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Fermentation pharmacy product quality soft measurement method based on GP learning model building

A soft measurement and product technology, which is applied in the field of soft measurement of fermentation and pharmaceutical product quality, can solve the problems of low measurement accuracy and low modeling accuracy.

Active Publication Date: 2009-04-29
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0008] In order to overcome the shortcomings of low modeling accuracy and low measurement accuracy of the existing soft measurement methods for the quality of fermented pharmaceutical products, the present invention provides a GP learning modeling method with high modeling accuracy and high measurement accuracy. Soft measurement method for the quality of fermented pharmaceutical products

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  • Fermentation pharmacy product quality soft measurement method based on GP learning model building
  • Fermentation pharmacy product quality soft measurement method based on GP learning model building
  • Fermentation pharmacy product quality soft measurement method based on GP learning model building

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings.

[0038] refer to Figure 1 ~ Figure 4 , a soft-sensing method for the quality of fermented pharmaceutical products based on GP learning modeling, the steps of the specific method are as follows:

[0039] 1) Collect a batch of process history data sets L of the fermentation process.

[0040] The data set L is composed of no more than 200 data samples {x, y} at the acquisition time, where x is the generalized input vector of the model, and its composition depends on the nonlinear model form adopted on the one hand (such as the serial-parallel structure ), on the other hand also depends on the qualitative process knowledge of biochemical reactions, reaction kinetics, etc. Generally, it is sufficient to take x as a combination of measurable conventional process variables and their delays.

[0041] y is the quality vector to be predicted, that is, the present invention ca...

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Abstract

The invention relates to a method for the quality soft sensing of a fermentation pharmaceutical product based on GP study modeling, which comprises the following steps: 1) acquiring a historical data set L of a fermentation pharmaceutical process, wherein the data set L consists of not more than 200 data samples {x , y} at acquiring moments, wherein x is a generalized input vector for a model, and y is a quality vector of a fitting forecast; 2) making use of a GP learning algorithm to establish a model f<*> of key quality indexes of the fitting model; and 3 ) acquiring a process variable x<*> on line, and substituting the process variable x<*> into the product quality model f<*> so as to obtain a real-time forecast product quality index. The invention provides the method for the quality soft sensing of the fermentation pharmaceutical product based on the GP study modeling, which has very high modeling precision and high measurement accuracy.

Description

technical field [0001] The invention relates to a soft-sensing method for an industrial batch production process, in particular to a soft-sensing method for the quality of fermented pharmaceutical products. Background technique [0002] Microorganism / gene pharmacy is a strategic high value-added industry, and batch fermentation is the main way of its industrial cultivation. Microbial fermentation pharmaceuticals are not only one of the important components of modern biotechnology, but also closely related to human health and quality of life. The fermentation pharmaceutical process is accompanied by the growth and reproduction of microorganisms, and has the characteristics of metabolic reactions of living organisms and chemical transfer phenomena. It is a very complex internal mechanism, and various factors influence and restrict each other on different scales (genes, cells and engineering). summation process. [0003] In addition, some key variables in the fermentation pro...

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Application Information

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IPC IPC(8): G01N33/15G06N1/00C12N1/00G06N99/00
Inventor 蒋宁盛颂恩陈挹
Owner ZHEJIANG UNIV OF TECH
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