Published February 28, 2023 | Version v1
Journal article Open

Revealing the peculiarities of average bicoherence of frequencies in the spectra of dangerous parameters of the gas environment during fire

Creators

  • 1. Scientific-Methodical Center of Educational Institutions in the Sphere of Civil Defence
  • 2. National University of Civil Defence of Ukraine
  • 3. National Aviation University
  • 4. Zhytomyr Medical Institute
  • 5. Melitopol Institute of Ecology and Social Technologies, University of "Ukraine"
  • 6. Bogdan Khmelnitsky Melitopol State Pedagogical University
  • 7. Mykolayiv National Agrarian University

Description

The object of this study is a change in the hazardous parameters of the gas environment when materials are ignited in the premises. The subject is the features of the average bicoherence of the frequencies of the spectra of changes in the hazardous parameters of the gas environment when materials are ignited. The importance of such studies is based on the fact that the examined features can be used for the early detection of fires. The value of the average bicoherence is proposed to be determined for each frequency, taking into account the average value of the cosine argument of the complex bispectrum for a given frequency interval. It was established that the values of the average bicoherence of the spectrum of changes in the temperature of the gaseous medium in the interval of no ignition of the materials, averaged by frequency in the range of 0–2 Hz, lie in the range from ‒0.052 to ‒0.35. At the same time, the frequency-averaged values of mean bicoherence at the ignition interval of materials lie in the range of ‒0.128 to +0.155. Averaged in the frequency range of 0–2 Hz, the value of the mean bicoherence of the spectrum of changes in smoke density in the interval of absence of ignition of materials lies in the range from ‒0.018 to +0.568. In the presence of fires, this value is in the range from –0.244 to +0.23. At the same time, the average value of the average bicoherence of the spectrum of changes in the concentration of carbon monoxide of the gas medium for test materials, averaged in the range from 0 to 2 Hz, ranges from +0.016 to +0.109. In the case of ignition of materials, the average values range from +0.0007 to +0.053, except for ignition of wood (+0.117). In general, the revealed features of the average bicoherence of the frequency components of the spectra of changes in the hazardous parameters of the gas environment indicate the possibility of their use to identify fires and prevent fires

Files

Revealing the peculiarities of average bicoherence of frequencies in the spectra of dangerous parameters of the gas environment during fire.pdf

Files (1.2 MB)

Additional details

References

  • Vambol, S., Vambol, V., Sychikova, Y., Deyneko, N. (2017). Analysis of the ways to provide ecological safety for the products of nanotechnologies throughout their life cycle. Eastern-European Journal of Enterprise Technologies, 1 (10 (85)), 27–36. doi: https://doi.org/10.15587/1729-4061.2017.85847
  • Semko, A., Rusanova, O., Kazak, O., Beskrovnaya, M., Vinogradov, S., Gricina, I. (2015). The use of pulsed high-speed liquid jet for putting out gas blow-out. The International Journal of Multiphysics, 9 (1), 9–20. doi: https://doi.org/10.1260/1750-9548.9.1.9
  • Popov, O., Іatsyshyn, A., Kovach, V., Artemchuk, V., Taraduda, D., Sobyna, V. et al. (2018). Conceptual Approaches for Development of Informational and Analytical Expert System for Assessing the NPP impact on the Environment. Nuclear and Radiation Safety, 3 (79), 56–65. doi: https://doi.org/10.32918/nrs.2018.3(79).09
  • Pospelov, B., Andronov, V., Rybka, E., Popov, V., Semkiv, O. (2018). Development of the method of frequency­temporal representation of fluctuations of gaseous medium parameters at fire. Eastern-European Journal of Enterprise Technologies, 2 (10 (92)), 44–49. doi: https://doi.org/10.15587/1729-4061.2018.125926
  • Dubinin, D., Korytchenko, K., Lisnyak, A., Hrytsyna, I., Trigub, V. (2017). Numerical simulation of the creation of a fire fighting barrier using an explosion of a combustible charge. Eastern-European Journal of Enterprise Technologies, 6 (10 (90)), 11–16. doi: https://doi.org/10.15587/1729-4061.2017.114504
  • Popov, O., Iatsyshyn, A., Kovach, V., Artemchuk, V., Taraduda, D., Sobyna, V. et al. (2019). Physical Features of Pollutants Spread in the Air During the Emergency at NPPs. Nuclear and Radiation Safety, 4 (84), 88–98. doi: https://doi.org/10.32918/nrs.2019.4(84).11
  • Vambol, V., Vambol, S., Kondratenko, O., Koloskov, V., Suchikova, Y. (2018). Substantiation of expedience of application of high-temperature utilization of used tires for liquefied methane production. Journal of Achievements in Materials and Manufacturing Engineering, 87 (2), 77–84. doi: https://doi.org/10.5604/01.3001.0012.2830
  • Dubinin, D., Korytchenko, K., Lisnyak, A., Hrytsyna, I., Trigub, V. (2018). Improving the installation for fire extinguishing with finely­dispersed water. Eastern-European Journal of Enterprise Technologies, 2 (10 (92)), 38–43. doi: https://doi.org/10.15587/1729-4061.2018.127865
  • Otrosh, Y., Rybka, Y., Danilin, O., Zhuravskyi, M. (2019). Assessment of the technical state and the possibility of its control for the further safe operation of building structures of mining facilities. E3S Web of Conferences, 123, 01012. doi: https://doi.org/10.1051/e3sconf/201912301012
  • Ragimov, S., Sobyna, V., Vambol, S., Vambol, V., Feshchenko, A., Zakora, A. et al. (2018). Physical modelling of changes in the energy impact on a worker taking into account high-temperature radiation. Journal of Achievements in Materials and Manufacturing Engineering, 1 (91), 27–33. doi: https://doi.org/10.5604/01.3001.0012.9654
  • Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Maksymenko, N., Meleshchenko, R. et al. (2020). Mathematical model of determining a risk to the human health along with the detection of hazardous states of urban atmosphere pollution based on measuring the current concentrations of pollutants. Eastern-European Journal of Enterprise Technologies, 4 (10 (106)), 37–44. doi: https://doi.org/10.15587/1729-4061.2020.210059
  • Otrosh, Y., Semkiv, O., Rybka, E., Kovalov, A. (2019). About need of calculations for the steel framework building in temperature influences conditions. IOP Conference Series: Materials Science and Engineering, 708 (1), 012065. doi: https://doi.org/10.1088/1757-899x/708/1/012065
  • Vambol, S., Vambol, V., Kondratenko, O., Suchikova, Y., Hurenko, O. (2017). Assessment of improvement of ecological safety of power plants by arranging the system of pollutant neutralization. Eastern-European Journal of Enterprise Technologies, 3 (10 (87)), 63–73. doi: https://doi.org/10.15587/1729-4061.2017.102314
  • Rybalova, O., Artemiev, S., Sarapina, M., Tsymbal, B., Bakharevа, A., Shestopalov, O., Filenko, O. (2018). Development of methods for estimating the environmental risk of degradation of the surface water state. Eastern-European Journal of Enterprise Technologies, 2 (10 (92)), 4–17. doi: https://doi.org/10.15587/1729-4061.2018.127829
  • World Fire Statistics (2022). No. 27. CTIF, 65. Available at: https://www.ctif.org/sites/default/files/2022-08/CTIF_Report27_ESG.pdf
  • Kovalov, A., Otrosh, Y., Rybka, E., Kovalevska, T., Togobytska, V., Rolin, I. (2020). Treatment of Determination Method for Strength Characteristics of Reinforcing Steel by Using Thread Cutting Method after Temperature Influence. Materials Science Forum, 1006, 179–184. doi: https://doi.org/10.4028/www.scientific.net/msf.1006.179
  • Pospelov, B., Andronov, V., Rybka, E., Samoilov, M., Krainiukov, O. et al. (2021). Development of the method of operational forecasting of fire in the premises of objects under real conditions. Eastern-European Journal of Enterprise Technologies, 2 (10 (110)), 43–50. doi: https://doi.org/10.15587/1729-4061.2021.226692
  • Andronov, V., Pospelov, B., Rybka, E. (2017). Development of a method to improve the performance speed of maximal fire detectors. Eastern-European Journal of Enterprise Technologies, 2 (9 (86)), 32–37. doi: https://doi.org/10.15587/1729-4061.2017.96694
  • Pospelov, B., Andronov, V., Rybka, E., Skliarov, S. (2017). Research into dynamics of setting the threshold and a probability of ignition detection by self­adjusting fire detectors. Eastern-European Journal of Enterprise Technologies, 5 (9 (89)), 43–48. doi: https://doi.org/10.15587/1729-4061.2017.110092
  • Cheng, C., Sun, F., Zhou, X. (2011). One fire detection method using neural networks. Tsinghua Science and Technology, 16 (1), 31–35. doi: https://doi.org/10.1016/s1007-0214(11)70005-0
  • Ding, Q., Peng, Z., Liu, T., Tong, Q. (2014). Multi-Sensor Building Fire Alarm System with Information Fusion Technology Based on D-S Evidence Theory. Algorithms, 7 (4), 523–537. doi: https://doi.org/10.3390/a7040523
  • Wu, Y., Harada, T. (2004). Study on the Burning Behaviour of Plantation Wood. Scientia Silvae Sinicae, 40, 131–136.
  • Ji, J., Yang, L., Fan, W. (2003). Experimental Study on Effects of Burning Behaviours of Materials Caused by External Heat Radiation. JCST, 9, 139.
  • Peng, X., Liu, S., Lu, G. (2005). Experimental Analysis on Heat Release Rate of Materials. Journal of Chongqing University, 28, 122.
  • Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Gornostal, S. (2018). Analysis of correlation dimensionality of the state of a gas medium at early ignition of materials. Eastern-European Journal of Enterprise Technologies, 5 (10 (95)), 25–30. doi: https://doi.org/10.15587/1729-4061.2018.142995
  • Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Borodych, P. (2018). Studying the recurrent diagrams of carbon monoxide concentration at early ignitions in premises. Eastern-European Journal of Enterprise Technologies, 3 (9 (93)), 34–40. doi: https://doi.org/10.15587/1729-4061.2018.133127
  • Pospelov, B., Rybka, E., Meleshchenko, R., Krainiukov, O., Biryukov, I., Butenko, T. et al. (2021). Short-term fire forecast based on air state gain recurrence and zero-order brown model. Eastern-European Journal of Enterprise Technologies, 3 (10 (111)), 27–33. doi: https://doi.org/10.15587/1729-4061.2021.233606
  • Pospelov, B., Rybka, E., Krainiukov, O., Yashchenko, O., Bezuhla, Y., Bielai, S. et al. (2021). Short-term forecast of fire in the premises based on modification of the Brown's zero-order model. Eastern-European Journal of Enterprise Technologies, 4 (10 (112)), 52–58. doi: https://doi.org/10.15587/1729-4061.2021.238555
  • Pospelov, B., Rybka, E., Togobytska, V., Meleshchenko, R., Danchenko, Y., Butenko, T. et al. (2019). Construction of the method for semi-adaptive threshold scaling transformation when computing recurrent plots. Eastern-European Journal of Enterprise Technologies, 4 (10 (100)), 22–29. doi: https://doi.org/10.15587/1729-4061.2019.176579
  • Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Karpets, K., Pirohov, O. et al. (2019). Development of the correlation method for operative detection of recurrent states. Eastern-European Journal of Enterprise Technologies, 6 (4 (102)), 39–46. doi: https://doi.org/10.15587/1729-4061.2019.187252
  • Sadkovyi, V., Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Rud, A. et al. (2020). Construction of a method for detecting arbitrary hazard pollutants in the atmospheric air based on the structural function of the current pollutant concentrations. Eastern-European Journal of Enterprise Technologies, 6 (10 (108)), 14–22. doi: https://doi.org/10.15587/1729-4061.2020.218714
  • Pospelov, B., Rybka, E., Meleshchenko, R., Krainiukov, O., Harbuz, S., Bezuhla, Y. et al. (2020). Use of uncertainty function for identification of hazardous states of atmospheric pollution vector. Eastern-European Journal of Enterprise Technologies, 2 (10 (104)), 6–12. doi: https://doi.org/10.15587/1729-4061.2020.200140
  • Floyd, J., Forney, G., Hostikka, S., Korhonen, T., McDermott, R., McGrattan, K. (2013). Fire Dynamics Simulator (Version 6) User's Guide. Vol. 1. National Institute of Standard and Technology.
  • Polstiankin, R. M., Pospelov, B. B. (2015). Stochastic models of hazardous factors and parameters of a fire in the premises. Problemy pozharnoy bezopasnosti, 38, 130–135. Available at: http://nbuv.gov.ua/UJRN/Ppb_2015_38_24
  • Heskestad, G., Newman, J. S. (1992). Fire detection using cross-correlations of sensor signals. Fire Safety Journal, 18 (4), 355–374. doi: https://doi.org/10.1016/0379-7112(92)90024-7
  • Gottuk, D. T., Wright, M. T., Wong, J. T., Pham, H. V., Rose-Pehrsson, S. L., Hart, S. et al. (2002). Prototype Early Warning Fire Detection System: Test Series 4 Results. NRL/MR/6180–02–8602. Naval Research Laboratory. Available at: https://apps.dtic.mil/sti/pdfs/ADA399480.pdf
  • Pospelov, B., Andronov, V., Rybka, E., Bezuhla, Y., Liashevska, O., Butenko, T. et al. (2022). Empirical cumulative distribution function of the characteristic sign of the gas environment during fire. Eastern-European Journal of Enterprise Technologies, 4 (10 (118)), 60–66. doi: https://doi.org/10.15587/1729-4061.2022.263194
  • Pospelov, B., Rybka, E., Savchenko, A., Dashkovska, O., Harbuz, S., Naden, E. et al. (2022). Peculiarities of amplitude spectra of the third order for the early detection of indoor fires. Eastern-European Journal of Enterprise Technologies, 5 (10 (119)), 49–56. doi: https://doi.org/10.15587/1729-4061.2022.265781
  • Pospelov, B., Bezuhla, Y., Yashchenko, O., Khalmuradov, B., Petukhova, O., Gornostal, S. et al. (2022). Revealing the features of the third order phase spectrum of the main dangerous parameters of the gas medium. Eastern-European Journal of Enterprise Technologies, 6 (10 (120)), 63–70. doi: https://doi.org/10.15587/1729-4061.2022.268437
  • Pasport. Spovishchuvach pozhezhnyi teplovyi tochkovyi. Arton. Available at: https://ua.arton.com.ua/files/passports/%D0%A2%D0%9F%D0%A2-4_UA.pdf
  • Pasport. Spovishchuvach pozhezhnyi dymovyi tochkovyi optychnyi. Arton. Available at: https://ua.arton.com.ua/files/passports/spd-32_new_pas_ua.pdf
  • Optical/Heat Multisensor Detector (2019). Discovery. Available at: https://www.nsc-hellas.gr/pdf/APOLLO/discovery/B02704-00%20Discovery%20Multisensor%20Heat-%20Optical.pdf
  • McGrattan, K., Hostikka, S., McDermott, R., Floyd, J., Weinschenk, C., Overholt, K. (2016). Fire Dynamics Simulator Technical Reference Guide. Vol. 3. National Institute of Standards and Technology. Available at: https://www.fse-italia.eu/PDF/ManualiFDS/FDS_Validation_Guide.pdf
  • Saeed, M., Alfatih, S. (2013). Nonlinearity detection in hydraulic machines utilizing bispectral analysis. TJ Mechanical engineering and machinery, 13–21. Available at: http://eprints.utm.my/id/eprint/42178/
  • Yang, K., Zhang, R., Chen, S., Zhang, F., Yang, J., Zhang, X. (2015). Series Arc Fault Detection Algorithm Based on Autoregressive Bispectrum Analysis. Algorithms, 8 (4), 929–950. doi: https://doi.org/10.3390/a8040929
  • Yang, B., Wang, M., Zan, T., Gao, X., Gao, P. (2021). Application of Bispectrum Diagonal Slice Feature Analysis in Tool Wear States Monitoring. Research Square. doi: https://doi.org/10.21203/rs.3.rs-775113/v1
  • Chua, K. C., Chandran, V., Acharya, U. R., Lim, C. M. (2010). Application of higher order statistics/spectra in biomedical signals – A review. Medical Engineering & Physics, 32 (7), 679–689. doi: https://doi.org/10.1016/j.medengphy.2010.04.009
  • Chua, K. C., Chandran, V., Acharya, U. R., Lim, C. M. (2008). Cardiac state diagnosis using higher order spectra of heart rate variability. Journal of Medical Engineering & Technology, 32 (2), 145–155. doi: https://doi.org/10.1080/03091900601050862
  • Cui, L., Xu, H., Ge, J., Cao, M., Xu, Y., Xu, W., Sumarac, D. (2021). Use of Bispectrum Analysis to Inspect the Non-Linear Dynamic Characteristics of Beam-Type Structures Containing a Breathing Crack. Sensors, 21 (4), 1177. doi: https://doi.org/10.3390/s21041177
  • Martín-Montero, A., Gutiérrez-Tobal, G. C., Kheirandish-Gozal, L., Jiménez-García, J., Álvarez, D., del Campo, F. et al. (2020). Heart rate variability spectrum characteristics in children with sleep apnea. Pediatric Research, 89 (7), 1771–1779. doi: https://doi.org/10.1038/s41390-020-01138-2
  • Max, J. (1981). Principes generaus et methods classiques. Vol. 1. Paris, 311.
  • Mohankumar, K. (2015). Implementation of an underwater target classifier using higher order spectral features. Cochin.
  • Nikias, C. L., Raghuveer, M. R. (1987). Bispectrum estimation: A digital signal processing framework. Proceedings of the IEEE, 75 (7), 869–891. doi: https://doi.org/10.1109/proc.1987.13824