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Results on Gas Detection and Concentration Estimation Via Mid-IR-Based Gas Detection System Analysis Model

机译:基于基于中红外的气体检测系统分析模型的气体检测和浓度估算结果

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摘要

In recent decades, laser-based spectroscopy has been used in a wide range of research and application fields due to developments in laser technology and infrared spectroscopy. A particular application of interest is mid-infrared (IR) laser-based gas detection systems for health and environment assessment. In this paper, we use our statistical analysis model for a generic mid-IR pulsed-laser gas detection system to predict trace gas detection and concentration estimation performance, and their sensitivity to system parameters. Based on the Pacific Northwest National Laboratory data and the Beer–Lambert law, we use the three main spectral peaks of a trace gas, as the basis for gas detection, and use the relationship between gas transmittance $beta$, molar absorptivity $varepsilon$, concentration $c$, and the sample-mean measurement, $x_{N}$, from the photo-detector, as the basis for concentration estimation using a standard confidence interval method. We also demonstrate the analysis model's adaptability and system performance sensitivity to system parameter values.
机译:近几十年来,由于激光技术和红外光谱学的发展,基于激光的光谱学已被广泛用于研究和应用领域。感兴趣的特定应用是用于健康和环境评估的基于中红外(IR)激光的气体检测系统。在本文中,我们将我们的统计分析模型用于通用的中红外脉冲激光气体检测系统,以预测痕量气体检测和浓度估算性能,以及它们对系统参数的敏感性。根据太平洋西北国家实验室的数据和比尔-兰伯特定律,我们使用痕量气体的三个主要光谱峰作为气体检测的基础,并使用气体透过率$ beta $,摩尔吸收率$ varepsilon $之间的关系,浓度$ c $和来自光电探测器的样品均值测量$ x_ {N} $,作为使用标准置信区间方法进行浓度估算的基础。我们还演示了分析模型对系统参数值的适应性和系统性能敏感性。

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