A four-channel-based mid-infrared methane sensor system using novel optical/electrical dual-domain self-adaptive denoising algorithm. (February 2022) - Song, Fang; Zheng, Chuantao; Yang, Shuo; Zheng, Kaiyuan; Ye, Weilin; Zhang, Yu; Wang, Yiding; Tittel, Frank K.
Highlights: A novel four-channel-based sensor structure was presented for methane measurement. A LS-FTF denoising algorithm was adopted to suppress the optical and electrical noise. Numerical simulations were carried out and sensor calibration and stability test were performed. The proposed structure shows an enhanced performance for improving sensor sensitivity. Abstract: 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 ∼ 207 parts per million by volume (ppmv) with a ∼ 3 s averaging time was obtained with no filter (NF) structure. Using self-adaptive filtering (SAF), the Allan deviation was decreased 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.