CH4, C2H6, and CO2 Multi-Gas Sensing Based on Portable Mid-Infrared Spectroscopy and PCA-BP Algorithm

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 3; p. 1413
• Main Authors: Yang, Yunting, Jiang, Jiachen, Zeng, Jiafu, Chen, Zhangxiong, Zhu, Xiaosong, Shi, Yiwei
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 27.01.2023; MDPI
• Subjects: Algorithms; BP neural network; Carbon dioxide; Flexibility; Gas absorption; Greenhouse gases; Lasers; Light; multi-gas detection; NDIR; Neural networks; PCA; Personal computers; Sensors; Spectrum analysis; China; Germany
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23031413

A multi-gas sensing system was developed based on the detection principle of the non-dispersive infrared (NDIR) method, which used a broad-spectra light source, a tunable Fabry–Pérot (FP) filter detector, and a flexible low-loss infrared waveguide as an absorption cell. CH4, C2H6, and CO2 gases were detected by the system. The concentration of CO2 could be detected directly, and the concentrations of CH4 and C2H6 were detected using a PCA-BP neural network algorithm because of the interference of CH4 and C2H6. The detection limits were achieved to be 2.59 ppm, 926 ppb, and 114 ppb for CH4, C2H6, and CO2 with an averaging time of 429 s, 462 s, and 297 s, respectively. The root mean square error of prediction (RMSEP) of CH4 and C2H6 were 10.97 ppm and 2.00 ppm, respectively. The proposed system and method take full advantage of the multi-component gas measurement capability of the mid-infrared broadband source and achieve a compromise between performance and system cost.