A sensitive synchronous detection method for multi-gas using the multiple linear regression analysis

Tunable diode laser absorption spectroscopy (TDLAS) technique has been widely investigated for gas concentration measurement in both industry and laboratory. In order to detect different gases within the multi-gas mixture based on TDLAS, different types of schemes have been developed, such as wavelength division multiplexing, time division multiplexing and so on. However, there are many drawbacks of the above methods, such as the slope of normalized baseline restricted the sensitivity and accuracy, the effect of cross-talking interferences becomes a technical bottleneck for multi-gas detection. Therefore, a high sensitive synchronous detection technology for multi-gas detection using the multiple linear regression analysis method is reported. The wavenumber of 4291cm^-1 has been selected to detect CO and CH₄. Several characteristic points are selected to establish multiple linear regression equations, then the concentrations of CH₄ and CO can be calculated, and the baseline can also be obtained simultaneously. The Allan variance results indicate that the optimal integration time has been improved to ~60s, the minimum measurement precision of CH₄ and CO is ~0.58% and ~0.41×10^-6 respectively. Meanwhile, the detection cost and response time can be reduced obviously