Condition Monitoring of Railway Pantograph Using R-CNN and Image Processing

초록

A railway pantograph supplies a vehicle with the electric power from the OCL (Overhead Contact Line). The contact strip, which directly contacts the OCL, is vulnerable to wear and should be periodically replaced to prevent accidents from power outages. To that end, the pantograph is regularly checked visually during routine maintenance, along with the panhead which includes the horn and the contact strip. However, real-time monitoring is still difficult, and a reliable method needs to be developed. The existing methods use image processing to detect the actual condition of the contact strip. In this paper, we suggest a method for detecting the wear size of the contact strip using image processing and deep learning. In addition, we demonstrate how to assess the condition of the panhead and the horn in the contact. The monitoring equipment is built on the test bed and is automatically configured to acquire images of the moving pantograph. The tilt of the panhead is estimated from image recognition and the condition of the horn is assessed with deep learning. In the future, this method can be used not only for efficient pantograph maintenance but also for determining the performance according to the contact condition.

키워드