Abstract
In practice, the condition state of Power Transformers (PT) is quantified by using Health Index (HI). This paperanalyzes and compares three different state-of-the-art algorithms to compute HI. The first one uses a Weighted SumModel (WSM), the second is based on a Fuzzy Inference System (FIS), and the third combines both techniques, i.e.,WSM and FIS. These three approaches are tested in a PT fleet composed of 30 units. Results show that eachapproach produces different HI values for the same PTs. Therefore, decision making regarding the PT fleet willdepend on the selected approach for HI calculation. This work proposes merging the knowledge involved in eachanalyzed approach by using a K-means clustering technique to overcome this drawback. This solution could help theasset manager to make adequate decisions regarding the maintenance scheduling of PT when there is uncertaintyabout the appropriate approach to be selected.
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