Abstract
Condition monitoring data in the form of oil test results are important for transformer ageing assessment and asset management. Analysis of variance-based factorial analysis was demonstrated as a data mining technique for identifying the influence of different factors on transformer ageing. Using a UK oil test database of 33/11(or 6.6) kV transformers, studies were performed to assess the influence of in-service age, manufacturer, year of manufacture, load and environment on the measured oil acidity. This methodology can reduce the workload of manually performing pairwise comparisons to understand the influence of each factor. In addition, it can also consider any interaction effect present among the factors. As a demonstration, influence of the year of manufacture on oil acidity was revealed, which was confirmed by identifying a change in design for late 1960s units and an early degradation phenomenon for late 1980s units.
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