Paper Info
Title
Issd: Improved Ssd For Insulator And Spacer Online Detection Based On Uav System
Abstract
In power inspection tasks, the insulator and spacer are important inspection objects. UAV (unmanned aerial vehicle) power inspection is becoming more and more popular. However, due to the limited computing resources carried by a UAV, a lighter model with small model size, high detection accuracy, and fast detection speed is needed to achieve online detection. In order to realize the online detection of power inspection objects, we propose an improved SSD (single shot multibox detector) insulator and spacer detection algorithm using the power inspection images collected by a UAV. In the proposed algorithm, the lightweight network MnasNet is used as the feature extraction network to generate feature maps. Then, two multiscale feature fusion methods are used to fuse multiple feature maps. Lastly, a power inspection object dataset containing insulators and spacers based on aerial images is built, and the performance of the proposed algorithm is tested on real aerial images and videos. Experimental results show that the proposed algorithm can efficiently detect insulators and spacers. Compared with existing algorithms, the proposed algorithm has the advantages of small model size and fast detection speed. The detection accuracy can achieve 93.8%. The detection time of a single image on TX2 (NVIDIA Jetson TX2) is 154 ms and the capture rate on TX2 is 8.27 fps, which allows realizing online detection.
Year
DOI
Venue
2020
10.3390/s20236961
SENSORS
Keywords
DocType
Volume
SSD, insulator, spacer, object detection, UAV, power inspection
Journal
20
Issue
ISSN
Citations 
23
1424-8220
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
ying liu136446.92
Li Yong226229.92
Feng Shuang300.34
Fang Gao400.34
Xiang Zhou500.34
Xingzhi Chen600.34