Abstract
The existing data-based monitoring and diagnosis methods for microbial manufacturing processes only consider macroscopic production variables and ignore microscopic metabolic mechanisms and flux changes. This paper proposed a fault monitoring strategy based on metabolic flux variables (intracellular and extracellular exchange fluxes) by introducing microbial cellular metabolic network information. First, the metabolic network of the microbial manufacturing process was analyzed and the dynamic metabolic flux analysis (DMFA) was used to obtain the dynamic distribution of metabolic fluxes inside microbial cells based on measurable extracellular metabolites concentration. Then, production variables and flux variables were combined to constitute a sample dataset of the microbial cell growth process. On this basis, a multiway principal component analysis (MPCA) method was used to establish a fault diagnosis model to monitor the process. Finally, the method’s effectiveness was verified using the fault monitoring strategy proposed in this paper for online monitoring of the penicillin manufacturing process.
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