scholarly journals Partial discharge patterns in high voltage insulation

2012 ◽  
Author(s):  
Hazlee Illias ◽  
Teo Soon Yuan ◽  
Ab Halim Abu Bakar ◽  
Hazlie Mokhlis ◽  
George Chen ◽  
...  
Keyword(s):  
High Voltage ◽  
Partial Discharge ◽  
High Voltage Insulation ◽  
Discharge Patterns

scholarly journals Anomaly Detection, Trend Evolution, and Feature Extraction in Partial Discharge Patterns

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3886
Author(s):  
Marek Florkowski
Keyword(s):  
Machine Learning ◽  
Feature Extraction ◽  
Anomaly Detection ◽  
Optical Flow ◽  
High Voltage ◽  
Partial Discharge ◽  
Electrical Power System ◽  
Deep Convolutional Neural Networks ◽  
High Voltage Insulation ◽  
Discharge Patterns

In the resilient and reliable electrical power system, the condition of high voltage insulation plays a crucial role. In the field of high voltage insulation integrity, the partial discharge (PD) inception and development trends are essential for assessment criteria in diagnostics systems. The observed trend to employ more and more sophisticated algorithms with machine learning features and artificial intelligence (AI) elements is observed everywhere. The classification and identification of features in PD images is perceived as a critical requirement for an effective high voltage insulation diagnosis. In this context, techniques allowing for anomaly detection, trends observation, and feature extraction in partial discharge patterns are important. In this paper, the application of few algorithms belonging to image processing, machine learning and optical flow is presented. The feature extraction refers to image segmentation and detection of coherent forms in the images. The anomaly detection algorithms can trigger early detection of the trend changes or the appearance of a new discharge form, and hence are suitable for PD monitoring applications. Anomaly detection can also handle transients and disturbances that appear in the PD image as an indication of an abnormal state. The future monitoring systems should be equipped with trend evolution algorithms. In this context, two examples of insulation aging and application of PD-based monitoring are shown. The first one refers to deep convolutional neural networks used for classification of deterioration stages in high voltage insulation. The latter one demonstrates application of optical flow approach for motion detection in partial discharge images. The motivation for the research was the strive to machine-controlled pattern analysis, leading towards intelligent PD-based diagnostics.

Impact of high voltage harmonics on interpretation of partial discharge patterns

2013 ◽  
Vol 20 (6) ◽  
pp. 2009-2016 ◽  
Author(s):  
Marek Florkowski ◽  
Barbara Florkowska ◽  
Jakub Furgal ◽  
Pawel Zydron
Keyword(s):  
High Voltage ◽  
Partial Discharge ◽  
Discharge Patterns ◽  
Voltage Harmonics

scholarly journals Research of partial discharge characteristics features in bushings

2021 ◽  
pp. 26-32
Author(s):  
D. A. Polyakov ◽  
◽  
N. A. Tereshchenko ◽  
K. I. Nikitin ◽  
◽  
...  
Keyword(s):  
High Voltage ◽  
Partial Discharge ◽  
Test Time ◽  
Test Results ◽  
High Voltage Electrode ◽  
Discharge Characteristics ◽  
Measurement And Analysis ◽  
Defect Localization ◽  
Sharp Edges ◽  
Discharge Patterns

The paper is devoted to partial discharge measurement and analysis in switchgear bushings. PD bushing structure analysis is described to assess possible defect sources in bushings. An experimental 10 kV bushing sample with the natural defect is obtained from the bushings’ manufacturer. It is tested using the PD measurement technique. Test results showed significant PD intensity at voltages from 12 kV and higher. We have an assumption that a part of registered discharges occurred in the air close to the high voltage electrode sharp edges. To check this assumption we grind them off and repeated the test. The second test does not show considerable PD characteristics change. Therefore, we assume that the bushing sample has an inner defect because the bushing’s surface is not contaminated to generate surficial discharges. The bushing is researched by a destroying method for defect localization. However, inside the bushing, possible defect locations are not found. It might be connected with the fact that the defect could not be found visually at the test time or the defect is located in the gasket between the high voltage electrode and insulator’s body. Besides, there are determined features of phase-resolved partial discharge patterns in switchgear bushings.

Sign in / Sign up

Export Citation Format

Share Document