基于自适应变量加权的汽油辛烷值预测方法
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作者单位:

1.湖南理工学院;2.中南大学

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中图分类号:

TP273

基金项目:

湖南省自然科学基金项目(2019JJ40110,2019JJ40104);湖南省教育厅科学研究项目(18B349,19A201);湖南省研究生科研创新项目(CX20190932,CX20190930)


Prediction method of gasoline octane number based on adaptive variable weighting
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Affiliation:

1.Hunan Institute of Science and Technology;2.Central South University

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    摘要:

    针对汽油精制过程中控制变量之间非线性和强耦联性,产品汽油中辛烷值难以测定的问题,提出了一种基于自适应变量加权的汽油辛烷值预测方法.该方法首先利用一种新颖的变量加权模块捕获变量之间的相关性获取变量权重,通过自适应变量加权的方式提升主要变量的重要性,抑制其他次要变量的作用;其次考虑到汽油脱硫过程对辛烷值的影响,输入加权激活后的变量到辛烷值预测模块,模型同时输出辛烷值和硫含量的预测结果;最后基于工业数据进行模型验证,结果表明,较之于没有变量加权模块的神经网络预测方法、基于随机森林的神经网络预测方法和基于变量加权堆叠自编码器的预测方法,本文提出的自适应变量加权汽油辛烷值预测方法具有更高的预测精度,可以用来优化汽油精制过程的操作条件.

    Abstract:

    In the gasoline refining process, maintaining the gasoline Research Octane Number (RON) is the focus of gasoline cleaning. However, due to the nonlinearity and strong coupling between the control variables in the petroleum refining process, it is difficult to measure the octane number in the product gasoline. Considering the importance of different variables to the octane number, a gasoline octane number prediction method based on adaptive variable weighting is proposed to predict the octane number. In this method, a novel variable weighting module is used to capture the correlation between the variables to obtain the variable weights, and the importance of the main variables is enhanced by the adaptive variable weighting method, and the effects of other secondary variables are suppressed. Then, considering the impact of gasoline desulfurization on the octane number, the weighted variables are input to the octane number prediction module, and the model outputs the prediction results of octane number and sulfur content. Finally, model validation is performed based on industrial data. The results showed that, compared with the neural network prediction method without variable weighting module, the neural network prediction method based on random forest algorithm and the prediction method based on variable-wise weighted stacked autoencoder, the prediction method of gasoline octane number based on adaptive variable weight has higher prediction accuracy, and it can be used to optimize the operating conditions of the gasoline refining process.

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  • 收稿日期:2021-01-12
  • 最后修改日期:2021-07-22
  • 录用日期:2021-07-30
  • 在线发布日期: 2021-09-01
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