Deep Learning-Based Detection of Catenary Support Component Defect and Fault in High-Speed Railways

11.04.2023

Englisch

9789819909520

Springer Singapore

Advances in High-speed Rail Technology

Nein

Zhigang Liu, Wenqiang Liu, Junping Zhong

239

Gebundene Ausgabe

Zhigang Liu (IEEE Fellow, IET Fellow, AAIA Fellow) received the Ph.D. degree in Power system and its Automation from Southwest Jiaotong University, China in 2003. He is currently a Full Professor of the School of Electrical Engineering, Southwest Jiaotong University, Chengdu. He is also a Guest Professor of Tongji University. Shanghai. He has authored three books and published more than 200 peer-reviewed journal and conference articles. His research interests include the electrical relationship of EMUs and traction, detection, and assessment of pantograph-catenary in high-speed railway. Dr. Liu is an Associate Editor-in-Chief of IEEE Transactions on Instrumentation and Measurement, Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Vehicular Technology and IEEE Access. He received the IEEE TIM's Outstanding Associate Editors for 2019, 2020 and 2021, and the Outstanding Reviewer of IEEE Transactions on Instrumentation and Measurement in 2018.

High-speed Railway, Pantograph-Catenary System, Automatic Detection, Image Processing, Deep Learning, Convolutional Neural Network, Reinforcement Learning, Generative Adversarial Network, Catenary Support Components, Image Enhancement

TRF - Schienenverkehrstechnik UYQM - Maschinelles Lernen TJF - Elektronik UYS - Digitale Signalverarbeitung (DSP) UN - Datenbanken TNH - Verkehrsingenieurwesen, Verkehrsplanung UYQ - Künstliche Intelligenz

235 mm

15.5 cm