Pattern recognition techniques for power transformer insulation diagnosis-a comparative study part 1: framework, literature, and illustration

Abstract

The condition of the insulation system of a power transformer has a significant impact on its overall reliability and serviceability. Transformer oil tests including breakdown voltage, acidity, dielectric dissipation factor, 2-furfuraldehyde, water content, and dissolved gases analysis have been commonly performed in utility companies to provide information regarding the conditions of transformer insulation. Over the past two decades, various pattern recognition techniques are proposed to interpret the oil tests results and make diagnosis on transformer insulation. However, there are still considerable challenging issues to be investigated before the pattern recognition technique can become a ready-to-use tool at utility companies. This paper provides a comparative study of pattern recognition techniques for power transformer insulation diagnosis using oil tests results. A general pattern recognition application framework will be outlined in the paper. And a comprehensive literature review on various pattern recognition techniques for transformer insulation diagnosis will be provided in the paper. The important issues for improving the applicability of pattern recognition techniques for transformer insulation diagnosis will also be discussed. A case study will be presented to demonstrate the procedure of applying pattern recognition techniques to practical transformer insulation diagnosis using oil test results. Copyright (c) 2014 John Wiley & Sons, Ltd.