Abstract: The present invention provides a knowledge reuse-based method and system for predicting a cell concentration in a fermentation process. The method includes: constructing a cell concentration soft sensor universal model in a fermentation process; acquiring and preprocessing process data of a fermentation stage A; determining a cell concentration soft sensor model of the fermentation stage A; designing a cell concentration online soft sensor of a fermentation stage B; and predicting a cell concentration of the fermentation stage B according to the cell concentration online soft sensor of the fermentation stage B. The present invention resolves the problems of weak generalization of a cell concentration soft sensor model and high costs of establishing models for fermentation stages separately, thereby improving the prediction accuracy of a cell concentration soft sensor.

Abstract: The present invention provides a knowledge reuse-based method and system for predicting a cell concentration in a fermentation process. The method includes: constructing a cell concentration soft sensor universal model in a fermentation process; acquiring and preprocessing process data of a fermentation stage A; determining a cell concentration soft sensor model of the fermentation stage A; designing a cell concentration online soft sensor of a fermentation stage B; and predicting a cell concentration of the fermentation stage B according to the cell concentration online soft sensor of the fermentation stage B. The present invention resolves the problems of weak generalization of a cell concentration soft sensor model and high costs of establishing models for fermentation stages separately, thereby improving the prediction accuracy of a cell concentration soft sensor.

Abstract: The invention provides real-time prediction and regulation methods and systems of product quality based on a process dynamic pattern. The prediction method includes: constructing a state space probability model of quality pattern dynamic motion equation; calculating a probability density function distribution of a quality pattern according to the probability model; performing optimized learning on parameters of the state space probability model of quality pattern dynamic motion equation according to the probability density function distribution, to obtain optimal model parameters and an optimized state space probability model of quality-pattern dynamic motion equation; and performing online prediction on product quality indicators based on the optimized state space probability model.

Abstract: The present disclosure discloses a method for evaluating estimation accuracy of energy consumption per ton in distillation processes, and belongs to the technical field of evaluation of estimation performance of energy consumption per ton in distillation processes.