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• W2990071526 startingPage "180935" @default.
• W2990071526 abstract "To ensure the safe operation of high-speed trains, catenary anomaly detection and alerting security have become an urgent problem to solve. In this paper, we propose a novel method for abnormal behavior localization of a pantograph-catenary for high-speed trains. First, a modified faster RCNN is proposed to detect the pantograph faults. By adjusting the parameters of the faster RCNN, the positional accuracy of the candidate box and accuracy of the algorithm are guaranteed. We perform the arc detection after detecting the pantograph head area. The detection accuracy is over 99%. The height of the pantograph center point is also obtained during detection. Then, the actual running mileage of the fault point is calculated. Experiments show that the method proposed in this paper is also applicable to various complex scenes and that this method can determine the fault localization in the shortest time, narrow the maintenance scope, and improve the overhaul efficiency." @default.
• W2990071526 created "2019-12-05" @default.
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• W2990071526 date "2019-01-01" @default.
• W2990071526 modified "2023-10-15" @default.
• W2990071526 title "Novel Vision-Based Abnormal Behavior Localization of Pantograph-Catenary for High-Speed Trains" @default.
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• W2990071526 doi "https://doi.org/10.1109/access.2019.2955707" @default.
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