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Ultrasonic dispersion instrument temperature control method based on neural network

A temperature control method and neural network technology, applied in the field of constant temperature control algorithms, can solve problems such as difficulty in obtaining control effects and rapid heat release.

Inactive Publication Date: 2019-04-09
杭州庆睿科技有限公司
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  • Summary
  • Abstract
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AI Technical Summary

Problems solved by technology

However, the traditional PID control method is difficult to achieve the expected control effect in the nonlinear, hysteresis, and time-varying temperature control.
And because the ultrasonic equipment releases heat quickly in actual work, it has high requirements for the rapidity, stability and robustness of temperature control, so only PID control is not enough to meet the requirements

Method used

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  • Ultrasonic dispersion instrument temperature control method based on neural network
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  • Ultrasonic dispersion instrument temperature control method based on neural network

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Embodiment Construction

[0096] The present invention adopts the method of feedforward plus feedback to control the temperature of the reactor. structured as figure 1 shown.

[0097] A neural network-based ultrasonic disperser temperature control method, the method specifically includes the following steps:

[0098] Step 1. Collect data on various indicators of the constant temperature control system through sensors.

[0099] The data collection of various parameters in the constant temperature control system is carried out through the sensor, the feed amount of the reaction material is collected by the flow sensor, the ambient temperature in the reactor is collected by the temperature sensor, and the flow rate in the cooling water pipe is collected by the flow sensor.

[0100] Step 2, BP neural network training and feedforward control.

[0101] The training process can be divided into two types, namely online training and offline training. The so-called online training is to use the temperature o...

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Abstract

The invention discloses an ultrasonic dispersion instrument temperature control method based on a neural network. The method comprises the following steps: performing data collection on various indexes of a constant temperature control system through a sensor, performing training and feed-forward control on the BP neural network, and then filtering a temperature sampling signal in a reaction stillby using a filter algorithm, training the RBF neural network, and finally computing a PID parameter by using a fuzzy RBF neural network; transmitting the PID parameter to a PID controller, and controlling an opening of a cooling water valve by outputting a control signal of the cooling water valve. The control method disclosed by the invention is fast in control speed, high in robustness and hassuper adjustment.

Description

technical field [0001] The invention relates to the field of constant temperature control algorithms, in particular to a neural network-based temperature control method. Background technique [0002] In recent years, ultrasonic dispersers have been widely used in fields such as traditional Chinese medicine extraction, ore pulp leaching, liquid treatment, dispersion, and emulsification. It has significant effects in improving product efficiency, shortening reaction time, and reducing system energy consumption. However, many problems will appear in the actual application process, and temperature control is one of them. Because the optimum temperature for extracting Chinese herbal medicines with an ultrasonic disperser is between 40°C and 60°C, too high a temperature will affect the stability of the extractant and affect the extraction efficiency, so the degree of temperature control is an important factor to consider the working efficiency of the disperser index. [0003] T...

Claims

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Application Information

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IPC IPC(8): G05D23/32G06N3/04G06N3/08
CPCG05D23/32G06N3/04G06N3/08
Inventor 陈华葵
Owner 杭州庆睿科技有限公司
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