This paper addresses the challenge of diagnosing open-circuit faults in power devices within three-level Neutral Point Clamped (NPC) converters. An enhanced one-dimensional Convolutional Neural ...

Real-time fault detection and classification are important for power system stability and resilience of the power grid to minimize downtime and prevent cascading failures. Numerical relays (NRs) are ...

To address these challenges, this study proposes a Transformer network model based on dual convolutional neural networks and cross-attention enhancement (Trans-DCC) for wheelset bearing fault ...

There is a growing consensus that graph neural networks (GNNs) offer a promising solution for the above challenges by integrating variable interactions, process mechanisms, and expert knowledge into ...

Department of Electrical Engineering, Vellore Institute of Technology, Vellore, India High Impedance Fault detection in a solar photovoltaic (PV) and wind generator integrated power system is ...

Abstract Fault diagnosis based on time-domain signals has become mainstream in recent years. Traditional methods require signal processing to extract fault features before feeding them into a neural ...

In chemical plants and other industrial facilities, the rapid and accurate detection of the root causes of process faults is essential for the prevention of unknown accidents. This study focused on ...