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Machine vision based automatic grabbing algorithm for steel coil crane

A technology of machine vision and steel coils, which is applied in the direction of load hanging components, transportation and packaging, etc., can solve the problems of reduced production efficiency, collision damage between positioning manipulator and steel coils, and high requirements for operators, so as to ensure positioning accuracy and improve The effect of the level of mechanical automation

Inactive Publication Date: 2020-06-05
ZHOUKOU NORMAL UNIV
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

[0002] The current steel coil grabbing system requires the operator to manually control the manipulator in terms of working methods, and the artificial manual control has high requirements for the operator and it is difficult to achieve high precision. Often due to inaccurate positioning, the manipulator Collision damage with the steel coil, resulting in reduced production efficiency

Method used

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  • Machine vision based automatic grabbing algorithm for steel coil crane

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Embodiment Construction

[0027] Below the specific implementation process of the present invention is described further below:

[0028] A kind of automatic grabbing algorithm of steel coil crane based on machine vision, is characterized in that: comprises the following steps:

[0029] 1) Data read

[0030] After the system is started, it first selects the coil to be hoisted as required, reads the coil information from the database, including the coil specification and the coil storage location, and then controls the coil hoist to reach the designated area.

[0031] 2) Binding belt detection

[0032] After the steel coil crane reaches the designated area, it returns to the arrival signal, and at the same time controls the spreader installed with the industrial camera to reach the designated height, and then commands the industrial camera to collect pictures of the steel coil. First, it detects whether the strapping is broken according to the picture. If it breaks, an alarm signal is issued. Inform th...

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Abstract

The invention discloses a machine vision based automatic grabbing algorithm for a steel coil crane. The machine vision based automatic grabbing algorithm for the steel coil crane comprises the following steps of data reading, strapping tape detection, horizontal adjustment of a lifting appliance, height adjustment of the lifting appliance, height finishing of the lifting appliance, storage path adjustment and placement height adjustment. The method is characterized in that the machine vision is adopted to process a steel coil, and the position deviation between the lifting appliance and a geometric center point of the steel coil is calculated, which is the important link for realizing the automatic grabbing of the steel coil crane. The machine vision based automatic grabbing algorithm forthe steel coil crane has the advantages of high positioning precision, high automation degree and high processing efficiency, and can greatly improve the working efficiency of the steel coil crane.

Description

technical field [0001] The invention relates to the field of steel coil handling and lifting equipment, in particular to an automatic grabbing algorithm for steel coil cranes based on machine vision. Background technique [0002] The current steel coil grasping system requires the operator to manually control the manipulator in the way of work, and the manual manual control requires high requirements for the operator and it is difficult to achieve high precision, often due to inaccurate positioning. Collision damage with the coil, resulting in reduced production efficiency. In order to improve the automation level of steel coil grasping, many steel coil finished product warehouses urgently need technology that can realize automatic positioning of steel coils. With the progress of computer, image processing, artificial intelligence, intelligent control and other technologies, flexible automation based on machine vision is made The technology has been realized and developed r...

Claims

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Application Information

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IPC IPC(8): B66C13/48B66C13/16
CPCB66C13/16B66C13/48
Inventor 许彩云周永升贺娅莉
Owner ZHOUKOU NORMAL UNIV
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