DocumentCode :
2206045
Title :
ANN inversion based soft-sensing of biochemical parameters in erythromycin fermentation
Author :
Dai, Xianzhong ; Yu, Dongchuan ; Ding, Yuhan ; Wang, Wancheng
Author_Institution :
Dept. of Autom. Control, Southeast Univ., Nanjing, China
fYear :
2004
fDate :
21-25 June 2004
Firstpage :
262
Lastpage :
266
Abstract :
This paper presents a novel soft-sensing approach based on artificial neural network (ANN) inversion to estimate some crucial biochemical parameters in erythromycin fermentation, which usually can not be directly measurable by commercial sensors. Such direct-unmeasurable variables as mycelia concentration, sugar concentration and chemical potency, can be derived from other direct-measurable variables such as dissolved oxygen concentration, pH, and volume by using the proposed ANN inversion. The ANN inversion consists of a static ANN and several differentiators and acts as a soft-sensor. Experimental results show that the soft-sensing values are almost identical with the actual ones and the proposed method would be helpful for the real-time control of the biochemical fermentation.
Keywords :
biochemistry; chemical sensors; fermentation; neural nets; artificial neural network; biochemical parameter; chemical potency; commercial sensor; erythromycin fermentation; mycelia concentration; oxygen concentration; real-time control; soft-sensing approach; sugar concentration; Artificial neural networks; Biosensors; Chemical and biological sensors; Chemical processes; Chemical sensors; Costs; Equations; Laboratories; Pharmaceuticals; Production facilities;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Acquisition, 2004. Proceedings. International Conference on
Print_ISBN :
0-7803-8629-9
Type :
conf
DOI :
10.1109/ICIA.2004.1373365
Filename :
1373365
Link To Document :
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