МОДЕЛЬ УПРАВЛЕНИЯ БЕЗОПАСНОСТЬЮ ПРИ РАБОТАХ НА ПОЖАРАХ В НЕПРИГОДНОЙ ДЛЯ ДЫХАНИЯ СРЕДЕ

Abstract

Introduction. Modem telemetry safety indicators monitoring systems of fire fighting participants and the metrological stmcture of data obtained from such systems determine the need to improve the methodological basis for fire fighters safety management, who work in unsuitable for breathing environment. A research task has been set up. It consists of the development of a safety management model for firefighting in unsuitable for breathing environment on the basis of a general theory of risk management. A method for calculation of the risk magnitude of implementing destructive events associated with a lack of volume of breathing mixture for the successful performance of work in unsuitable for breathing environment was developed in order to cope with this task. Formal task description and solution method . Officially, the task of the fire fighters safety management for fire-fighting in unsuitable for breathing environment is reduced to determining the risk of implementing an event that the volume of the breathing mixture is not enough to successfully complete the work during the required time period. Quantitative criteria for the successful completion of a set of operations in unsuitable for breathing environment were formed in a deterministic and probabilistic formulations in order to solve this task. The concepts of integral and local risk of the implementation of destructive events associated with the specifics of working in unsuitable for breathing environment were introduced. Conclusions . The developed probability model of safety management is based on the theoretical background of risk management when working in unsuitable for breathing environment. The model allows to use as initial data the results of safety indicators monitoring obtained from telemetrie systems. The advantage of the probability model is the possibility of varying interval values of safety indicators by changing the magnitude of local and integral risks. An additional useful property of the model is the possibility of a linear positive conversion of the initial probabilistic characteristics, which allows using not only planned figures, but actual values of the parameters included in the model in its practical application.