基于单一传感器的可燃混合气体RBF网络分析

催化传感器对不同可燃气体或在不同的工作温度下有不同的输出灵敏度,根据这一特点控制单一催化传感器工作在不同的温度,检测可燃混合气体时可以得到不同的输出信号,采用RBF神经网络和动态学习算法,建立了多种可燃气体分析的数学模型。通过对CH4,CO,H23种气体混合的样本进行实验,结果表明:所研究的方法可以较好地实现单一催化传感器对多种可燃混合气体的分析。

Analysis of mixed inflammable gases based on single sensor and RBF network

A catalytic sensor has different sensitivity to different gases or under different temperature.According to this characterictics,through controling a catalytic sensor worked under different temperature,different output singal can be obtained when detecting the inflammable gases.A mathematic model of analyzing the diversiform inflammable gases is erected by adopting radial basis function(RBF) neural network and dynamic learning algorithm.By the experiment of mixed gases such as firedamp,carbon monoxide and hydrogen,the results show the possibility to analyze mixed inflammable gases by one catalytic sensor.