Description

Early detection of fault in power electronic systems (PESs) to maintain reliability is one of the most important issues that has been significantly addressed in recent years. Fault detection in PESs, data mining-based techniques including, machine learning, and deep learning algorithms are introduced. Electrical energy has become an influential factor in the scientific, economic and welfare fields of human daily life. The results of evaluations show that the machine learning-based techniques given the ability of feature extraction from measured signals are more significantly method and future applications in power electronics industry are introduced. The system is developed based on random forest for predicting or detecting the fault in power systems effectively.