The contact wire wear is an important parameter to ensure the safety operation of electric railways. The contact wire may break if the wear is serious, which leads to transportation interruptions. This study proposes an optical measurement method of contact wire wear, using stereovision technology. The matching method of stereovision based on line-scan cameras is proposed. A lookup-table method is developed to exactly determine the image resolution caused by the contact wire being in different spatial positions. The wear width of the contact wire is extracted from catenaries’ images, and the residual thickness of the contact wire is calculated. The method was verified by field tests. The round-robin tests of the residual thickness at the same location present excellent measurement repetitiveness. The maximum difference value between dynamic test results and ground measurement results is 0.13 mm. This research represents a potential way to implement condition-based maintenance for contact wire wear in the future in order to improve the maintenance efficiency and ensure the safety of catenary infrastructure.

Defects on catenary components are a major part of device faults as a result of a much higher tension on high-speed catenary, such as looseness of bolts, component broken, and component missing. Traditional inspection on catenary components has to be performed only at night with human eyes. Not only the inspection speed is very slow but also the inspection results are not reliable, as a result of the poor lighting environment and long-time working tiredness. In this chapter, we present an automatic visual inspection system for checking the status of components on catenary. A dedicated designed camera system is mounted on an inspection car, which covers almost all the components to be checked and gives great details of each component. Considering the great data storm at each catenary post, high-performance servers with GPU acceleration are used, and technologies of multi-thread and parallel computing are exploited. Furthermore, an intelligent analysis framework is proposed, which uses structural analysis to localize each component in the image and perform automatic detection based on different features such as geometry, texture, and logic rules. The system has been successfully used in China’s high-speed railways, which shows great advantages in the catenary inspection application.