Investigation of High-Voltage Insulator Surface Conditions based on Machine Learning TensorFlow

Salama Manjang

Abstract


The insulator plays an essential role in preventing the flow of current from the phase conductor to the earth through supporting towers so that the insulation is a significant part of the electrical energy transmission system. Generally, high-voltage insulators are widely used as external plug insulators, for that the performance of insulators is influenced by environmental conditions that indirectly affect the surface condition of the insulators. In this study, a diagnostic tool used in the testing surface of the insulator, which can classify mechanically whether the insulator is good or damaged. The classification method uses TensorFlow Machine learning. Machine Learning is used as a brain in the isolation classification process while TensorFlow functions to store training data and test data in the classification process. The results obtained from this study show the accuracy of classification data is 98%.

Keywords


Insulator; Image processing; Machine Learning; TensorFlow;

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DOI: http://dx.doi.org/10.31963/intek.v7i1.2053

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