光谱学与光谱分析, 2019, 39 (9): 2725, 网络出版: 2019-09-28
Zernike矩在橡胶添加剂太赫兹光谱定量分析中的应用研究
Application of Zernike Moment in Terahertz Spectrum Quantitative Analysis of Rubber Additives
太赫兹时域光谱 定量分析 Zernike矩 橡胶添加剂 多组分混合物 Terahertz time-domain spectroscopy Quantitative analysis Zernike moment Rubber additives Multicomponent mixtures
摘要
近年来, “绿色轮胎”发展备受关注。 在绿色轮胎制造过程中需要多种橡胶添加剂, 而橡胶添加剂的含量与绿色轮胎能否达标密切相关, 因此, 对轮胎橡胶中相关橡胶添加剂的定量检测具有重要意义。 太赫兹时域光谱(THz-TDS)技术已经成功应用于物质定量分析领域, 但当定量分析对象为多组分混合物时, 由于混合物光谱出现重叠和失真等原因, 会导致定量分析结果不理想。 针对此问题, 将Zernike矩作为一种光谱预处理技术引入到橡胶添加剂多组分混合物的太赫兹光谱定量分析中, 提出了基于Zernike矩结合支持向量回归(Zernike moment-support vector regression, ZM-SVR)的太赫兹光谱定量分析方法。 首先, 以影响绿色轮胎质量能否达标的三种橡胶添加剂氧化锌、 白炭黑和2-巯基苯并噻唑(MBT)为定量检测对象, 将3种橡胶添加剂与丁腈橡胶构成多组分混合物实验样本, 并通过太赫兹时域光谱系统测得样本的太赫兹光谱; 然后, 对太赫兹光谱进行分析与处理, 得到其吸收系数、 消光系数和折射率3种光学参数后, 将3种光学参数构建为样本的太赫兹三维光谱, 并利用Zernike矩提取太赫兹三维光谱灰度图的特征信息; 最后, 利用支持向量回归建立样本太赫兹三维光谱灰度图特征信息和目标成分含量之间的定量模型, 从而对混合物样本中目标成分含量进行分析。 利用该方法得到的定量模型预测集相关系数均大于等于0952 2, 均方根误差均小于等于2267 2%。 为进一步验证该方法的有效性, 将定量分析结果与常规方法PLS和SVR的结果进行了对比。 对比发现, 相比常规方法得到的定量分析结果, Zernike矩结合支持向量回归方法所得结果的准确性和稳定性均得到了明显提升。 因此, Zernike矩结合支持向量回归方法为橡胶添加剂多组分混合物的太赫兹光谱定量检测提供了新思路, 在绿色轮胎及橡胶的质量检测领域具有广阔应用前景。
Abstract
In recent years, the development of “green tire” has attracted much attention. Many kinds of rubber additives are needed in the manufacturing process of green tires, and the content of rubber additives is closely related to whether green tires can meet the standards. Therefore, it is important to quantitatively detect the rubber additives in tire rubber. THz-TDS technology has been successfully applied in the field of quantitative analysis of substances. However, when the quantitative analysis object is a multi-component mixture, the results of quantitative analysis will not be satisfactory due to the overlap and distortion of the mixture spectrum. In order to solve this problem, Zernike moment is introduced as a spectral pretreatment technology into terahertz spectral quantitative analysis of multi-component mixtures of rubber additives. A quantitative analysis method of terahertz spectrum based on Zernike moment and support vector regression (ZM-SVR) is proposed. Firstly, three rubber additives, zinc oxide, silica and 2-Mercaptobenzothiazole (MBT), which affect the quality of green tires, were used as quantitative detection objects. Three rubber additives and nitrile-butadiene rubber were prepared as multi-mixture experimental samples, and the terahertz spectra of samples were measured by terahertz time-domain spectroscopy system. Then, terahertz spectroscopy was analyzed and processed. After obtaining the three optical parameters of absorption coefficient, extinction coefficient and refractive index, the three optical parameters were constructed into the THz three-dimensional spectrum of the sample, and the characteristic information of the THz three-dimensional spectral gray-scale image was extracted by Zernike moment. Finally, the quantitative model between the characteristic information of the THz three-dimensional spectral gray-scale image of the sample and the content of the target component was established by using support vector regression. The target component content in the mixture sample was analyzed. The correlation coefficients of the forecasting set of the quantitative model obtained by this method were greater than or equal to 0952 2, and the root mean square error was less than or equal to 2267 2%. To further verify the validity of this method, the results of quantitative analysis were compared with those of PLS and SVR. Compared with the quantitative analysis results obtained by conventional methods, the accuracy and stability of the results obtained by Zernike moment combined with support vector regression method have been significantly improved. Therefore, Zernike moment combined with support vector regression provides a new method for terahertz spectroscopy quantitative detection of multi-component mixture of rubber additives, and has broad application prospects in the field of quality detection of green tires and rubber.
殷贤华, 郭超, 李安, 莫玮. Zernike矩在橡胶添加剂太赫兹光谱定量分析中的应用研究[J]. 光谱学与光谱分析, 2019, 39(9): 2725. YIN Xian-hua, GUO Chao, LI An, MO Wei. Application of Zernike Moment in Terahertz Spectrum Quantitative Analysis of Rubber Additives[J]. Spectroscopy and Spectral Analysis, 2019, 39(9): 2725.