Induction motors make up approximately 80% of the electric motors in the railway sector due
to their robustness, high efficiency, and low maintenance cost. Nevertheless, these motors …

Induction motors are widely used worldwide for domestic and industrial applications. Fault
detection and classification techniques based on signal analysis have increased in …

Induction motors are robust and cost effective; thus, they are commonly used as power
sources in various industrial applications. However, due to the characteristics of induction …

Industry 5.0, also known as the “smart factory”, is an evolution of manufacturing technology
that utilizes advanced data analytics and machine learning techniques to optimize …

Using deep learning in three-phase induction motor fault diagnosis has gained increasing
interest nowadays. This paper proposes a Convolutional Neural Network (CNN) model to …

Induction machines (IMs) play a critical role in various industrial processes but are
susceptible to degenerative failures, such as broken rotor bars. Effective diagnostic …

Inter-turn short circuit (ITSC) is a common fault in induction motors. However, it is
challenging to detect the early stage of ITSC fault. To address this issue, this paper proposes …

The role of transformers in power distribution is crucial, as their reliable operation is
essential for maintaining the electrical grid's stability. Single-phase transformers are highly …

Induction motors are essential components in industry due to their efficiency and cost-
effectiveness. This study presents an innovative methodology for automatic fault detection by …

This article presents an innovative predictive maintenance for grinding mills, aiming to
enhance operational efficiency and minimize downtime. Leveraging advancements in data …