吴君鹏,唐少博,李相磊,张师.一种改进的基于卷积神经网络的绝缘子检测算法研究[J].电测与仪表,2022,59(5):116-122. Wu Junpeng,Tang Shaobo,Li Xianglei,Zhang Shi.Research on an improved insulator detection algorithm based on convolutional neural network[J].Electrical Measurement & Instrumentation,2022,59(5):116-122.
一种改进的基于卷积神经网络的绝缘子检测算法研究
Research on an improved insulator detection algorithm based on convolutional neural network
Aiming at the problem of the misdetection or omission caused by the different sizes and scales of target images and the mutual occlusion of target images caused by the shooting angle, an improved detection method of insulator images based on convolutional neural network is proposed in this paper. Firstly, the lightweight ZF network is adopted to achieve feature extraction, and then, the optimized anchor window ratio is determined to improve the detection accuracy of the target image. Finally, the NMS post-processing algorithm is improved, and a multi-stage penalty factor algorithm is proposed, which is suitable for complex situations such as multi-scale, multi-ratio and overlapping insulators. Experimental results show that the improved detection method of Faster R-CNN increases the AP from 0.797 7 to 0.905 8, which significantly improves the detection accuracy of insulator target image, and reduces the probability of insulator omission and misdetection.
