基于扁平锥形腔的带温度补偿的非色散红外 CO2 气体传感器的研制。

Development of a flat conical chamber-based non-dispersive infrared CO2 gas sensor with temperature compensation.

机构信息

Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China.

School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.

出版信息

Rev Sci Instrum. 2023 May 1;94(5). doi: 10.1063/5.0137836.

DOI:10.1063/5.0137836

PMID:37133346

Abstract

In order to accurately monitor CO2 concentration based on the non-dispersive infrared technique, a novel flat conical chamber CO2 gas sensor is proposed and investigated by simulation analysis and experimental verification. First, the optical design software and computational fluid dynamics method are utilized to theoretically investigate the relationship between the energy distribution, absorption efficiency of infrared radiation, and chamber size. The simulation results show that the chamber length has an optimal value of 8 cm when the cone angle is 5° and the diameter of the detection surface is 1 cm, which makes infrared absorption efficiency optimal. Then, the flat conical chamber CO2 gas sensor system is developed, calibrated, and tested. The experimental results indicate that the sensor can accurately detect CO2 gas concentrations in the range of 0-2000 ppm at 25 °C. It is found that the absolute error of calibration is within 10 ppm, and the maximum repeatability and stability errors are 5.5 and 3.5%, respectively. Finally, the genetic neural network algorithm is presented to compensate for the output concentration of the sensor to solve the problem of temperature drift. Experimental results demonstrate that the relative error of the compensated CO2 concentration is varied from -0.85 to 2.32%, which is significantly reduced. The study has reference significance for the structural optimization of the infrared CO2 gas sensor and the improvement of the measurement accuracy.

摘要

为了基于非分散红外技术准确监测 CO2 浓度，提出并通过仿真分析和实验验证研究了一种新型的扁平锥形腔 CO2 气体传感器。首先，利用光学设计软件和计算流体动力学方法从理论上研究了能量分布、红外辐射吸收效率与腔室尺寸之间的关系。仿真结果表明，当锥角为 5°且检测面直径为 1cm 时，腔室长度存在 8cm 的最佳值，这使得红外吸收效率达到最佳。然后，开发、校准和平稳性测试了扁平锥形腔 CO2 气体传感器系统。实验结果表明，该传感器可以在 25°C 下准确检测 0-2000ppm 范围内的 CO2 气体浓度。结果发现，校准的绝对误差在 10ppm 以内，最大重复性和稳定性误差分别为 5.5%和 3.5%。最后，提出了遗传神经网络算法来补偿传感器的输出浓度，以解决温度漂移问题。实验结果表明，补偿后的 CO2 浓度的相对误差变化范围为-0.85%至 2.32%，显著降低。该研究对红外 CO2 气体传感器的结构优化和测量精度的提高具有参考意义。