Pregled bibliografske jedinice broj: 418442
Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis – First Level of Diagnosis Using VAC and VEV Inference Methods
Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis – First Level of Diagnosis Using VAC and VEV Inference Methods // MIPRO 2009 32nd International Convention / Bogunović Nikola, Ribarić Slobodan (ur.).
Opatija: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2009. str. 244-248 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 418442 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Automatic Diagnosis of Power Transformers Based on Dissolved Gas Analysis – First Level of Diagnosis Using VAC and VEV Inference Methods
Autori
Banović, Mladen
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
MIPRO 2009 32nd International Convention
/ Bogunović Nikola, Ribarić Slobodan - Opatija : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2009, 244-248
ISBN
978-953-233-045-8
Skup
Intelligent Systems
Mjesto i datum
Opatija, Hrvatska, 25.05.2009. - 29.05.2009
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
automatic diagnosis; power transformer; inference method; dissolved gas analysis
Sažetak
Assessment of power transformer condition became very important for utilities, to ensure continuous power transmission and power supply. Therefore, different techniques are in use for better condition assessment, as offline diagnostics and on-line monitoring systems. The off-line diagnostics has some time period between consecutive diagnoses, and during this period the equipment condition is unknown. Diagnostic tools in monitoring system usually comprise comparison of values of monitored quantities to preset limits, and alarming if these limits are exceeded. In this way weak diagnostic capabilities are achieved. Therefore, a new diagnosis model for assessment of condition of oil immersed power transformers was developed. This model is aimed to continuously and automatically diagnose transformer condition. Principle of the diagnostics is interpretation of dissolved gas analysis results (DGA) using several standardized interpretation methods. Then, on the basis of obtained diagnosis an overall diagnosis is inferred using VAC or VEV inference methods in a similar way as it is done by the human diagnostician. The diagnostic model shows excellent application flexibility, high robustness and acceptable diagnostic accuracy.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Informacijske i komunikacijske znanosti
