A sensitive synchronous detection method for multi-gas using the multiple linear regression analysis

Tingting Zhang; Yu Zhang; Li Wang; Yubin Wei; Qinduan Zhang; Tongyu Liu

doi:10.1117/12.2651642

10 May 2023 A sensitive synchronous detection method for multi-gas using the multiple linear regression analysis

Tingting Zhang, Yu Zhang, Li Wang, Yubin Wei, Qinduan Zhang, Tongyu Liu

Proceedings Volume 12554, AOPC 2022: Advanced Laser Technology and Applications; 125540V (2023) https://doi.org/10.1117/12.2651642
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

Tunable diode laser absorption spectroscopy (TDLAS) technique has been widely investigated for gas concentration measurement in both industry and laboratory. In order to detect different gases within the multi-gas mixture based on TDLAS, different types of schemes have been developed, such as wavelength division multiplexing, time division multiplexing and so on. However, there are many drawbacks of the above methods, such as the slope of normalized baseline restricted the sensitivity and accuracy, the effect of cross-talking interferences becomes a technical bottleneck for multi-gas detection. Therefore, a high sensitive synchronous detection technology for multi-gas detection using the multiple linear regression analysis method is reported. The wavenumber of 4291cm^-1 has been selected to detect CO and CH₄. Several characteristic points are selected to establish multiple linear regression equations, then the concentrations of CH₄ and CO can be calculated, and the baseline can also be obtained simultaneously. The Allan variance results indicate that the optimal integration time has been improved to ~60s, the minimum measurement precision of CH₄ and CO is ~0.58% and ~0.41×10^-6 respectively. Meanwhile, the detection cost and response time can be reduced obviously

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Tingting Zhang, Yu Zhang, Li Wang, Yubin Wei, Qinduan Zhang, and Tongyu Liu "A sensitive synchronous detection method for multi-gas using the multiple linear regression analysis", Proc. SPIE 12554, AOPC 2022: Advanced Laser Technology and Applications, 125540V (10 May 2023); https://doi.org/10.1117/12.2651642

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KEYWORDS

Carbon monoxide

Absorption

Gases

Calibration

Semiconductor lasers

Absorption spectroscopy

Light

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