**1. Introduction**

Compared with traditional defects on stagger, arc, contact force, etc., defects on catenary components become more and more important on high-speed railways [1]. 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. **Figures 1** and **2** illustrate some typical defects on catenary components.

Traditional inspection for catenary components on high-speed railways has to be performed only at night with human eyes (**Figure 3**). 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.

**Figure 1.** *Component missing.*

**Figure 2.** *Looseness of bolts.*

Due to the great advances in machine vision technologies [2, 3], some visual inspections or visual measurement systems have been developed in the field of infrastructure inspection on track, catenary, etc. [4–8]. However, the development of a visual inspection system for catenary components is not an easy task. First, catenary is composed of many types of components, and these components are mounted in a large area and vary greatly in size and location, which brings great difficulties in the design of camera system. Second, most components concentrate at catenary posts, which means a great data storm for the image capturing, processing, and saving. Finally, the automatic data analysis is also of great challenge, as a result of the variety and large number of defect types.

In this paper, 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 with an image resolution up to 0.5 mm/pixel. A post detection module is integrated in order to trigger the cameras and lighting device at a proper

**139**

**Figure 4.**

*Structure of catenary.*

*Automatic Visual Inspection and Condition-Based Maintenance for Catenary*

location. Technologies of GPU acceleration, multi-thread and parallel computing, are exploited in the image acquisition, image compression, and data storage. Furthermore, an intelligent analysis framework is proposed to perform the

The rest of paper is organized as follows. Section 2 gives an overview of the system architecture. Section 3 describes the methodology of each system part in detail. Section 4 reports some application results of the system. Then we draw the

Catenary is composed of contact wire, cantilever, additional wire, hanging post (in tunnels), etc. (**Figure 4**). As a result, different kinds of catenary components

Considering that most components concentrate at catenary posts, we use groups of super-high-resolution area-scan cameras to capture image data of each region at a specific distance relative to each catenary post. A post detection module is applied to generate an accurate trigger signal for cameras and lighting device. Finally, image data from different cameras are paralleled processed and saved in a

are mounted in a large area and vary greatly in size and location.

The system architecture is illustrated in **Figure 5**.

*DOI: http://dx.doi.org/10.5772/intechopen.82149*

automatic analysis of image data.

conclusions in the last section.

**2. System architecture**

**Figure 3.**

*Traditional inspection.*

common data sever.

*Automatic Visual Inspection and Condition-Based Maintenance for Catenary DOI: http://dx.doi.org/10.5772/intechopen.82149*

**Figure 3.** *Traditional inspection.*

*Maintenance Management*

**Figure 1.** *Component missing.*

**Figure 2.** *Looseness of bolts.*

**138**

Due to the great advances in machine vision technologies [2, 3], some visual inspections or visual measurement systems have been developed in the field of infrastructure inspection on track, catenary, etc. [4–8]. However, the development of a visual inspection system for catenary components is not an easy task. First, catenary is composed of many types of components, and these components are mounted in a large area and vary greatly in size and location, which brings great difficulties in the design of camera system. Second, most components concentrate at catenary posts, which means a great data storm for the image capturing, processing, and saving. Finally, the automatic data analysis is also of great challenge, as a result

In this paper, 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 with an image resolution up to 0.5 mm/pixel. A post detection module is integrated in order to trigger the cameras and lighting device at a proper

of the variety and large number of defect types.

location. Technologies of GPU acceleration, multi-thread and parallel computing, are exploited in the image acquisition, image compression, and data storage. Furthermore, an intelligent analysis framework is proposed to perform the automatic analysis of image data.

The rest of paper is organized as follows. Section 2 gives an overview of the system architecture. Section 3 describes the methodology of each system part in detail. Section 4 reports some application results of the system. Then we draw the conclusions in the last section.
