26 results about "Cutting sequence" patented technology

The invention discloses a metal plate laser cutting control method, and relates to the technical field of laser cutting, material parameters, thickness information and cutting path data are obtained, a mixed enveloping rectangle algorithm is combined with a genetic algorithm to optimize a cutting sequence, and a path sequence containing idle stroke avoidance and nested graph priority is generated; constructing a laser parameter prediction model based on the material, thickness and path characteristics, and dynamically adjusting the power gradient; the slag splashing state is judged through data fusion of a capacitive sensor and an encoder, a quality feedback signal is extracted in combination with machine vision, and laser parameters are dynamically adjusted through a fuzzy control algorithm; wavefront distortion is monitored in real time, the correction frequency is adjusted according to the slag splashing state, and a deformable mirror is used for compensating the phase; when the quality is abnormal, historical parameter combinations are retrieved through a cosine similarity algorithm for joint compensation. According to the method, the path cutting efficiency is improved, and the problems of low efficiency of path planning and parameter adjustment lagging in the prior art are solved.

The invention relates to a cutting path generation system based on visual positioning, cutting equipment and a cutting method. The system comprises a scanning camera control module, an image acquisition and recognition module, an image processing module, a cutting path planning module and a cutting control module. According to the system, by combining a Laplace algorithm and an LBP and GLCM texture extraction technology, the boundary recognition problem under the condition that a pattern and a background are in the same color or low contrast is solved; the path smoothness and the cutting quality are improved by adopting contour optimization and curvature compensation algorithms, the cutting sequence is optimized by combining weighting functions of the area, complexity and overlapping degree, and material deformation is reduced. And motor driving is dynamically adjusted through PID control, and stable control over the speed of the tool bit is achieved. The method has the advantages of being high in recognition precision, high in adaptability, intelligent in path planning and stable in cutting process, the automatic cutting efficiency and the finished product quality of complex patterns or same-color materials are remarkably improved, and the overall cutting precision fluctuation is controlled within + / -2%.

The invention discloses a maritime work steel plate intelligent cutting path planning method based on multi-objective optimization, and belongs to the field of maritime work steel plate intelligent cutting path planning, the method comprises the following steps: collecting cutting damage data of maritime work steel plates of different materials and thicknesses, constructing a process damage feature library, and combining internal damage analysis to perfect data dimensions, so as to obtain a process damage feature library; and finally establishing a damage prediction model by using a machine learning algorithm. A comprehensive objective function containing the material utilization rate, the cutting efficiency and damage avoidance is constructed, initial layout and path planning of parts are conducted, and cutting of the first part is executed after an initial cutting sequence and track are generated; by collecting damage data to establish a prediction model, constructing a comprehensive objective function to plan an initial path, optimizing a subsequent path in combination with a damage thermodynamic diagram, and establishing an adaptive rule base to adjust parameters, intelligent planning of a cutting path is realized, and the qualified rate of parts and the production efficiency are improved.

The invention relates to the field of data prediction, and provides a method and a system for acquiring a cutting sequence of panel-type customized furniture based on a hybrid strategy. The method comprises the following steps: grouping furniture plates in a plurality of orders to be processed according to plate designs and colors to obtain a plurality of design and color groups; based on the number of the to-be-processed orders associated with the pattern groups and the occurrence frequency of the cross-pattern to-be-processed orders, performing initial arrangement on each pattern group to obtain an initial pattern group sequence; in each design and color group, according to the order coverage rate and the position sensitivity of each furniture plate, performing initial arrangement on each furniture plate to obtain a plate sequence in an initial group; dynamically optimizing the position of each flower color group in the initial flower color group sequence by adopting an adjacency exchange method, and performing secondary optimization on an adjacency exchange result; dynamically optimizing the position of each furniture plate in the plate sequence in the initial group on the basis of an adjacent exchange method through a tabu search algorithm; and building a furniture plate cutting sequence, and starting a production process of the plurality of orders to be processed.

The invention relates to the technical field of switch cabinet production, and particularly discloses a switch cabinet body plate laser cutting method, device and equipment and a medium, and the method comprises the steps that a three-dimensional design model and a two-dimensional expansion drawing of a target switch cabinet body are obtained; identifying the three-dimensional design model and extracting machining features about the cutting process; predicting the cutting deformation of the cabinet plate; according to the predicted cutting deformation, the offset of the machining features on the two-dimensional expansion graph is deduced reversely; generating a two-dimensional cutting map containing the compensated processing features; a cutting deviation factor is analyzed based on the two-dimensional cutting graph, a cutting sequence and a cutting forming path are optimized based on the cutting deviation factor, and a cutting strategy is generated; according to the method, a reliable reverse calculation mechanism is provided to compensate dimensional deviation caused by a forming process, accurate association of feature positions is ensured, and the laser cutting precision and the overall manufacturing quality of the switch cabinet body plate are remarkably improved.

The invention discloses a laser cutting path optimization method of laser cutting equipment, and relates to the technical field of cutting path optimization. According to the laser cutting path optimization method of the laser cutting equipment, geometric primitive data of a to-be-cut workpiece is obtained, contour analysis processing is carried out, and a contour geometric data set of the to-be-cut workpiece is extracted; cutting sequence planning processing is conducted on the contour geometric data set of the to-be-cut workpiece based on a genetic algorithm, and an initial cutting path of the to-be-cut workpiece is generated; multi-target collaborative optimization processing is conducted on the initial cutting path of the to-be-cut workpiece, and the optimized cutting path of the to-be-cut workpiece is obtained.According to the method, the optimized cutting path of the to-be-cut workpiece is verified, the optimized verification cutting path of the to-be-cut workpiece is generated, and therefore the machining efficiency is remarkably improved while the machining precision is guaranteed; therefore, the reliability of the cutting process is comprehensively improved.

The present invention belongs to the technical field related to path optimization, and discloses a collision-avoiding laser cutting path optimization method and system based on a potential field ant colony algorithm. The method comprises the following steps: Step 1: formulating an initial cutting sequence for parts with the goal of minimizing tool movement distance; the initial cutting sequence is obtained by solving a traveling salesman problem using an ant colony algorithm; Step 2: optimizing the cutting sequence using a potential field ant colony algorithm to obtain an optimal path based on collision-avoiding constraints; wherein the potential field ant colony algorithm adds an attraction factor and a repulsion factor based on an artificial potential field method to improve the potential field ant colony algorithm heuristic function. The present invention achieves collision-avoiding optimization by using gravity to guide path search and repulsion to eliminate obstacles, thereby reducing the number of paths passing through the cut area, increasing laser cutting speed, and completing the entire planning of the part cutting path while ensuring cutting quality, thereby improving processing efficiency.

A system for generating G-code for controlling operation of a laser cutting machine to cut parts from a sheet of material tests parts for potential distortion and generates G-code that avoids potential distortion upon receiving cutting data specifying a cutting order of the parts and a cutting order of edges of the individual parts. To test a current part, the system detects potential distortion when a final edge of the current part is adjacent to an edge of a previously cut part that was cut before the current part according to the cutting order of the parts. The system modifies the cutting order to select a modified cutting order in which the final edge is not adjacent to any edge of any previously cut part.

The present invention relates to a planning method for generating control data comprising a cut surface (10) with a cap cut (20), a side cut (30), a lenticular cut (40) and an access cut (50) for correcting the refraction of an eye (70). The problem addressed by the present invention is that of providing a method and a device for generating control data for correcting the refraction of an eye (70), which reduces the risk of occurrence of dysfunction due to distortions in the cornea (80). The problem is solved by a planning method which generates control data representing a sequence plan in which an outer cap cut (22) is made before the side cut (30), the side cut (30) is made before the lenticular cut (40), and the lenticular cut (40) is made before an inner cap cut (24). The problem is further solved by a corresponding planning unit (P), an ophthalmological laser therapy device (100) and by a computer program product.

The invention discloses a path planning method and system for processing a rigid-flex circuit board thin plate, relates to the field of circuit board path planning, and abandons the limitation that traditional CAM software only takes the shortest geometric path as a target, and constructs a stress field matrix reflecting thermal mismatch in a board by using a finite element analysis technology. Discretization processing and virtual cutting simulation are carried out on the cutting contour, and the stress release potential when each road section is cut off is quantified. On this basis, a stress gradient descent algorithm is adopted to reconstruct a processing time sequence: a low-risk path of which the stress release potential is lower than a safety threshold is executed preferentially so as to realize step-by-step stable release of internal energy of the plate; and reserving the path which is judged to be high in risk as a connection point, and optimizing a final cutting sequence according to symmetry and residual stress distribution. Therefore, violent springback and machining defects at the moment of product separation are effectively avoided, and the machining quality of high-precision plates is guaranteed.

This invention relates to the field of cutting path optimization, addressing the problem of excessive heat concentration leading to part damage or reduced cutting accuracy during laser cutting due to dense cutting paths. Specifically, it is a machine vision-based 3D automotive dashboard laser cutting path optimization method. When generating the cutting path, this invention considers the part to be cut in three dimensions, employing different cutting control strategies for three-dimensional and planar regions to ensure cutting quality. Simultaneously, it uses a binary progressive method to more comprehensively analyze the existence of minute local path densities and arranges the cutting sequence according to the concentration of the cutting path distribution. Sufficient heat dissipation time is reserved during the cutting process. Furthermore, during cutting path generation, a linkage analysis is performed based on the interaction between the material clamping parts and the cutting path to prioritize the cutting of interactive parts, reducing the impact of clamping stability decay on cutting accuracy during the cutting process.

The invention relates to the technical field of intelligent welding systems, and provides a low-thermal-stress laser precision cutting process suitable for thin-wall hardware, which comprises the following steps: establishing a three-dimensional model of the thin-wall hardware, and extracting a cutting path of each cutting area of the three-dimensional model; evaluating the sensitive degree of the cutting area to thermal stress, and constructing the heat capacity rigidity ratio of the cutting area; evaluating the significance degree of the thermal interaction influence of the cut area on the cut area, and constructing the accumulated heat conduction influence degree of the cut area; and deformation factors of the cutting areas are determined, the cutting sequence of all the cutting areas of the thin-wall hardware is determined in combination with the heat capacity rigidity ratio, and laser precision cutting of the thin-wall hardware is completed according to the cutting sequence. The method aims at determining the cutting sequence of the thin-wall hardware, and plastic deformation, caused by the heat accumulation effect, of the thin-wall hardware in the cutting process is avoided.

This invention relates to a vision-based cutting path generation system, cutting equipment, and cutting method. The system includes a scanning camera control module, an image acquisition and recognition module, an image processing module, a cutting path planning module, and a cutting control module. The system addresses boundary recognition issues when patterns and backgrounds are of the same color or have low contrast by combining Laplacian algorithm, LBP, and GLCM texture extraction techniques. It employs contour optimization and curvature compensation algorithms to improve path smoothness and cutting quality, and optimizes the cutting sequence using a weighted function of area, complexity, and overlap to reduce material deformation. PID control dynamically adjusts the motor drive to achieve stable cutter speed control. This invention offers advantages such as high recognition accuracy, strong adaptability, intelligent path planning, and stable cutting process, significantly improving the automatic cutting efficiency and finished product quality of complex patterns or materials of the same color, with overall cutting accuracy fluctuations controlled within ±2%.

The invention discloses a contour cutting track determination method and device, equipment and a storage medium. According to the scheme, the contours in the original image can be divided into different sub-regions according to the positions of the center points of the contours, then the target contour sequences of the different sub-regions are determined again according to the target cutting sequence mode, in this way, it can be ensured that the contours are cut in order according to the target cutting sequence mode, and the contour cutting efficiency is improved. Moreover, after the target contour sequence is determined, the cutter starting point coordinates of all the contours need to be re-determined according to the radius of the cutting tool, so that the distance between the cutter starting point coordinates of every two adjacent contours is shortened, the tool idle running time during contour cutting is shortened, and the contour cutting efficiency and quality are improved.

The invention discloses a generalized traveling salesman cutting path planning method and device based on reinforcement learning. The generalized traveling salesman cutting path planning method comprises the steps that a target layout drawing containing a plurality of part graphs is obtained; extracting a node set formed by all parts and cluster information corresponding to the node set; a cutting path planning problem is converted into a generalized travel salesman problem GTSP solving operation, an environment simulation model is constructed, node information of all parts and cluster information of corresponding nodes are input, and current state information is obtained; according to the current state information, the output strategy of the trained strategy model is input into the environment simulation model to obtain new state information, all part nodes are traversed until the optimal machining sequence result of the cutting sequence of all parts is obtained, a comprehensive path planning scheme is synthesized, and the whole cutting efficiency is greatly improved.

The application discloses a kind of intelligent cutting path planning method of offshore steel plate based on multi-objective optimization, belongs to the field of intelligent cutting path planning of offshore steel plate, this method includes the following steps: collecting the cutting damage data of different material, thickness offshore steel plate, constructing process damage feature library, and combining internal damage analysis to improve data dimension, finally using machine learning algorithm to establish damage prediction model;Build the comprehensive objective function containing material utilization, cutting efficiency, damage avoidance, perform the first part cutting after generating preliminary cutting sequence and trajectory of part initial layout and path planning;The application establishes prediction model by collecting damage data, builds comprehensive objective function to plan initial path, optimizes subsequent path in combination with damage thermogram, establishes adaptive rule base to adjust parameters, realizes intelligent planning of cutting path, improves part qualified rate and production efficiency.

The present disclosure relates to a system for optimizing a process path for metal processing based on artificial intelligence. According to the present disclosure, a method of operation for a process path optimization device receives input data including drawing data, material information, and thickness information of a metal to be processed, stores cutting history data including cutting sequences, movement paths, time required, and thermal deformation error data by material and thickness of previously performed cutting processes, performs reinforcement learning based on the input data and the cutting history data to calculate an optimal cutting sequence and entry path that minimizes the rapid traverse time of a processing head and disperses local heat accumulation of the metal to be processed, and converts the calculated optimal cutting sequence and entry path into a numerical control (NC) code and transmits it to a cutting device.

The invention discloses a cutting bed path optimization method based on global clustering window division, and belongs to the technical field of cutting bed path optimization, and the method comprises the steps: calculating the barycentric coordinate and area of each cutting piece according to the coordinate point set of each cutting piece in a to-be-cut order, and the average value of the areas of all cutting pieces; small pieces are screened out, and an initial global path is generated by adopting a nearest neighbor greedy algorithm; calculating a distance sequence according to the initial global path; performing jump detection on the distance sequence to obtain all path jump points, and dividing the initial global path into a plurality of path sub-segments; based on all the path sub-segments, dividing all the cutting pieces by adopting a global clustering window; establishing a target function of each clustering clipping block, and solving by adopting a variable neighborhood search algorithm to obtain an optimal cutting sequence of the corresponding clustering clipping blocks; and splicing the optimal cutting sequence of all the clustering cutting blocks to construct an optimal global path as a cutting bed path optimization result. The method is beneficial for improving the processing efficiency and the processing precision of the cut-parts.

The invention discloses a three-dimensional model cutting method, device and equipment. The three-dimensional model cutting method comprises the steps of obtaining graph structure data of a to-be-cut model and a plurality of to-be-determined cutting surfaces; taking the graph structure data and the plurality of to-be-determined cutting surfaces as input data of an RL model, cutting the to-be-cut model by the RL model, and outputting a cutting scheme which comprises a plurality of target cutting surfaces with a cutting sequence and forms a plurality of target sub-blocks of the to-be-cut model; repeating the step of outputting the cutting schemes by the RL model until the number of iterations of the RL model is equal to the preset number of iterations, and obtaining a plurality of cutting schemes; and determining an optimal cutting scheme for cutting the to-be-cut model in the plurality of cutting schemes. A plurality of cutting schemes capable of being used for cutting the to-be-cut model are output through the RL model, automatic cutting of the three-dimensional model is achieved, and manual participation is not needed; moreover, the adaptability to various complex models is realized through graph structure data used for representing the topological structure and geometric characteristics of the to-be-cut model.

This invention relates to the field of intelligent manufacturing technology, and provides a method and apparatus for planar cutting of sheet materials. The invention obtains the original outline of each object to be cut from a set of objects to be cut, determines the envelope rectangle of each object based on the original outline, and ensures that the adjacent edges of the envelope rectangle with the highest adjacent-side fit among multiple envelope rectangles coincide pairwise, generating a target cutting combination. This achieves effective combination and cutting sequence planning for various auxiliary material shapes. The target cutting combination is then used to cut the sheet material plane to obtain multiple cut objects. This invention establishes a general method for automatically cutting various auxiliary material shapes, solving the problems of low cutting efficiency and significant waste of raw materials in existing technologies for cutting large quantities of multi-shaped sheet materials.

The application belongs to the technical field of laser cutting, and discloses a laser cutting method, device, equipment and storage medium for a bridge middle plate. The method comprises the following steps: when a laser cutting instruction is received, a plurality of closed contours of a workpiece to be cut are acquired; feature point sets of the closed contours are determined; a cutting sequence of the plurality of closed contours is randomly determined, and a cutting point of each closed contour is randomly determined from the feature point set to form an initial cutting path; a new cutting path is generated, and a target empty path length of the new cutting path is determined; a difference between the target empty path length and an initial empty path length is determined; an optimal path is determined based on the difference and a preset value; and laser cutting of the workpiece to be cut is completed based on the optimal path. In the above manner, the empty path length of the laser cutting machine during laser cutting can be effectively reduced, and the cutting efficiency of the laser cutting machine can be effectively improved.

An apparatus comprising: at least one processor, and at least one memory including computer program code configured to, with the at least one processor, cause the apparatus at least to: determine a roll, a pitch and a yaw of a clamped key blank; and based at least in part on the determined roll, pitch and yaw of the key blank, determine a cutting sequence for cutting the key blank.

The invention relates to the field of cutting path optimization, in particular to a 3D automobile instrument board laser cutting path optimization method based on machine vision, and aims at solving the problem that in the laser cutting process, due to the fact that the cutting paths are dense, heating is too concentrated, parts are damaged or the cutting precision is affected. When the cutting path is generated, the cutting part is subjected to three-dimensional consideration, different cutting control strategies are adopted according to a three-dimensional area and a plane area, so that the cutting quality is guaranteed, meanwhile, the existing tiny local path dense condition is analyzed more comprehensively through a bipartite progressive method, and the cutting precision is improved. The method comprises the following steps: cutting a material to form a cutting path, separately arranging the cutting sequence according to the concentration of the distribution of the cutting path, reserving sufficient heat dissipation time in the cutting process, and performing linkage analysis according to the interactivity of the clamping part of the material and the cutting path when the cutting path is generated, so as to realize the division of the cutting priority of the interactive part. And the influence of clamping stability attenuation on the cutting precision in the cutting process is reduced.

The application provides a steel plate piece laser cutting path planning method and system based on step-by-step optimization, and relates to the technical field of production cutting. First, the cutting sequence of the steel plate piece is optimized by using a simulated annealing algorithm of adaptive large-range neighborhood search. Then, the cutting starting point of each steel plate piece is optimized by using a genetic algorithm. Finally, the cutting path is generated based on the cutting sequence of the steel plate piece and the cutting starting point of each steel plate piece. The application can reduce the cutting path, improve the operation efficiency, shorten the production cycle and improve the automation level of the production line.

The invention provides a line-edge tray optimization method based on a genetic algorithm, and the method comprises the steps: obtaining the attribute information of parts from modeling data, and dividing the parts into different trays according to a preset classification basis; all the steel plates used for cutting out the parts are numbered, a plurality of chromosomes are obtained, and the gene sequence in each chromosome represents the cutting sequence of the steel plates. And then the serial numbers are optimized and sorted based on a genetic algorithm to achieve different target expectations, and the target expectations comprise the minimization of the average completion period of tray neat sleeving, the minimization of the number of trays being manufactured at the same time and the minimization of the number of plate turnover times. Compared with manual repeated trial and error, the tray optimization method has the advantage that the problem solving efficiency is greatly improved. Meanwhile, according to the scheme, a group of equilibrium solutions can be obtained under the condition that multiple conflict targets are involved, and more choices are provided for decision makers.

According to the groove cutting method, a groove comprises a first groove edge and a second groove edge, the groove surface of the first groove edge is perpendicular to a YOZ plane, the groove surface of the second groove edge is perpendicular to an XOZ plane, and one end of the first groove edge intersects with one end of the second groove edge; the end, away from the second groove edge, of the first groove edge is divided into a first groove edge front half stroke and a second groove edge rear half stroke, and the end, close to the first groove edge, of the second groove edge is divided into a second groove edge front half stroke and a second groove edge rear half stroke. The cutting sequence is a first groove edge front half process, a first groove edge rear half process, a second groove edge front half process and a second groove edge rear half process. Through the improvement of the scheme, arc leading-out and arc leading-in of cutting points in the cutting process are omitted, gaps between parts on cutting base metal are reduced, the material utilization rate is increased, and the production cost is saved.