Skip to main content
SpringerLink
Log in

Application of a novel detection approach based on non-dispersive infrared theory to the in-situ analysis on indicator gases from underground coal fire

非分散红外光谱分析技术在煤矿火灾气体在线检测中的应用

  • Published:
Journal of Central South University Aims and scope Submit manuscript

Abstract

Coal mine fires, which can cause heavy casualties, environmental damages and a waste of coal resources, have become a worldwide problem. Aiming at overcoming the drawbacks, such as a low analysis efficiency, poor stability and large monitoring error, of the existing underground coal fire monitoring technology, a novel monitoring system based on non-dispersive infrared (NDIR) spectroscopy is developed. In this study, first, the measurement principle of NDIR sensor, the gas concentration calculation and its temperature compensation algorithms were expounded. Next, taking CO and CH4 as examples, the liner correlation coefficients of absorbance and the temperature correction factors of the two indicator gases were calculated, and then the errors of concentration measurement for CO, CO2, CH4 and C2H4 were further analyzed. The results disclose that the designed NDIR sensors can satisfy the requirements of industrial standards for monitoring the indicator gases for coal fire hazards. For the established NDIR-based monitoring system, the NDIR-based spectrum analyzer and its auxiliary equipment boast intrinsically safe and explosion-proof performances and can achieve real-time and in-situ detection of indicator gases when installed close to the coal fire risk area underground. Furthermore, a field application of the NDIR-based monitoring system in a coal mine shows that the NDIR-based spectrum analyzer has a permissible difference from the chromatography in measuring the concentrations of various indicator gases. Besides, the advantages of high accuracy, quick analysis and excellent security of the NDIR-based monitoring system have promoted its application in many coal mines.

摘要

煤矿井下火灾气体的实时监测对于实现采空区自燃危险性辨识，防范重特大热动力灾害发生，保障煤矿安全生产至关重要。为解决现有非防爆型异地检测技术气体分析速度慢、系统误差大、无法实现原位在线监测的缺陷，在此提出基于非分光红外光谱(NDIR)技术的气体传感器浓度计算方法，推导了温度补偿后的NDIR 传感器气体浓度计算公式；随后，以CO 和CH4为例计算了吸光度线性系数和温度修正系数，并进一步对比测试了CO、CO 2 、CH 4 和C 2 H 4 的计算精度和稳定性，结果表明基本误差和定量重复性均优于煤炭行业标准要求。基于NDIR 技术设计了具有本质安全和防爆性能的监测主机、配套子系统及软件平台，以实现煤矿井下气体的就地采集、有源预处理、原位在线分析。现场应用表明：大南湖一矿NDIR 气体在线监测与地面色谱分析的4 种气体浓度偏差均在标准允许范围内。基于NDIR 的气体监测系统具有精度高、分析速度快、安全性好等优点，已经在全国40 余对矿井推广应用，为评价煤矿井下热动力灾害的发生发展状态、提升防灾减灾救灾能力提供了科学依据。

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Reference

  1. LIANG Yun-tao, HOU Xian-jun, LUO Hai-zhu, et al. Development countermeasures and current situation of coal mine fire prevention & extinguishing in China [J]. Coal Science and Technology, 2016, 44(6): 1–6, 13. DOI: https://doi.org/10.13199/j.cnki.cst.2016.06.001. (in Chinese)

    Google Scholar 

  2. WANG De-ming. Thermodynamic disaster in coal mine and its characteristics [J]. Journal of China Coal Society, 2018(1): 137–142. (in Chinese)

  3. LI Min, WANG He-tang, WANG De-ming, et al. Risk assessment of gas explosion in coal mines based on fuzzy AHP and Bayesian network [J]. Process Safety and Environmental Protection, 2020, 135: 207–218. DOI: https://doi.org/10.1016/j.psep.2020.01.003.

    Article  Google Scholar 

  4. LIANG Yun-tao, ZHANG Jian, REN Ting, et al. Application of ventilation simulation to spontaneous combustion control in underground coal mine: A case study from Bulianta colliery [J]. International Journal of Mining Science and Technology, 2018, 28(2): 231–242. DOI: https://doi.org/10.1016/j.ijmst.2017.12.005

    Article  Google Scholar 

  5. LIANG Yun-tao, TIAN Fu-chao, GUO Bao-long, et al. Experimental investigation on microstructure evolution and spontaneous combustion properties of aerobic heated coal [J]. Fuel, 2021, 306: 121766. DOI: https://doi.org/10.1016/j.fuel.2021.121766.

    Article  Google Scholar 

  6. LIANG Yun-tao, TIAN Fu-chao, LUO Hai-zhu, et al. Characteristics of coal re-oxidation based on microstructural and spectral observation [J]. International Journal of Mining Science and Technology, 2015, 25(5): 749–754. DOI: https://doi.org/10.1016/j.ijmst.2015.07.008.

    Article  Google Scholar 

  7. ZHAO Yong-le, LI Guo-qiang, LI Tao, et al. Performance and mechanism of solid waste coking sulfur paste modified asphalt mixture before and after curing [J]. Journal of Central South University, 2021, 28(7): 2179–2192. DOI: https://doi.org/10.1007/s11771-021-4761-3.

    Article  Google Scholar 

  8. ZHANG Jian, ZHANG Hong-tu, REN Ting, et al. Proactive inertisation in longwall goaf for coal spontaneous combustion control—A CFD approach [J]. Safety Science, 2019, 113: 445–460. DOI: https://doi.org/10.1016/j.ssci.2018.12.023.

    Article  Google Scholar 

  9. BRODNY J, TUTAK M. Determination of the zone with a particularly high risk of endogenous fires in the goaves of a longwall with caving [J]. Journal of Applied Fluid Mechanics, 2018, 11(3): 545–553. DOI: https://doi.org/10.29252/jafm.11.03.27240.

    Article  Google Scholar 

  10. QIN Bo-tao, ZHONG Xiao-xin, WANG De-ming, et al. Research progress of coal spontaneous combustion process characteristics and prevention technology [J]. Coal Science and Technology, 2021, 49(1): 66–99. DOI: https://doi.org/10.13199/j.cnki.cst.2021.01.005. (in Chinese)

    Google Scholar 

  11. LIANG Yun-tao, TIAN Fu-chao, FENG Wen-bin, et al. Research progress of coal mine gas detection technology in China [J]. Journal of China Coal Society, 2021, 46(6): 1701–1714. DOI: https://doi.org/10.13225/j.cnki.jccs.HZ21.0456. (in Chinese)

    Google Scholar 

  12. LIANG Yun-tao, CHEN Cheng-feng, TIAN Fu-chao, et al. Methane gas detection technology and its application in coal mines [J]. Coal Science and Technology, 2021, 49(4): 40–48. DOI: https://doi.org/10.13199/j.cnki.cst.2021.04.005. (in Chinese)

    Google Scholar 

  13. WANG De-ming, SHAO Zhen-lu, ZHU Yun-fei. Several scientific issues on major thermodynamic disasters in coal mines [J]. Journal of China Coal Society, 2021, 46(1): 57–64. DOI: https://doi.org/10.13225/j.cnki.jccs.YG20.1798. (in Chinese)

    Google Scholar 

  14. GB/T 20104—2006. Method for identifying tendency of coal to spontaneous combustion by oxygen absorption with chromatograph [S]. (in Chinese)

  15. WANG Ying, SCHAFFERS W C, TAN Shuai, et al. Low temperature heating and oxidation to prevent spontaneous combustion using Powder River Basin coal [J]. Fuel Processing Technology, 2020, 199: 106221. DOI: https://doi.org/10.1016/j.fuproc.2019.106221.

    Article  Google Scholar 

  16. DU Jing-yi, YIN Cong, WANG Wei-feng, et al. Detection system of trace CO based on TDLAS and temperature and pressure compensation [J]. Optical Technique, 2018, 44(1): 19–24. DOI: https://doi.org/10.13741/j.cnki.11-1879/o4.2018.01.004. (in Chinese)

    Google Scholar 

  17. PAN Wei-dong, ZHANG Jia-wei, DAI Jing-ming, et al. Tunable diode laser absorption spectroscopy system for trace ethylene detection [J]. Spectroscopy and Spectral Analysis, 2012, 32(10): 2875–2878. DOI: https://doi.org/10.3964/j.issn.1000-0593(2012)10-2875-04. (in Chinese)

    Google Scholar 

  18. LIU Yang, WU Jia-nan, CHEN Mei-mei, et al. The trace methane sensor based on TDLAS-WMS [J]. Spectroscopy and Spectral Analysis, 2016, 36(1):279–282. DOI: https://doi.org/10.3964/j.issn.1000-0593(2016)01-0279-04. (in Chinese)

    Google Scholar 

  19. SHAO Xin, TANG Hai-mei, WANG Feng, et al. Research on closed indoor oxygen concentration of quasi-continuous Laser modulation absorption spectroscopy [J]. Spectroscopy and Spectral Analysis, 2018, 38(12): 3713–3717. DOI: https://doi.org/10.3964/j.issn.1000-0593(2018)12-3713-05. (in Chinese)

    Google Scholar 

  20. WEI Yu-bin, CHANG Jun, LIAN Jie, et al. A coal mine multi-point fiber ethylene gas concentration sensor [J]. Photonic Sensors, 2015, 5(1): 67–71. DOI: https://doi.org/10.1007/s13320-014-0206-z.

    Article  Google Scholar 

  21. ZHAO Xiao-hu, SUN Peng-shuai, YANG Juan, et al. Online monitoring system of index gases concentration applied to coal spontaneous combustion [J]. Journal of China Coal Society, 2021. DOI: https://doi.org/10.13225/j.cnki.jccs.2020.1368. (in Chinese)

  22. LIANG Yun-tao, TANG Xiao-jun, ZHANG Xu-liang, et al. Portable gas analyzer based on Fourier transform infrared spectrometer for patrolling and examining gas exhaust [J]. Journal of Spectroscopy, 2015, 2015: 136516. DOI: https://doi.org/10.1155/2015/136516.

    Article  Google Scholar 

  23. LIANG Yun-tao, SUN Yong, LUO Hai-zhu, et al. Spectral analysis of alkane gases of coal spontaneous combustion with a small quantity sample [J]. Journal of China Coal Society, 2015, 40(2): 371–376. DOI: https://doi.org/10.13225/j.cnki.jccs.2014.0765. (in Chinese)

    Google Scholar 

  24. ZHAO Jian-hua, GAO Ming-liang, WU Xiu-juan. Study on the quantitative analysis of common fire toxic gases by PLS-BP model [J]. Fire Safety Science, 2010, 19(3): 158–164. DOI: https://doi.org/10.1631/jzus.B1000005.

    Google Scholar 

  25. TIAN Fu-chao. The real-time analysis of infrared spectrum for fire gas in coal mine goaf [D]. Xuzhou: China University of Mining and Technology, 2019. (in Chinese)

    Google Scholar 

  26. WU Long, XING Li-kong. Study on quantitative measurement method of deleterious gases in underground mine using non-dispersive infrared technology [J]. Journal of safety Science and Technology, 2014, 10(3): 155–159. DOI: https://doi.org/10.11731/j.issn.1673-193x.2014.03.027. (in Chinese)

    Google Scholar 

  27. XU Sheng-you, CHEN Min-you. Design and modeling of non-linear infrared transducer for measuring methane using cross-correlation method [J]. Measurement, 2012, 45(3): 325–332. DOI: https://doi.org/10.1016/j.measurement.2011.11.015.

    Article  Google Scholar 

  28. KIM D H, LEE I, BANG I S, et al. Development of the smallest, high-accuracy NDIR methane sensor module to detect low concentration [J]. Journal of Sensor Science and Technology, 2018, 27(3): 199–203. DOI: https://doi.org/10.5369/JSST.2018.27.3.199.

    Article  Google Scholar 

  29. LIANG Yun-tao, ZHANG Jian, WANG Lian-cong, et al. Forecasting spontaneous combustion of coal in underground coal mines by index gases: A review [J]. Journal of Loss Prevention in the Process Industries, 2019, 57: 208–222. DOI: https://doi.org/10.1016/j.jlp.2018.12.003.

    Article  Google Scholar 

  30. LIU He-huan, SHI Yun-bo, WANG Tian. Design of a six-gas NDIR gas sensor using an integrated optical gas chamber [J]. Optics Express, 2020, 28(8): 11451–11462. DOI: https://doi.org/10.1364/OE.388713

    Article  Google Scholar 

  31. Parkhangil, YI Seung-hwan. Analysis of output voltage properties of non-dispersive infrared gas sensors according to ambient temperatures [J]. Journal of Sensor Science and Technology, 2018, 27(5): 294–299. DOI: https://doi.org/10.5369/JSST.2018.27.5.294.

    Google Scholar 

  32. YUAN Wei, LU Song, GUAN Yu, et al. Open-path Halon 1301 NDIR sensor with temperature compensation [J]. Infrared Physics & Technology, 2019, 97: 129–134. DOI: https://doi.org/10.1016/j.infrared.2018.12.038.

    Article  Google Scholar 

  33. LIANG Yun-tao, TANG Xiao-jun, LUO Hai-zhu, et al. Quantitative spectrum analysis of characteristic gases of spontaneous combustion coal [J]. Spectroscopy and Spectral Analysis, 2011, 31(9): 2480–2484.

    Google Scholar 

  34. DONG Hao-zhe, GOPINATH A. AlGaAs/GaAs active optical switch matrices [C]// 52nd Annual Device Research Conference. Boulder, CO, USA: IEEE, 1994: 17–18. DOI: https://doi.org/10.1109/DRC.1994.1009397.

    Google Scholar 

  35. DE BIASIO M, LEITNER R, KRALL C, et al. Ethylene gas sensing using non-dispersive infrared spectroscopy [C]//2016 IEEE Sensors. Orlando, FL, USA: IEEE, 2016: 1–3. DOI: https://doi.org/10.1109/ICSENS.2016.7808682.

    Google Scholar 

  36. CALAZA C, MECA E, MARCO S, et al. Assessment of the final metrological characteristics of a MOEMS-based NDIR spectrometer through system modeling and data processing [J]. IEEE Sensors Journal, 2003, 3(5): 587–594. DOI: https://doi.org/10.1109/JSEN.2003.817672.

    Article  Google Scholar 

  37. MT/T757 — 2019. General technical conditions of the tube bundle monitoring system for coal mine spontaneous combustion [S]. (in Chinese)

Download references

Author information

Authors and Affiliations

  1. College of Emergency Management and Safety Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China

    Fu-chao Tian  (田富超), Yun-tao Liang  (梁运涛), Hong-qing Zhu  (朱红青) & Jin-cheng Wang  (王金成)

  2. State Key Laboratory of Coal Mine Safety Technology, China Coal Technology & Engineering Group Shenyang Research Institute, Shenyang, 113122, China

    Fu-chao Tian  (田富超), Yun-tao Liang  (梁运涛), Ming-yi Chen  (陈明义) & Jin-cheng Wang  (王金成)

  3. Key Laboratory of Gas and Fire Control for Coal Mines (China University of Mining and Technology), Ministry of Education, Xuzhou, 221116, China

    Fu-chao Tian  (田富超) & Yun-tao Liang  (梁运涛)

  4. Key Laboratory of Roads and Railway Engineering Safety Control (Shijiazhuang Tiedao University), Ministry of Education, Shijiazhuang, 050043, China

    Ming-yi Chen  (陈明义)

Authors
  1. Fu-chao Tian  (田富超)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yun-tao Liang  (梁运涛)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hong-qing Zhu  (朱红青)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ming-yi Chen  (陈明义)
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jin-cheng Wang  (王金成)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Fu-chao Tian  (田富超) or Yun-tao Liang  (梁运涛).

Additional information

Foundation item

Project(2021MD703848) supported by the China Postdoctoral Science Foundation; Projects(52174229, 52174230) supported by the National Natural Science Foundation of China; Project(2021-KF-23-04) supported by the Natural Science Foundation of Liaoning Province, China; Project(2020CXNL10) supported by the Fundamental Research Funds for the Central Universities, China

Contributors

TIAN Fu-chao provided the concept and edited the draft of manuscript. LIANG Yun-tao conducted the literature review and wrote the first draft of the manuscript. ZHU Hong-qing and CHEN Ming-yi analyzed the supervision data. WANG Jin-cheng edited the draft of manuscript. All authors replied to reviewers’ comments and revised the final version.

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tian, Fc., Liang, Yt., Zhu, Hq. et al. Application of a novel detection approach based on non-dispersive infrared theory to the in-situ analysis on indicator gases from underground coal fire. J. Cent. South Univ. 29, 1840–1855 (2022). https://doi.org/10.1007/s11771-022-5006-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11771-022-5006-9

Key words

关键词

Search

Navigation