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采用小波去噪算法的高灵敏度宽带差分红外光声光谱法用于痕量气体检测。

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

作者信息

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

机构信息

School of Physics and Optoelectronic Engineering, Xidian University, Xi'an, 710071, China.

Center for Advanced Diffusion-Wave and Photoacoustic Technologies (CADIPT), Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, M5S 3G8, Canada.

出版信息

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

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.

摘要

对于实际应用而言,利用光声光谱法提高痕量气体的可探测性需要有效抑制强背景噪声。基于配备了专门设计的T型谐振器以及同时具备差分光学和光声测量能力的傅里叶变换红外(FTIR)光谱仪,研究了一种升级后的红外宽带痕量气体检测配置。通过使用乙炔和当地空气作为合适的样本,理论和实验均表明,由于非本征光学基线信号的光相关相干噪声抑制效果显著,差分光声模式的探测能力远优于纯光学方法。详细介绍了具有优化参数的小波域去噪算法,通过对差分光声测量中的非相干环境干扰进行去噪,极大地提高了信噪比。结果表明,对乙炔的灵敏度从5 ppmv(原始差分模式)提高到806 ppbv,提高了五倍。通过优化的小波域去噪算法实现背景噪声抑制后,宽带差分光声痕量气体检测被证明是一种有效的痕量气体检测方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4385/7749430/35211d80c8a4/gr1.jpg

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