The high voltage power transformer is the critical element of the power system, which
requires continuous monitoring to prevent sudden catastrophic failures and to ensure an …

This paper presents a state-of-the-art review on machine learning (ML) based intelligent
diagnostics that have been applied for partial discharge (PD) detection, localization, and …

With the development of the new generation of information technology, artificial intelligence,
cloud computing and big data are gradually becoming powerful engines of the smart grid. In …

Power cables, the most critical component of the power system, must be extremely reliable
in order to avoid revenue losses due to premature failure. The dielectric properties of cable …

Junction temperature monitoring (JTM) is essential for reliability evaluation and health
management for insulated-gate bipolar transistor (IGBT) modules, and thus is extensively …

As an onsite condition monitoring method, an infrared inspection can help to discover and
analyze abnormal temperature increases in power equipment. For improving the efficiency …

Medium-voltage (MV) cables often experience a shortened lifespan attributed to insulation
breakdown resulting from accelerated aging and anomalous operational and environmental …

The icing monitoring of transmission lines is of great significance to prevent freezing
disasters of transmission lines and ensure the security and stability of power system …

Intelligent fault diagnosis methods, especially convolutional neural network (CNN), have
made significant progress in gas-insulated switchgear (GIS) partial discharge (PD) …

This paper proposes a neural architecture search algorithm for obtaining an optimum
Transformer model to detect and localize different power system faults and uncertain …