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| Soft Measurement Model Based on Gradient Boosting Regression Tree Algorithm forCreases Level of Tissue Paper |
| Received:February 17, 2020 |
| DOI：10.11980/j.issn.0254-508X.2020.06.006 |
| Key Words:creping creases level soft measurement gradient boosting regression tree algorithm |
| Author Name | Affiliation | Postcode | | ZHANG Dongqi | State Key Lab of Pulp and Paper Engineering，South China University of Technology，Guangzhou, Guangdong Province, 510640 | 510640 | | HONG Mengna | State Key Lab of Pulp and Paper Engineering，South China University of Technology，Guangzhou, Guangdong Province, 510640 | 510640 | | LI Jigeng | State Key Lab of Pulp and Paper Engineering，South China University of Technology，Guangzhou, Guangdong Province, 510640 | 510640 | | MAN Yi | State Key Lab of Pulp and Paper Engineering，South China University of Technology，Guangzhou, Guangdong Province, 510640
Shenzhen Xinyichang Technology Co., Ltd., Shenzhen,Guangdong Province,518000)
(*E-mail:corresponding author:manyi@scut.edu.cn | 518000 |
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| Abstract:Creases level is one of the most important indicators to measure the quality of tissue paper. However, there is a lack of the real-time on-line measurement method of creases level in production. In order to address this issue, this paper analyzed the factors affecting the creases level of tissue paper by experiments. A soft measurement model of paper roughness，creases amplitude，creases frequency was established using the gradient boosting regression tree algorithm. And a real-time online soft measurement of creases levels could be realized by predicting these three indicators. In comparison with the industrial real data, it was found that the model had higher prediction accuracy for surface roughness, amplitude and frequency of the creases. The average relative error of the testing data was less than 5%. This model solved the problem of online soft measurement of creases level. It provided a new method and basis for the quality control of the tissue production process. |
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