Analysis of Rust Removal Performance of Q235 Steel by Laser Rust Removal Process based on Ridge Regression and Lasso Regression

Feng Jiang

doi:10.6919/ICJE.202506_11(6).0025

Authors

Feng Jiang

DOI:

https://doi.org/10.6919/ICJE.202506_11(6).0025

Keywords:

Laser Rust Removal; Ridge Regression; Lasso Regression; Predict.

Abstract

Laser rust removal is an effective method for eliminating rust from steel surfaces. The performance of rust removal is crucial for steel reuse, necessitating accurate prediction of laser derusting effects. This study evaluates the rust removal performance by analyzing the rust ratio before and after laser treatment on Q235 steel. Ridge regression and Lasso regression were employed to address multicollinearity among influencing factors, establishing two modified multiple regression models to predict derusting performance. These predictions were compared with actual experimental results. The findings reveal that the ridge regression model achieved an RMSE of 0.2379, while the Lasso regression model yielded an RMSE of 0.2460. The Lasso regression model demonstrated superior fitting performance, with predicted values closer to the actual results.

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References

[1] Mobin M, Aslam R. Experimental and theoretical study on corrosion inhibition performance of environmentally benign non-ionic surfactants for mild steel in 3.5% NaCl solution[J]. Process Safety and Environmental Protection, 2018(1): 279-295.

[2] Li XA, Wang WB. Overview of metal corrosion hazards and protection[J]. Chemical Enterprise Management, 2013(12): 158.

[3] Tong YQ, Zhang A, Huang JY, et al. Distribution and influence of oxygen content of laser pretreated aluminum alloy surface before welding[J]. Chinese Journal of Lasers, 2019, 46(2): 0202003.

[4] Xia PY, Yin YH, Cai AJ, et al. Laser cleaning of anodized films on 2219 aluminum alloy before welding[J]. Chinese Journal of Lasers, 2019, 46(1): 115–121.

[5] Qiu ZB, Zhu HH. Pulsed laser derusting process research[J]. Applied Laser, 2013, 33(4): 416–420.

[6] Zhang GX, Hua XM, Li F, et al. Research and application status of laser de-rusting and de-painting[J]. Hot Working Technology, 2019, 48(18): 1–4.

[7] Salimbeni R, Pini R, Siano S. Achievement of optimum laser cleaning in the restoration of artworks[J]. Spectrochimica Acta Part B: Atomic Spectroscopy, 2001, 56(6): 877–885.

[8] Pouli P, Fotakis C, Hermosin B, et al. The laser-induced discoloration of stonework[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2008, 71(3): 932–945.

[9] Daurélio G, Chita G, Cinqueplami M. New laser surface treatments: Cleaning, derusting, deoiling, depainting, deoxidizing, and degreasing[J]. Proceedings of SPIE, 1997, 3097: 369–391.

[10] Tian B, Zou WF, Liu SJ, et al. Introduction of rust removed by dry laser cleaning[J]. Cleaning World, 2006, 22(8): 33–38.

[11] Mateo MP, Ctvrtnickova T, Fernandez E, et al. Laser cleaning of varnishes and contaminants on brass[J]. Applied Surface Science, 2009, 255(10): 5579–5583.

[12] Li W. Mechanism and equipment development for laser rust removal[D]. Tianjin: Nankai University, 2014.

[13] Zhang J, Wang Y, Cheng P, et al. Effect of pulsing parameters on laser ablative cleaning of copper oxides[J]. Journal of Applied Physics, 2006, 99(6): 2217.

[14] Shen Q, Tong YQ, Ma GD. Study on surface roughness of the substrate after laser derusting[J]. Laser & Infrared, 2014, 44(6): 605–608.