摘要
提出了基于PROFIBUS-DP的热电偶温度测量系统非线性在线校正方法,通过DDE协议在上位机实现mAT-LAB与MCGS软件的数据交换,引入神经网络模型模拟检测系统非线性特性,并利用遗传算法的全局搜索能力对神经网络模型进行权值优化,新方法减轻了热电偶温度采集从站的负担,充分利用了PC机的数据处理能力,实现了热电偶温度采集系统的非线性实时补偿。实验证明该方法可将样本温度的最大相对误差从9.96%降低到4.76%。新方法具有模型可靠、自适应能力强、计算精度高等特点。
A new method was proposed to realize the on-line compensation for the nonlinearity of the thermocouple temperature measurement system based on PROFIBUS-DP bus.On the monitor PC the compensating programs written in MATLAB exchange the temperature data with the monitoring programs written in MCGS through the DDE protocol.Neural network was introduced to simulate the nonlinear characteristics of the measurement system,and the genetic algorithm was used to optimize the weights of the BP neural network for its g...
出处
《仪表技术与传感器》
CSCD
北大核心
2008年第4期56-58,共3页
Instrument Technique and Sensor
关键词
热电偶
非线性补偿
遗传算法
神经网络
thermocouple
nonlinearity compensation
genetic algorithm
neural network
