Machine vision-based coiled material off-line automatic parking rewinding method

Abstract

The invention provides a machine vision-based coiled material off-line automatic parking rewinding method, which comprises the following steps that: a rewinding control computer is used for receiving flaw data of a visual detection system on a target coiled material, and during rewinding operation, the rewinding control computer is used for sending position data of flaws closest to a stand in the longitudinal direction to a first PLC (Programmable Logic Controller) one by one; the first PLC sends a speed reduction signal to the rewinding machine PLC in advance corresponding to the longitudinal position data of the current flaw, and then sends a stop signal, so that the rewinding machine PLC controls the rewinding machine to stop under the condition that the speed is reduced aiming at the flaw which is about to arrive at the stand, and the flaw is stopped at the detection position on the stand. The rewinding efficiency and accuracy are improved, and meanwhile the working intensity of operators is reduced.

Description

technical field [0001] The invention relates to a method for rewinding a coil, which is applied to non-woven fabrics, copper foils and other industries or other rewinding machines that need to manually select defects. Background technique [0002] In the production process of roll-shaped materials, various defects will occur in the materials due to raw materials, processes or production environment. When defects occur, it is unrealistic to rely on human eyes to recognize when the production line is running at high speed. When a machine is installed When the visual inspection system is used, the category and coordinate position of the defect can be accurately identified. Because the production equipment is generally more expensive and the speed is relatively fast, the shutdown of the production line will damage the parts. From the perspective of economy and operability, it is impossible to stop the production equipment. The industry practice is that one production line equip...

AI Technical Summary

Problems solved by technology

When the production time is long, people are prone to fatigue, and if the label is lost during the transportation process, it is impossible to judge the loss manually, which will lead to the outflow of defects

[0004] In addition, artificially controlling defects and stopping on the kanban also requires operators to have considerable skills. It is not easy to stop accurately under the high-speed operation of the rewinder, and the operation is time-consuming.

[0005] Moreover, each customer may have different tolerance standards for defects

In the traditional method, the label cannot correspond to the type and size of the defect, and the operator needs to stop for each label, which will bring efficiency problems

[0006] Moreover, although there will be lighting equipment in the stands, the lighting of the lighting equipment can only be evenly distributed in the entire horizontal range, and it is not possible to focus on lighting for defects

The width of the material is often 3-4m, and the position of the defect in the horizontal direction is random. The search range in the horizontal position is too large, which is not conducive to the operation, especially when the defect is small, the workload of the search is very large for the personnel.

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