Keyhole Depth Prediction in Laser Deep Penetration Welding of Titanium Alloy Based on Spectral Information
Laser deep penetration welding has been widely applied in industrial fields. However, keyhole depth during the welding process significantly affects the service performance of final products. Based on the spectral signals generated in the laser welding process, this study employs a Long Short-Term M...
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MDPI AG
2025-05-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/15/5/527 |
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| author | Yunqian Li Yanfeng Gao Hao Pan Donglin Tao Hua Zhang |
| author_facet | Yunqian Li Yanfeng Gao Hao Pan Donglin Tao Hua Zhang |
| author_sort | Yunqian Li |
| collection | DOAJ |
| description | Laser deep penetration welding has been widely applied in industrial fields. However, keyhole depth during the welding process significantly affects the service performance of final products. Based on the spectral signals generated in the laser welding process, this study employs a Long Short-Term Memory (LSTM) neural network to predict keyhole depth in titanium alloy welding. A coaxial plasma optical information acquisition system is established to collect spectral signals emitted from the welding plasma and analyze the relationship between keyhole depth and plasma spectral features. By analyzing the spectral signals and calculating the plasma temperature, the mapping model between the plasma temperature and keyhole depth is built. The LSTM network prediction results show that the average relative error between the predicted and actual values is 2.31%, which demonstrates that the method proposed in this study has high accuracy for predicting keyhole depth in laser deep penetration welding. |
| format | Article |
| id | doaj-art-99424303fd97404daaac0ded408c64f4 |
| institution | OA Journals |
| issn | 2075-4701 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj-art-99424303fd97404daaac0ded408c64f42025-08-20T02:34:01ZengMDPI AGMetals2075-47012025-05-0115552710.3390/met15050527Keyhole Depth Prediction in Laser Deep Penetration Welding of Titanium Alloy Based on Spectral InformationYunqian Li0Yanfeng Gao1Hao Pan2Donglin Tao3Hua Zhang4School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaEngineering Research Center of Micro-Nano and Intelligent Manufacturing, Ministry of Education, Kaili 556011, ChinaSchool of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaLaser deep penetration welding has been widely applied in industrial fields. However, keyhole depth during the welding process significantly affects the service performance of final products. Based on the spectral signals generated in the laser welding process, this study employs a Long Short-Term Memory (LSTM) neural network to predict keyhole depth in titanium alloy welding. A coaxial plasma optical information acquisition system is established to collect spectral signals emitted from the welding plasma and analyze the relationship between keyhole depth and plasma spectral features. By analyzing the spectral signals and calculating the plasma temperature, the mapping model between the plasma temperature and keyhole depth is built. The LSTM network prediction results show that the average relative error between the predicted and actual values is 2.31%, which demonstrates that the method proposed in this study has high accuracy for predicting keyhole depth in laser deep penetration welding.https://www.mdpi.com/2075-4701/15/5/527laser deep penetration weldingkeyhole depth predictionLSTM modeltitanium alloy |
| spellingShingle | Yunqian Li Yanfeng Gao Hao Pan Donglin Tao Hua Zhang Keyhole Depth Prediction in Laser Deep Penetration Welding of Titanium Alloy Based on Spectral Information Metals laser deep penetration welding keyhole depth prediction LSTM model titanium alloy |
| title | Keyhole Depth Prediction in Laser Deep Penetration Welding of Titanium Alloy Based on Spectral Information |
| title_full | Keyhole Depth Prediction in Laser Deep Penetration Welding of Titanium Alloy Based on Spectral Information |
| title_fullStr | Keyhole Depth Prediction in Laser Deep Penetration Welding of Titanium Alloy Based on Spectral Information |
| title_full_unstemmed | Keyhole Depth Prediction in Laser Deep Penetration Welding of Titanium Alloy Based on Spectral Information |
| title_short | Keyhole Depth Prediction in Laser Deep Penetration Welding of Titanium Alloy Based on Spectral Information |
| title_sort | keyhole depth prediction in laser deep penetration welding of titanium alloy based on spectral information |
| topic | laser deep penetration welding keyhole depth prediction LSTM model titanium alloy |
| url | https://www.mdpi.com/2075-4701/15/5/527 |
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