高等学校化学学报

高等学校化学学报 ›› 2006, Vol. 27 ›› Issue (1): 55.

• 研究简报 • 上一篇    下一篇

气体传感器阵列信号的盲分离研究

魏广芬1, 唐祯安1, 陈正豪2, 余隽1, 王立鼎1, 闫桂珍3   

  1. 1. 大连理工大学微系统研究中心, 大连 116024; 2. 香港科技大学电机与电子工程系, 香港九龙清水湾; 3. 北京大学微电子学研究所, 北京 100871
  • 收稿日期:2004-11-23 出版日期:2006-01-10 发布日期:2006-01-10
  • 通讯作者: 唐祯安(1955年出生), 男, 教授、 博士生导师, 主要从事微传感器及微尺度理论研究. E-mail: tangza@dlut.edu.cn
  • 基金资助:

    基金项目: 国家自然科学基金(批准号: 59995550-5, 90207003), 国家“八六三”计划项目(批准号: 2003AA404180)资助.

Studies on Blind Separation of Gas Sensor Array Signals

WEI Guang-Fen1, TANG Zhen-An 1* , CHAN Philip C. H.2, YU Jun1, WANG Li-Ding1, YAN Gui-Zhen3   

  1. 1. Research Center for Micro Systems, Dalian University of Technology, Dalian 116024, China;
    2. Department of Electrical and Electronic Engineering, Hong Kong University of Science and Technology, Hong Kong, China;
    3. Institute of Microelectronics, Peking University, Beijing 100871, China
  • Received:2004-11-23 Online:2006-01-10 Published:2006-01-10
  • Contact: TANG Zhen-An, E-mail: tangza@dlut.edu.cn

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被引次数

8

摘要：

本文在使用一个四单元微热板式集成气体传感器阵列测试煤矿中的两种主要易燃易爆气体一氧化碳和甲烷的基础上, 将气体传感器阵列与盲信号分离技术相结合, 讨论了混合气体分析的盲可辨识性, 并使用盲信号分离中的一种主要方法独立分量分析法(ICA)进行了分析和验证.

关键词: 盲信号分离; 气体传感器阵列; 混合气体分析; 独立分量分析法

Abstract:

Responses of a Micro-hotplate based integrated gas sensor array to CO and CH4 were measured with an automated gas sensor calibration system. Combining with the blind source separation(BSS) techniques, the blind separability in gas mixture analysis was discussed. The widely used BSS approach-Independent Component Analysis(ICA) was adopted to verify the proposed method by analyzing the gas mixtures of CO and CH4. The analysis results demonstrate that BSS was an effective way to extract the information of gas components in mixtures, from which the gas concentrations can be estimated. The average relative quantification errors were 9.37% and 8.11% for CO and CH4, respectively, in the specified concentration ranges.

Key words: Blind source separation; Gas sensor array; Gas mixture analysis; Independent component analysis

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