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Fuzzy neural network-based oxygenator pressure control method

A fuzzy neural network and pressure control technology, applied in the field of medical equipment, can solve the problems of high pressure of molecular sieve adsorption tower, inability to ensure high-performance operation of oxygen generator, penetration and other problems

Inactive Publication Date: 2019-01-11
苏州日尚医疗科技有限公司
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Problems solved by technology

[0005] The present invention provides a method for controlling the pressure of an oxygen generator based on a fuzzy neural network. The purpose of the method is to solve the problem that the existing technology cannot guarantee the long-term continuous high-performance operation of the oxygen generator, and the molecular sieve adsorption tower is prone to breakthrough caused by too high pressure, or Problems of uneven load and low-efficiency operation of double-sided molecular sieve adsorption tower

Method used

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  • Fuzzy neural network-based oxygenator pressure control method
  • Fuzzy neural network-based oxygenator pressure control method
  • Fuzzy neural network-based oxygenator pressure control method

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Embodiment

[0096] Example: A Fuzzy Neural Network-Based Oxygen Concentrator Pressure Control Method

[0097] Include the following steps:

[0098] The first step is to construct a fuzzy neural network controller, which includes an antecedent network and a posterior network.

[0099] See attached figure 1 As shown in , FNNC is the fuzzy neural network controller, u(k) represents the control quantity, and K is the coefficient of the fuzzy neural network control quantity.

[0100] In this embodiment, the fuzzy controller adopts a double-input (two-dimensional) single-output structure.

[0101] The antecedent network is used to match the antecedents of the fuzzy rules, and the posterior network generates the consequents of the fuzzy rules. For the structural diagram of the fuzzy neural network controller, see the attached figure 2 .

[0102] The antecedent network has four layers.

[0103] The first layer is the input layer of the antecedent network. The total number of nodes in the ...

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Abstract

The invention relates to a fuzzy neural network-based oxygenator pressure control method. The method comprises the following steps of: 1, constructing a fuzzy neural network controller, wherein the fuzzy neural network controller comprises an antecedent network and a seccedent network, the antecedent network comprises four layers such as an antecedent network input layer, a fuzzification layer, afuzzy rule matching layer and a normalization layer, and the seccedent network comprises three layers such as a seccedent network input layer, a rule seccedent calculation layer and a controller output layer. The fuzzy neural network-based oxygenator pressure control method combines the advantages of fuzzy control and neural network control, is used for dynamically controlling system pressure of oxygenators in real time, is capable of solving deficiencies of oxygenators working in a manner of controlling switching via time or fixing pressure limit values, and is beneficial for stably and continuously preparing high-concentration oxygen.

Description

technical field [0001] The invention belongs to the field of medical equipment, and specifically relates to a method for controlling the pressure of an oxygen generator, in particular to a method for controlling the pressure of an oxygen generator based on a fuzzy neural network. Background technique [0002] At present, most small and medium-sized oxygen concentrators for rehabilitation use molecular sieve pressure swing adsorption technology for oxygen production. Whether the pressure of the oxygen generator system is stable or not has a significant impact on the high purity of the oxygen generator concentration and the long-term stable operation of the oxygen generator system. Due to the original discrete differences in molecular sieve material characteristics, the process capability distribution probability of the existing industrial technology level, the fluctuation of the power grid in the area where the oxygen generator is applied, and environmental changes, the syste...

Claims

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Application Information

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IPC IPC(8): G05B13/04G05D16/20
CPCG05B13/0285G05B13/042G05D16/20
Inventor 张志伟王凯杨滨
Owner 苏州日尚医疗科技有限公司
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