Laser cutting machine track-seeking path planning optimization method and system

Abstract

The present invention discloses a laser cutting machine track-seeking path planning optimization method and system, which relates to the field of laser cutting technology. The laser cutting machine track-seeking path planning optimization method comprises the following steps: analyzing the geometric features of the workpiece to be cut, and planning the initial cutting path of the laser cutting machine in combination with the processing drawing information; optimizing the initial cutting path using a path optimization algorithm to generate a priority cutting path; introducing a cutting head optimization algorithm to control the laser cutting head to avoid repeated cutting areas; analyzing the cutting interference factors that affect the workpiece in the cutting task, and respectively judging the error influence range of each cutting interference factor on the workpiece; based on the error influence range and using an error correction model to correct the error of the laser cutting head in real time. The present invention can more accurately consider the propagation path and characteristics of the laser beam, optimize the cutting path, and thus improve the positioning and tracking accuracy of the laser cutting head.

Description

Technical Field

[0001] The present invention relates to the field of laser cutting technology, and in particular to a laser cutting machine track-finding path planning optimization method and system. Background Art

[0002] Laser cutting machine is a kind of equipment that uses laser beam for cutting processing. It focuses high energy density laser beam on the surface of workpiece, so that local area of ​​workpiece is instantly heated, melted and vaporized, so as to realize the processing of cutting, engraving or marking of workpiece. Laser cutting machine usually includes laser source, optical system, control system and workbench. Laser cutting machine has the advantages of high precision, high speed and applicable to various materials and complex structure processing.

[0003] Path planning optimization can ensure that the laser cutting machine moves along the optimal trajectory during the cutting process, thereby reducing unnecessary idle time and improving production efficiency and productivity. At the same time, path planning optimization can reduce the movement distance and frequency of the laser cutting head and related mechanical components, slow down the mechanical wear rate, and reduce maintenance costs. By carefully planning the path, the laser cutting head can cut in a more precise and stable manner, avoiding unnecessary vibration and swing, thereby improving cutting accuracy and workpiece quality.

[0004] In the process of cutting workpieces using a laser cutting machine, the heat concentration effect is one of the important influencing factors in the laser cutting process. If its influence cannot be analyzed and considered, it may lead to uneven heat distribution during the cutting process, thereby affecting the cutting quality and accuracy, and causing local overheating or excessive thermal stress in the workpiece, thereby causing deformation, warping or even damage to the workpiece.

[0005] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0006] In view of the problems in the related art, the present invention proposes a laser cutting machine track-seeking path planning optimization method and system to overcome the above-mentioned technical problems existing in the existing related art.

[0007] To this end, the specific technical solution adopted by the present invention is as follows:

[0008] According to one aspect of the present invention, a laser cutting machine track-finding path planning optimization method is provided, and the laser cutting machine track-finding path planning optimization method comprises the following steps:

[0009] S1. Analyze the geometric features of the workpiece to be cut, and plan the initial cutting path of the laser cutting machine in combination with the processing drawing information;

[0010] S2, setting the cutting starting point in the initial cutting path as the reference cutting point, and optimizing the initial cutting path using a path optimization algorithm to generate a priority cutting path;

[0011] S3. When the laser cutting machine performs cutting tasks according to the priority cutting path, a cutting head optimization algorithm is introduced to control the laser cutting head to avoid repeated cutting areas;

[0012] S4. Analyze the cutting interference factors that affect the workpiece during the cutting task, and determine the error influence range of each cutting interference factor on the workpiece;

[0013] S5. Based on the error influence range and using the error correction model, the error of the laser cutting head is corrected in real time.

[0014] Preferably, the cutting starting point in the initial cutting path is set as the reference cutting point, and the initial cutting path is optimized using a path optimization algorithm. The generation of the priority cutting path includes the following steps:

[0015] S21, extracting workpiece contour features from the geometric features of the workpiece to be cut, and identifying original boundary corner points in the workpiece contour features;

[0016] S22, generating a minimum envelope rectangle based on the workpiece to be cut around the contour feature of the workpiece, and identifying several corner points in the minimum envelope rectangle;

[0017] S23, comparing the positional relationship between the original boundary corner point and each corner point to determine the cutting coordinates of the laser cutting machine, and taking the cutting starting point as the reference cutting point;

[0018] S24, optimizing the initial cutting path using a tree structure traversal algorithm, generating a priority cutting path, and executing the cutting task according to the priority cutting path;

[0019] S25. Analyze the heat accumulation effect in the cutting task, and adjust the cutting speed and cutting power of the laser cutting machine according to the heat accumulation effect.

[0020] Preferably, optimizing the initial cutting path by using a tree structure traversal algorithm to generate a priority cutting path, and executing the cutting task according to the priority cutting path includes the following steps:

[0021] S241, generating an interactive adjacency table of the current cutting path and the next cutting path of the workpiece based on the cutting coordinates of the laser cutting machine;

[0022] S242, defining a structure array and a cutting path tree function that describe the cutting path tree structure, and at the same time counting the number of sub-paths and corresponding sub-path numbers in the cutting path tree based on the cutting path tree function;

[0023] S243, using a post-order traversal algorithm to generate a cutting path tree sequence and a post-order traversal function, and starting from a reference cutting point in the cutting path tree, traversing the priorities of all sub-paths in the cutting path tree;

[0024] S244, sort and summarize the priorities of all sub-paths, take the sub-path with the highest priority as the priority cutting path, and execute the cutting task according to the priority cutting path.

[0025] Preferably, analyzing the heat accumulation effect in the cutting task and adjusting the cutting speed and cutting power of the laser cutting machine according to the heat accumulation effect comprises the following steps:

[0026] S251, obtaining initial cutting parameters of the laser cutting machine based on each cutting sub-path, and constructing a heat calculation model based on the initial cutting parameters to predict the heat distribution of the workpiece in the cutting task;

[0027] S252, based on the heat distribution of the workpiece, setting the initial cutting parameters of the laser cutting machine as initial cycle variables, and calculating the heat accumulation effect on the workpiece under different cutting parameters;

[0028] S253, determining whether the cutting order on each sub-path matches the preset cutting order, and if not, accumulating the heat accumulation effect of the sub-path and adjacent sub-paths;

[0029] S254, generating optimal cutting parameters of the laser cutting machine according to the accumulated heat concentration effect, and adjusting the initial cutting parameters of the laser cutting machine according to the optimal parameters.

[0030] Preferably, analyzing the cutting interference factors affecting the workpiece in the cutting task and respectively determining the error influence range of each cutting interference factor on the workpiece includes the following steps:

[0031] S41, obtaining and analyzing the cutting interference factors affecting the workpiece in the cutting task, where the cutting interference factors include the cutting starting point, the heat accumulation effect and the priority cutting path;

[0032] S42, analyzing the specific impact mechanism of each identified cutting interference factor on the cutting task, and evaluating the weighted impact degree of each cutting interference factor on the quality of the workpiece after cutting;

[0033] S43. Evaluate the error influence degree and error influence range of each cutting interference factor on the cutting task based on the weight influence degree.

[0034] Preferably, analyzing the specific impact mechanism of each identified cutting interference factor on the cutting task and evaluating the weighted impact degree of each cutting interference factor on the quality of the workpiece after cutting includes the following steps:

[0035] S421, using an association rule mining algorithm to determine weight evaluation indicators related to a cutting starting point, heat accumulation effect, and a priority cutting path;

[0036] S422, constructing an evaluation index system according to the screened weight evaluation indexes;

[0037] S423, based on the evaluation index system, respectively calculating the subjective weight and objective weight of each weight evaluation index, and using the game theory model to generate the combined weight of each weight evaluation index;

[0038] S424. Based on the combined weights of the weight evaluation indicators, a weight evaluation model based on the cloud model is constructed, and the weight evaluation model is used to evaluate the weight influence of the starting point, heat accumulation effect and priority cutting path on the quality of the workpiece after cutting.

[0039] Preferably, based on the error influence range and using the error correction model to correct the error of the laser cutting head in real time includes the following steps:

[0040] S51, obtaining the spatial position and posture of the laser cutting head in the cutting task, performing kinematic calibration on the laser cutting head, and establishing a dynamic stiffness model based on the laser cutting head;

[0041] S52, identifying modal parameters of a dynamic stiffness model of a laser cutting head, and introducing a laser beam tracking model into the dynamic stiffness model;

[0042] S53, detecting whether the laser beam spreading accuracy and dynamic stiffness model of the laser cutting head meet the adaptability of the laser cutting machine;

[0043] S54. If the adaptability requirement is met, kinematic calibration is performed on the laser beams at different postures of the laser cutting head, and static errors caused by cutting interference factors during the kinematic calibration process are analyzed;

[0044] S55, correcting the static error compensation dynamic stiffness model in the kinematic calibration process, and dynamically correcting the error of the laser cutting head in the cutting task according to the error compensation feedback of the dynamic stiffness model.

[0045] Preferably, identifying the modal parameters of the dynamic stiffness model of the laser cutting head and introducing the laser beam tracking model into the dynamic stiffness model comprises the following steps:

[0046] S521, analyzing the modal parameters of the dynamic stiffness model of the laser cutting head using the least square method;

[0047] S522, establishing a laser beam tracking model based on the variation law of the laser beam in the cutting task;

[0048] S523. Based on the analysis results of the modal parameters, a laser beam tracking model is introduced into the dynamic stiffness model to derive the conversion relationship between the deflection vector of the laser beam and the laser cutting head;

[0049] S524, establishing a disturbance coupling relationship between the laser beam tracking model and the dynamic stiffness model component, and optimizing the tracking accuracy of the laser beam tracking model in real time based on the disturbance coupling relationship.

[0050] Preferably, the calculation formula of the subjective weight is:

[0051] ;

[0052] In the formula, Indicates i The subjective weight of each weight evaluation indicator;

[0053] Indicates i Compared with the weight evaluation indicators, j The relative importance of the weighted assessment indicators;

[0054] n Indicates the number of cutting interference factors.

[0055] According to another aspect of the present invention, a laser cutting machine track-seeking path planning and optimization system is also provided, and the laser cutting machine track-seeking path planning and optimization system includes an initial path planning module, a priority path generation module, a cutting head optimization module, an error analysis module and an error correction module:

[0056] The initial path planning module is connected with the priority path generation module, the cutting head optimization module, the error analysis module and the error correction module in sequence;

[0057] The initial path planning module is used to analyze the geometric features of the workpiece to be cut and plan the initial cutting path of the laser cutting machine in combination with the processing drawing information;

[0058] A priority path generation module is used to set the cutting starting point in the initial cutting path as the reference cutting point, and optimize the initial cutting path using a path optimization algorithm to generate a priority cutting path;

[0059] The cutting head optimization module is used to introduce a cutting head optimization algorithm when the laser cutting machine performs cutting tasks according to the priority cutting path, and control the laser cutting head to avoid repeated cutting areas;

[0060] The error analysis module is used to analyze the cutting interference factors that affect the workpiece during the cutting task, and to determine the error influence range of each cutting interference factor on the workpiece;

[0061] The error correction module is used to correct the error of the laser cutting head in real time based on the error influence range and using the error correction model.

[0062] The beneficial effects of the present invention are:

[0063] 1. The present invention helps to determine the starting point of the cutting task by setting the cutting starting point as the reference cutting point, and can optimize the entire cutting path through the path optimization algorithm to ensure cutting in the optimal order, thereby improving production efficiency. The initial cutting path is adjusted by the path optimization algorithm, which helps to reduce unnecessary mechanical movement distance and idle time. At the same time, the workpieces are processed and cut in sequence from simple to complex according to their complexity, thereby reducing the total movement time during the cutting process, thereby making the system more adaptable to various processing requirements and improving the flexibility of the production line.

[0064] 2. The present invention can more accurately describe the dynamic response characteristics of the laser cutting head by identifying the dynamic stiffness model of the laser cutting head, thereby improving the cutting accuracy and ensuring the accuracy during the cutting process. The error correction model introduced can correct the error of the laser cutting head in real time, ensuring that the dynamic adjustment of the cutting path can quickly respond to changes in the actual working state and maintain the stability of the laser cutting head during the cutting process. At the same time, combined with the laser beam tracking model, the propagation path and characteristics of the laser beam are more accurately considered, the cutting path is optimized, and the positioning and tracking accuracy of the laser cutting head is improved.

[0065] 3. The present invention controls heat accumulation by adjusting the cutting speed and power, which can reduce the heat-affected zone and avoid excessive melting, deformation or burning of the material, thereby improving the smoothness of the processed surface and the overall processing quality. Since excessive heat accumulation will cause thermal expansion and thermal deformation in the area around the workpiece, the cutting parameters are appropriately adjusted to control the heat distribution, thereby effectively reducing the thermal deformation phenomenon, maintaining the geometric size and shape accuracy of the workpiece, and increasing the cutting speed without compromising the cutting quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0067] Figure 1 is a flow chart of a laser cutting machine track-seeking path planning optimization method according to an embodiment of the present invention;

[0068] Figure 2It is a principle block diagram of a laser cutting machine track-seeking path planning optimization system according to an embodiment of the present invention.

[0069] In the figure:

[0070] 1. Initial path planning module; 2. Priority path generation module; 3. Cutting head optimization module; 4. Error analysis module; 5. Error correction module. DETAILED DESCRIPTION

[0071] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention and are mainly used to illustrate the embodiments. They can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and advantages of the present invention.

[0072] According to an embodiment of the present invention, a method and system for optimizing tracking path planning of a laser cutting machine are provided.

[0073] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1 As shown, according to the laser cutting machine track-seeking path planning optimization method and system according to an embodiment of the present invention, the laser cutting machine track-seeking path planning optimization method includes the following steps:

[0074] S1. Analyze the geometric features of the workpiece to be cut, and plan the initial cutting path of the laser cutting machine based on the processing drawing information.

[0075] It should be noted that analyzing the geometric features of the workpiece to be cut and planning the initial cutting path of the laser cutting machine in combination with the processing drawing information includes: analyzing the geometric shape of the workpiece to be cut, including geometric features such as external dimensions, hole positions, and edge curves; determining factors such as the material type, thickness, and surface state of the workpiece; obtaining the processing drawing information of the workpiece, including key parameters such as the design size, cutting contour, and hole position of the workpiece; planning the initial cutting path based on the geometric features and processing drawing information, and determining the cutting starting point and cutting direction; optimizing the initial cutting path to improve cutting efficiency and quality, and adjusting the order, spacing, and path density of the cutting path to make the cutting process more stable and efficient.

[0076] S2. Setting the cutting starting point in the initial cutting path as the reference cutting point, and optimizing the initial cutting path using a path optimization algorithm to generate a priority cutting path.

[0077] The cutting starting point in the initial cutting path is set as the reference cutting point, and the initial cutting path is optimized by using the path optimization algorithm. The generation of the priority cutting path includes the following steps:

[0078] S21. Extracting workpiece contour features from the geometric features of the workpiece to be cut, and identifying original boundary corner points in the workpiece contour features.

[0079] It should be noted that extracting the workpiece contour features from the geometric features of the workpiece to be cut and identifying the original boundary corner points in the workpiece contour features include: using image processing to process the image or CAD model of the workpiece to be cut to extract the contour features of the workpiece, specifically, an edge detection algorithm or a contour extraction algorithm can be used; analyzing the extracted workpiece contour features, identifying the straight line segments and curve segments therein, and performing line segment fitting to obtain a simpler contour representation; in the simplified workpiece contour, using a corner point detection algorithm to identify the original boundary corner points, that is, the turning points or corners of the workpiece contour; verifying and screening the identified corner points to eliminate false detections or missed detections caused by image noise or incomplete contours, and verifying according to the distribution of pixels around the corner points, angle changes and other features to ensure that the selected corner points accurately reflect the geometric features of the workpiece contour; using the identified original boundary corner points for subsequent path planning, the corner point information can determine the starting point and turning point of the cutting path, optimize the cutting trajectory, and improve cutting efficiency and accuracy.

[0080] S22, generating a minimum enveloping rectangle based on the workpiece to be cut around the contour feature of the workpiece, and identifying a number of corner points in the minimum enveloping rectangle.

[0081] It should be noted that generating a minimum envelope rectangle based on the workpiece to be cut around the workpiece contour features and identifying several corner points in the minimum envelope rectangle includes: using image processing to process the image or CAD model of the workpiece to be cut to extract the contour features of the workpiece; based on the extracted workpiece contour features, using a greedy algorithm to generate a minimum envelope rectangle, that is, the minimum rectangle that can surround the entire workpiece contour; using a corner point detection algorithm to identify the corner points of the generated minimum envelope rectangle, that is, identifying the four vertices of the rectangle, and verifying the identified corner points to ensure that they belong to the corner points of the workpiece contour rather than noise or false detection.

[0082] S23, comparing the positional relationship between the original boundary corner point and each corner point to determine the cutting coordinates of the laser cutting machine, and taking the cutting starting point as the reference cutting point;

[0083] S24, optimizing the initial cutting path using a tree structure traversal algorithm, generating a priority cutting path, and executing the cutting task according to the priority cutting path.

[0084] Among them, optimizing the initial cutting path by using a tree structure traversal algorithm, generating a priority cutting path, and executing the cutting task according to the priority cutting path includes the following steps:

[0085] S241. Generate an interactive adjacency table between the current cutting path and the next cutting path of the workpiece based on the cutting coordinates of the laser cutting machine.

[0086] It should be noted that generating an interactive adjacency table between the current cutting path and the next cutting path of the workpiece based on the cutting coordinates of the laser cutting machine includes: generating the current cutting path and the next cutting path of the workpiece according to the cutting coordinates and cutting parameters of the laser cutting machine, the cutting path including the cutting start point, the cutting end point and the cutting trajectory; defining a data structure of an adjacency table to represent the adjacency relationship between cutting paths, each cutting path as a node, and the adjacency relationship between nodes represented as edges; taking the current cutting path as the current node and the next cutting path as the adjacent node, establishing an adjacency relationship: determining the edges in the adjacency table according to the relationship between the cutting paths, representing the switching relationship from the current path to the next path; gradually adding nodes and adjacency relationships to the adjacency table according to the generation order of the cutting paths, and using the graph theory algorithm to realize the generation of the adjacency table to ensure that the correct adjacency relationship between the cutting paths is expressed; using the generated adjacency table for path planning and cutting control to help the laser cutting machine achieve automatic cutting and path optimization.

[0087] S242. Define a structure array and a cutting path tree function that describe the cutting path tree structure, and count the number of sub-paths and corresponding sub-path numbers in the cutting path tree based on the cutting path tree function.

[0088] It should be noted that the structure array of the cutting path tree structure and the cutting path tree function include:

[0089] CutPath structure: This structure defines the basic information of the cutting path, including the path number, parent path number, and child path number.

[0090] CutPathTree structure: This structure defines the cutting path tree, including a structure array that stores path information and the number of paths.

[0091] initCutPathTree function: used to initialize the cutting path tree and set the number of paths to 0.

[0092] addCutPath function: used to add a new cutting path to the cutting path tree, including the path number, parent path number and child path number.

[0093] It should be noted that the number of subpaths and corresponding subpath numbers in the cutting path tree based on the cutting path tree function include:

[0094] countChildPaths function: This function accepts a cutting path tree and a parent path number as parameters, then traverses the cutting path tree, counts the number of child paths under the parent path, and prints out the number of each child path.

[0095] Sub-path number counting: The function checks the parent path number of each path by traversing the cut path tree. If it matches the given parent path number, it is treated as a sub-path of the parent path and the number is counted.

[0096] S243, using a post-order traversal algorithm to generate a cutting path tree sequence and a post-order traversal function, and starting from a reference cutting point in the cutting path tree, traversing the priorities of all sub-paths in the cutting path tree.

[0097] It should be noted that the post-order traversal algorithm is used to generate the cutting path tree sequence and the post-order traversal function, and starting from the reference cutting point in the cutting path tree, the priority of traversing all sub-paths in the cutting path tree includes: using the post-order traversal algorithm to traverse the cutting path tree. Post-order traversal is a depth-first search algorithm that traverses a binary tree or tree structure in the order of left subtree-right subtree-root node. The postOrderTraversal function accepts the path number of the cutting path tree and the reference cutting point (root node) as parameters, and traverses the entire cutting path tree through the post-order traversal algorithm, and summarizes the path number of each node at the same time; the function first recursively traverses the left subtree (subpath), and then recursively traverses the right subtree to generate the path number of the root node; starting from the reference cutting point in the cutting path tree, traverse the priority of all sub-paths in the cutting path tree; by calling the post-order traversal function, traverse all sub-paths with the reference cutting point as the starting point, and determine the priority according to the order of post-order traversal.

[0098] S244, sort and summarize the priorities of all sub-paths, take the sub-path with the highest priority as the priority cutting path, and execute the cutting task according to the priority cutting path.

[0099] It should be noted that sorting and summarizing the priorities of all sub-paths, taking the sub-path with the highest priority as the priority cutting path, and executing the cutting task according to the priority cutting path includes: evaluating the priority of each sub-path, and assigning a priority score to each sub-path based on multiple factors of priority evaluation (including cutting complexity, required time, material utilization, size of heat affected zone, etc.); sorting all sub-paths, putting the sub-path with the highest priority score at the front, and arranging them in descending order; planning the actual motion trajectory of the laser cutting machine according to the arranged priorities, considering the optimal path for the laser cutting machine to move from one sub-path to another, so as to reduce non-productive time and improve efficiency; and executing the cutting tasks in sequence according to the prioritized sub-paths, starting with cutting the sub-path with the highest priority, and then proceeding downwards in sequence.

[0100] It should be noted that by evaluating and sorting the sub-paths by priority, the execution order of the cutting task can be effectively planned, thereby optimizing the cutting efficiency, reducing material waste, and improving the quality and production efficiency of the entire cutting task.

[0101] S25. Analyze the heat accumulation effect in the cutting task, and adjust the cutting speed and cutting power of the laser cutting machine according to the heat accumulation effect.

[0102] Among them, analyzing the heat accumulation effect in the cutting task and adjusting the cutting speed and cutting power of the laser cutting machine according to the heat accumulation effect includes the following steps:

[0103] S251, obtaining initial cutting parameters of the laser cutting machine based on each cutting sub-path, and constructing a heat calculation model based on the initial cutting parameters to predict the heat distribution of the workpiece in the cutting task.

[0104] It should be noted that the initial cutting parameters of each cutting sub-path, including laser power, cutting speed, focal length, etc., are obtained through the laser cutting machine control system; based on the initial cutting parameters and the material characteristics of the workpiece, a heat calculation model is constructed to simulate the heat distribution during the laser cutting process; the constructed heat calculation model is used to predict the heat distribution of the workpiece in the cutting task; according to the initial parameters of each cutting sub-path and the geometric characteristics of the workpiece, the heat input and heat dissipation of each point are calculated to obtain the temperature distribution on the surface and inside of the workpiece; the predicted heat distribution is analyzed, and the heat affected zone and deformation that may occur during the cutting process are evaluated.

[0105] S252, based on the heat distribution of the workpiece, setting the initial cutting parameters of the laser cutting machine as initial cycle variables, and calculating the heat accumulation effect on the workpiece under different cutting parameters;

[0106] S253, determining whether the cutting sequence on each sub-path matches the preset cutting sequence, and if not, accumulating the heat accumulation effect of the sub-path and adjacent sub-paths.

[0107] It should be noted that whether the cutting order on each sub-path matches the preset cutting order is determined. If not, the heat accumulation effect of the sub-path and the adjacent sub-path is accumulated, including: obtaining the preset cutting order of each sub-path according to the requirements of the cutting task and the preset optimization algorithm, and comparing the cutting order of each sub-path with the preset cutting order in turn to see if it is consistent; if the cutting order does not match, it means that there is a possibility of adjusting or optimizing the cutting order; for the unmatched sub-path and its adjacent sub-path, the heat accumulation effect is accumulated; according to the accumulated heat accumulation effect, the cutting order is adjusted or optimized to reduce heat accumulation and improve cutting quality.

[0108] S254, generating optimal cutting parameters of the laser cutting machine according to the accumulated heat concentration effect, and adjusting the initial cutting parameters of the laser cutting machine according to the optimal parameters.

[0109] S3. When the laser cutting machine performs cutting tasks according to the priority cutting path, a cutting head optimization algorithm is introduced to control the laser cutting head to avoid repeated cutting areas.

[0110] It should be noted that when the laser cutting machine performs the cutting task according to the priority cutting path, a cutting head optimization algorithm is introduced to control the laser cutting head to avoid the repeated cutting area, including: determining the execution order of each cutting path according to the determined priority cutting path; introducing a heuristic search algorithm, such as an A* algorithm or a genetic algorithm, to optimize the movement path of the cutting head; searching for the optimal movement path of the cutting head according to a preset objective function, such as minimizing the total length of the cutting path or minimizing the repeated cutting area, and adjusting the movement path of the cutting head according to the results of the heuristic search algorithm to avoid the repeated cutting area; using machine vision to monitor the workpiece condition during the cutting process in real time to assist in optimizing the position of the cutting head; during the cutting process, the cutting area is monitored in real time to detect whether there is repeated cutting, and the movement path of the cutting head is adjusted according to the detection results of the repeated cutting area to ensure that the repeated cutting area is avoided during the cutting process.

[0111] S4. Analyze the cutting interference factors that affect the workpiece during the cutting task, and determine the error influence range of each cutting interference factor on the workpiece.

[0112] Among them, analyzing the cutting interference factors affecting the workpiece in the cutting task and respectively determining the error influence range of each cutting interference factor on the workpiece includes the following steps:

[0113] S41, obtaining and analyzing the cutting interference factors affecting the workpiece in the cutting task, where the cutting interference factors include the cutting starting point, the heat accumulation effect and the priority cutting path;

[0114] S42. Analyze the specific impact mechanism of each identified cutting interference factor on the cutting task, and evaluate the weighted impact degree of each cutting interference factor on the quality of the workpiece after cutting.

[0115] Among them, analyzing the specific impact mechanism of each identified cutting interference factor on the cutting task and evaluating the weighted impact degree of each cutting interference factor on the quality of the workpiece after cutting includes the following steps:

[0116] S421. Determine weight evaluation indicators corresponding to the cutting starting point, heat accumulation effect and priority cutting path using an association rule mining algorithm.

[0117] It should be noted that the use of association rule mining algorithm to determine the weight evaluation indicators corresponding to the cutting starting point, heat accumulation effect and priority cutting path includes: collecting relevant data including the cutting starting point, heat accumulation effect, and priority cutting path, and using the Apriori algorithm to mine frequent item sets and association rules from large-scale data to help understand the relationship between data; preprocessing the collected data, including data cleaning, deduplication, normalization and other operations, to improve the effect of association rule mining; using the Apriori algorithm to find the association rules between the cutting starting point, heat accumulation effect and priority cutting path, determine the thresholds of support and confidence, and filter out frequent item sets and rules with certain correlation; analyzing the association rules obtained by mining, explaining the relationship between different items, and finding rules related to the cutting starting point, heat accumulation effect, and priority cutting path; extracting weight evaluation indicators from these rules, and the weight evaluation indicators include confidence, lift and other indicators, which are used to evaluate the influence of different factors on the cutting process.

[0118] S422, constructing an evaluation index system according to the screened weight evaluation indexes;

[0119] S423. Based on the evaluation index system, the subjective weight and objective weight of each weight evaluation index are calculated respectively, and the combined weight of each weight evaluation index is generated by combining the game theory model.

[0120] It should be noted that based on the evaluation index system, the subjective weight and objective weight of each weight evaluation index are calculated respectively, and the game theory model is used to generate the combined weight of each weight evaluation index, including: collecting relevant subjective views and importance evaluations of each evaluation index through expert interviews or questionnaires; conducting statistical analysis on the collected subjective evaluations to calculate the subjective weight and objective weight of each weight evaluation index; regarding each weight evaluation index as a different stakeholder participating in the game, and using the game theory model to combine the weights; under the framework of the game theory model, determining the combined weight of each weight evaluation index through the game process.

[0121] The calculation formula of subjective weight is:

[0122] ;

[0123] In the formula, Indicates i The subjective weight of each weight evaluation indicator;

[0124] Indicates i Compared with the weight evaluation indicators, j The relative importance of the weighted assessment indicators;

[0125] n Indicates the number of cutting interference factors.

[0126] S424. Based on the combined weights of the weight evaluation indicators, a weight evaluation model based on the cloud model is constructed, and the weight evaluation model is used to evaluate the weight influence of the starting point, heat accumulation effect and priority cutting path on the quality of the workpiece after cutting.

[0127] S43. Evaluate the error influence degree and error influence range of each cutting interference factor on the cutting task based on the weight influence degree.

[0128] S5. Based on the error influence range and using the error correction model, the error of the laser cutting head is corrected in real time.

[0129] Among them, based on the error influence range and using the error correction model to correct the error of the laser cutting head in real time includes the following steps:

[0130] S51. Acquire the spatial position and posture of the laser cutting head in the cutting task, perform kinematic calibration on the laser cutting head, and establish a dynamic stiffness model based on the laser cutting head.

[0131] It should be noted that the spatial position and posture of the laser cutting head in the cutting task are obtained, and the laser cutting head is kinematically calibrated to establish a dynamic stiffness model based on the laser cutting head, including: using sensors or visual systems to monitor the position and posture of the laser cutting head in the workspace in real time; kinematically calibrating the laser cutting head to determine the exact relationship between it and the laser cutting machine; establishing a dynamic stiffness model based on the spatial position and posture information of the laser cutting head and the kinematic calibration results; obtaining the dynamic response data of the laser cutting head under different working conditions, so as to establish an accurate dynamic stiffness model.

[0132] S52, identifying modal parameters of a dynamic stiffness model of the laser cutting head, and introducing a laser beam tracking model into the dynamic stiffness model.

[0133] The steps of identifying the modal parameters of the dynamic stiffness model of the laser cutting head and introducing the laser beam tracking model into the dynamic stiffness model include the following steps:

[0134] S521, analyzing the modal parameters of the dynamic stiffness model of the laser cutting head using the least square method;

[0135] S522, establishing a laser beam tracking model based on the variation law of the laser beam in the cutting task;

[0136] S523. Based on the analysis results of the modal parameters, a laser beam tracking model is introduced into the dynamic stiffness model to derive the conversion relationship between the deflection vector of the laser beam and the laser cutting head;

[0137] S524, establishing a disturbance coupling relationship between the laser beam tracking model and the dynamic stiffness model component, and optimizing the tracking accuracy of the laser beam tracking model in real time based on the disturbance coupling relationship.

[0138] It should be noted that establishing a disturbance coupling relationship between the laser beam tracking model and the dynamic stiffness model, and optimizing the tracking accuracy of the laser beam tracking model in real time based on the disturbance coupling relationship includes: coupling the laser beam tracking model and the dynamic stiffness model to analyze the mutual influence relationship between the two; considering the disturbance effect of the mechanical structure response in the dynamic stiffness model on the laser beam, and the influence of the laser beam tracking accuracy on the dynamic stiffness model, to establish a coupling relationship model between the two; analyzing the influence degree and characteristics of different types of disturbances on the laser beam tracking model and the dynamic stiffness model, including the influence of mechanical vibration, ambient temperature change, workpiece deformation and other factors on the laser beam tracking accuracy and dynamic stiffness; based on the coupling relationship model, designing a real-time optimization algorithm for real-time adjustment of the parameters of the laser beam tracking model to improve the tracking accuracy and suppress the disturbance effect; according to the monitoring results, adjusting the parameters of the laser beam tracking model in real time to optimize its tracking accuracy, and adjusting the cutting process according to the state of the dynamic stiffness model.

[0139] S53, detecting whether the laser beam spreading accuracy and dynamic stiffness model of the laser cutting head meet the adaptability of the laser cutting machine;

[0140] S54. If the adaptability requirement is met, kinematic calibration is performed on the laser beams at different postures of the laser cutting head, and static errors caused by cutting interference factors during the kinematic calibration process are analyzed;

[0141] S55, correcting the static error compensation dynamic stiffness model in the kinematic calibration process, and dynamically correcting the error of the laser cutting head in the cutting task according to the error compensation feedback of the dynamic stiffness model.

[0142] It should be noted that the static error compensation dynamic stiffness model in the process of correcting the kinematic calibration, and dynamically correcting the error of the laser cutting head in the cutting task based on the error compensation feedback of the dynamic stiffness model include: correcting the static error by correcting the structural parameters of the laser cutting machine, adjusting the sensor position or adding calibration points, and updating the parameters in the dynamic stiffness model according to the corrected kinematic calibration results to reflect the actual mechanical system response characteristics; designing an error compensation feedback mechanism to provide real-time feedback to the control system based on the error information in the dynamic stiffness model; using a closed-loop control strategy to monitor the error situation in the actual cutting process, and feeding the error information back to the control system for real-time adjustment and compensation; dynamically adjusting the position and posture of the laser cutting head based on the error compensation feedback to reduce the error and improve the cutting accuracy.

[0143] According to another embodiment of the present invention, Figure 2 As shown, a laser cutting machine track-seeking path planning and optimization system is also provided, and the laser cutting machine track-seeking path planning and optimization system includes an initial path planning module 1, a priority path generation module 2, a cutting head optimization module 3, an error analysis module 4 and an error correction module 5:

[0144] The initial path planning module 1 is connected to the priority path generation module 2, the cutting head optimization module 3, the error analysis module 4 and the error correction module 5 in sequence;

[0145] The initial path planning module 1 is used to analyze the geometric features of the workpiece to be cut and plan the initial cutting path of the laser cutting machine in combination with the processing drawing information;

[0146] The priority path generation module 2 is used to set the cutting starting point in the initial cutting path as the reference cutting point, and optimize the initial cutting path using a path optimization algorithm to generate a priority cutting path;

[0147] The cutting head optimization module 3 is used to introduce a cutting head optimization algorithm when the laser cutting machine performs a cutting task according to a priority cutting path, and control the laser cutting head to avoid repeated cutting areas;

[0148] The error analysis module 4 is used to analyze the cutting interference factors that affect the workpiece during the cutting task, and to determine the error influence range of each cutting interference factor on the workpiece;

[0149] The error correction module 5 is used to correct the error of the laser cutting head in real time based on the error influence range and using the error correction model.

[0150] To sum up, with the help of the above-mentioned technical scheme of the present invention, the present invention helps to determine the starting point of the cutting task by setting the cutting starting point as the reference cutting point, and can optimize the entire cutting path through the path optimization algorithm to ensure cutting in the optimal order, thereby improving production efficiency, and using the path optimization algorithm to adjust the initial cutting path, which helps to reduce unnecessary mechanical movement distance and idle time. At the same time, according to the complexity of the workpiece, the workpiece is processed and cut in sequence from simple to complex, thereby reducing the total movement time in the cutting process, thereby making the system more adaptable to various processing needs and improving the flexibility of the production line; the present invention can more accurately describe the dynamic response characteristics of the laser cutting head by identifying the dynamic stiffness model of the laser cutting head, thereby improving the cutting accuracy and ensuring the accuracy of the cutting process, and the introduction of the error correction model can The error of the laser cutting head is corrected in real time to ensure that the dynamic adjustment of the cutting path can quickly respond to changes in the actual working state and maintain the stability of the laser cutting head during the cutting process. At the same time, combined with the laser beam tracking model, the propagation path and characteristics of the laser beam are more accurately considered to optimize the cutting path, thereby improving the positioning and tracking accuracy of the laser cutting head; the present invention controls the accumulation of heat by adjusting the cutting speed and power, which can reduce the heat-affected zone and avoid excessive melting, deformation or burning of the material, thereby improving the smoothness of the processed surface and the overall processing quality. Since excessive heat accumulation will cause thermal expansion and thermal deformation in the area surrounding the workpiece, the cutting parameters are appropriately adjusted to control the heat distribution, thereby effectively reducing the thermal deformation phenomenon, maintaining the geometric size and shape accuracy of the workpiece, and improving the cutting speed without compromising the cutting quality.

[0151] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A laser cutting machine track-seeking path planning optimization method, characterized in that: The method comprises the following steps: S1. Analyze the geometric features of the workpiece to be cut, and plan the initial cutting path of the laser cutting machine in combination with the processing drawing information; S2, setting the cutting starting point in the initial cutting path as the reference cutting point, and optimizing the initial cutting path using a path optimization algorithm to generate a priority cutting path; S3. When the laser cutting machine performs cutting tasks according to the priority cutting path, a cutting head optimization algorithm is introduced to control the laser cutting head to avoid repeated cutting areas; S4. Analyze the cutting interference factors that affect the workpiece during the cutting task, and determine the error influence range of each cutting interference factor on the workpiece; S5. Based on the error influence range and using the error correction model, the error of the laser cutting head is corrected in real time; The S4 comprises the following steps: S41, obtaining and analyzing cutting interference factors affecting the workpiece in the cutting task, wherein the cutting interference factors include a cutting starting point, a heat accumulation effect, and a priority cutting path; S42, analyzing the specific impact mechanism of each identified cutting interference factor on the cutting task, and evaluating the weighted impact degree of each cutting interference factor on the quality of the workpiece after cutting; S43, evaluating the error influence degree and error influence range of each cutting interference factor on the cutting task based on the weight influence degree; The S42 comprises the following steps: S421, using an association rule mining algorithm to determine weight evaluation indicators related to a cutting starting point, heat accumulation effect, and a priority cutting path; S422, constructing an evaluation index system according to the screened weight evaluation indexes; S423, based on the evaluation index system, respectively calculating the subjective weight and objective weight of each weight evaluation index, and using the game theory model to generate the combined weight of each weight evaluation index; S424. Based on the combined weights of the weight evaluation indicators, a weight evaluation model based on the cloud model is constructed, and the weight evaluation model is used to evaluate the weight influence of the starting point, heat accumulation effect and priority cutting path on the quality of the workpiece after cutting.

2. A laser cutting machine track-seeking path planning optimization method according to claim 1, characterized in that: The step of setting the cutting starting point in the initial cutting path as the reference cutting point and optimizing the initial cutting path using a path optimization algorithm to generate a priority cutting path includes the following steps: S21, extracting workpiece contour features from the geometric features of the workpiece to be cut, and identifying original boundary corner points in the workpiece contour features; S22, generating a minimum envelope rectangle based on the workpiece to be cut around the contour feature of the workpiece, and identifying several corner points in the minimum envelope rectangle; S23, comparing the positional relationship between the original boundary corner point and each corner point to determine the cutting coordinates of the laser cutting machine, and taking the cutting starting point as the reference cutting point; S24, optimizing the initial cutting path using a tree structure traversal algorithm, generating a priority cutting path, and executing the cutting task according to the priority cutting path; S25. Analyze the heat accumulation effect in the cutting task, and adjust the cutting speed and cutting power of the laser cutting machine according to the heat accumulation effect.

3. A laser cutting machine track-seeking path planning optimization method according to claim 2, characterized in that: The method of optimizing the initial cutting path by using a tree structure traversal algorithm, generating a priority cutting path, and executing the cutting task according to the priority cutting path includes the following steps: S241, generating an interactive adjacency table of the current cutting path and the next cutting path of the workpiece based on the cutting coordinates of the laser cutting machine; S242, defining a structure array and a cutting path tree function that describe the cutting path tree structure, and at the same time counting the number of sub-paths and corresponding sub-path numbers in the cutting path tree based on the cutting path tree function; S243, using a post-order traversal algorithm to generate a cutting path tree sequence and a post-order traversal function, and starting from a reference cutting point in the cutting path tree, traversing the priorities of all sub-paths in the cutting path tree; S244, sort and summarize the priorities of all sub-paths, take the sub-path with the highest priority as the priority cutting path, and execute the cutting task according to the priority cutting path.

4. A laser cutting machine track-seeking path planning optimization method according to claim 3, characterized in that: The analyzing the heat accumulation effect in the cutting task and adjusting the cutting speed and cutting power of the laser cutting machine according to the heat accumulation effect comprises the following steps: S251, obtaining initial cutting parameters of the laser cutting machine based on each cutting sub-path, and constructing a heat calculation model based on the initial cutting parameters to predict the heat distribution of the workpiece in the cutting task; S252, based on the heat distribution of the workpiece, setting the initial cutting parameters of the laser cutting machine as initial cycle variables, and calculating the heat accumulation effect on the workpiece under different cutting parameters; S253, determining whether the cutting order on each sub-path matches the preset cutting order, and if not, accumulating the heat accumulation effect of the sub-path and adjacent sub-paths; S254, generating optimal cutting parameters of the laser cutting machine according to the accumulated heat concentration effect, and adjusting the initial cutting parameters of the laser cutting machine according to the optimal parameters.

5. A laser cutting machine track-seeking path planning optimization method according to claim 4, characterized in that: The method of correcting the error of the laser cutting head in real time based on the error influence range and using the error correction model includes the following steps: S51, obtaining the spatial position and posture of the laser cutting head in the cutting task, performing kinematic calibration on the laser cutting head, and establishing a dynamic stiffness model based on the laser cutting head; S52, identifying modal parameters of a dynamic stiffness model of a laser cutting head, and introducing a laser beam tracking model into the dynamic stiffness model; S53, detecting whether the laser beam spreading accuracy and dynamic stiffness model of the laser cutting head meet the adaptability of the laser cutting machine; S54. If the adaptability requirement is met, kinematic calibration is performed on the laser beams at different postures of the laser cutting head, and static errors caused by cutting interference factors during the kinematic calibration process are analyzed; S55, correcting the static error compensation dynamic stiffness model in the kinematic calibration process, and dynamically correcting the error of the laser cutting head in the cutting task according to the error compensation feedback of the dynamic stiffness model.

6. A laser cutting machine track-seeking path planning optimization method according to claim 5, characterized in that: The method of identifying the modal parameters of the dynamic stiffness model of the laser cutting head and introducing the laser beam tracking model into the dynamic stiffness model comprises the following steps: S521, analyzing the modal parameters of the dynamic stiffness model of the laser cutting head using the least square method; S522, establishing a laser beam tracking model based on the variation law of the laser beam in the cutting task; S523. Based on the analysis results of the modal parameters, a laser beam tracking model is introduced into the dynamic stiffness model to derive the conversion relationship between the deflection vector of the laser beam and the laser cutting head; S524, establishing a disturbance coupling relationship between the laser beam tracking model and the dynamic stiffness model component, and optimizing the tracking accuracy of the laser beam tracking model in real time based on the disturbance coupling relationship.

7. A laser cutting machine track-seeking path planning optimization method according to claim 6, characterized in that: The calculation formula of the subjective weight is: Where W c (i) represents the subjective weight of the i-th weight evaluation indicator; b ij Indicates the relative importance of the jth weight evaluation indicator compared to the i-th weight evaluation indicator; n represents the number of cutting interference factors.

8. A laser cutting machine track-seeking path planning optimization system, used to implement the laser cutting machine track-seeking path planning optimization method according to any one of claims 1 to 7, characterized in that: The laser cutting machine track-seeking path planning and optimization system includes an initial path planning module, a priority path generation module, a cutting head optimization module, an error analysis module and an error correction module: The initial path planning module is respectively connected with the priority path generation module, the cutting head optimization module, the error analysis module and the error correction module in sequence; The initial path planning module is used to analyze the geometric features of the workpiece to be cut and plan the initial cutting path of the laser cutting machine in combination with the processing drawing information; The priority path generation module is used to set the cutting starting point in the initial cutting path as the reference cutting point, and optimize the initial cutting path using a path optimization algorithm to generate a priority cutting path; The cutting head optimization module is used to introduce a cutting head optimization algorithm when the laser cutting machine performs a cutting task according to a priority cutting path, and control the laser cutting head to avoid repeated cutting areas; The error analysis module is used to analyze the cutting interference factors that affect the workpiece during the cutting task, and to determine the error influence range of each cutting interference factor on the workpiece; The error correction module is used to correct the error of the laser cutting head in real time based on the error influence range and using the error correction model.

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