Paper Insulation Aging Estimation Using Swept-Source Optical Coherence Tomography

Abstract

In this article, an algorithm that uses subsurface structural images, obtained by swept-source optical coherence tomography (OCT), is developed to estimate the aging of insulation paper. Swept-source OCT, a novel and noninvasive diagnostic technique, is used to study the subsurface morphological changes in thermally stressed paper insulation. Obtaining subsurface structural images of the insulation paper enables an accurate estimation of the age of thermally deteriorated insulation paper. Accelerated thermal aging is employed to generate samples of oil-impregnated insulation paper with different levels of deterioration. Textural features, based on a spatial grayscale-level dependence matrix (SGLDM) obtained from the OCT images, are used to estimate the aging time of insulation paper based on changes in the subsurface morphology of the paper. Principal component analysis (PCA) is applied to the feature sets to reduce its dimension. The PCA output is then used to construct the age estimation model, and the leave-one-out-cross-validation (LOOCV) method is used to assess the estimation performance of the fitted model. The results of this work demonstrate that the development of OCT-equipped scanning probes to assess the condition of paper insulation is promising.