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Improving detection limit of non-dispersive infrared gas sensor system by wavelet denoising algorithm
Author(s): Libin Ch'ien; Yongjie Wang; Ancun Shi; Fang Li
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Paper Abstract

The improvement of the detection limit of gas sensors has always been the focus of sensor research. Compared with the improvement of hardware, the improvement of the algorithm is still relatively less. In this study, a dual-channel methane gas sensor system based on mid-infrared LED light source was designed. We apply the wavelet denoising algorithm to the high-frequency noise suppression of the sensor system, which achieves a 36dB signal-to-noise ratio improvement over the traditional low-pass filter, making the detection limit of the sensing system reach the level below 3ppm. We give an estimation method for the detection limit of the sensing system. The detection limits estimated by this theory are basically the same as those obtained by the Allen deviation analysis in the conventional method. Implementing better algorithms to improve sensor SNR in software can reduce the demands of improving sensor SNR solely from hardware improvements.

Paper Details

Date Published: 31 December 2019
PDF: 7 pages
Proc. SPIE 11384, Eleventh International Conference on Signal Processing Systems, 113841G (31 December 2019); doi: 10.1117/12.2559704
Show Author Affiliations
Libin Ch'ien, Institute of Semiconductors (China)
Univ. of Chinese Academy of Sciences (China)
Yongjie Wang, Univ. of Chinese Academy of Sciences (China)
Ancun Shi, Univ. of Chinese Academy of Sciences (China)
Fang Li, Institute of Semiconductors (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 11384:
Eleventh International Conference on Signal Processing Systems
Kezhi Mao, Editor(s)

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