Particle swarm based arc detection on time series in pantograph-catenary system. Aydın, İ, Yaman, O., Karaköse, M., & Çelebi, S. B. In 2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings, pages 344–349, June, 2014. doi abstract bibtex Pantograph-catenary system is the most important component for transmitting the electric energy to the train. If the faults have not detected in an early stage, energy can disrupt the energy and this leads to more serious faults. The arcs occurred in the contact point is the first step of a fault. When they are detected in an early stage, catastrophic faults and accidents can be avoided. In this study, a new approach has been proposed to detect arcs in pantograph-catenary system. The proposed method applies a threshold value to each video frame and the rate of sudden glares are converted to time series. The phase space of the obtained time series is constructed and the arc event is found by using particle swarm optimization. The proposed method is analyzed by using real pantograph-videos and good result have been obtained.
@inproceedings{aydin_particle_2014,
title = {Particle swarm based arc detection on time series in pantograph-catenary system},
doi = {10.1109/INISTA.2014.6873642},
abstract = {Pantograph-catenary system is the most important component for transmitting the electric energy to the train. If the faults have not detected in an early stage, energy can disrupt the energy and this leads to more serious faults. The arcs occurred in the contact point is the first step of a fault. When they are detected in an early stage, catastrophic faults and accidents can be avoided. In this study, a new approach has been proposed to detect arcs in pantograph-catenary system. The proposed method applies a threshold value to each video frame and the rate of sudden glares are converted to time series. The phase space of the obtained time series is constructed and the arc event is found by using particle swarm optimization. The proposed method is analyzed by using real pantograph-videos and good result have been obtained.},
booktitle = {2014 {IEEE} {International} {Symposium} on {Innovations} in {Intelligent} {Systems} and {Applications} ({INISTA}) {Proceedings}},
author = {Aydın, İ and Yaman, O. and Karaköse, M. and Çelebi, S. B.},
month = jun,
year = {2014},
keywords = {Arc detection, Computational modeling, Image edge detection, Particle swarm optimization, Strips, Time series analysis, Wires, accidents, arc event, arcs (electric), cameras, catastrophic fault detection, contact point, electric energy, fault diagnosis, image segmentation, object detection, pantograph-catenary system, pantographs, particle swarm based arc detection, particle swarm optimisation, phase space, power engineering computing, railway electrification, real pantograph-videos, time series, traffic engineering computing, video frame, video signal processing},
pages = {344--349}
}
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