朱强, 周维虎, 陈晓梅, 李冠楠, 石俊凯. 复杂衬底下的涂层厚度定量检测方法研究[J]. 红外与激光工程, 2022, 51(12): 20220156. DOI: 10.3788/IRLA20220156
引用本文: 朱强, 周维虎, 陈晓梅, 李冠楠, 石俊凯. 复杂衬底下的涂层厚度定量检测方法研究[J]. 红外与激光工程, 2022, 51(12): 20220156. DOI: 10.3788/IRLA20220156
Zhu Qiang, Zhou Weihu, Chen Xiaomei, Li Guannan, Shi Junkai. Research on quantitative detection method of coating thickness on complex substrates[J]. Infrared and Laser Engineering, 2022, 51(12): 20220156. DOI: 10.3788/IRLA20220156
Citation: Zhu Qiang, Zhou Weihu, Chen Xiaomei, Li Guannan, Shi Junkai. Research on quantitative detection method of coating thickness on complex substrates[J]. Infrared and Laser Engineering, 2022, 51(12): 20220156. DOI: 10.3788/IRLA20220156

复杂衬底下的涂层厚度定量检测方法研究

Research on quantitative detection method of coating thickness on complex substrates

  • 摘要: 纸币是国家发行并强制使用的货币符号,2019年中国人民银行发行的2019年版第五套人民币纸币,两面采用了抗脏污保护涂层,使纸币的整洁度明显改善。作为“国家名片”,在纸币生产过程中,对每一道工艺都有严格的质量控制,涂层是通过涂布机将涂布液转移、固化至纸币两面,由此称为涂布工艺。为了更加合理地控制涂布质量,生产中需要检测纸币涂层的厚度。针对该需求,文中建立了纸币图纹作为复杂衬底的涂层厚度光学漫反射模型,采用傅里叶近红外光谱仪和激光共聚焦显微系统对已涂布和未涂布的纸币进行识别并定量检测。文中首先根据涂层物质在近红外光谱可被有效识别的特点,对涂层的近红外吸收光谱数据提出了基于多元散射校正(MSC)与二阶导组合的分析方法,确定4 346.764 cm−1为特征波数。再根据反射率、粗糙度对涂层厚度的模型解耦,最后通过激光共聚焦显微系统检测了已涂布纸币的涂层变化,并将其与模型的厚度解耦结果关联,得出测量涂层厚度最小为3.807 μm,最大为12.738 μm。最终结果表明该检测方法对纸币生产中涂层质量控制具有重要的实践指导意义。

     

    Abstract: Banknote which is issued by the government and forced to use. In 2019, the People’s Bank of China issues the fifth set of RMB. The anti-fouling protection coating is used on both sides, which significantly improves the cleanliness of paper currency. In order to control the coating quality more reasonably, it is necessary to detect the coating thickness in the production. The coating thickness of this paper was to investigate, this paper establishes the optical diffuse reflection model of coating thickness with banknote pattern as a complex substrate surface, identifies and quantitatively detects the coated and uncoated banknote by using Fourier near-infrared spectrometer and confocal laser scanning microscopy system. In this paper, one analytical method based on the combination of multivariate scattering correction (MSC) and second-order derivative combination analysis is proposed for the near infrared (NIR) absorption spectrum data of the coating, that could be effectively identified in the NIR spectrum, and 4 346.764 cm−1 is determined as the characteristic wave number. Then, the coating thickness model is decoupled basing on the reflectance and roughness. Finally, the coating thickness changes of coated banknotes are detected by a confocal laser scanning microscopy system, and they are correlated with the decoupling result of the model to obtain the actual coating thickness. The final results show that the minimum is 3.807 μm, the maximum is 12.738 μm. The detection method has an important practical significance for coating quality control in banknote production.

     

/

返回文章
返回