Predicting the Failure of Switching Components Using Machine Learning in a Switching Circuit

The efficiency and application of switching circuits have been proven in various sectors of the electronics industry. Their ability in each of the industrial, commercial and military applications, to reduce the size of the equipment and increase the efficiency, has been determined during the past years. Major failures in such equipment during different working conditions and especially unfavorable conditions such as high ambient temperature are mainly due to switching parts, rectifiers and capacitors. To effectively monitor their condition, measuring their parameters with the help of machine learning provides a reliable method against comparative and traditional measurement techniques, because apart from comparative methods, in this work, the method Damage estimates with the help of artificial intelligence have been used. According to the results obtained by the proposed method, it is possible to use this method to detect possible failure in switching circuits with different applications.

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Key words: — Switching circuits ، machine learning ، failure prediction ، intelligent monitoring ، failure of switching parts