Journal
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 72, Issue -, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2023.3238742
Keywords
Power transmission lines; Object detection; Fitting; Monitoring; Feature extraction; Image processing; Transmission line measurements; Attention mechanism; Deformable YOLOX; dense small-target detection; image processing; multiscale feature fusion; transmission line connection fittings
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This article proposes a target detection model based on an image processing hierarchical algorithm. It constructs a dense small-target detection network suitable for a complex environment through anchor-free and decoupled head design ideas, ASFF multiscale information feature fusion strategy, and ECA + VariFocal Loss interactive saliency area capture strategy. The experimental results show that Deformable YOLOX outperforms 13 current advanced target detection algorithms in comprehensive performance. Combined with a target detection algorithm, an early warning algorithm for rust grade assessment of connecting fittings is proposed, and an online monitoring system is designed, which has practical engineering application value.
Dense distribution and significant size difference of transmission line connecting fittings are difficult to maintain, and long-term exposure to the outdoor environment is vulnerable to adverse environmental effects of rust failure. The common image processing methods and deep learning algorithms are not competent for this kind of dense small-target detection task, so the target detection model based on an image processing hierarchical algorithm is proposed in this article, which uses anchor-free and decoupled head design ideas, through ASFF multiscale information feature fusion strategy and ECA + VariFocal Loss interactive saliency area capture strategy to construct a dense small-target detection network suitable for a complex environment. The experimental results show that the comprehensive performance of Deformable YOLOX is superior to 13 current advanced target detection algorithms. Compared with the baseline model, Deformable YOLOX can better understand the multiscale semantic information of the image and learn the small details that are more difficult to distinguish. Combined with a target detection algorithm, an early warning algorithm for rust grade assessment of connecting fittings is proposed, and an online monitoring system is designed, which has practical engineering application value.
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