基于模糊神经网络的电阻炉温度控制系统设计  

Design of Resistance Furnace Temperature Control System Based on Fuzzy Neural Network

作　　者：李军 LI Jun(School of Electronic Information,Shaanxi National Defense Industry Vocational and Technical College,Xfan 710300,China)

机构地区：[1]陕西国防工业职业技术学院电子信息学院,陕西西安710300

出　　处：《工业加热》2022年第9期45-48,共4页Industrial Heating

摘　　要：为了解决传统工业电阻炉存在非线性、大惯性以及时滞等缺陷,本研究设计出一种基于模糊神经网络的电阻炉温度控制系统。该系统采用AVR系列的单片机作为硬件部分的核心设备,有利于对电阻炉温度的精准控制,并在系统内设置高温报警模块,对于系统的安全性具有保障作用。利用ATmega16作为该系统的控制芯片,支持系统在线编程接口。在模糊PID算法的控制下,可实现电阻炉温度控制系统在最短时间内将炉温升至目标值,达到预期温度控制效果。In order to solve the defects of traditional industrial resistance furnace, such as nonlinear, large inertia and time delay, this study designed a resistance furnace temperature control system based on fuzzy neural network.The system uses AVR series of single-chip microcomputer as the core equipment of the hardware part, which is conducive to the precise control of the temperature of the resistance furnace, and the high temperature alarm module is set in the system, which has a role in ensuring the safety of the system.ATmega16 is used as the control chip of the system to support the system online programming interface.Under the control of fuzzy PID algorithm, the temperature control system of resistance furnace can increase the furnace temperature to the target value in the shortest time, and achieve the desired temperature control effect.

关 键 词：模糊神经网络 电阻炉 温度控制 运行效果 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]