Application of Intelligent Technology on Tunnel Steel Structure Factory

Chenyang He and Jun Liu

Mathematical Problems in Engineering, 2022, vol. 2022, 1-9

Abstract: At present, the construction of tunnel steel structure factories has been common, but most of them are still on the low end. In addition, the manual processing modes face certain problems, such as high waste rate, low efficiency, and discrete welding of steel components. To address these problems, this paper introduces an intelligent management cloud platform, aiming to realize unmanned control methods and construct an intelligent tunnel steel component processing plant. There are four main production lines in the intelligent steel structure factory. First, an intelligent production line of a tunnel grille arch effectively improves the production efficiency, production quality, and dust removal effect of the grille arch through the automatic welding technology of a reinforcement mechanism-based welding robot. Second, a processing line of a steel pipe for tunnel construction improves the overall processing efficiency, saves costs, and reduces work intensity by using an intelligent numerical control system, a pneumatic clamping device, a plasma cutting hole assembly, and a 360-degree automatic rotation system. Third, an automatic feeding platform of section steel arch production line adopts the six-axis robot sensor clamping connecting plate positioning and six-axis robot sensing three-plane automatic welding system, which not only compensates for the defects of manual production but also realizes the reduction, increases efficiency, and improves welding quality and precision. Fourth, an automatic steel mesh production line saves much labor and enhances site management and production efficiency through vertical and horizontal reinforcement pay-off racks. Overall, in this study, the construction goals of informatization, intellectualization, and personnel downsizing of the tunnel steel structure processing have been achieved.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:7640504

DOI: 10.1155/2022/7640504

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