Electrical Control Equipment Patrol Inspection Method Based on High Quality Image Recognition Technology

Abstract

In order to ensure the safe, stable, and efficient operation of electrical control equipment, the patrol inspection and maintenance are especially important. Research on electrical control equipment patrol inspection method based on high quality image recognition technology is of great significance, because the method replaces traditional manual patrol inspection to some extent and reduces labor costs. The existing methods based on lowillumination image recognition technology meet the patrol inspection requirements in lowillumination environment to a certain extent, but they still have certain limitations. Therefore, this research aimed to study the electrical control equipment patrol inspection method based on high quality image recognition technology. Electrical control equipment patrol inspection images were enhanced based on Deep Curve Estimation Network (DCEN) in order to improve the visibility of equipment anomaly features, which helped reduce the misjudgment and misdetection risks during the patrol inspection process. The patrol inspection image set was reconstructed in super resolution, and was combined with clear images to construct a new image set, which improved the patrol inspection efficiency. The electrical control equipment detection process based on YOLO V3 was elaborated. The experimental results verified that the proposed method and constructed model in this study were effective.