Abstract
Multi-layer multi-pass (MLMP) welding of medium thickness plate is always the focus and difficulty of research and application. It is widely used in shipbuilding and pressure vessel manufacturing. This paper summarizes the research developments of MLMP in recent years, including welding technologies, advances and future prospects. In welding technology, some modified welding techniques are included, such as ASDAW. The welding simulation process is also discussed in detail. In automation part, the novel feature extraction methods based on different sensing techniques are summarized. Then, the emphasis is laid on the researches of recent years on path planning model and seam tracking techniques. At the end of this paper, summary is made and future prospects of application of advanced technology in intelligent robotic MLMP welding are given. And the promising development directions of MLMP are prospected in intelligent robotic welding of medium thickness plate.
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References
Zhang HJ (2009) New technology of double-side double arc welding and robot automatic welding for large thick plate of high strength steel. Harbin Institute of Technology
Zhang H, Zhang G, Cai C et al (2008) Fundamental studies on in-process controlling angular distortion in asymmetrical double-sided double arc welding. J Mater Process Technol 205(1–3):214–223
Miao Y, Xu X, Wu B et al (2014) Effects of bypass current on the stability of weld pool during double sided arc welding. J Mater Process Technol 214(8):1590–1596
Zhang HJ, Zhang GJ, Zhang XL et al Three dimension simulation analysis of the interpass stress and deformation during multipass welding. China Weld 72–78.
Chen YX, Xu YL, Chen HB, Zhang HJ, Chen SB, Han Y (2015) Temperature field of double-sided asymmetrical mag backing welding for thick plates. In: Tarn TJ, Chen SB, Chen XQ (eds) Robotic welding, intelligence and automation. RWIA 2014. Advances in Intelligent Systems and Computing, vol 363. Springer, Cham. https://doi.org/10.1007/978-3-319-18997-0_19
Wang J, Chen Q, Sun Z (2004) Multi-pass weld profile detection for spherical tank through “quasi double cameras” stereovision sensor. In: International conference on information acquisition, 2004 Proceedings. Hefei, pp 376–379. https://doi.org/10.1109/ICIA.2004.1373393
Ding Y, Huang W, Kovacevic R (2016) An online shape-matching weld seam tracking system. Robot Comput-Integr Manuf 42:103–112
Xu Y, Yu H, Zhong J et al (2012) Real-time seam tracking control technology during welding robot GTAW process based on passive vision sensor. J Mater Process Technol 212(8):1654–1662
Zou Y, Chen T (2018) Laser vision seam tracking system based on image processing and continuous convolution operator tracker. Opt Lasers Eng 105:141–149
Jeong S-W, Lee G-Y, Lee W-K, Kim S-B (2001) Development of high speed rotating arc sensor and seam tracking controller for welding robots. In: ISIE 2001. 2001 IEEE international symposium on industrial electronics proceedings (Cat. No. 01TH8570), vol 2. Pusan, South Korea, pp 845–850. https://doi.org/10.1109/ISIE.2001.931578
Jinle Z, Baohua C, Dong D et al (2018) A weld position recognition method based on directional and structured light information fusion in multi-layer/multi-pass welding. Sensors 18(2):129
Zhang HJ, Zhang GJ, Wu L (2007) Effects of arc distance on angular distortion by asymmetrical double sided arc welding. Sci Technol Weld Joining 12(6):564–571
Chen Y, Yang C, Chen H et al (2015) Microstructure and mechanical properties of HSLA thick plates welded by novel double-sided gas metal arc welding. Int J Adv Manuf Technol 78(1–4):457–464
Yang C, Zhang H, Zhong J et al (2014) The effect of DSAW on preheating temperature in welding thick plate of high-strength low-alloy steel. Int J Adv Manuf Technol 71(1–4):421–428
Jiang Z, Hua X, Huang L et al (2019) High efficiency and quality of multi-pass tandem gas metal arc welding for thick Al 5083 alloy plates. J Shanghai Jiaotong Univ (Sci) 24:148–157. https://doi.org/10.1007/s12204-018-1977-y
Zhang HJ, Zhang GJ, Cai CB et al (2009) Numerical simulation of three-dimension stress field in double-sided double arc multipass welding process. Mater Sci Eng a 499(1–2):309–314
Chen Y, He Y, Chen H et al (2014) Effect of weave frequency and amplitude on temperature field in weaving welding process. Int J Adv Manuf Technol 75(5–8):803–813
Zhang C, Li H, Jin Z, et al (2016) Seam sensing of multi-layer and multi-pass welding based on grid structured laser. Int J Adv Manuf Technol 2016
He Y, Zhou H, Wang J et al. (2016) Weld seam profile extraction of T-joints based on orientation saliency for path planning and seam tracking. In: Advanced robotics and its social impacts. IEEE
Zhu J, Wang J, Su N et al (2017) An infrared visual sensing detection approach for swing arc narrow gap weld deviation. J Mater Process Technol 243:258–268
Yang C, Ye Z, Chen Y et al (2014) Multi-pass path planning for thick plate by DSAW based on vision sensor. Sensor Rev 34(4):416–423
Yang CD, Huang HY, Zhang HJ et al (2012) Multi-pass route planning for thick plate of low alloy high strength steel by double-sided double arc welding. Adv Mater Res 590:28–34
Chang D, Son D, Lee J et al (2012) A new seam-tracking algorithm through characteristic-point detection for a portable welding robot. Robot Comput Integr Manuf 28(1):1–13
Zhang H, Lu H, Cai C et al (2011) Robot path planning in multi-pass weaving welding for thick plates
Zhang X (2015) Research on robotic welding system and multipass planning based on laser vision sensor. Shanghai Jiao Tong University
Wu Y, Go JZM, Ahmed SM, Lu W, Chew C, Pang CK (2015) Automated bead layout methodology for robotic multi-pass welding. In: 2015 IEEE 20th conference on emerging technologies and factory automation (ETFA). Luxembourg, pp 1–4, https://doi.org/10.1109/ETFA.2015.7301590
Ahmed SM, Yuan J, Wu Y, Chew CM, Pang CK (2015) Collision-free path planning for multi-pass robotic welding. In: 2015 IEEE 20th conference on emerging technologies and factory automation (ETFA). https://doi.org/10.1109/etfa.2015.7301594
Fang H, Ong S, Nee A (2016) Robot path planning optimization for welding complex joints. International Journal of Advanced Manufacturing Technology
Yan S, Fang H, Ong S et al (2017) Optimal pass planning for robotic welding of large-dimension joints with nonuniform grooves. Proc Inst Mech Eng Part B J Eng Manuf 2017:095440541771887
Xue K, Wang Z, Shen J, Hu S, Zhen Y, Liu J, Yang H (2020) Robotic seam tracking system based on vision sensing and human-machine interaction for multi-pass MAG welding. J Manuf Process
Horváth CM, Korondi P, Thomessen T (2017) Robotized multi-pass tungsten inner gas welding of Francis hydro power turbines. In: IEEE international symposium on industrial electronics. IEEE
He Y, Yu Z, Li J et al (2020) Discerning weld seam profiles from strong arc background for the robotic automated welding process via visual attention features. Chin J Mech Eng 33:21. https://doi.org/10.1186/s10033-020-00438-2
He Y, Yu Z, Li J et al (2019) Weld seam profile extraction using top-down visual attention and fault detection and diagnosis via EWMA for the stable robotic welding process. Int J Adv Manuf Technol 104:3883–3897. https://doi.org/10.1007/s00170-019-04119-w
Baek D, Moon HS, Park S (2017) Development of an automatic orbital welding system with robust weaving width control and a seam-tracking function for narrow grooves. Int J Adv Manuf Technol 93:767–777. https://doi.org/10.1007/s00170-017-0562-0
Gunnarsson KT, Prinz FB (1984) Ultrasonic sensors in robotic seam tracking. In: American control conference. IEEE
Yu P, Xu G, Gu X et al (2017) A low-cost infrared sensing system for monitoring the MIG welding process. Int J Adv Manuf Technol 92:4031–4038. https://doi.org/10.1007/s00170-017-0515-7
Mirapeix J, Cobo A, Conde OM (2006) Real-time arc welding defect detection technique by means of plasma spectrum optical analysis. NDT & E Int 39(5):356–360
Li PJ, Zhang YM (2001) Precision sensing of arc length in GTAW based on arc light spectrum. J Manuf Sci Eng 123(1):62
Ma X, Pan S, Li Y, Feng C, Wang A (2019) Intelligent welding robot system based on deep learning. In: 2019 Chinese automation congress (CAC). Hangzhou, China, pp 2944–2949. https://doi.org/10.1109/CAC48633.2019.8997310
Luo RC, Chou YC, Chen O (2007) Multisensor fusion and integration: algorithms, applications, and future research directions. In: International conference on mechatronics and automation. IEEE
Chen B, Wang J, Chen S (2010) Prediction of pulsed GTAW penetration status based on BP neural network and D-S evidence theory information fusion. Int J Adv Manuf Technol 48(1–4):83–94
Acknowledgements
This work is partly supported by the National Natural Science Foundation of China (No. 61873164, 61973213) and the Shanghai Natural Science Foundation (No.18ZR1421500).
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Xu, F., Xiao, R., Hou, Z., Xu, Y., Zhang, H., Chen, S. (2021). Multi-layer Multi-pass Welding of Medium Thickness Plate: Technologies, Advances and Future Prospects. In: Chen, S., Zhang, Y., Feng, Z. (eds) Transactions on Intelligent Welding Manufacturing. Transactions on Intelligent Welding Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-33-6502-5_1
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