Soft Sensors for Pulp Freeness and Outlet Consistency Estimation in the Alkaline Peroxide Mechanical Pulping (APMP) High-Consistency Refining Process
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 me...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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North Carolina State University
2016-02-01
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| Series: | BioResources |
| Subjects: | |
| Online Access: | http://ojs.cnr.ncsu.edu/index.php/BioRes/article/view/BioRes_11_2_3598_Zhang_Soft_Sensors_Pulp_Freeness_Outlet_Consistency |
| _version_ | 1818954262677291008 |
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| author | Xiangyu Zhang Jigeng Li Huanbin Liu Ping Zhou |
| author_facet | Xiangyu Zhang Jigeng Li Huanbin Liu Ping Zhou |
| author_sort | Xiangyu Zhang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T10:19:23Z |
| format | Article |
| id | doaj.art-073510273fe34c199538d718a207b2ef |
| institution | Directory Open Access Journal |
| issn | 1930-2126 1930-2126 |
| language | English |
| last_indexed | 2024-12-20T10:19:23Z |
| publishDate | 2016-02-01 |
| publisher | North Carolina State University |
| record_format | Article |
| series | BioResources |
| spelling | doaj.art-073510273fe34c199538d718a207b2ef2022-12-21T19:43:58ZengNorth Carolina State UniversityBioResources1930-21261930-21262016-02-011123598361310.15376/biores.11.2.3598-3613Soft Sensors for Pulp Freeness and Outlet Consistency Estimation in the Alkaline Peroxide Mechanical Pulping (APMP) High-Consistency Refining ProcessXiangyu Zhang0Jigeng Li1Huanbin Liu2Ping Zhou3South China University of Technology; ChinaSouth China University of Technology; ChinaSouth China University of Technology; ChinaNortheastern University; ChinaIn 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.http://ojs.cnr.ncsu.edu/index.php/BioRes/article/view/BioRes_11_2_3598_Zhang_Soft_Sensors_Pulp_Freeness_Outlet_ConsistencyAPMP pulpingSoft sensorCase-based reasoningPulp quality |
| spellingShingle | Xiangyu Zhang Jigeng Li Huanbin Liu Ping Zhou Soft Sensors for Pulp Freeness and Outlet Consistency Estimation in the Alkaline Peroxide Mechanical Pulping (APMP) High-Consistency Refining Process BioResources APMP pulping Soft sensor Case-based reasoning Pulp quality |
| title | Soft Sensors for Pulp Freeness and Outlet Consistency Estimation in the Alkaline Peroxide Mechanical Pulping (APMP) High-Consistency Refining Process |
| title_full | Soft Sensors for Pulp Freeness and Outlet Consistency Estimation in the Alkaline Peroxide Mechanical Pulping (APMP) High-Consistency Refining Process |
| title_fullStr | Soft Sensors for Pulp Freeness and Outlet Consistency Estimation in the Alkaline Peroxide Mechanical Pulping (APMP) High-Consistency Refining Process |
| title_full_unstemmed | Soft Sensors for Pulp Freeness and Outlet Consistency Estimation in the Alkaline Peroxide Mechanical Pulping (APMP) High-Consistency Refining Process |
| title_short | Soft Sensors for Pulp Freeness and Outlet Consistency Estimation in the Alkaline Peroxide Mechanical Pulping (APMP) High-Consistency Refining Process |
| title_sort | soft sensors for pulp freeness and outlet consistency estimation in the alkaline peroxide mechanical pulping apmp high consistency refining process |
| topic | APMP pulping Soft sensor Case-based reasoning Pulp quality |
| url | http://ojs.cnr.ncsu.edu/index.php/BioRes/article/view/BioRes_11_2_3598_Zhang_Soft_Sensors_Pulp_Freeness_Outlet_Consistency |
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