Spectroscopy and Spectral Analysis, Volume. 42, Issue 11, 3608(2022)

Transfer Learning Modeling of 2,6-Dimethylphenol Purity Based on PLS Subspace Alignment

Yun-fei WU*, Xiao-li LUAN*;, and Fei LIU
Author Affiliations
  • Key Laboratory of Advanced Process Control for Light Industry of the Ministry of Education, Institute of Automation, Jiangnan University, Wuxi 214122, China
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    Figures & Tables(8)
    Modeling flow diagram of transfer learning algorithm
    Process flow diagrams and Reactive principle sketch(a): Process flow diagram; (b): Reactive principle sketch
    Spectral comparison at different detecting points
    Different principal component numbers impact on model performance
    Different sample numbers of dephenolization tower impact on model performance(a): Impact on model performance for transferring different sample numbers of dephenolization tower;(b): Model performance improvement percentage for transferring different sample numbers of dephenolization tower
    Different sample numbers of o-cresol tower impact on model performance(a): Impact on model performance for transferring different sample numbers of o-cresol tower;(b): Model performance improvement percentage for transferring different sample numbers of o-cresol tower
    Model curve and Scatter plot(a): Model curve; (b): Scatter plot of prediceted and actual values
    • Table 1. 2,6-DMP purity distribution at different detecting points

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      Table 1. 2,6-DMP purity distribution at different detecting points

      样本集样本数均值
      /%
      变异系
      数/%
      最小值
      /%
      最大值
      /%
      脱苯酚塔检测点30081.322.27073.9083.97
      邻甲酚粗品塔检测点30097.490.37096.4798.67
      2,6-DMP产品塔检测点5099.860.03199.8199.95
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    Yun-fei WU, Xiao-li LUAN, Fei LIU. Transfer Learning Modeling of 2,6-Dimethylphenol Purity Based on PLS Subspace Alignment[J]. Spectroscopy and Spectral Analysis, 2022, 42(11): 3608

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    Paper Information

    Category: Research Articles

    Received: Oct. 9, 2021

    Accepted: --

    Published Online: Nov. 23, 2022

    The Author Email: WU Yun-fei (yfwuu@vip.jiangnan.edu.cn)

    DOI:10.3964/j.issn.1000-0593(2022)11-3608-07

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