SYNTHESIS OF A SYSTEM FOR ULTRA-FAST DETECTION OF FIREHAZARDOUS SITUATIONS BASED ON A COMPLEX OF INTERCONNECTED SENSORS

  • Sanni Singh Southern Federal University
  • А.V. Pribylskiy Southern Federal University
Keywords: Fire sensor, simulink, detection signal, standard deviation, activation function, mathematical modeling

Abstract

Modern technologies and urban infrastructure require innovative approaches to detecting fire hazards.
Effective and ultra-fast fire detection is becoming an integral part of safety. For this purpose, systems capable of
detecting and informing about a fire hazard situation in a matter of seconds are synthesized and implemented;
one of such systems is synthesized in the article. The research and synthesis of a mathematical model of a digital
universal fire sensor, which in turn is a complex of interconnected sensors, is relevant due to the constant development
of system infrastructure, the increasing complexity of electrical equipment and the need to reduce damage
arising from the outbreak and spread of fires. Predictive diagnostics of electrical equipment performance
allows timely identification and elimination of potential fire safety threats. Within the framework of this research,
a theoretical mathematical model of a real digital universal fire sensor is presented, first in a simplified
version, then in a more complicated version, taking into account the design and statistical approach to the problem
of finding the sensor response thresholds, a description of the parameters of the mathematical model and the
sequential principle of operation is given. This sensor is an innovative fire safety solution that provides a high
level of control and efficiency in real time. Based on the theoretical models presented in the article, a mathematical
model of the sensor has been developed, which is simulated using the Simulink software tool on real data
obtained from the sensor manufacturer. The simulation results showed that the model correctly describes the
behavior of a real sensor on all channels and can be used in further research, such as predicting and detecting
fire situations using neural networks. The synthesis of the proposed system is necessary for further research in
the field of forecasting and detection of fire hazardous situations based on the obtained mathematical model.

References

1. Sautin I.G. Kontseptsiya postroeniya bezopasnoy protivopozharnoy avtomatiki [The concept of constructing
safe fire-fighting automation], Algoritm bezopasnosti [Safety Algorithm], 2015, No. 4.
2. Sautin I.G. Sverkhrannee obnaruzhenie dyma. Novye vozmozhnosti [Ultra-early smoke detection.
New features], Algoritm bezopasnosti [Safety Algorithm], 2016, No. 5.
3. Sautin I.G. Bezopasnost' zdaniy i sooruzheniy [Safety of buildings and structures], Bezopasnost'.
Sredstva razmeshcheniya [Safety. Accommodation facilities], 2017, No. 1.
4. Sautin I.G. Protivopozharnaya zashchita: tekhnologii i resheniya [Fire protection: technologies and
solutions], Transport. Protivopozharnaya zashchita. Pozharnaya avtomatika. Sredstva spaseniya
[Transport. Fire protection. Fire automatics. Rescue means], 2018.
5. Sautin I.G. Osoboe mnenie. Mozhno li doverit' svoyu zhizn' dymovomu pozharnomu izveshchatelyu?
[Special opinion. Can you trust your life to a smoke alarm?], Algoritm bezopasnosti [Security algorithm],
2019, No. 6.
6. Zaytsev A.V. Dostovernost' i svoevremennost' obnaruzheniya pozhara, i kak ikh uchest' v normakh na
SPS [Reliability and timeliness of fire detection, and how to take them into account in ATP standards],
Algoritm bezopasnosti [Safety Algorithm], 2016, No. 2.
7. Ivanov A.N. K voprosu ob otsenke effektivnosti pozharnoy avtomatiki [On the issue of assessing the effectiveness
of fire automatics], Pozharnaya bezopasnost': sovremennye vyzovy. Problemy i puti
resheniya: Mater. Vseros. nauch.-prakt. konf. [Fire safety: modern challenges. Problems and solutions:
Materials of Vseros. scientific-practical conf.]. St. Petersburg: S.-Peterb. un-t GPS MChS Rossii, 2021.
8. Presnov A.I. [i dr.]. Pozharnaya tekhnika: ucheb. [Fire equipment: textbook]: in 2 part. Part 2.
St. Petersburg: S.-Peterb. Un-t GPS MChS Rossii, 2016, 404 p.
9. Qureshi W.S., Ekpanyapong M., Dailey M.N., Rinsurongkawong S., Malenichev A., Krasotkina O.
QuickBlaze: Early fire detection using a combined video processing approach, Fire Technol., 2016,
52, pp. 1293-1317. DOI: 10.1007/s10694-015-0489-7.
10. Mulholland, G.W. How well are we measuring smoke?, Fire and Materials, June 1982, Vol. 6, No. 2,
pp. 65-67.
11. Bywater D. Detection of Real Fires by Carbon Monoxide Detectors—Foreign Experience. The Results
of 10 Years of Research Lead to a Leap in Fire Detection Technology. Available online:
https://www.aktivsb.ru/statii/obnaruzhenie_realnykh_pozharov_detektorami_ugarnogo_gaza_zarubez
hnyy_opyt.html (accessed on 20 December 2023).
12. Luck H. and Hase K.R. Signal Detection Aspects in Automatic Fire Detection, Fire Safety Journal,
1983, 6, pp. 233-240.
13. Fedorov A., Bytcinskaya T., Lukyanchenko A., Hung T.D. Trends in the development of automatic fire
detectors, Technol. Technosphere Saf., 2009, 23, pp. 111-114. Available online:
https://cyberleninka.ru/article/n/tendentsii-razvitiya-avtomaticheskih-pozharnyh-izveschateley-1 (accessed
on 20 December 2023).
14. Petrov A.E., Fedorov A.V., Kochegarov A.V., Lomaev E.N., Preobrazhenskiy A.P. The Analysis of
Network Models for the Design of Industrial and Fire Safety Systems for Oil Refineries, IOP Conf.
Ser. Earth Environ. Sci., 2021, 808, 012024.
15. Bogdan L., Cristina B. The design of temperature control system using PIC18f4620; 2010.
16. MathWorks. «MATLAB & Simulink Help Center» MathWorks, 2023. Available at:
https://www.mathworks.com/help/index.html. Accessed 20 December 2023.
17. Moler Cleve B. Numerical Computing with Matlab. The MathWorks, Inc., Natik, 2004.
18. Chapra Steven C. Applied Numerical Methods with MATLAB for Engineers and Scientists. McGraw
Hill Companies, Inc. 2nd ed. New York, 2008.
19. Trench William F. Elementary Differential Equations. Trench, 2013.
20. Ukil A., Braendle H., Krippner P. Distributed temperature sensing: Review of technology and applications,
IEEE Sens. J., 2011, 12, pp. 885-892. DOI: 10.1109/JSEN.2011.2162060.
21. Fawad Khan, Zhiguang Xu, Recent Advances in Sensors for Fire Detection, PMID: 35590999, 2022
Apr 26, DOI: 10.3390/s22093310.
Published
2024-05-28
Section
SECTION I. CONTROL SYSTEMS AND MODELING