000			a
999			_c20792 _d20792
003			OSt
005			20240321090750.0
008			240321b xxu||||| |||| 00| 0 eng d
040			_aAIKTC-KRRC _cAIKTC-KRRC
100			_923081 _aModi, Mitul M.
245			_aIntelligent approach to interpret incipient faults of power transformer from DGA database
250			_aVol.104(4), Aug
260			_aUSA _bSpringer _c2023
300			_a869-876p.
520			_aPower transformer is most powerful and expensive tool in power system for transmitting and distributing electrical energy to all consumers. High-voltage transformers in power system are oil-immersed type transformer. Use of oil provides much needed cooling, insulation, and reduces vibrations to power transformer. Oil of the power transformer is monitored and diagnosed on a regular basis to preserve its dependability and efficiency. Dissolved gas analysis (DGA) is effective and efficient tools to interpret incipient faults. In DGA method, dissolved gases like H, CH, CH, CH, CH are extracted from oil. Based on the gases threshold values in oil, different faults are identified. The current article focus on three traditional fault diagnostic methods IEC, Roger ratio, and Duval triangle and one artificial neural network-based intelligent method. Result spot light that intelligent methods gives higher accuracy and consistency to identify the incipient faults of power transformer while traditional methods are proved inadequate, inaccurate and inconsistent.
650		0	_94642 _aHumanities and Applied Sciences
700			_923082 _aPatel, Rakesh A.
773	0		_x2250-2106 _tJournal of the institution of engineers (India): Series B
856			_uhttps://link.springer.com/article/10.1007/s40031-023-00891-2 _yClick here
942			_2ddc _cAR