J4 ›› 2013, Vol. 31 ›› Issue (2): 147-151.

• 论文 • 上一篇    下一篇

基于labview和PCA分析方法的电子鼻设计

赵万1, 梅笑冬1, 朱哲1, 张厚博1, 胡小龙1, 王彪2,卢革宇1   

  1. 1. 吉林大学 电子科学与工程学院, 长春 130012; 2. 中国科学院 长春光学精密机械与物理研究所, 长春 130033
  • 收稿日期:2013-01-04 出版日期:2013-03-23 发布日期:2013-06-05
  • 作者简介:赵万(1987—), 男, 陕西渭南人, 吉林大学硕士研究生, 主要从事先进传感器的应用研究, (Tel)86-13504433162(E-mail)zhaowan0619@mails.jlu.edu.cn;通讯作者:卢革宇(1963—), 男, 黑龙江海伦人,吉林大学教授, 博士生导师, 主要从事先进传感技术研究, (Tel)86-431-85167808(E-mail)lugy@jlu.edu.cn。
  • 基金资助:

    国家自然科学基金资助项目(61074172; 61134010); 教育部“长江学者和创新团队发展计划”创新团队基金资助项目(IRT1017)

Design of Embedded Electronic Nose Based on Labview and PCA Analytic Method

ZHAO Wan1, MEI Xiao-dong1, ZHU Zhe1, ZHANG Hou-bo1, HU Xiao-long1, WANG Biao2, LU Ge-yu1   

  • Received:2013-01-04 Online:2013-03-23 Published:2013-06-05

摘要:

为解决电子鼻在食物品质评价中的应用问题, 设计了基于金属氧化物半导体型气体传感器阵列和\{Labview\}虚拟仪器的电子鼻系统。该系统通过对不同样品进行信号采集建立气味数据库, 信号采集系统由STM32微控制器和24位模数转换器AD7794构成, 采集的信号通过串口被传输到PC(Personal Computer), PC接收数据后, 使用在Labview平台下搭建的上位机软件, 通过内嵌的Matlab脚本对数据进行整理, 最终利用PCA(Principal Component Analysis)对数据进行分析, 获取气味指纹。该系统通过对5种不同种类食用酱的挥发气体进行检测, 建立气味数据库, 进而实现对未知酱品的检测, 最终实现了对不同种类的食用酱准确区分的方法。

关键词: 电子鼻, 模式识别, 虚拟仪器, 主成分分析

Abstract:

In order to solve the application problems in food quality evaluation by electronic nose, an embedded electronic nose based on metal oxide semiconductor gas sensors array and VI (Virtual Instrument) Labview software was designed. The identification ability of the device was investigated by employing different categories of simple and complex odor databases. A data acquisition system based on ARM-STM32 microprocessor and 24-bit ADC (AD7794) was also presented. The test data were uploaded to PC (Personal Computer) through RS232 communication mode. Then Matlab software was used to the organization of test data. Finally the fingerprint information of the target gas was obtained by the PCA (Principal Component Analysis). In our experiment, five different sauces were tested though the volatile gases, which were derived from sauces. The original database was built. Then comparing with the database, the unknown sauce could be recognized well. The results show that this system has high accuracy in the classification of gas mixtures.

Key words: E-nose, pattern recognition, Labview, principal component analysis(PCA)

中图分类号: 

  • TP393.1