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论文类型：期刊论文

第一作者：He, Aixiang

通讯作者：Tang, ZN (reprint author), Dalian Univ Technol, Key Lab Liaoning Integrated Circuits Technol, Sch Elect Sci & Technol, Dalian 116024, Peoples R China.; Wei, GF (reprint author), Shandong Inst Business & Technol, Sch Informat & Elect Engn, Yantai 264005, Peoples R China.

合写作者：Yu, Jun,Wei, Guangfen,Chen, Yi,Wu, Hao,Tang, Zhenan

发表时间：2016-01-01

发表刊物：JOURNAL OF SENSORS

收录刊物：SCIE、EI、Scopus

卷号：2016

ISSN号：1687-725X

摘要：Because the sensor response is dependent on its operating temperature, modulated temperature operation is usually applied in gas sensors for the identification of different gases. In this paper, the modulated operating temperature of microhotplate gas sensors combined with a feature extraction method based on Short-Time Fourier Transform (STFT) is introduced. Because the gas concentration in the ambient air usually has high fluctuation, STFT is applied to extract transient features from time-frequency domain, and the relationship between the STFT spectrum and sensor response is further explored. Because of the low thermal time constant, the sufficient discriminatory information of different gases is preserved in the envelope of the response curve. Feature information tends to be contained in the lower frequencies, but not at higher frequencies. Therefore, features are extracted from the STFT amplitude values at the frequencies ranging from 0 Hz to the fundamental frequency to accomplish the identification task. These lower frequency features are extracted and further processed by decision tree-based pattern recognition. The proposed method shows high classification capability by the analysis of different concentration of carbon monoxide, methane, and ethanol.