瓦斯传感器非线性的动态调校  

Dynamic Correction of Nonlinear Characteristic of Methane Sensor

作　　者：童敏明[1] 

机构地区：[1]中国矿业大学,江苏省徐州市221008

出　　处：《仪表技术与传感器》2000年第11期34-36,共3页Instrument Technique and Sensor

基　　金：中国矿业大学科研基金资助项目

摘　　要：热催化元件是广泛地用于瓦斯检测的一种传感器 ,其非线性特性影响了瓦斯检测的准确性。由于瓦斯传感器的离散性 ,实行动态调校是非常必要的。本文阐述了通过神经网络模型—Adaline模型的网络学习 ,逼进非线性函数的方法。利用神经网络对催化传感器的非线性进行校正 。A catalytic sensor has been widely used for methane detection. Its nonlinear characteristic has lowed the accuracy of the methane detection.Due to the variance parameter of the sensor,the dynamic correction of nonlinear characteristic is very necessary for the accurate detection. A kind of neuron-network model,Adaline model, has been introduced in this paper. The function of intelligent learning in neuron-network is very useful for the process of the nonlinear characteristic of the sensor and has much increased the accuracy of methane detection.

关 键 词：瓦斯传感器 非线性补偿 动态标定 神经网络 

分 类 号：TD712.55[矿业工程—矿井通风与安全] TP212.06[自动化与计算机技术—检测技术与自动化装置]