Detection and Identification of Volatile Organic Compounds Based on Temperature-Modulated ZnO Sensors

A novel detection method based on ZnO metal-oxide sensors, capable of detecting various species and concentrations of aimed volatile organic compounds (VOCs), has been proposed in this article. In conjunction with signal processing algorithms, the characteristic signals of the sensors operated under...

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Bibliographic Details
Published inIEEE transactions on instrumentation and measurement Vol. 69; no. 7; pp. 4533 - 4544
Main Authors Yuan, Zhenyu, Han, Erchou, Meng, Fanli, Zuo, Kaiyuan
Format Journal Article
LanguageEnglish
Published New York IEEE 01.07.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Gas detectors
Gas identification
gas sensors
general regression neural network (GRNN)
General regression neural networks
Heating systems
Modulation
Sensor phenomena and characterization
Sensors
Signal processing
Temperature measurement
temperature modulation
Temperature sensors
VOCs
Volatile organic compounds
Waveforms
Zinc oxide
ZnO
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Summary:A novel detection method based on ZnO metal-oxide sensors, capable of detecting various species and concentrations of aimed volatile organic compounds (VOCs), has been proposed in this article. In conjunction with signal processing algorithms, the characteristic signals of the sensors operated under temperature modulating are investigated. When the sensor is operating in the temperature modulation mode and is exposed to different detection gases, it will display different output waveforms. Considering the stability of the sensors in practical applications, general regression neural network (GRNN) is used to distinguish the species and concentration of gas in detail.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2019.2948413