Soft sensors for pulp freeness and outlet consistency estimation in the alkaline peroxide mechanical pulping (APMP) high-consistency refining process

被引：0

作者：

Zhang X. ^{[1
]}

Li J. ^{[1
]}

Liu H. ^{[1
]}

Zhou P. ^{[2
]}

机构：

[1] State Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou

[2] State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang

来源：

Li, Jigeng (jigengli@scut.edu.cn) | 2016年 / North Carolina State University卷 / 11期

基金：

中国国家自然科学基金;

关键词：

APMP pulping; Case-based reasoning; Pulp quality; Soft sensor;

D O I：

10.15376/biores.11.2.3598-3613

中图分类号：

学科分类号：

摘要：

In the mechanical pulping process, some process state and product quality variables are difficult to measure on-line. In this paper, soft sensors were used to estimate Canadian Standard Freeness (CSF) and outlet consistency (Cout) after the high consistency refining stage of the alkaline peroxide mechanical pulping (APMP) process. After the secondary variables for modeling that are readily available processed measurements in pre-treatment and the HC refining stage was selected, models based on the case-based reasoning (CBR) method were developed to estimate CSF and Cout. The ability of CBR soft sensors to predict CSF and Cout was tested using data collected from an APMP mill, and the results were satisfactory. Additionally, two typical soft sensor methods that back propagation network (BP) algorithms and support vector regression algorithms (SVR) were employed to predict CSF and Cout and evaluate the performance of the CBR soft sensor. As a result, the proposed soft sensor demonstrated a better performance than the BP method and can be regarded as of comparable quality to the SVR method.

引用

页码：3598 / 3613

页数：15

共 34 条

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