Narrow-band multi-component gas analysis based on photothermal spectroscopy and partial least squares regression method

In spectroscopic multi-component gas sensing, the crosstalk in the overlapping region of gas absorption spectra will affect the measurement accuracy. This paper reports a new multi-component gas analyzing method based on partial least squares regression (PLSR), which can retrieve target gas concentration and the composition and concentration of interfering gas from an overlapping narrow-band spectrum. Two overlapping absorption spectra (acetylene and ammonia) around 1530 nm are selected to simulate the absorption crosstalk phenomenon. We built a fiber-optic photothermal interferometry system to verify the method on two-component gases in the overlapping region. The training of the PLSR model was based on 63 sets of photothermal second-harmonic signals, which acquired from the gases composed by 100–700 ppm ammonia and 100–900 ppm acetylene. The prediction error of PLSR model achieved 3.84 % when tested by extra data.