Optimization of the Monitoring of Coal Spontaneous Combustion Degree Using a Distributed Fiber Optic Temperature Measurement System: Field Application and Evaluation
Abstract
:1. Introduction
2. Detection System
2.1. Technical Principle
2.2. Demodulation Process
2.3. Description of DTSS
2.4. Performance Characteristics
3. Comparative Experiment of Casing on Optical Cable
3.1. Testing Method
3.2. Analysis of Temperature Value Accuracy
3.3. Analysis of the Speed of Temperature Sensing
4. Application
4.1. Field Temperature Measuring Design
4.2. Application Effect
4.3. Evaluation of the Effectiveness of Inhibitors
5. Conclusions
- The internal parallel steel cables and the external protective pipe improved the anti-damage ability of the optical cables. The technology of the protective pipe only increases the time required for detecting the actual temperature and does not affect the accuracy of temperature measurement. The temperature difference before and after use of the protective pipe is only 0.87 °C, 0.67 °C, and 0.24 °C, respectively. So, the protective pipe can be used with confidence.
- The technology of the DTSS could improve early warning ability for preventing the risk of CSC in gob. This technology can detect abnormal temperature conditions in gob in a timely manner. Through the monitoring and evaluation of the DTSS, the average temperature at the same location in the gob after spraying the inhibitor returned from 20.8 °C to 16.27 °C, with a decrease of 21.78%, which means the risk of CSC in the gob was eliminated.
- This study only analyzes the application effect of DTSS technology in coal mine gob, which is not comprehensive enough. So, in the future, to enrich these research findings, comparative research on other measurement methods, such as temperature measurement methods of thermal resistance, will be carried out. In addition, we also hope to use the DTSS for in-depth research in different scenarios.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Danish, E.; Onder, M. Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine. Saf. Health Work. 2020, 11, 322–334. [Google Scholar] [CrossRef] [PubMed]
- Hao, M.; Li, Y.; Song, X.; Kang, J.; Su, H.; Zhou, F. Hazardous areas determination of coal spontaneous combustion in shallow-buried gobs of coal seam group: A physical simulation experimental study. Environ. Earth Sci. 2019, 78, 39. [Google Scholar] [CrossRef]
- Liu, W.; Qin, Y. Multi-physics coupling model of coal spontaneous combustion in longwall gob area based on moving coordinates. Fuel 2017, 188, 553–566. [Google Scholar] [CrossRef]
- Jiang, X.; Yang, S.; Zhou, B.; Lan, L. The auto-oxidation characteristic of coal at different stages of the low-temperature oxidation process. Fuel 2023, 352, 129130. [Google Scholar] [CrossRef]
- Liu, W.; Zhang, F.; Gao, T.; Chu, X.; Qin, Y. Efficient prevention of coal spontaneous combustion using cooling nitrogen injection in a longwall gob: An application case. Energy 2023, 281, 128214. [Google Scholar] [CrossRef]
- Qiao, M.; Ren, T.; Roberts, J.; Yang, X.; Li, Z.; Wu, J. Insight into proactive inertisation strategies for spontaneous combustion management during longwall mining of coal seams with various orientations. Energy Sources Part A Recover. Util. Env. Eff. 2023, 45, 2788–2810. [Google Scholar] [CrossRef]
- Saffari, A.; Sereshki, F.; Ataei, M.; Ghanbari, K. Presenting an engineering classification system for coal spontaneous combustion potential. Int. J. Coal Sci. Technol. 2017, 4, 110–128. [Google Scholar] [CrossRef]
- Onifade, M.; Genc, B.; Gbadamosi, A.R.; Morgan, A.; Ngoepe, T. Influence of antioxidants on spontaneous combustion and coal properties. Process Saf. Environ. Prot. 2021, 148, 1019–1032. [Google Scholar] [CrossRef]
- Si, R.; Li, R. Dynamic characteristics of low-concentration oxygen-containing gas explosion and prevention and control key technologies. Coal Sci. Technol. 2020, 48, 17–36. [Google Scholar] [CrossRef]
- Ma, D.; Qin, B.; Gao, Y.; Jiang, J.; Feng, B. An experimental study on the methane migration induced by spontaneous combustion of coal in longwall gobs. Process Saf. Environ. Prot. 2021, 147, 292–299. [Google Scholar] [CrossRef]
- Ranjith, P.G.; Zhao, J.; Ju, M.; De Silva, R.V.S.; Rathnaweera, T.D.; Bandara, A.K.M.S. Opportunities and Challenges in Deep Mining: A Brief Review. Engineering 2017, 3, 546–551. [Google Scholar] [CrossRef]
- Zhang, L.; Wu, W.; Bian, Y.; Yang, M.; Luo, H. Influences of Gas Drainage Pipe Positions on Spontaneous Coal Combustion in the Gob: A Case Study of Baode Coal Mine in China. Combust. Sci. Technol. 2022, 194, 3357–3373. [Google Scholar] [CrossRef]
- Zou, J.; Zhang, R.; Zhou, F.; Zhang, X. Hazardous Area Reconstruction and Law Analysis of Coal Spontaneous Combustion and Gas Coupling Disasters in Goaf Based on DEM-CFD. ACS Omega 2023, 8, 2685–2697. [Google Scholar] [CrossRef]
- Shadab, A.; Ansari, M.T.I.; Raghuwanshi, S.K.; Kumar, S. Smoke Detection Using rGO-Coated eFBG Sensor for Early Warning of Coal Fire in Mines. IEEE Sens. J. 2023, 23, 2153–2160. [Google Scholar] [CrossRef]
- Liu, C.; Zhang, R.; Wang, Z.; Zhang, X. Research on the fire extinguishing performance of new gel foam for preventing and controlling the spontaneous combustion of coal gangue. Environ. Sci. Pollut. Res. 2023, 30, 88548–88562. [Google Scholar] [CrossRef]
- Deng, J.; Zhou, J.; Bai, Z.; Liu, L.; Wang, C. Effect of gas on microstructure and thermal reactivity of coal during low temperature oxidation. Coal Sci. Technol. 2023, 51, 304–312. [Google Scholar] [CrossRef]
- Zhao, X.; Sun, P.; Yang, J.; Zhang, Z.; Zhang, L.; Tang, Y.; Sun, M.; Pang, T.; Liu, X.; Xu, Q. Online monitoring system of index gases concentration applied to coal sponta-neous combustion. Meitan Xuebao/J. China Coal Soc. 2021, 46, 319–327. [Google Scholar] [CrossRef]
- Song, W.X.; Yang, S.Q.; Jiang, C.L.; Niu, J. Experimental research on the formation of CO during coal spontaneous combustion under the condition of methane-contained airflow. J. China Coal Soc. 2012, 37, 1320–1325. [Google Scholar] [CrossRef]
- Cheng, J.; Ma, Y.; Lu, W.; Liu, G.; Cai, F. Using inverting CO critical value to predict coal spontaneous combustion severity in mine gobs with considering air leakages—A case study. Process Saf. Environ. Prot. 2022, 167, 45–55. [Google Scholar] [CrossRef]
- Wang, K.; Li, Y.; Zhang, Y.; Deng, J. An approach for evaluation of grading forecasting index of coal spontaneous combustion by temperature-programmed analysis. Environ. Sci. Pollut. Res. 2023, 30, 3970–3979. [Google Scholar] [CrossRef]
- Tan, B.; Shao, Z.; Guo, Y.; Zhao, T.; Zhu, H.; Li, C. Research on grading and early warning of coal spontaneous combustion based on correlation analysis of index gas. China Saf. Sci. J. 2021, 31, 33–39. [Google Scholar] [CrossRef]
- Deng, J.; Xiao, Y.; Li, Q.; Lu, J.; Wen, H. Experimental studies of spontaneous combustion and anaerobic cooling of coal. Fuel 2015, 157, 261–269. [Google Scholar] [CrossRef]
- Zhang, J. Current Situation and Development Trend of Coal Mine Beam Tube Monitoring System. Saf. Coal Mines 2019, 50, 89–92. [Google Scholar] [CrossRef]
- Kong, D.; Pu, S.; Cheng, Z.; Wu, G.; Liu, Y. Coordinated Deformation Mechanism of the Top Coal and Filling Body of Gob-Side Entry Retaining in a Fully Mechanized Caving Face. Int. J. Geomech. 2021, 21, 04021030. [Google Scholar] [CrossRef]
- Qin, Y.; Yan, L.; Liu, W.; Xu, H.; Song, Y.; Guo, W. Continuous monitoring system of gob temperature and its application. Environ. Sci. Pollut. Res. 2022, 29, 53063–53075. [Google Scholar] [CrossRef]
- Wu, S.; Zhou, B.; Wang, J.; Yang, Q.; Dong, W.; Dong, Z. Isotope radon measurement method to identify spontaneous combustion regions in coal gangue hills: Case study for a coal mine in China. Int. J. Coal Prep. Util. 2023, 1–13. [Google Scholar] [CrossRef]
- Gao, Y.; Hao, M.; Wang, Y.; Dang, L.; Guo, Y. Multi-scale coal fire detection based on an improved active contour model from landsat-8 satellite and UAV images. ISPRS Int. J. Geo-Inf. 2021, 10, 449. [Google Scholar] [CrossRef]
- Li, F.; Li, J.; Liu, X.; Meng, X. Coal fire detection and evolution of trend analysis based on CBERS-04 thermal infrared imagery. Environ. Earth Sci. 2020, 79, 1–15. [Google Scholar] [CrossRef]
- Sun, Y.; Luo, X.; Gao, Y.; Ren, Q.; Wang, P.; He, Y. Application of the radioactive waveperspective technology to goaf detection in the coal mine resource integration. J. Saf. Environ. 2020, 20, 533–547. [Google Scholar] [CrossRef]
- Sun, M.; Tang, Y.; Yang, S.; Li, J.; Sigrist, M.W.; Dong, F. Fire source localization based on distributed temperature sensing by a dual-line optical fiber system. Sensors 2016, 16, 829. [Google Scholar] [CrossRef]
- Su, H.; Ou, B.; Yang, L.; Wen, Z. Distributed optical fiber-based monitoring approach of spatial seepage behavior in dike engineering. Opt. Laser Technol. 2018, 103, 346–353. [Google Scholar] [CrossRef]
- Zhong, X.; Wang, J.; Zhou, K. Monitoring and early warning technology of coal spontaneous combustion in coal mines: Research status and intelligent development trends. Ind. Mine Autom. 2021, 47, 7–17. [Google Scholar] [CrossRef]
- Shan, Y.; Ma, Y.; Fu, H.; Li, W.; Wang, C. Application of distributed optical fiber temperature measurement system in coal mine fire monitoring system. Chin. J. Sens. Actuators 2014, 27, 704–708. [Google Scholar] [CrossRef]
- Hou, G.; Hu, Z.; Li, Z.; Zhao, Q.; Feng, D.; Cheng, C.; Zhou, H. Present situation and prospect of coal mine safety monitoring based on fiber bragg grating and distributed optical fiber sensing technology. J. China Coal Soc. 2023, 48, 96–110. [Google Scholar] [CrossRef]
- Tereshchenko, E.R.; Shishlakov, V.F.; Gubanova, N.A.; Leonteva, A.B.; Manzuk, M.V. Application of Fiber Optic Temperature Sensor in the Development of a Distributed Data Acquisition System. In Proceedings of the 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), St. Petersburg, Russia, 26–29 January 2021; Volume 2021, pp. 1111–1112. [Google Scholar] [CrossRef]
- Du, C.; Hu, T.; Li, Y.; Wang, J. Feasibility study on distributed optical fiber monitoring of coal roadway roof. Min. Saf. Environ. Prot. 2022, 49, 81–88. [Google Scholar] [CrossRef]
- Viveiros, D.; Ribeiro, J.; Ferreira, J.; Pinto, A.M.R.; Perez-Herrera, R.A.; Diaz, S.; Lopez-Gil, A.; Dominguez-Lopez, A.; Esteban, O.; Martins, H.F.; et al. Monitoring of coal waste piles with fiber optic sensing technology. In Proceedings of the 2015 3rd Experiment International Conference (exp. at’15), Ponta Delgada, Portugal, 2–4 June 2015; pp. 147–148. [Google Scholar] [CrossRef]
- Ashry, I.; Mao, Y.; Wang, B.; Hveding, F.; Bukhamsin, A.Y.; Ng, T.K.; Ooi, B.S. A Review of Distributed Fiber-Optic Sensing in the Oil and Gas Industry. J. Light. Technol. 2022, 40, 1407–1431. [Google Scholar] [CrossRef]
- Kus, J. Impact of underground coal fire on coal petrographic properties of high volatile bituminous coals: A case study from coal fire zone No. 3.2 in the Wuda Coalfield, Inner Mongolia Autonomous Region, North China. Int. J. Coal Geol. 2017, 171, 185–211. [Google Scholar] [CrossRef]
- Kus, J. Oxidatively and thermally altered high-volatile bituminous coals in high-temperature coal fire zone No. 8 of the Wuda Coalfield (North China). Int. J. Coal Geol. 2017, 176–177, 8–35. [Google Scholar] [CrossRef]
- Zhu, L.; Gu, W.; Chai, J.; Ma, Z.; Qiu, F. Evolution of mining-induced overburden deformation using distributed optical fiber. J. Min. Strat. Control Eng. 2022, 4, 013014. [Google Scholar] [CrossRef]
- Zhang, Z.; Wang, J.; Yu, X.; Guo, N.; Wu, X.; Feng, H.; Insoo, S.; Sangki, O.; Yohee, K. The Research of Raman Type Distributed Optical Fiber Temperature Measuring Method. J. Optoelectron. 2001, 12, 596–600. [Google Scholar]
- Wen, H.; Wu, K.; Ma, L.; Wang, W.; Wang, T. Application of Distributed Optical Fiber Temperature Measurement System in Monitoring Goaf Coal Spontaneous Combustion. Saf. Coal Mines 2014, 5, 100–105. [Google Scholar] [CrossRef]
- Li, Z.; Li, F.; Wang, K.; Gao, X. Application of Distributed Optical Fiber Temperature Measurement System in Wanglou Coal Mine. Coal Technol. 2020, 39, 156–158. [Google Scholar] [CrossRef]
- Su, H.; Zhou, F.; Song, X.; Qiang, Z. Risk analysis of spontaneous coal combustion in steeply inclined longwall gobs using a scaled-down experimental set-up. Process Saf. Environ. Prot. 2017, 111, 1–12. [Google Scholar] [CrossRef]
- Ning, F.; Zhu, Y.; Cui, H.; Li, X.; Jin, Z. A Linear Correction Algorithm for Improving the Spatial Resolution of Distributed Fiber Optic Temperature Measurement System. Acta Photonica Sin. 2012, 41, 408–413. [Google Scholar] [CrossRef]
Performance Index | Parameters |
---|---|
Supply voltage | AC127V |
Working current | 800 mA |
Number of channels | Four |
Distance for temperature measurement | 4 km for one channel |
Scope of temperature | (0~100) °C |
Spatial resolution | 2 m |
Accuracy of positioning | ≤±0.4 m |
Accuracy of temperature | 1.54 °C |
Response time | 2 s |
Wavelength of the detection light | 1550 nm |
Emission power of the detection light | ≤0 dbm |
Communication interface | RJ45, RS485 |
Type of fiber that can be connected | Multi−mode optical fiber: 62.5/125 μm |
Inside connectors of optical fiber | E2000 |
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Zhang, F.; Han, D.; Qin, Y.; Peng, S.; Zhong, D.; Tang, F.; Xiang, Z.; Xu, H. Optimization of the Monitoring of Coal Spontaneous Combustion Degree Using a Distributed Fiber Optic Temperature Measurement System: Field Application and Evaluation. Fire 2023, 6, 410. https://doi.org/10.3390/fire6110410
Zhang F, Han D, Qin Y, Peng S, Zhong D, Tang F, Xiang Z, Xu H. Optimization of the Monitoring of Coal Spontaneous Combustion Degree Using a Distributed Fiber Optic Temperature Measurement System: Field Application and Evaluation. Fire. 2023; 6(11):410. https://doi.org/10.3390/fire6110410
Chicago/Turabian StyleZhang, Fengjie, Dongyang Han, Yueping Qin, Shiyang Peng, Dawei Zhong, Fei Tang, Zhencai Xiang, and Hao Xu. 2023. "Optimization of the Monitoring of Coal Spontaneous Combustion Degree Using a Distributed Fiber Optic Temperature Measurement System: Field Application and Evaluation" Fire 6, no. 11: 410. https://doi.org/10.3390/fire6110410
APA StyleZhang, F., Han, D., Qin, Y., Peng, S., Zhong, D., Tang, F., Xiang, Z., & Xu, H. (2023). Optimization of the Monitoring of Coal Spontaneous Combustion Degree Using a Distributed Fiber Optic Temperature Measurement System: Field Application and Evaluation. Fire, 6(11), 410. https://doi.org/10.3390/fire6110410