Identification of Electrical Tree Aging State in Epoxy Resin Using Partial Discharge Waveforms Compared to Traditional Analysis

Schurch, Roger; Munoz, Osvaldo; Ardila-Rey, Jorge Alfredo; Donoso, Pablo; Peesapati, Vidyadhar

doi:10.3390/polym15112461

Cited by 8 publications

(2 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Accordingly, the leakage current threshold values during partial discharge were determined. The peaks of the measured values that exceeded this threshold value for the applied voltage level indicate the commencement of partial discharge and result in signal deterioration [ 19 , 20 , 21 , 22 ].…”

Section: Measurement Methodologymentioning

confidence: 99%

Investigation of Novel Solid Dielectric Material for Transformer Windings

Ersoy,

Atalar,

Aydoğan

2023

Polymers

View full text Add to dashboard Cite

Improvement techniques aimed at enhancing the dielectric strength and minimizing the dielectric loss of insulation materials have piqued the interest of many researchers. It is worth noting that the electrical breakdown traits of insulation material are determined by their electrochemical and mechanical performance. Possible good mechanical, electrical, and chemical properties of new materials are considered during the generation process. Thermoplastic polyurethane (TPU) is often used as a high-voltage insulator due to its favorable mechanical properties, high insulation resistance, lightweight qualities, recovery, large actuation strain, and cost-effectiveness. The elastomer structure of thermoplastic polyurethane (TPU) enables its application in a broad range of high-voltage (HV) insulation systems. This study aims to evaluate the feasibility of using TPU on transformer windings as a solid insulator instead of pressboards. The investigation conducted through experiments sheds light on the potential of TPU in expanding the range of insulating materials for HV transformers. Transformers play a crucial role in HV systems, hence the selection of suitable materials like cellulose and polyurethane is of utmost importance. This study involved the preparation of an experimental setup in the laboratory. Breakdown tests were conducted by generating a non-uniform electric field using a needle–plane electrode configuration in a test chamber filled with mineral oil. Various voltages ranging from 14.4 kV to 25.2 kV were applied to induce electric field stress with a step rise of 3.6 kV. The partial discharges and peak numbers were measured based on the predetermined threshold values. The study investigated and compared the behaviors of two solid insulating materials under differing non-electric field stress conditions. Harmonic component analysis was utilized to observe the differences between the two materials. Notably, at 21.6 kV and 25.2 kV, polyurethane demonstrated superior performance compared to pressboard with regards to the threshold value of leakage current.

show abstract

Section: Measurement Methodologymentioning

confidence: 99%

Investigation of Novel Solid Dielectric Material for Transformer Windings

Ersoy,

Atalar,

Aydoğan

2023

Polymers

View full text Add to dashboard Cite

show abstract

“…In the literature, the conventional use of PRPD patterns is primarily to assess the severity of PD, regarding the amplitude and evolution of discharge levels [24]. PRPD patterns with commercial UHF antenna and PD classifications using the extraction of features from the envelopes of these pulses were performed by [25].…”

Section: Introductionmentioning

confidence: 99%

Classification of Partial Discharge Sources in Ultra-High Frequency Using Signal Conditioning Circuit Phase-Resolved Partial Discharges and Machine Learning

Santos Júnior,

Serres,

Xavier

et al. 2024

Electronics

View full text Add to dashboard Cite

This work presents a methodology for the generation and classification of phase-resolved partial discharge (PRPD) patterns based on the use of a printed UHF monopole antenna and signal conditioning circuit to reduce hardware requirements. For this purpose, the envelope detection technique was applied. In addition, test objects such as a hydrogenerator bar, dielectric discs with internal cavities in an oil cell, a potential transformer and tip–tip electrodes immersed in oil were used to generate partial discharge (PD) signals. To detect and classify partial discharges, the standard IEC 60270 (2000) method was used as a reference. After the acquisition of conditioned UHF signals, a digital signal filtering threshold technique was used, and peaks of partial discharge envelope pulses were extracted. Feature selection techniques were used to classify the discharges and choose the best features to train machine learning algorithms, such as multilayer perceptron, support vector machine and decision tree algorithms. Accuracies greater than 84% were met, revealing the classification potential of the methodology proposed in this work.

show abstract