An Image-Based Online Monitoring System for Pantograph Wear and Attitude
Xiaowen Yao, Zongyi Xing, Andong Sheng, Yuejian Chen
Abstract
The pantograph is one of the most critical electrical equipment in the electric locomotive as it transmits power from the contact wire to the locomotive. Condition monitoring of the pantograph is important to ensure the safe and consistent operation of a train. However, condition monitoring of the pantograph is difficult due to the complex lighting situation and background environment around the pantograph. In this paper, we propose an image-based online monitoring system for pantograph wear and attitude. First, the working principle of the system is introduced. Second, an evaluation method of sliding plate wear state is presented. The wear curves are extracted based on image processing algorithms such as the sliding plate positioning and edge detection. Four criteria are calculated from the wear curves to evaluate four wear types. Then, a pantograph head attitude monitoring method based on pantograph horn boundary points extraction is introduced. After the pantograph horn detection, the horn boundary points are extracted to calculate the attitude parameters and then evaluate whether the pantograph head attitude is normal. The system was implemented in Feieling metro station, Guangzhou Metro Line 9, China, and system performance was analyzed using real-time pantograph images. The experimental results shown that the proposed system can detect the four wear types of the sliding plate and monitor the attitude of the pantograph head with a higher accuracy and better repeatability compared to other systems and manual measurements.