Design of electronic nose system based on LabVIEW

ZHANG Jia-qi; JI Da-xuan; LI Jie-yi; REN Yuan

doi:10.13873/J.1000-9787(2015)05-0092-03

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Design of electronic nose system based on LabVIEW

更新时间：2025-09-11

- Design of electronic nose system based on LabVIEW
- Vol. 34, Issue 5, Pages: 92-94(2015)
- 作者机构：
  
  1. 天津理工大学环境科学与安全工程学院
  2. 天津房信建筑工程总承包有限公司
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)05-0092-03
  CLC： TP212
- Published：2015
- 稿件说明：
移动端阅览
[1]张嘉琪,冀大选,李杰一,任远.基于LabVIEW平台的电子鼻系统设计[J].传感器与微系统,2015,34(05):92-94.

ZHANG Jia-qi, JI Da-xuan, LI Jie-yi, et al. Design of electronic nose system based on LabVIEW[J]. 2015, 34(5): 92-94.
[1]张嘉琪,冀大选,李杰一,任远.基于LabVIEW平台的电子鼻系统设计[J].传感器与微系统,2015,34(05):92-94. DOI： 10.13873/J.1000-9787(2015)05-0092-03.

ZHANG Jia-qi, JI Da-xuan, LI Jie-yi, et al. Design of electronic nose system based on LabVIEW[J]. 2015, 34(5): 92-94. DOI： 10.13873/J.1000-9787(2015)05-0092-03.

摘要

为了检测CH4

CO气体

设计了基于STM32F103和LabVIEW的智能电子鼻系统;该系统利用STM32F103作为核心控制系统

筛选出6只电化学传感器组成的阵列

传感器的响应信号经过电路放大转换后传输到上位机;利用LabVIEW开发上位机软件

将数据采集系统与神经网络模式识别系统无缝连接。经过实验验证

该系统运行稳定可靠

通过对9种不同比例混合的CH4和CO气体进行检测

CO的平均误差为5.52×10-6

CH4的平均误差为7.15×10-6

测试结果满足要求。

Abstract

In order to detect the gas of CH4 and CO

electronic nose system is designed based on STM32F103 and LabVIEW; the system uses STM32F103 as core control system

filtrate sensor array maked up with which include six electrochemical sensors

and signal of sensor is transmitted to upper PC by conditioning circuit

software is developed based on Lab VIEW

which combine data acquisition and neural network. Experiment proves that the system operates stably and reliably

through detecting CH4 and CO which are mixed with nine different proportion

average error of CO is 5. 52 × 10- 6

and the average error of CH4 is 7. 15 × 10- 6

and the result meet requirement.

关键词

Keywords

references

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基于ZigBee网络的甲烷监测系统设计 [J]. 续文浩. 仪表技术 . 2014(01)

基于STM32的振弦式频率测量仪器研究 [J]. 杨光祥,刘渝新. 计算机测量与控制 . 2013(06)

基于恒电流源的电阻式气敏传感器检测系统 [J]. 刘树海,郑传涛,徐琳,宋宏伟. 吉林大学学报(信息科学版) . 2012(04)

基于气体传感器阵列的人工神经网络算法的设计及C语言实现 [D]. 李瑛. 电子科技大学 2012

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Portable e-nose to classify different kinds of wine [J] . M. Aleixandre,J. Lozano,J. Gutiérrez,I. Sayago,M.J. Fernández,M.C. Horrillo. Sensors & Actuators: B. Chemical . 2007 (1)

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Related Institution

State Key Laboratory on Integrated Optoelectronics,College of Electronic Science and Engineering,Jilin University

Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences

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