Numerical control cutting platform for ship steel structure machining
By using a CNC cutting platform in the machining of ship steel structures, the problems of low cutting efficiency, poor accuracy and complex operation in the cutting methods of ship steel structures in the prior art are solved, and higher cutting accuracy and efficiency are achieved.
Patent Information
- Application Number
- CN202411949057.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-27
- Publication Date
- 2025-05-16
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In the prior art, the cutting method of ship steel structures has problems such as low cutting efficiency, poor accuracy and complex operation.
It provides a CNC cutting platform for marine steel structure processing, including CNC cutting task acquisition module, cutting condition construction module, cutting factor optimization analysis module, CNC cutting first-order optimization module, CNC cutting second-order optimization module and CNC cutting module. Through these modules, high-precision and high-efficiency cutting conditions are achieved.
It improves the cutting accuracy and efficiency of the ship's steel structure, reduces burrs and other defects generated during the cutting process, and achieves better cutting quality.
Smart Images
Figure CN120010389A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of CNC cutting, and in particular to a CNC cutting platform for processing ship steel structures. Background Art
[0002] In the shipbuilding industry, the cutting of ship steel structures is a key process. The traditional ship steel structure cutting method is manual line cutting or semi-automatic cutting. Manual operation and semi-mechanical control are difficult to ensure high-precision cutting, especially in the cutting of complex-shaped steel. The error is large, and a large number of burrs and irregular cuts will be generated, which increases the difficulty and cost of subsequent processing, reduces cutting efficiency, and is difficult to meet the high-precision and high-efficiency requirements of modern shipbuilding.
[0003] Therefore, the ship steel structure cutting method in the prior art has the technical problems of low cutting efficiency, poor precision and complicated operation. Summary of the invention
[0004] This application solves the technical problems of low cutting efficiency, poor precision and complicated operation in the existing ship steel structure cutting method by providing a CNC cutting platform for ship steel structure processing. It improves the cutting precision and efficiency of ship steel structure, reduces burrs and other defects generated during the cutting process, and achieves a technical effect of better cutting quality.
[0005] The present application provides a CNC cutting platform for ship steel structure processing, the platform comprising: a CNC cutting task acquisition module, the CNC cutting task acquisition module is used to obtain CNC cutting task information, wherein the CNC cutting task information includes the target ship steel structure raw material and the target ship steel structure cutting expectation. A cutting condition construction module, the cutting condition construction module is used to construct CNC cutting constraints and CNC cutting expectation conditions based on the CNC cutting task information. A cutting factor optimization analysis module, the cutting factor optimization analysis module is used to perform optimization analysis on the CNC cutting factor based on the CNC cutting constraints and the CNC cutting expectation conditions, and determine the CNC cutting optimization source. A CNC cutting first-order optimization module, the CNC cutting first-order optimization module is based on the embedded CNC cutting first-order optimization formula, combines the CNC cutting constraints and the CNC cutting expectation conditions to perform optimization analysis on the CNC cutting optimization source, and obtains the CNC cutting first-order optimization result. A numerical control cutting second-order optimization module, the numerical control cutting second-order optimization module is used to perform optimization analysis on the numerical control cutting first-order optimization result according to the numerical control cutting second-order optimization condition and the numerical control cutting optimization source to obtain the numerical control cutting second-order optimization result. A numerical control cutting module, the numerical control cutting module is used to perform numerical control cutting on the target ship steel structure raw material based on the numerical control cutting second-order optimization result.
[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: The CNC cutting platform for ship steel structure processing provided in the present application includes: a CNC cutting task acquisition module, the CNC cutting task acquisition module is used to obtain CNC cutting task information, wherein the CNC cutting task information includes the target ship steel structure raw material and the target ship steel structure cutting expectation. A cutting condition construction module, the cutting condition construction module is used to construct CNC cutting constraints and CNC cutting expectation conditions based on the CNC cutting task information. A cutting factor optimization analysis module, the cutting factor optimization analysis module is used to perform optimization analysis on the CNC cutting factor based on the CNC cutting constraints and the CNC cutting expectation conditions, and determine the CNC cutting optimization source. A CNC cutting first-order optimization module, the CNC cutting first-order optimization module is based on the embedded CNC cutting first-order optimization formula, and combines the CNC cutting constraints and the CNC cutting expectation conditions to perform optimization analysis on the CNC cutting optimization source to obtain the CNC cutting first-order optimization result. A second-order optimization module for numerically controlled cutting, the second-order optimization module for numerically controlled cutting is used to perform optimization analysis on the first-order optimization result of numerically controlled cutting according to the second-order optimization conditions for numerically controlled cutting and the optimization source for numerically controlled cutting, so as to obtain the second-order optimization result of numerically controlled cutting. A numerically controlled cutting module, the numerically controlled cutting module is used to perform numerically controlled cutting on the target ship steel structure raw material based on the second-order optimization result of numerically controlled cutting. The technical problems of low cutting efficiency, poor precision and complex operation in the existing ship steel structure cutting method are solved. The cutting precision and efficiency of ship steel structures are improved, and burrs and other defects generated during the cutting process are reduced, so as to achieve a technical effect of better cutting quality. BRIEF DESCRIPTION OF THE DRAWINGS
[0007] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention are briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the platform according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.
[0008] Figure 1 A schematic diagram of the structure of a CNC cutting platform for ship steel structure processing provided in an embodiment of the present application; Figure 2 A schematic diagram of the process of determining the CNC cutting optimization source in the cutting factor optimization analysis module in the CNC cutting platform used for ship steel structure processing in this application.
[0009] Explanation of the accompanying drawings: CNC cutting task acquisition module 11, cutting condition construction module 12, cutting factor optimization analysis module 13, CNC cutting first-order optimization module 14, CNC cutting second-order optimization module 15, CNC cutting module 16. DETAILED DESCRIPTION
[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.
[0011] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.
[0012] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, platform, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, platforms, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.
[0013] The embodiment of the present application provides a CNC cutting platform for ship steel structure processing, such as Figure 1 As shown, the platform includes: The numerical control cutting task acquisition module 11 is used to obtain numerical control cutting task information, wherein the numerical control cutting task information includes the target ship steel structure raw material and the target ship steel structure cutting expectation.
[0014] The cutting condition building module 12 is used to build numerical control cutting constraint conditions and numerical control cutting expected conditions based on the numerical control cutting task information.
[0015] The cutting factor optimization analysis module 13 is used to perform optimization analysis on the numerical control cutting factor based on the numerical control cutting constraint condition and the numerical control cutting expected condition, and determine the numerical control cutting optimization source.
[0016] The numerical control cutting task information is obtained through the numerical control cutting task acquisition module 11, and the numerical control cutting task information is input based on the user end. Among them, the numerical control cutting task information includes the target ship steel structure raw material and the target ship steel structure cutting expectation. The target ship steel structure raw material is steel raw material information including characteristic parameters such as steel strength and steel thickness. The target ship steel structure cutting expectation is the final steel cutting expected cutting size, efficiency, i.e., single cutting time, and surface quality. The surface quality is identified by specific parameters, such as the surface quality parameter corresponding to the surface quality flatness and less burrs is 80. There are corresponding quality parameter values for different surface quality characteristics. The surface quality parameters can be obtained after the surface characteristics are evaluated by professional technicians. Subsequently, the cutting condition construction module 12 constructs numerical control cutting constraints and numerical control cutting expectation conditions based on the numerical control cutting task information. The numerical control cutting constraints are obtained based on the target ship steel structure. The numerical control cutting constraints are constraints based on steel characteristic parameters such as steel strength and thickness, which are used to constrain the control parameter range of the numerical control cutting task. The desired conditions for numerical control cutting are obtained based on the desired cutting of the target ship steel structure, and the desired conditions for numerical control cutting include all the desired conditions for the target ship steel structure cutting, such as the desired parameters for cutting size, the desired parameters for efficiency, and the desired parameters for surface quality. Further, the numerical control cutting factors are optimized based on the numerical control cutting constraints and the desired conditions for numerical control cutting by the cutting factor optimization analysis module 13. The numerical control cutting factors are multiple cutting control indicators such as laser cutting power, cutting speed, cutting gap, and other cutting control indicators. The numerical control cutting optimization source is determined. The numerical control cutting optimization source is the parameter control interval of the numerical control cutting machine cutting control indicators composed of multiple cutting control parameters that meet the requirements in the ship steel structure cutting record set.
[0017] Further, such as Figure 2 As shown, the cutting factor optimization analysis module 13 is also used to: retrieve a ship steel structure cutting record set. Perform CNC cutting feature registration on the ship steel structure cutting record set according to the CNC cutting constraint condition and the CNC cutting expected condition to obtain a CNC cutting parameter registration source. Perform feature integration on the CNC cutting parameter registration source according to the CNC cutting factor to generate the CNC cutting optimization source.
[0018] Determine the CNC cutting optimization source, including: retrieve the ship steel structure cutting record set, the ship steel structure cutting record set contains historical ship steel cutting record data, the historical ship steel cutting record data contains historical raw material information, historical cutting results, and historical cutting decision data. The historical cutting results contain the final cutting size, efficiency, and surface quality data. Perform CNC cutting feature registration on the ship steel structure cutting record set according to the CNC cutting constraints and the CNC cutting expected conditions to obtain a CNC cutting parameter registration source, which is the cutting decision data corresponding to the registration data in the ship steel structure cutting record set. Finally, perform feature integration on the CNC cutting parameter registration source according to the CNC cutting factor, obtain the parameter control interval of the CNC cutting factor composed of the cutting decision data of the CNC cutting parameter registration source, and generate the CNC cutting optimization source, that is, the parameter control interval of the cutting control index.
[0019] Furthermore, the cutting factor optimization analysis module 13 is also used to: perform registration and identification on the ship steel structure cutting record set according to the numerical control cutting constraint conditions to obtain a plurality of cutting constraint registration coefficients.
[0020] The ship steel structure cutting record set is registered and identified according to the desired numerical control cutting conditions to obtain a plurality of desired cutting registration coefficients.
[0021] The plurality of cutting constraint registration coefficients and the plurality of cutting expectation registration coefficients are weightedly calculated according to the cutting feature registration weight condition to generate a plurality of cutting feature registration indexes.
[0022] Based on the cutting feature registration threshold, the cutting parameters of the ship steel structure cutting record set are selected in combination with the multiple cutting feature registration indexes to generate the numerical control cutting parameter registration source.
[0023] Obtaining the CNC cutting parameter registration source includes: according to the CNC cutting constraint conditions, registering and identifying the historical raw material information of each record data in the ship steel structure cutting record set, respectively calculating the deviation ratio of the CNC cutting constraint conditions and the corresponding parameters of the historical raw material information, taking the steel thickness as an example, the deviation ratio calculation process is as follows: calculating the absolute value of the difference between the steel thickness in the CNC cutting constraint conditions and the steel thickness in the historical raw material information, obtaining the ratio result of the absolute value and the steel thickness in the CNC cutting constraint conditions, and finally subtracting the ratio result from 1 to obtain the deviation ratio of the steel thickness, respectively calculating the deviation ratio of all features in the CNC cutting constraint conditions, and performing sum calculation to obtain a cutting constraint registration coefficient. Calculating the cutting constraint registration coefficient for multiple data in the ship steel structure cutting record set to obtain multiple cutting constraint registration coefficients. According to the expected numerical control cutting conditions, the ship steel structure cutting record set is registered and identified, and the deviation ratios of the expected numerical control cutting conditions and the corresponding parameters in the historical cutting results of the ship steel structure cutting record set are calculated and summed to obtain an expected cutting registration coefficient. The expected cutting registration coefficients are calculated for multiple data in the ship steel structure cutting record set to obtain multiple expected cutting registration coefficients. Among them, the expected cutting registration coefficients and the cutting constraint registration coefficients correspond one to one. According to the cutting feature registration weight conditions, the multiple cutting constraint registration coefficients and the multiple expected cutting registration coefficients are weighted and summed to generate multiple cutting feature registration indexes, and each cutting feature registration index has corresponding historical cutting decision data recorded in the ship steel structure cutting record set. Among them, the weights of the cutting constraint registration coefficient and the expected cutting registration coefficient are set based on the actual parameter preference, and the default weights of both are 0.5. Finally, based on the cutting feature registration threshold, the cutting parameters of the ship steel structure cutting record set are selected in combination with the multiple cutting feature registration indexes, that is, multiple historical cutting decision data corresponding to multiple cutting feature registration indexes greater than or equal to the cutting feature registration threshold are obtained to generate the CNC cutting parameter registration source. The cutting feature registration threshold is the minimum cutting feature registration index requirement that meets the data similarity. When the cutting feature registration index is greater than or equal to the cutting feature registration threshold, the corresponding number of cutting records has a strong reference value.
[0024] The first-order optimization module 14 for numerically controlled cutting performs optimization analysis on the numerically controlled cutting optimization source based on the embedded first-order optimization formula for numerically controlled cutting in combination with the numerically controlled cutting constraint conditions and the numerically controlled cutting expected conditions to obtain the first-order optimization result for numerically controlled cutting.
[0025] The numerical control cutting second-order optimization module 15 is used to perform optimization analysis on the numerical control cutting first-order optimization result according to the numerical control cutting second-order optimization condition and the numerical control cutting optimization source to obtain the numerical control cutting second-order optimization result.
[0026] The CNC cutting module 16 is used to perform CNC cutting on the target ship steel structure raw material based on the CNC cutting second-order optimization result.
[0027] Through the first-order optimization formula of numerical control cutting embedded in the first-order optimization module 14, the numerical control cutting optimization source is optimized and analyzed in combination with the numerical control cutting constraint conditions and the numerical control cutting expected conditions, and the first-order optimization result of numerical control cutting is obtained, and the first-order optimization result of numerical control cutting includes multiple optimization results. Subsequently, through the second-order optimization module 15 of numerical control cutting, the first-order optimization result of numerical control cutting is optimized and analyzed according to the second-order optimization conditions of numerical control cutting and the numerical control cutting optimization source, and the optimization result of the control scheme with the minimum loss coefficient is extracted to obtain the second-order optimization result of numerical control cutting. Finally, the numerical control cutting module 16 controls the numerical control cutting machine tool to perform numerical control cutting on the target ship steel structure raw material based on the second-order optimization result of numerical control cutting. The technical problems of low cutting efficiency, poor precision and complex operation in the ship steel structure cutting method in the prior art are solved. The cutting precision and efficiency of ship steel structure are improved, and the burrs and other defects generated during the cutting process are reduced, so as to achieve the technical effect of better cutting quality.
[0028] Furthermore, the first-order optimization module 14 for numerically controlled cutting is also used to: generate a first numerically controlled cutting decision according to the numerically controlled cutting optimization source. Based on the numerically controlled cutting constraints, the numerically controlled cutting desired conditions and the first numerically controlled cutting decision, calculate the first cutting loss coefficient according to the first-order optimization formula for numerically controlled cutting. Determine whether the first cutting loss coefficient is less than the predetermined cutting loss coefficient. If the first cutting loss coefficient is less than the predetermined cutting loss coefficient, add the first numerically controlled cutting decision to the first-order optimization result of the numerically controlled cutting. If the first cutting loss coefficient is greater than / equal to the predetermined cutting loss coefficient, eliminate the first numerically controlled cutting decision. According to the predetermined cutting loss coefficient and the first-order optimization formula for numerically controlled cutting, the numerically controlled cutting optimization source is continuously optimized and analyzed in combination with the numerically controlled cutting constraints and the numerically controlled cutting desired conditions to generate the first-order optimization result of the numerically controlled cutting that meets the first-order optimization conditions for numerically controlled cutting.
[0029] Obtaining the first-order optimization result of numerical control cutting includes: generating a first numerical control cutting decision according to the numerical control cutting optimization source, wherein the first numerical control cutting decision is a numerical control cutting control parameter decision scheme randomly selected from a plurality of cutting control index control intervals in the numerical control cutting optimization source. Based on the numerical control cutting constraint condition, the numerical control cutting expected condition and the first numerical control cutting decision, the first cutting loss coefficient is calculated according to the first-order optimization formula of numerical control cutting. Further, judging whether the first cutting loss coefficient is less than a predetermined cutting loss coefficient, wherein the predetermined cutting loss coefficient is the maximum cutting coefficient loss of the simulation result that meets the expected condition of numerical control cutting, and when it is greater than the predetermined cutting loss coefficient, the cutting simulation result is poor and cannot meet the expected condition of numerical control cutting. If the first cutting loss coefficient is less than the predetermined cutting loss coefficient, the first numerical control cutting decision is added to the first-order optimization result of numerical control cutting. If the first cutting loss coefficient is greater than / equal to the predetermined cutting loss coefficient, the first numerical control cutting decision is eliminated. Further, the above steps are executed in a loop, and the CNC cutting optimization source is continuously iterated for optimization analysis according to the predetermined cutting loss coefficient and the first-order optimization formula of CNC cutting, combined with the CNC cutting constraint conditions and the expected conditions of CNC cutting, and the first CNC cutting decision is continuously generated, and a cutting decision judgment is performed to obtain a CNC cutting decision that meets the first-order optimization conditions of CNC cutting, that is, the cutting loss coefficient is less than the predetermined cutting loss coefficient, until the preset number of iterations is met, and the first-order optimization result of CNC cutting is obtained, and the first-order optimization result of CNC cutting includes multiple optimization results that meet the requirements.
[0030] Furthermore, the first-order optimization module 14 for numerically controlled cutting is also used to: construct a ship steel structure raw material model according to the numerically controlled cutting constraints. Perform simulated cutting on the ship steel structure raw material model according to the first numerically controlled cutting decision to generate a first raw material simulation cutting result, wherein the first raw material simulation cutting result includes the first simulated cutting after-dimension feature information, the first simulated cutting efficiency feature information and the first simulated cutting surface quality information. Activate a cutting loss evaluation channel, wherein the cutting loss evaluation channel includes a cutting dimension accuracy loss evaluation branch, a cutting efficiency loss evaluation branch and a cutting surface quality loss evaluation branch. Based on the numerically controlled cutting expected conditions and the first raw material simulation cutting result, output a first cutting loss evaluation result according to the cutting loss evaluation channel. Input the first cutting loss evaluation result into the first-order optimization formula for numerically controlled cutting to generate the first cutting loss coefficient.
[0031] Calculating the first cutting loss coefficient includes: constructing a ship steel structure raw material model according to the numerical control cutting constraint condition, the ship steel structure raw material model is a simulation model of steel, and the ship steel structure raw material model is modeled by finite element analysis (FEA) software. Subsequently, the ship steel structure raw material model is simulated cut according to the first numerical control cutting decision, the simulated cutting is designed based on CAD software, the simulation process is the simulated cutting process in the prior art, the ship steel structure raw material model is simulated to simulate the cutting process, and the first raw material simulation cutting result is generated, wherein the first raw material simulation cutting result includes the first simulated cutting after dimensional feature information, the first simulated cutting efficiency feature information and the first simulated cutting surface quality information. Activate the cutting loss evaluation channel, wherein the cutting loss evaluation channel includes a cutting dimensional accuracy loss evaluation branch, a cutting efficiency loss evaluation branch and a cutting surface quality loss evaluation branch. The cutting size accuracy loss evaluation branch, cutting efficiency loss evaluation branch and cutting surface quality loss evaluation branch are respectively used to calculate the deviation ratio of the size, efficiency and surface quality between the first raw material simulation cutting result and the expected conditions for CNC cutting. The deviation ratio is the ratio of the absolute value of the difference between each parameter in the first raw material simulation cutting result and the expected conditions for CNC cutting to each parameter of the expected conditions for CNC cutting, and the loss evaluation coefficient of each parameter is obtained. The loss evaluation coefficient includes the cutting size accuracy loss evaluation coefficient, the cutting efficiency loss evaluation coefficient and the cutting surface quality loss evaluation coefficient.
[0032] Based on the expected conditions for numerical control cutting and the first raw material simulation cutting result, the loss evaluation coefficients of each parameter are obtained according to the cutting loss evaluation channel, and the first cutting loss evaluation result is output, which includes the cutting size accuracy loss evaluation coefficient, the cutting efficiency loss evaluation coefficient, and the cutting surface quality loss evaluation coefficient. The first cutting loss evaluation result is input into the first-order optimization formula of numerical control cutting to generate the first cutting loss coefficient.
[0033] The first-order optimization formula for numerical control cutting is: .
[0034] Among them, L represents the cutting loss coefficient, g(x) represents the normalized cutting size accuracy loss evaluation coefficient, g(y) represents the normalized cutting efficiency loss evaluation coefficient, g(z) represents the normalized cutting surface quality loss evaluation coefficient, a, b, c represent the predetermined optimization calculation gain conditions, a, b, c are all positive numbers, and the sum of a, b, c is 1. The predetermined optimization calculation gain conditions are set based on the preference expectation. For example, if the preference expectation for efficiency is higher, the corresponding b optimization calculation gain condition has a higher value.
[0035] Furthermore, the CNC cutting second-order optimization module 15 is also used for: the CNC cutting second-order optimization condition includes a predetermined cutting variation capacity. Based on the predetermined cutting variation capacity, the variation capacity of the CNC cutting first-order optimization result is allocated to obtain a plurality of variation allocation capacities. Based on the CNC cutting optimization source, the CNC cutting first-order optimization result is mutated according to the plurality of variation allocation capacities to obtain a plurality of CNC cutting variation clusters. Cutting loss minimization optimization is performed according to the CNC cutting first-order optimization result and the plurality of CNC cutting variation clusters to generate the CNC cutting second-order optimization result.
[0036] Obtaining the second-order optimization result of numerical control cutting includes: the second-order optimization condition of numerical control cutting includes a predetermined cutting variation capacity, and the predetermined cutting variation capacity is the number of parameter variations to be performed on the first-order optimization result of numerical control cutting. Based on the predetermined cutting variation capacity, the variation capacity of each optimization result of the first-order optimization result of numerical control cutting is allocated to obtain multiple variation allocation capacities.
[0037] Taking the first optimization result in the first-order optimization result of CNC cutting as an example, the calculation formula of the variation allocation capacity of the first optimization result is:
[0038] Among them, L is the cutting loss coefficient of each result in the first-order optimization result of numerical control cutting, L1 is the cutting loss coefficient of the first result in the first-order optimization result of numerical control cutting, n is the total number of optimization results in the first-order optimization result of numerical control cutting, S is the predetermined cutting variation capacity, and the variation allocation capacity of the first optimization result is obtained by rounding down the result calculated based on the formula. The variation allocation capacity of the second optimization result is obtained in sequence until the variation allocation capacity of the nth optimization result.
[0039] Based on the CNC cutting optimization source, the first-order optimization result of the CNC cutting is subjected to data mutation according to the multiple variation allocation capacities, that is, each first-order optimization result is subjected to data mutation according to the corresponding variation allocation capacity, and the data mutation should be within the parameter constraint range of the CNC cutting optimization source, and multiple CNC cutting variation clusters are obtained. Finally, the cutting loss coefficient is obtained according to the first-order optimization result of the CNC cutting and the multiple CNC cutting variation clusters, and the loss coefficients of the multiple CNC cutting variation clusters are sorted, the control scheme optimization result with the minimum loss coefficient is extracted, the cutting loss minimization optimization is completed, and the second-order optimization result of the CNC cutting is generated.
[0040] Furthermore, the CNC cutting second-order optimization module 15 is also used to: extract the first variation allocation capacity and the first CNC cutting benchmark scheme according to the multiple variation allocation capacities and the CNC cutting first-order optimization result. Adjust the first CNC cutting benchmark scheme based on the CNC cutting optimization source to generate a first benchmark cutting adjustment scheme. Perform cutting loss verification according to the first benchmark cutting adjustment scheme, generate a first benchmark cutting variation scheme, and add the first benchmark cutting variation scheme to the first CNC cutting variation cluster. Continue to adjust the first CNC cutting benchmark scheme and perform cutting loss verification according to the CNC cutting optimization source until the first CNC cutting variation cluster that meets the first variation allocation capacity is generated.
[0041] According to the multiple variation allocation capacities and the first-order optimization result of the CNC cutting, the first variation allocation capacity and the first CNC cutting benchmark scheme are extracted. The first CNC cutting benchmark scheme is the first-order optimization result corresponding to the first variation allocation capacity in the first-order optimization result of the CNC cutting. The first CNC cutting benchmark scheme is randomly adjusted based on the CNC cutting optimization source to generate a first benchmark cutting adjustment scheme. According to the first benchmark cutting adjustment scheme, a cutting loss check is performed to determine whether the cutting loss coefficient of the first benchmark cutting adjustment scheme is less than the predetermined cutting loss coefficient. If it is less, a first benchmark cutting variation scheme is generated, and the first benchmark cutting variation scheme is added to the first CNC cutting variation cluster. According to the CNC cutting optimization source, the first CNC cutting benchmark scheme is continued to be adjusted and the cutting loss check is performed until the first CNC cutting variation cluster that meets the first variation allocation capacity is generated.
[0042] The CNC cutting platform for ship steel structure processing provided in the embodiment of the present application includes: a CNC cutting task acquisition module, the CNC cutting task acquisition module is used to obtain CNC cutting task information, wherein the CNC cutting task information includes the target ship steel structure raw material and the target ship steel structure cutting expectation. A cutting condition construction module, the cutting condition construction module is used to construct CNC cutting constraints and CNC cutting expectation conditions based on the CNC cutting task information. A cutting factor optimization analysis module, the cutting factor optimization analysis module is used to perform optimization analysis on the CNC cutting factor based on the CNC cutting constraints and the CNC cutting expectation conditions, and determine the CNC cutting optimization source. A CNC cutting first-order optimization module, the CNC cutting first-order optimization module is based on the embedded CNC cutting first-order optimization formula, and combines the CNC cutting constraints and the CNC cutting expectation conditions to perform optimization analysis on the CNC cutting optimization source to obtain the CNC cutting first-order optimization result. A second-order optimization module for numerically controlled cutting, the second-order optimization module for numerically controlled cutting is used to perform optimization analysis on the first-order optimization result of numerically controlled cutting according to the second-order optimization conditions for numerically controlled cutting and the optimization source for numerically controlled cutting, so as to obtain the second-order optimization result of numerically controlled cutting. A numerically controlled cutting module, the numerically controlled cutting module is used to perform numerically controlled cutting on the target ship steel structure raw material based on the second-order optimization result of numerically controlled cutting. The technical problems of low cutting efficiency, poor precision and complex operation in the existing ship steel structure cutting method are solved. The cutting precision and efficiency of ship steel structures are improved, and burrs and other defects generated during the cutting process are reduced, so as to achieve a technical effect of better cutting quality.
[0043] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
Claims
1. CNC cutting platform for ship steel structure processing, characterized by: The platform includes: A numerical control cutting task acquisition module, wherein the numerical control cutting task acquisition module is used to obtain numerical control cutting task information, wherein the numerical control cutting task information includes the target ship steel structure raw material and the target ship steel structure cutting expectation; A cutting condition building module, wherein the cutting condition building module is used to build numerical control cutting constraint conditions and numerical control cutting expected conditions based on the numerical control cutting task information; A cutting factor optimization analysis module, wherein the cutting factor optimization analysis module is used to perform optimization analysis on the numerical control cutting factor based on the numerical control cutting constraint condition and the numerical control cutting desired condition, and determine the numerical control cutting optimization source; A first-order optimization module for numerical control cutting, wherein the first-order optimization module for numerical control cutting performs optimization analysis on the numerical control cutting optimization source based on an embedded first-order optimization formula for numerical control cutting in combination with the numerical control cutting constraint conditions and the numerical control cutting desired conditions, and obtains a first-order optimization result for numerical control cutting; A second-order optimization module for numerically controlled cutting, wherein the second-order optimization module for numerically controlled cutting is used to perform optimization analysis on the first-order optimization result of numerically controlled cutting according to the second-order optimization condition for numerically controlled cutting and the optimization source for numerically controlled cutting, so as to obtain the second-order optimization result of numerically controlled cutting; A numerical control cutting module is used to perform numerical control cutting on the target ship steel structure raw material based on the numerical control cutting second-order optimization result.
2. The platform according to claim 1, characterized in that The cutting factor optimization analysis module is used to perform optimization analysis on the numerical control cutting factor based on the numerical control cutting constraint condition and the numerical control cutting expected condition, and determine the numerical control cutting optimization source, including: Retrieve the ship steel structure cutting record set; Performing CNC cutting feature registration on the ship steel structure cutting record set according to the CNC cutting constraint condition and the CNC cutting expected condition to obtain a CNC cutting parameter registration source; The numerical control cutting parameter registration source is feature integrated according to the numerical control cutting factor to generate the numerical control cutting optimization source.
3. The platform according to claim 2, characterized in that According to the numerical control cutting constraint condition and the numerical control cutting expected condition, the numerical control cutting feature registration is performed on the ship steel structure cutting record set to obtain a numerical control cutting parameter registration source, including: According to the numerical control cutting constraint conditions, the ship steel structure cutting record set is registered and identified to obtain a plurality of cutting constraint registration coefficients; According to the desired numerical control cutting conditions, the ship steel structure cutting record set is registered and identified to obtain a plurality of desired cutting registration coefficients; Performing weighted calculation on the plurality of cutting constraint registration coefficients and the plurality of cutting desired registration coefficients according to the cutting feature registration weight condition to generate a plurality of cutting feature registration indexes; Based on the cutting feature registration threshold, the cutting parameters of the ship steel structure cutting record set are selected in combination with the multiple cutting feature registration indexes to generate the numerical control cutting parameter registration source.
4. The platform according to claim 1, characterized in that The first-order optimization module for numerical control cutting performs optimization analysis on the numerical control cutting optimization source based on the embedded first-order optimization formula for numerical control cutting in combination with the numerical control cutting constraint conditions and the numerical control cutting desired conditions to obtain the first-order optimization result for numerical control cutting, including: Generating a first numerical control cutting decision according to the numerical control cutting optimization source; Based on the numerical control cutting constraint condition, the numerical control cutting desired condition and the first numerical control cutting decision, and according to the numerical control cutting first-order optimization formula, a first cutting loss coefficient is calculated; determining whether the first cutting loss coefficient is less than a predetermined cutting loss coefficient; If the first cutting loss coefficient is less than the predetermined cutting loss coefficient, adding the first numerical control cutting decision to the first-order optimization result of the numerical control cutting; If the first cutting loss coefficient is greater than / equal to the predetermined cutting loss coefficient, the first numerical control cutting decision is eliminated; According to the predetermined cutting loss coefficient and the first-order optimization formula of CNC cutting, the CNC cutting optimization source is further optimized and analyzed in combination with the CNC cutting constraint conditions and the CNC cutting expected conditions, so as to generate the first-order optimization result of CNC cutting that meets the first-order optimization conditions of CNC cutting.
5. The platform according to claim 4, characterized in that Based on the numerical control cutting constraint condition, the numerical control cutting desired condition and the first numerical control cutting decision, according to the numerical control cutting first-order optimization formula, a first cutting loss coefficient is calculated, including: According to the numerical control cutting constraint conditions, a raw material model of the ship steel structure is constructed; Performing simulated cutting on the ship steel structure raw material model according to the first numerical control cutting decision to generate a first raw material simulated cutting result, wherein the first raw material simulated cutting result includes first simulated cutting size feature information, first simulated cutting efficiency feature information, and first simulated cutting surface quality information; Activating a cutting loss evaluation channel, wherein the cutting loss evaluation channel includes a cutting size accuracy loss evaluation branch, a cutting efficiency loss evaluation branch, and a cutting surface quality loss evaluation branch; Based on the expected numerical control cutting conditions and the first raw material simulation cutting result, outputting a first cutting loss evaluation result according to the cutting loss evaluation channel; The first cutting loss evaluation result is input into the first-order optimization formula for numerical control cutting to generate the first cutting loss coefficient.
6. The platform according to claim 1, characterized in that The first-order optimization formula for numerical control cutting is: ； Among them, L represents the cutting loss coefficient, g(x) represents the normalized cutting size accuracy loss evaluation coefficient, g(y) represents the normalized cutting efficiency loss evaluation coefficient, g(z) represents the normalized cutting surface quality loss evaluation coefficient, a, b, c represent the predetermined optimization calculation gain conditions, a, b, c are all positive numbers, and the sum of a, b, c is 1.
7. The platform according to claim 1, characterized in that The numerical control cutting second-order optimization module is used to perform optimization analysis on the numerical control cutting first-order optimization result according to the numerical control cutting second-order optimization condition and the numerical control cutting optimization source to obtain the numerical control cutting second-order optimization result, including: The second-order optimization condition for numerical control cutting includes a predetermined cutting variation capacity; Based on the predetermined cutting variation capacity, variation capacity is allocated to the first-order optimization result of the numerical control cutting to obtain a plurality of variation allocation capacities; Based on the numerical control cutting optimization source, mutating the numerical control cutting first-order optimization result according to the multiple variation allocation capacities to obtain multiple numerical control cutting variation clusters; The cutting loss minimization optimization is performed according to the first-order optimization result of the numerical control cutting and the multiple numerical control cutting variation clusters to generate the second-order optimization result of the numerical control cutting.
8. The platform according to claim 7, characterized in that Based on the numerical control cutting optimization source, the numerical control cutting first-order optimization result is mutated according to the multiple variation allocation capacities to obtain multiple numerical control cutting variation clusters, including: Extracting a first variation allocation capacity and a first numerical control cutting benchmark solution according to the plurality of variation allocation capacities and the numerical control cutting first-order optimization result; Adjusting the first numerical control cutting reference scheme based on the numerical control cutting optimization source to generate a first reference cutting adjustment scheme; Performing a cutting loss check according to the first reference cutting adjustment scheme, generating a first reference cutting variation scheme, and adding the first reference cutting variation scheme to a first numerical control cutting variation cluster; The first numerical control cutting benchmark scheme is continuously adjusted and the cutting loss is checked according to the numerical control cutting optimization source until the first numerical control cutting variation cluster satisfying the first variation allocation capacity is generated.