Calibration method and device of laser processing equipment, computer equipment and storage medium

Abstract

The embodiment of the invention belongs to the technical field of image processing, and relates to a calibration method and device of laser processing equipment, computer equipment and a storage medium, and the method comprises the following steps: obtaining a laser position coordinate of an auxiliary fixing workpiece; calculating a mapping transformation relation between an axis plane and a CCD image plane according to the laser position coordinates; identifying a suction nozzle pixel coordinate at the center of the auxiliary fixed workpiece according to an image identification technology; calculating an axial distance position from the suction nozzle pixel coordinate to the axial plane coordinate according to the mapping transformation relation; and performing concentric calibration operation on the auxiliary fixing workpiece according to the axial distance position. The position of the auxiliary fixing workpiece is accurately adjusted, so that the strict requirement of the laser cutting technology for precision is met.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to calibration methods, apparatus, computer equipment and storage media for laser processing equipment. Background Technology

[0002] In the field of laser cutting, whether the geometric center of the laser cutting nozzle and the center of the laser beam formed by the laser beam can coincide—that is, the concentricity of the cutting nozzle and the laser beam—will affect the overall cutting quality of the cutting machine. For example, circles will not be cut perfectly round, straight lines will not be cut perfectly straight, and materials will not be cut through completely. The main reasons for the non-concentricity of the cutting nozzle and the laser beam include: errors in the overall mechanical structure of the cutting head, and nozzle displacement or deformation caused by prolonged cutting.

[0003] In existing technologies, the traditional method for adjusting the concentricity of the cutting nozzle and the laser beam is to manually adjust the center of the cutting nozzle and the center of the laser beam to coincide by human eyes. This method mainly relies on human eyes to find the reference position, which has a large error and is slow. It also requires manual adjustment each time, which is not flexible.

[0004] It is evident that traditional methods for adjusting the concentricity of the cutting nozzle and the laser beam suffer from significant errors and are too slow. Summary of the Invention

[0005] The purpose of this application is to provide a calibration method, apparatus, computer equipment, and storage medium for laser processing equipment, so as to solve the problems of large errors and slow efficiency in traditional methods of adjusting the concentricity of the cutting nozzle and the laser beam.

[0006] To address the aforementioned technical problems, this application provides a calibration method for a laser processing equipment. The laser processing equipment comprises a laser emission device, a charge-coupled device (CCD), a built-in motor, and an auxiliary workpiece. The CCCD is coaxial with the auxiliary workpiece. The method employs the following technical solution:

[0007] Obtain the laser position coordinates of the auxiliary fixed workpiece;

[0008] Calculate the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates;

[0009] The pixel coordinates of the suction nozzle at the center of the auxiliary fixed workpiece are identified using image recognition technology;

[0010] Calculate the axial distance from the nozzle pixel coordinates to the axial plane coordinates based on the mapping transformation relationship;

[0011] The auxiliary fixed workpiece is concentrically calibrated according to the axial distance position.

[0012] To address the aforementioned technical problems, this application also provides a calibration device for laser processing equipment. The laser processing equipment comprises a laser beam emitting device, a charge-coupled device (CCD), a built-in motor, and an auxiliary workpiece. The CCCD is coaxial with the auxiliary workpiece. The device employs the following technical solution:

[0013] A laser position acquisition module is used to acquire the laser position coordinates of the auxiliary fixed workpiece;

[0014] The mapping transformation relationship calculation module calculates the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates;

[0015] The nozzle pixel coordinate recognition module identifies the center pixel coordinates of the nozzle of the auxiliary fixed workpiece using image recognition technology;

[0016] The axial distance position calculation module calculates the axial distance position from the nozzle pixel coordinates to the axial plane coordinates based on the mapping transformation relationship;

[0017] The concentric calibration module performs a concentric calibration operation on the auxiliary fixed workpiece based on the axial distance position.

[0018] To address the aforementioned technical problems, this application also provides a computer device that employs the following technical solution:

[0019] It includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the calibration method for the laser processing equipment as described above.

[0020] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, employing the technical solution described below:

[0021] The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the calibration method for the laser processing equipment as described above.

[0022] This application provides a calibration method for laser processing equipment, comprising: acquiring the laser position coordinates of an auxiliary fixed workpiece; calculating the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates; identifying the nozzle pixel coordinates at the center of the auxiliary fixed workpiece using image recognition technology; calculating the axial distance position from the nozzle pixel coordinates to the axial plane coordinates based on the mapping transformation relationship; and performing a concentric calibration operation on the auxiliary fixed workpiece based on the axial distance position. Compared with the prior art, this application calibrates the mapping transformation relationship between the image plane and the axial plane by positioning the cutting nozzle at different positions on the coaxial CCD, thereby achieving precise adjustment of the laser cutting nozzle position to meet the stringent precision requirements of laser cutting processes. Attached Figure Description

[0023] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is an exemplary system architecture diagram to which this application can be applied;

[0025] Figure 2 This is a flowchart illustrating the implementation of the calibration method for the laser processing equipment provided in this application embodiment;

[0026] Figure 3 This is a schematic diagram of an irregularly shaped cutting nozzle provided in an embodiment of this application;

[0027] Figure 4 This is a schematic diagram illustrating the use of the molten pool width to locate the laser point, provided in an embodiment of this application.

[0028] Figure 5 This is a schematic diagram of the mapping transformation relationship between the axial plane and the CCD image plane provided in the embodiments of this application;

[0029] Figure 6 This is a schematic diagram of generating a straight line intersecting the edge of the suction nozzle, provided in an embodiment of this application.

[0030] Figure 7 This is a schematic diagram showing the formation of pixels between a straight line edge and the nozzle edge, provided in an embodiment of this application.

[0031] Figure 8 This is a schematic diagram showing the pixels where the confirmed straight line intersects with the suction nozzle, provided in an embodiment of this application.

[0032] Figure 9 This is a schematic diagram of a suction nozzle with abnormal edges provided in an embodiment of this application;

[0033] Figure 10 This is a schematic diagram of the structure of the calibration device for the laser processing equipment provided in the embodiments of this application;

[0034] Figure 11 This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0036] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0037] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0038] like Figure 1 As shown, system architecture 100 may include terminal device 101, network 102, and server 103. Terminal device 101 may be a laptop 1011, tablet 1012, or mobile phone 1013. Network 102 is used as a medium to provide a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0039] Users can use terminal device 101 to interact with server 103 via network 102 to receive or send messages, etc. Various communication client applications can be installed on terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

[0040] Terminal device 101 can be various electronic devices with a display screen and support web browsing. In addition to laptops 1011, tablets 1012, or mobile phones 1013, terminal device 101 can also be an e-book reader, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, and desktop computer, etc.

[0041] Server 103 can be a server that provides various services, such as a backend server that provides support for the pages displayed on terminal device 101.

[0042] It should be noted that the calibration method for the laser processing equipment provided in this application embodiment is generally executed by a server / terminal device, and correspondingly, the calibration device for the laser processing equipment is generally located in the server / terminal device.

[0043] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0044] Continue to refer to Figure 2 The diagram illustrates a flowchart of an embodiment of the calibration method for a laser processing apparatus according to this application. The calibration method for the laser processing apparatus includes steps S201, S202, S203, S204, and S205.

[0045] In step S201, the laser position coordinates of the auxiliary fixed workpiece are obtained.

[0046] In this embodiment, the auxiliary workpiece fixation system is a key component in the laser cutting system, and the laser emitted from it has a specific position in space. Obtaining the laser position coordinates typically requires a series of high-precision measuring devices or sensors. For example, a laser interferometer can be used, which can measure the positional changes of the laser beam in space with extremely high precision. By arranging multiple measurement points of the laser interferometer within the working area of ​​the laser cutting equipment, these measurement points can capture the positional information of the laser beam in real time and transmit the data to the control system. Alternatively, a visual positioning system can be used. An industrial camera is installed near the auxiliary workpiece fixation system. The camera captures the position of the laser beam spot on a specific target. Combining the camera's calibration parameters and spatial geometric relationships, image processing and calculations are performed to determine the laser's position coordinates in three-dimensional space. This step is the foundation for all subsequent calculations and calibration operations; accurate laser position coordinates ensure the accuracy of subsequent calculations.

[0047] In step S202, the mapping transformation relationship between the axial plane and the CCD image plane is calculated based on the laser position coordinates.

[0048] In this embodiment, the axial plane typically refers to the plane in a laser cutting device related to the motion axis (such as the X, Y, and Z axes), representing the coordinate space of the actual movement of the device. The CCD image plane, on the other hand, is the plane on which the industrial camera (CCD camera) images are captured; the image information captured by the camera resides on this plane. Since the axial plane and the CCD image plane are two different coordinate systems, with differences in spatial position and geometric relationships, a mapping transformation relationship needs to be established to achieve coordinate transformation between them.

[0049] In this embodiment, the calculation of this mapping transformation relationship typically employs a camera calibration method. First, a calibration board with a known geometry and size is placed on the axial plane, containing multiple feature points (such as the corner points of a checkerboard pattern). Then, a CCD camera is used to photograph the calibration board from different angles, acquiring multiple images containing these feature points. These images are processed to extract the pixel coordinates of the feature points. Simultaneously, based on the actual size and position of the calibration board on the axial plane, the coordinates of the feature points on the axial plane are determined. Next, using these corresponding pixel coordinates and axial plane coordinates, mathematical algorithms (such as the Zhang Zhengyou calibration method) are employed to calculate the camera's intrinsic parameters (focal length, principal point coordinates, etc.) and extrinsic parameters (rotation matrix and translation vector). These parameters describe the mapping transformation relationship between the CCD image plane and the axial plane. Once this mapping transformation relationship is established, the pixel coordinates on the CCD image plane can be accurately converted to coordinates on the axial plane, and vice versa.

[0050] In step S203, the pixel coordinates of the suction nozzle at the center of the workpiece are identified using image recognition technology.

[0051] In this embodiment, image recognition technology is mainly used to accurately identify the center position of the auxiliary fixed workpiece from the image captured by the CCD camera and obtain its corresponding pixel coordinates. First, the image acquired by the CCD camera needs to be preprocessed, including noise reduction (such as using Gaussian filtering) and image enhancement (such as histogram equalization) to improve image quality and facilitate subsequent feature extraction.

[0052] In this embodiment, image segmentation algorithms (such as threshold-based segmentation, edge detection algorithms, etc.) are used to separate the auxiliary fixed workpiece from the image background. For example, by setting an appropriate grayscale threshold, the nozzle portion (usually with a specific grayscale range) in the image can be distinguished from the background. Next, feature extraction methods (such as contour detection, circle fitting, etc.) are used to accurately determine the shape and center position of the nozzle. If the nozzle shape is approximately circular, the center pixel coordinates of the nozzle can be obtained by detecting the nozzle's contour and then performing circle fitting using the least squares method. The key to this step is selecting appropriate image processing algorithms and parameters to ensure accurate and stable identification of the nozzle's center position and obtaining precise pixel coordinates.

[0053] In step S204, the axial distance position from the nozzle pixel coordinates to the axial plane coordinates is calculated according to the mapping transformation relationship.

[0054] In this embodiment, after obtaining the pixel coordinates of the nozzle and the mapping transformation relationship between the axial plane and the CCD image plane, the pixel coordinates of the nozzle can be converted into coordinates on the axial plane. Specifically, the pixel coordinates of the nozzle are substituted into the mapping transformation formula obtained through camera calibration, and after a series of matrix operations (including rotation and translation transformations), the coordinates of the nozzle on the axial plane are obtained.

[0055] In this embodiment, the target axis plane coordinates typically refer to the accurate position coordinates at which the workpiece center is expected to be fixed during laser cutting. Calculating the axis distance involves comparing the actual coordinates of the nozzle on the axis plane with the target axis plane coordinates. By calculating the difference between the two, the distance deviation of the nozzle on the axis plane is obtained. This distance deviation includes components in the X, Y, and Z axis directions, representing the degree of deviation of the nozzle from the target position in the horizontal (X, Y axes) and vertical (Z axis) directions, respectively. This method clearly shows the difference between the current position and the desired position of the nozzle, providing a basis for subsequent calibration operations.

[0056] In step S205, the auxiliary fixed workpiece is concentrically calibrated according to the axial distance position.

[0057] In this embodiment, the pixel coordinates of the nozzle center identified by the image can be transformed into the axial distance position from the center of the cutting nozzle to the center of the laser point through a mapping transformation matrix, thereby driving the cutting nozzle to compensate for this distance position and achieving concentric calibration between the cutting nozzle and the laser point.

[0058] This application provides a calibration method for a laser processing equipment, comprising: acquiring the laser position coordinates of an auxiliary fixed workpiece; calculating the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates; identifying the nozzle pixel coordinates at the center of the auxiliary fixed workpiece using image recognition technology; calculating the axial distance position from the nozzle pixel coordinates to the axial plane coordinates based on the mapping transformation relationship; and performing a concentric calibration operation on the auxiliary fixed workpiece based on the axial distance position. Compared with the prior art, this application calibrates the mapping transformation relationship between the image plane and the axial plane by positioning the cutting nozzle at different positions on the coaxial CCD, eliminates abnormal edges of the nozzle based on the sampling consistency circle method, obtains the true geometric center of the nozzle, and achieves precise adjustment of the laser cutting nozzle position through the mapping transformation relationship to meet the stringent precision requirements of the laser cutting process.

[0059] In some optional implementations of the embodiments of this application, the step of obtaining the laser position coordinates of the auxiliary fixed workpiece specifically includes the following steps:

[0060] The laser beam-emitting device is activated to form a laser starting point on the laser photographic paper;

[0061] The workpiece is moved a preset distance l along the direction of the first photo paper on the laser photo paper by the built-in motor drive;

[0062] The laser that assists in fixing the workpiece is turned off, and the workpiece is moved a preset distance l along the second photographic paper direction, which is opposite to the first photographic paper direction, by the built-in motor.

[0063] The laser that assists in fixing the workpiece is activated, and the workpiece is moved a preset distance l on the laser photographic paper along a third photographic paper direction perpendicular to the first photographic paper direction, driven by the built-in motor.

[0064] Turn off the laser that assists in fixing the workpiece, and obtain images of two intersecting molten pools on the laser photographic paper using image recognition technology;

[0065] Calculate the coordinates of the intersection point of the two intersecting molten pool images to obtain the laser position coordinates for assisting in fixing the workpiece.

[0066] In this embodiment, laser dotting is used to determine the center of the laser dot. A sheet of black 3M photographic paper is attached tightly to the underside of the cutting nozzle, and the laser power is adjusted to create a white, circular dot. During production, it was found that lasers of different power levels produce different laser spots even at the same power. For example, a 10000W laser and a 3000W laser producing the same 1000W power produce significantly different laser spots. Combined with the short single-point emission time and the inconsistency of the lasers, this results in non-standard laser spots with various irregular shapes, as shown in the attached figure. Figure 3 As shown.

[0067] In this embodiment, the geometric center of the irregularly shaped light spot is not necessarily the actual location of the laser emission. If a conventional segmentation algorithm is used to determine the geometric center of the light spot, it may cause the detection of the actual laser point to be off-target, introducing errors into the calibration model. Figure 4 As shown, this invention proposes a method to find the actual laser point position by fitting the straight edge of the molten pool width. This method can significantly improve the accuracy of the detection point and eliminate the inconsistency problem caused by lasers of different power levels. Specifically:

[0068] a. Drive the nozzle to move upward a distance l from P0(0,0) as the starting point. During this process, the laser is turned on to form the first spot. Return to the starting point P0(0,0) and move to the right a distance l. During this process, the laser is turned on to form the second spot. Two intersecting molten pool widths are formed at the P0(0,0) position.

[0069] b. Using a line detection tool, the first and second fused pools formed at position P0(0,0) are detected respectively. Based on the image of the first fused pool, the first outer line l1 and the second outer line l2 are obtained, and the first angle bisector l3 of the first fused pool is calculated based on the first outer line l1 and the second outer line l2. Similarly, based on the image of the second fused pool, the fourth outer line l4, the fifth outer line l5, and the second angle bisector l6 of the second fused pool can be obtained. The intersection point (u0,v0) of the angle bisectors l3 and l6 is calculated, and this intersection point is the actual pixel position of P0(0,0).

[0070] Compared with the prior art, this application can obtain the precise laser position coordinates of the auxiliary fixed workpiece at position P0(0,0).

[0071] In some optional implementations of the embodiments of this application, the step of calculating the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates specifically includes the following steps:

[0072] The built-in motor drives the workpiece to be fixed so that the laser position coordinates move on the axis plane to the initial axis plane coordinates P0(0,0);

[0073] The pixel point of the auxiliary fixed workpiece with initial axis plane coordinates P0(0,0) on the CCD image plane is determined as the initial CCD image plane coordinates (u0,v0);

[0074] The built-in motor drives the auxiliary workpiece to move the laser position coordinates in the X-axis direction on the axial plane by a distance Δx, and drives the auxiliary workpiece to move the laser position coordinates in the Y-axis direction on the axial plane by a distance Δy, thus obtaining the target axial plane coordinates P1(Δx, Δy).

[0075] The pixel point of the auxiliary fixed workpiece with target axis plane coordinates P1(Δx, Δy) on the CCD image plane is determined as the target CCD image plane coordinates (u1, v1);

[0076] The mapping transformation relationship between the axis plane and the CCD image plane is calculated based on the initial CCD image plane coordinates (u0, v0), the target axis plane coordinates P1 (Δx, Δy), and the target CCD image plane coordinates (u1, v1).

[0077] In the embodiments of this application, as shown in the appendix Figure 5 As shown, the coordinate system relationship between the axial plane and the CCD image plane can be represented by three parameters: scaling factor S, rotation angle θ, and offset distance D. Their transformation relationship is as follows:

[0078] x=S(ucosθ-vsinθ)+D X ;

[0079] y = S(usinθ - vcosθ) + D y ;

[0080] Where (x,y) represents a point on the axial plane, and (u,v) represents a pixel on the CCD image plane, the matrix transformation relationship can be expressed as:

[0081]

[0082] Taking the position of the laser point as the starting point, as shown in the attached figure. Figure 5 As shown, P0(0,0) is the origin of the axis plane coordinate system and the first point to be calibrated, with its corresponding pixel point being (u0,v0); the axis plane drives the cutting nozzle to move Δx in the x-axis direction and Δy in the y-axis direction, that is, P1(Δx,Δy) in the figure above is the second point to be calibrated, with its corresponding pixel point being (u1,v1).

[0083] The scaling factor S can be solved:

[0084]

[0085] The rotation angle θ can be solved:

[0086]

[0087] The offset distance D can be solved:

[0088] D x = -S(u0cosθ-v0sinθ);

[0089] D y = -S(u0sinθ+v0cosθ);

[0090] Given the axial positions of two calibration points, their corresponding pixel coordinates can be obtained through image recognition, allowing us to determine the mapping relationship between the axial plane and the CCD image plane:

[0091]

[0092] In some optional implementations of the embodiments of this application, when the nozzle moves to position P1(Δx, Δy), the actual laser point position can be found by fitting the straight edge of the molten pool width. Specifically:

[0093] a. Drive the nozzle to move upward a distance l from P1(Δx, Δy) as the starting point. During this process, the laser is turned on to form the third spot. Return to the starting point P1(Δx, Δy) and move to the right a distance l. During this process, the laser is turned on to form the fourth spot. Two intersecting molten pool widths are formed at the P1(Δx, Δy) position.

[0094] b. Using a line detection tool, detect the third and fourth fused pools formed at position P1(Δx, Δy). Obtain the fifth outer line l1' and the sixth outer line l2' from the image of the third fused pool, and obtain the third fused pool's angle bisector l3' from the fifth outer line l1' and the sixth outer line l2'. Similarly, obtain the seventh outer line l4', the eighth outer line l5', and the fourth fused pool's angle bisector l6' from the image of the fourth fused pool. Calculate the intersection point (u1, v1) of the angle bisectors l3' and l6'. This intersection point is the actual pixel position of P1(Δx, Δy).

[0095] In some optional implementations of the embodiments of this application, the aforementioned auxiliary workpiece fixing device is a laser cutting nozzle, and the step of identifying the nozzle pixel coordinates of the center of the auxiliary workpiece fixing device using image recognition technology specifically includes the following steps:

[0096] Obtain the edge contour of the suction nozzle that assists in fixing the workpiece;

[0097] The geometric center of the nozzle edge contour is obtained based on the segmentation algorithm;

[0098] Starting from the geometric center, straight lines intersecting the edge of the suction nozzle are generated at preset angular intervals to obtain a set of suction nozzle intersection points;

[0099] The valid nozzle intersection points in the nozzle intersection point set are determined according to the consistency circle algorithm;

[0100] Calculate the proportion of the effective nozzle intersection points to the set of nozzle intersection points;

[0101] Determine whether the ratio meets the preset ratio threshold;

[0102] If the ratio meets the preset ratio threshold, then the least squares fitting operation is performed on the intersection point of the effective nozzles to obtain the center of the effective nozzle circle;

[0103] The center of the effective suction nozzle is determined as the nozzle pixel coordinate.

[0104] In this embodiment of the application, in a laser cutting system, in order to perform operations such as precise positioning, calibration or quality inspection of the auxiliary fixed workpiece, obtaining the edge contour of the suction nozzle is a crucial first step. Specifically, the method for obtaining the edge contour of the suction nozzle can be based on edge contour acquisition from image acquisition, or it can be based on edge contour acquisition from laser scanning.

[0105] In this embodiment of the application, after obtaining the edge contour of the nozzle, it is necessary to further determine the center position of the nozzle, which is usually represented in the form of pixel coordinates.

[0106] In this embodiment, the application uses a sampling consistency circle method to eliminate abnormal edges of the nozzle and obtain the true geometric center of the nozzle. Specifically:

[0107] (1) After obtaining the geometric center o(u, v) of the nozzle edge contour, a set of straight lines intersecting the nozzle edge are generated with the geometric center o(u, v) as the starting point and the angle interval α, as shown in the attached figure. Figure 6 As shown, the purpose is to find the intersection point of the straight line and the edge of the nozzle;

[0108] (2) Starting from the geometric center o(u, v), with an angular interval of α, generate a set of straight lines intersecting the edge of the nozzle, as shown in the attached figure. Figure 6 As shown, the purpose is to find the intersection point of the straight line and the edge of the nozzle, reduce the number of points to be calculated, and improve the speed of the algorithm.

[0109] (3) The effective nozzle intersection points are determined in the nozzle intersection point set by using the algorithm idea of ​​sampling consistency circle.

[0110] In some optional implementations of the embodiments of this application, before applying the sampling consistency circle algorithm, the distance from the intersection point to the preliminary geometric center o(u, v) can be calculated, and the points can be sorted from largest to smallest to generate a sorted set of intersection points M(u, v). i ,v i ), i = 1, 2, ..., n. This sorting mainly considers that intersections with large distances are more likely to be points on the normal edge of the suction nozzle. Prioritizing points on the normal edge can improve the algorithm speed.

[0111] Compared with existing technologies, this application can obtain the true geometric center of the laser cutting nozzle through the algorithm of sampling consistency circle.

[0112] In some optional implementations of the embodiments of this application, the step of generating straight lines intersecting the edge of the nozzle at preset angular intervals, starting from the geometric center, to obtain the set of nozzle intersection points specifically includes the following steps:

[0113] Iterate through the edge contour of each straight line that intersects the edge of the nozzle and the intersecting pixels on the edge contour of the nozzle in turn;

[0114] Identify the target intersecting pixels in the intersecting pixels, and construct the straight line equations for the nozzle edge and the straight line equations for the straight line edge based on the target intersecting pixels;

[0115] By performing joint calculations on the equations of the straight lines at the nozzle edge and the straight lines at the edge, the set of nozzle intersection points is obtained.

[0116] In this embodiment of the application, the intersection area of ​​the scanned straight line and the edge of the nozzle is used to generate a set of intersection points (u i ,v i Let i = 1, 2, ..., n, where n is the number of intersection points. A conventional method for finding intersection points is to iterate through the points on the line; if a point on the nozzle edge lies on the line, that pixel is taken as the intersection point. This method only achieves pixel-level accuracy, and when there are burrs on the edge, the intersection point may be detected in the burr area, causing a misalignment in the actual intersection point detection. For example... Figure 7 As shown, pixel 1 represents the edge of the nozzle, pixel 2 represents the edge of the straight line, and pixel 3 represents the intersection of the straight line and the nozzle. It is clear from the image that the protrusion of the nozzle edge causes a misalignment in the detection of the actual intersection point. To solve this problem, this invention proposes a method that scans the left and right neighboring pixels to fit two straight lines respectively, and then finds the intersection point of the nozzle edge and the straight line edge. This method achieves sub-pixel accuracy and can remove the influence of burrs or interference points, improving recognition accuracy. Specifically:

[0117] a. As attached Figure 8As shown, traverse the pixels on the edge of the straight line and the edge of the nozzle, and find the pixel numbered 3, which is the pixel p0 where the straight line and the nozzle intersect.

[0118] b. Starting from pixel p0, scan the pixels with a distance of d between the left and right adjacent pixels on the edge of the nozzle to obtain a set of 2d pixels numbered 1. Fit the linear equation A1x+B1y+C1=0 of the pixel set using the least squares method.

[0119] c. Starting from pixel p0, scan the pixels with a distance of d between the left and right adjacent pixels on the edge of the straight line to obtain a set of 2d pixels numbered 2. Fit the straight line equation A2x+B2y+C2=0 using the least squares method.

[0120] d. By combining the linear equations A1x+B1y+C1=0 and A2x+B2y+C2=0, the sub-pixel precision intersection point of the line edge and the nozzle edge can be obtained.

[0121] Compared with existing technologies, this application can obtain a set of nozzle intersection points with sub-pixel precision.

[0122] In some optional implementations of the embodiments of this application, the step of determining the valid nozzle intersection points in the nozzle intersection point set according to the consistency circle algorithm specifically includes the following steps:

[0123] Obtain three non-repeating target nozzle intersection points from the set of nozzle intersection points, and construct a target circle based on the three target nozzle intersection points;

[0124] Calculate the distance difference from each of the nozzle intersection points (excluding the target nozzle intersection point) to the target circle in each set of nozzle intersection points;

[0125] Determine whether the distance difference meets a preset error threshold;

[0126] If the distance difference meets the preset error threshold, then the intersection point of the target nozzles is determined as the effective nozzle intersection point;

[0127] If the distance difference does not meet the preset error threshold, the intersection point of the target nozzles is determined as an invalid nozzle intersection point;

[0128] Among the nozzle intersection points in the set of nozzle intersection points excluding the target nozzle intersection point, three non-repeating nozzle intersection points are selected as target nozzle intersection points. The target nozzle intersection points are then reconfirmed to confirm whether they are valid nozzle intersection points. This process continues until all nozzle intersection points in the set of nozzle intersection points have been confirmed.

[0129] In this embodiment of the application, the step of determining the valid nozzle intersection points in the nozzle intersection point set according to the consistency circle algorithm can specifically be:

[0130] Choose 3 unique points from the set of intersection points M. These 3 intersection points can generate a circle (uA). 2 +(vB) 2 =R 2 Calculate the distance difference from each of the other intersection points to the circle. When d i When the value is less than or equal to "error", the intersection point is considered to be a point on the circle. In each iteration, the set of intersection points with the largest number of occurrences is updated. When the proportion of points on the circle exceeds a certain percentage w, the current set of intersection points is considered the target set m, and the iteration ends. The target set m is then fitted using the least squares method, and the resulting circle's center is the actual center coordinate of the nozzle. In each iteration, three unique points are selected from the intersection set M.

[0131] a. First, copy the intersection point set M to M1, M2, and M3. The first point is selected from the first point in M1, and the first point in M2 and M3 is set to true, indicating that it has been visited and cannot be selected. The second point is selected from the second point in M2, and the second point in M3 is set to true. The third point is selected from the third point in M3. Check if the termination condition is met. If not, proceed to the next iteration cycle. The first and second points remain unchanged, and the third point is selected from the fourth point in M3, and so on. If the termination condition is not met, the third point can select all points that do not overlap with the first and second points.

[0132] b. If the first and second points remain unchanged, and the third point visits all non-repeating points but the termination condition is still not met, continue to the next iteration cycle. Then, the first point remains unchanged, the second point selects the third point in M2, and the third point in M3 is set to true. According to step a, visit all points in M3 that are not repeated by the first and second points.

[0133] c. If the first point remains unchanged, and the second and third points have visited all points but the termination condition is still not met, continue to the next iteration cycle. Then, select the second point in M1 as the first point, initialize all points in M2 and M3 to false, and set the first and second points in M2 and M3 to true, indicating that they have been visited and cannot be selected. Continue with steps a and b, and so on. If the termination condition is not met, all the possible cases of visiting the three non-repeating points in the intersection point set M can be reached.

[0134] In some optional implementations of the embodiments of this application, after the step of determining whether the ratio meets the preset ratio threshold, the following steps are further included:

[0135] If the ratio does not meet the preset ratio threshold, it is determined that the auxiliary fixed workpiece is not damaged, and the step of determining the nozzle pixel coordinates based on the geometric center is executed.

[0136] In this embodiment of the application, during the laser cutting process, due to prolonged cutting, some cutting nozzles suffer edge damage, resulting in abnormal edges, as shown in the attached figure. Figure 9 As shown, some nozzles with abnormal edges are not completely damaged and can still be used. It is necessary to determine whether the current auxiliary workpiece fixing is usable. Specifically:

[0137] (1) After obtaining the geometric center o(u, v) of the nozzle edge contour, a set of straight lines intersecting the nozzle edge are generated with the geometric center o(u, v) as the starting point and the angle interval α, as shown in the attached figure. Figure 6 As shown, the purpose is to find the intersection point of the straight line and the edge of the nozzle;

[0138] (2) Calculate the distance from the intersection point to the preliminary geometric center o(u, v), sort the intersection points from largest to smallest, and generate the sorted intersection point set M(u, v). i ,v i ), i = 1, 2, ..., n. This sorting mainly considers that intersections with large distances are more likely to be points on the normal edge of the suction nozzle. Prioritizing points on the normal edge can improve the algorithm speed.

[0139] (3) The algorithm idea of ​​sampling consistency circle: Select 3 non-repeating points from the intersection point set M. The 3 intersection points can generate a circle (uA). 2 +(vB) 2 =R 2 Calculate the distance difference from each of the other intersection points to the circle. When d i If <= error, the intersection point is considered to be a point on the circle. In the loop iteration cycle, each iteration needs to update the set of intersection points with the largest number. When the proportion of points on the circle that meet the criteria exceeds a certain proportion w, the auxiliary fixing workpiece is considered to be undamaged and can be used normally. Otherwise, the auxiliary fixing workpiece is determined to be damaged, and the nozzle pixel coordinates of the new auxiliary fixing workpiece can only be obtained after replacing it with a new auxiliary fixing workpiece.

[0140] Compared with the prior art, this application can determine whether the laser cutting nozzle is damaged based on the geometric center of the nozzle edge contour.

[0141] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0142] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0143] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0144] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0145] Further reference Figure 10 As a response to the above Figure 2 The implementation of the method shown in this application provides an embodiment of a calibration device for laser processing equipment, which is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0146] like Figure 10 As shown, the calibration device 200 of the laser processing equipment in this application embodiment includes:

[0147] The laser position acquisition module 210 is used to acquire the laser position coordinates of the workpiece that is assisted in fixing it.

[0148] The mapping transformation relationship calculation module 220 calculates the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates.

[0149] The nozzle pixel coordinate recognition module 230 identifies the nozzle pixel coordinates of the center of the workpiece using image recognition technology;

[0150] The axial distance position calculation module 240 calculates the axial distance position from the nozzle pixel coordinates to the axial plane coordinates based on the mapping transformation relationship;

[0151] The concentric calibration module 250 performs concentric calibration on the cutting nozzle based on the axial distance position.

[0152] In this embodiment, a calibration device 200 for laser processing equipment is provided, comprising: a laser position acquisition module 210 for acquiring the laser position coordinates of an auxiliary workpiece; a mapping transformation relationship calculation module 220 for calculating the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates; a nozzle pixel coordinate recognition module 230 for recognizing the nozzle pixel coordinates at the center of the auxiliary workpiece using image recognition technology; an axial distance position calculation module 240 for calculating the axial distance position from the nozzle pixel coordinates to the axial plane coordinates based on the mapping transformation relationship; and a concentric calibration module 250 for performing concentric calibration on the cutting nozzle based on the axial distance position. Compared with the prior art, this application calibrates the mapping transformation relationship between the image plane and the axial plane by positioning the cutting nozzle at different positions on the coaxial CCD, eliminates abnormal edges of the nozzle based on the sampling consistency circle method, obtains the true geometric center of the nozzle, and achieves precise adjustment of the laser cutting nozzle position through the mapping transformation relationship to meet the stringent precision requirements of the laser cutting process.

[0153] In some optional implementations of the embodiments of this application, the laser position acquisition module includes:

[0154] The laser starter submodule is used to start the laser that assists in fixing the workpiece to form the laser starting point on the laser photographic paper;

[0155] The first laser moving submodule is used to move the fixed workpiece along the direction of the first photo paper on the laser photo paper by a preset distance l according to the built-in motor drive;

[0156] The second laser moving submodule is used to turn off the laser that assists in fixing the workpiece, and to move the workpiece a preset distance l along the second photo paper direction opposite to the first photo paper direction according to the built-in motor driving the workpiece to be fixed.

[0157] The third laser moving submodule is used to activate the laser that assists in fixing the workpiece, and to drive the workpiece to move a preset distance l on the laser photographic paper along the third photographic paper direction perpendicular to the first photographic paper direction according to the built-in motor.

[0158] The molten pool image acquisition submodule is used to turn off the laser that assists in fixing the workpiece and acquire two intersecting molten pool images on the laser photographic paper based on image recognition technology.

[0159] The laser position acquisition submodule is used to calculate the coordinates of the intersection point of two intersecting molten pool images to obtain the laser position coordinates for assisting in fixing the workpiece.

[0160] In some optional implementations of the embodiments of this application, the above-mentioned mapping transformation relationship calculation module includes:

[0161] The initial axis plane coordinate determination submodule is used to fix the workpiece with the help of the built-in motor drive so that the laser position coordinates move on the axis plane to the initial axis plane coordinates P0(0,0);

[0162] The initial CCD image plane coordinate determination submodule is used to determine the pixel point of the auxiliary fixed workpiece with initial axis plane coordinate P0(0,0) on the CCD image plane as the initial CCD image plane coordinate (u0,v0);

[0163] The target axis plane coordinate determination submodule is used to determine the target axis plane coordinates P1(Δx, Δy) by using the built-in motor to drive the workpiece to move the laser position coordinates in the axis plane by a distance Δx in the X-axis direction and a distance Δy in the Y-axis direction.

[0164] The target CCD image plane coordinate determination submodule is used to determine the pixel point of the auxiliary fixed workpiece with target axis plane coordinate P1(Δx, Δy) on the CCD image plane as the target CCD image plane coordinate (u1, v1);

[0165] The mapping transformation calculation submodule is used to calculate the mapping transformation relationship between the axis plane and the CCD image plane based on the initial CCD image plane coordinates (u0, v0), the target axis plane coordinates P1 (Δx, Δy), and the target CCD image plane coordinates (u1, v1).

[0166] In some optional implementations of the embodiments of this application, the above mapping transformation relationship T is represented as:

[0167]

[0168] Where S represents the scaling factor, θ represents the rotation angle, and D represents the offset distance, the scaling factor S is expressed as:

[0169]

[0170] The rotation angle θ is expressed as:

[0171]

[0172] The offset distance D is represented as:

[0173] D x = -S(u0 cosθ - v0 sinθ)

[0174] D y = -S(u0 sinθ+v0 cosθ).

[0175] In some optional implementations of the embodiments of this application, the aforementioned auxiliary workpiece fixing device is a laser cutting nozzle, and the aforementioned nozzle pixel coordinate recognition module includes:

[0176] The nozzle edge contour acquisition submodule is used to acquire the nozzle edge contour that helps fix the workpiece.

[0177] The geometric center calculation submodule is used to obtain the geometric center of the nozzle edge contour based on the segmentation algorithm;

[0178] The nozzle intersection point set acquisition submodule is used to generate straight lines intersecting with the nozzle edge at preset angle intervals, starting from the geometric center, to obtain the nozzle intersection point set;

[0179] The target circle construction submodule is used to obtain three non-repeating target nozzle intersection points from the nozzle intersection point set, and construct a target circle based on the three target nozzle intersection points;

[0180] The distance difference calculation submodule is used to calculate the distance difference from each nozzle intersection point (excluding the target nozzle intersection point) to the target circle in each nozzle intersection point set.

[0181] The error threshold judgment submodule is used to determine whether the distance difference meets the preset error threshold.

[0182] The effective nozzle intersection point determination submodule is used to determine the target nozzle intersection point as the effective nozzle intersection point if the distance difference meets the preset error threshold.

[0183] The invalid nozzle intersection point determination submodule is used to determine the target nozzle intersection point as an invalid nozzle intersection point if the distance difference does not meet the preset error threshold.

[0184] The loop iteration submodule is used to obtain three non-repeating nozzle intersection points from the nozzle intersection point set other than the target nozzle intersection point as the target nozzle intersection point, and to reconfirm whether the target nozzle intersection point is a valid nozzle intersection point.

[0185] The effective nozzle intersection point ratio acquisition submodule is used to obtain the ratio of effective nozzle intersection points to the total effective nozzle intersection points in the nozzle intersection point set after all nozzle intersection points in the nozzle intersection point set have completed the confirmation operation.

[0186] The ratio threshold judgment submodule is used to determine whether the ratio meets the preset ratio threshold.

[0187] The effective nozzle center acquisition submodule is used to perform least squares fitting on the intersection points of the effective nozzles to obtain the effective nozzle center if the ratio meets the preset ratio threshold.

[0188] The nozzle pixel coordinate determination submodule is used to determine the effective nozzle center as the nozzle pixel coordinate.

[0189] In some optional implementations of the embodiments of this application, the above-mentioned nozzle intersection point set acquisition submodule includes:

[0190] The intersecting pixel traversal unit is used to sequentially traverse the edge contour of each straight line that intersects the edge of the nozzle and the intersecting pixels on the edge contour of the nozzle.

[0191] The line equation construction unit is used to identify the target intersecting pixels in the intersecting pixels, and to construct the nozzle edge line equation and the line edge line equation based on the target intersecting pixels;

[0192] The joint calculation unit is used to perform joint calculation operations on the straight line equation of the nozzle edge and the straight line equation of the straight line edge, respectively, to obtain the set of nozzle intersection points.

[0193] In some optional implementations of the embodiments of this application, the above-mentioned nozzle pixel coordinate recognition module further includes:

[0194] The damage confirmation submodule is used to determine that the auxiliary fixed workpiece is not damaged if the ratio does not meet the preset ratio threshold, and to perform the step of determining the nozzle pixel coordinates based on the geometric center.

[0195] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 11 , Figure 11 This is a basic structural block diagram of a computer device according to an embodiment of this application.

[0196] The computer device 300 includes a memory 310, a processor 320, and a network interface 330 that are interconnected via a system bus. It should be noted that only the computer device 300 with components 310-330 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0197] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0198] The memory 310 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 310 may be an internal storage unit of the computer device 300, such as the hard disk or memory of the computer device 300. In other embodiments, the memory 310 may also be an external storage device of the computer device 300, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. Of course, the memory 310 may also include both internal storage units and external storage devices of the computer device 300. In this embodiment, the memory 310 is typically used to store the operating system and various application software installed on the computer device 300, such as computer-readable instructions for calibration methods of laser processing equipment. Furthermore, the memory 310 can also be used to temporarily store various types of data that have been output or will be output.

[0199] In some embodiments, the processor 320 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 320 is typically used to control the overall operation of the computer device 300. In this embodiment, the processor 320 is used to execute computer-readable instructions stored in the memory 310 or to process data, such as computer-readable instructions for executing a calibration method for the laser processing equipment.

[0200] The network interface 330 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 300 and other electronic devices.

[0201] The computer equipment provided in this application calibrates the mapping transformation relationship between the image plane and the axial plane by positioning the cutting nozzle at different positions on the coaxial CCD. Based on the sampling consistency circle method, it eliminates abnormal edges of the nozzle and obtains the true geometric center of the nozzle. Through the mapping transformation relationship, it achieves precise adjustment of the position of the auxiliary fixed workpiece to meet the strict precision requirements of the laser cutting process.

[0202] This application also provides another embodiment, namely, a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor to cause the at least one processor to perform the steps of the calibration method for the laser processing equipment as described above.

[0203] The computer-readable storage medium provided in this application calibrates the mapping transformation relationship between the image plane and the axial plane by positioning the cutting nozzle at different positions on a coaxial CCD. It eliminates abnormal edges of the nozzle based on the sampling consistency circle method, obtains the true geometric center of the nozzle, and achieves precise adjustment of the position of the auxiliary fixed workpiece through the mapping transformation relationship to meet the strict precision requirements of the laser cutting process.

[0204] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0205] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A calibration method for a laser processing equipment, the laser processing equipment comprising a laser beam emitting device, a charge-coupled device (CCD), a built-in motor, and an auxiliary workpiece, wherein the CCDD is coaxial with the auxiliary workpiece, characterized in that... Includes the following steps: Obtain the laser position coordinates of the auxiliary fixed workpiece; Calculate the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates; The pixel coordinates of the suction nozzle at the center of the auxiliary fixed workpiece are identified using image recognition technology; Calculate the axial distance from the nozzle pixel coordinates to the axial plane coordinates based on the mapping transformation relationship; The auxiliary fixed workpiece is concentrically calibrated according to the axial distance position.

2. The calibration method for laser processing equipment according to claim 1, characterized in that, The step of obtaining the laser position coordinates of the auxiliary fixed workpiece specifically includes the following steps: The laser beam-emitting device is activated to form a laser starting point on the laser photographic paper; The auxiliary fixed workpiece is moved a preset distance l along the first photo paper direction on the laser photo paper by the built-in motor drive; The laser of the auxiliary fixing workpiece is turned off, and the auxiliary fixing workpiece is moved a preset distance l along the second photographic paper direction opposite to the first photographic paper direction by the built-in motor. The laser for the auxiliary fixed workpiece is activated, and the auxiliary fixed workpiece is moved a preset distance l on the laser photographic paper along a third photographic paper direction perpendicular to the first photographic paper direction, driven by the built-in motor. Turn off the laser that assists in fixing the workpiece, and obtain two intersecting molten pool images on the laser photographic paper using image recognition technology; The coordinates of the intersection point of the two intersecting molten pool images are calculated to obtain the laser position coordinates of the auxiliary fixed workpiece.

3. The calibration method for laser processing equipment according to claim 1, characterized in that, The step of calculating the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates specifically includes the following steps: The auxiliary fixed workpiece is driven by the built-in motor to move the laser position coordinates on the axis plane to the initial axis plane coordinates P0(0,0); The pixel point of the auxiliary fixed workpiece with the initial axis plane coordinate P0(0,0) in the CCD image plane is determined as the initial CCD image plane coordinate (u0,v0). The built-in motor drives the auxiliary fixing workpiece to move the laser position coordinates in the X-axis direction on the axial plane by a distance Δx, and drives the auxiliary fixing workpiece to move the laser position coordinates in the Y-axis direction on the axial plane by a distance Δy, thereby obtaining the target axial plane coordinates P1(Δx, Δy). The pixel point of the auxiliary fixed workpiece with the target axis plane coordinate P1(Δx, Δy) on the CCD image plane is determined as the target CCD image plane coordinate (u1, v1); The mapping transformation relationship between the axis plane and the CCD image plane is calculated based on the initial CCD image plane coordinates (u0, v0), the target axis plane coordinates P1 (Δx, Δy), and the target CCD image plane coordinates (u1, v1).

4. The calibration method for laser processing equipment according to claim 3, characterized in that, The mapping transformation relationship T is expressed as follows: Where S represents the scaling factor, θ represents the rotation angle, and D represents the offset distance, the scaling factor S is expressed as: The rotation angle θ is expressed as: The offset distance D is represented as: D x =-S(u0 cosθ-v0 sinθ) D y =-S(u0 sinθ+v0 cosθ)。 5. The calibration method for laser processing equipment according to claim 1, characterized in that, The auxiliary workpiece is a laser cutting nozzle. The step of identifying the nozzle pixel coordinates at the center of the auxiliary workpiece using image recognition technology specifically includes the following steps: Obtain the nozzle edge contour of the auxiliary fixed workpiece; The geometric center of the nozzle edge contour is obtained and calculated according to the segmentation algorithm; Starting from the geometric center, straight lines intersecting the edge of the suction nozzle are generated at preset angular intervals to obtain a set of suction nozzle intersection points; The valid nozzle intersection points in the nozzle intersection point set are determined according to the consistency circle algorithm; Calculate the proportion of the effective nozzle intersection points to the set of nozzle intersection points; Determine whether the ratio meets the preset ratio threshold; If the ratio meets the preset ratio threshold, then the least squares fitting operation is performed on the intersection point of the effective nozzles to obtain the center of the effective nozzle circle; The center of the effective suction nozzle is determined as the nozzle pixel coordinate.

6. The calibration method for laser processing equipment according to claim 5, characterized in that, The step of generating straight lines intersecting the edge of the suction nozzle at preset angular intervals, starting from the geometric center, to obtain the set of intersection points of the suction nozzle specifically includes the following steps: The edge contour of each straight line intersecting the edge of the nozzle and the intersecting pixels on the edge contour of the nozzle are traversed sequentially. Identify the target intersecting pixels among the intersecting pixels, and construct the nozzle edge line equation and the line edge line equation based on the target intersecting pixels; The intersection point set of the nozzle is obtained by performing joint calculations on the straight line equation of the nozzle edge and the straight line equation of the straight line edge.

7. The calibration method for laser processing equipment according to claim 5, characterized in that, The step of determining the valid nozzle intersection points in the nozzle intersection point set according to the consensus circle algorithm specifically includes the following steps: Obtain three non-repeating target nozzle intersection points from the set of nozzle intersection points, and construct a target circle based on the three target nozzle intersection points; Calculate the distance difference from each of the nozzle intersection points (excluding the target nozzle intersection point) to the target circle in each set of nozzle intersection points; Determine whether the distance difference meets a preset error threshold; If the distance difference meets the preset error threshold, then the intersection point of the target nozzles is determined as the effective nozzle intersection point; If the distance difference does not meet the preset error threshold, the intersection point of the target nozzles is determined as an invalid nozzle intersection point; Among the nozzle intersection points in the set of nozzle intersection points excluding the target nozzle intersection point, three non-repeating nozzle intersection points are selected as target nozzle intersection points. The target nozzle intersection points are then reconfirmed to confirm whether they are valid nozzle intersection points. This process continues until all nozzle intersection points in the set of nozzle intersection points have been confirmed.

8. A calibration device for laser processing equipment, characterized in that, The laser processing equipment comprises a laser beam emitting device, a charge-coupled device (CCD), a built-in motor, and an auxiliary workpiece fixing device. The CCCD is coaxial with the auxiliary workpiece fixing device. The device includes: A laser position acquisition module is used to acquire the laser position coordinates of the auxiliary fixed workpiece; The mapping transformation relationship calculation module calculates the mapping transformation relationship between the axial plane and the CCD image plane based on the laser position coordinates; The nozzle pixel coordinate recognition module identifies the center pixel coordinates of the nozzle of the auxiliary fixed workpiece using image recognition technology; The axial distance position calculation module calculates the axial distance position from the nozzle pixel coordinates to the axial plane coordinates based on the mapping transformation relationship; The concentric calibration module performs a concentric calibration operation on the auxiliary fixed workpiece based on the axial distance position.

9. A computer device, comprising a memory and a processor, characterized in that, The memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, it implements the steps of the calibration method for the laser processing equipment as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the calibration method for the laser processing equipment as described in any one of claims 1 to 7.

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