Power transformer incipient faults diagnosis using Dissolved Gas Analysis and Rough Set

Dissolved Gas Analysis (DGA) is standard technique to detect and diagnose power transformer incipient faults. Many methods based on DGA have been proposed such as Duval Triangle, IEC, Roger´s Ratio, Key Gases, etc. The relationship between gas and type of faults is difficult to model and highly non-linear. Knowledge Discovery from Data (KDD) based on Rough Set Theory (RST) can be used to find that relationship. Thus RST is used in this research. The objective of this research is to diagnose incipient fault of power transformer. The diagnosis method is using DGA and RST. All of possible gas ratios are used as input to determine types of fault. The value of gas ratios are discretized before being processed with Rough Set Theory (RST). The number of input attributes is reduced using RST. The knowledge is extracted in the form of IF-THEN rules. The extracted and reduced rules are used to diagnose the incipient faults of power transformer. The resulting rules have the accuracy of 81.25%.