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Abstrakt

The quick leakage alarm and the accurate concentration prediction are two important aspects of natural gas safety monitoring. In this paper, a rapid monitoring method of sensor data sharing, rapid leakage alarm and simultaneous output of concentrations prediction is proposed to accelerate the alarm speed and predict the possible impact of leakage. In this method, the Dempster-Shafer evidence theory is used to fuse the trend judgment and the CUSUM (cumulative sum) and the Gauss-Newton iteration is used to predict the concentration. The experiment system based on the TGS2611 natural gas sensor was built. The results show that the fusion method is significantly better than the single monitoring method. The alarm time of fusion method was more advanced than that of the CUSUM method and the trend method (being averagely, 10.4% and 7.6% in advance in the CUSUM method and the trend method respectively). The relative deviations of the predicted concentration were the maximum (13.3%) at 2000 ppm (parts per million) and the minimum (0.8%) at 6000 ppm, respectively.
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Bibliografia

[1] P. Lustenberger, F. Schumacher, M. Spada, P. Burgherr, and B. Stojadinovic, ”Assessing the performance of the European natural gas network for selected supply disruption scenarios using open-source information”, Energies 12, 1–28 (2019). https://doi.org/10.3390/en12244685
[2] S. Kakuma, and K. Noda, ”Practical and Sensitive Measurement of Methane Gas Concentration Using a 1.6 μm Vertical–Cavity–Surface– Emitting–Laser Diode”, Sensors and Materials 22 (7), 365–375 (2010).
[3] K. L. Su, Y. L. Liao, S. W. Shiau, and J. H. Guo, ”Bayesian-Estimation– Algorithm-Based Gas Detection Modules”, Sensors and Materials 25 (6), 397–402 (2013).
[4] Y. Xia, J. Wang, L. Xu, X. Li, and S. J. Huang, ”A roomtemperature methane sensor based on Pd-decorated ZnO/rGO hybrids enhanced by visible light photocatalysis”, Sensors and Actuators B:Chemical 304, DOI: 10.1016/j.snb.2019.127334 (2020). https://doi.org/10.1016/j.snb.2019.127334
[5] T. Long, E. Li, L. Yang, J. F. Fan, and Z. Z. Lian, ”Analysis and design of an effective light interference methane sensor based on threedimensional optical path model”, Journal of Sensors Article ID 1342593, 1-11 (2018). https://doi.org/10.1155/2018/1342593
[6] Q. Xiao, J. Li, Z. Bai, J. Sun, N. Zhou, and Z. Zeng, ”A small leak detection method based on VMD adaptive de-noising and ambiguity correlation classification intended for natural gas pipelines”, Sensors 12, 1-16 (2016). https://doi.org/10.3390/s16122116
[7] Z. M. Zhou, J. Zhang, X. S. Huang, and X. S. Guo, ”Experimental study on distributed optical-fiber cable for high-pressure buried natural gas pipeline leakage monitoring”, Optical Fiber Technology 53, Article ID 102028 (2019). https://doi.org/10.1016/j.yofte.2019.102028
[8] T. Jia, T. Guo, X. Wang, D. Zhao, C. Wang, Z. Zhang, S. Lei, W. Liu, H. Liu, and X. Li, ”Mixed Natural Gas Online Recognition Device Based on a Neural Network Algorithm Implemented by an FPGA”, Sensors 19 (9), 1-16 (2019). https://doi.org/10.3390/s19092090
[9] A. X. He, J. Yu, G. F. Wei, Y. Chen, H. Wu, and Z. A. Tang, ”A. Short-time fourier transform and decision tree-based pattern recognition for gas identification using temperature modulated microhotplate gas sensors”, Journal of Sensors Article ID 7603931, 1-12 (2016). https://doi.org/10.1155/2016/7603931
[10] Z. Y. Yang, M. Yin, J. G. Xu, and W. Lin, ”Spatial evolution model of tourist destinations based on complex adaptive system theory: a case study of Southern Anhui, China”, Journal of Geographical Sciences 29 (8), 1411–1434 (2019). https://doi.org/10.1007/s11442-019-1669-z
[11] L. W. Tian, D. J. Moschandreas, J. H. Hao, ”The impact of kitchen activities on indoor pollutant concentrations”, Indoor and Built Environment 17 (4), 377–383 (2008). https://doi.org/10.1177/1420326x08094626
[12] N. Hu, S. D. Liu, Y. Q. Gao, J. P. Xu, X. Zhang, Z. Zhang, and X. H. Lee, ”Large methane emissions from natural gas vehicles in Chinese cities”, Atmospheric Environment 187, 374–380 (2018). https://doi.org/10.1016/j.atmosenv.2018.06.007
[13] Y. Li, C. Hu, C. Huang, and L. Duan, ”The concept of smart tourism in the context of tourism information services”, Tourism Management 58, 293-300 (2016). https://doi.org/10.1016/j.tourman.2016.03.014
[14] P. Zhao, R. Zhuo, S. Li, C. Shu, B. Laiwang, Y. Jia, Y. Shi, and L. Suo, ”Analysis of advancing speed effect in gas safety extraction channels and pressure-relief gas extraction”, Fuel 265, Article ID 116825 (2020). https://doi.org/10.1016/j.fuel.2019.116825
[15] E. R. S. Jaclyn, N. N. A. Franz, C. M. J. Fernando, and M. D. Fabian, ”Developing a chemical and hazardous waste inventory system”, Journal of Chemical Health and Safety 18 (6), 15–18 (2011). https://doi.org/10.1016/j.jchas.2011.05.012
[16] F. Mehraliyev, Y. Choi, and M. A. Koseoglu, ”Progress on smart tourism research”, Journal of Hospitality and Tourism Technology 10, 522-538 (2019). https://doi.org/10.1108/jhtt-08-2018-0076
[17] F. Mehraliyev, I. C. C. Chan, Y. Choi, and M. A. Koseoglu, ”A state-of-the-art review of smart tourism research”, Journal of Travel and Tourism Marketing 37 (1), 78–91 (2020). https://doi.org/10.1080/10548408.2020.1712309
[18] M. Pastell, J. Hietaoja, J. Yun, J. Tiusanen, and A. Valros, ”Predicting farrowing of sows housed in crates and pens using accelerometers and CUSUM charts”, Computers and Electronics in Agriculture 127, 197–203 (2016). https://doi.org/10.1016/j.compag.2016.06.009
[19] S. C. Chapra, ”Applied Numerical Methods with MATLAB for Engineers and Scientists”, McGraw-Hill, New York, 2001.
[20] Q. Liu, Y. Tian, and B. Kang, ”Derive knowledge of Znumber from the perspective of Dempster–Shafer evidence theory”, Applications of Artificial Intelligence 85, 754–764 (2019). https://doi.org/10.1016/j.engappai.2019.08.005
[21] D. Su, Q. Shi, H. Xu, ”Nonintrusive Load Monitoring Based on Complementary Features of Spurious Emissions”, Electronics 8 (9), 1-13 (2019). https://doi.org/10.3390/electronics8091002
[22] Y. S. Chen, ”Research on Self-Validating Methods for Metal Oxide Semiconductor Gas Sensor Arrays”, Doctor’s Thesis, Harbin Institute of Technology, Harbin, China, (2017).
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Autorzy i Afiliacje

Rongli Li
1
Yuexin Fan
2

  1. Faculty of Sanjiang University, Nanjing, China
  2. Faculty of Fujian Normal University, Fuzhou, China

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