电子鼻多组分气体检测算法与性能研究

Algorithm and Performance Study of Electronic Nose for Multi-component Gas Detection

多组分气体检测在工业和环境监测、人体呼出气检测等领域需求广泛。通过对多组分气体的快速检测分析,有助于保障工业生产安全、保护生态环境。电子鼻系统是一种重要的多组分气体检测技术,它能够模拟人类嗅觉,对多种气体或气味进行快速识别。文中针对人体呼出气中常见气体NO_(2)、乙醇和甲醛,通过电子鼻动态配气系统配制不同浓度的单一和混合气体,重点研究电子鼻信号特征提取与多组分气体检测算法,实现了对目标气体的可靠检测,具有较高的定性识别和定量分析准确性,为多组分气体检测技术研究提供了思路和手段。

Multi-component gas detection is widely demanded in industries,environmental monitoring,human breath analysis and other fields.Rapid detection and analysis of multi-component gases can help ensure industrial safety and protect the ecological environment.The electronic nose system is an important technology of multi-component gas detection that can simulate human olfaction and rapidly identify various gases or odors.In this paper,aiming at the common gases NO_(2),ethanol,and formaldehyde in human breath,by using an electronic nose dynamic gas mixing system to prepare different concentrations of single and mixed gases,the signal feature extraction and multi-component gas detection algorithm of the electronic nose system was studied.Reliable detection of the target gas is achieved with high qualitative identification and quantitative analysis accuracy,providing ideas and means for the research of multi-component gas detection technology.