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A data-driven model for weld bead monitoring during the laser welding assisted by magnetic field

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Abstract

In this research, a data-driven model is developed to monitor the seam during the laser beam welding under the influence of an external magnetic field (LBW-AMF). Firstly, a visible LBW-AMF system is built for tracking the laser melting pool and keyhole. Then, the features of the laser melting pool and keyhole are extracted with image processing techniques. The approach for an ensemble of different neural networks which includes radial basis function neural network, back-propagation neural network, and generalized regression neural network is proposed to establish the correlations of the characteristics of the laser melting pool and keyhole and the welding seam. Finally, LBW-AMF experimental results are obtained to validate the performance of the proposed data-driven model. Results illustrate that the developed model can provide a reliable result for monitoring the weld bead, which could give guidance for controlling the processing parameters in real time to improve the weld quality for practical LBW-AMF.

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Abbreviations

AK:

The area of the keyhole

WM:

The width of the molten pool

BPNN:

Back-propagation neural network

ENN:

The ensemble of neural networks

GRNN:

Generalized regression neural network

GTAW:

Gas tungsten arc welding

LK:

The length of the keyhole

LBW-AMF:

Laser beam welding assisted by magnetic field

MAE:

Maximum absolute error

WK:

The width of keyhole

MF:

Magnetic field

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Acknowledgments

This research has been supported by the National Natural Science Foundation of China (NSFC) under Grant No. 51805179, and the National Defense Innovation Program under Grant No. 18-163-00-TS-004-033-01.

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Authors and Affiliations

  1. School of Aerospace Engineering, Huazhong University of Science & Technology, Luoyu Road, 1037, Wuhan, People’s Republic of China

    Longchao Cao & Yuda Wu

  2. The State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science & Technology, Luoyu Road, 1037, Wuhan, People’s Republic of China

    Longchao Cao & Lili Zhang

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  1. Longchao Cao
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  2. Lili Zhang
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  3. Yuda Wu
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Correspondence to Lili Zhang.

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Cao, L., Zhang, L. & Wu, Y. A data-driven model for weld bead monitoring during the laser welding assisted by magnetic field. Int J Adv Manuf Technol 107, 475–487 (2020). https://doi.org/10.1007/s00170-020-05028-z

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