基于支持向量机算法的造纸过程磨后纤维形态软测量模型

作者：Jiang Lun; Man Yi^*; Li Jigeng; Hong Mengna; Meng Ziwei; Zhu Xiaolin

来源：Transactions of China Pulp and Paper, 2020, 35(2): 52-58.

DOI：10.11981/j.issn.1000-6842.2020.02.52

• Fiber morphology
• Pulping process
• Soft sensing technology
• SVM algorithm

In this study, a soft measurement model of post-refining fiber morphology in a papermaking process based on support vector machine algorithm (SVM) was proposed. The model used the parameters of original pulp sheet and refining as input for online soft measurement of post-refining fiber morphology. The results showed that when SVM was used for modeling, the average relative error of the seven kinds of soft measurement models of post-refining fiber morphology was between 2.87% and 5.61%, which was better than the modeling based on PLS algorithm (the average relative error was between 3.09% and 6.60%), and the model precision was good, which met the error requirements of real-time fiber morphology measurement in production. ? 2020, China National Pulp and Paper Research Institute(CNPPRI). All right reserved.

• 单位
  华南理工大学