非色散红外气体传感器稳态扩散高斯分布浓度校正方法

流程工业中气体浓度测量至关重要。非色散红外传感器是一种基于不同气体对红外光吸收强度差异性测量气体浓度的传感器，气体浓度测量精度高，广泛用于流程工业中CO₂和N₂O气体浓度测量。非色散红外传感器内气体不均匀扩散使气体浓度测量会产生原理性误差，需要得到气体在传感器气室内达到稳态扩散时间降低浓度测量误差，提高测量精度。本文提出一种非色散红外传感器高斯分布扩散模型预测气体稳态扩散时间计算方法，14组不同条件下CO₂和N₂O的仿真实验得到本文提出高斯扩散模型的拟合度分别为0.82和0.80,验证所提出高斯模型预测气体稳态扩散时间的鲁棒性。本文所提方法非色散红外传感器浓度测量不均匀扩散产生误差补偿提供保障。

Gaussian distribution of stable diffusion for gas concentration correction on infrared dispersive gas sensor

Gas concentration measurement is crucial in the process industry. The measurement principle of non-dispersive infrared (NDIR) sensors is based on the difference in the absorption intensity of infrared light for different gases. It is widely used to measure CO2 and N2O concentrations for reducing the influence of environmental factors. But, the inhomogeneous gas diffusion in NDIR sensor chamber generates principle errors. It is necessary to determine the accurate time when CO2 and N2O reach stable diffusion within the gas chamber to reduce errors and improve the measurement accuracy. In this article, a Gaussian diffusion model is proposed to predict the gas stable diffusion time in the gas chamber of the NDIR sensor to correct gas concentration. The effectiveness of the proposed Gaussian diffusion model is evaluated by the simulation experiment. Fourteen sets of simulations for CO2 and N2O under different conditions show that the fitness of the proposed Gaussian diffusion model is 0. 82 and 0. 80, respectively, which verifies the robustness of the proposed model. The Gaussian diffusion model between gas stable diffusion time and inlet flow velocity provides theoretical support for error correction generated by inhomogeneous gas diffusion which finally improves the measurement accuracy.