|
|
|
|
|
|
Research on the Controllability of Aircraft Skin Laser Paint Remove Based on Laser-Induced Breakdown Spectrum and Composition Analysis |
YANG Wen-feng1*, QIAN Zi-ran1, CAO Yu2, WEI Gui-ming1, ZHU De-hua2, WANG Feng3, FU Chan-yuan1 |
1. Civil Aviation Flight University of China,Guanghan 618307,China
2. College of Mechanical and Electrical Engineering, Wenzhou University,Wenzhou 325035,China
3. LTB-CHINA, CHENGDU OFFICE,Chengdu 610000,China |
|
|
Abstract Laser paint removal, as a branch of laser cleaning technology, will replace the traditional polishing and chemical paint removal technology to achieve the controlled paint removal of the aircraft skin surface.However,the process and quality of controlled paint removal depend on effective in-situ online monitoring technology. For the multi-paint layer on the surface of the aircraft aluminum alloy skin,LIBS technology is used to analyze the spectral and the component of characteristic elements of different paint layers and different paint thicknesses during laser paint removal.Based on signal interpretation, to establish the relationship between the paint layer and paint thicknesses of laser paint removal and the change of LIBS spectrum.And to realize the real-time monitoring and feedback control of the paint removal process and quality.The results show that the spectral peak of the characteristic elements (Fe, Ti) of the layer disappears when the topcoat or primer is completely removed in the process of layered removal.Once LIBS monitors the characteristic element Fe of topcoat at 501.494 1 and 521.517 9 nm Fe Ⅰ spectral characteristic peak disappears, the topcoat has been completely removed at the same time. And when the characteristic element Ti of primer at 498.173 0, 499.107 0 and 521.039 0 nm Ti Ⅰ spectral characteristic peak disappears, determine primer has been completely removed.When the paint is removed in different thicknesses, the spectral peak strength of the paint characteristic element (Ca) decreases correspondingly with the decrease of the paint thickness or the increase of laser pulse. Until the paint thickness is 0 (completely removed), the spectral peak of the paint characteristic element disappears, and the matrix characteristic element (Al) appears.By applying the LIBS spectral signal intensity changes of Ca Ⅰ at 616.217 0, 643.907 0 and 422.673 0 nm, the remaining paint thicknesses during laser paint removal could be monitored and further realizes Laser-based Thickness Controlled Paint Removal. In addition, combined with EDS and SEM testing and analysis, the feasibility of LIBS for aircraft skin laser paint removal process and effect monitoring, Laser-based Layered Controlled Paint Removal and Laser-based Thickness Controlled Paint Removalare verified. It shows that under the premise of not damaging the oxide layer of the substrate, by monitoring the characteristic element spectrum and composition change law of the topcoat and primer at the corresponding wavelength position, Laser-based Layered Controlled Paint Removal and Laser-based Thickness Controlled Paint Removal can be achieved.
|
Received: 2020-10-09
Accepted: 2021-02-12
|
|
Corresponding Authors:
YANG Wen-feng
E-mail: ywfcyy@163.com
|
|
[1] WANG Xiao-dong, YU Jin, MO Ze-qian, et al(王晓东, 余 锦, 貊泽强,等). Laser & Optoelectronics Progress(激光与光电子学进展), 2020, 57(5): 59.
[2] Shakeel H, Haq S U, Aisha G, et al. Physics of Plasmas, 2017, 24(6): 063516.
[3] Sheta S, Afgan M S, Hou Z, et al. Journal of Analytical Atomic Spectrometry, 2019, 34(6): 1047.
[4] Botto A, Campanella B, Legnaioli S, et al. Journal of Analytical Atomic Spectrometry, 2019, 34(1): 81.
[5] Palmieri F L, Ledesma R I, Dennie J G, et al. Composites Part B: Engineering, 2019, 175: 107155.
[6] Ledesma R, Palmieri F, Connell J. International Journal of Adhesion and Adhesives, 2020, 98: 102528.
[7] Yin Y, Sun D, Su M, et al. Optics & Laser Technology, 2019, 120: 105689.
[8] SUN Lan-xiang, WANG Wen-ju, QI Li-feng,et al(孙兰香, 王文举, 齐立峰, 等). Chinese Journal of Lasers(中国激光), 2020, 47(11): 299.
[9] XIN Yong, LI Yang, CAI Zhen-rong, et al(辛 勇, 李 洋, 蔡振荣, 等). Metallurgical Analysis(冶金分析), 2019, 39(1): 15.
[10] CHEN Lin, DENG Guo-liang, FENG Guo-ying, et al(陈 林, 邓国亮, 冯国英,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2018, 38(2): 367.
[11] Zhou Qionghua, Deng Guoliang, Chen Yin et al. Applied Optics, 2019, 58(34): 9421.
[12] Li An, Guo Shuai, Wazir Nasrullah, et al. Optics Express, 2017, 25(22): 27559.
[13] WANG Xian-shuang, GUO Shuai, XU Xiang-jun, et al(王宪双, 郭 帅, 徐向君, 等). Chinese Optics(中国光学), 2019, 12(4): 888.
[14] ZHANG Rui, SUN Lan-xiang, CHEN Tong, et al(张 蕊, 孙兰香, 陈 彤, 等). Acta Geologica Sinica(地质学报), 2020, 94(3): 991.
[15] GAO Liao-yuan, ZHOU Jian-zhong, SUN Qi, et al(高辽远, 周建忠, 孙 奇, 等). Chinese Journal of Lasers(中国激光), 2019, 46(5): 335. |
[1] |
LIU Jia1, 2, GUO Fei-fei2, YU Lei2, CUI Fei-peng2, ZHAO Ying2, HAN Bing2, SHEN Xue-jing1, 2, WANG Hai-zhou1, 2*. Quantitative Characterization of Components in Neodymium Iron Boron Permanent Magnets by Laser Induced Breakdown Spectroscopy (LIBS)[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 141-147. |
[2] |
YANG Wen-feng1, LIN De-hui1, CAO Yu2, QIAN Zi-ran1, LI Shao-long1, ZHU De-hua2, LI Guo1, ZHANG Sai1. Study on LIBS Online Monitoring of Aircraft Skin Laser Layered Paint Removal Based on PCA-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3891-3898. |
[3] |
SUN Cheng-yu1, JIAO Long1*, YAN Na-ying1, YAN Chun-hua1, QU Le2, ZHANG Sheng-rui3, MA Ling1. Identification of Salvia Miltiorrhiza From Different Origins by Laser
Induced Breakdown Spectroscopy Combined with Artificial Neural
Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3098-3104. |
[4] |
LIU Shu1, JIN Yue1, 2, SU Piao1, 2, MIN Hong1, AN Ya-rui2, WU Xiao-hong1*. Determination of Calcium, Magnesium, Aluminium and Silicon Content in Iron Ore Using Laser-Induced Breakdown Spectroscopy Assisted by Variable Importance-Back Propagation Artificial Neural Networks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3132-3142. |
[5] |
LI Chang-ming1, CHEN An-min2*, GAO Xun3*, JIN Ming-xing2. Spatially Resolved Laser-Induced Plasma Spectroscopy Under Different Sample Temperatures[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2032-2036. |
[6] |
ZHAO Yang1, ZHANG Lei2, 3*, CHENG Nian-kai4, YIN Wang-bao2, 3*, HOU Jia-jia5, BAI Cheng-hua1. Research on Space-Time Evolutionary Mechanisms of Species Distribution in Laser Induced Binary Plasma[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2067-2073. |
[7] |
WANG Bin1, 2, ZHENG Shao-feng2, GAN Jiu-lin1, LIU Shu3, LI Wei-cai2, YANG Zhong-min1, SONG Wu-yuan4*. Plastic Reference Material (PRM) Combined With Partial Least Square (PLS) in Laser-Induced Breakdown Spectroscopy (LIBS) in the Field of Quantitative Elemental Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2124-2131. |
[8] |
HU Meng-ying1, 2, ZHANG Peng-peng1, 2, LIU Bin1, 2, DU Xue-miao1, 2, ZHANG Ling-huo1, 2, XU Jin-li1, 2*, BAI Jin-feng1, 2. Determination of Si, Al, Fe, K in Soil by High Pressure Pelletised Sample and Laser-Induced Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2174-2180. |
[9] |
WU Shu-jia1, 2, YAO Ming-yin2, 3, ZENG Jian-hui2, HE Liang2, FU Gang-rong2, ZENG Yu-qi2, XUE Long2, 3, LIU Mu-hua2, 3, LI Jing2, 3*. Laser-Induced Breakdown Spectroscopy Detection of Cu Element in Pig Fodder by Combining Cavity-Confinement[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1770-1775. |
[10] |
YUAN Shu, WU Ding*, WU Hua-ce, LIU Jia-min, LÜ Yan, HAI Ran, LI Cong, FENG Chun-lei, DING Hong-bin. Study on the Temporal and Spatial Evolution of Optical Emission From the Laser Induced Multi-Component Plasma of Tungsten Carbide Copper Alloy in Vacuum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1394-1400. |
[11] |
WANG Qiu, LI Bin, HAN Zhao-yang, ZHAN Chao-hui, LIAO Jun, LIU Yan-de*. Research on Anthracnose Grade of Camellia Oleifera Based on the Combined LIBS and Fourier Transform NIR Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1450-1458. |
[12] |
CHAI Shu1, PENG Hai-meng1, WU Wen-dong1, 2*. Acoustic-Based Spectral Correction Method for Laser-Induced Breakdown Spectroscopy in High Temperature Environment[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1401-1407. |
[13] |
NING Qian-qian, YANG Jia-hao, LIU Xiao-lin, HE Yu-han, HUANGFU Zhi-chao, YU Wen-jing, WANG Zhao-hui*. Design and Study of Time-Resolved Femtosecond Laser-Induced
Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1083-1087. |
[14] |
DING Kun-yan1, HE Chang-tao2, LIU Zhi-gang2*, XIAO Jing1, FENG Guo-ying1, ZHOU Kai-nan3, XIE Na3, HAN Jing-hua1. Research on Particulate Contamination Induced Laser Damage of Optical Material Based on Integrated Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1234-1241. |
[15] |
SU Yun-peng, HE Chun-jing, LI Ang-ze, XU Ke-mi, QIU Li-rong, CUI Han*. Ore Classification and Recognition Based on Confocal LIBS Combined With Machine Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 692-697. |
|
|
|
|