A New Transmission Line Foreign Object Detection Network Structure: TLFOD Net

doi:10.3969/j.issn.1006-2475.2019.02.021

Abstract

Abstract: Floating foreign bodies suspended on high voltage transmission lines may cause great harm to power transmission, but the existing object detection methods can not effectively identify irregular objects. This paper proposes a new network structure for foreign body detection: TLFOD Net (Transmission Line Foreign Object Detection Net). According to the characteristics of foreign bodies, this paper designs the TLFOD Net network structure, which mainly includes feature extraction network, region proposal network and classified regression network, optimizes suitable candidate boxes and proposes end-to-end joint training mode to improve the performance of TLFOD Net. Through image reversal technology, the number of training sets is increased. The experimental results show that TLFOD Net improves the detection speed and accuracy significantly compared with the existing networks.

Key words: transmission line, foreign object detection, deep learning, TLFOD Net

CLC Number:

TP312

SHEN Mao-dong1, PEI Jian1, FU Xin-yang1, ZHANG Jun-ling1, GONG Fan-kui1, LIU Xia2. A New Transmission Line Foreign Object Detection Network Structure: TLFOD Net[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.02.021.

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