Multivariate-coupled-enhanced photoacoustic spectroscopy with Chebyshev rational fractional-order filtering algorithm...

Area of Science:

• Environmental Science
• Analytical Chemistry
• Spectroscopy

Background:

• Accurate and sensitive detection of trace gases like methane (CH4) is crucial for environmental monitoring and industrial safety.
• Traditional photoacoustic spectroscopy (PAS) sensors face limitations in sensitivity and size for trace gas detection.
• Miniaturization of PAS devices is essential for portable and widespread application.

Purpose of the Study:

• To develop an innovative, miniature photoacoustic spectroscopy (PAS) gas sensor for ultra-sensitive trace methane (CH4) detection.
• To enhance the performance of PAS sensors through a novel multivariate-coupled amplification photoacoustic cell (MVCA-PAC) design.
• To introduce and evaluate the Chebyshev rational fractional-order filtering (CRFOF) algorithm for improved PAS signal processing.

Main Methods:

• Development of a miniature multivariate-coupled amplification photoacoustic cell (MVCA-PAC) with a total length of 100 mm.
• Utilized acoustic pressure distribution simulations to optimize the MVCA-PAC design for enhanced acoustic pressure.
• Incorporated 22 reflections within the MVCA-PAC to maximize the absorption optical path and photoacoustic signal amplitude.
• Applied the Chebyshev rational fractional-order filtering (CRFOF) algorithm for advanced signal processing.
• Conducted 48-hour continuous monitoring of atmospheric CH4 to validate sensor performance.

Main Results:

• The MVCA-PAC achieved approximately 3.9 times higher acoustic pressure than conventional cells at resonance.
• The MVCA-PAC design resulted in a 2-fold increase in photoacoustic signal amplitude and a 4.5-fold increase in 2-f signal intensity compared to traditional cells.
• Achieved a detection limit of 0.572 ppm for CH4 with Allan variance analysis.
• The CRFOF algorithm improved measurement precision by 15.4-fold, reaching 0.578 ppm.
• Demonstrated reliable and feasible continuous atmospheric CH4 monitoring over 48 hours.

Conclusions:

• The developed miniature PAS sensor with MVCA-PAC and CRFOF algorithm offers ultra-sensitive and precise trace CH4 detection.
• The innovative MVCA-PAC design significantly enhances photoacoustic signal generation and sensitivity.
• The CRFOF algorithm effectively improves measurement precision, making the sensor suitable for real-world applications.
• The sensor's reliability and feasibility were validated through continuous atmospheric CH4 monitoring.