Abstract
Railway tunnel 3D clearance inspection is critical to guaranteeing railway operation safety. However, it is a challenge to inspect railway tunnel 3D clearance using a vision system, because both the spatial range and field of view (FOV) of such measurements are quite large. This paper summarizes our work on dynamic railway tunnel 3D clearance inspection based on a multi-camera and structured-light vision system (MSVS). First, the configuration of the MSVS is described. Then, the global calibration for the MSVS is discussed in detail. The onboard vision system is mounted on a dedicated vehicle and is expected to suffer from multiple degrees of freedom vibrations brought about by the running vehicle. Any small vibration can result in substantial measurement errors. In order to overcome this problem, a vehicle motion deviation rectifying method is investigated. Experiments using the vision inspection system are conducted with satisfactory online measurement results.
Highlights
IntroductionWith the speed of trains increasing and the departure frequency improving, railway infrastructure quality requires a more proper and effective maintenance system to guarantee its operational security
With the speed of trains increasing and the departure frequency improving, railway infrastructure quality requires a more proper and effective maintenance system to guarantee its operational security.Railway tunnels, as an important part of railway infrastructure, have critical dimension limitations regarding their 3D clearance
We focus on the two key issues in railway tunnel 3D clearance dynamic inspection: one is the global calibration of multi-camera and structured-light vision system (MSVS); the other is the compensation approach to reduce the measurement errors induced by vehicle vibrations
Summary
With the speed of trains increasing and the departure frequency improving, railway infrastructure quality requires a more proper and effective maintenance system to guarantee its operational security. The LT method, by adopting a laser stripe modulated by the structured-light plane intersecting with the object, makes the extraction of feature points from the captured images facile and has the additional advantages of flexibility, fast on-site acquisition and high accuracy It is quite suitable for quickly measuring objects’ surfaces. Using the LT method to detect railway tunnel 3D clearance with a complete field of view (FOV), a multi-camera and structured-light vision system (MSVS) should be employed to capture the images of railway tunnel surfaces from different orientations, because the FOV of a single vision sensor is often too limited. We focus on the two key issues in railway tunnel 3D clearance dynamic inspection: one is the global calibration of MSVS; the other is the compensation approach to reduce the measurement errors induced by vehicle vibrations.
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