МЕТОДИКА КОНТРОЛЯ И ПРОГНОЗИРОВАНИЯ ТЕХНИЧЕСКОГО СОСТОЯНИЯ СИСТЕМЫ ВТОРИЧНОГО ЭЛЕКТРОПИТАНИЯ ПОЛЕВЫХ ОБЪЕКТОВ СВЯЗИ НА ОСНОВЕ НЕЙРОСЕТЕВОГО ПОХОДА

Abstract

Introduction: сurrently, the control of the technical condition of complex technical systems, such as the secondary power supply system of field communication facilities, is a long and non-automated process that is carried out by operators directly at the control facilities themselves. This circumstance has a negative impact on the timely detection of failures of the controlled object. Also, a very negative factor is the complete absence of any forecast of the technical condition of the control object, which leads to sudden disconnections of the secondary power supply system of field communication facilities, and, accordingly, a break in communication. The combination of these factors has an extremely negative effect both on the stable operation of the communication system as a whole, and on the coefficient of serviceable operation of the communication direction, in particular. The purpose of the work is to develop methods for monitoring and predicting the technical condition of the secondary power supply system of field communication facilities. Methods used: the application of the neural network approach allows you to achieve very accurate results and get high performance systems in real time. The novelty of the work is to increase the accuracy and speed of control, the ability to predict the technical condition, the integration of the secondary power supply system into the information environment of the field communication object by using neural network technologies. Result: the application of the neural network approach allows you to predict the technical condition, as well as more accurately classify the technical condition of the control object. Also, it becomes possible to centralize control, which, in turn, reduces the control time. Practical significance: the results of the work can be used in the process of monitoring and predicting the technical condition of complex technical systems, which will significantly reduce the number of accidents.