基于近红外光谱与支持向量机的纸浆卡伯值在线测量

The Online Measurement for Pulp Kappa Number Based on Near Infrared Spectroscopy and Support Vector Machine

提出了用近红外光谱漫反射技术和支持向量机建模方法实现纸浆卡伯值在线测量的新方法。采集45份松木浆样品的近红外漫反射光谱,选择各样品15个振动吸收峰对应的吸收率,采用动态独立分量分析(DICA)对输入样本数据进行特征提取,建立基于支持向量机(SVM)的纸浆卡伯值预测模型。45份样品中选择35份组成校正集,另10份作为预测集对模型进行验证。基于支持向量机的纸浆卡伯值预测模型外部验证均方差和确定系数分别为0.26和0.93;基于线性回归的纸浆卡伯值预测模型外部验证均方差和确定系数分别为0.45和0.81。研究结果不仅表明纸浆卡伯值近红外测量方法的可行性和有效性,而且验证了基于支持向量机的纸浆卡伯值预测模型比线性回归模型具有更高的准确性和鲁棒性。

A new method for online measurement of pulp Kappa number by means of near infrared diffuse reflectance spectroscopy and support vector machine （SVM） modeling has been developed in this paper. The near infrared diffuse reflectance spectroscopy of 45 Chinese red pine wood pulp samples was acquired. Selecting the absorption rates in 15 vibration absorption peaks of each sample and using dynamic independent component analysis （DICA） to distill the characters of input sample data, the pulp Kappa number predictive model based on SVM was built. From the whole 45 samples, 35 samples was selected to be the calibration set, and the predictive set consisted of the other 10 samples was used to validate the the pulp Kappa number predictive model. The external validation standard deviation is 0. 26 for pulp Kappa number predictive model based on SVM, and the determining factor is 0. 93 for the model. The internal cross validation standard deviation is 0. 22 for pulp Kappa number predictive model based on SVM, and the determining factor is 0. 96 for the model. To analyze the effectiveness of SVM method used to build the pulp Kappa number predictive model, the pulp Kappa number predictive model based on linear regression（LR） was also established. The external validation standard deviation is 0. 45 for the model based on linear regression（LR）, and the determining factor is 0. 81 for the model. The internal cross validation standard deviation is 0. 41 for the model based on linear regression （LR）, and the determining factor is 0.85 for the model. For the 10 test samples, the pulp Kappa number predictive model based on Linear regression（LR） and the model based on SVM all have certain predictive accuracy, but the later higher. The experiment results not only show the feasibility and effectiveness of the near infrared measurement method for pulp Kappa number, but also validate that the pulp Kappa number predictive model based on SVM is more accurate and robust than linear regression model. Keywords Pulp