Progress and perspectives of in-situ optical monitoring in laser beam welding: Sensing, characterization and modeling

被引:63
作者
Wu, Di [1 ,2 ,4 ]
Zhang, Peilei [1 ,2 ,5 ]
Yu, Zhishui [1 ,2 ]
Gao, Yanfeng [1 ,3 ]
Zhang, Hua [1 ,3 ]
Chen, Huabin [4 ]
Chen, Shanben [4 ]
Tian, YingTao [6 ]
机构
[1] Shanghai Univ Engn Sci, Sch Mat Engn, Shanghai 201620, Peoples R China
[2] Shanghai Collaborat Innovat Ctr Laser Mfg Technol, Shanghai 201620, Peoples R China
[3] Shanghai Collaborat Innovat Ctr Intelligent Mfg R, Shanghai 201620, Peoples R China
[4] Shanghai Jiao Tong Univ, Shanghai 200240, Peoples R China
[5] Fraunhofer Inst Laser Technol ILT, D-52074 Aachen, Germany
[6] Univ Lancaster, Dept Engn, Lancaster LA1 4YW, England
基金
美国国家科学基金会; 中国博士后科学基金;
关键词
Laser beam welding; Optical monitoring; Behavior characterization; Machine learning; Weld quality; Process model; MOLTEN POOL; DEFECTS DETECTION; NEURAL-NETWORK; ACOUSTIC-EMISSION; STAINLESS-STEEL; PLASMA PLUME; X-RAY; POROSITY FORMATION; SPATTER FORMATION; KEYHOLE GEOMETRY;
D O I
10.1016/j.jmapro.2022.01.044
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Laser beam welding manufacturing (LBW), being a promising joining technology with superior capabilities of high-precision, good-flexibility and deep penetration, has attracted considerable attention over the academic and industry circles. To date, the lack of repeatability and stability are still regarded as the critical technological barrier that hinders its broader applications especially for high-value products with demanding requirements. One significant approach to overcome this formidable challenge is in-situ monitoring combined with artificial intelligence (AI) techniques, which has been explored by great research efforts. The main goal of monitoring is to gather essential information on the process and to improve the understanding of the occurring complicated weld phenomena. This review firstly describes ongoing work on the in-situ optical sensing, behavior characterization and process modeling during dynamic LBW process. Then, much emphasis has been placed on the optical radiation techniques, such as multi-spectral photodiode, spectrometer, pyrometer and high-speed camera for observing the laser physical phenomenon including melt pool, keyhole and vapor plume. In particular, the advanced image/signal processing techniques and machine-learning models are addressed, in order to identify the correlations between process parameters, process signatures and product qualities. Finally, the major challenges and potential solutions are discussed to provide an insight on what still needs to be achieved in the field of process monitoring for metal-based LBW processes. This comprehensive review is intended to provide a reference of the state-of-the-art for those seeking to introduce intelligent welding capabilities as they improve and control the welding quality.
引用
收藏
页码:767 / 791
页数:25
相关论文
共 195 条
  • [1] Abt F, 2011, INT C APPL LASERS EL, P179
  • [2] Novel X-ray System for in-situ Diagnostics of Laser Based Processes - First Experimental Results
    Abt, Felix
    Boley, Meiko
    Weber, Rudolf
    Graf, Thomas
    Popko, Gregor
    Nau, Siegfried
    [J]. LASERS IN MANUFACTURING 2011: PROCEEDINGS OF THE SIXTH INTERNATIONAL WLT CONFERENCE ON LASERS IN MANUFACTURING, VOL 12, PT A, 2011, 12 : 761 - 770
  • [3] Optical sensor for real-time monitoring of CO2 laser welding process
    Ancona, A
    Spagnolo, V
    Lugarà, PM
    Ferrara, M
    [J]. APPLIED OPTICS, 2001, 40 (33) : 6019 - 6025
  • [4] Andrev A., 2009, LASER TECHNIK J, V5, P20
  • [5] Simulation and experimental analysis of acoustic signal characteristics in laser welding
    Ao, Sansan
    Luo, Zhen
    Feng, Mengnan
    Yan, Fuyu
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2015, 81 (1-4) : 277 - 287
  • [6] Process monitoring of laser welding using chromatic filtering of thermal radiation
    Baik, SH
    Kim, MS
    Park, SK
    Chung, CM
    Kim, CJ
    Kim, KJ
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2000, 11 (12) : 1772 - 1777
  • [7] More Is Less: Signal Processing and the Data Deluge
    Baraniuk, Richard G.
    [J]. SCIENCE, 2011, 331 (6018) : 717 - 719
  • [8] Optical techniques for real-time penetration monitoring for laser welding
    Bardin, F
    Cobo, A
    Lopez-Higuera, JM
    Collin, O
    Aubry, P
    Dubois, T
    Högström, M
    Nylen, P
    Jonsson, P
    Jones, JDC
    Hand, DP
    [J]. APPLIED OPTICS, 2005, 44 (19) : 3869 - 3876
  • [9] Bautze T., 2015, LASERS MANUFACTURING, P1
  • [10] Bhujbal VD, 2013, INT J ENG SCI INNOV, V2, P221