Graph source contour construction method and equipment for laser cutting nesting software and medium

Abstract

The invention provides a graph source contour construction method for laser cutting nesting software, and the method can gradually select the most suitable curve fitting type from a straight line, an arc, a quadratic curve and a cubic spline according to the geometrical characteristics of an input point set. The adaptive curve fitting type selection mechanism can significantly improve the fitting precision and quality of the image source contour curve, and at the same time, the method can also reduce unnecessary calculation complexity, thereby further improving the fitting efficiency.

Description

Technical Field

[0001] This application relates to the field of laser cutting technology, and more specifically, to a method, device, and medium for constructing a source image contour for laser cutting nesting software. Background Art

[0002] In laser cutting and computer-aided manufacturing (CAM), two-dimensional nesting (also known as nesting or layout) software typically needs to import two-dimensional drawings generated by computer-aided design (CAD) software, parse the geometric shapes of the parts to be processed therein, and thereby construct machining trajectories, so as to output machining programs executed by corresponding cutting machines.

[0003] Generally speaking, what can be extracted from the two-dimensional graphic files output by CAD software are a series of points and the element types between points, including three types: straight lines, arcs, and full circles. For simple graphics, straight lines and arcs are sufficient to describe their geometric shapes, but for those complex geometric graphics, curves are needed to describe their shapes.

[0004] When these complex curves are exported to a standard format (such as DXF or DWG), they are usually approximately processed into a large number of small line segments. For example, a short complex curve may be represented as hundreds or even thousands of tiny straight line segments. Although this representation method ensures geometric accuracy, it poses a huge challenge to CAM software.

[0005] Currently, most CAM software adopts the following relatively simple methods when processing such inputs. For example: (1) Deleting overly short line segments: Although this method can reduce the data volume, it may cause distortion of geometric shapes. (2) Converting large arcs into straight line segments: Although this method simplifies data processing, it may affect the cutting quality, especially in applications that require high precision. (3) Simple graphic closing processing: This method may not be able to correctly process complex open contours or internal structures.

[0006] These methods are usually sufficient when processing conventional parts. However, with the progress of laser processing technology and the expansion of application fields, CAM software increasingly needs to process special-shaped parts with complex shapes. The existing methods show obvious limitations when facing the processing tasks of these special-shaped parts with complex shapes, including: (1) Precision loss: Excessive simplification may lead to the loss of key geometric features, affecting the quality of the final product. (2) Low efficiency: A large number of tiny line segments increase the complexity of data processing and reduce the efficiency of nesting and path planning. (3) Cutting quality problems: Especially when processing tiny line segments less than 1 mm, the existing methods may result in unsatisfactory tool compensation effects, thereby affecting the cutting quality.

[0007] (4)Lack of adaptability: Fixed processing methods are difficult to adapt to the special requirements of different types of parts. (5)Difficulty in optimization: A large number of tiny line segments make further graphic optimization extremely difficult and it is hard to achieve the best material utilization rate.

[0008] In recent years, some improvement schemes have been successively proposed in the industry. For example, someone proposed a fitting method based on B-spline curves to approximately fit complex curves by optimizing control points. Some researchers have also explored the use of adaptive segmentation algorithms to balance accuracy and efficiency. However, these methods often only focus on a single objective (such as geometric accuracy) and fail to comprehensively consider various requirements in actual processing. Summary of the Invention

[0009] In view of at least one defect or improvement requirement of the prior art, this application proposes a method, device and medium for constructing the source image contour of a laser cutting nesting software, which is used to improve the fitting accuracy and quality of the source image contour curve and at the same time improve the fitting efficiency.

[0010] To achieve the above object, in the first aspect, this application provides a method for constructing the source image contour of a laser cutting nesting software, including:

[0011] Parse the CAD file, extract the point set data and perform preprocessing;

[0012] For each preprocessed point set, use the straight-line equation for straight-line fitting to obtain the straight-line fitting error; if the straight-line fitting error is less than the first preset threshold, select the straight line as the fitting curve for this segment;

[0013] If the straight-line fitting error is not less than the first preset threshold, use the circle equation for circular arc fitting to obtain the circular arc fitting error; if the circular arc fitting error is less than the second preset threshold, select the circular arc as the fitting curve for this segment;

[0014] If the circular arc fitting error is not less than the second preset threshold, use the quadratic equation for quadratic curve fitting to obtain the quadratic curve fitting error; if the quadratic curve fitting error is less than the third preset threshold, select the quadratic curve as the fitting curve for this segment;

[0015] If the quadratic curve fitting error is not less than the third preset threshold, select the cubic spline curve as the fitting curve for this segment;

[0016] After determining the type of each fitting curve, perform curve fitting to construct the source image contour for the laser cutting nesting software.

[0017] Further, the step of performing curve fitting to construct the source image contour for the laser cutting nesting software after determining the type of each fitting curve includes:

[0018] Take one or more of geometric fitting error, curve smoothness, cutting path length, and machining efficiency as optimization objectives, and construct a comprehensive objective function based on the corresponding objective weights;

[0019] Use the particle swarm optimization algorithm to minimize the comprehensive objective function and obtain the source image contour for the laser cutting nesting software.

[0020] Furthermore, the step of taking one or more of geometric fitting error, curve smoothness, cutting path length, and machining efficiency as optimization objectives and constructing a comprehensive objective function based on the corresponding objective weights includes:

[0021] Geometric fitting error E 1 Is defined as the mean square distance from the original point to the corresponding point on the fitted curve, that is Where, (x i , y i ) represents the coordinates of the original point extracted from the parsed CAD file, and (x′ i , y′ i ) represents the coordinates of the corresponding point on the fitted curve;

[0022] Curve smoothness E 2 Is measured by the sum of the squares of the curvatures of the uniformly sampled points on the fitted curve, that is Where, κ i Represents the curvature of m sampled points;

[0023] Cutting path length E 3 Take the total length L of the fitted curve, that is E 3 = L;

[0024] Machining efficiency E 4 Considers the influence of cutting speed and is defined as Where, v i Represents the recommended cutting speed of each segment of the fitted curve;

[0025] The expression of the comprehensive objective function is E = ∑w i E i , where, E i Represents the aforementioned several optimization objectives, and w i Represents the corresponding objective weight coefficient of the optimization objective E i ;

[0026] Furthermore, it also includes:

[0027] Perform continuity processing on adjacent curve segments of the constructed source image contour to ensure tangent continuity, and the relevant formulas include:

[0028]

[0029] Among them, C 1 ′(t) represents the tangent direction of the first curve at the connection point t 0 ; C 2 ′(t) represents the tangent direction of the second curve at the connection point t 0 . represents approaching t from the first side 0 , represents approaching t from the second side opposite to the first side 0 .

[0030] Furthermore, it also includes:

[0031] Performing a fitting curve optimization considering the tool radius compensation on the constructed source image contour to ensure that the curvature of the cutting path does not exceed the limit that the laser cutting machine can handle. The relevant formulas include:

[0032]

[0033] Among them, C′(t) and C″(t) respectively represent the first-order and second-order derivative vectors of the fitting curve; K represents the curvature of the cutting path; r represents the tool radius compensation.

[0034] Furthermore, it also includes:

[0035] Performing a global path planning on the constructed source image contour to minimize the total idle running time and improve the overall processing efficiency. The relevant formulas include:

[0036] D = ∑||P i+1 – P i ||;

[0037] Among them, P i represents the starting point of the i-th cutting path; D represents the total idle running distance, and minimizing the total idle running time can be achieved by minimizing the total idle running distance.

[0038] Furthermore, the preprocessing includes:

[0039] Performing a smoothing process on each continuous point set using the moving average method to reduce the influence of noise information.

[0040] Furthermore, the preprocessing includes:

[0041] Using the Douglas - Peucker algorithm to extract key feature points to reduce the data volume.

[0042] In a second aspect, the present application provides an electronic device, including at least one processing unit and at least one storage unit. Wherein, the storage unit stores a computer program, and when the computer program is executed by the processing unit, the processing unit is enabled to execute the steps of the method for constructing a source image contour for a laser cutting nesting software as described in any one of the above.

[0043] In a third aspect, the present application provides a storage medium, which stores a computer program executable by an access authentication device. When the computer program runs on the access authentication device, the access authentication device is enabled to execute the steps of the method for constructing a source image contour for a laser cutting nesting software as described in any one of the above.

[0044] Generally speaking, compared with the prior art through the above technical solutions conceived by the present application, the following beneficial effects can be achieved:

[0045] (1) The present application uniquely proposes a method for adaptively selecting the most suitable curve type. This method can automatically and gradually select the most suitable curve fitting type among straight lines, circular arcs, quadratic curves, and cubic spline curves according to the geometric characteristics of the input point set. This adaptive curve fitting type selection mechanism can significantly improve the fitting accuracy and quality of the source image contour curve. At the same time, this method can also reduce unnecessary computational complexity, thereby further improving the fitting efficiency.

[0046] (2) The present application innovatively integrates multiple objective functions into an optimization framework. These objectives can include geometric fitting error, curve smoothness, cutting path length, and processing efficiency. By using the corresponding weight coefficients of each objective, the importance of each objective can be dynamically adjusted. This method can flexibly balance various requirements in different application scenarios and achieve comprehensive optimization.

[0047] (3) The present application introduces innovative post-processing steps after fitting, which can include G1 continuity processing, curve optimization considering the tool radius compensation, and global path planning and other processing methods. These steps fully consider the physical constraints and process requirements in the actual laser cutting process, ensuring the practicality and machinability of the fitting results. Description of the Drawings

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0049] Figure 1It is the core flowchart of a method for constructing a source image contour for a laser cutting nesting software provided by an embodiment of the present application;

[0050] Figure 2 It is the detailed flowchart of a method for constructing a source image contour for a laser cutting nesting software provided by an embodiment of the present application;

[0051] Figure 3 It is the block diagram of an electronic device suitable for implementing the method for constructing a source image contour for a laser cutting nesting software described above provided by an embodiment of the present application. Detailed implementation manners

[0052] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. In addition, the technical features involved in the various embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0053] Terms such as "first", "second" or "nth" in the specification, claims or the above-mentioned drawings of the present application are used to distinguish different objects rather than to describe a specific order. In addition, the terms "include" or "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products or devices.

[0054] Brief introduction of terms:

[0055] (1) CAM: computer Aided Manufacturing, that is, computer-aided manufacturing, which is a process of using a computer to manage, control and operate production equipment. The information it inputs is the process route and operation content of parts, and the information it outputs is the movement trajectory (tool position file) during tool processing and the numerical control program.

[0056] (2) CAD: Computer Aided Design, that is, computer-aided design, which uses a computer and its graphic devices to assist designers in their design work.

[0057] (3) Nesting software: A computer-aided manufacturing (CAM) software mainly used to create nests and prepare parts for cutting. It usually imports part geometries from CAD, applies various cutting parameters, prepares files for machining, and finally creates nests manually or automatically by the user. Nesting software is widely used in multiple industries, especially in metal processing, textile and other fields. Currently, nesting software has been highly automated and has a simple operation logic. Users only need to import steel plates and DXF part drawings, and the software will automatically arrange materials and generate NC codes.

[0058] (4) Douglas-Peucker algorithm: That is, the Douglas-Peucker algorithm, which is an algorithm for approximately representing a curve as a series of points and reducing the number of points. Its advantage is that it has translational and rotational invariance. Given a curve and a threshold, the sampling result is certain.

[0059] (5) PSO: Particle Swarm Optimization, that is, particle swarm optimization, also known as particle swarm algorithm, is an evolutionary computing technology developed by J. Kennedy and R. C. Eberhart et al. in 1995, originating from the simulation of a simplified social model. The "swarm" in it comes from the five basic principles of swarm intelligence proposed by M. M. Millonas when developing a model applied to artificial life. "Particle" is a compromise choice because it is necessary to describe the members in the group as having no mass and no volume, while also describing its speed and acceleration state.

[0060] The PSO algorithm was initially developed to graphically simulate the graceful and unpredictable movement of bird flocks. Through the observation of the social behavior of animals, it was found that the social sharing of information in a group provides an evolutionary advantage, and this was used as the basis for developing the algorithm. By adding velocity matching of neighbors, considering multi-dimensional search and acceleration based on distance, the initial version of PSO was formed. Subsequently, the inertial weight w was introduced to better control exploitation and exploration, forming the standard version.

[0061] (6) Spline curve: Refers to a curve obtained by given a set of control points. The general shape of the curve is controlled by these points. It can generally be divided into interpolation splines and approximation splines. Interpolation splines are usually used for digital drawing or animation design, and approximation splines are generally used to construct the surface of an object.

[0062] (7)DWG: A drawing saving format created by AutoCAD, which has now become the standard format for 2D CAD. DWG files not only contain all the information of the graphics, such as lines, dimensions, texts, layers, etc., but also save the attributes such as the position, color and linetype of the graphics on the screen. Therefore, DWG files are the most common file format in the AutoCAD drawing process.

[0063] (8)DXF: Drawing Exchange Format, which is an ASCII text file mainly used for the exchange and communication of CAD designs. DXF files contain all the information of the corresponding DWG files, but they are not stored in ASCII code form, so their readability is poor. However, due to the fast exchange speed of DXF files, they are widely used for the exchange and sharing of CAD data.

[0064] Both DWG and DXF are commonly used file formats in CAD.

[0065] (9)Tool compensation radius: Also known as tool radius compensation, it is an important concept in numerical control machining. It involves programming according to the contour dimensions of the part during programming, and the tool path of the numerical control machine tool will be automatically offset according to the preset offset amount (i.e., the tool radius), so as to ensure that the machined part meets the accuracy requirements. This process is achieved through specific numerical control instructions, including G41 (left compensation), G42 (right compensation) and G40 (cancellation of compensation). The main functions of tool radius compensation include simplifying the programming work, adapting to tool wear or replacement, realizing flexible switching between roughing and finishing, and machining internal and external contours by changing the compensation direction.

[0066] In modern manufacturing, computer-aided design (CAD) software widely uses spline curves to create precise part models, and this trend is particularly obvious in the process of converting 3D models into 2D floor plans. However, this precise modeling method poses severe challenges to computer-aided manufacturing (CAM) software. Spline curves can essentially be regarded as a collection of a large number of continuous points, and straight line segments are usually used to connect between points, resulting in a seemingly simple curve that may be represented as hundreds or even thousands of straight lines in DXF format files. This complex representation significantly increases the difficulty of CAM software in realizing functions such as graphic import, typesetting, part editing and source image scaling.

[0067] CAM software faces multiple dilemmas when dealing with these complex graphics. First of all, in order to improve material utilization rate, the software needs to optimize the graphics. However, a large number of small line segments make the optimization algorithm extremely complex and difficult to find the optimal solution within a reasonable time. Secondly, a large number of tiny line segments with lengths less than 1mm in the spline curve have a serious impact on the establishment of tool compensation during the laser cutting process, which may lead to a significant decrease in cutting accuracy. Therefore, in the process of optimizing the graphic import of laser cutting nesting software, small line segment fitting has become a crucial link. Effective small line segment fitting can not only smooth and simplify the cutting path, but also significantly reduce the number of machine movements and the overall processing time.

[0068] Facing these challenges, existing processing methods often seem inadequate. Simple line segment deletion or merging may lead to the loss of key geometric features, thus affecting the functionality and aesthetics of the parts. And overly conservative processing methods are difficult to effectively reduce the data volume and cannot significantly improve the efficiency of subsequent processing. In addition, existing methods usually only focus on geometric fitting accuracy, but often ignore other important factors such as the smoothness of the cutting path and processing efficiency, making it difficult to meet the diverse needs in actual production.

[0069] In view of this, this application aims to develop an innovative small line segment fitting algorithm specifically for laser cutting nesting software. The core goal of this algorithm is to effectively fit a large number of continuous points in CAD files such as DXF and DWG into an approximate curve. This method not only needs to ensure geometric accuracy, but also needs to consider multiple aspects such as cutting efficiency and path smoothness. By introducing an adaptive fitting curve type selection mechanism and a multi-objective optimization framework, this application is committed to significantly improving data processing efficiency and cutting quality while maintaining the key features of the parts.

[0070] The purpose of this application is not only limited to solving the difficulties faced by current CAM software in dealing with complex curves, but also to provide a more accurate, efficient and flexible solution for the entire laser cutting industry. By optimizing the curve fitting process, this application aims to improve material utilization rate, reduce processing time and ultimately improve product quality. This innovative method is expected to bring substantial technological progress to modern manufacturing, enabling laser cutting technology to better adapt to the increasingly complex industrial design requirements.

[0071] Reference Figure 1 and Figure 2, an embodiment of the present application proposes an adaptive curve fitting method based on multi-objective optimization (i.e., a method for constructing the source image contour for laser cutting nesting software), which is specifically used for processing small line segments in two-dimensional laser cutting nesting. This method integrates multiple key links such as data preprocessing, adaptive curve type selection, multi-objective optimization fitting, and post-processing optimization, aiming to improve the accuracy and efficiency of curve fitting while taking into account the practicality of the cutting path. The specific implementation process of this method will be elaborated in detail below.

[0072] First, in the data preprocessing stage, this method parses the input CAD files such as DXF or DWG, and extracts all the point set data. For each continuous point set, the moving average method is used for smoothing processing to reduce the influence of noise information. Let the original point set be {(x i , y i ), i = 1, 2, …, n}, then the smoothed point set {(X i , Y i )} can be calculated by the following formula:

[0073]

[0074] This smoothing process can effectively reduce the random fluctuations in the data and lay a foundation for subsequent curve fitting.

[0075] Subsequently, the Douglas-Peucker algorithm is applied to extract key feature points to significantly reduce the data volume. Set the distance threshold ε, and recursively judge the maximum distance d max from the point to the line segment, and retain the points that are crucial for shape description, thereby greatly reducing the number of points while maintaining geometric features.

[0076] d max = max(||(x i , y i ) - proj((x i , y i ), AB)||);

[0077] Among them, proj((x i , y i ), AB) is the projection of the point (x i , y i ) on the line segment AB.

[0078] In the adaptive curve type selection stage, this method considers four curve types: straight line, circular arc, quadratic curve, and cubic spline curve.

[0079] For each preprocessed point set, first attempt linear regression to calculate the straight line equation y = kx + b. If the straight line fitting error is less than the preset threshold δ 1 , then select the straight line as the fitting curve for this segment.

[0080] If the straight line fitting does not meet the requirements, then perform circular arc fitting and use the least squares method to solve the circle equation (x - a) 2 +(y - b) 2 = r 2 . If the circular arc fitting error is less than the preset threshold δ 2 , then select the circular arc as the fitting curve for this segment.

[0081] If the circular arc fitting is still not ideal, then attempt quadratic curve fitting and solve the quadratic equation y = ax 2 + bx + c. When the quadratic curve fitting error is less than the preset threshold δ 3 , select the quadratic curve as the fitting curve for this segment.

[0082] If none of the above three curve types can meet the requirements for fitting accuracy, then by default, select the cubic spline curve as the fitting curve.

[0083] After determining the type of fitting curve for each segment, perform curve fitting to construct the source image contour for the laser cutting nesting software.

[0084] This application uniquely proposes a method for adaptively selecting the most suitable curve type. This method can automatically and gradually select the most suitable curve fitting type from straight lines, circular arcs, quadratic curves, and cubic spline curves according to the geometric characteristics of the input point set. This adaptive curve fitting type selection mechanism can significantly improve the fitting accuracy and quality of the source image contour curve. At the same time, this method can also reduce unnecessary computational complexity, thereby further improving the fitting efficiency.

[0085] When the types of curves to be fitted for each segment are determined, preferably, an embodiment of this application introduces a multi-objective optimization framework to perform more accurate curve fitting. Considering the actual requirements of laser cutting, several optimization objectives including but not limited to geometric fitting error, curve smoothness, cutting path length, and processing efficiency are carefully set.

[0086] The geometric fitting error E 1 is defined as the mean square distance from the original points to the corresponding points on the fitting curve, that is:

[0087]

[0088] where (x i , y i ) represents the coordinates of the original points extracted from the parsed CAD file, (x' i, y' i ) represents the coordinates of the corresponding point on the fitting curve.

[0089] Curve smoothness E 2 It is measured by the sum of the squares of the curvatures of uniformly sampled points on the fitting curve, that is:

[0090]

[0091] where κ i represents the curvatures of m sampled points.

[0092] Cutting path length E 3 Take the total length L of the fitting curve, that is:

[0093] E 3 = L;

[0094] Processing efficiency E 4 Taking into account the influence of the cutting speed, it is defined as:

[0095]

[0096] where v i represents the recommended cutting speed for each segment of the fitting curve.

[0097] These four objectives can be combined into a comprehensive objective function E through their respective weight coefficients w i That is:

[0098] E = w 1 E 1 + w 2 E 2 + w 3 E 3 + w 4 E 4 ;

[0099] where E i represents the aforementioned several optimization objectives, and w i represents the corresponding objective weight coefficient of the optimization objective E i .

[0100] To solve this multi-objective optimization problem, this embodiment adopts the particle swarm optimization algorithm (PSO). PSO iteratively updates the positions and velocities of particles by simulating swarm intelligence and finally converges to the optimal solution. Each particle represents a set of curve parameters. By continuously adjusting these parameters, the comprehensive objective function E is minimized, thereby obtaining an accurate and practical fitting curve.

[0101] This application innovatively integrates multiple objective functions into an optimization framework. These objectives can include geometric fitting error, curve smoothness, cutting path length, and machining efficiency. By using the corresponding weight coefficients of each objective, the importance of each objective can be dynamically adjusted. This method can flexibly balance various requirements in different application scenarios, thus achieving comprehensive optimization.

[0102] After completing the aforementioned main curve fitting process, preferably, an embodiment of this application further introduces a post-processing optimization step to further improve the practicality of the fitting result.

[0103] First, perform continuity processing on adjacent curve segments to ensure G1 continuity, that is, tangent continuity, which is crucial for ensuring the smoothness of the cutting path. The relevant formulas include:

[0104]

[0105] Among them, C 1 ′(t) represents the tangent direction of the first curve at the connection point t 0 , and C 2 ′(t) represents the tangent direction of the second curve at the connection point t 0 ; represents approaching t 0 , represents approaching t 0 .

[0106] Secondly, according to the characteristics of the laser cutting machine, especially considering the tool compensation radius r, optimize the fitted curve to avoid sharp turns smaller than the tool compensation radius and ensure that the curvature K does not exceed the allowable value. The relevant formulas include:

[0107]

[0108] In the above formulas, C(t) is the parameterized curve equation, and C′(t) and C″(t) represent the first derivative vector and the second derivative vector of the curve respectively. This formula will ensure that the curvature of the cutting path does not exceed the limit that the laser cutting machine can handle.

[0109] Finally, based on the optimized curve, perform global path planning to minimize the total idle running time to improve the overall machining efficiency. The relevant formulas include:

[0110] D = Σ||P i+1 – P i ||;

[0111] Among them, P iRepresents the starting point of the i-th cutting path; D represents the total non-cutting travel distance. Minimizing the total non-cutting travel time can be achieved by minimizing the total non-cutting travel distance. Non-cutting travel refers to the movement of the laser cutting machine when it is not actually cutting, usually occurring when moving from the end of one cutting path to the starting point of the next path.

[0112] G1 continuity processing, curve optimization considering tool compensation radius, and global path planning respectively target different optimization goals of smoothness, machinability, and processing efficiency, solve different technical problems, and theoretically can be independently applied in several cases or used together.

[0113] This application introduces innovative post-processing steps after fitting, which may include G1 continuity processing, curve optimization considering tool compensation radius, and global path planning and other processing methods. These steps fully consider the physical constraints and process requirements in the actual laser cutting process, ensuring the practicality and machinability of the fitting results.

[0114] Figure 3 Schematically shows a block diagram of an electronic device suitable for implementing the source image contour construction method for laser cutting nesting software described above according to an embodiment of the present application.

[0115] Figure 3 The shown electronic device is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0116] As Figure 3 shown, the electronic device 1000 described in this embodiment includes: a processor 1001, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1002 or the program loaded from the storage section 1008 into the random access memory (RAM) 1003. The processor 1001 may include, for example, a general microprocessor (such as a CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (such as an application specific integrated circuit (ASIC)), and so on. The processor 1001 may also include on-board memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the source image contour construction method process for laser cutting nesting software according to the embodiments of the present application.

[0117] In the RAM 1003, various programs and data required for the operation of the electronic device 1000 are stored. The processor 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. The processor 1001 performs various operations of the source image contour construction method flow for the laser cutting nesting software according to the embodiments of the present application by executing the programs in the ROM 1002 and / or the RAM 1003. It should be noted that the programs may also be stored in one or more memories other than the ROM 1002 and the RAM 1003. The processor 1001 may also perform various operations of the source image contour construction method flow for the laser cutting nesting software according to the embodiments of the present application by executing the programs stored in the one or more memories.

[0118] According to an embodiment of the present application, the electronic device 1000 may further include an input / output (I / O) interface 1005, and the input / output (I / O) interface 1005 is also connected to the bus 1004. The electronic device 1000 may further include one or more of the following components connected to the I / O interface 1005: an input portion 1006 including a keyboard, a mouse, etc.; an output portion 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage portion 1008 including a hard disk, etc.; and a communication portion 1009 including a network interface card such as a LAN card, a modem, etc. The communication portion 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed so that a computer program read therefrom can be installed into the storage portion 1008 as needed.

[0119] The source image contour construction method flow for the laser cutting nesting software according to the embodiments of the present application may be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes program codes for executing the source image contour construction method for the laser cutting nesting software shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 1009, and / or installed from the removable medium 1011. When the computer program is executed by the processor 1001, the above functions defined in the system of the embodiments of the present application are executed. According to an embodiment of the present application, the above-described systems, devices, apparatuses, modules, and / or units, etc. may be implemented by computer program modules.

[0120] Embodiments of the present application further provide a computer-readable storage medium. The computer-readable storage medium may be included in the device / device / system described in the above embodiments, or may exist independently without being assembled into the device / device / system. The above computer-readable storage medium carries one or more programs. When the above one or more programs are executed, the steps of the source image contour construction method for the laser cutting nesting software according to the embodiments of the present application can be implemented.

[0121] According to an embodiment of the present application, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In an embodiment of the present application, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present application, the computer-readable storage medium may include one or more memories other than the ROM 1002 and / or RAM 1003 described above.

[0122] It should be noted that in various embodiments of the present application, each functional module may be integrated in one processing module, or each module may exist physically independently, or two or more modules may be integrated in one module. The above integrated module may be implemented in the form of hardware or in the form of a software functional module. When the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product.

[0123] The flowcharts and / or block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart and / or block diagram may represent a module, a segment of a program, or a portion of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks may occur in an order different from that noted in the accompanying drawings. It should also be noted that each block in the block diagram or flowchart, as well as combinations of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0124] Those skilled in the art will understand that the features recited in the various embodiments and / or claims of the present application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly recited in the present application. In particular, without departing from the spirit and teachings of the present application, the technical features recited in the various embodiments and / or claims of the present application can be combined and / or combined in various ways, and all such combinations and / or combinations fall within the scope of the present application.

[0125] Although the present application has been shown and described with reference to specific exemplary embodiments thereof, those skilled in the art should understand that various changes in form and detail may be made therein without departing from the spirit and scope of the present application as defined by the appended claims and their equivalents. Therefore, the scope of the present application should not be limited to the above embodiments, but should be determined not only by the appended claims, but also by the equivalents of the appended claims.

Claims

1. A method for constructing a source contour for laser cutting nesting software, characterized in that: include: Parse CAD files, extract point set data and do preprocessing; For each preprocessed point set, use the straight line equation to perform straight line fitting and obtain the straight line fitting error; If the straight line fitting error is less than a first preset threshold, selecting the straight line as the fitting curve of the segment; If the straight line fitting error is not less than the first preset threshold, an arc is fitted using a circle equation to obtain an arc fitting error; if the arc fitting error is less than a second preset threshold, an arc is selected as a fitting curve for the segment; If the arc fitting error is not less than the second preset threshold, a quadratic curve is fitted using a quadratic equation to obtain a quadratic curve fitting error; if the quadratic curve fitting error is less than a third preset threshold, a quadratic curve is selected as the fitting curve for the segment; If the quadratic curve fitting error is not less than the third preset threshold, selecting a cubic spline curve as the fitting curve for the segment; After determining the type of each fitting curve, curve fitting is performed to construct the source profile for the laser cutting nesting software.

2. The method for constructing a source contour for laser cutting nesting software according to claim 1, characterized in that: After determining the type of each fitting curve, curve fitting is performed to construct a source profile for laser cutting nesting software, including: Taking one or more of geometric fitting error, curve smoothness, cutting path length and processing efficiency as optimization targets, and constructing a comprehensive objective function based on corresponding target weights; The particle swarm optimization algorithm is used to minimize the comprehensive objective function and obtain the image source contour for laser cutting nesting software.

3. The method for constructing a source contour for laser cutting nesting software according to claim 2, characterized in that: The optimization targets are one or more of geometric fitting error, curve smoothness, cutting path length and processing efficiency, and a comprehensive objective function is constructed based on corresponding objective weights, including: The geometric fitting error E1 is defined as the average square distance from the original point to the corresponding point of the fitting curve, that is, Among them, (x i ,y i ) represents the coordinates of the original points extracted by parsing the CAD file, (x′ i ,y′ i ) represents the coordinates of the corresponding points on the fitting curve; The curve smoothness E2 is measured by the sum of the squares of the curvatures of the uniformly sampled points on the fitting curve, that is, Among them, κ i Represents the curvature of m sampling points; The cutting path length E3 is the total length L of the fitting curve, that is, E3 = L; The processing efficiency E4 takes into account the influence of cutting speed and is defined as Among them, v i Indicates the recommended cutting speed for each segment of the fitting curve; The expression of the comprehensive objective function is E = ∑w i E i , where E i represents the aforementioned optimization objectives, w i Denotes the optimization objective E i The corresponding target weight coefficient.

4. The method for constructing a source contour for laser cutting nesting software according to claim 3, characterized in that: Also includes: The adjacent curve segments of the constructed source contour are processed for continuity to ensure tangent continuity. The relevant formulas include: Wherein, C1′(t) represents the tangent direction of the first curve segment at the connection point t0, and C2′(t) represents the tangent direction of the second curve segment at the connection point t0; represents approaching t0 from the first side, It indicates approaching t0 from a second side opposite to the first side.

5. The method for constructing a source contour for laser cutting nesting software according to claim 3, characterized in that: Also includes: The constructed source contour is optimized by fitting the curve taking into account the tool compensation radius to ensure that the curvature of the cutting path does not exceed the limit that the laser cutting machine can handle. The relevant formulas include: Where C′(t) and C″(t) represent the first-order and second-order derivative vectors of the fitting curve, respectively; K represents the curvature of the cutting path; and r represents the tool compensation radius.

6. The method for constructing a source contour for laser cutting nesting software according to claim 3, characterized in that: Also includes: Perform global path planning on the constructed source contour to minimize the total idle time to improve the overall processing efficiency. The relevant formulas include: D=∑||P i+1 –P i ||; Among them, P i represents the starting point of the i-th cutting path; D represents the total idling distance, and minimizing the total idling time can be achieved by minimizing the total idling distance.

7. The method for constructing a source contour for laser cutting nesting software according to claim 1, characterized in that: The pre-processing comprises: Each continuous point set is smoothed using the moving average method to reduce the impact of noise information.

8. The method for constructing a source contour for laser cutting nesting software according to claim 1, characterized in that: The pre-processing comprises: The Douglas-Peucker algorithm is used to extract key feature points to reduce the amount of data.

9. An electronic device, characterized in that: It includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the computer program is executed by the processing unit, the processing unit is able to execute the steps of the image source contour construction method for laser cutting nesting software as described in any one of claims 1 to 8.

10. A storage medium, characterized in that: It stores a computer program executable by an access authentication device. When the computer program runs on the access authentication device, the access authentication device is enabled to execute the steps of the image source contour construction method for laser cutting nesting software as described in any one of claims 1 to 8.

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