Advanced Search
WANG Chao, CHEN Xinyu, WU Chunbiao, LI Lei, WANG Jie. Optimization of 304 stainless steel laser welding process based on the fast bees test method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(2): 102-110. DOI: 10.12073/j.hjxb.20220325012
Citation: WANG Chao, CHEN Xinyu, WU Chunbiao, LI Lei, WANG Jie. Optimization of 304 stainless steel laser welding process based on the fast bees test method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(2): 102-110. DOI: 10.12073/j.hjxb.20220325012

Optimization of 304 stainless steel laser welding process based on the fast bees test method

More Information
  • Received Date: March 24, 2022
  • Available Online: February 15, 2023
  • Based on the engineering background of determining the reasonable combination of process parameters in engineers' proofing, a fast bees test method for optimizing process parameters was developed with reference to the ternary bees algorithm. Aiming at the high tensile strength requirement of 304 stainless steel plate in laser welding, the optimization results obtained by response surface method, bees algorithm optimization solution based on the fitting equation of response surface method and fast bees test method were compared. The optimal solutions predicted by the previous two methods were approximately 688 MPa, while the optimal process parameters obtained by the fast bees test method obtain the tensile strength of 734 MPa. The results show that compared with the response surface method, the fast bees test method can reduce the number of tests and avoid the problem of ignoring the different probability density in different regions. The fast bees test method can be used as a test method with low learning cost and emphasis on the result to highlight the test point, which can help engineers quickly obtain a better combination of process parameters in the process of proofing.
  • 吴晓红. 电池连接片紫铜激光焊工艺研究[J]. 应用激光, 2020, 40(1): 62 − 66.

    Wu Xiaohong. Research on laser welding process of copper in battery connector[J]. Applied Laser, 2020, 40(1): 62 − 66.
    曹海涛, 张鹏, 杜云慧, 等. Mg-Gd-Y-Zr激光焊工艺优化及高温力学性能[J]. 焊接学报, 2020, 41(10): 87 − 96.

    Cao Haitao, Zhang Peng, Du Yunhui, et al. Optimization of Mg-Gd-Y-Zr laser welding process parameters and study on high temperature mechanical properties[J]. Transactions of the China Welding Institution, 2020, 41(10): 87 − 96.
    王传洋, 郝云, 沈璇璇, 等. 工艺参数对激光透射焊接聚碳酸酯影响[J]. 焊接学报, 2016, 37(7): 57 − 60.

    Wang Chuanyang, Hao Yun, Shen Xuanxuan, et al. Effect of process parameters on laser transmission welding polycarbonate[J]. Transactions of the China Welding Institution, 2016, 37(7): 57 − 60.
    李莉, 张赛, 何强, 等. 响应面法在试验设计与优化中的应用[J]. 实验室研究与探索, 2015, 34(8): 41 − 45. doi: 10.3969/j.issn.1006-7167.2015.08.011

    Li Li, Zhang Sai, He Qiang, et al. Application of response surface methodology in experimental design and optimization[J]. Research and Exploration in Laboratory, 2015, 34(8): 41 − 45. doi: 10.3969/j.issn.1006-7167.2015.08.011
    Chelladurai S J S, Murugan K, Ray A P, et al. Optimization of process parameters using response surface methodology: A review[J]. Materials Today: Proceedings, 2021, 37: 1301 − 1304. doi: 10.1016/j.matpr.2020.06.466
    丁亚茹, 陈芙蓉, 杨帆, 等. 响应面法分析7075铝合金激光焊参数对焊接质量的影响规律[J]. 材料导报, 2021, 35(2): 2103 − 2108. doi: 10.11896/cldb.20070158

    Ding Yaru, Chen Furong, Yang Fan, et al. Analyzing the influence of laser welding parameters on the welding quality of 7075 aluminum alloy by response surface methodology[J]. Materials Reports, 2021, 35(2): 2103 − 2108. doi: 10.11896/cldb.20070158
    褚振涛, 于治水, 张培磊, 等. 基于响应面分析的T型接头激光深熔焊焊缝形貌预测及工艺参数优化[J]. 中国激光, 2015, 42(2): 108 − 116.

    Chu Zhengtao, Yu Zhishui, Zhang Peilei, et al. Weld profile prediction and process parameters optimization of T-joints of laser full penetration welding via response surface methodology[J]. Chinese Journal of Lasers, 2015, 42(2): 108 − 116.
    成奇, 郭宁, 付云龙, 等. 基于响应曲面法的铝合金激光封边焊接[J]. 焊接学报, 2022, 43(10): 1 − 10. doi: 10.12073/j.hjxb.20210903001

    Cheng Qi, Guo Ning, Fu Yunlong, et al. Study on laser edge sealing welding of aluminum alloy based on response surface method[J]. Transactions of the China Welding Institution, 2022, 43(10): 1 − 10. doi: 10.12073/j.hjxb.20210903001
    Goswami S, Ghosh S, Chakraborty S. Reliability analysis of structures by iterative improved response surface method[J]. Structural Safety, 2016, 60: 56 − 66. doi: 10.1016/j.strusafe.2016.02.002
    Guimarães H, Matos J C, Henriques A A. An innovative adaptive sparse response surface method for structural reliability analysis[J]. Structural Safety, 2018, 73: 12 − 28. doi: 10.1016/j.strusafe.2018.02.001
    Choudhary A, Kumar M, Gupta M K, et al. Mathematical modeling and intelligent optimization of submerged arc welding process parameters using hybrid PSO-GA evolutionary algorithms[J]. Neural Computing and Applications, 2020, 32(10): 5761 − 5774. doi: 10.1007/s00521-019-04404-5
    Vedrtnam A, Singh G, Kumar A. Optimizing submerged arc welding using response surface methodology, regression analysis, and genetic algorithm[J]. Defence Technology, 2018, 14(3): 204 − 212. doi: 10.1016/j.dt.2018.01.008
    王霄, 张成, 王凯, 等. 基于遗传算法-响应曲面方法的激光透射焊接聚碳酸酯工艺的多目标优化[J]. 中国激光, 2012, 39(6): 75 − 81.

    Wang Xiao, Zhang Cheng, Wang Kai, et al. Multi-objective optimization of laser transmission welding of polycarbonate process based on genetic algorithm-response surface methodology[J]. Chinese Journal of Lasers, 2012, 39(6): 75 − 81.
    余果, 尹玉环, 高嘉爽, 等. 基于正交试验-BP神经网络的GH4169膜片微束TIG焊接工艺优化[J]. 焊接学报, 2018, 39(11): 119 − 123,128. doi: 10.12073/j.hjxb.2018390285

    Yu Guo, Yin Yuhuan, Gao Jiashuang, et al. Orthogonal experiment method and BP neural networks in optimization of microbeam TIG welded GH4169[J]. Transactions of the China Welding Institution, 2018, 39(11): 119 − 123,128. doi: 10.12073/j.hjxb.2018390285
    Pham D T, Castellani M. A comparative study of the Bees Algorithm as a tool for function optimisation[J]. Cogent Engineering, 2015, 2(1): 1091540. doi: 10.1080/23311916.2015.1091540
    Laili Y, Tao F, Pham D T, et al. Robotic disassembly re-planning using a two-pointer detection strategy and a super-fast bees algorithm[J]. Robotics and Computer-Integrated Manufacturing, 2019, 59: 130 − 142. doi: 10.1016/j.rcim.2019.04.003
  • Related Articles

    [1]FAN Wenxue, CHEN Furong. Prediction and optimization of tensile strength of 7A52 aluminum alloy friction stir welding joints based on response surface methodology[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2021, 42(9): 55-60. DOI: 10.12073/j.hjxb.20210322001
    [2]JIA Zhihong, WAN Xiaohui, GUO Delun. Optimization of UHFP-GTAW process based on response surface method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2020, 41(6): 90-96. DOI: 10.12073/j.hjxb.20190807005
    [3]ZHOU Liucheng, ZHOU Lei, LI Yinghong, WANG Cheng. Effect of laser shock processing on tensile strength of welded joints[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2011, (4): 52-54,58.
    [4]JIANG Qinglei, LI Yajiang, WANG Juan, XU Zonglin, FU Jinliang. Strength matching on mechanical properties of welded joint of Q550 high strength steel[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2010, (10): 65-68.
    [5]GANG Tie, ZHAO Xuemei, LIN Sanbao, LUAN Yilin. Non-destructive evaluation of FSW tensile property[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2009, (6): 1-4.
    [6]XUE Song-bai, WU Yu-xiu, CUI Guo-ping, ZHANG Ling. Numerical simulation of effect of thermal cycling on tensile strength and microstructure of QFP soldered joint[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2006, (11): 1-4.
    [7]YAO Li-hua, XUE Song-bai, WANG Peng, LIU Lin. Effect of diode-laser parameters on tensile strength of QFP micro-joints[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2005, (10): 90-92.
    [8]HU Yong-fang, XUE Song-bai, YU Sheng-lin. Study on strength of soldered micro-joints of QFP devices[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2005, (10): 78-80.
    [9]HU Yong-fang, XUE Song-bai, SHI Yi-ping, YU Sheng-lin. Effects of lead-free solder on the tensile strength of QFP micro-joints soldered with different pitchs[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2005, (10): 72-74.
    [10]ZHU Liang, CHEN Jian-hang. Characteristics of stress distribution and prediction of strength inheat-affected zone softened welded joints[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2004, (3): 48-51.
  • Cited by

    Periodical cited type(3)

    1. 刘双耀,卢煜成,程文锋,王瑞权,王伟,高建森. 机器人CMT-P焊接参数对4043铝合金焊缝成形影响的试验研究. 金属加工(热加工). 2025(03): 56-62 .
    2. 任香会,梁文奇,王瑞超,韩善果,武威. 焊接模式对电弧增材制造316不锈钢组织及力学性能的影响. 焊接学报. 2024(04): 79-85+92+133-134 . 本站查看
    3. 姚屏,李文强,陈威,何日恒,张佩美,张广潮. 基于鲸鱼优化算法的焊缝尺寸预测. 焊接学报. 2024(11): 133-139 . 本站查看

    Other cited types(0)

Catalog

    Article views (235) PDF downloads (43) Cited by(3)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return