基于蝙蝠算法优化ESN的氯乙烯质量分数软测量模型预测

doi:10.3969/j.issn.2095-2198.2024.01.012

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为解决氯乙烯因其精馏过程具有较强的非线性，无法实现对氯乙烯质量分数实时测量的问题，提出一种基于蝙蝠算法(bat algorithm，BA)优化回声状态网络(echo state network，ESN)的软测量模型BA-ESN.首先，通过对氯乙烯精馏过程的分析，选取模型的辅助变量，并将归一化处理后的数据作为模型输入变量；其次，由于回声状态网络中的权值和阈值都是随机产生的，影响其泛化能力，故采用蝙蝠算法对回声状态网络的输出权值进行优化,从而提高ESN模型的收敛速度;最后，将BA-ESN模型预测氯乙烯质量分数的预测结果与ESN模型和BP模型的预测结果进行对比.仿真结果表明：BA-ESN模型的预测精度较高，泛化能力和鲁棒性都较好，能够满足氯乙烯精馏过程实时测量的要求.

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关键词: 氯乙烯精馏过程')" href="#">

氯乙烯精馏过程软测量蝙蝠算法回声状态网络

Abstract:

To solve the problem that the purity of vinyl chloride cannot be measured in real time due to the strong nonlinear rectification process of vinyl chloride,a soft-sensor modele based on bat algorithm(BA) was proposed to optimize echo state network(ESN).Firstly,through the analysis of vinyl chloride rectification process,the auxiliary variables of the model were selected,and the normalized data were used as the input variables of the model.Secondly,since the weights and thresholds in the echo state network are randomly generated,which affects its generalization ability,the bat algorithm was used to optimize the output weight of the echo state network,thereby improving the convergence speed of the ESN model.Finally,the proposed BA-ESN model was used to predict the concentration of vinyl chloride,and the prediction results were compared with those of the ESN model and the BP model.The simulation results showed that the BA-ESN model has higher prediction accuracy,better generalization ability and robustness,and can meet the requirements of real-time measurement in vinyl chloride rectification process.

Key words: vinyl chloride rectification process')" href="#">

vinyl chloride rectification process soft sensor bat algorithm echo state network

出版日期: 2024-02-29 发布日期: 2024-09-24 整期出版日期: 2024-02-29

ZTFLH:

TP273

基金资助:

辽宁省自然科学基金项目（20170540725）；辽宁省高端人才建设项目-辽宁省特聘教授(﹝2018﹞3533)

作者简介: 高淑芝（1968—），女，河南郸城人，教授，博士，主要从事优化算法和复杂工业过程建模等研究.

引用本文:

高淑芝1, 李晓宇2, 张毅蒙1.

基于蝙蝠算法优化ESN的氯乙烯质量分数软测量模型预测 [J]. 沈阳化工大学学报, 2024, 38(1): 83-89.
GAO Shuzhi1, LI Xiaoyu2, ZHANG Yimeng1.

Optimization of ESN Based on Bat Algorithm for Soft Sensing Model Prediction of Vinyl Chloride Weight Fraction . Journal of Shenyang University of Chemical Technology, 2024, 38(1): 83-89.

链接本文:

https://xuebao.syuct.edu.cn/CN/10.3969/j.issn.2095-2198.2024.01.012 或 https://xuebao.syuct.edu.cn/CN/Y2024/V38/I1/83

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