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针对铝合金薄板材料，开展自冲铆成形试验研究，建立声发射信号采集系统以获取自冲铆成形过程中的声发射信号，分析载荷-行程曲线与声发射信号间的映射关系；研究了不同成形缺陷(裂纹、底部厚度不足和镦粗)在时域、频域中的声发射信号特征，分析了其信号特征参数、频域和幅值概率密度的统计量等。结果表明，自冲铆成形过程的声发射信号在铆钉刺入上板、铆钉刺入下板和铆钉腿扩张阶段具有明显的过程特征；有缺陷试件声发射信号强度低于无缺陷试件，底部厚度不足缺陷试件的信号强度高于有裂纹缺陷试件，有镦粗缺陷试件的信号强度最弱；裂纹缺陷试件的频谱主要集中在50 kHz,底部厚度不足缺陷试件的频谱主要集中在175～220 kHz,镦粗缺陷试件的频谱主要集中在225 kHz。利用能量值和峭度值可以区分不同类型的缺陷，可以将其作为自冲铆成形过程在线监测的特征指标。
Abstract：Aiming at aluminum alloy sheet materials, the experimental study of self-piercing riveting forming was carried out. The acoustic emission signal acquisition system was established to obtain the acoustic emission signal during self-piercing riveting forming process, and the mapping relationship between the load-stroke curves and the acoustic emission signal was analyzed. The acoustic emission signal characteristics of different forming defects(crack, insufficient bottom thickness and upsetting) in time domain and frequency domain were studied, and the statistics of signal characteristic parameters, frequency domain and amplitude probability density were analyzed. The results show that the acoustic emission signal of the self-piercing riveting forming process has obvious process characteristics in the rivet piercing the upper plate, the rivet piercing the lower plate and the rivet leg expansion stage; the acoustic emission signal strength of the specimens with defects is less than that of specimens without defects, the signal strength of the specimens with defects of insufficient bottom thickness is stronger than that of specimens with crack defects, and the signal strength of the specimens with upsetting defects is the weakest. The frequency spectrum of the specimens with crack defect is mainly concentrated in 50 kHz, the frequency spectrum of the specimens with defect of insufficient bottom thickness is mainly concentrated in 175-220 kHz, and the frequency spectrum of the specimens with upsetting defect is mainly concentrated in 225 kHz. The energy value and kurtosis value can be used to distinguish different types of defects, which can be used as the characteristic index of online monitoring for self-piercing riveting forming process.
[1] 李永兵，马运五，楼铭，等.轻量化多材料汽车车身连接技术进展[J].机械工程学报，2016,52(24):1-23.LI Yongbing,MA Yunwu,LOU Ming,et al.Progress of lightweight multi-material vehicle body connection technology[J].Journal of Mechanical Engineering,2016,52(24):1-23.
[2] 秦怡歆，邢保英，张洪申，等.穿透式自冲铆接接头成形工艺及力学性能[J].塑性工程学报，2024,31(5):48-54.QIN Yixin,XING Baoying,ZHANG Hongshen,et al.Forming process and mechanical properties of self-piercingthrough riveting joint[J].Journal of Plasticity Engineering,2024,31(5):48-54.
[3] SONG C,XING B Y,HE X C,et al.Self-piercing riveting for single-strap butt joints in similar aluminum alloys[J].Science and Technology of Welding and Joining,2021,26(4):301-308.
[4] ABE Y,KATO T,MORI K.Self-piercing riveting of high tensile strength steel and aluminum alloy sheets using conventional rivet and die[J].Journal of Materials Processing Technology,2009,209(8):3914-3922.
[5] 黄舒彦，李永兵，楼铭，等.基于力与位移信号的自冲铆接质量在线监测 [J].机械设计与研究，2011,27(3):86-90.HUANG Shuyan,LI Yongbing,LOU Ming,et al.Online monitoring of self-punching riveting quality based on force and displacement signals[J].Machine Design and Research,2011,27(3):86-90.
[6] ZHANG X L,HE X C,WEI W J,et al.Fatigue characte-rization and crack propagation mechanism of self-piercingriveted joints in titanium plates[J].International Journal of Fatigue,2020,134(5):1-10.
[7] JOHNSON P,CULLEN J D,SHARPLES L,et al.Online visualmeasurement of self-pierce riveting systems to help determine the quality of the mechanical interlock[J].Measurement,2009,42(5):661-667.
[8] GAY A,ROCHE J M,LAPEYRONNIE P,et al.Non-destructive inspection of initial defects of PA6.6-GF50/aluminum self-piercing riveted joints and damage monitoring under mechanical static loading[J].International Journal of Damage Mechanics,2017,26(8):1127-1146.
[9] CHEN J B,XING B Y,ZHANG H S,et al.Analysis of acoustic emission signal in the tensile process of weld-bonding joint and its damage model[J].Nondestructive Testing and Evaluation,2025,40(2):751-769.
[10] LIN S,ZHAO L,WANG S,et al.Non-destructive monitoring of forming quality of self-piercing riveting via a lightweight deep learning[J].Science Reports,2023,(13):6083.
[11] HE X C,XING B Y,ZENG K,et al.Numerical and experimental investigations of self-piercing riveting[J].The Intern-ational Journal of Advanced Manufacturing Technology,2013,(69):715-721.
[12] 邢保英，何晓聪，王玉奇，等.多铆钉自冲铆接头力学性能机理[J].吉林大学学报(工学版),2015,45(5):1488-1494.XING Baoying,HE Xiaocong,WANG Yuqi,et al.Mechanical properties mechanism of multi-rivet self-punch riveting joint[J].Journal of Jilin University(Engineering and Technology Edition),2015,45(5):1488-1494.
[13] 韩佳佳，贾继德，贾翔宇，等.基于幅值概率统计与SVM的柴油机失火故障诊断[J].军事交通学院学报，2018,20(2):45-50.HAN Jiajia,JIA Jide,JIA Xiangyu,et al.Diesel engine misfire fault diagnosis based on amplitude probability statisticsand SVM [J].Journal of Military Transportation University,2018,20(2):45-50.
基本信息:
DOI：
中图分类号:TG938
引用信息:
[1]李银波,杨建,邢保英等.基于声发射的铝合金薄板自冲铆成形过程分析[J].塑性工程学报,2025,32(05):52-59.
基金信息:
国家自然科学基金资助项目(51565022;52065034)