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Pregled bibliografske jedinice broj: 622328

Inference Model for Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis


Banović, Mladen; Maljković, Zlatko; Sanchez, Jean
Inference Model for Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis // International review on modelling and simulations, 5 (2012), 6; 2610-2617 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 622328 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Inference Model for Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis

Autori
Banović, Mladen ; Maljković, Zlatko ; Sanchez, Jean

Izvornik
International review on modelling and simulations (1974-9821) 5 (2012), 6; 2610-2617

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Fault diagnosis; Inference Mechanisms; Power Transformers

Sažetak
Reliability of electricity delivery is highly related to condition of power system equipment, like power transformers. Lot of real-time data are being collected using existing solutions for transformer condition monitoring, but interpretation of these data and condition assessment are challenging. Therefore, R&D efforts are directed toward solutions for automatic diagnosis inference, but experience shows that besides diagnosis (condition), users need also diagnosis probability and tools for validation of obtained diagnosis to be able to make reliable decisions. This paper presents a new model of automatic diagnosis for power transformers on basis of dissolved gas analysis. The model uses eight interpretation methods as voters, and developed voting algorithm estimates probability of each diagnosis and proposes final diagnosis. Using variable diagnosis resolution of model it is possible to validate obtained diagnosis. Besides usual tests on sets of DGA data from different transformers, the model in this research was subjected to tests on historical data from transformers to verify consistency of diagnostic model on DGA data set from certain transformer. All tests showed promising results.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Projekti:
036-0361616-1617 - Revitalizacija i pogon hidrogeneratora (Maljković, Zlatko, MZOS ) ( CroRIS)
275-0361616-1620 - Nove strukture poboljšanja dinamičke stabilnosti hidroagregata (Milković, Mateo, MZO ) ( CroRIS)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Zlatko Maljković (autor)

Avatar Url Mladen Banović (autor)


Citiraj ovu publikaciju:

Banović, Mladen; Maljković, Zlatko; Sanchez, Jean
Inference Model for Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis // International review on modelling and simulations, 5 (2012), 6; 2610-2617 (međunarodna recenzija, članak, znanstveni)
Banović, M., Maljković, Z. & Sanchez, J. (2012) Inference Model for Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis. International review on modelling and simulations, 5 (6), 2610-2617.
@article{article, author = {Banovi\'{c}, Mladen and Maljkovi\'{c}, Zlatko and Sanchez, Jean}, year = {2012}, pages = {2610-2617}, keywords = {Fault diagnosis, Inference Mechanisms, Power Transformers}, journal = {International review on modelling and simulations}, volume = {5}, number = {6}, issn = {1974-9821}, title = {Inference Model for Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis}, keyword = {Fault diagnosis, Inference Mechanisms, Power Transformers} }
@article{article, author = {Banovi\'{c}, Mladen and Maljkovi\'{c}, Zlatko and Sanchez, Jean}, year = {2012}, pages = {2610-2617}, keywords = {Fault diagnosis, Inference Mechanisms, Power Transformers}, journal = {International review on modelling and simulations}, volume = {5}, number = {6}, issn = {1974-9821}, title = {Inference Model for Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis}, keyword = {Fault diagnosis, Inference Mechanisms, Power Transformers} }

Časopis indeksira:


  • Scopus


Uključenost u ostale bibliografske baze podataka::


  • Academic Search Complete - EBSCO Information Services
  • Cambridge Scientific Abstracts - CSA/CIG
  • Elsevier Bibliographic Database SCOPUS
  • Index Copernicus





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