Key Laboratory for Information Science of Electromagnetic Waves (MoE), Fudan University, Shanghai 200433, China.
Zhongshan-Fudan Joint Innovation Center, Zhongshan 528437, China.
Sensors (Basel). 2023 Jan 27;23(3):1413. 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. CH, CH, and CO gases were detected by the system. The concentration of CO could be detected directly, and the concentrations of CH and CH were detected using a PCA-BP neural network algorithm because of the interference of CH and CH. The detection limits were achieved to be 2.59 ppm, 926 ppb, and 114 ppb for CH, CH, and CO with an averaging time of 429 s, 462 s, and 297 s, respectively. The root mean square error of prediction (RMSEP) of CH and CH 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.
基于非分散红外（NDIR）方法的检测原理，开发了一种多气体传感系统，该系统采用宽谱光源、可调谐法布里-珀罗（FP）滤波器探测器和灵活的低损耗红外波导作为吸收池。该系统可以检测 CH、CH 和 CO 气体。由于 CH 和 CH 的干扰，系统采用 PCA-BP 神经网络算法来检测 CO 的浓度，以及 CH 和 CH 的浓度。对于 CH、CH 和 CO，平均时间分别为 429 s、462 s 和 297 s 时，检测限分别达到 2.59 ppm、926 ppb 和 114 ppb。CH 和 CH 的预测均方根误差（RMSEP）分别为 10.97 ppm 和 2.00 ppm。所提出的系统和方法充分利用了中红外宽带光源的多组分气体测量能力，在性能和系统成本之间取得了折衷。
