Transformer silicon steel sheet suit cutting optimization method and system based on linear programming

Abstract

The invention relates to a transformer silicon steel sheet suit cutting optimization method and system based on linear programming, and the method comprises the following steps: constructing a target cut piece set and a to-be-processed raw material set of a silicon steel sheet for a suit cutting task of the silicon steel sheet; abstracting a suit-cutting task into a mathematical problem, and forming a corresponding relation of a suit-cutting combination scheme of a target cutting piece set and a to-be-processed raw material set of the silicon steel sheet; constructing constraint conditions of the target cutting piece and the to-be-processed raw material; constructing a silicon steel sheet suit cutting model according to the corresponding relation and the constraint condition; and solving the silicon steel sheet suit cutting model so as to obtain an optimal scheme for carrying out silicon steel sheet suit cutting on the target cut piece set by using the to-be-processed raw material set. According to the method, the mathematical model is established according to the characteristics of the actual situation of the transformer suit cutting task, the linear programming mathematical model is established for the suit cutting problem, the optimized suit cutting scheme is obtained through solving, automatic optimization of the suit cutting scheme is achieved, and the purposes of reducing cost and improving efficiency are achieved.

Description

Technical Field

[0001] This invention belongs to the field of transformer design and manufacturing, specifically a method and system for optimizing the cutting and trimming of silicon steel sheets for transformer cores based on linear programming. Background Technology

[0002] The transformer industry is a traditional manufacturing sector. With the rapid technological advancements of recent years, the differences in technology and manufacturing between domestic and international transformer manufacturers have gradually diminished and even disappeared, leading to increasingly fierce competition. This necessitates more refined transformer design and manufacturing to ensure optimal performance while maintaining the best cost. Influenced by changes in the global economic landscape and rising material costs, transformer production has begun to implement cost-reduction and efficiency-enhancing measures in various aspects. Improving the utilization rate of silicon steel sheet cutting is a highly practical measure for achieving these goals.

[0003] In general factories, the nesting of silicon steel sheets is mainly done manually based on experience. The problem with manual nesting is that it doesn't achieve optimal utilization and is inefficient. The development of computers in recent years has led us to believe that automating this task (letting computers perform the calculations) will yield satisfactory results and truly achieve the goal of cost reduction and efficiency improvement. However, there is still no unified and comprehensive method for solving the nesting problem. Summary of the Invention

[0004] The purpose of this invention is to provide a linear programming-based optimization method and program implementation for silicon steel sheet nesting in transformers. This solves the problem of manually nesting silicon steel sheets in the core workshop, improving nesting efficiency and optimization results. It features convenient input, strong parameterization capabilities, personalized output, multi-threading technology, and multi-objective sorting and comparison functions (utilization rate, number of cuts), making it easier for users to cope with cost constraints under various conditions.

[0005] The technical solution adopted by this invention to achieve the above objectives is: a transformer silicon steel sheet cutting optimization method based on linear programming, comprising the following steps:

[0006] For the task of nesting silicon steel sheets, construct the target set of silicon steel sheets and the set of raw materials to be processed;

[0007] The nesting task is abstracted into a mathematical problem, forming a correspondence between the target set of silicon steel sheets and the nesting combination scheme of the raw materials to be processed;

[0008] Construct constraints for the target cut piece and the raw material to be processed;

[0009] Construct a silicon steel sheet cutting model based on the correspondence and constraints;

[0010] Solving the silicon steel sheet nesting model yields the optimal solution for nesting silicon steel sheets using the set of raw materials to be processed onto the target set of cut sheets.

[0011] The task of nesting silicon steel sheets involves constructing a target set of cut silicon steel sheets and a set of raw materials to be processed, as detailed below:

[0012] The target cut piece set includes the target piece width and its weight:

[0013]

(Width 1, Target Weight 1), (Width 2, Target Weight 2), ..., (Width D, Target Weight D)

[0014] The set of raw materials to be processed includes the available sheet width and its weight:

[0015]

(Width 1, Available Weight 1), (Width 2, Available Weight 2), ..., (Width K, Available Weight K)

[0016] The process of abstracting the nesting task into a mathematical problem, and establishing the correspondence between the target set of silicon steel sheets and the set of raw materials to be processed in nesting combination schemes, includes the following steps:

[0017] Construct a table of nesting combinations of target piece width and available piece width; the coefficients corresponding to the rows and columns express the correspondence between the nesting combination schemes of target piece width and available piece width;

[0018] The rows represent the nesting combinations that can be split into each target width for a given available piece width; the columns represent the width of the target piece width and the weight of the nesting combination.

[0019] The correspondence between the target piece width and the available piece width tailoring combination scheme is expressed as M. ji Meanwhile, the available piece width and weight used in each feasible nesting scheme are expressed as X. j ;

[0020] in, This represents the coefficient corresponding to the i-th target width when performing the p-th available piece width and the q-th feasible nesting combination. n represents the total number of nesting combinations that can be split into various target widths for all available piece widths; sp represents the number of nesting combinations that can be split into different target widths for the p-th available piece width; sm represents the number of nesting combinations that can be split into different target widths for the m-th available piece width. This represents the available piece width weight used in the j-th feasible nesting scheme, that is, the weight used to split the target piece width according to the q-th method for the p-th available piece width.

[0021] The specific constraints on the target cut piece are as follows:

[0022] a i1 X1+a i2 X2+...a ij X j +...+a in X n ≥Target weight i

[0023] Wherein, coefficient a ij =M ji *DWidth i / SW, i∈[1,D],j∈[1,n];

[0024] SW represents the width of the available slice corresponding to the j-th split; DWidth i It is the width of the i-th target slice, and D represents the number of target slice widths. The weight of the available piece width used in the j-th feasible nesting scheme is the weight used to split the target piece width in the q-th way for the p-th available piece width; n represents the total number of nesting combinations that can be split into various target piece widths for all available piece widths.

[0025] The constraints on the available slice width are as follows:

[0026] a (D+m)1 X1+a (D+m)2 X2 + ... + a (D+m)j X j +...+a (D+m)n X n ≤ Available weight m

[0027] Where m∈[1,K], and D represents the target slice width. This represents the weight of the available piece width used in the j-th feasible nesting scheme, i.e., the weight used to split the target piece width according to the q-th method for the p-th available piece width; n represents the total number of nesting combinations that can be split into various target piece widths for all available piece widths; a (D+m)j Let j be the coefficient, and j∈[1,n].

[0028] The silicon steel sheet nesting model is constructed based on the correspondence and constraints:

[0029] beg The minimum value;

[0030] The constraints are:

[0031] a i1 X1+a i2 X2+...a ij X j +...+a in X n≥Target weight i

[0032] a (D+m)1 X1+a (D+m)2 X2 + ... + a (D+m)j X j +...+a (D+m)n X n ≤ Available weight m

[0033] And X j ≥0;

[0034] Wherein, coefficient a ij =M ji *DWidth i / SW, This represents the coefficient corresponding to the i-th target piece width when performing the p-th available piece width and the q-th feasible nesting combination. n represents the total number of nesting combinations that can be split into various target widths for all available piece widths; sm represents the number of nesting combinations that can be split into different target widths for the m-th available piece width; The weight of the available piece width used in the j-th feasible nesting scheme is the weight used to split the target piece width according to the q-th method for the p-th available piece width; n represents the total number of nesting combinations that can split various target piece widths for all available piece widths; D represents the number of target piece widths; m∈[1,K], a (D+m)j is a coefficient.

[0035] The process of obtaining the optimal target set of silicon steel sheets by solving the silicon steel sheet cutting model includes the following steps:

[0036] The silicon steel sheet nesting model is solved as a linear programming problem to obtain the optimal nesting combination, that is, the available sheet width and weight used in each feasible nesting scheme under the nesting constraints, expressed as X. j ; This represents the available piece width weight used in the j-th feasible nesting scheme, that is, the weight used to split the target piece width according to the q-th method for the p-th available piece width.

[0037] A transformer silicon steel sheet cutting optimization system based on linear programming includes:

[0038] The logic execution module is used for the nesting task of silicon steel sheets. It constructs the target set of silicon steel sheets and the set of raw materials to be processed; it abstracts the nesting task into a mathematical problem, forming a correspondence between the nesting combination schemes of the target set of silicon steel sheets and the set of raw materials to be processed; it constructs the constraints of the target sheets and raw materials to be processed; and it constructs the silicon steel sheet nesting model based on the correspondence and constraints.

[0039] The GLPK solver module is used to solve the silicon steel sheet nesting model, thereby obtaining the optimal solution for nesting silicon steel sheets using the set of raw materials to be processed onto the set of target sheets.

[0040] A transformer silicon steel sheet cutting optimization system based on linear programming is implemented using the MFC framework.

[0041] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method for optimizing the cutting of silicon steel sheets for transformers based on linear programming.

[0042] The present invention has the following beneficial effects and advantages:

[0043] 1. This invention establishes a mathematical model based on the actual characteristics of transformer tailoring tasks. By establishing a linear programming mathematical model for the tailoring problem and solving it, an optimized tailoring scheme is obtained, thereby achieving automatic optimization of the tailoring scheme and realizing the goal of cost reduction and efficiency improvement.

[0044] 2. The transformer silicon steel sheet cutting program development method provided by this invention adopts the MFC framework design, resulting in a better user experience. Except for the target sheet width and available sheet width, all other program parameters can be set to default, eliminating the need for extensive data input. Calculation results are displayed in tabular and graphical form in real time, and data export is supported, facilitating user access to the results. Furthermore, a multi-threaded programming approach is employed to improve operational efficiency.

[0045] 3. The transformer silicon steel sheet cutting program provided by this invention has been practically applied to the process of formulating silicon steel sheet cutting schemes in the core workshop. As a powerful tool for cutting workers, it helps them improve the efficiency and quality of cutting. Attached Figure Description

[0046] Figure 1 This is a flowchart of the method of the present invention;

[0047] Figure 2 This is a schematic diagram of the main interface unit of the present invention. Detailed Implementation

[0048] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0049] A method for optimizing transformer core cross-section based on linear programming includes the following steps:

[0050] 1) Assume there is a requirement for nesting silicon steel sheets as follows:

[0051] The set of target piece width and weight is [(width1, target weight1), (width2, target weight2), ..., (widthD, target weightD)].

[0052] The set of available width and weight is [(width1, available weight1), (width2, available weight2), ..., (widthK, available weightK)].

[0053] 2) Based on the requirements analysis, abstract the problem and transform the business problem into a mathematical problem.

[0054] The following uses a given available sheet width to split a given target sheet width of material. When splitting, the following rule must be met: the sum of the widths of the target sheet widths must not exceed the width of the available sheet widths used for splitting. For example, a 1000-width material can be split into a combination of 800-width and 100-width materials, or a combination of 800-width and 200-width materials, but cannot be split into a combination of 800-width and 300-width materials. The possible splitting combinations are counted and a table is generated (refer to Table 1: Silicon Steel Sheet Cutting Combinations).

[0055] Table 1. Silicon Steel Sheet Cutting Combinations

[0056]

[0057] Explanation of some contents in the table, M ji This refers to the coefficient corresponding to the combination of rows. For example, if the m-th row has a width of 1000, it can be split into two 300-pixels and one 260-pixel. Since width 2 equals 300 and width 7 equals 260, then M... m2 =2,M m7 =1,M mi =0 (where i is neither equal to 2 nor equal to 7).

[0058] This represents the coefficient corresponding to the i-th target width when performing the p-th available piece width and the q-th feasible nesting combination. n represents the total number of nesting combinations that can be split into various target widths for all available piece widths; sp represents the number of nesting combinations that can be split into different target widths for the p-th available piece width; sm represents the number of nesting combinations that can be split into different target widths for the m-th available piece width. This represents the available piece width weight used in the j-th feasible nesting scheme, that is, the weight used to split the target piece width according to the q-th method for the p-th available piece width.

[0059] Based on the requirements of nesting, the following constraints are obtained.

[0060] Constraints on target piece width (the weight of various target piece widths generated from the overlay result data cannot be less than a given value):

[0061] a 11 X1+a 12 X2 + ... + a1n X n ≥Target Weight 1

[0062] a 21 X1+a 22 X2 + ... + a 2n X n ≥Target Weight 2

[0063] …………

[0064] a D1 X1+a D2 X2 + ... + a Dn X n ≥Target weight D

[0065] Where a ij =M ji *D Width i / SW where i∈[1,D],j∈[1,n], and SW is the width of the available slice corresponding to the j-th split, as shown in the table. The corresponding available width is [width p], therefore SW at this time equals the value of [width p]. DWidth i This refers to the target width i corresponding to the target weight i. For example, if a material with a width of 1000 is split into a material with a width of 450, then SW = 1000 and DWidth = 450.

[0066] DWidth i It is the width of the i-th target slice, and D represents the number of target slice widths. The weight of the available piece width used in the j-th feasible nesting scheme is the weight used to split the target piece width in the q-th way for the p-th available piece width; n represents the total number of nesting combinations that can be split into various target piece widths for all available piece widths.

[0067] Constraints on available piece widths (the weight of all available piece widths used in the nesting result data cannot exceed a given value):

[0068] a (D+1)1 X1+a (D+1)2 X2 + ... + a (D+1)n X n ≤Useful weight 1

[0069] a (D+2)1 X1+a (D+2)2 X2 + ... + a (D+2)n X n ≤Useful weight 2

[0070] …………

[0071] a (D+K)1 X1+a(D+K)2 X2 + ... + a (D+K)n X n ≤ Available weight K

[0072] Where for a (D+m)1 X1+a (D+m)2 X2 + ... + a (D+m)n X n ≤ Available weight m, m∈[1,K], if X j The values ​​j∈[1,n] are derived from the available weight m, which can be found in "Table 1 Silicon Steel Sheet Cutting Combinations". The corresponding a... (D+m)j =1 otherwise a (D+m)j =0.

[0073] Since the goal of nesting is to maximize utilization, however It is a given value, therefore when The smaller it is, the higher its utilization rate.

[0074] 3) Establish a mathematical model

[0075] Based on the previous analysis, we can establish the following mathematical model for the cutting of silicon steel sheets:

[0076] beg minimum value

[0077] The constraints are

[0078] a 11 X1+a 12 X2 + ... + a 1n X n ≥Target Weight 1

[0079] a 21 X1+a 22 X2 + ... + a 2n X n ≥Target Weight 2

[0080] …………

[0081] a D1 X1+a D2 X2 + ... + a Dn X n ≥Target weight D

[0082] a (D+1)1 X1+a (D+1)2 X2 + ... + a (D+1)n X n ≤Useful weight 1

[0083] a (D+2)1 X1+a(D+2)2 X2 + ... + a (D+2)n X n ≤Useful weight 2

[0084] …………

[0085] a (D+K)1 X1+a (D+K)2 X2 + ... + a (D+K)n X n ≤ Available weight K

[0086] And X j ≥0j=1..n;

[0087] Note: The total number of constraints is D+K+n.

[0088] It is evident that the objective function f in this mathematical model is linear, and the D+K+n constraints are also linear. Therefore, this is a typical linear programming problem, which can be solved using methods for solving linear programming problems. The simplification method, a typical method for solving linear programming problems, can accomplish this task well.

[0089] 4) Currently, there are many software programs available for solving linear programming problems. Commercial options include Lingo and MATLAB, while open-source options include GLPK. From a cost-saving perspective, GLPK is extremely powerful in solving pure linear programming problems. However, practical applications may present numerous requirements and limitations. Appropriate techniques can be employed, such as adjusting the target quantity, the order of available quantities, and removing certain combinations. Leveraging the high performance of computers and the characteristics of computer languages ​​(e.g., multithreading), multiple nesting schemes can be calculated, and the scheme suitable for actual production needs can be selected.

[0090] like Figure 1 The diagram shown is a flowchart of the method of the present invention. The present invention provides a linear programming optimization method for the cutting and fitting of silicon steel sheets in transformers, characterized by comprising the following steps:

[0091] 1) Analyze the silicon steel sheet nesting problem, input the required silicon steel sheet slicing requirements, the available raw material requirements, and constraints such as whether the slices can be spliced ​​and cutting restrictions.

[0092] 2) Based on the current process characteristics of the workshop, the input slice data and raw material data are subjected to feasibility grouping calculations to obtain several feasible groups.

[0093] 3) Perform tailoring optimization on each set of data.

[0094] 3.1) Perform linear programming data modeling.

[0095] 3.2) The optimal solution is obtained by applying GLPK to the model.

[0096] 3.3) Post-process the optimal solution obtained from the model.

[0097] 3.4) Add the processing results to the result set and display them on the screen.

[0098] 4) After each group of results is calculated or considered to have terminated the calculation, sort the result set and display the result set.

[0099] 5) If you think the result set is sorted well, select the result that best meets your multiple goals, display it in detail, and export the information.

[0100] The transformer silicon steel sheet cutting optimization method based on linear programming of the present invention is implemented based on a transformer cutting calculation system, which includes: a main interface unit, a data input module, a logic operation module, and a GLPK solver module.

[0101] The main interface unit is based on the multi-document architecture of the MFC framework and has been expanded and encapsulated according to the interaction requirements. It is used to visualize the process of optimizing the cutting of silicon steel sheets for transformers and the results of the optimization.

[0102] The data input module includes reading in the input data. Except for the slice data and raw material data parameters, all other parameters in the program input interface are optional. For unfilled parameters, default values ​​are provided through configuration. The program reads the configuration file and assigns default values ​​to these parameters during the initial logic execution. After reading in the input data, it is converted into structured data for easier separation of data and interface, and for calculation.

[0103] The logic execution module performs logical processing on the data, establishes the data structure required for linear programming (GLPK), and calls the GLPK solver module to solve the problem and obtain the optimal solution. At the same time, it performs post-processing on the solution, converts it into a number of results that are easy to display and sort, and adds them to the result set. This module also controls the multi-threaded operation of the program.

[0104] The GLPK solver module is a modified version of the GLPK open-source project designed to meet our needs and is specifically designed to solve linear programming problems. This module is not only suitable for our project, but can also be applied to other linear programming and integer programming problems.

[0105] like Figure 2 The diagram shown is a schematic of the main interface unit of the present invention. The main interface unit includes: a function area, an input area, a parameter definition area, a result set output area, a result display area, and a process display area. The diagram provides a user-friendly operating interface.

[0106] The function area defines function buttons such as Open, Save, Execute Cutting Scheme, Terminate Calculation, Confirm Final Scheme, and User Instructions;

[0107] The input area is for inputting the slicing data and raw material data required for the program to cut the material;

[0108] The parameter definition area defines some necessary parameters for the tailoring program, which are generally default values.

[0109] The results output area displays a summary of several cutting schemes generated by the cutting software to the user. Users can click on a specific scheme to view its detailed information in the results display.

[0110] The results display area is defined to show detailed cutting data for a specific cutting scheme, including details of the cutting form and processing weight.

[0111] The canvas document is the canvas area where vector graphics of the iron core cross section are drawn, and graphic elements are rendered into this area.

[0112] The process display area shows the data analysis chart of the overlay scheme at the current calculation progress (including the end of the calculation).

[0113] See the optimized program execution flowchart. Figure 1 The specific execution process of the optimization program is explained below. After entering the main program interface, first input the data, such as slice data, raw material data, and some customized parameters (generally default). Click the "Execute Cutting Scheme" button, and then the cutting calculation will begin. During the calculation process, cutting schemes that meet the conditions will be added to the cutting result set in real time, and the cutting scheme data analysis chart will be updated and displayed.

[0114] Below is an example of nesting:

[0115] Examples of silicon steel sheet cutting requirements are shown in Tables 2 and 3:

[0116] Table 2 lists the available combinations of sheet width and weight.

[0117] width weight width weight width weight width weight 975 4473 980 7226 985 4451 990 21635 995 26571 1000 34772 1005 35784 1010 27218 1015 2527 1025 4960 - - - -

[0118] Table 3. List of Combinations of Target Piece Width and Weight

[0119] width weight width weight width weight width weight 565 8420 555 4747 545 3240 540 25162 535 2644 525 2221 520 2385 510 2747 495 2237 490 2052 480 1998 465 1719 460 1838 450 1537 440 1481 435 1434 420 2573 405 1112 400 1266 390 995 380 1147 370 1125 360 2378 350 939 340 1251 330 827 310 809 305 871 285 759 280 796 260 1900 235 477 210 387 320 5032 220 3264 - -

[0120] The nesting requirements of the silicon steel sheets above were programmed using linear programming to obtain the nesting schemes shown in Table 4 (this result was selected from many nesting schemes, and we added many restrictions to the data in the experiment. For example, the number of nesting combinations (1000 = 200 + 200 + 200 + 200 + 200, so its number of nesting combinations is equal to 5) does not exceed 3).

[0121] Table 4. List of test results for silicon steel sheet cutting.

[0122] Large material width 1 piece width 2 pieces wide 3-inch wide Large material weight 1 975 320 565 - 2170 2 975 555 420 - 1567 3 975 305 535 - 735 4 980 320 565 - 5221 5 980 540 220 220 2005 6 985 420 565 - 4451 7 990 555 435 - 3544 8 990 390 540 - 2526 9 990 280 405 220 2814 10 990 540 450 - 3555 11 990 540 360 - 6540 12 990 540 350 - 2656 13 995 310 565 - 2816 14 995 320 545 - 5915 15 995 555 440 - 3349 16 995 400 540 - 3149 17 995 305 540 - 2091 18 995 540 235 220 2437 19 995 540 380 - 3789 20 995 540 370 - 3025 21 1000 260 520 220 4587 22 1000 460 540 - 3996 23 1000 540 340 - 4143 24 1000 510 220 210 867 25 1005 320 285 330 2519 26 1005 540 465 - 3715 27 1005 480 525 - 4252 28 1005 510 495 - 4542 29 1010 260 540 210 2748 30 1025 490 535 - 4292

[0123] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, extensions, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A method for optimizing the cutting and fitting of silicon steel sheets for transformers based on linear programming, characterized in that, Includes the following steps: For the task of nesting silicon steel sheets, construct the target set of silicon steel sheets and the set of raw materials to be processed; The nesting task is abstracted into a mathematical problem, forming a correspondence between the target set of silicon steel sheets and the nesting combination scheme of the raw materials to be processed; Construct constraints for the target cut piece and the raw material to be processed; Construct a silicon steel sheet cutting model based on the correspondence and constraints; Solving the silicon steel sheet nesting model yields the optimal solution for nesting silicon steel sheets using the set of raw materials to be processed onto the target set of cut sheets.

2. The method for optimizing the cutting and fitting of silicon steel sheets for transformers based on linear programming according to claim 1, characterized in that, The task of nesting silicon steel sheets involves constructing a target set of cut silicon steel sheets and a set of raw materials to be processed, as detailed below: The target cut piece set includes the target piece width and its weight: 【(Width 1, Target Weight 1), (Width 2, Target Weight 2), ..., (Width D, Target Weight D)】; D represents the number of target slices; The set of raw materials to be processed includes the available sheet width and its weight: 【(Width 1, Available Weight 1), (Width 2, Available Weight 2), ..., (Width K, Available Weight K)】, where K represents the number of available sheet widths.

3. The method for optimizing the cutting and fitting of silicon steel sheets for transformers based on linear programming according to claim 1, characterized in that, The process of abstracting the nesting task into a mathematical problem, and establishing the correspondence between the target set of silicon steel sheets and the set of raw materials to be processed in nesting combination schemes, includes the following steps: Construct a table of nesting combinations of target piece width and available piece width; the coefficients corresponding to the rows and columns express the correspondence between the nesting combination schemes of target piece width and available piece width; The rows represent the nesting combinations that can be split into each target width for a given available piece width; the columns represent the width of the target piece width and the weight of the nesting combination.

4. The method for optimizing the cutting and fitting of silicon steel sheets for transformers based on linear programming according to claim 3, characterized in that, The correspondence between the target piece width and the available piece width tailoring combination scheme is expressed as M. ji Meanwhile, the available piece width and weight used in each feasible nesting scheme are expressed as X. j ; in, This represents the coefficient corresponding to the i-th target width when performing the p-th available piece width and the q-th feasible nesting combination. n represents the total number of nesting combinations that can be split into various target widths for all available piece widths; sp represents the number of nesting combinations that can be split into different target widths for the p-th available piece width; sm represents the number of nesting combinations that can be split into different target widths for the m-th available piece width. This represents the available piece width weight used in the j-th feasible nesting scheme, that is, the weight used to split the target piece width according to the q-th method for the p-th available piece width.

5. The method for optimizing the cutting and fitting of silicon steel sheets for transformers based on linear programming according to claim 1, characterized in that, The specific constraints on the target cut piece are as follows: a i1 X1+a i2 X2+...a ij X j +...+a in X n ≥Target weight i Wherein, coefficient a ij =M ji *D Width i / SW, i∈[1,D],j∈[1,n]; SW represents the width of the available slice corresponding to the j-th split; DWidth i It is the width of the i-th target slice, and D represents the number of target slice widths. The weight of the available piece width used in the j-th feasible nesting scheme is the weight used to split the target piece width in the q-th way for the p-th available piece width; n represents the total number of nesting combinations that can be split into various target piece widths for all available piece widths.

6. The method for optimizing the cutting and fitting of silicon steel sheets for transformers based on linear programming according to claim 1, characterized in that, The constraints on the available slice width are as follows: a (D+m)1 X1+a (D+m)2 X2 + ... + a (D+m)j X j +...+a (D+m)n X n ≤ Available weight m Where m∈[1,K], and D represents the target slice width. This represents the weight of the available piece width used in the j-th feasible nesting scheme, i.e., the weight used to split the target piece width according to the q-th method for the p-th available piece width; n represents the total number of nesting combinations that can be split into various target piece widths for all available piece widths; a (D+m)j Let j be the coefficient, and j∈[1,n].

7. The method for optimizing the cutting and fitting of silicon steel sheets for transformers based on linear programming according to claim 1, characterized in that, The silicon steel sheet nesting model is constructed based on the correspondence and constraints: beg The minimum value; The constraints are: a i1 X1+a i2 X2+...a ij X j +...+a in X n ≥Target weight i a (D+m)1 X1+a (D+m)2 X2 + ... + a (D+m)j X j +...+a (D+m)n X n ≤ Available weight m And X j ≥0; Wherein, coefficient a ij =M ji *DWidth i / SW, This represents the coefficient corresponding to the i-th target piece width when performing the p-th available piece width and the q-th feasible nesting combination. n represents the total number of nesting combinations that can be split into various target widths for all available piece widths; sm represents the number of nesting combinations that can be split into different target widths for the m-th available piece width; The weight of the available piece width used in the j-th feasible nesting scheme is the weight used to split the target piece width according to the q-th method for the p-th available piece width; n represents the total number of nesting combinations that can split various target piece widths for all available piece widths; D represents the number of target piece widths; m∈[1,K], a (D+m)j is a coefficient.

8. The method for optimizing the cutting and fitting of silicon steel sheets for transformers based on linear programming according to claim 1, characterized in that, The process of obtaining the optimal target set of silicon steel sheets by solving the silicon steel sheet cutting model includes the following steps: The silicon steel sheet nesting model is solved as a linear programming problem to obtain the optimal nesting combination, that is, the available sheet width and weight used in each feasible nesting scheme under the nesting constraints, expressed as X. j ; This represents the available piece width weight used in the j-th feasible nesting scheme, that is, the weight used to split the target piece width according to the q-th method for the p-th available piece width.

9. A transformer silicon steel sheet cutting optimization system based on linear programming, characterized in that, include: The logic execution module is used for the nesting task of silicon steel sheets, and constructs the target set of silicon steel sheets and the set of raw materials to be processed; The nesting task is abstracted into a mathematical problem, forming a correspondence between the target set of silicon steel sheets and the set of raw materials to be processed in the nesting combination scheme; the constraints of the target sheets and the raw materials to be processed are constructed; and a silicon steel sheet nesting model is constructed based on the correspondence and constraints. The GLPK solver module is used to solve the silicon steel sheet nesting model, thereby obtaining the optimal solution for nesting silicon steel sheets using the set of raw materials to be processed onto the set of target sheets.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements a method for optimizing the cutting of silicon steel sheets for transformers based on linear programming as described in any one of claims 1-8.

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