Cutting path planning method, system and medium for wire-cut electric discharge machine

Abstract

The present invention relates to the field of wire-cut electric discharge machines, and specifically to a method, system and medium for planning cutting paths for wire-cut electric discharge machines. The planning method comprises the following steps: acquiring CAD model data of a workpiece, including the geometric shape, size and material information of the workpiece; preprocessing the CAD model data to extract geometric features of the workpiece, wherein the geometric features include boundary curves, feature points and surface information; determining the cutting start and end points according to the geometric shape, setting the cutting layer thickness, and generating the preliminary cutting path by scanning the workpiece model layer by layer. The present invention reduces the complexity and error rate of manual programming and improves the efficiency of path planning by providing a method for acquiring the CAD model data of the workpiece, preprocessing the model data, and generating a preliminary cutting path in combination with an intelligent algorithm.

Description

Technical Field

[0001] The invention relates to the field of electric spark wire cutting machine tools, and in particular to a cutting path planning method, system and medium for electric spark wire cutting machine tools. Background Art

[0002] Wire Electrical Discharge Machining (WEDM) is a processing method for machining complex shapes and high-precision parts. Existing EDM wire path planning methods mainly rely on experience and manual programming. Due to the diversity and complexity of workpiece geometry, the planning of the cutting path requires a lot of calculations and experience. Manual programming is prone to errors and inefficient. In addition, during the EDM wire cutting process, electrode loss and cutting gap have a significant impact on the machining accuracy. Existing path planning methods lack effective optimization methods, and it is usually difficult to achieve the optimal path, which makes it difficult to compensate and optimize in real time, resulting in difficulty in ensuring machining accuracy. Summary of the invention

[0003] The present invention provides a cutting path planning method, system and medium for an electric spark wire cutting machine tool to solve the problems of low efficiency and difficulty in optimization and compensation of the existing electric spark wire path planning manual programming.

[0004] The technical solution of the present invention to solve the above technical problems is as follows:

[0005] On the one hand, a cutting path planning method for a wire-cut electric discharge machine is provided, the planning method comprising the following steps:

[0006] Obtain the CAD model data of the workpiece, including the workpiece's geometry, size, and material information;

[0007] Preprocessing the CAD model data to extract geometric features of the workpiece, wherein the geometric features include boundary curves, feature points and surface information;

[0008] Determine the cutting start point and end point according to the geometric shape, set the cutting layer thickness, and generate the preliminary cutting path by scanning the workpiece model layer by layer;

[0009] Performing selection, crossover and mutation operations on the preliminary cutting path to obtain an optimized cutting path;

[0010] The optimized cutting path is compensated for electrode loss and cutting gap, and the kinematic and dynamic characteristics of the machine tool are taken into consideration to obtain a final cutting path.

[0011] On the other hand, a cutting path planning system for a wire-cut electric discharge machine is provided, the planning system comprising:

[0012] Workpiece CAD model data acquisition module, used to receive and store the workpiece's geometric shape, size and material information;

[0013] CAD model data preprocessing module, used to extract the geometric features of the workpiece, and perform meshing and geometric error repair;

[0014] A preliminary cutting path generation module, used for generating a preliminary cutting path based on the geometric features and process parameters of the workpiece;

[0015] A cutting path optimization module, used for performing selection, crossover and mutation operations on the preliminary cutting path to obtain an optimized cutting path;

[0016] The final cutting path generation module is used to generate the final cutting path considering electrode loss, cutting gap compensation and the kinematic and dynamic characteristics of the machine tool;

[0017] Instruction code generation module, used to convert the final cutting path into machine tool instruction G code and M code;

[0018] The simulation verification module is used to simulate and verify the cutting path, including cutting time estimation, thermal deformation analysis and collision detection;

[0019] A user interface module, used for displaying cutting path planning results and accepting optimization parameters input by users;

[0020] Cloud computing platform module, used to store and process path planning data.

[0021] On the other hand, a computer-readable storage medium is provided, which stores a program. When the program is run on a computer, the cutting path planning method for a wire electric discharge machine tool as described above is executed.

[0022] The beneficial effects of the present invention are:

[0023] The present invention provides a method for obtaining CAD model data of a workpiece, preprocessing the model data, and combining an intelligent algorithm to generate a preliminary cutting path, thereby reducing the complexity and error rate of manual programming and improving the efficiency of path planning. By optimizing the preliminary cutting path, the optimal cutting path is generated by considering factors such as the length, complexity, electrode loss, and cutting gap compensation of the cutting path, thereby improving the cutting efficiency and processing quality. By considering electrode loss and cutting gap compensation when generating the final cutting path, the accuracy of the cutting path is effectively improved, thereby ensuring the processing accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of a planning method in one embodiment of the present invention;

[0025] Figure 2A flowchart of a preliminary cutting path operation in one embodiment of the present invention;

[0026] Figure 3 This is a flow chart of preprocessing CAD model data in one embodiment of the present invention;

[0027] Figure 4 A flowchart of layer-by-layer scanning in one embodiment of the present invention;

[0028] Figure 5 A flow chart of radial scanning and spiral scanning in one embodiment of the present invention;

[0029] Figure 6 A flow chart of electrode loss and cutting gap compensation in one embodiment of the present invention;

[0030] Figure 7 A flow chart of cutting path time optimization in one embodiment of the present invention;

[0031] Figure 8 A flowchart of removing redundant data and repairing geometric errors in one embodiment of the present invention;

[0032] Fig. 9 It is a block diagram of the structure of the cutting path planning system in one embodiment of the present invention;

[0033] In the accompanying drawings, the components represented by the reference numerals are listed as follows:

[0034] 100. Workpiece CAD model data acquisition module; 200. CAD model data preprocessing module; 300. Preliminary cutting path generation module; 400. Cutting path optimization module; 500. Final cutting path generation module; 600. Instruction code generation module; 700. Simulation verification module; 800. User interface module; 900. Cloud computing platform module. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0036] The present invention provides the following preferred embodiments: Example

[0037] In order to solve the problems of low path generation efficiency, poor path optimization effect, insufficient compensation for electrode loss and cutting gap in the path planning process of existing electric spark wire cutting machines, this embodiment further optimizes the various steps of the electric spark wire cutting path planning method to ensure the efficiency and accuracy of the path generation and optimization process.

[0038] like Figure 1 As shown, the planning method includes the following steps:

[0039] S100, obtaining CAD model data of the workpiece, including geometric shape, size and material information of the workpiece;

[0040] S200, preprocessing the CAD model data to extract geometric features of the workpiece, where the geometric features include boundary curves, feature points, and surface information;

[0041] S300, determining the cutting start and end points according to the geometric shape, setting the cutting layer thickness, and generating a preliminary cutting path by scanning the workpiece model layer by layer;

[0042] S400, performing selection, crossover and mutation operations on the preliminary cutting path to obtain an optimized cutting path;

[0043] S500, performing electrode loss and cutting gap compensation on the optimized cutting path, and taking into account the kinematic and dynamic characteristics of the machine tool, to obtain a final cutting path.

[0044] Specifically, this embodiment adopts a CAD model data acquisition and preprocessing method, and the acquired CAD model data includes the geometric shape, size and material information of the workpiece. The geometric shape information includes boundary curves, feature points and surface information, which are acquired through advanced 3D scanning technology and high-precision measuring equipment to ensure the accuracy and integrity of the data. In the preprocessing, the boundary curves, feature points and surface information of the workpiece are extracted from the CAD model through an automated geometric feature extraction algorithm. These geometric features provide the necessary basic data for subsequent path generation and optimization.

[0045] Furthermore, the cutting start and end points are determined based on the geometric shape information. In order to improve the accuracy and efficiency of path planning, an optimized start and end point setting algorithm is selected. This algorithm comprehensively considers the machinability of the start and end points and the continuity of the path according to the geometric shape and processing requirements of the workpiece to minimize the length of the non-processing path and reduce the processing time. When setting the cutting layer thickness, the material characteristics of the workpiece and the cutting process requirements are combined, and the optimal balance between fine processing and rough processing is achieved by dynamically adjusting the cutting layer thickness.

[0046] Furthermore, in the process of generating the preliminary cutting path, the present embodiment adopts an algorithm for scanning the workpiece model layer by layer. Through the layer-by-layer scanning technology, the preliminary cutting path is generated layer by layer from bottom to top according to the set cutting layer thickness. This method can not only ensure the uniformity and continuity of the path, but also adapt to the geometric shapes of workpieces of different complexities. During the scanning process, the density and direction of the scanning path are dynamically adjusted in combination with the geometric feature information of the workpiece to ensure the accuracy and efficiency of the path generation.

[0047] Furthermore, after the preliminary cutting paths are generated, the present embodiment performs selection, crossover and mutation operations on these paths to obtain optimized cutting paths. Specifically, a path optimization method based on a genetic algorithm is adopted. First, the fitness of the preliminary cutting paths is evaluated, and the evaluation criteria include path length, processing time, electrode loss and cutting quality. According to the fitness evaluation results, paths with high fitness are selected for crossover operations to generate new path combinations; then, the newly generated paths are mutated to increase the diversity and optimization possibilities of the paths through small-scale random adjustments. After multiple generations of iteration and optimization, a set of optimized cutting paths is finally obtained.

[0048] Furthermore, this embodiment compensates for electrode loss and cutting gap in the optimized cutting path. It should be understood that electrode loss and cutting gap are key factors affecting machining accuracy during wire EDM. To this end, this embodiment adopts a dynamic compensation algorithm to adjust the compensation amount of the cutting path in real time according to the real-time status of the cutting path and the wear of the electrode to ensure the accuracy and consistency of the cutting path. Specifically, by monitoring the service life and wear rate of the electrode, the offset of the cutting path is dynamically adjusted to ensure that each cutting is performed in the optimal state.

[0049] In addition, this embodiment also takes into account the kinematic and dynamic characteristics of the machine tool when generating the final cutting path. It should be understood that the kinematic characteristics of the machine tool directly affect the execution effect of the cutting path. In order to ensure the executable nature and processing quality of the path, this embodiment comprehensively considers factors such as the maximum acceleration, maximum speed, range of motion and dynamic characteristics of the machine tool during the path optimization process. By establishing the kinematic and dynamic models of the machine tool, the optimized cutting path is verified and adjusted to ensure the executable nature and stability of the path in actual processing.

[0050] The benefits of this embodiment are that the accuracy and efficiency of geometric feature extraction are improved by optimizing the acquisition and preprocessing of CAD model data; the accuracy and continuity of path generation are improved by advanced start and end point setting algorithms and layer-by-layer scanning to generate preliminary cutting paths; the optimization of paths is achieved by selecting, crossing and mutating paths through genetic algorithms; the accuracy and consistency of cutting paths are ensured by compensating for electrode loss and cutting gap; and the executableness and processing quality of paths are guaranteed by considering the kinematic and dynamic characteristics of machine tools. Through this embodiment, the EDM wire cutting path planning method achieves high efficiency and accuracy, greatly improving processing efficiency and quality. Example

[0051] In order to solve the problems of low efficiency in path selection and optimization and unstable optimization effect in the process of wire EDM path optimization, this embodiment further refines the selection, intersection and mutation operations of the preliminary cutting path to ensure the efficiency and stability of the optimized cutting path.

[0052] like Figure 2 As shown, the selection, crossover and mutation operations on the preliminary cutting path include the following steps:

[0053] S401, initializing a population and generating a plurality of initial cutting paths, wherein the initial cutting paths are generated based on geometric features of the workpiece and cutting process parameters;

[0054] S402, evaluating the fitness of each initial cutting path, the fitness evaluation is based on the objective function, and the objective function expression is:

[0055] ,

[0056] Among them, F is the objective function value, Rs is the surface roughness of the workpiece, Vc is the cutting speed, Ec is the cutting energy consumption, Tc is the cutting time, and α, β, γ and δ are weight coefficients respectively;

[0057] S403, selecting a preliminary cutting path with high fitness according to the fitness value to perform crossover and mutation operations to generate an optimized cutting path, wherein the crossover operation includes exchanging path segments, and the mutation operation includes random adjustment of path nodes;

[0058] S404, evaluating the fitness of the optimized cutting path, and updating the population according to the fitness value until the optimization condition is met, where the optimization condition includes that the fitness value reaches a preset threshold or the number of iterations reaches a preset upper limit.

[0059] Specifically, in the process of initializing the population, this embodiment generates multiple initial cutting paths based on the geometric features of the workpiece and the cutting process parameters. Specifically, each path in the initial population is based on the geometric features of the workpiece, such as boundary curves, feature points and surface information, and cutting process parameters, such as cutting speed, cutting layer thickness and electrode loss. When generating the initial path, the geometric features and process parameters are combined to ensure that the initial path has a good fitness basis.

[0060] Furthermore, in this embodiment, fitness evaluation is performed on each initial cutting path. Fitness evaluation is based on the objective function. Through fitness evaluation, the comprehensive performance of each cutting path under different evaluation criteria can be quantified, thereby providing a basis for subsequent path selection and optimization.

[0061] Furthermore, in the path selection stage, this embodiment selects a preliminary cutting path with high fitness according to the fitness value to perform crossover and mutation operations. The crossover operation includes the exchange of path segments, by exchanging some path segments in two paths, generating a new path combination to increase path diversity and optimization possibilities. The mutation operation includes the random adjustment of path nodes, by randomly adjusting the position or order of some nodes in the path, introducing new path variations, and further improving the optimization space of the path. It should be understood that the purpose of these operations is to introduce diversity in the population and avoid the optimization process from falling into a local optimal solution.

[0062] Furthermore, this embodiment performs fitness evaluation on the generated optimized cutting path and updates the population according to the fitness value. In each generation of iteration, the paths with high fitness are screened out through fitness evaluation, and crossover and mutation operations are performed to continuously optimize the path population. The optimization process continues until the optimization condition is met, that is, the fitness value reaches a preset threshold or the number of iterations reaches a preset upper limit. It can be understood that the setting of the preset threshold and the upper limit of the number of iterations is based on actual processing requirements and computing resources to balance the optimization effect and computing cost.

[0063] Furthermore, in order to ensure the efficiency and stability of the optimization process, this embodiment also introduces a variety of auxiliary algorithms and technologies in the path optimization process. For example, by dynamically adjusting the weight coefficients α, β, γ and δ, it can adapt to the changes in different processing stages and processing requirements to ensure the flexibility and adaptability of the objective function. At the same time, by introducing parallel computing technology, the computational efficiency of path optimization can be greatly improved and the optimization time can be shortened.

[0064] The benefits of this embodiment are that by generating the initial cutting path based on the workpiece geometric features and process parameters, the fitness basis of the initial path is improved; the comprehensive performance of the path is quantified through fitness evaluation based on the objective function; the diversity and optimization space of the path are increased through path selection, crossover and mutation operations; and the efficiency and stability of path optimization are further improved by dynamically adjusting the weight coefficient and introducing parallel computing technology. Example

[0065] In order to solve the problems of uneven meshing and insufficient accuracy when wire EDM processes complex workpiece geometric features, this embodiment further optimizes and refines the steps of CAD model data preprocessing to ensure the rationality and accuracy of meshing.

[0066] like Figure 3 As shown, preprocessing the CAD model data includes the following steps:

[0067] S201, analyzing the geometric features of the workpiece, determining the complex area and the simple area, using smaller grid units in the complex area and larger grid units in the simple area, and dynamically adjusting the size of the grid units according to the complexity of the geometric features of the workpiece;

[0068] S202, refining the complex area multiple times until the mesh density meets the preset standard;

[0069] S203, smoothing the refined grid to eliminate mutations between grid cells;

[0070] S204, calculating the geometric properties of each grid cell, including area, side length and angle, to ensure uniformity and accuracy of grid division;

[0071] S205, performing quality assessment on the mesh division results, and locally refining or re-dividing the mesh units with poor quality until the mesh quality meets the preset standard.

[0072] Specifically, during the preprocessing process, this embodiment first conducts an in-depth analysis of the geometric features of the workpiece and automatically identifies the complex and simple areas in the workpiece model. Complex areas usually have large curvature changes and rich details, while simple areas are relatively smooth and have fewer changes. In order to adapt to the geometric complexity of different areas, this embodiment adopts adaptive meshing technology. In complex areas, smaller grid units are used to capture detailed features; in simple areas, larger grid units are used to improve computing efficiency. The size of the grid unit is dynamically adjusted according to the complexity of the workpiece's geometric features to ensure that the grid can adapt to changes in the workpiece's morphology.

[0073] Furthermore, the present embodiment refines the identified complex areas multiple times. The refinement process uses an iterative algorithm to gradually reduce the size of the grid cells until the grid density meets the preset standard. The preset standard is based on the workpiece machining accuracy requirements and machine tool characteristics to ensure that the refined grid can achieve the required accuracy for machining without sacrificing computing resources.

[0074] Furthermore, in the refinement process, the present embodiment also performs smoothing on the mesh at the same time. The purpose of smoothing is to eliminate mutations between mesh units, such as sharp angles, distortions, etc., to ensure the geometric coherence and smoothness of the mesh. Through smoothing, errors or instabilities caused by mesh quality problems in subsequent cutting path planning can be avoided.

[0075] This embodiment calculates the geometric properties of each grid cell, including area, side length and angle. These geometric properties are crucial for evaluating the quality and uniformity of the grid cells. By accurately calculating these properties, the uniformity of the grid division can be ensured, thereby improving the planning accuracy of the cutting path.

[0076] Furthermore, in order to ensure the quality of the meshing results, this embodiment also performs a systematic quality assessment on the meshing results. The quality assessment uses a series of quality indicators, such as the regularity, aspect ratio, angle offset, etc. of the mesh unit. For the poor mesh units found in the quality assessment, this embodiment uses a local refinement or re-division method for optimization.

[0077] The benefit of this embodiment is that the mesh quality of a specific area can be improved without affecting the overall mesh structure until the preset quality standard is met. Through adaptive meshing, the cutting path planning problem of complex workpieces can be handled more effectively. Example

[0078] In order to solve the problems of inaccurate path generation, discontinuous cutting process and poor path optimization effect in the EDM wire cutting path planning process, this embodiment further refines the steps of generating a preliminary cutting path by scanning the workpiece model layer by layer to ensure the accuracy and continuity of path generation.

[0079] like Figure 4 As shown, the step of generating a preliminary cutting path by scanning the workpiece model layer by layer includes a scanning algorithm based on the workpiece contour, and the scanning algorithm generates a path by scanning the workpiece model layer by layer. The specific steps include:

[0080] S301, determining the cutting start point and end point of the workpiece, and setting the cutting layer thickness according to the geometric features of the workpiece;

[0081] S302, starting from the cutting starting point, scanning the workpiece model layer by layer to generate a cutting path for each layer, the path including straight line segments, arc segments and spline curve segments;

[0082] S303, smoothing the cutting path of each layer to eliminate sharp corners and mutations in the path to ensure the continuity and smoothness of the cutting path;

[0083] S304: Merge the cutting paths of each layer to generate a preliminary cutting path, and make a preliminary evaluation and adjustment on the preliminary cutting path to ensure the feasibility and effectiveness of the path.

[0084] Specifically, in the initial stage of path generation, this embodiment first determines the starting point and end point of the workpiece cutting. The starting point and end point are determined based on the geometric features of the workpiece, and the starting position and end position of the cutting are set by analyzing the outer contour and internal features of the workpiece. The setting of the cutting layer thickness combines the material, size and cutting process requirements of the workpiece to achieve the best cutting effect and processing efficiency.

[0085] Furthermore, this embodiment adopts a scanning algorithm based on the workpiece contour, scanning the workpiece model layer by layer from the cutting starting point to generate a cutting path for each layer. During the scanning process, the cutting path of each layer may include straight line segments, arc segments, and spline curve segments according to the geometric features of the workpiece. Straight line segments are used to process the straight parts of the workpiece, arc segments are suitable for circular or curved edges, and spline curve segments are used to process complex curved surfaces to ensure that the cutting path can accurately fit the actual shape of the workpiece.

[0086] Furthermore, after generating the cutting path of each layer, the present embodiment performs a smoothing process on the path. The purpose of the smoothing process is to eliminate sharp corners and mutations in the path to ensure the continuity and smoothness of the cutting path. Through the smoothing process, the discontinuous points and sharp changes in the path are smoothly transitioned, thereby avoiding the discontinuity and vibration problems that may occur during the cutting process and improving the cutting quality.

[0087] Furthermore, after the cutting paths of each layer are generated, this embodiment merges these paths to form an overall preliminary cutting path. During the merging process, the connection and transition of the paths of different layers are taken into consideration to ensure the continuity and consistency of the path in three-dimensional space. In order to further verify the effectiveness and feasibility of the preliminary cutting path, this embodiment conducts a preliminary evaluation and adjustment of the generated preliminary cutting path. The evaluation criteria include multiple aspects such as the length of the path, cutting time, cutting accuracy, and machine tool motion trajectory. Through evaluation and adjustment, it is ensured that the preliminary cutting path is not only feasible in theory, but also can be executed efficiently and stably in actual operation.

[0088] It should be understood that in the process of generating the preliminary cutting path, this embodiment also takes into account the loss of the electrode during the cutting process and the compensation of the cutting gap. Through real-time monitoring and dynamic adjustment, the accuracy and consistency of the cutting path of each layer are ensured. In addition, in order to improve the cutting efficiency and the intelligent level of path planning, this embodiment introduces intelligent algorithms, such as genetic algorithms and particle swarm optimization algorithms, to further optimize the generation and adjustment process of the preliminary cutting path.

[0089] The benefit of this embodiment is that the cutting path is generated by scanning the workpiece contour layer by layer, so that the accuracy and continuity of the path generation are achieved; the sharp corners and mutations in the path are eliminated through smoothing processing, and the smoothness and stability of the cutting path are improved; the feasibility and effectiveness of the path are ensured through preliminary evaluation and adjustment. Through this embodiment, the EDM wire cutting path planning method not only improves the efficiency of path generation and optimization, but also improves the quality and stability of cutting processing. Example

[0090] In order to solve the problem of unreasonable and inefficient path generation for workpieces of different shapes in wire EDM path planning, this embodiment further optimizes the scanning algorithm and improves the rationality and effectiveness of cutting path generation by adopting radial scanning and spiral scanning modes.

[0091] like Figure 5 As shown, the scanning algorithm includes radial scanning and spiral scanning, which are respectively suitable for workpieces of different shapes. The radial scanning and spiral scanning include the following steps:

[0092] S3021. In radial scanning mode, radial scanning is performed from the center point of the workpiece to the outside to generate a cutting path, which is suitable for circular or approximately circular workpieces;

[0093] S3022, in spiral scanning mode, starting from the center point of the workpiece, scanning outward layer by layer in a spiral path to generate a cutting path, which is suitable for workpieces with complex shapes;

[0094] S3023. Select the appropriate scanning mode according to the actual shape of the workpiece and the processing requirements, and evaluate and optimize the scanning results to ensure the rationality and effectiveness of the cutting path.

[0095] Specifically, in the radial scanning mode, this embodiment generates a cutting path for circular or nearly circular workpieces by radially scanning outward from the center point of the workpiece. This method is based on the geometric center of the workpiece, and the scanning is expanded outward layer by layer, and the path planning is realized by calculating the cutting path of each layer. The advantage of radial scanning is that its path is simple and the amount of calculation is small, which is particularly suitable for circular workpieces with high regularity. Through this scanning method, the uniformity of path generation and the stability of cutting can be ensured, and the calculation burden caused by complex path planning can be avoided.

[0096] Furthermore, this embodiment adopts a spiral scanning mode for cutting path generation of complex-shaped workpieces. The spiral scanning starts from the center point of the workpiece and scans outward layer by layer in a spiral path to generate a cutting path. This method is suitable for workpieces with complex geometric features, such as irregular polygons, workpieces with inner cavities or rich details. The spiral scanning path can fully adapt to the complex contours of the workpiece, provide a continuous and smooth cutting path, and avoid the problems of path breakage or sharp changes that may occur in traditional path planning methods.

[0097] It should be understood that the present embodiment selects a suitable scanning mode according to the actual shape of the workpiece and the processing requirements. When making a specific selection, the geometric features of the workpiece are analyzed in detail to determine its shape features and processing requirements, thereby deciding whether to use radial scanning or spiral scanning. In some cases, the two scanning modes may be used in combination to fully utilize their respective advantages and ensure the optimal generation of the cutting path.

[0098] Furthermore, in order to ensure the rationality and effectiveness of the scanning results, this embodiment evaluates and optimizes the generated cutting path. During the evaluation process, a series of quality indicators are used, such as path continuity, smoothness, cutting efficiency, and path length. Through a comprehensive analysis of these indicators, it is evaluated whether the path generated by the scan meets the preset quality standards. For paths that do not meet the standards, this embodiment performs optimization adjustments. The optimization process includes smoothing sharp corners and mutations in the path, and fine-tuning the path nodes to improve the smoothness and stability of the path.

[0099] Furthermore, in the process of path evaluation and optimization, this embodiment also introduces intelligent algorithms, such as genetic algorithms and particle swarm optimization algorithms. These intelligent algorithms can quickly search for optimal path combinations by simulating natural selection and group collaboration, significantly improving the efficiency and effect of path optimization. It should be understood that the introduction of these intelligent algorithms can not only increase the speed of path generation, but also effectively avoid the problem of local optimal solutions, ensuring that the final generated cutting path has global optimal characteristics.

[0100] The benefit of this embodiment is that by adopting radial scanning and spiral scanning modes, the appropriate path generation method is flexibly selected according to the shape characteristics of the workpiece, and the reasonable planning of the cutting path is realized; through detailed path evaluation and optimization, the continuity and smoothness of the path are ensured, and the precision and quality of cutting are improved; by introducing intelligent algorithms, the efficiency and effect of path generation and optimization are improved. Through this embodiment, the EDM wire cutting path planning method can better adapt to the processing requirements of workpieces of different shapes, significantly improve the efficiency and quality of cutting processing, and meet the high-precision requirements of complex processing tasks. Example

[0101] In order to solve the processing errors caused by electrode loss and cutting gap in EDM wire cutting path planning, this embodiment further refines the steps of compensating for electrode loss and cutting gap in the optimized cutting path to ensure the accuracy and effectiveness of the path and meet the processing requirements of the workpiece.

[0102] like Figure 6 As shown, the electrode loss and cutting gap compensation for the optimized cutting path includes the following steps:

[0103] S501, calculating the electrode loss according to the workpiece material and cutting parameters, and adjusting the optimized cutting path to compensate for the electrode loss;

[0104] S502, calculating the cutting gap compensation amount, the calculation formula of the cutting gap compensation is:

[0105] ,

[0106] Among them, Gc is the cutting gap compensation, De is the electrode diameter, and Dw is the EDM wire diameter;

[0107] S503, simulating the generated optimized cutting path and estimating the cutting time. The estimation formula of the cutting time is:

[0108] ,

[0109] Where Li is the length of the i-th path, and n is the number of path segments;

[0110] S504, perform workpiece thermal deformation analysis to evaluate the thermal stress and thermal deformation of the workpiece during cutting to ensure cutting quality;

[0111] S505, evaluating the simulation results, if the cutting time and the thermal deformation are beyond the preset range, adjusting the optimized cutting path, and re-simulating and verifying until the simulation results meet the processing requirements;

[0112] S506: Verify the adjusted optimized cutting path to ensure the accuracy and effectiveness of the path, and make final adjustments to the path to obtain a final cutting path.

[0113] Specifically, in the process of path optimization, this embodiment first considers the problem of electrode loss. According to the material properties of the workpiece and cutting parameters, such as cutting current, pulse width and discharge frequency, the amount of electrode loss during the cutting process is calculated. By establishing an electrode loss model, the wear of the electrode is monitored and calculated in real time, and the optimized cutting path is dynamically adjusted. It should be understood that the compensation amount of electrode loss changes continuously as the cutting process proceeds, so the adjustment of the compensation path is a dynamic and continuous process to ensure that the cutting path is always kept in the best state.

[0114] Furthermore, this embodiment calculates the compensation amount of the cutting gap. The cutting gap refers to the gap between the electrode and the workpiece during the wire EDM process, and its size directly affects the cutting accuracy. Through the calculation formula of the cutting gap compensation, the gap amount that needs to be compensated can be accurately calculated, so that corresponding adjustments can be made on the cutting path to eliminate the dimensional deviation caused by the gap.

[0115] Furthermore, the adjusted cutting path is verified to ensure the accuracy of the path. In this embodiment, the adjusted path is pre-verified through path simulation. The simulation process includes evaluating the continuity, smoothness and matching degree of the cutting path with the actual contour of the workpiece. Through simulation verification, problems in the path can be discovered and corrected in a timely manner to ensure that the final generated cutting path can meet the requirements of actual processing.

[0116] Furthermore, in order to estimate the cutting time, this embodiment introduces a cutting time estimation formula. Through the cutting time estimation formula, the time required for the entire cutting process can be accurately estimated, which helps to optimize the time allocation and resource scheduling of the cutting process and improve processing efficiency.

[0117] Furthermore, thermal deformation analysis of the workpiece is performed to ensure the cutting quality. During the wire EDM process, the workpiece will produce certain thermal stress and thermal deformation due to high-temperature discharge. This embodiment evaluates the thermal stress distribution and deformation of the workpiece during the cutting process through thermal deformation analysis. By monitoring the thermal stress and deformation, corresponding compensation measures can be taken in advance to reduce the processing error caused by thermal deformation and ensure the stability and reliability of the cutting quality.

[0118] Furthermore, the simulation result evaluation is to verify the adjustment effect of the cutting path. This embodiment systematically evaluates the simulation results. If it is found that the cutting time and thermal deformation exceed the preset range, the optimized cutting path is readjusted and the simulation verification is performed again. This process is repeated until the simulation results meet the processing requirements. Through this iterative optimization, it is ensured that the final generated cutting path is not only feasible in theory, but also can achieve the expected effect in actual operation.

[0119] Through this embodiment, the optimized cutting path has obtained effective electrode loss and cutting gap compensation, and the path accuracy and effectiveness have been significantly improved; through simulation verification and thermal deformation analysis, the stability and high quality of the cutting process are ensured; through accurate estimation of cutting time, the processing efficiency and resource utilization are improved. Finally, this embodiment realizes the precise control and optimization of EDM wire cutting path planning, meeting the needs of high-precision processing and complex workpiece processing. Example

[0120] In order to solve the problem of cutting time optimization in EDM wire cutting path planning, this embodiment further refines the steps of simulating the generated cutting path, especially the time optimization of the cutting path, to ensure that the cutting time is minimized and the processing efficiency is improved while ensuring the cutting quality.

[0121] like Figure 7 As shown, simulating the generated cutting path includes time optimization of the cutting path, and the steps of time optimization of the cutting path include:

[0122] S5031, analyzing the key points and turning points in the cutting path, and optimizing the cutting path time according to the positions of these points and the cutting speed;

[0123] S5032. Calculate the cutting time of each path and adjust the path to minimize the cutting time. The optimization formula for the cutting time is:

[0124] ,

[0125] Among them, Topt is the optimized cutting time, Vc,i is the cutting speed of the i-th path;

[0126] S5033. Perform simulation verification on the optimized cutting path to ensure that the cutting time and cutting quality meet the processing requirements of the workpiece.

[0127] Specifically, in the time optimization process of the cutting path, this embodiment first analyzes the key points and turning points in the cutting path. Key points and turning points refer to path change points in the cutting path due to workpiece geometric features or process requirements. The position and cutting speed of these points have a direct impact on the cutting time. Through the detailed analysis of these key points and turning points, their contribution to the overall time of the cutting path can be understood, and targeted time optimization can be performed accordingly.

[0128] Furthermore, this embodiment accurately calculates the cutting time of each path segment based on the path length and cutting speed. Through the optimization formula of cutting time, the cutting time of each path segment can be determined, and then the time optimization adjustment can be performed. It should be understood that in the actual adjustment process, not only the cutting speed of each path segment should be considered, but also the stability and processing quality of the cutting process should be comprehensively considered to achieve the best time optimization effect.

[0129] Furthermore, after the time optimization of the path, the present embodiment simulates and verifies the optimized cutting path. The purpose of the simulation verification is to ensure that the optimized path can not only minimize the cutting time, but also meet the processing quality requirements of the workpiece. In the simulation process, the actual processing process of the cutting path is simulated to evaluate its time and quality performance. The simulation verification includes multiple aspects such as the continuity, smoothness and matching degree of the path with the actual contour of the workpiece. Through comprehensive evaluation, it is ensured that the path does not affect the cutting quality while optimizing the time.

[0130] Furthermore, this embodiment also considers the influence of thermal deformation and thermal stress of the workpiece on the cutting process when optimizing the cutting path time. Through the analysis of thermal stress and thermal deformation, it is possible to foresee the deformation of the workpiece that may occur during the cutting process, and take corresponding compensation measures to ensure that the cutting path remains consistent and stable throughout the entire processing process. Thermal deformation analysis includes a comprehensive evaluation of parameters such as the thermal conductivity characteristics and thermal expansion coefficient of the workpiece, so as to ensure cutting quality while optimizing time.

[0131] The benefit of this embodiment is that, by analyzing the key points and turning points of the cutting path, combined with the accurate calculation of the path length and cutting speed, the cutting time is minimized; by simulation verification, the practical feasibility and processing quality of the optimized path are ensured; by thermal deformation analysis, the path stability and consistency during the cutting process are ensured. Through this embodiment, the EDM wire cutting path planning method not only improves the cutting efficiency, but also significantly improves the cutting quality. Example

[0132] In order to solve the problems of inaccurate path planning and processing errors caused by redundancy and geometric errors in CAD model data in electric spark wire cutting path planning, this embodiment further optimizes the preprocessing steps of CAD model data, ensures the integrity and accuracy of model data by removing redundant data and repairing geometric errors, thereby improving the quality and efficiency of cutting path planning.

[0133] like Figure 8 As shown, preprocessing the CAD model data also includes removing redundant data and repairing geometric errors, and removing redundant data and repairing geometric errors include the following steps:

[0134] S206, parsing the CAD model data, identifying and removing redundant data, such as repeated vertices, edges and faces;

[0135] S207, checking the integrity of the geometric model, identifying and repairing geometric errors, which include openings, polygon holes, and self-intersections;

[0136] S208. Perform quality assessment on the repaired geometric model to ensure the integrity and accuracy of the model.

[0137] Specifically, in the CAD model data preprocessing process, the present embodiment first parses the CAD model data. The parsing process includes reading geometric information in the CAD file, such as vertices, edges and faces, and analyzing these geometric elements one by one. Through parsing, redundant parts in the model data, such as repeated vertices, edges and faces, can be identified. These redundant data not only increase the complexity of data processing, but also may cause errors in path planning. Therefore, by effectively parsing and identifying, these redundant data are removed, the model structure is simplified, and the efficiency of data processing is improved.

[0138] Furthermore, the present embodiment checks the integrity of the geometric model and identifies and repairs geometric errors. Geometric errors include openings, polygonal holes, and self-intersections, which can seriously affect the accuracy and integrity of the model. An opening refers to an unclosed edge on the model surface, which may cause the cutting path to be incorrectly generated in that area. A polygonal hole refers to a hole inside the model that should not exist, which affects the continuity and consistency of the path planning. A self-intersection refers to a self-intersection on the model surface, which can cause the path planning algorithm to be unable to correctly identify the model boundary, thereby affecting the cutting accuracy.

[0139] It should be understood that in the process of repairing geometric errors, this embodiment can use a series of algorithms and techniques. For example, for the opening problem, the boundary extension and closing algorithm can be used to connect the unclosed edges to form a complete closed boundary. For polygonal holes, a filling algorithm can be used to fill the holes according to the surrounding geometric information to restore the integrity of the model. For the self-intersection problem, the self-intersection area can be decomposed into non-self-intersection sub-areas through the geometric decomposition and reconstruction algorithm, thereby eliminating the self-intersection.

[0140] Furthermore, quality assessment of the repaired geometric model ensures model integrity and accuracy. This embodiment uses a series of quality assessment indicators to perform a detailed inspection of the repaired model. The quality assessment indicators include the topological structure integrity, geometric shape accuracy, and surface smoothness of the model. Through these assessments, it can be ensured that the repaired model is completely correct in geometry, has no residual errors, and is suitable for subsequent path planning and processing.

[0141] Furthermore, in the quality assessment process, this embodiment can also introduce automated detection and repair tools. These tools can quickly and efficiently identify potential problems in the model and automatically repair them, thereby improving the efficiency and accuracy of preprocessing. For example, using machine learning-based algorithms, common geometric error patterns can be learned and identified, thereby quickly repairing them. Through the application of these tools, the preprocessing process is more intelligent and automated, reducing the need for manual intervention.

[0142] The benefit of this embodiment is that by effectively preprocessing the redundancy and geometric errors of the CAD model data, the integrity and accuracy of the model data are ensured, providing high-quality basic data for subsequent cutting path planning; by introducing algorithms and automation tools, the efficiency and effect of preprocessing are improved, and the impact of human factors on processing quality is reduced; through quality assessment and testing, it is ensured that the repaired model has no geometric errors and is suitable for high-precision processing requirements. Through this embodiment, the EDM wire cutting path planning method not only achieves high efficiency and accuracy in the data processing link, but also significantly improves the quality and efficiency of the entire processing process. Example

[0143] In order to solve the complexity and accuracy problems in cutting path planning of wire-cut electric discharge machines, this embodiment further optimizes the various modules of the cutting path planning system to achieve efficient and accurate path planning, and fully considers factors such as electrode loss, cutting gap compensation, and machine tool kinematics and dynamics.

[0144] like Fig. 9 As shown, the cutting path planning system of this embodiment includes multiple functional modules, each of which works together to ensure the overall performance and reliability of the system. First, the workpiece CAD model data acquisition module is used to receive and store the geometric shape, size and material information of the workpiece. This module automatically imports and stores the workpiece model data through the interface with the CAD software, providing basic data for subsequent path planning. It should be understood that accurate geometric shape and material information are the key to path planning, and any data error will affect the final cutting quality.

[0145] Furthermore, the CAD model data preprocessing module processes the imported workpiece model. This module is responsible for extracting the geometric features of the workpiece, and performing meshing and geometric error repair. Meshing is to decompose complex geometric shapes into small, processable units, making subsequent path planning more refined and accurate. Geometric error repair is to repair problems such as openings, holes, and self-intersections that may exist in the model to ensure the integrity and accuracy of the model. Through preprocessing, the model data is more standardized, laying the foundation for the generation of the preliminary cutting path.

[0146] Furthermore, the preliminary cutting path generation module generates a preliminary cutting path based on the geometric features and process parameters of the workpiece. The module generates a cutting path that meets the preliminary requirements by analyzing the geometric features of the workpiece, such as contours, inner holes and grooves, and combining cutting process parameters, such as cutting speed and discharge voltage. It should be understood that the preliminary cutting path is a preliminary result, and its main purpose is to provide a preliminary cutting plan, which needs to be further optimized later.

[0147] Furthermore, the cutting path optimization module optimizes the preliminary cutting path. This module obtains the optimized cutting path through selection, crossover and mutation operations. The selection operation is to select the appropriate path segment from the preliminary cutting path for optimization, the crossover operation is to combine different path segments, and the mutation operation is to fine-tune and improve the path segment. Through these operations, an optimized cutting path can be obtained to ensure the continuity, smoothness and processing efficiency of the path.

[0148] Furthermore, the final cutting path generation module generates the final cutting path based on the optimized cutting path, taking into account electrode loss, cutting gap compensation, and the kinematic and dynamic characteristics of the machine tool. Electrode loss compensation is to adjust the path according to the electrode wear during the cutting process, cutting gap compensation is to compensate the gap according to the electrode diameter and the diameter of the EDM wire, and the kinematic and dynamic characteristics of the machine tool are to optimize the path according to the actual motion characteristics of the machine tool to ensure the actual feasibility of the cutting path.

[0149] Furthermore, the instruction code generation module converts the final cutting path into machine tool instruction G code and M code. G code and M code are instructions for the machine tool to perform cutting operations. The instruction code generated by this module can be directly imported into the machine tool control system to realize automatic cutting operations. It should be understood that the accuracy and completeness of the instruction code are the key to ensure the normal operation of the machine tool. Any wrong code will lead to cutting failure.

[0150] Furthermore, the simulation verification module simulates and verifies the cutting path. This module simulates the cutting process to perform cutting time estimation, thermal deformation analysis, and collision detection. Cutting time estimation is to estimate the time of the entire cutting process to ensure that the cutting process is completed within the expected time. Thermal deformation analysis is to evaluate the thermal stress and thermal deformation of the workpiece during the cutting process to ensure the cutting quality. Collision detection is to detect potential collisions between the cutting path and the workpiece or machine tool to avoid accidents during the cutting process.

[0151] Furthermore, the user interface module is used to display the cutting path planning results and accept the optimization parameters input by the user. Through the user interface, the user can view the generation and optimization process of the cutting path, adjust the cutting parameters, and monitor the cutting progress in real time. It should be understood that the friendliness and ease of use of the user interface directly affect the user's operating experience and the efficiency of the system.

[0152] Furthermore, the cloud computing platform module is used to store and process path planning data and provide high-performance computing resources. Through the cloud computing platform, big data storage and processing can be realized, and the calculation efficiency and accuracy of path planning can be improved. At the same time, the cloud computing platform can also realize multi-user collaborative work and improve the overall performance of the system.

[0153] Through this embodiment, the cutting path planning system realizes efficient and accurate cutting path planning under the collaborative work of various modules; through the preprocessing of model data and path optimization, the accuracy and quality of the cutting path are ensured; through the application of simulation verification and cloud computing platform, the reliability and computing efficiency of the system are improved. The system is suitable for the high-precision processing requirements of complex workpieces and provides strong support for the development of wire EDM technology. Example

[0154] In order to solve the problems of complexity, accuracy and efficiency that may be encountered by electric spark wire cutting machines in the path planning process, this embodiment further optimizes the cutting path planning method and stores it in a computer-readable storage medium. When the program runs on a computer, it can execute the optimized cutting path planning method for electric spark wire cutting machines.

[0155] Specifically, the computer-readable storage medium of this embodiment includes multiple functional modules, each of which works together to ensure the overall performance and reliability of the path planning method. The functions of the multiple functional modules have been detailed in the above embodiments and will not be repeated in this embodiment.

[0156] It should be understood that in this embodiment, data exchange and communication are performed between the modules through interfaces and protocols to ensure the efficiency and stability of the system operation. For example, the data transmission between the workpiece CAD model data acquisition module and the CAD model data preprocessing module ensures accurate data transmission and processing through standardized data formats and communication protocols. The interaction between the preliminary cutting path generation module and the cutting path optimization module realizes dynamic adjustment and update of path optimization through parameter adjustment of the optimization algorithm. The interface between the final cutting path generation module and the instruction code generation module realizes seamless conversion of cutting paths to machine tool instructions through code generation rules and templates.

Claims

1. A cutting path planning method for a wire-cut electric discharge machine, characterized in that: The planning method comprises the following steps: Obtain the CAD model data of the workpiece, including the workpiece's geometry, size, and material information; Preprocessing the CAD model data to extract geometric features of the workpiece, wherein the geometric features include boundary curves, feature points and surface information; Determine the cutting start and end points according to the geometric shape, set the cutting layer thickness, and generate a preliminary cutting path by scanning the workpiece model layer by layer; Performing selection, crossover and mutation operations on the preliminary cutting path to obtain an optimized cutting path; Compensating the optimized cutting path for electrode loss and cutting gap, and taking into account the kinematic and dynamic characteristics of the machine tool to obtain a final cutting path; The selection, crossover and mutation operations on the preliminary cutting path include the following steps: Initializing a population to generate a plurality of initial cutting paths, wherein the initial cutting paths are generated based on geometric features of the workpiece and cutting process parameters; The fitness of each initial cutting path is evaluated, and the fitness evaluation is based on the objective function, and the objective function expression is: ， Among them, F is the objective function value, Rs is the surface roughness of the workpiece, Vc is the cutting speed, Ec is the cutting energy consumption, Tc is the cutting time, and α, β, γ and δ are weight coefficients respectively; According to the value of the fitness, the preliminary cutting path with high fitness is selected to perform crossover and mutation operations to generate an optimized cutting path, wherein the crossover operation includes exchanging path segments, and the mutation operation includes random adjustment of path nodes; The fitness of the optimized cutting path is evaluated, and the population is updated according to the fitness value until the optimization condition is met, wherein the optimization condition includes that the fitness value reaches a preset threshold value or the number of iterations reaches a preset upper limit.

2. The cutting path planning method of wire-cut electric discharge machine according to claim 1, characterized in that: Preprocessing the CAD model data includes the following steps: Analyze the geometric features of the workpiece to determine the complex area and the simple area, use smaller grid units in the complex area and larger grid units in the simple area, and the size of the grid unit is dynamically adjusted according to the complexity of the geometric features of the workpiece; Refine the complex area multiple times until the mesh density meets the preset standard; At the same time, the refined grid is smoothed to eliminate the mutations between grid cells; Calculate the geometric properties of each grid cell, including area, side length, and angle; The quality of the meshing results is evaluated, and the mesh elements with poor quality are locally refined or re-divided until the mesh quality meets the preset standards.

3. The cutting path planning method of wire-cut electric discharge machine tool according to claim 1, characterized in that: The step of generating the preliminary cutting path by scanning the workpiece model layer by layer includes a scanning algorithm based on the workpiece contour, and the scanning algorithm generates a path by scanning the workpiece model layer by layer. The specific steps include: Determine the cutting start and end points of the workpiece, and set the cutting layer thickness according to the geometric features of the workpiece; Starting from the cutting starting point, the workpiece model is scanned layer by layer to generate a cutting path for each layer, wherein the path includes a straight line segment, an arc segment, and a spline curve segment; Smooth the cutting path of each layer to eliminate sharp corners and mutations in the path; The cutting paths of each layer are merged to generate a preliminary cutting path, and the preliminary cutting path is preliminarily evaluated and adjusted.

4. The cutting path planning method of wire-cut electric discharge machine tool according to claim 3, characterized in that: The scanning algorithm includes radial scanning and spiral scanning, which are respectively applicable to workpieces of different shapes. The radial scanning and spiral scanning include the following steps: In radial scanning mode, radial scanning is performed from the center point of the workpiece to the outside to generate a cutting path, which is suitable for circular or nearly circular workpieces; In the spiral scanning mode, starting from the center point of the workpiece, the cutting path is generated by scanning outward layer by layer in a spiral path; Select the appropriate scanning mode according to the actual shape of the workpiece and processing requirements, and evaluate and optimize the scanning results.

5. The cutting path planning method for a wire-cut electric discharge machine tool according to claim 1 or 2, characterized in that: Preprocessing the CAD model data further includes removing redundant data and repairing geometric errors, wherein removing redundant data and repairing geometric errors include the following steps: Parsing the CAD model data to identify and remove redundant data, including duplicate vertices, edges, and faces; Checking the integrity of the geometric model, identifying and repairing geometric errors, including openings, polygon holes, and self-intersections; Perform quality assessment on the repaired geometric model.

6. A computer-readable storage medium storing a program, characterized in that: When the program is run on a computer, the cutting path planning method for a wire-cut electric discharge machine tool according to any one of claims 1 to 5 is executed.

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