Statistical Analysis of the Partial Discharge Data for the Classification of Transformer Oil

被引：0

作者：

Tharamal, Lakshmi ^{[1
]}

Preetha, P. ^{[1
]}

Sindhu, T. K. ^{[1
]}

机构：

[1] Natl Inst Technol, Calicut, Kerala, India

来源：

2021 96TH IEEE CONFERENCE ON ELECTRICAL INSULATION AND DIELECTRIC PHENOMENA (CEIDP 2021) / 16TH IEEE NANOTECHNOLOGY MATERIALS AND DEVICES CONFERENCE (IEEE NMDC 2021) | 2021年

关键词：

transformer oil; partial discharge measurements; histogram similarity measures; classification;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Statistical analysis of the Partial Discharge (PD) data is proposed for the quality assessment of the transformer oil. Initially, the PD data is represented as X and Y marginal histograms and the Histogram Similarity Measures (HSM) are adopted for the supervised classification of the transformer oil. Three different HSM techniques: cross-correlation, Chi-square and the Kolmogorov-Smirnov tests are employed. 45 transformer oil samples collected from the State Electricity Board are used for the classification of the oil samples to Class 1, Class 2 and Class 3 as per IEEE C.57.106-2006 standard. The proposed statistical method using the Chi-square test classifies the oil samples with an accuracy of 100%, proving its superior performance over any other physical, chemical or electrical tests suggested in the literature.

引用

页码：204 / 207

页数：4

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