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 …

Online partial discharge (PD) measurements have long been used as an effective means to
assess the condition of the stator windings of large generators. An increase in the use of PD …

This paper introduces a new application of deep belief network (DBN) as an emerging
artificial neural network for recognizing and classifying different partial discharge (PD) …

In modern power systems, condition based monitoring and diagnosis is essential to ensure
the effective and reliable operation of different high voltage equipment (HVE). Compared to …

This paper compiles, summarizes, and deliberates over one hundred important works on the
different approaches and advances in the surveillance and diagnosis of the internal status of …

In order to investigate how artificial neural networks (ANNs) have been applied for partial
discharge (PD) pattern recognition, this paper reviews recent progress made on ANN …

The presence of air-filled cavities within the insulation of active power cables affects the
electric field distribution in the insulation bulk and increases the electrical stress inside and …

Partial discharge (PD) diagnostics is a reliable technique for the health assessment of
electrical motors. This paper presents a unique methodology for the failure risk assessment …

This paper compared the capabilities of the artificial neural network (ANN) and the fuzzy
logic (FL) approaches for recognizing and discriminating partial discharge (PD) fault …

This article describes a complete approach to filtering partial discharge (PD) pulses from
interference in high voltage (HV) electrical equipment using supervised machine learning …