基于轻量级双层金字塔结构的伞裙破损检测算法

在无人机电力线路巡检系统中，针对伞裙破损检测的准确性和实时性，该文提出了一种基于双层金字塔结构的轻量级伞裙破损检测算法，通过充分提取图片中高低级语义特征，可有效防止有用信息被过滤。同时，利用多通道特征增加了模型特征表达能力。此外，该文还利用深度可分离卷积来优化卷积内核性能，使其可以在低功耗嵌入式系统上实时运行。实验结果表明，该算法在不同光照、拍摄角度和破损模糊条件下，对伞裙破损检测均有较好的准确性、实时性和鲁棒性。

A Lightweight Double-Layer Pyramid Structure based on Insulator Skirt Damage Detection Algorithm

In order to meet the requirements for the accuracy and efficiency of the insulator skirt damage detection in the field of UAV power inspection, a lightweight insulator skirt damage detection algorithm based on a double-layer pyramid structure is proposed in this paper. To avoid the filtering of useful information, the proposed method utilized both high-level and low-level semantic features from images. Simultaneously, multi-channel feature extraction is used to increase the feature expression ability of the model. In addition, deep separable convolution is employed to optimize the performance of the convolution kernel for real-time operation on a low-power embedded front-end. Experimental results show that the proposed algorithm has good accuracy, real-time performance and robustness for the insulator skirt damage detection under different working conditions.