Study on CO concentration measurement of TDLAS based on baseline nonlinear improvement

CO is one of the main air pollution gases. The monitoring of CO concentration is very important for air pollution control. At present, TDLAS has been widely used in air environment monitoring. However, in the measurement process, the baseline fitting error will lead to a large error in CO concentration measurement. Therefore, this paper proposes to adjust the input signal of the signal generator iteratively and modify the baseline nonlinearity to improve the baseline fitting error, so as to effectively reduce the CO concentration measurement error. First of all, by comparing the real baseline with the polynomial fitting baseline of different orders, the polynomial fitting error is 33% ~ 56%, which proves that the non-linearity of baseline will lead to large concentration measurement error. Secondly, by modifying the baseline nonlinearity, polynomial fitting is used to measure the baseline concentration, the error is reduced to 6.2%, and the measurement accuracy is improved obviously. This method improves the polynomial fitting baseline error caused by baseline nonlinearity, improves the accuracy of CO concentration measurement, and provides technical support for CO monitoring in air pollution.