DGA Interpretation for Increasing the Percent of Accuracy by Bayesian Network Method Comparing IEC TC 10 Database
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2018 by IJETT Journal|
|Year of Publication : 2018|
|Authors : Shalaka Bhimrao Wanjare, P. S. Swami, Dr.A.G.Thosar
|DOI : 10.14445/22315381/IJETT-V62P208|
MLA Style: Shalaka Bhimrao Wanjare, P. S. Swami, Dr.A.G.Thosar "DGA Interpretation for Increasing the Percent of Accuracy by Bayesian Network Method Comparing IEC TC 10 Database" International Journal of Engineering Trends and Technology 62.1 (2018): 46-51.
APA Style:Shalaka Bhimrao Wanjare, P. S. Swami, Dr.A.G.Thosar (2018). DGA Interpretation for Increasing the Percent of Accuracy by Bayesian Network Method Comparing IEC TC 10 Database. International Journal of Engineering Trends and Technology, 62(1), 46-51.
Dissolved gas analysis (DGA) is a method of estimating the presence of dissolved gases in oil of transformer. The health of transformer majorly depends on the state of transformer oil. The percentage of gases dissolve in oil may lead to different faults on transformer. Various methods are used to analyse the faults in transformer like Rogers Ratio Method (RRM), Doernenburgs Ratio Method (DRM), Duval Triangle Method (DTM), Duval Pentagon Method (DPM), and IEC Ratio Method (IRM). Various gases are evolved in transformer. The amount of dissolve gases liberated in transformer oil produces different faults. In transformer oil, usually the gases which are evolved are hydrogen (H), methane (CH4), ethylene (C2H6), acetylene (C2H2), carbon monoxide (CO), carbon dioxide (CO2), nitrogen (N2) and oxygen (O2). This paper proposes DGA interpretation for increasing the per cent of accuracy by Bayesian network.
 Shalaka Bhimrao Wanjare, “DGA interpretation for increasing the percent of accuracy by different methods: A Review,28 March 2018.
 Barin G. Steward, Jose Ignacio Aizpurua, Stephen D. J. McArthur, and Victoria M. Catterson, “ Improving the Accuracy of Transformer DGA Diagnosis in the Presence of Conflicting Evidence,” Electrical insulation conference (EIC), Baltimore, MD,USA.
 M. Duval, "A review of faults detectable by gas-in-oil analysis in transformers," IEEE Electr. Insul. Mag., vol. 18, pp. 8-17, 2002.
 R. R. Rogers, "IEEE and IEC Codes to interpret incipient faults in transformers, using gas in oil analysis," IEEE Trans. Dielectr. Electric Insul. Vol. EI-13, pp. 349-354, 1978.
 "IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers," IEEE Std C57.104-2008, pp. 1-36, 2009.
 K. Spurgeon, W. H. Tang, Q. H. Wu and G. Moss, "Dissolved gas analysis using evidential reasoning," IEE Proceedings - Science, Measurement and Technology, vol. 152, pp. 110-117, 2005.
 M. Duval "Interpretation of gas-in-oil analysis using new IEC publication 60599 and IEC TC 10 databases," IEEE Electr. Insul. Mag., vol. 17, pp. 31-41, 2001
 H.-C. Sun and C.-M. Huang, "A Review of Dissolved Gas Analysis in Power Transformers," Energy Procedia, vol. 14, pp. 12201225, 2012
 A. Abu-Siada and S. Islam, "A new approach to identify power transformer criticality and asset management decision based on dissolved gas-in-oil analysis," Dielectrics and Electrical Insulation, IEEE Transactions on, vol. 19, pp. 1007-1012, 2012.
 M. Duval and J. Dukarm, "Improving the reliability of transformer gasin-oil diagnosis," Electrical Insulation Magazine, IEEE, vol. 21, pp. 2127, 2005.
 S. Corporation, "Serveron White Paper : DGA Diagnostic Methods," 2007.
 M. Duval, "New techniques for dissolved gas-in-oil analysis," Electrical Insulation Magazine, IEEE, vol. 19, pp. 6-15, 2003.
 M. Duval and A. dePabla, "Interpretation of gas-in-oil analysis using new IEC publication 60599 and IEC TC 10 databases," IEEE Electrical Insulation Magazine,vol. 17, pp. 31-41, 2001.
Dissolved Gas Analysis (DGA), transformer fault prediction, graphical user interface (GUI).