A vehicle-mounted adjustment platform for tunnel image acquisition and its implementation method

Abstract

The invention relates to a vehicle-mounted adjustment platform for tunnel image acquisition and an implementation method thereof. It includes installation platform, motion branch, base and slewing drive; there are three motion branches, two of which are in the form of SPR structure and the other is in the form of RPS structure; the movement branch is connected to the base, and the base is connected to the vehicle through the slewing platform. The luggage rack is connected; the slewing platform can rotate under the drive of the stepping motor. Compared with the prior art, the invention has the ability to move longitudinally along the tunnel, and can keep the distance between the digital camera and the lining surface of the tunnel within the range of the depth of field of the camera; the vertical height of the digital camera can be adjusted in real time. In addition, the application of parallel robots in the field of image acquisition of highway tunnels avoids the impact of vehicle trajectory deviation on image acquisition equipment during the acquisition process. At the same time, the spatial position of the digital camera can be adjusted according to the size of the tunnel structure, which solves the problem of existing image acquisition systems. There are many technical problems in the application of road tunnels.

Description

technical field [0001] The invention belongs to the technical field of road detection, and in particular relates to a vehicle-mounted adjustment platform for tunnel image acquisition and an implementation method thereof. Background technique [0002] Due to geological disasters, operating years and other reasons, expressway tunnels will have cracks, which seriously threaten the operation safety of expressways. At present, tunnel crack detection methods and equipment are still relatively backward, and manual or manual instruments are often used to complete the detection task with the help of aerial vehicles. This method based on manual detection is inefficient and highly subjective, especially in the case of a number of new super-long tunnels in my country, and it is impossible to complete the detection task in a short period of time by relying on manual labor. [0003] The core and key of machine vision technology is how to acquire high-quality images, which requires that t...

AI Technical Summary

Problems solved by technology

On the one hand, it reduces the intelligence of the system; on the other hand, vehicle bumps affect the focusing device of the digital camera, which disturbs the image acquisition

To sum up, the existing technical conditions limit the application of machine vision technology in the intelligent detection of highway tunnels. The root cause is the lack of a set of image stabilization acquisition devices, resulting in poor quality of the collected images, which affects subsequent image processing and features. identify

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