A method, device and equipment for optimizing the knife axis vector of a high energy beam ruled surface

Abstract

The present invention discloses a method, device and equipment for optimizing the tool axis vector of a high-energy beam ruled surface, comprising: determining an initial tool axis vector according to a generatrix of a ruled surface to be processed or a preset cutting direction; judging whether the initial tool axis vector generates a processing path offset during the processing according to the initial tool axis vector and a workpiece model and executing the processing; in the case where the initial tool axis vector generates a processing path offset, calling a prediction mathematical model to predict the longitudinal and lateral processing errors that will be caused when processing is performed in the direction of the initial tool axis vector during the processing; calculating a reversely compensated tool axis offset based on the prediction mathematical model and preset process parameters, optimizing the offset initial tool axis vector according to the reversely compensated offset to effectively compensate for the error caused during the processing, obtaining an optimal tool axis vector, reducing the cutting error caused by ruled surface processing that changes dynamically with the change of cutting point parameters, and improving processing efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical control machining, and in particular to a method, device and equipment for optimizing a tool axis vector on a high-energy beam ruled surface. Background Art

[0002] CNC technology is one of the important indicators to measure the level of a country's machinery manufacturing industry, and it is also an important indicator of the technical level of a machinery manufacturing enterprise. The rapid development of CNC technology has brought fundamental changes to the traditional mechanical design and manufacturing methods. In particular, the widespread use of modern multi-axis CNC machine tools, with the help of computer-aided programming tools, has greatly shortened the manufacturing cycle of products and improved the competitiveness of enterprises. According to the processing tools, straight surface processing can be divided into rigid tool processing and soft tool processing. For example, water jet cutting, laser cutting, plasma arc cutting, and electric spark wire cutting are all "soft knife" straight surface processing, that is, soft tool straight surface processing; milling cutters are rigid tools.

[0003] In the current three-dimensional CAM (computer-aided manufacturing) software, the programming of the above-mentioned "soft knife" ruled surface machining is to sort the machining surfaces and offset the tool compensation in the three-dimensional graphics of the workpiece, and then cut the upper and lower curves of the machining surface into a series of straight line segments (rough interpolation), and write the spatial angle of the machining vector of the end point of the straight line segment, together with the coordinates of the end point and the running speed of the machining vector into a line of program code (such as G code, G code is an instruction in the numerical control program. Generally referred to as G instruction, the code of the entire program is interpolated and calculated in the lower computer (motion controller) of the CNC (Computer numerical control) numerical control system to form the motion command required for each motion axis.

[0004] However, there are still some problems in the application of current 3D CAM software in ruled surface processing: Unlike relatively rigid tools such as milling cutters, "soft knife" ruled surface processing is prone to errors when process variables are not considered during the process, such as the jet bending backward during cutting. The curvature of the jet during the cutting process depends on the workpiece parameters, cutting speed and jet parameters, and the width of the slit also varies with the thickness direction, such as "taper" error. If these process variables are not taken into account, it is very difficult to accurately process parts using only this flexible tool, and errors are easily generated during the processing.

[0005] The application number is 201710543378X, and the patent name is a method, device and equipment for generating a straight surface processing path. It records: when the mathematical model includes the mathematical model of the upper edge curve, the mathematical model of the lower edge curve, and the correlation function between the upper edge curve and the lower edge curve of the target straight surface, the step of determining the current spatial angle and the actual cutting thickness at each location of the processing path includes: interpolating and dividing the upper edge curve at each location of the processing path to obtain a first position point; finding the second position point corresponding to the lower edge curve according to the correlation function; and calculating the current spatial angle and the actual cutting thickness between the first position point and the second position point according to the current processing vector formed by the first position point and the second position point. ", the patent changes dynamically with the change of the cutting point parameters during the processing process, which is prone to cutting errors. Summary of the invention

[0006] The purpose of the present invention is to provide a method, device and equipment for optimizing the tool axis vector of a high-energy beam ruled surface. On the basis of the initial tool axis vector, a mathematical model is added to calculate the corresponding drag amount and taper, and reverse compensation is performed, thereby effectively compensating for the errors caused during the processing and obtaining the optimal tool axis vector.

[0007] The present invention provides a method for optimizing a cutter axis vector of a high energy beam ruled surface, comprising:

[0008] Determine the initial tool axis vector according to the generatrix of the ruled surface to be processed or the preset cutting direction;

[0009] Determine whether the initial tool axis vector generates a machining path offset during the machining process according to the initial tool axis vector and the workpiece model;

[0010] In the case where the initial tool axis vector deviates from the machining path, the prediction mathematical model is called to predict the machining longitudinal and lateral errors that will be caused when machining is performed in the direction of the initial tool axis vector during the machining process;

[0011] The offset required for reverse compensation is calculated based on the predictive mathematical model and preset process parameters, and the initial tool axis vector after the offset is optimized according to the reverse compensation offset to effectively compensate for the error caused by the machining process and obtain the optimal tool axis vector.

[0012] Preferably, the calculation based on the prediction mathematical model and the preset process parameters to obtain the offset required for reverse compensation, and the optimization of the offset initial tool axis vector according to the reverse compensation offset to effectively compensate for the error caused by the machining process further includes:

[0013] The first prediction mathematical model is called to calculate the drag amount of the cutting workpiece according to the target parameter information of the current position point, and then calculate the first angle that needs to be swung along the cutting feed direction to perform reverse compensation;

[0014] Acquire a first component of the initial tool axis vector along the cutting feed direction, and perform a first optimization according to the first angle to obtain a second component result of the optimized tool axis vector along the cutting feed direction;

[0015] The second prediction mathematical model is called to calculate the lateral taper generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the second angle that needs to be swung in the vertical direction along the cutting feed direction to perform reverse compensation;

[0016] Obtaining a third component of the initial tool axis vector in a direction perpendicular to the cutting feed direction, and performing a second optimization according to the second angle to obtain a fourth component result of the optimized tool axis vector perpendicular to the cutting feed direction;

[0017] According to the values ​​of the second component and the fourth component, the final optimized tool axis vector is synthesized.

[0018] Preferably, the prediction mathematical model includes but is not limited to one or more of a cutting speed model, a kerf taper model, a backlash model and a machine tool random error model established based on a processing mechanism.

[0019] Preferably, the method of calling the prediction mathematical model for prediction includes:

[0020] Determine the current cutting speed in the water jet cutting scenario;

[0021] The cutting speed of each point on the cutting path is calculated based on the mathematical model corresponding to the ruled surface and the preset processing parameters. ;

[0022] Among them, v is the cutting speed, Nm is the material processing parameter, Pw is the water pressure, is the water flow rate, is the abrasive flow rate, Cs is the proportional factor, q is the cutting quality grade, H is the material thickness, and D is the jet beam diameter.

[0023] Preferably, the calling of the first prediction mathematical model to calculate the drag amount generated by cutting the workpiece according to the target parameter information of the current position point includes:

[0024] Get the current cutting speed, and combine the material thickness, material type, and process parameter information at the current position to calculate the drag amount caused by water jet cutting as follows:

[0025] ;

[0026] Among them, J(h) is the towing amount, P is the water pressure, is the abrasive flow rate, h is the cutting depth, and v is the cutting speed.

[0027] Preferably, the calling of the second prediction mathematical model to calculate the lateral taper produced by cutting the workpiece according to the target parameter information of the current position point comprises:

[0028] Get the current cutting speed and material thickness, and calculate the current lateral taper angle:

[0029] ;

[0030] Among them, TA is the lateral taper produced by cutting, V is the cutting speed, and H is the thickness of the material being cut at the current cutting point.

[0031] Preferably, determining the initial tool axis vector according to the generatrix of the ruled surface to be processed or a preset cutting direction comprises:

[0032] If the upper edge curve and the lower edge curve of the straight-grained machining surface are simple geometric curves, the upper edge curve and the lower edge curve are perpendicular to the machining surface and offset outward by a tool radius;

[0033] If the upper edge curve and the lower edge curve of the ruled surface are not simple geometric curves, each ruled surface is discretized into a combination of straight generatrixes;

[0034] The straight generatrix group is offset outwards by a tool radius perpendicular to the machining surface, and the upper point of the offset straight generatrix group is fitted as the upper edge curve as the trajectory curve of the tool position point, and the lower point of the straight generatrix group is fitted as the lower edge curve as the trajectory curve of the tool axis point.

[0035] The present invention also provides a high-energy beam ruled surface cutter axis vector optimization device, comprising:

[0036] An initial module is used to determine the initial tool axis vector according to the generatrix of the ruled surface to be processed or the preset cutting direction;

[0037] A judgment module, used for judging whether the initial tool axis vector generates a machining path deviation during the machining process in which the machining path is generated according to the initial tool axis vector and the workpiece model and the initial tool axis vector is executed;

[0038] A calling module is used to call a prediction mathematical model to predict the longitudinal and lateral errors of machining caused by machining in the direction of the initial tool axis vector when the initial tool axis vector deviates from the machining path;

[0039] The optimization module is used to calculate the offset required for reverse compensation based on the predictive mathematical model and preset process parameters, and optimize the deviated initial tool axis vector according to the reverse compensation offset to effectively compensate for the error caused by the processing process and obtain the optimal tool axis vector.

[0040] Preferably, the optimization module further comprises:

[0041] The drag amount calculation submodule is used to call the first prediction mathematical model, calculate the drag amount generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the first angle that needs to be swung along the cutting feed direction for reverse compensation; obtain the first component of the initial tool axis vector along the cutting feed direction, and perform a first optimization according to the first angle to obtain the second component result of the optimized tool axis vector along the cutting feed direction;

[0042] The taper calculation submodule is used to call the second prediction mathematical model, calculate the lateral taper generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the second angle that needs to be swung in the vertical direction along the cutting feed direction for reverse compensation; obtain the third component of the initial tool axis vector in the vertical direction along the cutting feed direction, and perform a second optimization according to the second angle to obtain the fourth component result of the optimized tool axis vector perpendicular to the cutting feed direction;

[0043] The synthesis optimization module is used to synthesize the final optimized tool axis vector according to the values ​​of the second component and the fourth component.

[0044] The present invention also provides an electronic device, comprising:

[0045] A memory, the memory being used to store a processing program;

[0046] A processor, wherein when executing the processing program, the processor implements the high energy beam ruled surface tool axis vector optimization method as described in the embodiment of the present invention.

[0047] With respect to the prior art, the present invention has the following beneficial effects:

[0048] The present invention provides a method for optimizing the tool axis vector for a ruled surface. A predictive mathematical model is added to the initial tool axis vector, and the required longitudinal and lateral swing angles are calculated based on unique process parameters, so as to further obtain the final tool axis vector direction. This can compensate for the error caused by the original tool axis vector on the one hand, and can flexibly add the required angles on the other hand to obtain the optimal tool axis vector. And according to the drag amount and taper calculated by the predictive mathematical model, reverse compensation can be performed, so as to effectively compensate for the errors caused by the processing process and obtain the optimal tool axis vector. The method solves the technical problems of the deviation from the route in the subsequent processing process after the existing ruled surface tool axis vector is determined, and the lack of control, compensation and process variable consideration of the "soft knife" processing defects, reduces the cutting error caused by the ruled surface processing that changes dynamically with the changes in the cutting point parameters, and improves the ruled surface processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic flow chart of a method for optimizing a cutter axis vector of a high energy beam ruled surface according to an embodiment of the present invention;

[0050] Figure 2 This is an example diagram of a workpiece cut by a water jet in one embodiment of the present invention;

[0051] Figure 3 This is an example diagram of the backward bending, i.e., deviation, of a water jet when cutting glass in one embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0054] It should be noted that the concepts such as "once" and "second" mentioned in the present application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0055] It should be noted that the modifications of "one" and "plurality" mentioned in the disclosure of this application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0056] Embodiment 1

[0057] like Figure 1 As shown, the present invention provides a method for optimizing the cutter axis vector of a high-energy beam ruled surface, which uses a heat source of high-energy beam heat treatment, usually laser, electron beam, ion beam, electric spark, ultra-high frequency induction shock, solar energy and synchrotron radiation, to quickly heat, melt and cool the material surface, and the power density supplied to the material surface is at least ≥10^3W / cm^2. When the high-energy beam generator outputs an energy beam with a power density of at least 10^3W / cm^2, it acts on the metal surface in a directional manner, causing it to undergo physical, chemical or phase structure transformation, thereby achieving the purpose of metal surface modification. This heat treatment method is called high-energy beam heat treatment, and includes:

[0058] S1: Determine the initial tool axis vector according to the generatrix of the ruled surface to be processed or the preset cutting direction; In this embodiment, the implementation steps of determining the initial tool axis vector are as follows: obtain each target ruled surface in the three-dimensional image of the target workpiece to be processed; generate the mathematical model of each target ruled surface according to each target ruled surface; determine the current processing speed according to the mathematical model of the target ruled surface and the preset processing parameters; calculate the processing path data corresponding to the target ruled surface according to the current processing speed and the current position of the processing vector; or, calculate the process correction parameters according to the mathematical model of the target ruled surface and the preset processing parameters; correct the first position point and the current spatial angle of the upper edge curve according to the process correction parameters; calculate the processing path data corresponding to the target ruled surface according to the corrected first position point, the corrected current spatial angle and the current processing speed. Here, the mathematical model of the target ruled surface refers to the mathematical model of the upper edge curve, the mathematical model of the lower edge curve, and the correlation function between the upper edge curve and the lower edge curve of the target ruled surface; or the mathematical model of the upper edge curve of the target ruled surface, the processing vector direction limiting conditions, and also include processing quality indicators and workpiece thickness parameters. Among them, the upper edge curve of the target ruled surface refers to the curve formed by the intersection of the tool centerline during cutting and the feed surface during actual processing; the lower edge curve of the target ruled surface refers to the curve formed by the intersection of the tool centerline and the exit surface when no compensation is performed. After the three-dimensional image of the target workpiece is imported into the CAM software, the user can set the processing surface and the non-processing surface (including the feed surface and the exit surface). Uniformly discrete points are taken on the given surface, and the intersection of the surface tangent plane and the surface at each point is used to determine whether it is a ruled surface. If there is an intersection that does not contain a straight line segment passing through the point, the surface is an unruled surface; the intersection contains a single straight line segment passing through the point, and these straight line segments are taken out according to the initial conditions and other constraints for optimization and reordering; the intersection contains two or more finite straight line segments passing through the point, and a group of straight line segments are selected according to the initial conditions and other constraints and optimized and reordered; the intersection contains countless straight line segments passing through the point, and the surface is a plane, and a group of straight line segments are planned and sorted according to the initial conditions and other constraints. This set of straight line segments is offset outward by a tool offset by the average surface normal vector of each point on each straight line segment to obtain a new set of straight line segments, which are interpolated as a ruled surface. The ruled surface is defined as a machining vector surface, the intersection line with the predefined entry surface is the upper edge curve, the intersection line with the predefined exit surface is the lower edge curve, and the corresponding function of the two end points of the straight generatrix of the machining vector surface is the association function.

[0059] In this embodiment, determining the initial tool axis vector according to the generatrix of the ruled surface to be processed or the preset cutting direction includes:

[0060] CAM software Figure 2The workpiece shown generates a machining path for water jet cutting. Water jet can only machine ruled surfaces. If the upper and lower curves of the ruled surface are simple geometric curves, the upper and lower curves are perpendicular to the machining surface and offset outward by a tool radius; if the upper and lower curves of the ruled surface are not simple geometric curves, each ruled surface is discretized into a combination of straight generatrixes; the straight generatrix group is perpendicular to the machining surface and offset outward by a tool radius, and the upper point of the offset straight generatrix group is fitted as the upper curve as the trajectory curve of the tool position point, and the lower point of the straight generatrix group is fitted as the lower curve as the trajectory curve of the tool axis point. If the upper curve or the lower curve is a simple geometric curve, it is not necessary to determine its parameter equation by curve fitting, but its parameters can be directly determined by using the existing function expression as its mathematical model. Among them, the special case of the mathematical model of a simple geometric curve is an arc, and the parameter equation of the arc is x(u)=cos(u), y(u)=sin(u). If the upper edge curve or the lower edge curve is not a simple geometric curve, but a complex curve, curve fitting is required. Specifically, any available method can be used to fit the upper edge curve and the lower edge curve to obtain their mathematical models, which is not limited in the embodiments of the present application. A special case of the mathematical model of a complex curve is the non-uniform rational B-splines (NonUniformRationalB-Splines, NURBS) curve parameter equation. From the above analysis, it can be seen that in the embodiments of the present application, the mathematical model of the upper edge curve and the mathematical model of the lower edge curve can correspond to a straight line or an arc or a spline curve, or can correspond to one or a group of other complex functions, or can correspond to a database, etc. Moreover, in actual applications, the upper edge curve and the lower edge curve corresponding to the same straight surface can be the same or different, which is not limited in the embodiments of the present application.

[0061] CAM inserts the upper edge curve, i.e. the trajectory curve of the tool position point, and the lower edge curve, i.e. the trajectory curve of the tool axis point, at the starting point of the first machining surface and at the end point of the last machining surface. Because there is no corresponding machining surface for cutting in and cutting out, the straight generatrix of the point, i.e. the end points of the upper edge curve and the lower edge curve, are generally connected, and offset a set distance perpendicular to the machining surface to obtain a straight generatrix after offset. The upper edge curve is obtained by connecting the upper points of the straight generatrix before and after the offset, and the lower edge curve is obtained by connecting the lower points of the straight generatrix before and after the offset. The fast-forward line, i.e. the trajectory curve of the tool position point, is inserted between the starting point of the path and the starting point of the cutting-in line, between the end point of the cutting-out line and the starting point of the next cutting-in line (for multiple contour cutting), and between the end point of the last cutting-out line and the end point of the path. The fast-forward line also has no corresponding machining surface. The formation of the tool axis point trajectory mainly considers the safe avoidance of the workpiece and the fixture. Generally, the fast-forward line can be offset vertically downward by a set distance to obtain the tool axis point trajectory curve.

[0062] S2: Determine whether the initial tool axis vector generates a processing path offset during the processing according to the initial tool axis vector and the workpiece model; for example, when cutting materials with a water jet or laser, not only will a back drag be generated in the feed direction, but also a taper will be generated in the vertical direction of the feed direction. Moreover, the back drag and taper change dynamically with the change of the cutting point parameters, thereby causing cutting errors. If cutting is performed in the direction determined by the initial tool axis vector, errors are bound to exist. In order to overcome this error, the following predictive mathematical model is established and used to correct the processing path offset generated by the tool axis vector.

[0063] S3: when the initial tool axis vector is offset from the machining path, a prediction mathematical model is called to predict the machining longitudinal and lateral errors that will be caused when machining is performed in the direction of the initial tool axis vector during machining, thereby correcting the initial tool axis vector that causes the machining path offset;

[0064] S4: The offset required for reverse compensation is calculated based on the predicted mathematical model and the preset process parameters, and the initial tool axis vector after the offset is optimized according to the reverse compensation offset to effectively compensate for the error caused by the machining process and obtain the optimal tool axis vector.

[0065] In this embodiment, Figure 3 As shown, the tool axis vector is offset during the jet processing. By calling the prediction mathematical model to correct the initial tool axis vector, the offset can be compensated, so that the jet can cut the material better. As shown in the figure, the nozzle is assumed to be the initial tool axis vector. At present, the initial assumption is perpendicular to the workpiece, but it can also be not perpendicular to the workpiece. It is mainly determined according to the generatrix. As shown in the figure, the feed direction of the jet produces a back drag. The angle of the back head is calculated to obtain an angle that needs to be corrected with the vertical direction. This angle is reversely compensated to such an initial vector, and it is rotated in the opposite direction by a small angle. Finally, the curved cutting line of the jet can be pulled to be approximately perpendicular to the workpiece, so that the jet cutting line can cut out better results.

[0066] The core of this embodiment is to add the quantity calculated by the mathematical model on the basis of the initial tool axis vector, so as to effectively compensate for the error caused by the processing process and obtain the optimal tool axis vector. The specific implementation steps include:

[0067] Call the first prediction mathematical model, calculate the amount of drag caused by cutting the workpiece according to the target parameter information of the current position point, and then calculate the first angle that needs to be swung along the cutting feed direction for reverse compensation; the first prediction mathematical model is determined by domain knowledge. Taking the water jet as an example, the amount of drag caused by water jet cutting is calculated according to the material thickness, material type, process parameters, etc. at the current point, and then calculate the angle that needs to be swung longitudinally, where longitudinal refers to the cutting feed direction. Obtain the first component of the initial tool axis vector along the cutting feed direction, and perform the first optimization based on the first angle to obtain the second component result of the optimized tool axis vector along the cutting feed direction; it can be understood that the value of the optimized tool axis vector along the cutting feed component is obtained by using the component of the initial tool axis vector along the cutting feed direction + the longitudinal swing angle calculated by the first prediction mathematical model in the previous step.

[0068] The second prediction mathematical model is called to calculate the lateral taper generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the second angle that needs to be swung along the vertical direction of the cutting feed direction for reverse compensation; the second prediction mathematical model is determined by domain knowledge. Taking the water jet as an example, the lateral taper generated by the water jet cutting the workpiece is calculated according to the material thickness, material type, process parameters, etc. at the current point, and then the angle required for lateral swing is calculated, where the lateral refers to the vertical direction of the cutting feed direction. The third component of the initial tool axis vector along the vertical direction of the cutting feed direction is obtained, and the second optimization is performed according to the second angle to obtain the fourth component result of the optimized tool axis vector perpendicular to the cutting feed direction; it can be understood that the component of the initial tool axis vector along the vertical direction of the cutting feed direction + the side swing angle calculated by the previous mathematical model is used to obtain the value of the optimized tool axis vector perpendicular to the cutting feed component. According to the values ​​of the second component and the fourth component, the final optimized tool axis vector is synthesized. In this way, the required vertical swing and side swing angles are calculated according to the unique process parameters and the established prediction mathematical model, and the final tool axis vector direction is further obtained. On the one hand, this can compensate for the error caused by the original tool axis vector, and on the other hand, it can flexibly add the required angle to obtain the optimal tool axis vector.

[0069] In one embodiment, the prediction mathematical model includes but is not limited to one or more of a cutting speed model, a kerf taper model, a backlash model, and a machine tool random error model established based on a processing mechanism.

[0070] In one embodiment, the calling of the prediction mathematical model for prediction includes:

[0071] Determine the current cutting speed in the water jet cutting scenario;

[0072] The cutting speed of each point on the cutting path is calculated based on the mathematical model corresponding to the ruled surface and the preset processing parameters. ;

[0073] Among them, v is the cutting speed, Nm is the material processing parameter, Pw is the water pressure, is the water flow rate, is the abrasive flow rate, Cs is the proportional factor, q is the cutting quality level, H is the material thickness, and D is the jet beam diameter. In the embodiment of the present application, Pw, , The specific values ​​corresponding to the superscripts , D are not limited in the embodiments of the present application, and the specific values ​​in the above formula are only examples.

[0074] In one embodiment, the calling of the first prediction mathematical model to calculate the drag amount generated by cutting the workpiece according to the target parameter information of the current position point includes:

[0075] Get the current cutting speed, and combine the material thickness, material type, and process parameter information at the current position to calculate the drag amount caused by water jet cutting as follows:

[0076] ;

[0077] Among them, J(h) is the towing amount, P is the water pressure, is the abrasive flow rate, h is the cutting depth, and v is the cutting speed. In the embodiment of the present application, the fixed values ​​of each parameter can be predetermined according to demand or experiment, etc., and the embodiment of the present application is not limited to this, and the specific values ​​in the above formula are only examples.

[0078] In one embodiment, the calling of the second prediction mathematical model to calculate the lateral taper generated by cutting the workpiece according to the target parameter information of the current position point includes:

[0079] Get the current cutting speed and material thickness, and calculate the current lateral taper angle:

[0080] ,

[0081] Wherein, TA is the taper angle, v is the cutting speed, and H is the material thickness (mm). In the embodiment of the present application, the fixed values ​​of each parameter can be predetermined according to requirements or experiments, etc., and the embodiment of the present application is not limited to this, and the specific values ​​in the above formula are only examples.

[0082] Embodiment 2

[0083] Based on the same concept, the present invention provides a high energy beam ruled surface cutter axis vector optimization device, comprising:

[0084] An initial module is used to determine the initial tool axis vector according to the generatrix of the ruled surface to be processed or the preset cutting direction;

[0085] A judgment module, used for judging whether the initial tool axis vector generates a machining path deviation during the machining process in which the machining path is generated according to the initial tool axis vector and the workpiece model and the initial tool axis vector is executed;

[0086] A calling module is used to call a prediction mathematical model to predict the longitudinal and lateral errors of machining caused by machining in the direction of the initial tool axis vector when the initial tool axis vector deviates from the machining path;

[0087] The optimization module is used to calculate the offset required for reverse compensation based on the predictive mathematical model and preset process parameters, and optimize the initial tool axis vector after the offset according to the reverse compensation offset to effectively compensate for the error caused by the processing process and obtain the optimal tool axis vector.

[0088] Specifically, the optimization module further includes:

[0089] The drag amount calculation submodule is used to call the first prediction mathematical model, calculate the drag amount generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the first angle that needs to be swung along the cutting feed direction for reverse compensation; obtain the first component of the initial tool axis vector along the cutting feed direction, and perform a first optimization according to the first angle to obtain the second component result of the optimized tool axis vector along the cutting feed direction;

[0090] The taper calculation submodule is used to call the second prediction mathematical model, calculate the lateral taper generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the second angle that needs to be swung in the vertical direction along the cutting feed direction for reverse compensation; obtain the third component of the initial tool axis vector in the vertical direction along the cutting feed direction, and perform a second optimization according to the second angle to obtain the fourth component result of the optimized tool axis vector perpendicular to the cutting feed direction;

[0091] The synthesis optimization submodule is used to synthesize the final optimized tool axis vector according to the values ​​of the second component and the fourth component.

[0092] The implementation principles of the above-mentioned initial module, judgment module, calling module, optimization module, drag amount calculation submodule, taper calculation submodule and synthesis optimization submodule have been described in the above-mentioned embodiments, so they will not be repeated here.

[0093] Embodiment 3

[0094] Based on the same concept, in some embodiments of the present application, an electronic device is also provided. The electronic device includes a memory and a processor, wherein the memory is used to store a processing program, and the processor executes the processing program according to instructions. When the processor executes the processing program, the high-energy beam ruled surface tool axis vector optimization method in the above-mentioned embodiment is implemented.

[0095] In some embodiments of the present application, a readable storage medium is further provided, which may be a non-volatile readable storage medium or a volatile readable storage medium. The readable storage medium stores instructions, and when the instructions are executed on a computer, an electronic device including the readable storage medium executes the above-mentioned high-energy beam ruled surface tool axis vector optimization method.

[0096] It is understandable that, for the above-mentioned ruled surface cutter axis vector optimization method, if it is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0097] Computer readable storage media may include data signals propagated in baseband or as part of a carrier wave, wherein readable program codes are carried. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program codes contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0098] The program code involved in executing the technical solution disclosed in the present application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and also conventional procedural programming languages ​​such as C language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on the remote computing device, or completely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the knife axis vector of a high energy beam ruled surface, characterized in that: include: Determine the initial tool axis vector according to the generatrix of the ruled surface to be processed or the preset cutting direction; Determine whether the initial tool axis vector generates a machining path offset during the machining process according to the initial tool axis vector and the workpiece model; In the case where the initial tool axis vector is offset from the machining path, the prediction mathematical model is called to predict the machining longitudinal and lateral errors that will be caused when machining is performed in the direction of the initial tool axis vector during the machining process; The offset required for reverse compensation is calculated based on the prediction mathematical model and the preset process parameters, and the initial tool axis vector after the offset is optimized according to the reverse compensation offset to effectively compensate for the error caused by the machining process, and the optimal tool axis vector is obtained, including: The first prediction mathematical model is called to calculate the drag amount of the cutting workpiece according to the target parameter information of the current position point, and then calculate the first angle that needs to be swung along the cutting feed direction to perform reverse compensation; Acquire a first component of the initial tool axis vector along the cutting feed direction, and perform a first optimization according to the first angle to obtain a second component result of the optimized tool axis vector along the cutting feed direction; The second prediction mathematical model is called to calculate the lateral taper generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the second angle that needs to be swung in the vertical direction along the cutting feed direction to perform reverse compensation; Obtaining a third component of the initial tool axis vector in a direction perpendicular to the cutting feed direction, and performing a second optimization according to the second angle to obtain a fourth component result of the optimized tool axis vector perpendicular to the cutting feed direction; According to the values ​​of the second component and the fourth component, the final optimized tool axis vector is synthesized.

2. The high energy beam ruled surface tool axis vector optimization method according to claim 1, characterized in that: The prediction mathematical model includes but is not limited to one or more of a cutting speed model, a slit taper model, a backlash model and a machine tool random error model established based on a processing mechanism.

3. The method for optimizing the cutter axis vector of a high energy beam ruled surface according to claim 1, characterized in that: The calling prediction mathematical model for prediction includes: Determine the current cutting speed in the water jet cutting scenario; The cutting speed of each point on the cutting path is calculated based on the mathematical model corresponding to the ruled surface and the preset processing parameters. ; Where, v is the cutting speed, Nm is the material machinability parameter, Pw is the water pressure, is the water flow rate, is the abrasive flow rate, Cs is the proportional factor, q is the cutting quality grade, H is the material thickness, and D is the jet beam diameter.

4. The method for optimizing the cutter axis vector of a high energy beam ruled surface according to claim 1, characterized in that: The calling of the first prediction mathematical model to calculate the drag amount generated by cutting the workpiece according to the target parameter information of the current position point includes: Get the current cutting speed, and combine the material thickness, material type, and process parameter information at the current position to calculate the drag amount caused by water jet cutting as follows: ； Among them, J(h) is the towing amount, P is the water pressure, is the abrasive flow rate, h is the cutting depth, and v is the cutting speed.

5. The method for optimizing the cutter axis vector of a high energy beam ruled surface according to claim 1, characterized in that: The calling of the second prediction mathematical model to calculate the lateral taper produced by cutting the workpiece according to the target parameter information of the current position point includes: Get the current cutting speed and material thickness, and calculate the current lateral taper angle: ； Among them, TA is the lateral taper produced by cutting, V is the cutting speed, and H is the thickness of the material being cut at the current cutting point.

6. The method for optimizing the cutter axis vector of a high energy beam ruled surface according to claim 1, characterized in that: Determining the initial tool axis vector according to the generatrix of the ruled surface to be processed or the preset cutting direction includes: If the upper edge curve and the lower edge curve of the straight-grained machining surface are simple geometric curves, the upper edge curve and the lower edge curve are perpendicular to the machining surface and offset outward by a tool radius; If the upper edge curve and the lower edge curve of the ruled surface are not simple geometric curves, each ruled surface is discretized into a combination of straight generatrixes; The straight generatrix group is offset outwards by a tool radius perpendicular to the machining surface, and the upper point of the offset straight generatrix group is fitted as the upper edge curve as the trajectory curve of the tool position point, and the lower point of the straight generatrix group is fitted as the lower edge curve as the trajectory curve of the tool axis point.

7. A high energy beam ruled surface knife axis vector optimization device, characterized in that: include: An initial module is used to determine the initial tool axis vector according to the generatrix of the ruled surface to be processed or the preset cutting direction; A judgment module, used for judging whether the initial tool axis vector generates a machining path deviation during the machining process in which the machining path is generated according to the initial tool axis vector and the workpiece model and the initial tool axis vector is executed; A calling module is used to call a prediction mathematical model to predict the longitudinal and lateral errors of machining caused by machining in the direction of the initial tool axis vector when the initial tool axis vector deviates from the machining path; The optimization module is used to calculate the offset required for reverse compensation based on the prediction mathematical model and the preset process parameters, and optimize the initial tool axis vector after the offset according to the reverse compensation offset to effectively compensate for the error caused by the processing process, and obtain the optimal tool axis vector, including: The drag amount calculation submodule is used to call the first prediction mathematical model, calculate the drag amount generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the first angle that needs to be swung along the cutting feed direction for reverse compensation; obtain the first component of the initial tool axis vector along the cutting feed direction, and perform a first optimization according to the first angle to obtain the second component result of the optimized tool axis vector along the cutting feed direction; The taper calculation submodule is used to call the second prediction mathematical model, calculate the lateral taper generated by cutting the workpiece according to the target parameter information of the current position point, and then calculate the second angle that needs to be swung in the vertical direction along the cutting feed direction for reverse compensation; obtain the third component of the initial tool axis vector in the vertical direction along the cutting feed direction, and perform a second optimization according to the second angle to obtain the fourth component result of the optimized tool axis vector perpendicular to the cutting feed direction; The synthesis optimization module is used to synthesize the final optimized tool axis vector according to the values ​​of the second component and the fourth component.

8. An electronic device, characterized in that: include: A memory, the memory being used to store a processing program; A processor, wherein when executing the processing program, the processor implements the high-energy beam ruled surface tool axis vector optimization method as described in any one of claims 1 to 6.

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