The optimum structural parameters of the adhesive layer are determined by Pareto solution set: adhesive layer thickness of 0.531 mm, particle size of 61.765 μm, and particle volume fraction of 4.099%. The errors between the predicted value and the real value are 5.7% (failure load) and 0.9% (energy absorption value), respectively.
Key words:  particle reinforced    bonding joint    response surface method    genetic algorithm
出版日期:  2024-03-25      发布日期:  2024-04-07
ZTFLH:  TG495  
基金资助: 国家自然科学基金(51565022;52065034)
通讯作者:  *曾凯,昆明理工大学机电工程学院副教授、硕士研究生导师。2011年7月毕业于清华大学,获机械工程专业博士学位。同年加入昆明理工大学机电工程学院工作至今,主要从事板材连接技术、结构可靠性设计分析、无损检测等方面的研究工作。在国内外重要期刊发表文章30余篇,获国家授权发明专利7项。   
作者简介:  秦怡歆,2021年6月于天津商业大学获得工学学士学位。现为昆明理工大学硕士研究生,在曾凯副教授的指导下进行研究。目前主要研究领域为板材连接新技术。
引用本文:    
秦怡歆, 曾凯, 邢保英, 张洪申, 何晓聪. 颗粒增强粘接层结构参数对连接强度的影响及工艺优化[J]. 材料导报, 2024, 38(6): 22060206-5.
QIN Yixin, ZENG Kai, XING Baoying, ZHANG Hongshen, HE Xiaocong. Effect of Structural Parameters of Particle Reinforced Bonding Process on Bonding Strength and Process Optimization. Materials Reports, 2024, 38(6): 22060206-5.
链接本文:  
https://www.mater-rep.com/CN/10.11896/cldb.22060206  或          https://www.mater-rep.com/CN/Y2024/V38/I6/22060206
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