The disposability of clothing has emerged as a critical concern, precipitating waste
accumulation due to product quality degradation. Such consequences exert significant …

The traditional power transformer diagnosis method relies on a lot of experience knowledge
and a complex sampling process, which brings great difficulties to the fault diagnosis work …

A voiceprint signal as a non-contact test medium has a broad application prospect in power-
transformer operation condition monitoring. Due to the high imbalance in the number of fault …

To quickly and accurately identify faulty components based on the alarm information is
critical for the fault diagnosis of power grids. To address this challenge, this paper proposes …

This paper proposes a novel fault diagnosis method by fusing the information from multi-
sensor signals to improve the reliability of the conventional vibration-based wind turbine …

Multiple features fusion through artificial intelligence holds the potential to enhance the
reliability of transformer protection. However, the existing methods encounter challenges …

Overcoming the drawback of the incorrect action of differential protection induced by the
inrush current is a crucial issue for transformer protection. This paper proposes a deep …

Cross-linked polyethylene (XLPE) power cables are commonly used in flexible DC
transmission applications. The diagnosis of the defects of XLPE power cable has …

Deep learning techniques have been widely applied to wind turbine bearing fault diagnosis
in recent years. However, current methods often face challenges in feature extraction, which …

Numerous methods exist to distinguish between inrush current and internal faults, but these
approaches have not yet become practical due to their inherent limitations. As a result …