Размер шрифта: 

The objective of the study is the development of an intelligent fire-fighting multi-sensor system for sea-going vessels. The system has a set of sensors for measuring temperature, carbon dioxide concentration, carbon monoxide and smoke concentration, which provide early detection of a fire. For rapid deployment and higher flexibility, the sensors are connected using a wireless Thread interface that allows devices to communicate at three levels of ISO. The algorithm implemented in the computational block makes a decision about the presence and type of ignition based on the neural network, which continuously analyzes the information received from the set of sensors. The correctness of the solution depends on the number of sensors and their location in the space of the room. To optimize the location of the sensors, a genetic algorithm is proposed, the objective function for which is the detection time of the ignition. Complexity of the description of premises on sea vessels, types of ignitions and their localization leads to expediency of application of a modeling method. A model of ignition in the vessel's premises is developed on the basis of the Navier-Stokes equations. Modeling of fires of several types of materials: rags, gasoline, oil, diesel fuel, electric cables was carried out in the supercomputer center of the Peter the Great Polytechnic University. The supercomputer is capable of performing up to 1.2PFLOPS. The supercomputer consists of two independent computing systems "RSC Tornado cluster system" and massively parallel "RSC PetaStream". The simulation results are used to form the objective function of the genetic algorithm when optimizing the location of the sensors in the ship's room.