Time balance based dual-head laser cutting path optimization method and apparatus

Abstract

The application discloses a double-head laser cutting path optimization method and device based on time balancing, and relates to the technical field of laser cutting. The method comprises the following steps: dividing a plate after part layout into two pre-processing areas; calculating the optimal cutting route of each laser head in the corresponding pre-processing area to obtain the processing sequence of all parts in each pre-processing area and the cutting starting point of each part in each pre-processing area; calculating the actual distance of the two laser heads, planning a collision box for each part according to the actual distance of the two laser heads and the two optimal cutting routes; dividing the plate area into two pre-processing areas again according to the actual processing time of the two laser heads; and repeating steps S2 to S4 until the processing time of the two laser heads is balanced. The application allows two laser heads to cut parts on the plate after part layout is completed, guarantees that the cutting time of the two laser heads is basically consistent, realizes the acquisition of the optimal cutting path in the partition, and avoids collision between the two laser heads in the cutting process.

Description

Technical Field

[0001] This invention relates to the field of laser cutting technology, and in particular to a method and apparatus for optimizing dual-head laser cutting paths based on time equalization. Background Technology

[0002] The laser cutting path optimization problem involves determining the cutting sequence and starting point of the parts on a pre-laid sheet metal to obtain the optimal laser cutting path and improve laser processing efficiency. The laser cutting path optimization problem can be categorized as a GTSP (generalized traveling salesman problem), with the key challenge being determining the cutting sequence and starting point of the parts.

[0003] Currently, most research on laser cutting path optimization is based on single-head lasers, typically employing intelligent optimization algorithms such as simulated annealing, ant colony optimization, or genetic algorithms. These methods are largely suitable for single-head laser cutting path optimization problems, but cannot further improve laser processing efficiency. They are not applicable to the dual-head laser cutting path optimization problem required by our company, which involves operating within a fixed area. Furthermore, they cannot guarantee balanced cutting time between the two laser heads, nor can they prevent collisions between the two laser heads during cutting.

[0004] Therefore, there is an urgent need for a time-equalized dual-head laser cutting path optimization method and device to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a time-equalized dual-head laser cutting path optimization method and apparatus, which allows two laser heads to collaboratively process parts on a sheet metal after part layout has been completed in a fixed area, ensuring that the cutting time of the two laser heads is basically consistent. By drawing on the solution to the single-head laser cutting path optimization problem, the optimal cutting path within the partition is obtained, and collisions between the two laser heads are avoided during the cutting process. Therefore, it can significantly improve the laser cutting efficiency compared to single-head lasers, and has important practical value and reference significance in the field of laser cutting path optimization.

[0006] To achieve the above objectives, this invention discloses a dual-head laser cutting path optimization method based on time equalization, which includes the following steps:

[0007] S1. Divide the sheet metal after part layout into two pre-processing areas. Each pre-processing area corresponds to a laser head, and each pre-processing area contains at least one part.

[0008] S2. Calculate the optimal cutting path of each laser head in the corresponding pre-processing area to obtain the processing sequence of all parts in each pre-processing area and the cutting starting point of each part in each pre-processing area.

[0009] S3. Calculate the actual distance between the two laser heads, and plan a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths;

[0010] S4. Based on the actual processing time of the two laser heads, the plate area is re-divided into two pre-processing areas;

[0011] S5. Repeat steps S2 to S4 until the processing times of the two laser heads are equalized.

[0012] Preferably, let the fixed area of ​​the plate be L in length and W in width, the initial dividing line S = L / 2, the initial position coordinates of the first laser head be (L / 2, 0), the initial position coordinates of the second laser head be (L, 0), the laser head cutting speed be v, the number of plate parts be n, the cutting time of the i-th part be ti, the number of iterations be c, and the fixed area has n parts, i ≤ n, where i and n are both natural numbers greater than 1. In step S1, the time-balanced collaborative partitioning algorithm and the dynamic adjustment of the region division of the two pre-processed areas according to the processing time of each pre-processed area under the corresponding laser head specifically include:

[0013] S11. Divide the fixed area into a first pre-processing area and a second pre-processing area according to the initial dividing line S. Let T be the processing time of the first pre-processing area. l0 The processing time for the second pre-processing area is T. r0 ;

[0014] S12, Compare T l0 and T r0 Based on the size of the part and the comparison results and the time-balanced collaborative partitioning algorithm, each part located on the initial dividing line is assigned to one of the pre-processing areas, thus obtaining the new processing time T for the first pre-processing area. l1 The new processing time for the second pre-processing area is T. r1 ;

[0015] S13, Compare T l1 and T r1 Based on the comparison results and the bisection method, the initial dividing line is directed towards T. l1 and T r1The pre-processing area corresponding to the larger value is moved to obtain a new first pre-processing area and a second pre-processing area;

[0016] S14. Repeat steps S11 to S13 until the following comparison retention formula R is satisfied. k :

[0017] ,

[0018] The number of times steps S11 to S13 are repeated is k-1.

[0019] Specifically, the cutting of each of the aforementioned parts is performed via the same laser head.

[0020] Preferably, in step S2, the optimal cutting path of each laser head in the corresponding pre-processing area is calculated using an improved dual-chromosome genetic algorithm. Specifically, the calculation of the optimal cutting path of each laser head in the corresponding pre-processing area using the improved dual-chromosome genetic algorithm includes:

[0021] S21. Obtain the coordinates of the starting point of each part to be cut within the current pre-processing area, and encode the cutting sequence of the parts and the starting point of the cutting sequence.

[0022] S22. Set the initial generation number of the population Gen=0, and randomly generate m individuals as the initial population according to the cycle start principle to start the iteration;

[0023] S23. Calculate individual fitness;

[0024] S24. Based on the roulette wheel algorithm, combine the elite retention strategy to select individuals with high fitness, add the selected individuals to the next generation of the population, and update the population.

[0025] S25. Randomly select two individuals in the population to pair up and exchange segments. The new individuals generated by the crossover are mixed with the parent individuals and arranged to retain the top half of the individuals with the highest fitness. The population is then updated.

[0026] S26. Mutation operation: Randomly select an individual to mutate. After mutation, perform an unobstructed adjustment operation. The mutated individual replaces the original individual and updates the population. Set Gen = Gen + 1 and return to step S23.

[0027] S27. Compare the current population generation number Gen with the preset iteration number G. If Gen > G, output the optimal solution and use the optimal solution as the optimal cutting path of the corresponding laser head in the current pre-processing area. If Gen <= G, return to step S23 to recalculate the individual fitness.

[0028] Preferably, each of the parts has multiple edges. In step S3, combined with the improved axial bounding box algorithm, a collision box is planned for each part based on the actual distance between the two laser heads and the two optimal cutting paths. Let the empty line distance of the first laser head be d. l The empty line distance of the second laser head is d. r The limiting distance between the first laser head and the second laser head is d. f The improved axial bounding box algorithm, which plans a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths, specifically includes:

[0029] Compare d l With d r The size of the values ​​determines the pre-processed area corresponding to the larger value as the collision area and the pre-processed area corresponding to the smaller value as the anti-collision area.

[0030] In the collision zone:

[0031] Based on the improved axial bounding box algorithm, the minimum value of the horizontal coordinate of the i-th part is defined as x. imin The maximum value is x imax The minimum value in the vertical direction is y. imin The maximum value is y imax ;

[0032] According to x imin x imax y imin y imax and d f Build a large collision box for the current part;

[0033] Based on the improved axial bounding box algorithm, the minimum value of the horizontal coordinate of the j-th edge of the i-th part is defined as x. ijmin The maximum value is x ijmax The minimum value in the vertical direction is y. ijmin The maximum value is y ijmax ;

[0034] According to x ijmin x ijmax y ijmin y ijmax and d f Construct a small collision box for the j-th edge of the current part;

[0035] Record the start and end processing times of each part and its sides in the collision area;

[0036] In the collision avoidance zone:

[0037] When the laser head corresponding to the anti-collision zone performs processing and cutting, it is determined whether the current laser head has entered the large collision box corresponding to any part in the collision zone;

[0038] If so, determine whether the processing times of the two laser heads conflict;

[0039] If so, determine which side of the small collision box the laser head is entering;

[0040] Determine whether the processing times of the two laser heads conflict;

[0041] If so, the distance between the two laser heads is calculated based on their processing time and current position coordinates.

[0042] Whether a collision will occur is determined based on the current distance between the two laser heads;

[0043] If so, the laser head corresponding to the anti-collision area is made to stay still and wait, and the laser head corresponding to the collision area is made to continue moving until the collision time interval ends.

[0044] Preferably, let the collision time interval be t, and the coordinates of the first laser head be (x... l y l The coordinates of the second laser head are (x...). r y r Then, the distance between the two laser heads can be calculated using the following formula:

[0045] ,

[0046] in, Let be the velocity component of the laser beam from the first laser head in the x-direction. Let x be the length component of the first laser head traveled in the x-direction. Let be the velocity component of the laser beam from the first laser head in the y-direction. This represents the length component of the first laser head's travel in the y-direction. Let be the velocity component of the laser beam from the second laser head in the x-direction. Let x be the length component of the second laser head traveled in the x-direction. Let be the velocity component of the laser beam from the second laser head in the y-direction. This represents the length component of the second laser head traveled in the y-direction.

[0047] Preferably, step S4 specifically includes:

[0048] Based on the processing time and waiting time of the two laser heads, the actual processing time of the two laser heads is calculated, and the larger of the actual processing times of the laser heads is taken as the total processing time.

[0049] Calculate the ratio of the difference in actual processing time between the two laser heads to the total processing time, and record the result as the adjustment parameter S. lr ;

[0050] If S lr If the value is greater than the first adjustment parameter, then select the three parts on or near the corresponding optimal cutting path with the smallest value in the pre-processing area with a larger actual processing time, and move them to the pre-processing area with a smaller actual processing time.

[0051] If S lr If the value is greater than the second adjustment parameter, then select the two parts on or near the corresponding optimal cutting path with the smallest value in the pre-processing area with the longer actual processing time, and move them to the pre-processing area with the shorter actual processing time.

[0052] If S lr If the value is greater than the third adjustment parameter, then select the second smallest part on or near the corresponding optimal cutting path in the pre-processing area with a longer actual processing time, and move it to the pre-processing area with a shorter actual processing time.

[0053] If S lr If the adjustment parameter is less than the third adjustment parameter, the processing time of the two laser heads will satisfy the time balance, wherein the first adjustment parameter > the second adjustment parameter > the third adjustment parameter.

[0054] Specifically, the adjustment parameter S is calculated according to the following formula. lr :

[0055] ,

[0056] in, This represents the actual processing time of the first laser head. This represents the actual processing time of the second laser head.

[0057] Accordingly, the present invention also discloses a dual-head laser cutting path optimization device based on time equalization, which includes:

[0058] The first division module is configured to divide the sheet metal after part layout into two pre-processing areas, each pre-processing area corresponding to a laser head, and each pre-processing area containing at least one part;

[0059] The first calculation module is configured to calculate the optimal cutting path of each laser head in the corresponding pre-processing area, so as to obtain the processing sequence of all parts in each pre-processing area and the cutting starting point of each part in each pre-processing area.

[0060] The second calculation module is configured to calculate the actual distance between the two laser heads and plan a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths;

[0061] The second division module is configured to re-divide the plate area into two pre-processing areas based on the actual processing time of the two laser heads;

[0062] The repeat module is configured to sequentially repeat the actions of the first calculation module, the second calculation module, and the second division module until the processing times of the two laser heads are equalized.

[0063] Accordingly, the present invention also discloses a computer-readable storage medium storing a cutting path optimization program, which, when executed by a processor, implements the steps of the time-equalized dual-head laser cutting path optimization method as described above.

[0064] Compared with existing technologies, this invention allows two laser heads to collaboratively process parts on a sheet metal after part layout has been completed in a fixed area, ensuring that the cutting time of the two laser heads is basically the same. By drawing on the solution to the single-head laser cutting path optimization problem, the optimal cutting path within the partition is obtained, and collisions between the two laser heads during the cutting process are avoided. Therefore, compared with single-head laser, the laser cutting efficiency is greatly improved, and it has important practical value and reference significance in the field of laser cutting path optimization. Attached Figure Description

[0065] Figure 1 This is a flowchart of the time-equalized dual-head laser cutting path optimization method of the present invention;

[0066] Figure 2 This is an algorithm flowchart of the dual-head laser cutting path optimization method based on time equalization of the present invention;

[0067] Figure 3 This is a flowchart of the time-balanced collaborative partitioning algorithm of the present invention;

[0068] Figure 4 This invention defines the starting point for part cutting and represents one feasible cutting path.

[0069] Figure 5 This represents a feasible cutting path according to the present invention;

[0070] Figure 6 This is a flowchart of the dual-chromosome genetic algorithm for solving the laser cutting path optimization algorithm of the present invention;

[0071] Figure 7This is a schematic diagram illustrating the relationship between the size collision boxes based on the improved axial bounding box algorithm of the present invention;

[0072] Figure 8 This is the result of the time-equalized dual-head laser cutting path optimization algorithm of the present invention;

[0073] Figure 9 This is a schematic diagram of the structure of the dual-head laser cutting path optimization device based on time equalization of the present invention. Detailed Implementation

[0074] To illustrate the technical content, structural features, objectives, and effects of the present invention in detail, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0075] Please see Figures 1-8 As shown in this embodiment, the dual-head laser cutting path optimization method based on time equalization includes the following steps:

[0076] S1. Divide the sheet metal after part layout into two pre-processing areas. Each pre-processing area corresponds to a laser head, and each pre-processing area contains at least one part.

[0077] S2. Calculate the optimal cutting path of each laser head in the corresponding pre-processing area to obtain the processing sequence of all parts in each pre-processing area and the cutting starting point of each part in each pre-processing area.

[0078] S3. Calculate the actual distance between the two laser heads, and plan a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths;

[0079] S4. Based on the actual processing time of the two laser heads, the plate area is re-divided into two pre-processing areas;

[0080] S5. Repeat steps S2 to S4 until the processing times of the two laser heads are equalized.

[0081] Preferably, let the fixed area of ​​the sheet metal have a length of L and a width of W, an initial dividing line S = L / 2, an initial position coordinate of the first laser head (L / 2, 0), an initial position coordinate of the second laser head (L, 0), a laser head cutting speed of v, a sheet metal part number of n, a cutting time of ti for the i-th part, and an iteration number of c. The fixed area has n parts, i ≤ n, where i and n are both natural numbers greater than 1. In step S1, a time-balanced collaborative partitioning algorithm is used, and the region division of the two pre-processing areas is dynamically adjusted according to the processing time of each pre-processing area under the corresponding laser head. Figure 3A flowchart of a time-equalization-based collaborative partitioning algorithm is shown. The time-equalization-based collaborative partitioning algorithm, and the specific steps of dynamically adjusting the region division between the two pre-processing regions based on the processing time of each pre-processing region under the corresponding laser head, include:

[0082] S11. Divide the fixed area into a first pre-processing area and a second pre-processing area according to the initial dividing line S. Let T be the processing time of the first pre-processing area. l0 The processing time for the second pre-processing area is T. r0 ;

[0083] S12, Compare T l0 and T r0 Based on the size of the part and the comparison results and the time-balanced collaborative partitioning algorithm, each part located on the initial dividing line is assigned to one of the pre-processing areas, thus obtaining the new processing time T for the first pre-processing area. l1 The new processing time for the second pre-processing area is T. r1 ;

[0084] S13, Compare T l1 and T r1 Based on the comparison results and the bisection method, the initial dividing line is directed towards T. l1 and T r1 The pre-processing area corresponding to the larger value is moved to obtain a new first pre-processing area and a second pre-processing area;

[0085] S14. Repeat steps S11 to S13 until the following comparison retention formula R is satisfied. k :

[0086] ,

[0087] The number of times steps S11 to S13 are repeated is k-1.

[0088] Understandably, the above steps can dynamically adjust the partitioning of a fixed area based on the part processing time, so that the part processing time of the pre-partitioned plan is as balanced as possible. This makes it easier for subsequent steps to redivide the processing area based on the processing time of the two laser heads, after solving the problems of laser cutting path optimization and collision detection within the partition. Ultimately, this can balance the processing time of the two laser heads, which greatly improves the processing efficiency compared to a single laser head.

[0089] Specifically, to ensure the continuity of processing for each part, the cutting of each part described in this embodiment is performed via the same laser head.

[0090] Preferably, in step S2, the optimal cutting path of each laser head in the corresponding pre-processing area is calculated using an improved dual-chromosome genetic algorithm. Specifically, the calculation of the optimal cutting path of each laser head in the corresponding pre-processing area using the improved dual-chromosome genetic algorithm includes:

[0091] S21. Obtain the coordinates of the starting point of each part to be cut within the current pre-processing area, and encode the cutting sequence of the parts and the starting point of the cutting sequence.

[0092] S22. Set the initial generation number of the population Gen=0, and randomly generate m individuals as the initial population according to the cycle start principle to start the iteration;

[0093] S23. Calculate individual fitness;

[0094] S24. Based on the roulette wheel algorithm, combine the elite retention strategy to select individuals with high fitness, add the selected individuals to the next generation of the population, and update the population.

[0095] S25. Randomly select two individuals in the population to pair up and exchange segments. The new individuals generated by the crossover are mixed with the parent individuals and arranged to retain the top half of the individuals with the highest fitness. The population is then updated.

[0096] S26. Mutation operation: Randomly select an individual to mutate. After mutation, perform an unobstructed adjustment operation. The mutated individual replaces the original individual and updates the population. Set Gen = Gen + 1 and return to step S23.

[0097] S27. Compare the current population generation number Gen with the preset iteration number G. If Gen > G, output the optimal solution and use the optimal solution as the optimal cutting path of the corresponding laser head in the current pre-processing area. If Gen <= G, return to step S23 to recalculate the individual fitness.

[0098] Figure 6 This illustrates a flowchart of a dual-chromosome genetic algorithm for solving laser cutting path optimization. In step S2, based on the processing area defined in step S1, the optimal laser cutting path is sought for each of the two laser heads using an improved dual-chromosome genetic algorithm. In existing technologies, the main challenges in single-head laser cutting path optimization are how to select the cutting sequence and the starting point for cutting the part. Figure 4 The diagram illustrates the determination of the cutting starting point and the representation of one feasible cutting path. Figure 5 A feasible cutting path representation is shown. Traditional genetic algorithms solve the two problems separately. The improved dual-chromosome genetic algorithm used in this embodiment can integrate the two problems and solve them together, reducing the complexity of the problem. The laser cutting path optimization problem is defined as follows: the number of sheet metal parts is n, and the cutting starting point of the i-th part is p(x...).i y i The cutting starting point for the (i+1)th part is p(x). i+1 y i+1 If the initial position of the laser head is p(x0, y0), then the formula for calculating the blank line distance cut by the laser head is:

[0099] .

[0100] To better understand how the improved dual-chromosome genetic algorithm calculates the optimal cutting path for each laser head in the corresponding pre-processing area in step S2, the following provides a specific implementation of the improved dual-chromosome genetic algorithm for solving the laser cutting path optimization problem:

[0101] (1) Encoding:

[0102] For the path optimization problem in laser cutting, the encoding method is the same as that used to solve the Traveling Salesman Problem, employing an integer permutation encoding method, and further using a double-chromosome encoding. In the double-chromosome encoding, two chromosomes are distributed vertically, each with a length consistent with the number of parts. The first row of chromosomes represents the cutting order of each part, and the second row represents the starting cutting position corresponding to each part. For example, if the parts are numbered 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, and their corresponding cutting starting point numbers range from 0 to 6, after random sorting, the first row of chromosomes is encoded as (0, 2, 4, 3, 5, 1, 6, 8, 7, 9), and the second row is encoded as (2, 5, 1, 0, 2, 3, 4, 2, 0, 1).

[0103] (2) Population initialization:

[0104] Let the number of parts to be processed be n. According to the constraints, use a random function to arrange the part numbers and the corresponding cutting start points of the parts, generate two chromosomes to form a single individual, and finally generate m individuals.

[0105] (3) Calculate the fitness function:

[0106] An optimization objective function is established based on the formula for calculating the blank line distance during laser head cutting. A smaller objective function value is better. The objective function needs to be transformed into a fitness function by taking its reciprocal. To allow for adjustment, μ can be set as an adjustment coefficient. The fitness function formula is:

[0107] ;

[0108] (4) Select operation:

[0109] The selection operation of the double-chromosome genetic algorithm is the process of determining how parental individuals transmit genes to the next generation. Individuals with low fitness have a higher probability of being eliminated, and individuals with high fitness have a higher probability of being selected. According to the roulette wheel algorithm, the selection probability calculation formula is:

[0110] ,

[0111] where P i represents the probability that an individual is selected, represents the fitness value of an individual. To prevent the destruction of excellent genes during the selection process, an elite retention strategy is combined with the roulette wheel algorithm, and the optimal individual in the parental generation is directly copied to the next generation. The specific selection operation is as follows: First, calculate the fitness values of all individuals in the current population and sort them; Second, select the first s (s < m) elite individuals with high fitness values and directly copy them to the next generation; Finally, for the remaining m - s individuals in the population, perform the selection operation using the roulette wheel algorithm;

[0112] (5) Crossover operation:

[0113] The crossover operation combines the characteristics of two parental individuals to generate new offspring individuals. Since the coding method of the GTSP problem is integer permutation coding, simple segment swapping cannot be done, and some adjustments need to be made to the chromosome after swapping. According to the constraint conditions, a crossover operation is designed. The specific operation is as follows: Parent 1 and Parent 2 are alternately placed in the transitional generation according to the part cutting order of the first row, while the corresponding second row remains unchanged, that is, the cutting starting point remains unchanged. Then, the genes of the first row of the transitional generation are taken in turn. If the gene is not included in offspring 1, it is placed in offspring 1, otherwise it is placed in offspring 2;

[0114] (6) Mutation operation:

[0115] To suit the particularity of the laser cutting path planning problem, two mutation operations are designed based on the double chromosome. The first mutation operation adopts the transposition mutation strategy, randomly selects two out-of-position numbers on the part cutting numbers of the first row for swapping, while the corresponding second row remains unchanged, that is, the cutting starting point remains unchanged. The second mutation operation randomly mutates the part cutting starting points of the second row, while the corresponding first row remains unchanged, that is, the cutting order remains unchanged.

[0116] It can be understood that, compared with the traditional genetic algorithm, by improving the double-chromosome genetic algorithm to jointly determine the part cutting order and the corresponding cutting starting point, the complexity of the problem is reduced; and through the elite retention strategy in the selection operation and the strategy of retaining individuals with higher fitness by mixing the parental and offspring generations in the swapping operation, it is ensured that the optimal individuals in the evolutionary process are not lost.

[0117] Preferably, each of the said parts has multiple edges, Figure 7A schematic diagram of the relationship between the size collision boxes based on the improved axial bounding box algorithm is shown. In step S3, combining the improved axial bounding box algorithm, a collision box is planned for each part based on the actual distance between the two laser heads and the two optimal cutting paths. Let the empty line distance of the first laser head be d. l The empty line distance of the second laser head is d. r The limiting distance between the first laser head and the second laser head is d. f The improved axial bounding box algorithm, which plans a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths, specifically includes:

[0118] Compare d l With d r The size of the values ​​determines the pre-processed area corresponding to the larger value as the collision area and the pre-processed area corresponding to the smaller value as the anti-collision area.

[0119] In the collision zone:

[0120] Based on the improved axial bounding box algorithm, the minimum value of the horizontal coordinate of the i-th part is defined as x. imin The maximum value is x imax The minimum value in the vertical direction is y. imin The maximum value is y imax ;

[0121] According to x imin x imax y imin y imax and d f Build a large collision box for the current part;

[0122] Based on the improved axial bounding box algorithm, the minimum value of the horizontal coordinate of the j-th edge of the i-th part is defined as x. ijmin The maximum value is x ijmax The minimum value in the vertical direction is y. ijmin The maximum value is y ijmax ;

[0123] According to x ijmin x ijmax y ijmin y ijmax and d f Construct a small collision box for the j-th edge of the current part;

[0124] Record the start and end processing times of each part and its sides in the collision area;

[0125] In the collision avoidance zone:

[0126] When the laser head corresponding to the anti-collision zone performs processing and cutting, it is determined whether the current laser head has entered the large collision box corresponding to any part in the collision zone;

[0127] If so, determine whether the processing times of the two laser heads conflict;

[0128] If so, determine which side of the small collision box the laser head is entering;

[0129] Determine whether the processing times of the two laser heads conflict;

[0130] If so, the distance between the two laser heads is calculated based on their processing time and current position coordinates.

[0131] Whether a collision will occur is determined based on the current distance between the two laser heads;

[0132] If so, the laser head corresponding to the anti-collision area is made to stay still and wait, and the laser head corresponding to the collision area is made to continue moving until the collision time interval ends.

[0133] Preferably, let the collision time interval be t, and the coordinates of the first laser head be (x... l y l The coordinates of the second laser head are (x...). r y r Then, the distance between the two laser heads can be calculated using the following formula:

[0134] ,

[0135] in, Let be the velocity component of the laser beam from the first laser head in the x-direction. Let x be the length component of the first laser head traveled in the x-direction. Let be the velocity component of the laser beam from the first laser head in the y-direction. This represents the length component of the first laser head's travel in the y-direction. Let be the velocity component of the laser beam from the second laser head in the x-direction. Let x be the length component of the second laser head traveled in the x-direction. Let be the velocity component of the laser beam from the second laser head in the y-direction. This represents the length component of the second laser head traveled in the y-direction.

[0136] Understandably, based on the improved axial bounding box algorithm, collision boxes are planned not only for individual parts in the collision area, but also for each edge of an individual part, further compressing the range of the collision detection area. In addition, there is only a certain probability that a collision will occur when the laser head enters the collision box within the conflict time. Therefore, the actual distance between the two laser heads at this time is calculated based on the formula of time and distance, and the collision between the two laser heads is accurately determined. This improves the accuracy of collision detection and the efficiency of processing time to a certain extent.

[0137] Preferably, step S4 specifically includes:

[0138] Based on the processing time and waiting time of the two laser heads, the actual processing time of the two laser heads is calculated, and the larger of the actual processing times of the laser heads is taken as the total processing time.

[0139] Calculate the ratio of the difference in actual processing time between the two laser heads to the total processing time, and record the result as the adjustment parameter S. lr ;

[0140] If S lr If the value is greater than the first adjustment parameter, then the three parts with the smallest corresponding optimal cutting path or closest to the corresponding optimal cutting path in the pre-processing area with a longer actual processing time are selected and moved to the pre-processing area with a shorter actual processing time. In this embodiment, the value of the first adjustment parameter is 0.15;

[0141] If S lr If the value is greater than the second adjustment parameter, then in the pre-processing area with a longer actual processing time, select the two parts on or near the corresponding optimal cutting path with the shortest corresponding optimal cutting path, and move them to the pre-processing area with a shorter actual processing time. In this embodiment, the value of the second adjustment parameter is 0.1;

[0142] If S lr If the value is greater than the third adjustment parameter, then the part that is on or near the second smallest part on the corresponding optimal cutting path in the pre-processing area with a longer actual processing time is selected and moved to the pre-processing area with a shorter actual processing time. In this embodiment, the value of the third adjustment parameter is 0.05.

[0143] If S lr If the time is less than the third adjustment parameter, the processing time of the two laser heads will satisfy the time balance requirement.

[0144] Specifically, the adjustment parameter S is calculated according to the following formula. lr :

[0145] ,

[0146] in, This represents the actual processing time of the first laser head. This represents the actual processing time of the second laser head.

[0147] Figure 8 The diagram shows the cutting path planning results of a time-equalized dual-laser path optimization algorithm for dual-laser operation, indicating the positions where the laser heads will collide and the waiting times. The solid line represents the cutting path of the first laser head, and the dashed line represents the cutting path of the second laser head.

[0148] Please see Figure 9 As shown, correspondingly, the present invention also discloses a dual-head laser cutting path optimization device based on time equalization, which includes:

[0149] The first division module 10 is configured to divide the sheet metal after part layout into two pre-processing areas, each pre-processing area corresponding to a laser head, and each pre-processing area containing at least one part;

[0150] The first calculation module 20 is configured to calculate the optimal cutting path of each laser head in the corresponding pre-processing area, so as to obtain the processing sequence of all parts in each pre-processing area and the cutting starting point of each part in each pre-processing area.

[0151] The second calculation module 30 is configured to calculate the actual distance between the two laser heads and plan a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths;

[0152] The second division module 40 is configured to re-divide the plate area into two pre-processing areas based on the actual processing time of the two laser heads;

[0153] The repeat module 50 is configured to sequentially repeat the actions of the first calculation module, the second calculation module, and the second division module until the processing times of the two laser heads are equalized.

[0154] Accordingly, the present invention also discloses a computer-readable storage medium storing a cutting path optimization program, which, when executed by a processor, implements the steps of the time-equalized dual-head laser cutting path optimization method as described above.

[0155] Combination Figures 1-9This invention allows two laser heads to collaboratively process parts on a sheet metal after part layout has been completed in a fixed area, ensuring that the cutting time of the two laser heads is basically the same. By drawing on the solution to the single-head laser cutting path optimization problem, the optimal cutting path within the partition is obtained, and collisions between the two laser heads during the cutting process are avoided. Therefore, compared with single-head laser, the laser cutting efficiency is greatly improved, and it has important practical value and reference significance in the field of laser cutting path optimization.

[0156] The above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for optimizing the path of a dual-head laser cutting head based on time equalization, characterized in that, Includes the following steps: S1. Divide the sheet metal after part layout into two pre-processing areas. Each pre-processing area corresponds to a laser head, and each pre-processing area contains at least one part. S2. Calculate the optimal cutting path of each laser head in the corresponding pre-processing area to obtain the processing sequence of all parts in each pre-processing area and the cutting starting point of each part in each pre-processing area. S3. Calculate the actual distance between the two laser heads, and plan a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths; S4. Based on the actual processing time of the two laser heads, the plate area is re-divided into two pre-processing areas; S5. Repeat steps S2 to S4 until the processing times of the two laser heads are equalized; In step S3, combined with the improved axial bounding box algorithm, a collision box is planned for each part based on the actual distance between the two laser heads and the two optimal cutting paths. Let the empty line distance of the first laser head be d. l The empty line distance of the second laser head is d. r The limiting distance between the first laser head and the second laser head is d. f The improved axial bounding box algorithm, which plans a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths, specifically includes: Compare d l With d r The size of the values ​​determines the pre-processed area corresponding to the larger value as the collision area and the pre-processed area corresponding to the smaller value as the anti-collision area. In the collision zone: Based on the improved axial bounding box algorithm, the minimum value of the horizontal coordinate of the i-th part is defined as x. imin The maximum value is x imax The minimum value in the vertical direction is y. imin The maximum value is y imax ; According to x imin x imax y imin y imax and d f Build a large collision box for the current part; Based on the improved axial bounding box algorithm, the minimum value of the horizontal coordinate of the j-th edge of the i-th part is defined as x. ijmin The maximum value is x ijmax The minimum value in the vertical direction is y. ijmin The maximum value is y ijmax ; According to x ijmin x ijmax y ijmin y ijmax and d f Construct a small collision box for the j-th edge of the current part; Record the start and end processing times of each part and its sides in the collision area; In the collision avoidance zone: When the laser head corresponding to the anti-collision zone performs processing and cutting, it is determined whether the current laser head has entered the large collision box corresponding to any part in the collision zone; If so, determine whether the processing times of the two laser heads conflict; If so, determine which side of the small collision box the laser head is entering; Determine whether the processing times of the two laser heads conflict; If so, the distance between the two laser heads is calculated based on their processing time and current position coordinates. Whether a collision will occur is determined based on the current distance between the two laser heads; If so, the laser head corresponding to the anti-collision area is made to stay still and wait, and the laser head corresponding to the collision area is made to continue moving until the collision time interval ends.

2. The dual-head laser cutting path optimization method based on time equalization as described in claim 1, characterized in that, let... The fixed area of ​​the plate has a length of L and a width of W. The initial dividing line is S = L / 2. The initial position coordinates of the first laser head are (L / 2, 0), the initial position coordinates of the second laser head are (L, 0), the laser head cutting speed is v, the number of plate parts is n, the cutting time of the i-th part is ti, the number of iterations is c, and the fixed area has n parts, i ≤ n, where i and n are both natural numbers greater than 1. In step S1, the time-balanced collaborative partitioning algorithm and the dynamic adjustment of the region division of the two pre-processed areas according to the processing time of each pre-processed area under the corresponding laser head specifically include: S11. Divide the fixed area into a first pre-processing area and a second pre-processing area according to the initial dividing line S. Let T be the processing time of the first pre-processing area. l0 The processing time for the second pre-processing area is T. r0 ; S12, Compare T l0 and T r0 Based on the size of the part and the comparison results and the time-balanced collaborative partitioning algorithm, each part located on the initial dividing line is assigned to one of the pre-processing areas, thus obtaining the new processing time T for the first pre-processing area. l1 The new processing time for the second pre-processing area is T. r1 ; S13, Compare T l1 and T r1 Based on the comparison results and the bisection method, the initial dividing line is directed towards T. l1 and T r1 The pre-processing area corresponding to the larger value is moved to obtain a new first pre-processing area and a second pre-processing area; S14. Repeat steps S11 to S13 until the following comparison retention formula R is satisfied. k : , The number of times steps S11 to S13 are repeated is k-1.

3. The dual-head laser cutting path optimization method based on time equalization as described in claim 2, characterized in that, The cutting of each of the aforementioned parts is performed via the same laser head.

4. The dual-head laser cutting path optimization method based on time equalization as described in claim 1, characterized in that, In step S2, the optimal cutting path of each laser head in the corresponding pre-processing area is calculated using an improved dual-chromosome genetic algorithm. Specifically, the calculation of the optimal cutting path of each laser head in the corresponding pre-processing area using the improved dual-chromosome genetic algorithm includes: S21. Obtain the coordinates of the starting point of each part to be cut within the current pre-processing area, and encode the cutting sequence of the parts and the starting point of the cutting sequence. S22. Set the initial generation number of the population Gen=0, and randomly generate m individuals as the initial population according to the cycle start principle to start the iteration; S23. Calculate individual fitness; S24. Based on the roulette wheel algorithm, combine the elite retention strategy to select individuals with high fitness, add the selected individuals to the next generation of the population, and update the population. S25. Randomly select two individuals in the population to pair up and exchange segments. The new individuals generated by the crossover are mixed with the parent individuals and arranged to retain the top half of the individuals with the highest fitness. The population is then updated. S26. Mutation operation: Randomly select an individual to mutate. After mutation, perform an unobstructed adjustment operation. The mutated individual replaces the original individual and updates the population. Set Gen = Gen + 1 and return to step S23. S27. Compare the current population generation number Gen with the preset iteration number G. If Gen > G, output the optimal solution and use the optimal solution as the optimal cutting path of the corresponding laser head in the current pre-processing area. If Gen <= G, return to step S23 to recalculate the individual fitness.

5. The dual-head laser cutting path optimization method based on time equalization as described in claim 1, characterized in that, let... The collision time interval is t, and the coordinates of the first laser head are (x, y). l y l The coordinates of the second laser head are (x...). r y r Then, the distance between the two laser heads is calculated using the following formula: ， in, Let be the velocity component of the laser beam from the first laser head in the x-direction. Let x be the length component of the first laser head traveled in the x-direction. Let be the velocity component of the laser beam from the first laser head in the y-direction. This represents the length component of the first laser head's travel in the y-direction. Let be the velocity component of the laser beam from the second laser head in the x-direction. Let x be the length component of the second laser head traveled in the x-direction. Let be the velocity component of the laser beam from the second laser head in the y-direction. This represents the length component of the second laser head traveled in the y-direction.

6. The dual-head laser cutting path optimization method based on time equalization as described in claim 1, characterized in that, Step S4 specifically includes: Based on the processing time and waiting time of the two laser heads, the actual processing time of the two laser heads is calculated, and the larger of the actual processing times of the laser heads is taken as the total processing time. Calculate the ratio of the difference in actual processing time between the two laser heads to the total processing time, and record the result as the adjustment parameter S. lr ; If S lr If the value is greater than the first adjustment parameter, then select the three parts on or near the corresponding optimal cutting path with the smallest value in the pre-processing area with a larger actual processing time, and move them to the pre-processing area with a smaller actual processing time. If S lr If the value is greater than the second adjustment parameter, then select the two parts on or near the corresponding optimal cutting path with the smallest value in the pre-processing area with the longer actual processing time, and move them to the pre-processing area with the shorter actual processing time. If S lr If the value is greater than the third adjustment parameter, then select the second smallest part on or near the corresponding optimal cutting path in the pre-processing area with a longer actual processing time, and move it to the pre-processing area with a shorter actual processing time. If S lr If the adjustment parameter is less than the third adjustment parameter, the processing time of the two laser heads will satisfy the time balance, wherein the first adjustment parameter > the second adjustment parameter > the third adjustment parameter.

7. The dual-head laser cutting path optimization method based on time equalization as described in claim 6, characterized in that, The adjustment parameter S is calculated according to the following formula. lr : ， in, This represents the actual processing time of the first laser head. This represents the actual processing time of the second laser head.

8. A time-equalized dual-head laser cutting path optimization device, used to implement the time-equalized dual-head laser cutting path optimization method according to any one of claims 1-7, characterized in that, include: The first division module is configured to divide the sheet metal after part layout into two pre-processing areas, each pre-processing area corresponding to a laser head, and each pre-processing area containing at least one part; The first calculation module is configured to calculate the optimal cutting path of each laser head in the corresponding pre-processing area, so as to obtain the processing sequence of all parts in each pre-processing area and the cutting starting point of each part in each pre-processing area. The second calculation module is configured to calculate the actual distance between the two laser heads and plan a collision box for each part based on the actual distance between the two laser heads and the two optimal cutting paths; The second division module is configured to re-divide the plate area into two pre-processing areas based on the actual processing time of the two laser heads; The repeat module is configured to sequentially repeat the actions of the first calculation module, the second calculation module, and the second division module until the processing times of the two laser heads are equalized.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a cutting path optimization program, which, when executed by a processor, implements the steps of the time-equalized dual-head laser cutting path optimization method as described in any one of claims 1-7.

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