Development of the method of frequency­temporal representation of fluctuations of gaseous medium parameters at fire

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.125926

Keywords:

fire source, gaseous medium, equilibrium state, frequency-temporal representation, fire sensors

Abstract

The method of operative frequency-temporal representation of fluctuations of gaseous media parameters at an early stage of fire at premises was developed. The basic assumptions about the peculiarities of dynamics of hazardous factors of gaseous medium at early ignition at premises were stated. The authors created theoretical framework for development of the method, based on the fact that violation of equilibrium state of gaseous medium is translated by the medium to the zone of sensors’ localization and responds to emergence of an ignition in premises. The fire source in this case is considered a moving source of disturbances and parameters of the medium carry information about temporal and frequency shifts of disturbances. It was shown that these shifts of disturbances are characterized by the correspondent uncertainty function, which is an invariant with respect to the double Fourier transformation, determined by squared modulus of frequency-temporal energy density of the parameter. The proposed method is a further development of frequency-temporal representations of the Cohen class in case of fluctuations of gaseous medium parameters at early ignitions in premises. The main features of the method are its relative simplicity and the use of data in real time. The verification of the developed method was performed based on the experimental data of the main parameters of the gaseous medium at an early ignition of alcohol, paper, wood, and textiles in the simulation chamber.

Author Biographies

Boris Pospelov, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

Doctor of Technical Sciences, Professor

Research Center

Vladimir Andronov, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

Doctor of Technical Sciences, Professor

Research Center

Evgeniy Rybka, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

PhD

Research Center

Vadym Popov, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

Doctor of Technical Sciences, Associate Professor

Research Center

Oleg Semkiv, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

Doctor of Technical Sciences, Associate Professor

Department of service organization

References

  1. Poulsen, A., Jomaas, G. (2011). Experimental Study on the Burning Behavior of Pool Fires in Rooms with Different Wall Linings. Fire Technology, 48 (2), 419–439. doi: 10.1007/s10694-011-0230-0
  2. Zhang, D., Xue, W. (2010). Effect of Heat Radiation on Combustion Heat Release Rate of Larch. Journal of West China Forestry Science, 39, 148.
  3. Ji, J., Yang, L., Fan, W. (2003). Experimental Study on Effects of Burning Behaviours of Materials Caused by External Heat Radiation. Journal of Combustion Science and Technology, 9, 139.
  4. Peng, X., Liu, S., Lu, G. (2005). Experimental Analysis on Heat Release Rate of Materials. Journal of Chongqing University, 28, 122.
  5. Andronov, V., Pospelov, B., Rybka, E. (2016). Increase of accuracy of definition of temperature by sensors of fire alarms in real conditions of fire on objects. Eastern-European Journal of Enterprise Technologies, 4 (5 (82)), 38–44. doi: 10.15587/1729-4061.2016.75063
  6. 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: 10.15587/1729-4061.2017.96694
  7. Pospelov, B., Andronov, V., Rybka, E., Skliarov, S. (2017). Design of fire detectors capable of self-adjusting by ignition. Eastern-European Journal of Enterprise Technologies, 4 (9 (88)), 53–59. doi: 10.15587/1729-4061.2017.108448
  8. 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: 10.15587/1729-4061.2017.110092
  9. Pospelov, B., Rybka, E., Meleshchenko, R., Gornostal, S., Shcherbak, S. (2017). Results of experimental research into correlations between hazardous factors of ignition of materials in premises. Eastern-European Journal of Enterprise Technologies, 6 (10 (90)), 50–56. doi: 10.15587/1729-4061.2017.117789
  10. Korn, G. A., Korn, T. M. (2000). Mathematical handbook for scientists and engineers: definitions, theorems, and formulas for reference and review. Dover Publications, 1152.
  11. Bendat, J. S., Piersol, A. G. (2010). Random data: analysis and measurement procedures. John Wiley & Sons. doi: 10.1002/9781118032428
  12. Shafi, I., Ahmad, J., Shah, S. I., Kashif, F. M. (2009). Techniques to Obtain Good Resolution and Concentrated Time-Frequency Distributions: A Review. EURASIP Journal on Advances in Signal Processing, 2009 (1). doi: 10.1155/2009/673539
  13. Singh, P. (2016). Time-frequency analysis via the fourier representation. HAL, 1–8. Available at: https://hal.archives-ouvertes.fr/hal-01303330/document
  14. Bundy, M., Hamins, A., Johnsson, E. L., Kim, S. C., Ko, G. H., Lenhert, D. B. (2007). Measurements of heat and combustion products in reduced-scale ventilation-limited compartment fires. NIST Technical Note 1483, 155. doi: 10.6028/nist.tn.1483
  15. Pretrel, H., Querre, P., Forestier, M. (2005). Experimental Study Of Burning Rate Behaviour In Confined And Ventilated Fire Compartments. Fire Safety Science, 8, 1217–1228. doi: 10.3801/iafss.fss.8-1217
  16. Stankovic, L., Dakovic, M., Thayaparan, T. (2014). Time-frequency signal analysis. Kindle edition, 655.
  17. Avargel, Y., Cohen, I. (2010). Modeling and Identification of Nonlinear Systems in the Short-Time Fourier Transform Domain. IEEE Transactions on Signal Processing, 58 (1), 291–304. doi: 10.1109/tsp.2009.2028978
  18. Giv, H. H. (2013). Directional short-time Fourier transform. Journal of Mathematical Analysis and Applications, 399 (1), 100–107. doi: 10.1016/j.jmaa.2012.09.053
  19. Dragoman, D. (2005). Applications of the Wigner distribution function in signal processing. EURASIP Journal on Advances in Signal Processing, 2005 (1), 1520–1534. doi: 10.1155/asp.2005.1520
  20. Poularikas, A. (2010). Transforms and applications handbook. CRC Press, 911. doi: 10.1201/9781420066531
  21. Chassande-Mottin, E., Pai, A. (2005). Discrete time and frequency Wigner-Ville distribution: Moyal's formula and aliasing. IEEE Signal Processing Letters, 12 (7), 508–511. doi: 10.1109/lsp.2005.849493
  22. Boashash, B. (2003). Time-frequency signal analysis and processing: a comprehensive reference. Elsevier, 102–113.
  23. Pospelov, B., Andronov, V., Rybka, E., Popov, V., Romin, A. (2018). Experimental study of the fluctuations of gas medium parameters as early signs of fire. Eastern-European Journal of Enterprise Technologies, 1 (10 (91)), 50–55. doi: 10.15587/1729-4061.2018.122419
  24. Andronov, V., Pospelov, B., Rybka, E., Skliarov, S. (2017). Examining the learning fire detectors under real conditions of application. Eastern-European Journal of Enterprise Technologies, 3 (9 (87)), 53–59. doi: 10.15587/1729-4061.2017.101985

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Published

2018-03-13

How to Cite

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. https://doi.org/10.15587/1729-4061.2018.125926