Artificial Neural Network Assisted Digital Image Processing to Determine the Hydrophobicity of Polymeric Materials

Abstract

Hydrophobicity of polymeric insulators of high power transmission line is an important property because it is a good monitor of aging of polymeric outdoor insulator. An employee on the high-voltage transmission line makes this procedure during operation, which can lead to injuries and incorrect estimation of the insulator integrity. In this way, digital image processing is a promising and objective tool to analyze the polymer surface. In this study, two thousand pictures were taken from the wetted insulator surface and analyzed by artificial neural network assisted digital image processing. The neural network used is based on back-propagation method, and Haralicks descriptors were used to quantify the hydrophobic aspect of various polymeric aged surfaces.