Suppr超能文献

基于空间外差光谱仪的视觉电子鼻系统研究

Research on a Visual Electronic Nose System Based on Spatial Heterodyne Spectrometer.

作者信息

Zhang Wenli, Tian Fengchun, Song An, Hu Youwen

机构信息

College of Communication Engineering, Chongqing University, 174 Sha Pingba, Chongqing 400044, China.

出版信息

Sensors (Basel). 2018 Apr 13;18(4):1188. doi: 10.3390/s18041188.

Abstract

Light absorption gas sensing technology has the characteristics of massive parallelism, cross-sensitivity and extensive responsiveness, which make it suitable for the sensing task of an electronic nose (e-nose). With the performance of hyperspectral resolution, spatial heterodyne spectrometer (SHS) can present absorption spectra of the gas in the form of a two dimensional (2D) interferogram which facilitates the analysis of gases with mature image processing techniques. Therefore, a visual e-nose system based on SHS was proposed. Firstly, a theoretical model of the visual e-nose system was constructed and its visual maps were obtained by an experiment. Then the local binary pattern (LBP) and Gray-Level Co-occurrence Matrix (GLCM) were used for feature extraction. Finally, classification algorithms based on distance similarity (Correlation coefficient (CC); Euclidean distance to centroids (EDC)) were chosen to carry on pattern recognition analysis to verify the feasibility of the visual e-nose system.

摘要

光吸收气体传感技术具有大规模并行性、交叉敏感性和广泛响应性等特点,使其适用于电子鼻(e-nose)的传感任务。空间外差光谱仪(SHS)具有高光谱分辨率的性能,能够以二维(2D)干涉图的形式呈现气体的吸收光谱,便于利用成熟的图像处理技术对气体进行分析。因此,提出了一种基于SHS的可视化电子鼻系统。首先,构建了可视化电子鼻系统的理论模型,并通过实验获得了其可视化图谱。然后,使用局部二值模式(LBP)和灰度共生矩阵(GLCM)进行特征提取。最后,选择基于距离相似度的分类算法(相关系数(CC);到质心的欧几里得距离(EDC))进行模式识别分析,以验证可视化电子鼻系统的可行性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9a9/5948887/41b3323564c2/sensors-18-01188-g004.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验