A laser cutting machine control method and control system

Abstract

The present invention relates to the technical field of laser cutting, and provides a laser cutting machine control method and a control system. The method includes the following steps: obtaining the parameters of the workpiece to be cut, and obtaining the cutting path area according to the parameters of the workpiece to be cut; obtaining an image of the cutting path area, and obtaining multi-dimensional defect information of the cutting path area according to the image of the cutting path area; obtaining an optimal cutting path according to the multi-dimensional defect information of the cutting path area; and controlling the operation of the laser cutting machine according to the optimal cutting path to perform laser cutting on the workpiece to be cut. The present invention can minimize the defect flaws on the surface of the workpiece after cutting as much as possible on the basis that the cut workpiece meets the required shape and size, thereby optimizing the surface appearance quality of the workpiece after cutting. It solves the problem that when the existing laser cutting machine plans the cutting path for the workpiece, it often only considers the shape and size requirements and ignores the defects existing on the surface of the workpiece, which easily causes poor surface quality of the workpiece after cutting.

Description

Technical Field

[0001] The present invention relates to the technical field of laser cutting, and more specifically, to a laser cutting machine control method and a control system Background Art

[0002] Laser cutting is a technology that uses a highly focused high-power density laser beam to irradiate a workpiece, causing the irradiated material to quickly melt, vaporize, ablate, or reach the ignition point. At the same time, a high-speed gas flow coaxial with the beam is used to blow away the molten material, thereby realizing the cutting of the workpiece. A laser cutting machine system generally consists of a laser generator, a beam transmission component, a workbench, a microcomputer numerical control cabinet, a cooler, and a computer (hardware and software), etc. Through laser cutting technology, workpieces can be cut into the required shapes and sizes, and the cutting objects include metal profiles, plates, plastics, quartz, ceramics, and so on

[0003] For some workpieces, such as ceramics, wood plates, and aluminum profiles, etc., their cutting shapes and sizes are not unique. When the existing laser cutting machines plan the cutting paths for the above workpieces, they often only consider their shape and size requirements, ignoring the defects existing on the surface of the workpieces, which easily causes problems with the surface of the workpieces after cutting. Therefore, it is necessary to develop a laser cutting machine control method to plan the cutting path according to the surface defects of the workpiece to be cut, so that the surface appearance quality of the workpiece after cutting is optimized on the basis of meeting the required shape and size Summary of the Invention

[0004] Based on this, in order to solve the problem that when the existing laser cutting machines plan the cutting paths for workpieces, they often only consider the shape and size requirements, ignoring the defects existing on the surface of the workpieces, which easily causes problems with the surface of the workpieces after cutting, the present invention provides a laser cutting machine control method and a control system, which can obtain the cutting path area according to the workpiece parameters to be cut, and obtain the multi-dimensional defect information of the cutting path area according to the image of the cutting path area, and then obtain the optimal cutting path, so that the surface appearance quality of the workpiece after cutting is optimized as much as possible on the basis of meeting the required shape and size. The specific technical solutions are as follows

[0005] A laser cutting machine control method, which includes the following steps

[0006] Obtain the workpiece parameters to be cut, and obtain the cutting path area according to the workpiece parameters to be cut

[0007] Obtain the image of the cutting path area, and obtain the multi-dimensional defect information of the cutting path area according to the image of the cutting path area

[0008] Obtain the optimal cutting path according to the multi-dimensional defect information of the cutting path area

[0009] Control the movement of the laser cutting machine according to the optimal cutting path, and perform laser cutting on the workpiece to be cut.

[0010] By obtaining the cutting path area and multi-dimensional defect information of the cutting path area, and obtaining the optimal cutting path according to the multi-dimensional defect information of the cutting path area, the laser cutting machine control method can minimize the defect flaws on the surface of the workpiece after cutting while making the cut workpiece meet the required shape and size, thereby optimizing the surface appearance quality of the workpiece after cutting. It solves the problem that when the existing laser cutting machine plans the cutting path for the workpiece, it often only considers the shape and size requirements and ignores the defects existing on the surface of the workpiece, which is likely to cause poor surface quality of the workpiece after cutting.

[0011] Preferably, the specific method for obtaining the cutting path area according to the parameters of the workpiece to be cut includes the following steps:

[0012] Obtain the initial cutting path and the allowable deviation range according to the parameters of the workpiece to be cut;

[0013] Obtain the cutting path area according to the initial cutting path and the allowable deviation range.

[0014] Preferably, the specific method for obtaining the optimal cutting path according to the multi-dimensional defect information of the cutting path area includes the following steps:

[0015] Construct a multi-dimensional defect index function

[0016] Obtain the optimal cutting path according to the multi-dimensional defect index function to minimize DefectIndex×γ1+ΔD×γ2;

[0017] Where, n represents the number of dimensions of the multi-dimensional defect information, λ i represents the defect characteristic value of the i-th dimension, α i represents the defect characteristic adjustment coefficient of the i-th dimension, C i represents the defect characteristic correction value of the i-th dimension, ΔD represents the deviation distance between the optimal cutting path and the initial cutting path, and γ1 and γ2 respectively represent the multi-dimensional defect index adjustment coefficient and the deviation distance adjustment coefficient.

[0018] Preferably, the laser cutting machine control method further includes performing visual calibration on the camera for obtaining the image of the cutting path area, and the visual calibration method includes the following steps:

[0019] Obtain the number p of standard calibration images, the calibration plate accuracy ca, the preset standard calibration accuracy sca, the standard cutting error scd, the preset cutting error pcd, the reprojection error threshold Ree', and the reprojection error estimate Ree;

[0020] Calculate the total number of calibration images according to the number of standard calibration images, the accuracy of the calibration plate, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, and the estimated reprojection error value;

[0021] According to the total number of calibration images, collect multiple actual calibration images through the camera, and calibrate the camera according to the multiple actual calibration images to obtain the estimated values of internal and external parameters;

[0022] Perform multiple iterative optimizations on the estimated values of internal and external parameters through an iterative optimization method until the reprojection error value is minimized;

[0023] Obtain the optimal estimated values of internal and external parameters, and calibrate the camera according to the optimal estimated values of internal and external parameters.

[0024] Preferably, according to the formula

[0025] Calculate the total number of calibration images;

[0026] Among them, β1, β2, and β3 respectively represent the first calibration coefficient, the second calibration coefficient, and the third calibration coefficient, e represents the natural constant, CF represents the image calibration correction factor, and [] represents the rounding function.

[0027] Preferably, the specific method for performing multiple iterative optimizations on the estimated values of internal and external parameters through an iterative optimization method until the reprojection error value is minimized includes the following steps:

[0028] Perform multiple iterative optimizations on the estimated values of internal and external parameters through an iterative optimization method until the maximum number of iterations is reached or the reprojection error value is less than the preset threshold;

[0029] Among them, the maximum number of iterations m is a preset constant, represents the ceiling function.

[0030] A laser cutting machine control system for implementing the laser cutting machine control method as described above, includes:

[0031] A path area acquisition module, configured to acquire the parameters of the workpiece to be cut, and acquire the cutting path area according to the parameters of the workpiece to be cut;

[0032] A multi-dimensional information acquisition module, configured to acquire an image of the cutting path area, and acquire multi-dimensional defect information of the cutting path area according to the image of the cutting path area;

[0033] An optimal path acquisition module, configured to acquire the optimal cutting path according to the multi-dimensional defect information of the cutting path area;

[0034] A control module, configured to control the actions of a laser cutting machine according to the optimal cutting path, and perform laser cutting on the workpiece to be cut.

[0035] Preferably, the path area acquisition module includes:

[0036] A first path acquisition unit, configured to acquire an initial cutting path and an allowable deviation range according to the workpiece parameters to be cut;

[0037] A second path acquisition unit, configured to acquire a cutting path area according to the initial cutting path and the allowable deviation range.

[0038] Preferably, the optimal path acquisition module includes:

[0039] A function construction unit, configured to construct a multi-dimensional defect index function;

[0040] A path calculation unit, configured to acquire an optimal cutting path according to the multi-dimensional defect index function, so that DefectIndex×γ1+ΔD×γ2 is minimized;

[0041] Wherein, n represents the number of dimensions of the multi-dimensional defect information, λ i represents the defect feature value of the i-th dimension, α i represents the defect feature adjustment coefficient of the i-th dimension, C i represents the defect feature correction value of the i-th dimension, ΔD represents the deviation distance between the optimal cutting path and the initial cutting path, and γ1 and γ2 respectively represent the multi-dimensional defect index adjustment coefficient and the deviation distance adjustment coefficient.

[0042] Preferably, the laser cutting machine control system further includes:

[0043] A parameter acquisition module, configured to acquire the number of standard calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, the reprojection error threshold, and the reprojection error estimate value;

[0044] An image total number calculation module, configured to calculate the total number of calibration images according to the number of standard calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, and the reprojection error estimate value;

[0045] An internal and external parameter calculation module, configured to collect multiple actual calibration images through the camera according to the total number of calibration images, and calibrate the camera according to the multiple actual calibration images to obtain internal and external parameter estimation values;

[0046] An iterative optimization module, configured to perform multiple iterative optimizations on the internal and external parameter estimation values through an iterative optimization method until the reprojection error value is minimized;

[0047] The calibration module is used to obtain the optimal internal and external parameter estimation values and calibrate the camera according to the optimal internal and external parameter estimation values. Description of the Drawings

[0048] The present invention can be further understood from the following description in conjunction with the drawings. The components in the drawings are not necessarily drawn to scale, but the emphasis is placed on showing the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0049] Figure 1 It is a schematic diagram of the overall flow of a laser cutting machine control method in an embodiment of the present invention;

[0050] Figure 2 It is a schematic diagram of the flow of a specific method for obtaining a cutting path area in an embodiment of the present invention;

[0051] Figure 3 It is a schematic diagram of the process of visually calibrating a camera in an embodiment of the present invention;

[0052] Figure 4 It is a schematic diagram of the overall structure of a laser cutting machine control method in an embodiment of the present invention. Detailed Embodiments

[0053] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with its embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not limit the protection scope of the present invention.

[0054] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there may also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration and do not represent the only implementation manner.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used herein in the description of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0056] In the present invention, the so-called "first" and "second" do not represent specific quantities and orders, but are only used for name distinction.

[0057] For some workpieces, such as ceramic tiles, aluminum profiles, aluminum-plastic panels, and some decorative panels, if there are defects such as cracks, spots, protrusions, pits, and dirt on their surfaces, it will reduce their surface appearance quality. With the development of laser cutting machine technology, laser cutting is increasingly widely used in the cutting of the above workpieces. For many factories, the size and shape requirements of workpieces from different customers often vary to a certain extent. In this case, when using laser cutting to process workpieces, it is possible to consider the different size and shape requirements of the workpieces to be cut and adjust and plan the cutting path as reasonably as possible. On the basis of making the cut workpieces meet the required size and shape, the surface appearance quality of the cut workpieces is optimized to the greatest extent.

[0058] In existing laser cutting machines, when planning the cutting path for workpieces, they often only consider their size and shape requirements and ignore the defects existing on the surfaces of the workpieces, which easily causes problems with the surface of the cut workpieces. Even if some laser cutting machines will first identify the defects existing on the surface of the workpiece through visual recognition technology before cutting the workpiece, most of them only screen and remove the workpieces to be cut with defects, and will not comprehensively consider the different sizes and shapes required for workpiece cutting and the acceptable degree of defects to optimize the cutting path, so as to obtain workpieces that meet both the required size and shape requirements and the acceptable degree of defects requirements.

[0059] To solve the technical problems existing in the above-mentioned prior art, as Figure 1 shown, the present invention provides a control method for a laser cutting machine, which includes the following steps:

[0060] S1, obtaining the parameters of the workpiece to be cut, and obtaining the cutting path area according to the parameters of the workpiece to be cut.

[0061] The parameters of the workpiece to be cut include, but are not limited to, the type of the workpiece to be cut, the size and shape of the cut, and the error range.

[0062] The laser cutting machine at least includes a laser generator, a beam transmission component, a workbench, a microcomputer numerical control cabinet, and a central controller. It controls the laser generator to output a laser beam to cut the workpiece into the required shape and size. The cutting objects include, but are not limited to, metal profiles, plates, plastics, quartz, and ceramics. Since the specific structure of the above laser cutting machine belongs to the conventional technical means in the art, it will not be described in detail here.

[0063] Preferably, as Figure 2 shown, the specific method for obtaining the cutting path area according to the parameters of the workpiece to be cut includes the following steps:

[0064] S10. Obtain the initial cutting path and the allowable deviation range according to the parameters of the workpiece to be cut. For the initial cutting path, first, obtain the image and the edge contour of the workpiece to be cut. Combine the image, the edge contour of the workpiece to be cut, and the specific cutting shape and size to obtain at least one initial cutting path. Cut the workpiece to be cut along the initial cutting path, and a workpiece that meets the requirements of the specific cutting shape and size can be obtained. The allowable deviation range can be determined based on a preset cutting error. For example, if the preset cutting error is expressed as ±ε, then the allowable deviation range is ±ε, or it can be set by technicians according to the actual situation and experience.

[0065] S11. Obtain the cutting path area according to the initial cutting path and the allowable deviation range.

[0066] Specifically, if the initial cutting path is represented by a curve or a straight-line function y = f(x), and the allowable deviation range is ±ε, then the cutting path area can be represented as f(x) ± ε, which can be understood as the area enclosed by two cutting paths obtained by translating y = f(x) by ±ε.

[0067] S2. Obtain an image of the cutting path area, and obtain multi-dimensional defect information of the cutting path area according to the image of the cutting path area. The multi-dimensional defect information includes, but is not limited to, cracks, burrs, pits, dirt, protrusions, and deformations, which are specifically related to the type of the workpiece to be cut. Since it is a conventional technical means in the art to identify the multi-dimensional defect information of the cutting path area based on the visual image recognition technology, it will not be elaborated here.

[0068] S3. Obtain the optimal cutting path according to the multi-dimensional defect information of the cutting path area.

[0069] Preferably, the specific method for obtaining the optimal cutting path according to the multi-dimensional defect information of the cutting path area includes the following steps:

[0070] S30. Construct a multi-dimensional defect index function

[0071] S31. Obtain the optimal cutting path according to the multi-dimensional defect index function to minimize DefectIndex × γ1 + ΔD × γ2;

[0072] where, n represents the number of dimensions of the multi-dimensional defect information, λ i represents the defect characteristic value of the i-th dimension, α i represents the defect characteristic adjustment coefficient of the i-th dimension, C iThe defect feature correction value for the i-th dimension is denoted as, ΔD represents the deviation distance between the optimal cutting path and the initial cutting path, γ1 and γ2 respectively represent the multi-dimensional defect index adjustment coefficient and the deviation distance adjustment coefficient, and DefectIndex represents the multi-dimensional defect index.

[0073] For the defect feature correction value of the i-th dimension, it can be set by the technician. Preferably, the defect feature correction value of the i-th dimension is calculated based on the actual reprojection error after camera calibration. The method for obtaining the defect feature value is as follows: Based on image recognition technology, the defect contour line in the cutting path area is obtained, and the defect area is calculated according to the defect contour line, and the defect area is used as the defect feature value. The deviation distance is obtained by calculating the average value of the distances between multiple sampling points on the optimal cutting path and the initial cutting path, or by constructing the XY-axis coordinates and placing the optimal cutting path and the initial cutting path in the XY-axis coordinate system, and calculating the difference in the integral area between the optimal cutting path and the initial cutting path, and using the difference in the integral area as the deviation distance.

[0074] Taking MIN DefectIndex×γ1 + ΔD×γ2 as the condition for obtaining the optimal cutting path, the optimal cutting path is obtained to minimize DefectIndex×γ1 + ΔD×γ2. The optimal cutting path can make the surface of the workpiece after cutting have as few defect flaws as possible on the basis of meeting the required shape and size, thereby optimizing the surface appearance quality of the workpiece after cutting. Due to the setting of the multi-dimensional defect index adjustment coefficient and the deviation distance adjustment coefficient, through the formula DefectIndex×γ1 + ΔD×γ2, the deviation distance between the shape and size of the workpiece after cutting and the shape and size corresponding to the initial cutting path and the weight of the final surface defect flaws of the workpiece can also be adjusted according to the actual situation, comprehensively considering the different shape and size requirements for workpiece cutting and the acceptable flaw and defect degree to optimize the cutting path, so as to obtain a workpiece that meets both the required shape and size requirements and the acceptable flaw and defect degree requirements, improving flexibility and wide applicability.

[0075] Preferably, according to the multi-dimensional defect index function, the optimal cutting path is obtained. While minimizing DefectIndex×γ1 + ΔD×γ2, the multi-dimensional defect index DefectIndex meets the preset acceptable flaw and defect degree requirements. The acceptable flaw and defect degree requirements can be preset by the technician in the form of a multi-dimensional defect index. In this way, the method can comprehensively consider the different shape and size requirements for workpiece cutting and the acceptable flaw and defect degree to optimize the cutting path, so as to obtain a workpiece that meets both the required shape and size requirements and the acceptable flaw and defect degree requirements.

[0076] S4. According to the optimal cutting path, control the movement of the laser cutting machine to perform laser cutting on the workpiece to be cut along the optimal cutting path.

[0077] Preferably, after performing laser cutting on the workpiece to be cut, the quality of the workpiece can also be classified according to the magnitude of DefectIndex×γ1 + ΔD×γ2, so as to perform different subsequent treatments on the cut workpiece. It combines the magnitude of the multi-dimensional defect index of the workpiece after cutting and the actual deviation of the shape and size corresponding to the initial cutting path, providing a new idea for classifying the quality of the cut workpiece.

[0078] The laser cutting machine control method obtains the cutting path area and the multi-dimensional defect information of the cutting path area, and obtains the optimal cutting path according to the multi-dimensional defect information of the cutting path area. It can minimize the defect flaws on the surface of the workpiece after cutting while making the cut workpiece meet the required shape and size, thereby optimizing the surface appearance quality of the cut workpiece. It solves the problem that when the existing laser cutting machine plans the cutting path for the workpiece, it often only considers the shape and size requirements and ignores the defects existing on the surface of the workpiece, which easily causes poor surface quality of the cut workpiece. In addition, the laser cutting machine control method can optimize the cutting path by comprehensively considering the different shape and size requirements and the acceptable defect degree required for workpiece cutting, and can obtain workpieces that simultaneously meet the required shape and size requirements and the acceptable defect degree requirements.

[0079] Camera calibration, as the basis of visual measurement, its accuracy will affect the accuracy of the shape and size of the workpiece after cutting along the optimal cutting path and the defect characteristic values collected based on the visual image technology, which directly affects the overall performance of the system.

[0080] Existing laser control systems generally perform camera calibration on the system through a calibration board. In camera calibration, the accuracy of feature point detection is one of the important factors affecting the reprojection error. If the feature point detection is inaccurate, it will lead to a large reprojection error, thus affecting the accuracy of the calibration result. The estimation accuracy of the camera internal parameters and distortion coefficients has a direct impact on the reprojection error. The number and quality of calibration images also affect the reprojection error. The more calibration images, the wider the covered field of view, and usually more accurate camera parameter estimation can be obtained. Therefore, the accuracy of feature point detection can be improved by increasing the number of calibration images, thereby reducing the reprojection error and improving the camera calibration accuracy. However, increasing the number of calibration images means more image acquisition and processing time and computing resources.

[0081] To balance the requirements of the visual measurement accuracy of the system and the image acquisition, processing time and computing resources requirements, and improve the overall performance of the system, as a preferred technical solution, such as Figure 3As shown, the laser cutting machine control method further includes visual calibration of the camera for acquiring the image of the cutting path area, and the visual calibration method includes the following steps:

[0082] S5. Obtain the number p of standard calibration images, the calibration plate accuracy ca, the preset standard calibration accuracy sca, the standard cutting error scd, the preset cutting error pcd, the reprojection error threshold Ree', and the estimated reprojection error Ree.

[0083] The number of standard calibration images, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, the reprojection error threshold, and the estimated reprojection error can all be set by technicians. The calibration plate accuracy is obtained according to the accuracy parameters of the actual calibration plate used in camera calibration.

[0084] S6. Calculate the total number of calibration images according to the number of standard calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, and the estimated reprojection error.

[0085] Preferably, calculate the total number of calibration images according to the formula

[0086] where β1, β2, and β3 respectively represent the first calibration coefficient, the second calibration coefficient, and the third calibration coefficient, which can be set and adjusted by technicians, e represents the natural constant, CF represents the image calibration correction factor, [] represents the rounding function, and CalibrationPictureTotal represents the total number of calibration images.

[0087] For the image calibration correction factor, first obtain the difference between the real-time parameter characteristics of multiple external environmental factors affecting the reprojection error, such as system temperature, vibration value, temperature and humidity value, and light brightness, etc., and the preset standard characteristic values, then calculate the ratio value between the difference and the preset standard characteristic values, and finally calculate the weighted average value of the ratio values to obtain it.

[0088] By setting the image calibration correction factor and taking into account the influence of external factors on the reprojection error, the accuracy of camera calibration can be improved, which is more in line with the actual situation.

[0089] S7. According to the total number of calibration images, collect multiple actual calibration images through the camera, and calibrate the camera according to the multiple actual calibration images to obtain the estimated values of internal and external parameters.

[0090] Since calibrating the camera through calibration images to obtain the estimated values of internal and external parameters belongs to the conventional technical means in this field, it will not be elaborated here.

[0091] S8. The internal and external parameter estimation values are iteratively optimized multiple times through an iterative optimization method until the reprojection error value is minimized.

[0092] Here, the iterative optimization method includes, but is not limited to, the least squares method and the gradient descent method.

[0093] Preferably, the specific method of iteratively optimizing the internal and external parameter estimation values multiple times through an iterative optimization method until the reprojection error value is minimized includes the following steps: The internal and external parameter estimation values are iteratively optimized multiple times through an iterative optimization method until the maximum number of iterations is reached or the reprojection error value is less than a preset threshold.

[0094] Among them, the maximum number of iterations m is a preset constant, denotes the ceiling function. The maximum number of iterations is associated with the total number of calibration images and is proportional to the total number of calibration images. By setting a reasonable preset constant m, an appropriate maximum number of iterations can be obtained, avoiding the risk of overfitting and waste of computing resources caused by too large a number of iterations, as well as the problem of the risk of underfitting caused by too small a number of iterations.

[0095] S9. Obtain the optimal internal and external parameter estimation values, and calibrate the camera according to the optimal internal and external parameter estimation values. Specifically, the optimal internal and external parameter estimation values can be obtained according to the minimized reprojection error value after iteratively optimizing the internal and external parameter estimation values multiple times.

[0096] Calculate the total number of calibration images through the standard number of calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, and the pre-estimated reprojection error. According to the total number of calibration images, collect multiple actual calibration images through the camera, and then calibrate the camera according to the multiple actual calibration images to obtain the internal and external parameter estimation values, and obtain the optimal internal and external parameter estimation values to calibrate the camera. It comprehensively measures multiple different factors, and can appropriately balance and meet the requirements of image acquisition and processing time and computing resources on the basis of meeting the visual measurement accuracy requirements of the system, improving the overall comprehensive performance of the system.

[0097] As a preferred technical solution, the defect feature correction value of the i-th dimension is calculated according to the actual reprojection error after camera calibration, that is, calculated according to the minimized reprojection error value after iteratively optimizing the internal and external parameter estimation values multiple times. Specifically, the defect feature correction value of the i-th dimension is equal to the product of the minimized reprojection error value and the preset defect feature correction weight coefficient of the i-th dimension.

[0098] Since the actual reprojection error is related to the camera calibration accuracy, calculating the defect feature correction value of the i-th dimension based on the actual reprojection error after camera calibration can indirectly improve the accuracy of the multi-dimensional defect index, thereby making the optimal cutting path more accurate.

[0099] The present invention also provides a laser cutting machine control system for implementing the above-mentioned laser cutting machine control method, as Figure 4 shown, which includes a path area acquisition module, a multi-dimensional information acquisition module, an optimal path acquisition module, and a control module.

[0100] The path area acquisition module is used to acquire the parameters of the workpiece to be cut, and obtain the cutting path area according to the parameters of the workpiece to be cut; preferably, the path area acquisition module includes a first path acquisition unit and a second path acquisition unit. The first path acquisition unit is used to obtain the initial cutting path and the allowable deviation range according to the parameters of the workpiece to be cut, and the second path acquisition unit is used to obtain the cutting path area according to the initial cutting path and the allowable deviation range.

[0101] The allowable deviation range can be determined based on a preset cutting error. For example, if the preset cutting error is expressed as ±ε, the allowable deviation range is ±ε, or it can be set by technicians according to the actual situation and experience. If the initial cutting path is expressed as a curve or a straight-line function y = f(x), and the allowable deviation range is ±ε, then the cutting path area can be expressed as f(x) ± ε, which can be understood as the area enclosed by two cutting paths obtained by translating y = f(x) by ±ε.

[0102] The multi-dimensional information acquisition module is used to acquire the image of the cutting path area, and obtain the multi-dimensional defect information of the cutting path area according to the image of the cutting path area; the multi-dimensional defect information includes but is not limited to cracks, burrs, pits, dirt, protrusions, and deformations, which are specifically related to the type of the workpiece to be cut.

[0103] The optimal path acquisition module is used to obtain the optimal cutting path according to the multi-dimensional defect information of the cutting path area; the control module is used to control the action of the laser cutting machine according to the optimal cutting path, and perform laser cutting on the workpiece to be cut.

[0104] Preferably, the optimal path acquisition module includes a function construction unit and a path calculation unit. The function construction unit is used to construct a multi-dimensional defect index function, and the multi-dimensional defect index function is expressed as The path calculation unit is used to obtain the optimal cutting path according to the multi-dimensional defect index function, so as to minimize DefectIndex × γ1 + ΔD × γ2.

[0105] Among them, n represents the number of dimensions of the multi-dimensional defect information, λ irepresents the defect eigenvalue of the i-th dimension, α i represents the defect feature adjustment coefficient of the i-th dimension, C i represents the defect feature correction value of the i-th dimension. ΔD represents the deviation distance between the optimal cutting path and the initial cutting path, and γ1, γ2 represent the multi-dimensional defect index adjustment coefficient and the deviation distance adjustment coefficient respectively.

[0106] Taking DefectIndex×γ1 + ΔD×γ2 as the condition for obtaining the optimal cutting path, the optimal cutting path is obtained to minimize DefectIndex×γ1 + ΔD×γ2. The optimal cutting path can make the cut workpiece, on the basis of meeting the required shape and size, minimize the defect flaws on the surface of the cut workpiece as much as possible, thereby optimizing the surface appearance quality of the cut workpiece. Due to the setting of the multi-dimensional defect index adjustment coefficient and the deviation distance adjustment coefficient, through the formula DefectIndex×γ1 + ΔD×γ2, the weight of the deviation distance between the shape and size of the cut workpiece and the shape and size corresponding to the initial cutting path and the defect flaws on the surface of the finally cut workpiece can also be adjusted according to the actual situation, improving the flexibility and wide applicability.

[0107] The laser cutting machine control system can obtain the optimal cutting path according to the multi-dimensional defect information of the cutting path area by acquiring the cutting path area and the multi-dimensional defect information of the cutting path area. It can make the cut workpiece, on the basis of meeting the required shape and size, minimize the defect flaws on the surface of the cut workpiece as much as possible, thereby optimizing the surface appearance quality of the cut workpiece. It solves the problem that when the existing laser cutting machine plans the cutting path for the workpiece, it often only considers the shape and size requirements and ignores the defects existing on the surface of the workpiece, which is likely to cause poor surface quality of the cut workpiece.

[0108] As a preferred technical solution, the laser cutting machine control system further includes a parameter acquisition module, an image total number calculation module, an internal and external parameter calculation module, an iterative optimization module, and a calibration module.

[0109] The parameter acquisition module is used to acquire the number of standard calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, the reprojection error threshold, and the reprojection error pre-estimation value; the image total number calculation module is used to calculate the total number of calibration images according to the number of standard calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, and the reprojection error pre-estimation value;

[0110] Specifically, the total number of calibration images Among them, β1, β2, and β3 respectively represent the first calibration coefficient, the second calibration coefficient, and the third calibration coefficient, which can be set and adjusted by technicians. e represents the natural constant, CF represents the image calibration correction factor, and [] represents the rounding function.

[0111] By setting the image calibration correction factor and taking into account the influence of external factors on the reprojection error, the accuracy of camera calibration can be improved, making it more in line with the actual situation.

[0112] The internal and external parameter calculation module is used to collect multiple actual calibration images through the camera according to the total number of calibration images, and calibrate the camera based on the multiple actual calibration images to obtain the estimated values of the internal and external parameters; the iterative optimization module is used to perform multiple iterative optimizations on the estimated values of the internal and external parameters through the iterative optimization method until the reprojection error value is minimized.

[0113] Preferably, the estimated values of the internal and external parameters are iteratively optimized multiple times through the iterative optimization method until the maximum number of iterations is reached or the reprojection error value is less than the preset threshold.

[0114] Among them, the maximum number of iterations m is a preset constant, represents the ceiling function.

[0115] The calibration module is used to obtain the optimal estimated values of the internal and external parameters and calibrate the camera according to the optimal estimated values of the internal and external parameters.

[0116] Calculate the total number of calibration images through the standard calibration image quantity, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, and the pre-estimated reprojection error value. According to the total number of calibration images, collect multiple actual calibration images through the camera, and then calibrate the camera based on the multiple actual calibration images to obtain the estimated values of the internal and external parameters, and obtain the optimal estimated values of the internal and external parameters to calibrate the camera. It comprehensively measures multiple different factors, can appropriately balance and meet the requirements of image acquisition and processing time and computing resources on the basis of meeting the visual measurement accuracy requirements of the system, and improve the overall comprehensive performance of the system.

[0117] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0118] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the appended claims.

Claims

1. A method for controlling a laser cutting machine, characterized in that, The laser cutting machine control method includes the following steps: Obtain the parameters of the workpiece to be cut, and obtain the cutting path area according to the parameters of the workpiece to be cut; Obtain the image of the cutting path area, and obtain the multi-dimensional defect information of the cutting path area according to the image of the cutting path area; Obtain the optimal cutting path according to the multi-dimensional defect information of the cutting path area; According to the optimal cutting path, control the action of the laser cutting machine to perform laser cutting on the workpiece to be cut; The specific method for obtaining the cutting path area according to the parameters of the workpiece to be cut includes the following steps: Obtain the initial cutting path and the allowable deviation range according to the parameters of the workpiece to be cut; Obtain the cutting path area according to the initial cutting path and the allowable deviation range; The specific method for obtaining the optimal cutting path according to the multi-dimensional defect information of the cutting path area includes the following steps: Construct a multi-dimensional defect index function Obtain the optimal cutting path according to the multi-dimensional defect index function to minimize DefectIndex×γ1+ΔD×γ2; where n represents the number of dimensions of the multi-dimensional defect information, λ i represents the defect eigenvalue of the i-th dimension, αi represents the defect feature adjustment coefficient of the i-th dimension, Ci represents the defect feature correction value of the i-th dimension, ΔD represents the deviation distance between the optimal cutting path and the initial cutting path, and γ1 and γ2 respectively represent the multi-dimensional defect index adjustment coefficient and the deviation distance adjustment coefficient.

2. The laser cutting machine control method according to claim 1, characterized in that The laser cutting machine control method further includes performing visual calibration on the camera for obtaining the image of the cutting path area. The visual calibration method includes the following steps: Obtain the number p of standard calibration images, the calibration plate accuracy ca, the preset standard calibration accuracy sca, the standard cutting error scd, the preset cutting error pcd, the reprojection error threshold Ree', and the reprojection error estimated value Ree; Calculate the total number of calibration images according to the number of standard calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, and the reprojection error estimated value; According to the total number of calibration images, collect multiple actual calibration images through the camera, and calibrate the camera according to the multiple actual calibration images to obtain the internal and external parameter estimated values; Perform multiple iterative optimizations on the internal and external parameter estimated values through the iterative optimization method until the reprojection error value is minimized; Obtain the optimal internal and external parameter estimated values, and calibrate the camera according to the optimal internal and external parameter estimated values.

3. The control method of a laser cutting machine according to claim 2, characterized in that According to the formula calculate the total number of calibration images CalibrationPictureTotal; Among them, β1, β2, and β3 respectively represent the first calibration coefficient, the second calibration coefficient, and the third calibration coefficient, e represents the natural constant, CF represents the image calibration correction factor, and [] represents the rounding function.

4. The control method of a laser cutting machine according to claim 3, characterized in that The specific method for performing multiple iterative optimizations on the internal and external parameter estimated values through the iterative optimization method until the reprojection error value is minimized includes the following steps: Perform multiple iterative optimizations on the internal and external parameter estimated values through the iterative optimization method until the maximum number of iterations is reached or the reprojection error value is less than the preset threshold; Among them, the maximum number of iterations m is a preset constant, represents the ceiling function.

5. A laser cutting machine control system for implementing the laser cutting machine control method according to any one of claims 1-4, characterized in that, The laser cutting machine control system includes: A path area acquisition module for obtaining the parameters of the workpiece to be cut and obtaining the cutting path area according to the parameters of the workpiece to be cut; A multi-dimensional information acquisition module for obtaining the image of the cutting path area and obtaining the multi-dimensional defect information of the cutting path area according to the image of the cutting path area; An optimal path acquisition module for obtaining the optimal cutting path according to the multi-dimensional defect information of the cutting path area; A control module for controlling the action of the laser cutting machine according to the optimal cutting path to perform laser cutting on the workpiece to be cut; The path area acquisition module includes: A first path acquisition unit, configured to obtain an initial cutting path and an allowable deviation range according to the workpiece parameters to be cut; A second path acquisition unit, configured to obtain a cutting path area according to the initial cutting path and the allowable deviation range; The optimal path acquisition module includes: A function construction unit, configured to construct a multi-dimensional defect index function; A path calculation unit, configured to obtain an optimal cutting path according to the multi-dimensional defect index function, so that DefectIndex×γ1 + ΔD×γ2 is minimized; where n represents the number of dimensions of the multi-dimensional defect information, λ i represents the defect eigenvalue of the i-th dimension, α i represents the defect feature adjustment coefficient of the i-th dimension, C i represents the defect feature correction value of the i-th dimension, ΔD represents the deviation distance between the optimal cutting path and the initial cutting path, and γ1 and γ2 respectively represent the multi-dimensional defect index adjustment coefficient and the deviation distance adjustment coefficient.

6. The control system of a laser cutting machine according to claim 5, characterized in that, The laser cutting machine control system further includes: A parameter acquisition module, configured to acquire the number of standard calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, the reprojection error threshold, and the reprojection error estimated value; An image total number calculation module, configured to calculate the total number of calibration images according to the number of standard calibration images, the calibration plate accuracy, the preset standard calibration accuracy, the standard cutting error, the preset cutting error, and the reprojection error estimated value; An internal and external parameter calculation module, configured to collect multiple actual calibration images by a camera according to the total number of calibration images, and calibrate the camera according to the multiple actual calibration images to obtain internal and external parameter estimated values; An iterative optimization module, configured to perform multiple iterative optimizations on the internal and external parameter estimated values through an iterative optimization method until the reprojection error value is minimized; A calibration module, configured to obtain optimal internal and external parameter estimated values, and calibrate the camera according to the optimal internal and external parameter estimated values.

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