Neural network detection of abnormalities in fed-batch fermentation.
- Author:
Yun-Feng LI
1
;
Jing-Qi YUAN
Author Information
1. Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China.
- Publication Type:Journal Article
- MeSH:
Bioreactors;
microbiology;
Cephalosporins;
biosynthesis;
Culture Media;
Fermentation;
Hydrogen-Ion Concentration;
Models, Biological;
Neural Networks (Computer)
- From:
Chinese Journal of Biotechnology
2005;21(1):102-106
- CountryChina
- Language:Chinese
-
Abstract:
During fermentation, it is often difficult to detect the abnormalities, for example, caused by contamination on-line. Instead, the faults were detected usually by off-line laboratory analysis or other ways, which in most cases, is too late to remedy the situation. In this paper, a simple three-layers BP network was used for the early prediction of the amount of product, based on the difference in prediction errors between normal and abnormal charges and other accessorial information, such as profit function and pH value. In addition, three indications characteristic to abnormal charge are incorporated in practical operation. The prediction for Cephalosporin C Fed-batch Fermentation in a Chinese pharmaceutical factory was studied in details as an example and the result shows the abnormal charge can be discovered early successfully using the method.
