期刊
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
卷 69, 期 7, 页码 4533-4544出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2019.2948413
关键词
Temperature sensors; Gas detectors; Temperature measurement; Modulation; Sensor phenomena and characterization; Heating systems; Gas identification; gas sensors; general regression neural network (GRNN); temperature modulation; ZnO
资金
- National Natural Science Foundation of China [61973058, 61833006, 61673367, 61504023]
- Fundamental Research Funds for the Central Universities in China [N180408018, N170405001, N180102032, N170407005]
- Liao Ning Revitalization Talents Program [XLYC1807198]
- Liaoning Province Natural Science Foundation [20180550483, 20170540324]
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.
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