Wire rod position identification method and system used in tunnel pickling driving process

Abstract

The invention discloses a wire rod position identification method and system used in a tunnel pickling driving process, and the method comprises the steps: scanning vehicles in a tunnel pickling driving workshop, and obtaining point cloud data; filtering the point cloud data, removing interference point cloud, and obtaining filtered point cloud data; preprocessing the filtered point cloud data, and detecting an edge curve; and performing ellipse identification on the edge curve to obtain position parameters of the wire rod. According to the method and the system, the position of the wire rod can be accurately identified through scanning, filtering, detection and identification in combination with the environmental characteristics in the tunnel pickling driving process, so that material taking, feeding and bin cover taking and placing are accurate, the method and the system are not influenced by field illumination and environment, the identification distance is long, the identification precision is high, and the response speed is high; and rapid loading and unloading operation in the tunnel pickling traveling process is guaranteed.

Description

technical field [0001] The present application relates to the field of pickling of metal materials and intelligent control of tunnel pickling, in particular to a system and method for disc position recognition. Background technique [0002] In the tunnel pickling driving, the hoisting of the coil is the main operation, and the position of the coil needs to be known during the hoisting process. The traditional way is to rely on the experience of the operator for positioning. The operator is prone to large displacement errors and angular deflection when he is tired from working for a long time. In addition, under the external conditions of strong interference, the control of the operator Produce bigger influence, work efficiency reduces greatly. Obviously, the manual positioning method is not suitable for the crane used for tunnel pickling. In order to realize the fully automatic operation of the hoisting process, the crane used for tunnel pickling must have an accurate posit...

AI Technical Summary

Problems solved by technology

The traditional way is to rely on the experience of the operator for positioning. When the operator is tired after working for a long time, it is easy to produce large displacement errors and angular deflection. In addition, under the external conditions of strong interference, the control of the operator is also difficult. Great impact, work efficiency is greatly reduced

Obviously, the manual positioning method is not suitable for the crane used for tunnel pickling. To realize the fully automatic operation of the round hoisting process, the crane used for tunnel pickling must have an accurate position recognition system instead of only relying on the travel switch during manual operation. Easy Position Detection

In order to accurately identify the position of the disk circle, the influence of the environment in the workshop needs to be considered. The traditional image recognition method has the characteristics of small recognition range, easy to be affected by weather, light environment and the color of the car surface, and it is difficult to meet the requirements of driving in tunnel pickling. Requirements for accurate retrieving, feeding and hopper cover removal

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