An artificial neural network for biomass estimation from automatic pH control signal

被引:0
|
作者
Hur, Won [1 ]
Chung, Yoon-Keun [1 ]
机构
[1] Kangwon Natl Univ, Coll Engn, Dept Bioengn & Technol, Chunchon 200701, South Korea
关键词
on-line monitoring; software sensor; alkali consumption; buffer capacity; biomass;
D O I
暂无
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
This study developed an artificial neural network (ANN) to estimate the growth of microorganisms during a fermentation process. The ANN relies solely on the cumulative consumption of alkali and the buffer capacity, which were measured on-line from the on/off control signal and pH values through automatic pH control. The two input variables were monitored on-line from a series of different batch cultivations and used to train the ANN to estimate biomass. The ANN was refined by optimizing the network structure and by adopting various algorithms for its training. The software estimator successfully generated growth profiles that showed good agreement with the measured biomass of separate batch cultures carried out between at 25 and 35 degrees C.
引用
收藏
页码:351 / 356
页数:6
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