This paper presents the application of shallow neural networks (SNNs): multi-layer
perceptron (MLP) and self-organizing Kohonen maps (SOMs) to the early detection and …

High efficiency, high reliability and excellent dynamic performance have been key aspects
considered in recent years when selecting motors for modern drive systems. These features …

This paper deals with the possibility of using transfer learning (TL) of a deep convolutional
network (CNN) to develop a universal stator winding fault diagnostic system for the induction …

Automatic fault detection is currently combined with deep networks owing to the possibility of
dispensing signal processing, which significantly accelerates reactions to faults. Changing …

Permanent-magnet synchronous motors (PMSMs) have played a key role in recent years in
both industrial and commercial applications. Despite their many significant advantages …

Modern permanent magnet synchronous motor (PMSM) diagnostic systems are now
combined with advanced artificial intelligence techniques, such as deep neural networks …

The article concerns the problem of capacitor diagnosis in a hybrid aircraft. Capacitors are
one of the most commonly damaged components of electrical vehicle drive systems. The …

An accurate classification method is highly required in the development of a fault detection
system. Various deep-learning techniques have recently been used for fault classification …

To prevent fossil resources from being depleted and protect the natural balance, renewable
resources come to the forefront as an alternative to fossil resources. Wind energy resources …

Deep neural networks learnt in line with transfer learning are now increasingly used in
electrical drive diagnostic applications. This fact is related to the possibility of completely …