Method for early ignition detection based on the sampling dispersion of dangerous parameter

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.299001

Keywords:

early detection of fire, ignition materials, selective dispersion, hazardous parameters, gas environment

Abstract

The object of the study is the selective dispersion of dangerous parameters of the gas environment during material fires. The practical importance of research consists in using the difference of sample dispersions of dangerous parameters of the gas environment on the intervals of absence and presence of ignition of materials for detection of ignition. The theoretical substantiation of the method of detecting fires in premises based on sample dispersions of current measurements of an arbitrary dangerous parameter of the gas environment, corresponding to the general populations of reliable absence and presence of fire, has been carried out. The method, at a given level of significance, determines the unbiased uniformly most powerful fire detection rule. This makes it possible to determine how much differences in sample variances are significant with a given level of significance and are caused by ignition or are random factors. Laboratory experiments were conducted to verify the proposed method. It was established that the influence of ignition on the value of the difference in the sample dispersion at the corresponding intervals of monitoring the carbon monoxide concentration, smoke density, and temperature of the gaseous environment of the laboratory chamber is different and depends on the type of ignition material. At the same time, the minimum difference of the sample dispersions is characteristic for observing the smoke density for all the studied materials. However, early detection of ignition of alcohol, paper, wood, and textiles when observing the smoke density is carried out when the threshold is exceeded by 9.01, 5.31, 2.13 and 2.55 times, respectively. It is shown that the method of early detection of fires, which is based on the detection of significant differences in sample dispersions of data from the relevant general populations

Author Biographies

Boris Pospelov, Scientific-Methodical Center of Educational Institutions in the Sphere of Civil Defence

Doctor of Technical Sciences, Professor

Evgenіy Rybka, National University of Civil Defence of Ukraine

Doctor of Technical Sciences, Professor

Research Center

Olekcii Krainiukov, V. N. Karazin Kharkiv National University

Doctor of Geographical Sciences, Professor

Department of Environmental Safety and Environmental Education

Vasyl Fedyna, National Aviation University

PhD, Associate Professor

Department of Civil and Industrial Safety

Yuliia Bezuhla, National University of Civil Defence of Ukraine

PhD, Associate Professor

Department of Prevention Activities and Monitoring

Andrii Melnychenko, National University of Civil Defence of Ukraine

PhD

Department of Logistics and Technical Support of Rescue Operations

Pavlo Borodych, National University of Civil Defence of Ukraine

PhD, Associate Professor

Department of Fire and Rescue Training

Svitlana Hryshko, Bogdan Khmelnitsky Melitopol State Pedagogical University

PhD, Associate Professor

Department of Geography and Tourism

Svyatoslav Manzhura, National Academy of the National Guard of Ukraine

PhD

Research Center

Olha Yesipova, National Academy of the National Guard of Ukraine

PhD

Scientific and Organizational Department

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Method for early ignition detection based on the sampling dispersion of dangerous parameter

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Published

2024-02-28

How to Cite

Pospelov, B., Rybka, E., Krainiukov, O., Fedyna, V., Bezuhla, Y., Melnychenko, A., Borodych, P., Hryshko, S., Manzhura, S., & Yesipova, O. (2024). Method for early ignition detection based on the sampling dispersion of dangerous parameter. Eastern-European Journal of Enterprise Technologies, 1(10 (127), 55–63. https://doi.org/10.15587/1729-4061.2024.299001

Issue

Vol. 1 No. 10 (127) (2024): Ecology

Section

Ecology

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Copyright (c) 2024 Boris Pospelov, Evgenіy Rybka, Olekcii Krainiukov, Vasyl Fedyna, Yuliia Bezuhla, Andrii Melnychenko, Pavlo Borodych, Svitlana Hryshko, Svyatoslav Manzhura, Olha Yesipova

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