High-precision methane isotopic abundance analysis using near-infrared absorption spectroscopy at 100 Torr
Zhiwei Liu, Chuantao Zheng, Tianyu Zhang, Yù Zhang, Yiding Wang, Frank K. Tittel
Abstract
profile caused by superimposition of multiple lines, two statistical analysis algorithms including linear regression and neural network prediction were respectively employed on the retrieval of molecule fractions instead of the traditionally used standard absorption line fitting method. Performance assessment and a comparison between the two methods were carried out. Compared with the concentration deducing method based on the maximum absorbance in rough data, the linear regression and the neural network prediction obtained a sensitivity enhancement by ∼2 times and ∼10 times, respectively. A simultaneous measurement of pressure and concentration was performed using the neural network, which indicated a good potential of the technique for multi-parameter analysis using a single LAS-based sensor system.