LEADER 03638nam 2200553 450 001 9910686480303321 005 20230731000155.0 010 $a981-9909-53-8 024 7 $a10.1007/978-981-99-0953-7 035 $a(CKB)5840000000241903 035 $a(DE-He213)978-981-99-0953-7 035 $a(MiAaPQ)EBC7236673 035 $a(Au-PeEL)EBL7236673 035 $a(PPN)269658025 035 $a(EXLCZ)995840000000241903 100 $a20230731d2023 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep learning-based detection of catenary support component defect and fault in high-speed railways /$fZhigang Liu, Wenqiang Liu, and Junping Zhong 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore Pte Ltd.,$d[2023] 210 4$dİ2023 215 $a1 online resource (XIII, 239 p. 212 illus., 149 illus. in color.) 225 1 $aAdvances in High-speed Rail Technology,$x2363-5029 311 $a981-9909-52-X 320 $aIncludes bibliographical references. 327 $aOverview of Catenary Detection of Electrified Railways -- Advance of Deep Learning -- Catenary Support Components and their Characteristics in High-speed Railways -- Preprocessing of Catenary Support Components? Images -- Positioning of Catenary Support Components -- Detection of Catenary Support Component Defect and Fault -- Detection of The parameters of Catenary Support Devices based on 3D Point Clouds. 330 $aThis book focuses on the deep learning technologies and their applications in the catenary detection of high-speed railways. As the only source of power for high-speed trains, the catenary's service performance directly affects the safe operation of high-speed railways. This book systematically shows the latest research results of catenary detection in high-speed railways, especially the detection of catenary support component defect and fault. Some methods or algorithms have been adopted in practical engineering. These methods or algorithms provide important references and help the researcher, scholar, and engineer on pantograph and catenary technology in high-speed railways. Unlike traditional detection methods of catenary support component based on image processing, some advanced methods in the deep learning field, including convolutional neural network, reinforcement learning, generative adversarial network, etc., are adopted and improved in this book. The main contents include the overview of catenary detection of electrified railways, the introduction of some advance of deep learning theories, catenary support components and their characteristics in high-speed railways, the image reprocessing of catenary support components, the positioning of catenary support components, the detection of defect and fault, the detection based on 3D point cloud, etc. 410 0$aAdvances in High-speed Rail Technology,$x2363-5029 606 $aDeep learning (Machine learning) 606 $aFault location (Engineering) 606 $aHigh speed trains 615 0$aDeep learning (Machine learning) 615 0$aFault location (Engineering) 615 0$aHigh speed trains. 676 $a006.31 700 $aLiu$b Zhigang$0739891 702 $aLiu$b Wenqiang 702 $aZhong$b Junping 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910686480303321 996 $aDeep Learning-Based Detection of Catenary Support Component Defect and Fault in High-Speed Railways$93334635 997 $aUNINA