A four-channel-based mid-infrared methane sensor system using novel optical/electrical dual-domain self-adaptive denoising algorithm

By incorporating two wide-band mid-infrared (MIR) incandescence light sources and two dual-channel pyroelectric detectors, a new four-channel-based mid-infrared gas sensor is presented for the measurement of methane (CH4) mole fractions. A least-square fast transverse filtering (LS-FTF) self-adaptive denoising algorithm was proposed to improve the robustness, stability, and noise immunity performance of the sensor. Numerical simulations were carried out to validate the function of the LS-FTF algorithm by introducing interference with different frequencies in the simulation. Sensor calibration and stability test were performed for the self-adaptive sensor using standard or diluted CH4 samples. With the intrinsic noise considered only, an Allan deviation of similar to 207 parts per million by volume (ppmv) with a similar to 3 s averaging time was obtained with no filter (NF) structure. Using selfadaptive filtering (SAF), the Allan deviation was decreased to similar to 162 ppmv with the same averaging time. Noise with different modulation frequencies was imposed on the detection channel to validate the denoising performance of the four-channel structure. The reported four-channel-based sensor using LS-FTF technique shows an enhanced denoising performance as compared to the two or three-channel-based sensor structure.

Automated summary

A new four-channel-based mid-infrared gas sensor using LS-FTF technique has been developed, showing enhanced denoising performance compared to two or three-channel-based sensor structures. Numerical simulations and experimental results demonstrate that the sensor has improved stability and noise immunity with the LS-FTF self-adaptive denoising algorithm.