基于人工神经网络的电子鼻对混合气体检测研究

Research on Detection of Mixed Gas by Electronic Nose Based on Artificial Neural Network

在简要概述电子鼻系统原理的基础上,分析人工神经网络模式识别的特性、结构和识别原理,阐述一种基于人工神经网络的混合气体检测方法。结果证明通过人工神经网络的模式识别和气体传感器阵列技术相结合,能够有效地解决气体传感器阵列的交叉敏感问题,从而实现对混合气体的定性定量检测,并且拥有广泛的应用前景。

On the basis of the brief overview of principles of the electronic nose system ,analyzes the characteristics, structure and identification theory to explain a mixed gas detection method based on artificial neural network. The result shows that the gas sensor array cross-sensitive issue can be effectively solved through the combination of the pattern recognition of artificial neural networks and the gas sensor array technology, which accordingly realizes the detection of qualitative and quantitative mixed gas and has broad application prospects.