Soft measuring method and system for key variables of lysine fermentation process based on PSO-FSVM

A PSO-FSVM and lysine fermentation technology, applied in the interdisciplinary field of biotechnology and information science, can solve the problems of difficult real-time online measurement of key biochemical parameters, large lag, etc., to improve the timeliness of measurement, low cost, and reduce workload Effect

Inactive Publication Date: 2017-02-22
JIANGSU UNIV
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Problems solved by technology

In the present invention, a PSO-FSVM soft sensor modeling method is proposed to solve the problems of nonlinearity, large lag, multivariable dynamic coupling, and difficulty in real-time online measurement of key biochemical parameters in the lysine fermentation process.

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  • Soft measuring method and system for key variables of lysine fermentation process based on PSO-FSVM
  • Soft measuring method and system for key variables of lysine fermentation process based on PSO-FSVM
  • Soft measuring method and system for key variables of lysine fermentation process based on PSO-FSVM

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Embodiment Construction

[0032] The following implementation examples combined with the prediction of key state variables in the lysine fermentation process and figure 2 The shown implementation flowchart describes in detail the implementation example of the present invention:

[0033] 1. Select auxiliary vectors: select external variables that can be directly measured and are closely related to the process, and use the consistent correlation method to analyze their correlation with key state variables, and take the correlation degree r ij External variables ≥0.7 were used as auxiliary variables in the soft sensor model.

[0034] (1) Acquisition of fermentation process data

[0035] In the lysine fermentation process, Corynebacterium pekinense was used as the strain, and the WKT-30L fermentation monitoring system was used for fermentation and cultivation. Such as figure 1 The monitoring system shown is composed of a fermenter 1, a steam generator 2, an air compressor 3, an air filter 4 and a water...

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Abstract

The invention discloses a soft measuring method and system for key variables of a lysine fermentation process based on PSO-FSVM. The method relies on a hardware platform, a measuring instrument and a computer system software used for intelligent computing. The method includes the following steps: analyzing the technological mechanism of the lysine fermentation process, selecting appropriate auxiliary variables, and establishing a training sample database according to historical pot batch data; mapping a training sample into a high dimensional kernel space, and calculating the fuzzy membership degree corresponding to each sample point in the kernel space; then conducting on-line optimization on a kernel function parameter and a penalty coefficient by a particle swarm algorithm, training the fuzzy training sample by a fuzzy support vector machine, and establishing a soft measurement model; finally, achieving prediction of the key state variables according to the latest to-be-predicted pot batch input vector. The soft measuring method and system achieve the on-line real-time prediction of the key state variables in the lysine fermentation process, and are of great significance for the parameter prediction and the optimal control of the lysine fermentation process.

Description

technical field [0001] The invention belongs to the interdisciplinary field of biotechnology and information science, and mainly relates to a soft-measurement method for three key state variables that are difficult to be measured online and in real time by physical sensors in the lysine fermentation process—hyphae concentration, substrate concentration, and product concentration. system construction method. Background technique [0002] Biological fermentation is an important class of industrial production engineering, which provides medicines (antibiotics, genetic engineering heavy drugs, vaccines, vitamins, etc.), various amino acids (nucleic acids) and other products (alcoholic beverages, soy sauce vinegar, biological health products, etc.). Its typical characteristics are complex internal mechanism, poor repeatability, poor production fluctuation, and highly nonlinear and time-varying characteristics; at the same time, many key parameters of the fermentation process (su...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04G06F19/28
CPCG05B13/042G16B50/00
Inventor 王博张逸康张生鹏赵若妤
Owner JIANGSU UNIV
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