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An Artificial Neural Network for Biomass Estimation from Automatic pH Control Signal  

Hur, Won (Department of Bioengineering and Technology, College of Engineering, Kangwon National University)
Chung, Yoon-Keun (Department of Bioengineering and Technology, College of Engineering, Kangwon National University)
Publication Information
Biotechnology and Bioprocess Engineering:BBE / v.11, no.4, 2006 , pp. 351-356 More about this Journal
Abstract
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 $35^{\circ}C$.
Keywords
on-line monitoring; software sensor; alkali consumption; buffer capacity; biomass;
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