CN111347174B

CN111347174B - Automatic feeding type laser cutting method and system based on AI technology

Info

Publication number: CN111347174B
Application number: CN202010286328.XA
Authority: CN
Inventors: 李荣辉; 谭春晖; 康志国; 申仁军
Original assignee: Shenzhen Make Laser Equipment Co ltd
Current assignee: Shenzhen Make Laser Equipment Co ltd
Priority date: 2020-04-13
Filing date: 2020-04-13
Publication date: 2021-02-19
Anticipated expiration: 2040-04-13
Also published as: CN111347174A

Abstract

The embodiment of the application provides an automatic feeding formula laser cutting system based on AI technique, the system includes: the automatic feeding device, the laser cutting device and the AI device; the technical scheme of this application has the advantage that cutting accuracy is high.

Description

Automatic feeding type laser cutting method and system based on AI technology

Technical Field

The application relates to the technical field of electronics and laser, in particular to an automatic feeding type laser cutting method and system based on an AI technology.

Background

The laser cutting machine focuses laser emitted from a laser into a laser beam with high power density through an optical path system. The laser beam irradiates the surface of the workpiece to make the workpiece reach a melting point or a boiling point, and simultaneously, the high-pressure gas coaxial with the laser beam blows away the molten or gasified metal. And finally, the material is cut along with the movement of the relative position of the light beam and the workpiece, so that the cutting purpose is achieved.

The laser cutting processing is to replace the traditional mechanical knife by invisible light beams, has the characteristics of high precision, quick cutting, no limitation on cutting patterns, automatic typesetting, material saving, smooth cut, low processing cost and the like, and can gradually improve or replace the traditional metal cutting process equipment. The mechanical part of the laser tool bit is not in contact with the workpiece, so that the surface of the workpiece cannot be scratched in the working process; the laser cutting speed is high, the cut is smooth and flat, and subsequent processing is generally not needed; the cutting heat affected zone is small, the deformation of the plate is small, and the cutting seam is narrow; the notch has no mechanical stress and no shearing burr; the processing precision is high, the repeatability is good, and the surface of the material is not damaged; the numerical control programming can be used for processing any plan, the whole board with large breadth can be cut, a die does not need to be opened, and the method is economical and time-saving.

Along with the development of AI technique, in the AI technique was used to the laser cutting technique, the AI technique confirmed the material based on picture information's discernment, then called corresponding processing drawing and process this material, but current AI laser cutting machine's automatic feeding machine when the material loading, because the picture that the removal of material loading leads to gathering has the ambiguity, and then leads to the accuracy of discernment, has reduced the yields of material.

Disclosure of Invention

The embodiment of the application discloses an automatic feeding type laser cutting method based on an AI technology, which can accurately identify materials of an AI laser cutting machine and improve the yield of the materials.

The embodiment of the application discloses first aspect discloses an automatic feeding formula laser cutting system based on AI technique, the system includes: the automatic feeding device, the laser cutting device and the AI device;

the AI device is used for collecting information of a plurality of images after the automatic feeding device stops;

the AI device is also used for cutting a set area from the multiple pieces of image information along the moving direction to obtain a plurality of images to be processed; identifying each image to be processed to determine a moving result, inquiring an x-th image to be processed which is not moved from the plurality of images to be processed, and determining image information corresponding to the x-th image to be processed as input image information of the AI device;

the AI device identifying each image to be processed and determining the movement result specifically includes:

draw left side 3 x 3 pixel of a pending image, 3 x 3 pixel and right side 3 x 3 pixel in the middle of, to left side 3 x 3 pixel, 3 x 3 pixel in the middle of and 3 x 3 pixel on the right side respectively identify and confirm the removal result, and the identification operation can specifically include: using 3 pixel points on the left side as the center, searching y 3 pixel points which are the same as the 3 pixel points on the left side in the moving direction, calculating the total average value AVG of the brightness of (2y +1) 3 pixel points in the number of 3 pixel points on the left side_{Left side of}Calculating the average brightness value and AVG of (2y +1) 3 x 3 pixels_{Left side of}Variance S of² _{Left side of}And performing identification operation on the 3 x 3 pixel points in the middle to obtain S² _InAnd performing identification operation on the right 3 x 3 pixel points to obtain S² _{Right side}Will beS² _{Left, right,}S² _{Middle part,}S² _{Right side}Comparing the minimum value with a movement threshold, if the minimum value is larger than the movement threshold, determining that the image to be processed does not move, and if the minimum value is larger than or equal to the movement threshold, determining that the image to be processed moves;

the AI device is also used for carrying out boundary identification on the input graphic information to determine the material position, and sending the material position to the laser cutting device for laser cutting.

A second aspect of the embodiments of the present application provides an automatic feeding type laser cutting method based on an AI technology, where the method is applied to a system, and the system includes: the automatic feeding device, the laser cutting device and the AI device; the method comprises the following steps:

the AI device collects a plurality of pieces of image information after the automatic feeding device stops;

the AI device cuts a set area from a plurality of pieces of image information along the moving direction to obtain a plurality of images to be processed; identifying each image to be processed to determine a moving result, inquiring an x-th image to be processed which is not moved from the plurality of images to be processed, and determining image information corresponding to the x-th image to be processed as input image information of the AI device;

draw left side 3 x 3 pixel of a pending image, 3 x 3 pixel and right side 3 x 3 pixel in the middle of, to left side 3 x 3 pixel, 3 x 3 pixel in the middle of and 3 x 3 pixel on the right side respectively identify and confirm the removal result, and the identification operation can specifically include: using 3 pixel points on the left side as the center, searching y 3 pixel points which are the same as the 3 pixel points on the left side in the moving direction, calculating the total average value AVG of the brightness of (2y +1) 3 pixel points in the number of 3 pixel points on the left side_{Left side of}Calculating the average brightness value and AVG of (2y +1) 3 x 3 pixels_{Left side of}Variance S of² _{Left side of}And performing identification operation on the 3 x 3 pixel points in the middle to obtain S² _InFor the right 3 x 3 pixelsThe point execution identification operation is S² _{Right side}Will S² _{Left, right,}S² _{Middle part,}S² _{Right side}Comparing the minimum value with a movement threshold, if the minimum value is larger than the movement threshold, determining that the image to be processed does not move, and if the minimum value is larger than or equal to the movement threshold, determining that the image to be processed moves;

and the AI device performs boundary identification on the input graphic information to determine the position of the material, and sends the position of the material to the laser cutting device for laser cutting.

A third aspect of embodiments of the present application provides a computer-readable storage medium, which is characterized by storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute the method provided in the second aspect.

By implementing the embodiment of the application, the technical scheme provided by the application acquires information of a plurality of images after the AI device stops at the automatic feeding device; cutting a set area from the plurality of pieces of image information along the moving direction to obtain a plurality of images to be processed; the method comprises the steps of identifying each image to be processed to determine a movement result, inquiring an x-th unmoved image to be processed from the plurality of images to be processed, determining image information corresponding to the x-th image to be processed as input image information of an AI device, identifying a boundary of the input image information by the AI device to determine a material position, and sending the material position to a laser cutting device for laser cutting.

Drawings

The drawings used in the embodiments of the present application are described below.

Fig. 1 is a schematic structural diagram of an automatic feeding type laser cutting system based on AI technology according to an embodiment of the present application;

fig. 2 is a schematic flow chart of an automatic feeding type laser cutting method based on an AI technology according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of an apparatus provided in an embodiment of the present application.

Detailed Description

The embodiments of the present application will be described below with reference to the drawings.

The term "and/or" in this application is only one kind of association relationship describing the associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in this document indicates that the former and latter related objects are in an "or" relationship.

The "plurality" appearing in the embodiments of the present application means two or more. The descriptions of the first, second, etc. appearing in the embodiments of the present application are only for illustrating and differentiating the objects, and do not represent the order or the particular limitation of the number of the devices in the embodiments of the present application, and do not constitute any limitation to the embodiments of the present application. The term "connect" in the embodiments of the present application refers to various connection manners, such as direct connection or indirect connection, to implement communication between devices, which is not limited in this embodiment of the present application.

The AI device in the embodiments of the present application may refer to various forms of UE, access terminal, subscriber unit, subscriber station, mobile station, MS (mobile station), remote station, remote terminal, mobile device, computer, server, cloud system user terminal, terminal device (terminal equipment), wireless communication device, user agent, or user device. The terminal device may also be a cellular phone, a cordless phone, an SIP (session initiation protocol) phone, a WLL (wireless local loop) station, a PDA (personal digital assistant) with a wireless communication function, a handheld device with a wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a future 5G network or a terminal device in a future evolved PLMN (public land mobile network, chinese), and the like, which are not limited in this embodiment.

Referring to fig. 1, fig. 1 is a schematic block diagram of an automatic feeding type laser cutting system based on AI technology, and as shown in fig. 1, the apparatus includes: automatic loading attachment, laser cutting device, AI device, wherein the AI device includes: camera, memory, treater (can be general-purpose processor, also can be special AI treater). The technical scheme of this application does not have the improvement to laser cutting device and automatic feeding device, and this automatic feeding device, laser cutting device can adopt current laser cutting device, and this automatic feeding device also can adopt current automatic feeding device.

For an automatic feeding device, a stepping motor is generally adopted for control, after the automatic feeding device moves a material to a preset position, image information is collected by a camera, the image information is identified to determine the position of the material, and the position of the material is sent to a laser cutting device to cut the material.

Referring to fig. 2, fig. 2 provides an automatic feeding type laser cutting method based on the AI technology, which is performed by the automatic feeding type laser cutting apparatus based on the AI technology shown in fig. 1, and the method shown in fig. 2 includes the following steps:

step S201, the AI device collects information of a plurality of images after the automatic feeding device stops;

the collection mode in step S201 may be collected by a camera.

Step S202, the AI device cuts a set area from a plurality of pieces of image information along the moving direction to obtain a plurality of images to be processed;

step S203, the AI device identifies each image to be processed to determine a movement result, inquires an x-th image to be processed which is not moved from the plurality of images to be processed, and determines image information corresponding to the x-th image to be processed as input image information of the AI device;

in an optional scheme, the identifying, by the AI device, each to-be-processed image to determine a movement result may specifically include:

draw left side 3 x 3 pixel of a pending image, 3 x 3 pixel and right side 3 x 3 pixel in the middle of, to left side 3 x 3 pixel, 3 x 3 pixel in the middle of and 3 x 3 pixel on the right side respectively identify and confirm the removal result, and the identification operation can specifically include: using 3 pixel points on the left side as the center, searching y 3 pixel points which are the same as the 3 pixel points on the left side in the moving direction, calculating the total average value AVG of the brightness of (2y +1) 3 pixel points in the number of 3 pixel points on the left side_{Left side of}Calculating the average brightness value and AVG of (2y +1) 3 x 3 pixels_{Left side of}Variance S of² _{Left side of}And performing identification operation on the 3 x 3 pixel points in the middle to obtain S² _InAnd performing identification operation on the right 3 x 3 pixel points to obtain S² _{Right side}Will S² _{Left, right,}S² _{Middle part,}S² _{Right side}The minimum value in the image to be processed is compared with a movement threshold value, if the minimum value is larger than the movement threshold value, the image to be processed is determined not to move, and if the minimum value is larger than or equal to the movement threshold value, the image to be processed is determined to move.

For example, when y is 1, S² _{Left side of}＝[(lum1^2_AVG² _{Left side of})+(lum2^2_AVG² _{Left side of})+(lum3^2_AVG² _{Left side of})]A/3; the lum1 is the average value of the brightness of 1 pixel 3 × 3 pixels which are the same as the left pixel 3 × 3 pixels, the lum2 is the average value of the brightness of the left pixel 3 × 3 pixels, and the lum3 is the average value of the brightness of 1 pixel 3 × 3 pixels which are the same as the left pixel 3 × 3 pixels, which are searched in the moving reverse direction.

For the shooting of image information in a moving state, the method has the characteristic that the difference between brightness values of the same pixel points is small, based on the characteristic, 3 x 3 pixel points of an image to be processed serve as an identified basic pixel block, then the variance of the basic pixel block is calculated, the fluctuation size of the brightness of the basic pixel block is determined through the variance, when the fluctuation is large, for example, larger than a moving threshold value, the image to be processed is determined to be moving, and otherwise, the image to be processed is determined not to be moving.

In an optional manner, the searching y 3 × 3 pixels that are the same as the left 3 × 3 pixels along the moving direction by using the left 3 × 3 pixels as the center may specifically include:

and 3, determining 3 RGB channels in the 3X 3 pixel points on the left side, and searching y 3X 3 pixel points which are the same as the 3X 3 RGB channels and have the shortest distance in the moving direction.

For example, the left 3 × 3 pixels (first row and last row) are B, G, B, G, R, G, B, G, B; then, y 3 × 3 pixels that are the same as the RGB channel and closest to the RGB channel are searched along the moving direction, that is, y 3 × 3 pixels (listed in front and back) are searched, B, G, B, G, R, G, B, G, B.

And S204, the AI device performs boundary identification on the input graphic information to determine the position of the material, and sends the position of the material to the laser cutting device for laser cutting.

The boundary identification and laser cutting method can be implemented in the existing method, and will not be described herein.

According to the technical scheme provided by the application, a plurality of pieces of image information are collected after the AI device stops at the automatic feeding device; cutting a set area from the plurality of pieces of image information along the moving direction to obtain a plurality of images to be processed; the method comprises the steps of identifying each image to be processed to determine a movement result, inquiring an x-th unmoved image to be processed from the plurality of images to be processed, determining image information corresponding to the x-th image to be processed as input image information of an AI device, identifying a boundary of the input image information by the AI device to determine a material position, and sending the material position to a laser cutting device for laser cutting.

The application still provides an automatic feeding formula laser cutting system based on AI technique, the system includes: the automatic feeding device, the laser cutting device and the AI device;

draw left side 3 x 3 pixel of a pending image, 3 x 3 pixel and right side 3 x 3 pixel in the middle of, to left side 3 x 3 pixel, 3 x 3 pixel in the middle of and 3 x 3 pixel on the right side respectively identify and confirm the removal result, and the identification operation can specifically include: using 3 pixel points on the left side as the center, searching y 3 pixel points which are the same as the 3 pixel points on the left side in the moving direction, calculating the total average value AVG of the brightness of (2y +1) 3 pixel points in the number of 3 pixel points on the left side_{Left side of}Calculating the average brightness value and AVG of (2y +1) 3 x 3 pixels_{Left side of}Variance S of² _{Left side of}And performing identification operation on the 3 x 3 pixel points in the middle to obtain S² _InAnd performing identification operation on the right 3 x 3 pixel points to obtain S² _{Right side}Will S² _{Left, right,}S² _{Middle part,}S² _{Right side}Comparing the minimum value with a movement threshold, if the minimum value is larger than the movement threshold, determining that the image to be processed does not move, and if the minimum value is larger than or equal to the movement threshold, determining that the image to be processed moves;

In an optional scheme, the AI device is specifically configured to determine 3 × 3 RGB channels of the left 3 × 3 pixels, and search y 3 × 3 pixels that are the same as the 3 × 3 RGB channels and closest to the left pixel along the moving direction.

In an alternative, if y is 1, the AI device is specifically for S² _{Left side of}＝[(lum1^2_AVG² _{Left side of})+(lum2^2_AVG² _{Left side of})+(lum3^2_AVG² _{Left side of})]A/3; the lum1 is the average value of the brightness of 1 pixel 3 × 3 pixels which are the same as the left pixel 3 × 3 pixels, the lum2 is the average value of the brightness of the left pixel 3 × 3 pixels, and the lum3 is the average value of the brightness of 1 pixel 3 × 3 pixels which are the same as the left pixel 3 × 3 pixels, which are searched in the moving reverse direction.

An embodiment of the present application further provides a computer program product, and when the computer program product runs on a terminal, the method flow shown in fig. 2 is implemented.

Embodiments of the present application also provide a terminal including a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps in the method of the embodiment shown in fig. 2.

Referring to fig. 3, fig. 3 is a device 30 (control center) provided in an embodiment of the present application, where the device 30 includes a processor 301, a memory 302, and a communication interface 303, and the processor 301, the memory 302, and the communication interface 303 are connected to each other through a bus 304.

The memory 302 includes, but is not limited to, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a portable read-only memory (CD-ROM), and the memory 302 is used for related computer programs and data. The communication interface 303 is used to receive and transmit data.

The processor 301 may be one or more Central Processing Units (CPUs), and in the case that the processor 301 is one CPU, the CPU may be a single-core CPU or a multi-core CPU.

The processor 301 in the device 30 is configured to read the computer program code stored in the memory 302, and perform the following operations:

it should be noted that the implementation of each unit may also correspond to the corresponding description of the method embodiment shown in fig. 2.

Collecting information of a plurality of images after the automatic feeding device stops;

cutting a set area from the plurality of pieces of image information along the moving direction to obtain a plurality of images to be processed; identifying each image to be processed to determine a moving result, inquiring an x-th image to be processed which is not moved from the plurality of images to be processed, and determining image information corresponding to the x-th image to be processed as input image information of the AI device;

identifying each image to be processed to determine a movement result specifically comprises:

draw left side 3 x 3 pixel of a pending image, 3 x 3 pixel and right side 3 x 3 pixel in the middle of, to left side 3 x 3 pixel, 3 x 3 pixel in the middle of and 3 x 3 pixel on the right side respectively identify and confirm the removal result, and the identification operation can specifically include: using 3 pixel points on the left side as the center, searching y 3 pixel points which are the same as the 3 pixel points on the left side in the moving direction, calculating the total average value AVG of the brightness of (2y +1) 3 pixel points in the number of 3 pixel points on the left side_{Left side of}Calculating the average brightness value and AVG of (2y +1) 3 x 3 pixels_{Left side of}Variance S of² _{Left side of}And performing identification operation on the 3 x 3 pixel points in the middle to obtain S² _InAnd performing identification operation on the right 3 x 3 pixel points to obtain S² _{Right side}Will S² _{Left, right,}S² _{Middle part,}S² _{Right side}Comparing the minimum value with a moving threshold value, if the minimum value is larger than the moving threshold value, determining that the image to be processed does not move, if the minimum value is larger than or equal to the moving threshold value, determining that the image to be processed isMoving;

The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the above-mentioned functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.

Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes an electronic device.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. An automatic feed type laser cutting system based on AI technology, the system comprising: the automatic feeding device, the laser cutting device and the AI device; it is characterized in that the preparation method is characterized in that,

draw left side 3 x 3 pixel of a pending image, 3 x 3 pixel and right side 3 x 3 pixel in the middle of, to left side 3 x 3 pixel, 3 x 3 pixel in the middle of and 3 x 3 pixel on the right side respectively identify and confirm the removal result, and the identification operation can specifically include: using 3 pixel points on the left side as the center, searching y 3 pixel points which are the same as the 3 pixel points on the left side in the moving direction, calculating the total average value AVG of the brightness of (2y +1) 3 pixel points in the number of 3 pixel points on the left side_{Left side of}Calculating the average brightness value and AVG of (2y +1) 3 x 3 pixels_{Left side of}Variance S of² _{Left side of}And performing identification operation on the 3 x 3 pixel points in the middle to obtain S² _InAnd performing identification operation on the right 3 x 3 pixel points to obtain S² _{Right side}Will S² _{Left side of}、S² _In、S² _{Right side}Comparing the minimum value with a movement threshold, if the minimum value is larger than the movement threshold, determining that the image to be processed does not move, and if the minimum value is larger than or equal to the movement threshold, determining that the image to be processed moves;

2. The system of claim 1,

the AI device is specifically configured to determine 3 × 3 RGB channels in the left 3 × 3 pixels, and search y 3 × 3 pixels that are the same as the 3 × 3 RGB channels and closest to the pixels along the moving direction.

3. The system of claim 1,

if y is 1, the AI device is specifically for S² _{Left side of}＝[(lum1²-AVG² _{Left side of})+(lum2²-AVG² _{Left side of})+(lum3²-AVG² _{Left side of})]A/3; the lum1 is the average value of the brightness of 1 pixel 3 × 3 pixels which are the same as the left pixel 3 × 3 pixels, the lum2 is the average value of the brightness of the left pixel 3 × 3 pixels, and the lum3 is the average value of the brightness of 1 pixel 3 × 3 pixels which are the same as the left pixel 3 × 3 pixels, which are searched in the moving reverse direction.

4. An automatic feeding type laser cutting method based on AI technology is applied to a system, and the system comprises: the automatic feeding device, the laser cutting device and the AI device; characterized in that the method comprises the following steps:

5. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to claim 4.