On-line monitoring of TIG welding quality of nuclear power plug tube based on arc spectrum

BAI Zijian; LI Zhiwen; ZHANG Zhifen; QIN Rui; ZHANG Shuai; XU Yaowen; WEN Guangrui

doi:10.12073/j.hjxb.20230610002

TRANSACTIONS OF THE CHINA WELDING INSTITUTION > 2024 > 45(5): 8-19. > DOI: 10.12073/j.hjxb.20230610002

BAI Zijian, LI Zhiwen, ZHANG Zhifen, QIN Rui, ZHANG Shuai, XU Yaowen, WEN Guangrui. On-line monitoring of TIG welding quality of nuclear power plug tube based on arc spectrum[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2024, 45(5): 8-19. DOI: 10.12073/j.hjxb.20230610002

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On-line monitoring of TIG welding quality of nuclear power plug tube based on arc spectrum

BAI Zijian^{1, 2,},
LI Zhiwen^{1, 2},
ZHANG Zhifen^{1, 2, ,},
QIN Rui^{1, 2},
ZHANG Shuai^{1, 2},
XU Yaowen³,
WEN Guangrui^{1, 2}

1.
National Key Laboratory of Aeronautical Power Systems and Plasma Technology, Xi'an Jiaotong University, Xi'an, 710049, China
2.
School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
3.
Xi’an Thermal Power Research Institute Co., Ltd., Xi'an, 710054, China

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Received Date: June 09, 2023
Available Online: March 08, 2024

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Abstract

Abstract

In order to monitor the quality of TIG welding for blocked tube welding of high-temperature gas-cooled reactor steam generators under the constraints of operation space and radiation environment, a real-time monitoring system based on a fiber optic spectrometer for TIG welding process was developed for monitoring the depth of penetration during welding. This study used the system to collect arc spectra and utilized Principal Component Analysis to obtain the spectral principal components of different weld penetration depths. An innovative ATT-L2R-BiLSTM deep learning model was proposed to achieve classification and recognition of weld penetration depth during blocked tube TIG welding. The results show that the model achieved an accuracy of 92.61% under laboratory conditions, which is 5.11% higher than that of the Bi-LSTM network. The model was tested and verified on a blocked tube verification platform for nuclear power steam generators, achieving an accuracy of 99.26%. Finally, deep mining of welding quality features and precise evaluation of weld penetration depth during TIG welding were achieved under incomplete spectral information.
- arc spectroscopy,
- tungsten inert gas shielded welding,
- principal component analysis,
- online monitoring,
- deep learning

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References (28)

References

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On-line monitoring of TIG welding quality of nuclear power plug tube based on arc spectrum