Multivariate-coupled-enhanced photoacoustic spectroscopy with Chebyshev rational fractional-order filtering algorithm for trace CH4 detection

Multivariate-coupled-enhanced photoacoustic spectroscopy with Chebyshev rational fractional-order filtering algorithm for trace CH4 detection

An innovative and miniature photoacoustic spectroscopy (PAS) gas sensor based on a multivariate-coupled amplification photoacoustic cell (MVCA-PAC) with a total length of 100 mm was developed to achieve ultra-sensitive trace CH4 detection. Acoustic pressure distribution simulations reveal that at th...

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Bibliographic Details
Main Authors: Shenlong Zha, Hang Chen, Chen Liu, Yuxiang Guo, Hongliang Ma, Qilei Zhang, Lingli Li, Shengbao Zhan, Gang Cheng, Yanan Cao, Pan Pan
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Photoacoustics
Subjects:
Photoacoustic spectroscopy
Multivariate coupled amplification
Chebyshev rational fractional-order filtering
Detection limit
Measurement precision
Online Access:http://www.sciencedirect.com/science/article/pii/S2213597925000114
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Summary:An innovative and miniature photoacoustic spectroscopy (PAS) gas sensor based on a multivariate-coupled amplification photoacoustic cell (MVCA-PAC) with a total length of 100 mm was developed to achieve ultra-sensitive trace CH4 detection. Acoustic pressure distribution simulations reveal that at the first-order resonance frequency, the MVCA-PAC achieves a maximum acoustic pressure approximately 3.9 times higher than that of a conventional photoacoustic cell. The absorption optical path of the MVCA-PAC reached 2068 mm through 22 reflections, resulting in a 2-fold increase in the amplitude of photoacoustic signals compared to the traditional photoacoustic cell with an equivalent absorption optical path. Furthermore, compared to a single-pass photoacoustic cell, the 2-f signal intensity of the MVCA-PAC increased by a factor of 4.5. Allan variance analysis indicated a detection limit of 0.572 ppm for CH4 detection with an averaging time of approximately 300 s. To further improve the measurement precision of the designed sensor, the Chebyshev rational fractional-order filtering (CRFOF) algorithm was introduced for PAS signal processing for the first time. Post-processing results demonstrated a 15.4-fold improvement in measurement precision, achieving a precision of 0.578 ppm. Finally, continuous monitoring of atmospheric CH4 over a 48-hour period validated the reliability and feasibility of the sensor.
ISSN:2213-5979

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