Engineering experiments demonstrate improved ice coverage detection and de-icing efficiency using enhanced YOLOv7, highlighting its engineering value.
Aiming at the ice coating problem on medium-voltage overhead lines, this paper proposes a resonance de-icing device based on an improved YOLOv7 algorithm to achieve efficient and intelligent ice detection and removal. First, by introducing the SimAM three-dimensional attention mechanism to optimize feature extraction capability, combining the MPDIoU loss function to enhance bounding box regression accuracy, and designing a task-specific context decoupling head to separate classification and regression tasks, the ice detection accuracy and real-time performance are significantly improved. Second, an integrated ice observation/de-icing device is developed, which incorporates the improved YOLOv7 visual detection algorithm and a resonance vibration module. Through a dynamic frequency optimization strategy, precise matching between the excitation frequency and the inherent frequency of the conductor is achieved. The findings from the engineering experiments demonstrate that the de-icing apparatus conceptualized in this study is capable of effectively identifying the condition of ice-covered conductors and de-icing them. This research presents a novel technical solution for the intelligent de-icing of overhead lines, which holds significant value for engineering applications.
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Ma et al. (2025) studied this question.
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