[1] Chen Y, Hong Z H, Liao Y H et al. Automatic detection of display defects for smart meters based on deep learning[J]. Journal of Computing and Information Technology, 28, 241-254(2021).

[2] Lin S, He Z Y, Sun L N. A novel micro-defect classification system based on attention enhancement[J]. Journal of Intelligent Manufacturing, 35, 703-726(2024).

[3] Zhu Y F, Yao L Z, Zhou X Y et al. Classification of thyroid ultrasound standard section based on ResNet-cbam[J]. Proceedings of SPIE, 12716, 127160V(2023).

[4] Yan P, Wang G, Chen J et al. Skin lesion classification based on the VGG-16 fusion residual structure[J]. International Journal of Imaging Systems and Technology, 33, 53-68(2023).

[5] Pan Q, Yu Y N, Berihu H H. Research on lightweight few-shot learning algorithm based on convolutional block attention mechanism[J]. International Journal of Computational Intelligence and Applications, 22, 2350020(2023).

[6] Quesne N L. How to weld stainless steel with keyhole TIG[EB/OL]. https:∥www.fabricatingandmetalworking.com/2017/10/how-to-weld-stainless-steel-with-keyhole-tig/

[7] Wu S, Wang G L, Jiang N et al. Fault diagnosis of wind turbine blades based on image fusion and ResNet[J]. Journal of Physics: Conference Series, 2718, 012059(2024).

[8] Tao X R, Gao H J, Yang K et al. Expanding the defect image dataset of composite material coating with enhanced image-to-image translation[J]. Engineering Applications of Artificial Intelligence, 133, 108590(2024).

[9] González Olivares E A, Gonçalves e Silva R H, Dutra J C. Study of keyhole TIG welding by comparative analysis of two high-productivity torches for joining medium-thickness carbon steel plates[J]. Welding International, 31, 337-347(2017).

[10] Huang Y F, Luo Z, Wang Z M et al. Numerical simulation of temperature fields in backside water-cooling keyhole TIG welding[J]. Transactions of the China Welding Institution, 38, 103-107(2017).

[11] Zhang L F, Wang F, Liu H B et al. Numerical simulation of keyhole-TIG welding arc based on Fluent software[J]. Heat Treatment, 38, 35-40, 49(2023).

[12] Zhang B R, Shi Y H, Cui Y X et al. Prediction of keyhole TIG weld penetration based on high-dynamic range imaging[J]. Journal of Manufacturing Processes, 63, 179-190(2021).

[13] Karppi R. Keyhole TIG-a new welding process for stainless steel[J]. Hitsaustekniikka, 54, 3-10(2004).

[14] Liu Z M, Fang Y X. Keyhole thermal behaviour in K-TIG welding[C](2017).

[15] Liu Z M, Fang Y X, Cui S L et al. Sustaining the open keyhole in slow-falling current edge during K-TIG process: Principle and parameters[J]. International Journal of Heat and Mass Transfer, 112, 255-266(2017).

[16] Han T, Gu S W, Xu L et al. Study on stress and deformation of keyhole gas tungsten arc-welded joints[J]. China Welding, 29, 17-25(2020).

[17] Sun J S, Wu C S, Dong B L et al. Numerical simulation of keyhole formation during PAW+TIG double-sided arc welding[J]. Acta Metallrugica Sinica, 39, 79-84(2003).

[18] Gong W, Zhao W H, Wang X T et al. Machine learning for laser micro/nano manufacturing: applications and prospects[J]. Chinese Journal of Lasers, 50, 2000001(2023).

[19] Zhang B R, Gu S Y, Shi Y H. Robotic deep penetration K-TIG welding system based on weld penetration detection[J]. Journal of Mechanical Engineering, 55, 14-21(2019).

[20] Bonser G R, Lawson S W. Defect detection in partially completed SAW and TIG welds using online radioscopy and image processing[J]. Proceedings of SPIE, 3399, 231-239(1998).

[21] Manoharan N, Rani B S, Venkataraman B et al. Automatic detection and quantification of incomplete penetration in TIG welding through segmentation and morphological image processing of thermographs[EB/OL]. https:∥www.ndt.net/search/docs.php3?id=4414

[22] Ma D Y, Shu L S, Zhou Q et al. Online porosity defect detection based on convolutional neural network for Al alloy laser welding[J]. Journal of Physics: Conference Series, 1884, 012008(2021).

[23] Teker T, Karakurt E M, Demir F. Mechanical property effects of symmetrical hour glass shapes formed during double-sided TIG keyhole arc welding of AISI1040 joints[J]. Materials Testing, 59, 524-529(2017).

[24] Zhang B R, Shi Y H, Gu S Y. Narrow-seam identification and deviation detection in keyhole deep-penetration TIG welding[J]. The International Journal of Advanced Manufacturing Technology, 101, 2051-2064(2019).