Cold-rolled strip steel head shearing control method and device, medium and product

Abstract

The invention provides a cold-rolled strip steel head shearing control method and device, a medium and a product, and relates to the technical field of cold rolling intelligent management and control. The method comprises the steps that strip steel images are collected in real time, defect pixels of the strip steel images are extracted through a preset image segmentation algorithm, and the positions of the different defect pixels in the strip steel surface are determined; inputting the defect pixel into a preset neural network model, and outputting a defect type to which the pixel belongs; according to the defect type of each defect pixel and the position of each defect pixel on the surface of the strip steel, determining the length of the strip head needing to be sheared; and the shearing device is controlled to shear the tape head according to the to-be-sheared tape head length. The problem that in the prior art, the length of the belt head needing to be sheared is difficult to determine by recognizing the defects and the position of the belt head due to dependence on manual work or a fixed length set value, and the shearing effect is poor is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cold rolling intelligent management and control, in particular to a cold-rolled strip head shearing control method, device, medium and product. BACKGROUND

[0002] As an indispensable basic material in manufacturing industry, cold-rolled strip steel is widely used in many core fields such as automobile manufacturing, home appliance production, building decoration, etc. The quality of the strip head directly affects the stability of subsequent rolling, stamping, welding and other processes, as well as the precision and service life of the final product. In the cold rolling production process, the strip head is prone to edge cracks, edge waves, emulsion stains, oil stains and other defects due to factors such as raw material blank defects, rolling equipment wear, tension fluctuations, uneven temperature, etc. If these defects are not timely and effectively removed, they will further expand in subsequent processing, leading to strip tearing, equipment jamming, and increased production energy consumption and maintenance costs, which seriously restricts production efficiency and product quality.

[0003] The existing strip head shearing technology mainly relies on manual visual judgment or fixed length shearing mode. The manual visual method is affected by factors such as operator experience, visual fatigue, and environmental light, has low defect recognition accuracy and strong subjectivity, and is difficult to accurately locate the defect position and assess the defect severity, often resulting in insufficient or excessive shearing. The fixed length shearing mode does not consider the actual distribution and type difference of the strip head defects, and only shears according to the preset uniform length, which cannot completely remove the defect area and may cause a large amount of qualified strip steel material waste, resulting in reduced raw material utilization. SUMMARY

[0004] Embodiments of the present application provide a cold-rolled strip head shearing control method, device, medium and product, aiming to solve the problem that the prior art relies on manual or fixed length setting value, making it difficult to determine the length of the strip head that needs to be sheared by identifying the strip head defects and position, resulting in poor shearing effect.

[0005] To achieve the above-mentioned purpose, in a first aspect, the present application provides a cold-rolled strip head shearing control method, comprising the following steps: By real-time acquisition of strip images, a predetermined image segmentation algorithm is used to extract defect pixels of the strip images, and the positions of different defect pixels in the strip surface are determined; The defect pixels are input into a predetermined neural network model, and the defect type to which the pixels belong is output; According to the defect type of each defect pixel and its position in the strip surface, the length of the strip head that needs to be sheared is determined; According to the length of the strip head that needs to be sheared, a shearing device is controlled to shear the strip head.

[0006] Further, the strip steel image is collected, two linear array cameras are arranged before the entry shearing device, and two strip light sources are arranged respectively to collect image information of upper and lower surfaces of the strip steel.

[0007] Further, the image segmentation algorithm, when the distance between two defect pixels is less than a preset value, the two defect pixels are combined into one defect pixel.

[0008] Further, the defect types include edge cracks, edge waves, emulsion spots and / or oil stains.

[0009] Further, the edge cracks and the edge waves are defect types that need to be sheared, and the emulsion spots and the oil stains are defect types that do not need to be sheared.

[0010] Further, when the length of the head that needs to be sheared exceeds a preset first threshold value, the head is sheared according to the length of the first threshold value.

[0011] Further, the first threshold value is 80 cm.

[0012] In a second aspect, the present application provides a cold-rolled strip steel head shearing control device, comprising a memory and a processor, the memory stores at least one program, and the at least one program is executed by the processor to realize the cold-rolled strip steel head shearing control method as described above.

[0013] In a third aspect, the present application provides a computer readable storage medium, the storage medium stores at least one program, and the at least one program is executed by the processor to realize the cold-rolled strip steel head shearing control method as described above.

[0014] In a fourth aspect, the present application provides a computer program product, comprising a computer program, and the computer program is executed by the processor to realize the steps of the cold-rolled strip steel head shearing control method as described above.

[0015] The above technical solution has the following technical effects: By collecting the strip steel image in real time, the defect pixels of the strip steel image are extracted by using the predetermined image segmentation algorithm, and the positions of different defect pixels in the strip steel surface are determined; the defect pixels are input into the predetermined neural network model, and the defect type to which the pixel belongs is output; according to the defect type of each defect pixel and the position of the defect pixel in the strip steel surface, the length of the head that needs to be sheared is determined; and according to the length of the head that needs to be sheared, the shearing device is controlled to shear the head. The present application solves the problem that the prior art is difficult to determine the length of the head that needs to be sheared by identifying the head defects and positions, resulting in poor shearing effect. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1A flowchart of a cold-rolled strip head shearing control method according to an embodiment of the present application; Figure 2 A structural diagram of a cold-rolled strip head shearing control device according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] To further illustrate the embodiments, the present application provides accompanying drawings. These drawings are part of the disclosure of the present application, and mainly serve to illustrate the embodiments, and can be used to explain the operating principle of the embodiments in conjunction with the relevant description of the specification. Those of ordinary skill in the art should be able to understand other possible implementations and advantages of the present application in conjunction with these. The components in the drawings are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0018] The present application will be further described in conjunction with the accompanying drawings and specific embodiments.

[0019] Embodiment one: Figure 1 A flowchart of a cold-rolled strip head shearing control method according to an embodiment of the present application, as shown in Figure 1 The method of this embodiment includes the following steps: By collecting the strip image in real time, the predetermined image segmentation algorithm is used to extract the defect pixels of the strip image, and the positions of different defect pixels in the surface of the strip are determined. In one specific implementation, two linear array cameras are arranged in front of the entry shearing device, and two strip-shaped light sources are arranged respectively to collect the image information of the upper and lower surfaces of the strip. The two linear array cameras are triggered to take pictures by the encoder signal near the entrance, and can accurately track the detected strip meter.

[0020] In one specific implementation, the image gray scale algorithm is used to segment and extract defects from the collected images, and defects with similar distances are merged according to the positions of the defects to obtain the final defect image.

[0021] The defect pixels are input into a predetermined neural network model such as a convolutional neural network model, and the defect type to which the pixels belong is output. In one specific implementation, the defect types include edge cracks, edge waves, emulsion stains, and / or oil stains.

[0022] In one specific implementation, edge cracks and edge waves are defect types that need to be sheared, and emulsion stains and oil stains are defect types that do not need to be sheared.

[0023] According to the defect types of each defect pixel and its position in the surface of the strip, the length of the strip head that needs to be sheared is determined. In one specific implementation, the length of the strip head that needs to be sheared is obtained by the distance between the start point of the strip head and the position of the last defect of the defect type that needs to be sheared.

[0024] In a specific implementation, when the length of the strip head to be cut exceeds a preset first threshold value, such as 80 cm, the strip head is cut according to the length of the first threshold value; if the length of the detected defect is less than 80 cm and no defect of interest appears behind, the length of the cutting is set to the length of the strip head to be cut calculated in this embodiment, and the length of the cutting that is too long or too short can be unfavorable for the collection of the waste after cutting.

[0025] The cutting device cuts the strip head according to the length of the strip head to be cut.

[0026] Embodiment two: Figure 2 A structure diagram of the cold-rolled strip head cutting control device in an embodiment of the present application is shown in FIG. 1, which includes a processor 201, a memory 202, a bus 203, and a computer program stored in the memory 202 and executable on the processor 201, the processor 201 includes one or more processing cores, the memory 202 is connected to the processor 201 through the bus 203, the memory 202 is used to store program instructions, and the processor executes the computer program to implement the steps in the above method embodiment of the first embodiment of the present application. Figure 2

[0027] Further, as an executable solution, the cold-rolled strip head cutting control device can be a computer unit, which can be a desktop computer, a notebook, a palm computer, a cloud server, and the like. The computer unit can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above-mentioned constituent structure of the computer unit is only an example of the computer unit, and does not constitute a limitation on the computer unit, and can include more or fewer components than the above, or combine certain components, or different components. For example, the computer unit can also include an input / output device, a network access device, a bus, and the like, and the present application does not limit this.

[0028] ​Further, as an executable solution, the processor can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor or the like, which is a control center of the computer unit, and connects all parts of the computer unit through various interfaces and lines.

[0029] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the computer unit by running or executing the computer program and / or modules stored in the memory, and calling data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required by a function; and the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory device.

[0030] Embodiment three: The application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the method in the above embodiments of the application.

[0031] The modules / cells integrated by the computer units, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be realized. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM) and software distribution medium, etc. It should be noted that the content included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.

[0032] Embodiment four: The application further provides a computer program product, comprising a computer program, which, when executed by a processor, realizes the steps of the cold-rolled strip head shearing control method as described above.

[0033] Although the application is specifically shown and described in connection with the preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the spirit and scope of the application as defined by the appended claims.

Claims

1. A method for controlling the shearing of cold-rolled strip, characterized in that, Includes the following steps: By acquiring strip images in real time, a predetermined image segmentation algorithm is used to extract defect pixels from the strip images and determine the positions of different defect pixels on the strip surface. The defective pixel is input into a predetermined neural network model, which outputs the defect type to which the pixel belongs. Based on the defect type of each defect pixel and its position on the strip surface, determine the strip head length that needs to be cut. The shearing device is controlled to cut the strip head according to the required strip head length.

2. The method for controlling the shearing of cold-rolled strip according to claim 1, characterized in that, To acquire images of the strip steel, two line scan cameras are set up in front of the inlet shearing device, and two strip light sources are respectively arranged to acquire image information of the upper and lower surfaces of the strip steel.

3. The method for controlling the shearing of cold-rolled strip according to claim 1, characterized in that, When the distance between two defective pixels is less than a preset value, the image segmentation algorithm merges the two defective pixels into one defective pixel.

4. The method for controlling the shearing of cold-rolled strip according to claim 1, characterized in that, The defect types include edge cracks, edge waviness, emulsion spots, and / or oil stains.

5. The method for controlling the shearing of cold-rolled strip according to claim 4, characterized in that, The edge cracks and edge waves are defect types that require shearing, while the emulsion spots and oil stains are defect types that do not require shearing.

6. The method for controlling the shearing of cold-rolled strip according to claim 1, characterized in that, When the length of the strip to be cut exceeds a preset first threshold, the strip is cut according to the length of the first threshold.

7. The method for controlling the shearing of cold-rolled strip according to claim 1, characterized in that, The first threshold is 80cm.

8. A cold-rolled strip shearing control device, characterized in that, The method includes a memory and a processor, wherein the memory stores at least one program, which is executed by the processor to implement the cold-rolled strip shearing control method as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The storage medium stores at least one program, which is executed by a processor to implement the cold-rolled strip shearing control method as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the cold-rolled strip shearing control method as described in any one of claims 1-7.

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