|Table of Contents|

VIP optimal neural network inverse system soft sensing method in bio-fermentation process

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2015年04期
Page:
447-
Research Field:
Publishing date:

Info

Title:
VIP optimal neural network inverse system soft sensing method in bio-fermentation process
Author(s):
Yu Shuang1Liu Guohai2Mei Congli2Cheng Jinxiang2
1.Department of Mechanical and Electrical Engineering,Suzhou Institute of Industrial Technology, Suzhou 215104,China; 2.School of Electrical and Information Engineering,Jiangsu University,Zhenjiang 212013,China
Keywords:
variable importance in the project neural network inverse system soft sensing fermentation process inherent sensing variables selection online measuring
PACS:
TP273
DOI:
-
Abstract:
To solve the online measuring of biochemical variables in the fermentation process,a neural network inverse soft sensing method which is optimized using the variable importance in the project(VIP)is proposed.According to the inverse system theory,a soft sensing model of biochemical variables is constructed.Due to the complexity of the fermentation process,the soft sensing model is not unique and not exact.This paper proposes that secondary variables should be optimized using the VIP method.The variables which have greater contribution to key variables are selected as the secondary variables of the soft sensing model.This paper collectes the fermentation process data offline and trains neural network approximating complex soft sensing model.The optimal neural network inverse system soft sensing model is obtained.It can estimate the mycelium concentration and substrate concentration online.Numerical simulations based on the Pensim data platform show that the optimal soft sensing model has higher estimation accuracy and stronger generation ability.

References:

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Last Update: 2015-08-31