摘要
根据催化传感器在不同的工作温度下具有不同气体检测灵敏度的特点,提出基于恒温检测与RBF神经网络的单一热催化传感器检测可燃混合气体的新方法。采用动态学习算法的RBF神经网络建立了多种可燃气体分析的数学模型。通过对甲烷,一氧化碳和氢气三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。
Based on the sensitivity of catalytic sensor is different in different temperatures , a new method of analyzing flammable gases with a single catalytic sensor based on thermostatic detection and RBF neural network theory was put forward. A mathematic model of analyzing the diversiform inflammable gases was erected by RBF neural network of dynamic learning algorithm. By the experiment of mixed gases such as firedamp, carbon monoxide and hydrogen, the result showed the possibility to analyze mixed inflammable gases by one catalytic sensor.
出处
《传感技术学报》
CAS
CSCD
北大核心
2009年第5期623-626,共4页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金资助项目(50374067)
