Uncooled Snapshot Infrared Video Spectrometer and Its Data Processing
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摘要:
随着现代社会的工业化进程和快速发展，工业生产中的危险化学气体泄漏严重危及人身财产安全。如何有效检测污染气体的存在并获取气体的浓度和分布等信息，成为气体泄漏检测的重要课题。非制冷快照式红外视频光谱成像仪（Uncooled Snapshot Infrared Video Spectrometer, USIVS）是一种理想的硬件方案，能够直接从图像中感知危险化学气体的存在并获取危险化学气体的位置，为紧急处置提供有力支持。但是，商业化的轻量级被动式红外光谱成像仪的灵敏度和光谱分辨率相对受限，已有的气体浓度反演方法难以准确检测污染气体的存在。本文介绍了一种基于非制冷快照式红外视频光谱成像仪及其适用的数据处理技术流程。利用气体浓度反演方法对不同温度和光程长度下的气体进行了模拟实验，并得到了较为准确的反演结果，平均误差分别为2.88%和0.61%。在实验室和室外场景下进行了气体浓度反演方法的测量实验，结果表明该算法具有较好的稳定性，平均误差分别为6.18%和7.47%。通过USIVS与数据处理技术流程的有效结合，能够快速准确地检测污染气体的存在并给出图像中每个像素的气体浓度，实现气云浓度反演的效果，为后续该类技术的商业化及实用化提供了参考。
Abstract:Owing to industrialization and the rapid development of modern society, the leakage of dangerous chemical gases in industrial production seriously endangers the safety of human life and property. Effectively detecting the presence of contaminated gas and obtaining information on the gas concentration and distribution have become important topics in gas leakage detection. Uncooled Snapshot Infrared Video Spectrometer (USIVS) is an ideal hardware scheme that can directly perceive the existence of dangerous chemical gas from the image and obtain the position of dangerous chemical gas to provide strong support for emergency responses. However, the sensitivity and spectral resolution of commercial lightweight passive infrared spectral imagers are relatively limited, and it is difficult to accurately detect the presence of polluted gases using existing inversion methods. In this study, an infrared video spectral imager is introduced based on an uncooled snapshot and its applicable data-processing technology. The gas concentration inversion method is used to simulate gas at different temperatures and optical path lengths, and the inversion results are relatively accurate, with average errors of 2.88% and 0.61%, respectively. The gas concentration inversion method is tested in laboratory and outdoor settings. The results show that the algorithm has good stability with average errors of 6.18% and 7.47%. The effective combination of USIVS and data processing technology can quickly and accurately detect the presence of polluted gas and provide the gas concentration of each pixel in the image. This in turn can realize gas cloud concentration inversion, providing a reference for the commercialization and practical application of this technology in the future.
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低照度成像技术是解决低光照（具体指0.1 lux以下）环境获取视频图像的技术。按照是否包含真空系统，低照度成像器件主要分为三类：第一类是利用外光电效应的真空光电子成像器件，比如基于多碱材料体系的超二代微光像增强器、基于GaAs材料体系的三代微光像增强器；第二类是利用内光电效应的固体成像器件，比如基于硅材料体系的电子倍增CCD（EMCCD）/CMOS（EMCMOS）和低照度CMOS成像器件、基于Ⅲ-Ⅴ族InP/InGaAs材料体系的短波红外InGaAs探测器等；第三类是结合真空和固体器件优势的混合型成像器件，如电子轰击CCD（EBCCD）、电子轰击有源像素CMOS器件的EBAPS。为促进我国低照度成像技术尤其是新一代昼夜通用高灵敏度图像传感器EBAPS的发展，2024年10期，《红外技术》推出了“低照度成像技术”专栏，共收录6篇学术论文，其中2篇文章以EBAPS为主题，1篇综述了EBAPS的研究进展，另1篇提出连通域检测算法筛选高亮噪点区域和异常像素点自适应中值替代的离散系数测试方法并研制了EBAPS闪烁噪声系统；与此形成对照的是1篇微光像增强器的闪烁噪声测试方法，结合了离散系数与Harris角点检测；1篇片上集成偏振单元的EMCCD器件，还有2篇聚焦于低照度图像处理方法。专栏旨在为我国相关科研人员和广大读者提供学术参考，为低照度成像技术的创新发展提供一些新思路和新手段。
最后，感谢各位审稿专家和编辑的辛勤工作。
——王岭雪 -
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图 1 非制冷快照式红外视频光谱成像仪实物图(a)和内部示意图(b)
Figure 1. Uncooled snapshot infrared video spectral imager physical photo(a) and interior diagram (b)
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图 2 气体浓度反演方法数据处理流程
Figure 2. Data processing flow chart of gas concentration inversion method
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图 5 非制冷快照式红外视频光谱成像仪气体探测全链路响应模型
Figure 5. Full-link response model of gas detection in uncooled snapshot infrared video spectrometer
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图 9 九通道30000 ppm SF6气体成像效果图（室外天空背景）
Figure 9. Imaging effect of nine channel 30000 ppm sulfur hexafluoride gas (outdoor sky background)
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图 10 30000 ppm SF6气体轮廓图(a)和气体浓度伪彩图(b)
Figure 10. Gas profile diagram (a) of 30000 ppm sulfur hexafluoride, pseudo-color diagram (b) of 30000 ppm sulfur hexafluoride gas concentration
表 1 USIVS技术指标
Table 1 Specification of USIVS
Wavelength range/nm Sensitivity NETD/mK Field of view range Frame rate Spatial resolution 7320-8020 0.2169 12.0°×14.6° ≥2 Hz 0.55 mrad 9830-10530 0.3262 9130-9830 0.2015 8350-9050 0.2219 9460-10160 0.3221 8720-9420 0.2397 10200-10900 0.3481 7980-8680 0.2502 7610-8310 0.2438 
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表 2 DN值与辐亮度转换关系式
Table 2 Relationship between DN value and radiance conversion
Number of channels The conversion relationship between DN value and radiance 1 L=1.039e－02*DN－67.8 2 L=6.427e－03*DN－39.14 3 L=7.853e－03*DN－48.38 4 L=8.854e－03*DN－56.1 5 L=9.571e－03*DN－60.51 6 L= 1.059e－02*DN－67.71 7 L= 6.116e－03*DN－37.35 8 L= 8.865e－03*DN－56.45 9 L= 7.813e－03*DN－49.57
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表 3 不同温度下100 ppm SF6气体的浓度反演仿真
Table 3 Inversion simulation of 100 ppm sulfur hexafluoride gas concentration at different temperatures
Gas temperature/℃ Set concentration/ppm Simulated concentration/ppm Relative error/% 15 100 101.40 1.40 20 100 96.21 3.79 25 100 97.05 2.95 30 100 101.58 1.58 35 100 104.70 4.70 Average error 2.88
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表 4 不同光程长度下100 ppm六氟化硫气体的浓度反演仿真
Table 4 Inversion simulation of 100 ppm sulfur hexafluoride gas concentration under different optical path length
Optical path length/cm Set concentration/ppm Simulated concentration/ppm Relative error/% 20 100 100.17 0.17 40 100 100.25 0.25 60 100 100.56 0.56 80 100 99.46 0.54 100 100 101.52 1.52 120 100 100.62 0.62 Average error 0.61
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表 5 气体池浓度反演结果
Table 5 Inversion results of gas pool concentration
True concentration/ppm Invert concentration/ppm Relative error/% 5000 4677 6.46 15000 13802 7.99 25000 26564 6.26 35000 32940 5.89 50000 52155 4.31 Average relative error 6.18
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表 6 外场浓度反演结果
Table 6 Inversion results of outfield concentration
True concentration/ppm Invert concentration/ppm Relative error/% 10000 10590 5.90 20000 17760 11.2 30000 28410 5.30 Average relative error 7.47
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