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IMPROVED YOLOV3 ALGORITHM for Pantograph safety state detection

Abstract: The pantograph is a critical component that connects the rolling stock to the power supply grid, so the safety status of the pantograph is vital to the smooth and stable operation of the rolling stock. In this paper, by analyzing frame by frame, the pantograph video images monitored by the on-board video monitoring system, the safety status of the pantograph is monitored in real-time by modifying the YOLOV3 target recognition algorithm widely used in industry to identify structural abnormalities, sparks, and foreign object intrusion of the pantograph at the same time. Experiments have proven that a single channel can reach 40fps on a Tienuo on-board intelligent analysis server. The comprehensive detection accuracy mAP@0.5 can get 98%, achieving real-time and relatively accurate detection results.

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