Predictive maintenance is an essential aspect of microgrid operations as it enables
identifying potential equipment failures in advance, reducing downtime, and increasing the …

This paper highlights the importance of maintenance techniques in the coming industrial
revolution, reviews the evolution of maintenance techniques, and presents a comprehensive …

This paper reviews the recent literature on machine learning (ML) models that have been
used for condition monitoring in wind turbines (eg blade fault detection or generator …

This paper reviews the recent advancement made in data-driven technologies based on
SCADA data for improving wind turbines' operation and maintenance activities (eg condition …

The proliferation and application of machine learning-based Intrusion Detection Systems
(IDS) have allowed for more flexibility and efficiency in the automated detection of cyber …

Wind energy has emerged as a highly promising source of renewable energy in recent
times. However, wind turbines regularly suffer from operational inconsistencies, leading to …

With the rapid development of electrical power systems in recent years, microgrids (MGs)
have become increasingly prevalent. MGs improve network efficiency and reduce operating …

Experimental measurement and numerical simulation are two typical methods to monitor the
strength variation of structures. However, the former method is difficult to lay sufficient …

Prognostic and Health Management (PHM) systems are some of the main protagonists of
the Industry 4.0 revolution. Efficiently detecting whether an industrial component has …

Recurrent neural network (RNN) is one of the most used deep learning techniques in fault
detection and diagnosis (FDD) of industrial systems. However, its implementation suffers …