Диагностика асинхронного электродвигателя тепловизором с использованием нейронных сетей

ДИАГНОСТИКА АСИНХРОННОГО ЭЛЕКТРОДВИГАТЕЛЯ ТЕПЛОВИЗОРОМ С ИСПОЛЬЗОВАНИЕМ НЕЙРОННЫХ СЕТЕЙ

DIAGNOSTICS OF AN ASYNCHRONOUS MOTOR THERMAL INSULATOR USING NEURAL NETWORKS

Сторінки: 192-194. Номер: №4, 2019 (275)
Автори:
Д.Ю. ЗУБЕНКО, О.М. ПЕТРЕНКО
Харьковский национальный университет городского хозяйства имени О.Н. Бекетова
D. ZUBENKO, О. PETRENKO
O.M. Beketov National University of Urban Economy in Kharkiv
DOI: https://www.doi.org/10.31891/2307-5732-2019-275-4-192-194
Рецензія/Peer review : 04.06.2019 р.
Надрукована/Printed : 17.07.2019 р.

Анотація мовою оригіналу

Электрические двигатели применяются на самом экологически чистом наземном транспорте – электротранспорте. Однако, используемые электродвигатели выделяют значительное количество тепла из-за больших мощностей, что в свою очередь влияет как на работу самих двигателей, так и отрицательно влияет на окружающую среду путем повышения температуры. В данной статье рассматриваются вопросы диагностики асинхронных электродвигателей с помощью тепловизора и анализа полученной картинки при помощи нейронных сетей. Данная методика позволяет следить за предельно-допустимым излучением тепловой энергии в атмосферу, а также увеличить надежность работы электромеханической системы.
Ключевые слова: тепловой контроль, электродвигатель, тепловизор, диагностика, бесконтактные методы, нечеткая логика, безотказная работа, нейронная сеть.

Розширена анотація англійською мовою

Electric engines are used on the most environmentally friendly land transport – electric transport. However, the used electric motors emit a significant amount of heat due to high power, which in turn affects both the operation of the engines themselves and negatively affects the environment, by increasing the temperature. This article addresses the issues of diagnosing asynchronous electric motors using a thermal imager and analysing the resulting image using neural networks. This method allows you to monitor the maximum permissible radiation of thermal energy into the atmosphere, as well as to increase the reliability of the electromechanical system. Electric transport is one of the environmentally friendly technical means for the transport of passengers. However, the operation of its main electrical components contributes to the release of significant amounts of heat into the atmosphere, which adversely affects the environment and leads to environmental changes on the planet. Failures of electric rotating motors also lead to operation failures and can be listed as: stator faults, rotor electrical faults, mechanical rotor faults. However, the methods for the faults mentioned become complex and specific. In the literature, methods for diagnosing faults have been developed by scientists. Analyses of electrical signals, acoustic signals, vibrations, thermal imaging of electric motors have been very popular in recent literature. Methods for diagnosing electrical faults in electric motors have been developed in the literature. MCSA (Motor Current Signature Analysis) is a fault diagnosis technology. In the literature, MCSA was used to detect specific malfunctions of electrical and mechanical asynchronous motors. MCSA has many advantages, because it is not expensive. Infrared physics and technologies of stator winding diagnostics, not subject to stress or asymmetry. As well as the ease of installation of current sensors. However, this has drawbacks, such as stator current data must be selected after the engine speed reaches a steady state. Vibration alarms were also very popular for troubleshooting. Methods based on vibration analysis have an advantage and are more sensitive than MCSA to certain malfunctions.
Keywords: thermal control, electric motor, thermal imager, diagnostics, contactless methods, fuzzy logic, trouble-free operation, neural network.

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