Mechanism and characterization of nanosecond laser rust-removal on AH36 steel

Qing Tao , Wenxiang Kuang , Liangpeng Wei , Yegang Yin , Jian Cheng , Dun Liu

Optoelectronics Letters ›› 2023, Vol. 19 ›› Issue (4) : 227 -234.

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Optoelectronics Letters ›› 2023, Vol. 19 ›› Issue (4) : 227 -234. DOI: 10.1007/s11801-023-2136-8
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Mechanism and characterization of nanosecond laser rust-removal on AH36 steel

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Abstract

In this paper, the effects of different laser powers, repetition rates, and spot overlaps on the surface roughness, micro-morphology, and Vickers hardness of rusted AH36 steel were researched in the rust removal experiment of fiber pulse laser on the marine steel surface. Then, the mechanical properties, corrosion resistance, and metallographic microstructure of the surface of samples after laser cleaning were analyzed. The experimental results show that when the processing parameters were the laser power of 40 W, the repetition rate of 110 kHz, and the spot overlap of 50%, the rust removal effect on AH36 steel was the best, and it met the cleanliness standard of marine steel coating. Moreover, its Vickers hardness, mechanical properties, corrosion resistance, and repainting properties were superior to those of the original substrate.

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Qing Tao, Wenxiang Kuang, Liangpeng Wei, Yegang Yin, Jian Cheng, Dun Liu. Mechanism and characterization of nanosecond laser rust-removal on AH36 steel. Optoelectronics Letters, 2023, 19(4): 227-234 DOI:10.1007/s11801-023-2136-8

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References

[1]

TianY, ZhangG, MorimotoK, et al.. Automated rust removal: rust detection and visual servo control[J]. Automation in construction, 2022, 134: 104043

[2]

ChoudhuryM D, DasS, BanpurkarA G, et al.. Regression analysis of wetting characteristics for different random surface roughness of polydimethylsiloxane using sandpapers[J]. Colloids and surfaces A: physicochemical and engineering aspects, 2022, 647: 129038

[3]

YabeA, OkadaM, HaraE S, et al.. Self-adhering implantable device of titanium: enhanced soft-tissue adhesion by sandblast pretreatment[J]. Colloids and surfaces B: biointerfaces, 2022, 211: 112283

[4]

LuY, DingY, WangG, et al.. Ultraviolet laser cleaning and surface characterization of AH36 steel for rust removal[J]. Journal of laser applications, 2020, 32(3):032023

[5]

NarayananV, SinghR K, MarlaD. Laser cleaning for rust removal on mild steel: an experimental study on surface characteristics[J]. MATEC web of conferences, 2018, 221: 01007

[6]

SianoS, SalimbeniR. Advances in laser cleaning of artwork and objects of historical interest: the optimized pulse duration approach[J]. Accounts of chemical research, 2010, 43(6): 739-750

[7]

LiF, ChenX, LinW, et al.. Nanosecond laser ablation of Al-Si coating on boron steel[J]. Surface and coatings technology, 2017, 319: 129-135

[8]

LiX, HuangT, ChongA W, et al.. Laser cleaning of steel structure surface for paint removal and repaint adhesion[J]. Opto-electronic engineering, 2017, 44(3):340-344

[9]

ZhouJZ, LihT, SunQ, et al.. Laser derusting mechanism of AH32 steel based on cleaned surface topography[J]. Optics and precision engineering, 2019, 27(8):1754-1764

[10]

LiX Y, LiC Y, WangD. Effect of laser scanning speeds on cleaning quality of rusted layer on Q345 steel surface[J]. Chinese journal of lasers, 2020, 47(10):1002010

[11]

QiaoY L, ZhaoJ X, WangS J, et al.. Laser cleaning and elemental composition analysis of rusty surface[J]. Laser & infrared, 2018, 48(3): 299-304

[12]

XuJ, GuiC, HanQ. Recognition of rust grade and rust ratio of steel structures based on ensembled convolutional neural network[J]. Computer-aided civil and infrastructure engineering, 2020, 35(10):1160-1174

[13]

WanH, MinJ, LinJ, et al.. Effect of laser spot overlap ratio on surface characteristics and adhesive bonding strength of an Al alloy processed by nanosecond pulsed laser[J]. Journal of manufacturing processes, 2021, 62: 555-565

[14]

LinQ, FanZ J, WangW, et al.. The effect of spot overlap ratio on femtosecond laser planarization processing of SiC ceramics[J]. Optics & laser technology, 2020, 129: 106270

[15]

VaterJ M, GruberF, GrahlertW, et al.. Prediction of coating adhesion on laser-cleaned metal surfaces of battery cells using hyperspectral imaging and machine learning[J]. Coatings, 2021, 11(11):1388

[16]

ZhuL X, SunB T, LiZ, et al.. The weld quality improvement via laser cleaning pre-treatment for laser butt welding of the HSLA steel plates[J]. Welding in the world, 2020, 139: 106785

[17]

YangL, SongH L, ChangJ W. Comparison and analysis of coating cross-cut test in different standards[J]. Coating and protection, 2021, 42(1): 39-42

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