IMPROVING THE ACCURACY OF DGA INTERPRETATION FOR DETECTION OF INCIPIENT FAULTS USING MATLAB GUI

Dissolved Gas Analysis (DGA) is the powerful method used for supervising the condition of power transformer. DGA has become so accurate and reliable that it is globally used as a method for identifying the early faults to prevent further damage to the power transformers. These early faults primarily occur because of the electrical and thermal stresses causing the insulating paper and transformer oil to decompose. This decomposition leads to the generation of several gases which comprises of hydrogen, methane, acetylene, ethylene and ethane, while paper deterioration causes generation of carbon monoxide and carbon dioxide that may affect the performance of the power transformer. The concentrations of the generated gases are useful in determining the fault type and its acuteness. There exists various methods to interpret the DGA results and these are methods are known as DGA interpretation methods which include; Key Gas method, Doernenburg Ratio method, Rogers Ratio method, IEC Ratio method and Duval Triangle method. This paper presents the development and implementation of computational tool to automate the diagnosis and prediction of transformer faults. A MATLAB GUI program based on the combined use of traditional criteria of DGA published in IEEE standard guidelines. In this paper four existing DGA interpretation methods i.e. Doernenburg Ratio method, Rogers Ratio method, IEC Ratio method and Duval Triangle method are used to obtain desired results. The MATLAB GUI gives a visual display of the fault types as predicted by all the above mentioned DGA interpretation methods in a single frame. The results obtained are promising in predicting the correct incipient faults in transformer with an accuracy of 86.67%.