Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System

Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System

Simulated moving bed (SMB) chromatographic separation technology is a new adsorption separation technology with strong separation ability. Based on the principle of the adaptive neural fuzzy inference system (ANFIS), a soft sensing modeling method was proposed for realizing the prediction of the pur...

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Main Authors: Dan Wang, Jie-Sheng Wang, Shao-Yan Wang, Shou-Jiang Li, Zhen Yan, Wei-Zhen Sun
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Journal of Sensors
Online Access:http://dx.doi.org/10.1155/2019/1312709
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spelling doaj-7831943bc2f742e3af0bb289dc1352f72020-11-25T01:13:29ZengHindawi LimitedJournal of Sensors1687-725X1687-72682019-01-01201910.1155/2019/13127091312709Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference SystemDan Wang0Jie-Sheng Wang1Shao-Yan Wang2Shou-Jiang Li3Zhen Yan4Wei-Zhen Sun5School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan City, Liaoning Province, ChinaSchool of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan City, Liaoning Province, ChinaSchool of College of Chemical Engineering, University of Science and Technology Liaoning, Anshan City, Liaoning Province, ChinaSchool of College of Chemical Engineering, University of Science and Technology Liaoning, Anshan City, Liaoning Province, ChinaSchool of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan City, Liaoning Province, ChinaFujian Institute of Research on the Structure, Fujian Province, ChinaSimulated moving bed (SMB) chromatographic separation technology is a new adsorption separation technology with strong separation ability. Based on the principle of the adaptive neural fuzzy inference system (ANFIS), a soft sensing modeling method was proposed for realizing the prediction of the purity of the extract and raffinate components in the SMB chromatographic separation process. The input data space of the established soft sensor model is divided, and the premise parameters are determined by utilizing the meshing partition method, subtractive clustering algorithm, and fuzzy C-means (FCM) clustering algorithm. The gradient, Kalman, Kaczmarz, and PseudoInv algorithms were used to optimize the conclusion parameters of ANFIS soft sensor models so as to predict the purity of the extract and raffinate components in the SMB chromatographic separation process. The simulation results indicate that the proposed ANFIS soft sensor models can effectively predict the key economic and technical indicators of the SMB chromatographic separation process.http://dx.doi.org/10.1155/2019/1312709
collection DOAJ
language English
format Article
sources DOAJ
author Dan Wang
Jie-Sheng Wang
Shao-Yan Wang
Shou-Jiang Li
Zhen Yan
Wei-Zhen Sun
spellingShingle Dan Wang
Jie-Sheng Wang
Shao-Yan Wang
Shou-Jiang Li
Zhen Yan
Wei-Zhen Sun
Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System
Journal of Sensors
author_facet Dan Wang
Jie-Sheng Wang
Shao-Yan Wang
Shou-Jiang Li
Zhen Yan
Wei-Zhen Sun
author_sort Dan Wang
title Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System
title_short Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System
title_full Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System
title_fullStr Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System
title_full_unstemmed Soft Sensing Modeling of the SMB Chromatographic Separation Process Based on the Adaptive Neural Fuzzy Inference System
title_sort soft sensing modeling of the smb chromatographic separation process based on the adaptive neural fuzzy inference system
publisher Hindawi Limited
series Journal of Sensors
issn 1687-725X
1687-7268
publishDate 2019-01-01
description Simulated moving bed (SMB) chromatographic separation technology is a new adsorption separation technology with strong separation ability. Based on the principle of the adaptive neural fuzzy inference system (ANFIS), a soft sensing modeling method was proposed for realizing the prediction of the purity of the extract and raffinate components in the SMB chromatographic separation process. The input data space of the established soft sensor model is divided, and the premise parameters are determined by utilizing the meshing partition method, subtractive clustering algorithm, and fuzzy C-means (FCM) clustering algorithm. The gradient, Kalman, Kaczmarz, and PseudoInv algorithms were used to optimize the conclusion parameters of ANFIS soft sensor models so as to predict the purity of the extract and raffinate components in the SMB chromatographic separation process. The simulation results indicate that the proposed ANFIS soft sensor models can effectively predict the key economic and technical indicators of the SMB chromatographic separation process.
url http://dx.doi.org/10.1155/2019/1312709
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AT shaoyanwang softsensingmodelingofthesmbchromatographicseparationprocessbasedontheadaptiveneuralfuzzyinferencesystem
AT shoujiangli softsensingmodelingofthesmbchromatographicseparationprocessbasedontheadaptiveneuralfuzzyinferencesystem
AT zhenyan softsensingmodelingofthesmbchromatographicseparationprocessbasedontheadaptiveneuralfuzzyinferencesystem
AT weizhensun softsensingmodelingofthesmbchromatographicseparationprocessbasedontheadaptiveneuralfuzzyinferencesystem
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