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First Name:
Venera
Last Name:
Nurmanova
Datasets & Competitions
Regular and rigorous inspection of outdoor insulators is essential for uninterrupted power grid operation. Recent advances in computer vision enabled replacing conventional subjective, costly, and inefficient visual insulator inspection with automated diagnosis from unmanned aerial vehicle (UAV) taken images. In this study, advanced computer vision algorithms, namely, family of YOLOv3 and YOLOv5 architectures, are trained and compared for classification of frequently encountered insulator mechanical faults from UAV images.
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64 Views
Distribution and power transformers are essential components of any electricity network, hence electrical and mechanical safety of the transformer unit is among the highest concerns of electricity providers. Over the course of their operation, transformers face with a wide range of internal and external disturbances which may lead to a partial or full malfunction of the equipment. The service life and condition requirements for distribution and power transformers are now changed and utilities altered their maintenance policy from time-based to condition-based approach.
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104 Views
The project provides trained models of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for outdoor insulator detection and classification of the surface contamination, such as salt, snow, cement, soil and wet soil. The project is based on YOLOv3 implementation developed by Ultralytics/YOLOv3. The models were trained on custom insulator dataset consisting of 11816 images of different type insulators under various conditions.
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59 Views