Chinese Journal of Lasers, Volume. 49, Issue 8, 0802010(2022)

Elman-Neural-Network Based Prediction of Microsecond Laser Coloring on Stainless Steel

Longda Zhang, Haofa Li, Fengshuo An, Zhiwen Wang*, and Hongyu Zheng
Author Affiliations
  • School of Mechanical Engineering, Shandong University of Technology, Zibo, Shandong 255000, China
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    Conclusions

    By adjusting the process parameters of the ultraviolet microsecond laser, stable colors including black, blue, purple, purple-red, orange, and light yellow are induced on the surface of 304 stainless steel. Coloring mechanism of 304 stainless steel induced by the microsecond laser is discussed and believed to be the color of the oxide layer and the film interference effect. The HSB values of the color patches are predicted by using the Elman neural network for the given laser parameters. The predicted results show that the average relative errors of hue, saturation, and brightness are 4.04%, 13.33% and 4.05%, respectively. The colors of the processed pattern have a good consistency with the predicted colors.

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    Longda Zhang, Haofa Li, Fengshuo An, Zhiwen Wang, Hongyu Zheng. Elman-Neural-Network Based Prediction of Microsecond Laser Coloring on Stainless Steel[J]. Chinese Journal of Lasers, 2022, 49(8): 0802010

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    Paper Information

    Category: laser manufacturing

    Received: Aug. 18, 2021

    Accepted: Oct. 9, 2021

    Published Online: Mar. 23, 2022

    The Author Email: Zhiwen Wang (wangzhiwen@sdut.edu.cn)

    DOI:10.3788/CJL202249.0802010

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