Research on the Inversion Algorithm of Carbon Dioxide Detection By the Non-Dispersive Infrared Technology

Abstract

Carbon dioxide (CO2) of the automobile exhausts is not only direct atmospheric contaminants, but also contributes to the formation of the greenhouse effect and frequent natural disasters, directly threatening human health and the ecological environment. This work is focused on the monitoring of CO2 by non-dispersive infrared (NDIR) technology. The NDIR instrument is non-poisonous, robust and durable. It has the characteristics of long life, easy maintenance and operation. Accurate measurement of CO2 concentration is very important for monitoring the quality of automobile exhausts. The absorption line of CO2, centered at 4.26μm has been selected due to the very strong absorption peak. The inversion algorithm of CO2 detection is researched in the wide dynamic range of 0-20% for CO2 on NDIR. According to the Beer-Lambert law, the calibration curve are obtained. The least squares method is used to respectively fit the logarithmic function, exponential function, polynomial, etc. to establish three inversion models. After analyzing and verifying these three models, the measurement error is less than 7% in the range of 0-20% for CO2 on NDIR. The results of the experiment shows that three inversion models are effective. They not only overcomes the shortcomings of the detection sensitivity and wide dynamic measurement range on NDIR technology, but also have a good measurement linearity for CO2 detection. They provide a necessary precondition for the interference correction of gas analysis. In addition, this method also provides a solution for the measurement of other gases (such as SO2 and NO2) with high precision and wide dynamic range.