Near-Infrared Off-Axis Cavity-Enhanced Optical Frequency Comb Spectroscopy for CO₂/CO Dual-Gas Detection Assisted by...

Area of Science:

• Spectroscopy
• Optical Sensing
• Gas Analysis

Background:

• Cavity-enhanced direct frequency comb spectroscopy (CE-DFCS) offers high sensitivity for gas detection.
• On-axis coupling in CE-DFCS is limited by cavity-mode noise, requiring complex external devices.
• This complexity hinders the development of stable and field-deployable gas sensing systems.

Purpose of the Study:

• To propose and validate an off-axis cavity-enhanced optical frequency comb spectroscopy technique.
• To improve the accuracy and stability of gas sensing by suppressing cavity-mode noise.
• To develop an intelligent sensor system for simultaneous detection of multiple gases like CO and CO2.

Main Methods:

• Implemented an off-axis coupling scheme using an erbium-doped fiber frequency comb and a resonant cavity.
• Excited high-order modes to effectively suppress cavity-mode noise.
• Utilized machine learning models, including Particle Swarm Optimization Support Vector Machine (PSO-SVM), for gas concentration inversion.

Main Results:

• The off-axis technique successfully suppressed cavity-mode noise.
• The PSO-SVM model demonstrated the highest predictive accuracy for single- and dual-gas concentrations.
• Achieved a detection limit of 8.247 ppmv for CO and simultaneous detection limits of 13.196 ppmv for CO2 and 4.658 ppmv for CO.

Conclusions:

• Off-axis CE-DFCS offers a simplified and more stable approach to gas sensing.
• The developed technique shows potential for field-deployable, intelligent sensors capable of multi-gas detection.
• Machine learning integration enhances the performance of optical gas sensing systems.