In recent years, with the development of wind energy, the number and scale of wind farms
have been develo** rapidly. Since offshore wind farms have the advantages of stable …

The objective of this paper is to present a comprehensive review of the contemporary
techniques for fault detection, diagnosis, and prognosis of rolling element bearings (REBs) …

The battery system is vital for the safety and durability of a real-world electric vehicle (EV),
and the prognosis of battery thermal runaway trigged by various abuse conditions is critical …

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 …

This article presents an online data-driven diagnosis method for multiple insulated gate
bipolar transistors (IGBTs) open-circuit faults and current sensor faults in the three-phase …

A novel convolutional neural network namely the modified CNN-GAP model is proposed for
fast fault diagnosis of the DC-DC inverter. This method improves the model structure of the …

Machine learning (ML) based data-driven methods have shown promising performance in
power converter fault diagnosis. However, the existing ML model trained by one fault …

A method, being based on multi-class support vector machine (SVM) classifier and hybrid
particle swarm optimization (PSO) and gravity search algorithm (GSA), is presented to …

This paper proposes “An Integrated Self-diagnosis System (ISS) for an Autonomous Vehicle
based on an Internet of Things (IoT) Gateway and Deep Learning” that collects information …

Early fault detection in power electronic systems (PESs) to maintain reliability is one of the
most important issues that has been significantly addressed in recent years. In this article …