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Faulty insulator diagnosis for UAV videos based on repetitiveness feature
Lin L(蔺蘭); Li BF(李冰锋); Wang L(王玲); Cong Y(丛杨); Tang YD(唐延东)
Conference Name3rd International Conference on Applied Mechanics, Materials and Manufacturing, ICAMMM 2013
Conference DateAugust 24-25, 2013
Conference PlaceDalian, China
Source PublicationApplied Mechanics and Materials
PublisherTrans Tech Publications Ltd
Publication PlaceZurich-Durnten, Switzerland
Indexed ByEI ; CPCI(ISTP)
EI Accession number20134416915504
WOS IDWOS:000339363800496
Contribution Rank1
AbstractIn this paper, we proposed a faulty insulator diagnosis method for insulator faulty detection based on repetitiveness feature from UAV video sequence. The repetitiveness feature which describes the relationship of each structural element of insulator is employed for the insulator faulty diagnosis, and is robust to noise, camera motivation and complex backgrounds. Base on the repetition of structural element, our method can not only deal with single insulator with multi-faults, but also work on double insulator strings. The recognition results on insulator dataset and UAV video show the effectiveness of our method. © (2013) Trans Tech Publications, Switzerland.
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Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Corresponding AuthorLin L(蔺蘭)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
2.Benxi power supply company of Liaoning electric power company, Benxi, 117000, China
3.University of Chinese Academy of Sciences, Beijing, 100049, China
4.Henan Polytechnic University, Jiaozuo, China
Recommended Citation
GB/T 7714
Lin L,Li BF,Wang L,et al. Faulty insulator diagnosis for UAV videos based on repetitiveness feature[C]. Zurich-Durnten, Switzerland:Trans Tech Publications Ltd,2013:2536-2542.
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