scholarly journals Partial Discharge Analysis and Simulation Using the Consecutive Pulses Correlation Method

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2567
Author(s):  
Ondřej Kozák ◽  
Josef Pihera
Keyword(s):  
Sequence Analysis ◽  
Evaluation Method ◽  
Pulse Sequence ◽  
Partial Discharge ◽  
Correlation Method ◽  
Partial Discharges ◽  
Time Resolved ◽  
Test Conditions ◽  
Fault Locating ◽  
Dc Stress

The behaviour of partial discharge as consequences of an alternating current (AC) is already well defined. AC partial discharges have completely different behaviour, background physics and parameters than partial discharges (PD) under direct current (DC) stress. This paper focuses on the most used and promising evaluation method of the PD DC stress—pulse sequence analysis (PSA). The first step is understanding and verifying the mechanisms and principles of this method. It is provided by well-known fundamentals of AC PD and by comparison with the other diagnostic and fault-locating methods such as phase-resolved partial discharge (PRPD) and pulse diagrams. The paper shows the PSA simulations and PD analyses performed at AC and partly at DC test conditions on typical PD test arrangements such as corona, surface and internal discharges. It is shown that the simulations performed, compared and validated with data obtained from measurements on different PD arrangements are a good match. This fact opens the way for the PD source recognition in DC, especially the time-resolved pulse sequence analysis described in detail in the paper.

scholarly journals Device for online monitoring of insulation faults in high-voltage switchgears

2021 ◽  
Vol 17 (2) ◽  
pp. 155014772199928
Author(s):  
Jiajia Song ◽  
Jinbo Zhang ◽  
Xinnan Fan
Keyword(s):  
Fourier Transform ◽  
High Voltage ◽  
Online Monitoring ◽  
Pulse Current ◽  
Partial Discharge ◽  
Current Method ◽  
Capacitive Sensor ◽  
Accurate Diagnosis ◽  
Partial Discharges ◽  
Urgent Problem

Partial discharges are the major cause of deterioration in the insulation characteristics of switchgears. Therefore, timely detection of partial discharge in switchgear and potential insulation faults is an urgent problem that needs to be addressed in the power supervision industry. In this study, a device was proposed for online monitoring of high-voltage switchgears based on pulse current method and ozone (O3) detection. The pulse current method obtains the PD signal by monitoring the phase holes on the switch indicator. Occurrence of a partial discharge in a certain phase leads to the production of a discharge pulse, which can be coupled out by a capacitive sensor. The current spectrum and the O3 produced by partial discharge were processed via fast Fourier transform for accurate diagnosis of the occurrence of partial discharge and its severity in switchgears. The proposed method allows for convenient acquisition of the partial discharge signal, simple installation of the device, and realization with inexpensive sensors.

scholarly journals Novel Features and PRPD Image Denoising Method for Improved Single-Source Partial Discharges Classification in On-Line Hydro-Generators

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3267
Author(s):  
Ramon C. F. Araújo ◽  
Rodrigo M. S. de Oliveira ◽  
Fernando S. Brasil ◽  
Fabrício J. B. Barros
Keyword(s):  
Image Denoising ◽  
Recognition Performance ◽  
Partial Discharge ◽  
Classification Performance ◽  
Partial Discharges ◽  
Denoising Method ◽  
Internal Parameters ◽  
On Line ◽  
Automatic Removal ◽  
The Impact

In this paper, a novel image denoising algorithm and novel input features are proposed. The algorithm is applied to phase-resolved partial discharge (PRPD) diagrams with a single dominant partial discharge (PD) source, preparing them for automatic artificial-intelligence-based classification. It was designed to mitigate several sources of distortions often observed in PRPDs obtained from fully operational hydroelectric generators. The capabilities of the denoising algorithm are the automatic removal of sparse noise and the suppression of non-dominant discharges, including those due to crosstalk. The input features are functions of PD distributions along amplitude and phase, which are calculated in a novel way to mitigate random effects inherent to PD measurements. The impact of the proposed contributions was statistically evaluated and compared to classification performance obtained using formerly published approaches. Higher recognition rates and reduced variances were obtained using the proposed methods, statistically outperforming autonomous classification techniques seen in earlier works. The values of the algorithm’s internal parameters are also validated by comparing the recognition performance obtained with different parameter combinations. All typical PD sources described in hydro-generators PD standards are considered and can be automatically detected.

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