|
|
|
|
|
|
| Study on Spectral Radiation Characteristics of Carbon Disulfide Flame Based on Infrared Spectroscopy |
| NING Jia-lian1, TANG Jin1, HU Tian-you1, LIU Qiang2, WANG Hao-wen1, CHEN Zhi-li1* |
1. College of Environmental Science and Engineering，Guilin University of Technology，Guilin 541004，China
2. Research Institute of Chemical Defense, Beijing 102205, China |
|
|
|
|
Abstract In recent years, the demand for carbon disulfide in the chemical industry is increasing, and carbon disulfide is flammable and explosive. In the production process, fire accidents of carbon disulfide are prone to occur, which are extremely harmful and easy to cause economic losses and casualties. In the study of fire accident hazard, the flame spectrum research is very necessary. Because the flame spectrum contains much information, including flame temperature, combustion components, thermal radiation intensity of each band, etc., it is necessary to conduct an in-depth study of its flame spectral radiation. In this paper, carbon disulfide as the research object, and the flame spectrum test platform was built based on infrared spectroscopy. The test platform was mainly composed of VSR infrared spectrometer, telescopic device and burner. The carbon disulfide, styrene, acetonitrile and ethyl acetate were tested at 5 cm combustion scale. The combustion flame spectrum of carbon disulfide, styrene, acetonitrile and ethyl acetate fuels in the infrared range of 1～14 μm was tested at 5 cm combustion scale, and the carbon disulfide was mixed with styrene, acetonitrile and ethyl acetate in 1∶1. Flame spectrum, the characteristic band of carbon disulfide flame spectrum was obtained, and the carbon dioxide flame spectrum characteristic database was constructed. In the study of fuel flame spectrum, the carbon dioxide flame is blue when it burns, and does not smoke, it is flame spectrum radiation mainly comes from three kinds of molecular radiations of SO2, CO2 and H2O at high temperature. The characteristic peak of SO2 is 4.05, 7.4 and 8.51 μm, CO2 characteristic peak is 2.7 and 4.3 μm, H2O characteristic peak is 2.5，2.7 and 5.5～7 μm. The spectral characteristics of acetonitrile and ethyl acetate fuel combustion flames are basically similar. The flame spectrum radiation mainly comes from CO2 and H2O molecular radiation at high temperature. In addition to high-temperature gas radiation, styrene flame spectrum radiation has strong carbon black radiation, the carbon black has a center wavelength of 7 μm and a temperature of about 414 K. In addition, styrene fuel has a unique C—H* stretching peak at 3.6 μm compared to the other three chemicals. Compared with the flame spectrum characteristics of styrene, acetonitrile and ethyl acetate, the carbon disulfide flame spectrum has unique characteristic peaks at 4.05, 7.4 and 8.51 μm, which are generated by SO2 molecules. These characteristic peaks can be used as one of the fire bases for space exploration. In the study of fuel mixed combustion flame spectroscopy, when carbon disulfide is mixed with styrene, acetonitrile and ethyl acetate, the combustion flame spectrum characteristics are basically similar. The flame spectrum radiation mainly comes from CO2, H2O and SO2 molecular radiation at high temperature. The experimental results also show that in the mixed combustion, the flame spectral characteristic peak of carbon disulfide is not interfered by the components of other fuels, and the characteristic peak is still obvious. This result can lay a foundation for the research on detecting and identifying carbon disulfide fire using space remote sensing detection technology.
|
|
Received: 2019-04-26
Accepted: 2019-08-15
|
|
|
|
Corresponding Authors:
CHEN Zhi-li
E-mail: 1012262034@qq.com
|
|
[1] Abdollahi M H A. Encyclopedia of Toxicology, 2014, 108(3): 678.
[2] Wang B, Sivret E C, Parcsi G, et al. Talanta, Elsevier, 2015, 137: 71.
[3] Du Z, Li J, Cao X, et al. Sensors and Actuators B: Chemical, Elsevier, 2017, 247: 384.
[4] GUAN Lin-qiang, DENG Hao，YAO Lu, et al(管林强, 邓 昊, 姚 路, 等). Acta Physica Sinica(物理学报), 2019, 68(8)：084204.
[5] Mcguirk C M, Siegelman R L, Drisdell W S, et al. Nature Communications, 2018, 9(1): 5133.
[6] Kilo S, Zonnur N, Uter W, et al. Annals of Work Exposures and Health, 2015, 59(8): 972.
[7] Yan X, Sun Y, Zhu T, et al. Journal of Hazardous Materials, Elsevier, 2013, 261: 669.
[8] Tukhbatullin A A, Sharipov G L, Bagautdinova A R. Journal of Luminescence, North-Holland, 2016, 173: 127.
[9] Sun B, Guo K, Pareek V K. Journal of Loss Prevention in the Process Industries, 2015, 35: 200.
[10] LIU Hong-tao, CHEN Zhi-li, HU Tan-gao, et al（刘洪涛，陈志莉，胡谭高，等）. Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(10): 3442.
[11] Isojärvi T, Bordbar H, Hostikka S, et al. International Journal of Heat and Mass Transfer, Pergamon, 2018, 127: 1101.
[12] Gordon I E, Rothman L S, Hill C, et al. Journal of Quantitative Spectroscopy and Radiative Transfer, 2017. |
| [1] |
CHENG Jia-wei1, 2，LIU Xin-xing1, 2*，ZHANG Juan1, 2. Application of Infrared Spectroscopy in Exploration of Mineral Deposits: A Review[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 15-21. |
| [2] |
LIANG Ya-quan1, PENG Wu-di1, LIU Qi1, LIU Qiang2, CHEN Li1, CHEN Zhi-li1*. Analysis of Acetonitrile Pool Fire Combustion Field and Quantitative
Inversion Study of Its Characteristic Product Concentrations[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3690-3699. |
| [3] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
| [4] |
GUO Ge1, 3, 4, ZHANG Meng-ling3, 4, GONG Zhi-jie3, 4, ZHANG Shi-zhuang3, 4, WANG Xiao-yu2, 5, 6*, ZHOU Zhong-hua1*, YANG Yu2, 5, 6, XIE Guang-hui3, 4. Construction of Biomass Ash Content Model Based on Near-Infrared
Spectroscopy and Complex Sample Set Partitioning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3143-3149. |
| [5] |
ZHANG Mei-zhi1, ZHANG Ning1, 2, QIAO Cong1, XU Huang-rong2, GAO Bo2, MENG Qing-yang2, YU Wei-xing2*. High-Efficient and Accurate Testing of Egg Freshness Based on
IPLS-XGBoost Algorithm and VIS-NIR Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1711-1718. |
| [6] |
WU Mu-lan1, SONG Xiao-xiao1*, CUI Wu-wei1, 2, YIN Jun-yi1. The Identification of Peas (Pisum sativum L.) From Nanyang Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1095-1102. |
| [7] |
SHANG Chao-nan1, XIE Yan-li2, GAO Xiao3, ZHOU Xue-qing2, ZHAO Zhen-dong2, MA Jia-xin1, CUI Peng3, WEI Xiao-xiao3, FENG Yu-hong1, 2*, ZHANG Ming-nan2*. Research on Qualitative and Quantitative Analysis of PE and EVA in Biodegradable Materials by FTIR[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3380-3386. |
| [8] |
HU Yun-you1, 2, XU Liang1*, XU Han-yang1, SHEN Xian-chun1, SUN Yong-feng1, XU Huan-yao1, 2, DENG Ya-song1, 2, LIU Jian-guo1, LIU Wen-qing1. Adaptive Matched Filter Detection for Leakage Gas Based on Multi-Frame Background[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3307-3313. |
| [9] |
LIU Qing-song1, DAN You-quan1, YANG Peng2, XU Luo-peng1, YANG Fu-bin1, DENG Nan1. Simulation of Emission Spectrum of Abyssal Methane Based on
HITRAN Database[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2714-2719. |
| [10] |
GENG Ying-rui1, SHEN Huan-chao1, NI Hong-fei2, CHEN Yong1, LIU Xue-song1*. Support Vector Machine Optimized by Near-Infrared Spectroscopic
Technique Combined With Grey Wolf Optimizer Algorithm to
Realize Rapid Identification of Tobacco Origin[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2830-2835. |
| [11] |
PEI Huan1, CHEN Lei1*, WANG Si-yuan2, YANG Kun1, SONG Peng2. Flame Spectrum and Active Particles Analysis of the Effect of Dielectric Barrier Discharge Induced on Gliding Arc Discharge With the Mixture of Methane-Air-Ar Within A Dual Mode Discharge[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(07): 2007-2012. |
| [12] |
WANG Yue1, 3, 4, CHEN Nan1, 2, 3, 4, WANG Bo-yu1, 5, LIU Tao1, 3, 4*, XIA Yang1, 2, 3, 4*. Fourier Transform Near-Infrared Spectral System Based on Laser-Driven Plasma Light Source[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1666-1673. |
| [13] |
ZHA Ling-ling1, 2, 3, WANG Wei2*, XIE Yu1, SHAN Chang-gong2, ZENG Xiang-yu2, SUN You-wen2, YIN Hao2, HU Qi-hou2. Observation of Variations of Ambient CO2 Using Portable FTIR
Spectrometer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1036-1043. |
| [14] |
PENG Wu-di1, NING Jia-lian2, CHEN Zhi-li1*, TANG Jin1, LIU Li-xi1, CHEN Lin1. Construction of CS2 Combustion Flame Spectral Radiation Model and Inversion of Characteristic Pollution Product Concentration[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 672-677. |
| [15] |
LI Yan-yan1, 2, LUO Hai-jun1, 2*, LUO Xia1, 2, FAN Xin-yan1, 2, QIN Rui1, 2. Detection of Craniocerebral Hematoma by Array Scanning Sensitivity Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 392-398. |
|
|
|
|
