Investigation on fatigue life prediction approach of welded joints via integrated data-driven method

FENG Chao; ZHAO Lei; XU Lianyong; HAN Yongdian

doi:10.12073/j.hjxb.20221116002

TRANSACTIONS OF THE CHINA WELDING INSTITUTION > 2023 > 44(11): 8-13, 51. > DOI: 10.12073/j.hjxb.20221116002

FENG Chao, ZHAO Lei, XU Lianyong, HAN Yongdian. Investigation on fatigue life prediction approach of welded joints via integrated data-driven method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(11): 8-13, 51. DOI: 10.12073/j.hjxb.20221116002

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Investigation on fatigue life prediction approach of welded joints via integrated data-driven method

FENG Chao^{1, 2,},
ZHAO Lei^{1, 2},
XU Lianyong^{1, 2, ,},
HAN Yongdian^{1, 2}

1.
School of Materials Science and Engineering, Tianjin University, Tianjin 300350, China
2.
Tianjin Key Laboratory of Advanced Joining Technology, Tianjin 300350, China

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Received Date: November 15, 2022
Available Online: August 18, 2023

Graphical Abstract

Abstract

Abstract

In this study, a novel intelligent fatigue life prediction approach was established via the integrated data-driven method (Borderline-Synthetic Minority Over-Sampling Technique, eXtreme Gradient Boosting, Deep Convolutional Neural Network). Among them, the Borderline-Synthetic Minority Over-Sampling Technique was used to enhance the data quality of the fatigue performance dataset, the eXtreme Gradient Boosting was used to realize the weight analysis of the influencing factors of fatigue life, and the Deep Convolutional Neural Network was used as the model framework to understand the multiple nonlinear relationships between fatigue life and its influencing factors. Based on the analysis of different technology combinations, it was found that weight analysis and data augmentation were both beneficial for improving prediction accuracy, with the former having better results than the latter. And by comparing with other novel prediction models, the accuracy and stability of the proposed method were verified.
- fatigue life,
- life prediction,
- data-driven,
- welded joints

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References (26)

References

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Investigation on fatigue life prediction approach of welded joints via integrated data-driven method