Interpreting DGA Key Gas using Fuzzy OMA3S

This paper discusses about interpreting DGA key gas using Fuzzy OMA3S. DGA key gas data is compared to standard and put into condition group. Each group is given score and is assigned to the corresponding fault in the observation matrix. The next step is to calculate New Knowledge Probability Distribution (NKPD) on each observation, which is the maximum value of a group of sensors that indicates each hypothesis. To show Knowledge growth, NKPD over Time (NKPDT) is used. At the last observation, the hypothesis with the highest value of NKPDT becomes the DoC. The goal of this paper is to compare the crisp logic of the conventional OMA3S and the Fuzzy logic OMA3S in interpreting 6-sensor-4-hypothesis DGA.