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Soft-sensing method of crucial biochemical quantity in penicillin fermentation process based on fuzzy neural inverse and system structure thereof

A penicillin fermentation, fuzzy neural technology, applied in biological neural network model, electrical program control, comprehensive factory control, etc., can solve problems such as inability to improve the accuracy of soft measurement, complex model, omission of important information of industrial objects, etc.

Inactive Publication Date: 2012-05-23
JIANGSU UNIV
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Problems solved by technology

The selection of traditional auxiliary variables is mainly based on the process mechanism of industrial objects and expert experience. The number of auxiliary variables determined in this way is considerable, and the degree of correlation varies greatly. If they are all used as auxiliary variables of soft measurement, the model is bound to be very complicated. Not only can not improve the accuracy of soft measurement, but also important information of industrial objects may be missed

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  • Soft-sensing method of crucial biochemical quantity in penicillin fermentation process based on fuzzy neural inverse and system structure thereof
  • Soft-sensing method of crucial biochemical quantity in penicillin fermentation process based on fuzzy neural inverse and system structure thereof
  • Soft-sensing method of crucial biochemical quantity in penicillin fermentation process based on fuzzy neural inverse and system structure thereof

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[0046] specific implementation plan

[0047] Embodiments of the present invention: Firstly, according to the mechanism model of the penicillin fermentation process, the feed input, online directly measurable output, and indirect measurable quantities requiring offline testing are selected and determined for the penicillin fermentation process. Then choose to determine the input and output of the soft sensor in the penicillin fermentation process, and establish the model of the soft sensor and the model of the inverse of the soft sensor, and then use the static fuzzy neural network plus 7 differentiators and determine through the training of the static fuzzy neural network Its weight parameters constitute the fuzzy neural inverse, realizing the function of soft sensor inverse. Finally, the obtained fuzzy nerves are inversely connected after the penicillin fermentation process, and the indirect measurable (hyphae concentration x 1 , total sugar concentration x 2 , product conc...

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Abstract

Soft-sensing method of crucial biochemical quantity in penicillin fermentation process based on fuzzy neural inverse and system structure thereof is a method for resloving the problem that the crucial biochemical quantity in penicillin fermentation process is difficult to be measured by physical sensor on-line and real-time. Fuzzy neural inverse soft-sensing method establishes a soft-sensor (11) model based on a kinetic equation in penicillin fermentation process (1), on this basis establishes an inverse model of the soft-sensor according to inverse system method, and then uses static fuzzy neural network (41) and a different or to establish fuzzy neural inverse (4) through a free parameters determined by training the static fuzzy neural network, then the soft-sensor inverse is implemented, finally links the fuzzy neural inverse after the penicillin fermentation process to implement on-line and real-time soft-sensing of fungi concentration x[1], substrate concentration x[2] and products concentration x[3]. Specific implementation of the fuzzy neural inverse is the constructed fuzzy neural inverse system applies embedded microprocessor ARM processor.

Description

technical field [0001] The invention is an on-line estimation problem of three key biochemical quantities, which are difficult to be measured by physical sensors in real-time on-line during the penicillin fermentation process, the total sugar concentration and mycelia concentration, and belongs to the technical field of soft measurement and system construction . Background technique [0002] In many industrial control occasions, there is a large category of such variables: they are closely related to product quality and need to be strictly controlled, but due to technical or economical reasons, it is currently difficult or impossible to directly detect through physical sensors. Typical examples are product component concentrations in distillation columns, reactant concentrations and product distribution in chemical reactors, and biochemical quantities in biological fermenters. In order to solve the measurement problem of such variables, soft sensor technology came into bein...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/06G05B19/418
CPCY02P90/02
Inventor 孙玉坤黄永红王博嵇小辅刘国海
Owner JIANGSU UNIV
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