Steel beam hoisting monitoring system and method based on machine vision

Abstract

The invention discloses a steel beam hoisting monitoring system based on machine vision. A deck crane is connected to a to-be-erected beam section through a steel wire lifting rope; the industrial camera is fixed on the deck crane, and a lens of the industrial camera is vertically downward; the network switch is in communication connection with the industrial camera, the intelligent computing terminal and the wireless network bridge. The square reference targets are positioned on two sides of an upper bridge surface of an erected beam section; the square monitoring targets are located on the two sides of the upper bridge floor of the beam end to be erected and correspond to the square reference targets one to one. The system is simple in structure, the monitoring method is high in engineering field practicability, high in monitoring precision and low in operation and maintenance cost, and the system has the advantages of unmanned real-time monitoring, wireless data transmission, intelligent auxiliary control and the like.

Description

technical field [0001] The invention relates to the field of bridge steel beam hoisting monitoring methods. More specifically, the present invention relates to a machine vision-based monitoring system and method for hoisting a steel beam. Background technique [0002] In the construction of existing bridge steel beams, the method of cantilever assembly is usually used for hoisting. With the increase of bridge span and the development of science and technology, the construction space of steel beams becomes more and more complicated, and the hoisting difficulty becomes more and more difficult. [0003] The traditional steel beam hoisting monitoring method adjusts its posture in advance before the beam is hoisted to keep it horizontal and has no corners, installs a tension sensor at the hoist cable to obtain the tension data, and judges whether the steel beam is not based on the symmetry of the force. There is deflection. During the lifting process, the displacement and rotati...

AI Technical Summary

Problems solved by technology

This kind of monitoring method has large errors, requires high professional level of command personnel, has strong human subjective uncertainty, and is greatly affected by environmental factors.

[0004] The emerging displacement monitoring technology based on machine vision has many advantages such as non-contact, long-distance, high precision, time-saving and labor-saving, and multi-point monitoring. It has been widely used in bridge deflection and displacement monitoring, but the existing methods can only measure bridge multi-point In-plane relative displacement, the relative relationship between the spatial positions of the two beam segments cannot be determined

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