Citation: | XU Fei, CHEN Li, LU Wei, GUO Luyun. Effect of heat input on weld appearance for fiber laser welding 6A02 aluminum alloy[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2017, 38(8): 119-123. DOI: 10.12073/j.hjxb.20150830004 |
左铁钏, 肖荣诗, 陈 铠, 等. 高强铝合金的激光加工[M]. 北京: 国防工业出版社, 2002.[2] 陈 俐, 巩水利. 铝合金激光焊接技术的应用与发展[J]. 航空制造技术, 2011(11): 46-49. Chen Li, Gong Shuili. Application and development of laser welding technology for aluminum alloy[J]. Aeronautical Manufacturing Technology, 2011(11): 46-49.[3] Quintino L, Costa A, Miranda R,etal. Welding with high power fiber lasers-a preliminary study[J]. Materials and Design, 2007, 28(4): 1231-1237.[4] 陈 俐. 航空钛合金激光全熔透稳定性及焊接物理冶金研究[D]. 武汉: 华中科技大学, 2005.[5] 姚 伟, 巩水利, 陈 俐. 钛合金激光穿透焊的焊缝成形(Ⅱ)[J]. 焊接学报, 2004, 25(5): 74-76. Yao Wei, Gong Shuili, Chen Li. Weld shaping for laser fully penetration welding titanium alloy(Ⅱ)[J]. Transactions of the China Welding Institution, 2004, 25(5): 74-76.[6] 许 飞, 巩水利, 陈 俐, 等. 钛合金光纤激光焊接接头特征分析[J]. 航空制造技术, 2013, 436(16): 90-92. Xu Fei, Gong Shuili, Chen Li,etal. Characteristics of titanium alloy by fibre laser welding[J]. Welding Technology in Aerospace Industry, 2013, 436(16): 90-92.[7] 许 飞, 杨 璟, 巩水利, 等. 热输入对铝合金光纤激光穿透焊缝成形的影响[J]. 中国激光, 2014, 41(12): 1203001. Xu Fei, Yang Jing, Gong Shuili,etal. Effect of heat input on weld appearance for fiber laser beam full penetration welding aluminum alloy[J]. Chinese Journal of Lasers, 2014, 41(12): 1203001.[8] 中国航空材料手册编辑委员会. 中国航空材料手册第3卷, 铝合金 镁合金[M]. 第2版. 北京: 中国标准出版社, 2002,[9] 温 鹏, 张旭东, 陈武柱, 等. 薄板激光焊时失稳变形及其控制[J]. 焊接学报, 2006, 27(9): 99-102. Wen Peng, Zhang Xudong, Chen Wuzhu,etal. Buckling distortion of laser welded thin plates and its control by dynamic cooling[J]. Transactions of the China Welding Institution, 2006, 27(9): 99-102.[10] 闫俊霞, 霍立兴, 张玉凤, 等. 焊接薄板失稳变形预测方法[J]. 焊接学报, 2005, 26(6): 50-53. Yan Junxia, Huo Lixing, Zhang Yufeng,etal. Prediction method of buckling distortion of welding thin plate[J]. Transactions of the China Welding Institution, 2005, 26(6): 50-53.[11] Chon L T, Han M S. Thermal and mechanical evolution of welding induced buckling distortion[J]. Journal of the Chinese Institute of Engineers, 2004, 27(6): 905-918.[12] Michaleris P, Debiccari A. Prediction of welding distortion[J]. Welding Journal, 1997, 76(4): 172-181.[13] 陈伯蠡. 焊接冶金原理[M]. 北京: 清华大学出版社, 1991.[14] 周振丰. 焊接冶金学(金属焊接性)[M]. 北京: 机械工业出版社, 1995.
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