摘要
由于电化学气体传感器存在温度漂移和交叉灵敏度问题。基于SF_6气体质量综合分析仪为硬件基础,利用线性神经网络学习思想,设计了多传感器数据融合算法。详细介绍了CO和H_2S二维气体传感器数据融合算法设计和权值迭代学习方法步骤。实验结果表明,该SF_6气体质量综合分析仪对SF_6气体分解产物具有较好检测效果。
Due to the electrochemical gas sensor temperature drift and cross-sensitivity problems and based on hardware of the quality of SF_6 gas comprehensive analyzer,using linear neural network learning thought,multisensory data fusion algorithm was designed. The CO and H_2S two-dimensional gas sensor data fusion algorithm and weight iterative learning steps were designed. The experimental results show that SF_6 gas comprehensive analyzer has a good detection effect.
出处
《仪表技术与传感器》
CSCD
北大核心
2016年第5期15-17,24,共4页
Instrument Technique and Sensor
关键词
电化学气体传感器
交叉灵敏度
线性神经网络
迭代学习
electrochemical gas sensor
cross-sensitivety
linear artificial neural network
iterative learning
