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Penicillin fermentation process soft measurement method based on dynamic Bayesian network

A dynamic Bayesian and penicillin fermentation technology is applied in the field of soft measurement of penicillin fermentation process, which can solve the problems of static soft measurement model estimation accuracy decline and model failure, and achieve the effects of improving soft measurement modeling accuracy and prediction accuracy.

Pending Publication Date: 2020-11-13
CHINA JILIANG UNIV
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Problems solved by technology

However, the actual penicillin fermentation process is dynamic. When the dynamic change of the process is obvious, the estimation accuracy of the static soft sensor model will be greatly reduced, and even cause the model to fail.

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  • Penicillin fermentation process soft measurement method based on dynamic Bayesian network
  • Penicillin fermentation process soft measurement method based on dynamic Bayesian network
  • Penicillin fermentation process soft measurement method based on dynamic Bayesian network

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Embodiment Construction

[0034] The present invention will be further described below in conjunction with drawings and embodiments.

[0035] Embodiments of the present invention and its implementation process are as follows:

[0036] The fermentation process of penicillin is taken as an example to illustrate below. Penicillin is an antibiotic widely used clinically. Its fermentation process is a typical biochemical reaction. The process flow chart is as follows: figure 1 . Pensim2.0 is a modular fed-batch fermentation process: a modular simulation package for penicillin fermentation, which establishes a non-structural model of quantitative fermentation penicillin production, and its simulator structure can use different modules according to the user's application requirements . The present invention has selected process variable and quality variable as shown in table 1 according to the variable data that uses Pensim2.0 penicillin fermentation process simulation package to obtain, wherein x 1 -x 1...

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Abstract

The invention discloses a penicillin fermentation process soft measurement method based on a dynamic Bayesian network. According to the method, the structure of a dynamic Bayesian network is designed,the advantages of the dynamic Bayesian network in a time-varying process are brought into full play, and soft measurement modeling for a penicillin fermentation process is achieved by dividing a training sample into a certain number of time slices and inputting the time slices into the dynamic Bayesian network. Aiming at the time-varying characteristic of the penicillin fermentation process, thetraditional Bayesian network is expanded in time, so that the prediction precision of the penicillin content in the penicillin fermentation process is improved, and a method reference is provided forsoft measurement modeling of other complex chemical production process quality variables with the time-varying characteristic.

Description

technical field [0001] The invention belongs to the field of continuous chemical process control and soft measurement, in particular to a soft measurement method for penicillin fermentation process based on dynamic Bayesian network. Background technique [0002] The biological fermentation process is usually a complex dynamic system with severe nonlinearity and time-varying nature. Since some quality variables related to production safety, quality and efficiency cannot be measured online, it is often very difficult and time-consuming to establish a mechanism model for it. For example, in the fermentation process of penicillin, although most chemical parameters and physical parameters can be directly measured and monitored online, some biological parameters, such as cell concentration, matrix concentration and product concentration, have higher requirements for measurement conditions. The cost of such sensors is high, and the measurement accuracy cannot be guaranteed, so it i...

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Application Information

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IPC IPC(8): G16C20/10G16C10/00G06N3/04
CPCG16C20/10G16C10/00G06N3/045
Inventor 徐玉雪何雨辰严天宏
Owner CHINA JILIANG UNIV
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