U-Net-Based Segmentation for Electrical Lines and Its Application to Real-Time Maintenance Algorithm for Electricity Facilities

Abstract

Inspections for maintenance of electricity facility are performed by patrols which are always in a potentially dangerous traffic accident. In this study, we address the inspection procedure with leveraging advanced deep learning algorithms on images for patrollers to focus on driving to reduce the danger, assuming that facility images are obtained by photographing automatically with a monocular camera during patrols. Toward the goal with restriction of our concerns on an electrical line and related devices, it is initially proposed a new image segmentation algorithm for electrical lines, U-Net-based CNN model, which can be used as a basic step of real-time maintenance algorithms for electricity facilities. It is then introduced a novel inference algorithm for the connectivity between an insulator and an electrical line, as one realization of real-time maintenance algorithms. Experiments demonstrate that the both proposed algorithms are effective and efficient enough to be feasible for real-time algorithms. The proposed methods expect not only to help dangerous labor done by patrollers but also to save lots of money and time by products. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.