Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection

Lixian Liu; Huiting Huan; Wei Li; Andreas Mandelis; Yafei Wang; Le Zhang; Xueshi Zhang; Xukun Yin; Yuxiang Wu; Xiaopeng Shao

doi:10.1016/j.pacs.2020.100228

Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection

Photoacoustics. 2020 Dec 5:21:100228. doi: 10.1016/j.pacs.2020.100228. eCollection 2021 Mar.

Authors

Lixian Liu^{1

2

3}, Huiting Huan^{1

2

3}, Wei Li¹, Andreas Mandelis^{2

3}, Yafei Wang³, Le Zhang¹, Xueshi Zhang¹, Xukun Yin¹, Yuxiang Wu¹, Xiaopeng Shao¹

Affiliations

¹ School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, 710071, China.
² Center for Advanced Diffusion-Wave and Photoacoustic Technologies (CADIPT), Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, M5S 3G8, Canada.
³ School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, 610054, China.

Abstract

Enhancement of trace gas detectability using photoacoustic spectroscopy requires the effective suppression of strong background noise for practical applications. An upgraded infrared broadband trace gas detection configuration was investigated based on a Fourier transform infrared (FTIR) spectrometer equipped with specially designed T-resonators and simultaneous differential optical and photoacoustic measurement capabilities. By using acetylene and local air as appropriate samples, the detectivity of the differential photoacoustic mode was demonstrated to be far better than the pure optical approach both theoretically and experimentally, due to the effectiveness of light-correlated coherent noise suppression of non-intrinsic optical baseline signals. The wavelet domain denoising algorithm with the optimized parameters was introduced in detail to greatly improve the signal-to-noise ratio by denoising the incoherent ambient interference with respect to the differential photoacoustic measurement. The results showed enhancement of sensitivity to acetylene from 5 ppmv (original differential mode) to 806 ppbv, a fivefold improvement. With the suppression of background noise accomplished by the optimized wavelet domain denoising algorithm, the broadband differential photoacoustic trace gas detection was shown to be an effective approach for trace gas detection.

Keywords: Differential detection mode; Fourier-transform infrared photoacoustic spectroscopy; Gas detection sensitivity; Noise elimination; Wavelet domain denoising.