CN111232845A - An Algorithm for Automatic Grabbing of Coil Cranes Based on Machine Vision - Google Patents

Abstract

The invention discloses a steel coil crane automatic grabbing algorithm based on machine vision, which comprises the following steps: 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 a machine vision is adopted to process the steel coil, the position deviation of the lifting appliance and the geometric center point of the steel coil is calculated, and the method is an important link for realizing the automatic grabbing of the steel coil lifting appliance. The invention 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

An Algorithm for Automatic Grabbing of Coil Cranes Based on Machine Vision

technical field

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

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 rapidly, and the automatic positioning technology of steel coil based on machine vision has been widely researched and applied.

SUMMARY OF THE INVENTION

For the mechanical automation level of the steel coil crane, the present invention provides a machine vision-based automatic grabbing algorithm for the steel coil crane, which is realized through the following technical solutions:

A machine vision-based automatic grabbing algorithm for steel coil cranes, comprising the following steps:

1) Data read

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.

2) Binding belt detection

After the steel coil crane reaches the designated area, it returns to the arrival signal, and controls the spreader installed with the industrial camera to reach the designated height, and then commands the industrial camera to capture the steel coil picture. First, it detects whether the strapping belt is broken according to the picture, and if it breaks, an alarm signal is issued. Inform the crew to select other steel coils to continue the judgment, and the strapping belt is normal to go to the next step.

3) Spreader level adjustment

Perform image processing on the coil with normal strapping, calculate the horizontal displacement deviation between the spreader and the geometric center point of the coil, and call the automatic planning path program to move the spreader to the top of the coil to be hoisted.

4) Spreader height adjustment

After the spreader reaches the top of the steel coil, an instruction is issued to lower the spreader, and the laser displacement sensor measures the distance between the fixture and the steel coil in real time, and calculates the descending height of the spreader according to the specifications of the steel coil. After reaching the specified height, the spreader stops descending.

5) Spreader height finishing

The proximity switch judges whether the fixture has reached the steel coil shaft center, if not, it will be finished, and after reaching the shaft center position, the steel coil will be clamped and lifted.

6) Storage path adjustment

After the spreader grabs the steel coil, it first rises to the specified height, and then calls the automatic planning path program to transport the steel coil to the specified area.

7) Placement height adjustment

The system controls the spreader to descend to the specified position according to the calibration data of the specified area, the clamp is released, the crane returns to the initial position, and the operation ends.

The specific algorithm for image processing of the normal steel coil with the strapping is as follows:

① Read the picture of the steel coil and perform grayscale processing;

② Adopt filter changes to perform noise reduction processing;

③Use the active contour model to extract the edge of the coil;

④ Find the center of the circumscribed circle for the edge of the extracted steel coil;

⑤ Convert the pixel coordinates of the center of the circle to actual coordinates.

Compared with the prior art, the present invention has the following obvious advantages: the mechanical automation level of the steel coil crane is improved, double positioning is performed in both the horizontal direction and the height direction, and the positioning accuracy is ensured.

Description of drawings

Fig. 1 is the algorithm flow chart of the present invention.

Detailed ways

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

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

1) Data read

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.

2) Binding belt detection

After the steel coil crane reaches the designated area, it returns to the arrival signal, and controls the spreader installed with the industrial camera to reach the designated height, and then commands the industrial camera to capture the steel coil picture. First, it detects whether the strapping belt is broken according to the picture, and if it breaks, an alarm signal is issued. Inform the crew to select other steel coils to continue the judgment, and the strapping belt is normal to go to the next step.

3) Spreader level adjustment

Perform image processing on the coil with normal strapping, calculate the horizontal displacement deviation between the spreader and the geometric center point of the coil, and call the automatic planning path program to move the spreader to the top of the coil to be hoisted. Among them, image processing is performed on the steel coil with normal strapping, and the specific algorithm is as follows:

① Read the picture of the steel coil and perform grayscale processing;

② Adopt filter changes to perform noise reduction processing;

③Use the active contour model to extract the edge of the coil;

④ Find the center of the circumscribed circle for the edge of the extracted steel coil;

⑤ Convert the pixel coordinates of the center of the circle to actual coordinates.

4) Spreader height adjustment

After the spreader reaches the top of the steel coil, an instruction is issued to lower the spreader, and the laser displacement sensor measures the distance between the fixture and the steel coil in real time, and calculates the descending height of the spreader according to the specifications of the steel coil. After reaching the specified height, the spreader stops descending.

5) Spreader height finishing

The proximity switch judges whether the fixture has reached the steel coil shaft center, if not, it will be finished, and after reaching the shaft center position, the steel coil will be clamped and lifted.

6) Storage path adjustment

After the spreader grabs the steel coil, it first rises to the specified height, and then calls the automatic planning path program to transport the steel coil to the specified area.

7) Placement height adjustment

The system controls the spreader to descend to the specified position according to the calibration data of the specified area, the clamp is released, the crane returns to the initial position, and the operation ends.

The invention is an automatic grabbing algorithm of the steel coil crane based on machine vision, which improves the mechanical automation level of the steel coil crane, performs double positioning regardless of the horizontal direction and the height direction, and ensures the positioning accuracy.

The technical means disclosed in the solution of the present invention are not limited to the technical means disclosed in the above embodiments, but also include technical solutions composed of any combination of the above technical features. It should be pointed out that for those skilled in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications are also regarded as the protection scope of the present invention.

Claims (2)

1. The utility model provides a coil of strip hangs automatic algorithm of snatching based on machine vision which characterized in that: the method comprises the following steps:

1) data reading

After the system is started, firstly, a steel coil to be hung is selected according to needs, steel coil information including the specification of the steel coil and the storage position of the steel coil is read from a database, and then the steel coil crane is controlled to reach a specified area.

2) Strapping detection

After the steel coil crane reaches a specified area, an arrival signal is returned, meanwhile, the crane provided with the industrial camera is controlled to reach a specified height, then the industrial camera is instructed to collect a steel coil picture, whether the strapping tape is broken or not is detected according to the picture, an alarm signal is sent out if the strapping tape is broken, meanwhile, a crew is informed to select other steel coils to continue judging, and the strapping tape normally enters the next step.

3) Horizontal adjustment of lifting appliance

And (3) carrying out image processing on the steel coil with normal strapping tape, calculating the horizontal plane displacement deviation between the lifting appliance and the geometric center point of the steel coil, and calling an automatic path planning program to move the lifting appliance to the position right above the steel coil to be lifted.

4) Height adjustment of lifting appliance

And after the lifting appliance reaches the position right above the steel coil, sending an instruction to descend the lifting appliance, measuring the distance between the clamp and the steel coil in real time by using the laser displacement sensor, calculating the descending height of the lifting appliance according to the specification of the steel coil, and stopping descending the lifting appliance after reaching the specified height.

5) High finishing of lifting appliance

And the proximity switch judges whether the clamp reaches the axis of the steel coil, if not, finishing is carried out, and the steel coil is clamped and lifted after reaching the position of the axis.

6) Storage path adjustment

After the lifting appliance grabs the steel coil, the steel coil is lifted to a specified height, and then an automatic path planning program is called to convey the steel coil to a specified area.

7) Adjustment of placement height

And the system controls the lifting appliance to descend to a specified position according to the specified region calibration data, the clamp is released, the crane returns to the initial position, and the operation is finished.

2. The steel coil crane automatic grabbing algorithm based on the machine vision as claimed in claim 1, characterized in that: the image processing is carried out on the steel coil with the normal strapping tape, and the specific algorithm is as follows:

① reading the steel coil picture, and performing gray processing;

②, filtering and reducing noise;

③ extracting the edge of the steel coil by adopting an active contour model;

④ calculating the circle center of the circumscribed circle of the edge of the extracted steel coil;

⑤ transform the center pixel coordinates to actual coordinates.

Images