Hybrid Algorithm Based on Machine Learning and Deep Learning to Identify Ceramic Insulators and Detect Physical Damages

This work proposes a hybrid algorithm that is based on machine and deep learning algorithms. The paper studied and implemented an Aggregate Channel Feature and Semantic Segmentation to identify the existence of a ceramic insulator in an image, then pass a cropped image to a deep learning classifier to diagnose the insulators’ health status. The Artificial Intelligence networks were developed via a reliable database that consisted of thousands of images. The work concludes with a comparison and evaluation of the performance between the developed object detection techniques.