教师名录

陈华斌

研究员
所属二级机构:智能化焊接与材料精密制造研究所
硕导/博导:博导
通讯地址:上海市东川路800号材料F楼207室
电子邮箱:hbchen@sjtu.edu.cn
办公电话:34202740
论文信息
  • Wu D, Zhang P, Yu Z,Gao Y, Zhang H,Chen H,et al. Progress and perspectives of in-situ optical monitoring in laser beam welding: Sensing, characterization and modeling[J].Journal of Manufacturing Processes,2022,75: 767-791.
  • Ren X, Huang X, Chai Z, Chen H,et al. A study of dynamic energy partition in belt grinding based on grinding effects and temperature dependent mechanical properties[J]. Journal of Materials Processing Technology, 2021, 294: 117112.
  • Wu D, Chen Y, Chen H, et al. Influences of weaving parameters on dynamic characteristics and stability control of the droplet transfer in arc-weaving P-GMAW process[J]. The International Journal of Advanced Manufacturing Technology, 2022: 1-18.
  • Chen C, Xiao R, Chen H, et al. Prediction of welding quality characteristics during pulsed GTAW process of aluminum alloy by multisensory fusion and hybrid network model[J]. Journal of Manufacturing Processes, 2021, 68: 209-224.
  • Li L, Ren X, Feng H, et al. A novel material removal rate model based on single grain force for robotic belt grinding[J]. Journal of Manufacturing Processes, 2021, 68: 1-12.
  • Liu L, Chen H, Chen S. Quality analysis of CMT lap welding based on welding electronic parameters and welding sound[J]. Journal of Manufacturing Processes, 2022, 74: 1-13.
  • Feng H, Ren X, Li L, Chen H,et al. A novel feature-guided trajectory generation method based on point cloud for robotic grinding of freeform welds[J]. The International Journal of Advanced Manufacturing Technology, 2021, 115(5): 1763-1781.
  • Gao K, Chen H, Zhang X, et al. A novel material removal prediction method based on acoustic sensing and ensemble XGBoost learning algorithm for robotic belt grinding of Inconel 718[J]. The International Journal of Advanced Manufacturing Technology, 2019, 105(1): 217-232.
  • Zhang X, Chen H, Xu L, et al. Cracking mechanism and susceptibility of laser melting deposited Inconel 738 superalloy[J]. Materials & Design, 2019, 183: 108105.
  • Chen H, Song Y, Chen X, et al. In situ studies of full-field residual stress mapping of SS304 stainless steel welds using DIC[J]. The International Journal of Advanced Manufacturing Technology, 2020, 109(1): 45-55.
  • Zhang X, Chai Z, Chen H, et al. A novel method to prevent cracking in directed energy deposition of Inconel 738 by in-situ doping Inconel 718[J]. Materials & Design, 2021, 197: 109214.
  • Xiangfei W, Zhang X, Xukai R, Chen H,et al. Point cloud 3D parent surface reconstruction and weld seam feature extraction for robotic grinding path planning[J]. The International Journal of Advanced Manufacturing Technology, 2020, 107(1-2): 827-841.
  • Chen K, Chen H, Liu L, et al. Prediction of weld bead geometry of MAG welding based on XGBoost algorithm[J]. The International Journal of Advanced Manufacturing Technology, 2019, 101(9): 2283-2295.
  • Wu D, Huang Y, Zhang P, Chen H,et al. Visual-acoustic penetration recognition in variable polarity plasma arc welding process using hybrid deep learning approach[J]. IEEE Access, 2020, 8: 120417-120428.
  • Wu D, Huang Y, Chen H, et al. VPPAW penetration monitoring based on fusion of visual and acoustic signals using t-SNE and DBN model[J]. Materials & Design, 2017, 123: 1-14.
  • Huang Y, Wu D, Lv N, Chen H,et al. Investigation of porosity in pulsed GTAW of aluminum alloys based on spectral and X-ray image analyses[J]. Journal of Materials Processing Technology, 2017, 243: 365-373.
  • Wu D, Chen H, Huang Y, et al. Monitoring of weld joint penetration during variable polarity plasma arc welding based on the keyhole characteristics and PSO-ANFIS[J]. Journal of Materials Processing Technology, 2017, 239: 113-124.
  • Wu D, Chen H, Huang Y, et al. Online monitoring and model-free adaptive control of weld penetration in VPPAW based on extreme learning machine[J]. IEEE Transactions on Industrial Informatics, 2018, 15(5): 2732-2740.
  • Chen H, Wang J, Zhen G, et al. Effects of initial oxide on microstructural and mechanical properties of friction stir welded AA2219 alloy[J]. Materials & Design, 2015, 86: 49-54.
  • Zhang X, Chen H, Xu J, et al. A novel sound-based belt condition monitoring method for robotic grinding using optimally pruned extreme learning machine[J]. Journal of Materials Processing Technology, 2018, 260: 9-19.
专利著作
  • 一种机器人焊接过程多信息采集监控系统及方法,2021年授权,ZL 201710339759.6
  • 一种焊缝轮廓特征识别及其焊道实时规划的方法,2019年授权,ZL201710339759.6
  • 焊接装配间隙和错边前馈的熔池监控系统及熔透监测方法,2021年授权,ZL 201911204810.8
  • 一种激光增材过程功率联合调控方法,2021年授权,ZL202011131563.6
  • 一种等离子转移弧堆焊控制系统及控制方法,2021年授权,ZL202011432556.X
  • 基于视觉传感的管道全位置焊背面在线监测及特征提取方法,2022年授权,ZL202011358409.2
  • 基于三维数字图像相关方法的焊接应变测量系统及方法,2021年授权,ZL201911206871.8
  • 机器人焊接制造生产线无线网络监控系统,2016年授权,ZL201310462320.4
  • 搅拌摩擦焊接头弱连接缺陷制备方法,2015年授权,ZL 201310327248.4
  • 厚板机器人焊接系统及多层多道焊缝实时跟踪、规划方法,2016年授权,ZL 201410146344.3
  • 基于二维和三维数字图像相关法的焊接应变和应力计算软件,软著登字第7278741号
  • 基于激光视觉信息的多层多道焊接自适应规划系统软件,软著登字第4084814号
  • 基于工业云的焊接制造智能管理系统软件,软著登字第4068506号
  • 机器人TIG焊多信息监测及多参数控制软件系统,软著登字第4163588号
  • 基于单目视觉的初始焊位三维重建及线结构光标定系统,软著登字第2015753号
研究情况

近年来先后主持承担了国家自然科学基金3项、国家重点研发“SLM增材制造不锈钢激光填丝焊接头强韧化研究”专项1项、国家智能制造专项“航天结构制造数字化车间”子课题1项以及企业(中核、中车、上海航天等)横向合作课题多项。作为项目骨干参与了国家智能制造专项课题1项、国家自然基金面上项目1项以及国家自然基金联合基金重点项目1项。先后发表SCI/EI学术论文60余篇,授权国家发明专利15项,登记软著6项。

荣誉信息
  • 上海市科技进步二等奖
  • 上海交通大学“烛光奖励计划”二等奖
  • 上海交通大学“教学成果奖”特等奖
  • 上海交通大学晨星计划-SMC优秀青年教师
  • 中国机械工业科学技术一等奖
教育经历
  • 2009-01    上海交通大学   材料科学与工程     博士
工作经历
  • 2022-01 ~ 至今    上海交通大学  材料科学与工程学院研究员、博士生导师,从事复杂场景下的智能化焊接研究和教学工作。
  • 2014-01 ~ 2015-01    美国橡树岭国家实验室(Oak Ridge National Laboratory,ORNL)  ASTRO高级研究员,从事储氢装置开发与接头残余应力中子衍射表征研究。
研究方向
  • 焊接多信息传感及知识建模
  • 数字化与智能化焊接工程应用