A method and system for optimizing processing parameters of wave-absorbing plates

Abstract

This invention provides a method and system for optimizing processing parameters of microwave absorbing panels, relating to the field of data processing technology. The method includes: optimizing the processing parameters of the absorbing layer within the range of absorbing parameters to improve absorbing performance, obtaining multiple sets of absorbing parameters; predicting the absorbing temperature and panel quality of the absorbing panel based on the electromagnetic parameters of the working environment of the absorbing panel, obtaining multiple sets of panel quality information, and selecting the optimal absorbing parameter set; optimizing the processing parameters of the heat dissipation layer within the range of heat dissipation parameters to reduce the absorbing temperature rise, obtaining the optimal heat dissipation parameter set; and combining the optimal absorbing parameters and the optimal heat dissipation parameters as the optimization result of the processing parameters of the absorbing panel. This solves the technical problem in the prior art of lacking control over the parameters of the absorbing panel during the processing, resulting in a low pass rate of the absorbing panel, and achieves rational and accurate optimization of the processing parameters of the absorbing panel, thereby improving the pass rate of the absorbing panel.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for optimizing processing parameters of an absorbing plate. Background Art

[0002] With the rapid development of science and technology, the application scope of electromagnetic waves is becoming more and more extensive. The large-scale release of electromagnetic waves has also brought a series of problems, one of which is the interference of electromagnetic wave radiation on human health and electronic equipment. The absorbing material is used to absorb and eliminate the radiation of electromagnetic waves.

[0003] Absorbing material is a material that can absorb electromagnetic waves and convert them into other forms of energy. It can effectively absorb electromagnetic waves, reduce their reflection and propagation, and thus reduce the radiation intensity of electromagnetic waves. With the expansion of the application field of absorbing materials, the research and development of absorbing materials has entered a wider range. Now, there is a lack of control over the parameters of absorbing panels during the processing process in the existing technology, resulting in a low pass rate of absorbing panels. Summary of the invention

[0004] The present application provides a method and system for optimizing processing parameters of absorbing plates, which are used to solve the technical problem in the prior art of lack of control over parameters of absorbing plates during processing, resulting in a low qualified rate of absorbing plates.

[0005] In view of the above problems, the present application provides a method and system for optimizing processing parameters of an absorbing plate.

[0006] In a first aspect, the present application provides a method for optimizing processing parameters of an absorbing plate, the method comprising: obtaining a processing parameter range for processing an absorbing layer in an absorbing plate to be prepared, and a processing parameter range for a heat dissipation layer, to obtain an absorbing parameter range and a heat dissipation parameter range; within the absorbing parameter range, optimizing the processing parameters of the absorbing layer based on improving absorbing performance, to obtain a plurality of absorbing parameter sets; based on the plurality of absorbing parameter sets, respectively predicting the absorbing temperature and the plate quality of the absorbing plate according to the electromagnetic parameters of the working environment of the absorbing plate, to obtain a plurality of plate quality information sets; selecting and obtaining an optimal absorbing parameter set according to the plurality of plate quality information sets; based on the optimal absorbing parameter set, optimizing the processing parameters of the heat dissipation layer within the heat dissipation parameter range for the purpose of reducing the absorbing heating temperature, to obtain an optimal heat dissipation parameter set; combining the optimal absorbing parameters and the optimal heat dissipation parameters in the optimal absorbing parameter set and the optimal heat dissipation parameter set as the processing parameter optimization result of the absorbing plate.

[0007] In a second aspect, the present application provides a processing parameter optimization system for an absorbing plate, the system comprising: a parameter range acquisition module, the parameter range acquisition module is used to obtain a processing parameter range for processing an absorbing layer in an absorbing plate to be prepared, and a processing parameter range for a heat dissipation layer, to obtain an absorbing parameter range and a heat dissipation parameter range; a first optimization module, the first optimization module is used to optimize the processing parameters of the absorbing layer within the absorbing parameter range based on improving absorbing performance, to obtain multiple absorbing parameter sets; a first prediction module, the first prediction module is used to, based on the multiple absorbing parameter sets, according to the electromagnetic parameters of the working environment of the absorbing plate, The absorbing temperature prediction and the plate quality prediction of the absorbing plate are respectively performed to obtain multiple plate quality information sets; a second optimization module, the second optimization module is used to select and obtain the optimal absorbing parameter set according to the multiple plate quality information sets; a third optimization module, the third optimization module is used to optimize the heat dissipation layer processing parameters within the heat dissipation parameter range based on the optimal absorbing parameter set for the purpose of reducing the absorbing heating temperature, and obtain the optimal heat dissipation parameter set; a fourth optimization module, the fourth optimization module is used to combine the optimal absorbing parameters and the optimal heat dissipation parameters in the optimal absorbing parameter set and the optimal heat dissipation parameter set as the processing parameter optimization result of the absorbing plate.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages: A method and system for optimizing processing parameters of absorbing plates provided in the present application relate to the field of data processing technology, solve the technical problem in the prior art of lack of control over parameters of absorbing plates during processing, resulting in a low qualified rate of absorbing plates, and achieve reasonable and accurate optimization of processing parameters of absorbing plates, thereby improving the qualified rate of absorbing plates. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic flow chart of a method for optimizing processing parameters of an absorbing plate is provided for this application;

[0010] Figure 2 A schematic diagram of the structure of a processing parameter optimization system for an absorbing plate is provided for this application.

[0011] Explanation of the accompanying drawings: parameter range acquisition module 1, first optimization module 2, first prediction module 3, second optimization module 4, third optimization module 5, fourth optimization module 6. DETAILED DESCRIPTION

[0012] The present application provides a method and system for optimizing processing parameters of absorbing plates, so as to solve the technical problem in the prior art of lack of control over parameters of absorbing plates during processing, resulting in a low qualified rate of absorbing plates.

[0013] Embodiment 1

[0014] like Figure 1 As shown, the embodiment of the present application provides a method for optimizing processing parameters of an absorbing plate, the method comprising:

[0015] Step A100: obtaining a processing parameter range for processing the wave absorbing layer in the wave absorbing plate to be prepared and a processing parameter range for the heat dissipation layer, and obtaining a wave absorbing parameter range and a heat dissipation parameter range;

[0016] In the present application, a processing parameter optimization method for an absorbing plate provided in an embodiment of the present application is applied to a processing parameter optimization system for an absorbing plate. The processing parameter optimization system for an absorbing plate is used to collect data on the processing parameters of the absorbing plate, and the processing parameter range of the absorbing layer in the absorbing plate to be prepared and the processing parameter range of the heat dissipation layer are obtained. The absorbing plate may be an absorbing layer made by making a resin system. At the same time, the parameters included in the absorbing layer in the absorbing plate may be processing parameters such as temperature parameters, stirring time parameters, and alcohol content parameters. On this basis, the absorbing parameter range of the absorbing plate is defined. Furthermore, the processing parameters of the heat dissipation layer may include processing parameters such as thermal conductive particle parameters, absorbing particle parameters, and thermal conductive adhesive parameters. On this basis, the heat dissipation parameter range of the absorbing plate is defined, which serves as an important reference for optimizing the processing parameters of the absorbing plate in the later stage.

[0017] Step A200: optimizing the processing parameters of the absorbing layer within the absorbing parameter range based on improving the absorbing performance, and obtaining a plurality of absorbing parameter sets;

[0018] Furthermore, step A200 of the present application also includes:

[0019] Step A210: Based on improving the absorbing performance, construct an absorbing optimization function, as shown in the following formula:

[0020] abs=∑ i M ＝1 w i K i ;

[0021] Where abs is the absorbing adaptability, M is the number of types of electromagnetic waves in the working environment of the absorbing plate, and w i is the weight of the i-th electromagnetic wave, K i is the reflection loss of the absorbing plate processed according to the absorbing parameters when the ith electromagnetic wave is used to test the absorbing plate;

[0022] Step A220: optimizing the processing parameters of the absorbing layer within the absorbing parameter range according to the absorbing optimization function to obtain a plurality of absorbing parameter sets.

[0023] In this application, the above-defined absorbing parameter range is used as the boundary data, and the processing parameters of the absorbing layer are optimized based on improving the absorbing performance of the absorbing plate. First, based on improving the absorbing performance, an absorbing optimization function is constructed, as shown in the following formula:

[0024] abs=∑ i M ＝1 w i K i ;

[0025] Where abs is the absorbing adaptability, M is the number of types of electromagnetic waves in the working environment of the absorbing plate, and w i is the weight of the i-th electromagnetic wave, K i is the reflection loss of the absorbing plate processed according to the absorbing parameters when the ith electromagnetic wave is used to test the absorbing plate;

[0026] According to the number of types of electromagnetic waves in the working environment of the absorbing plate, the i-th electromagnetic wave is selected and the reflection loss of the absorbing plate processed according to the absorbing parameters is multiplied by the weight of the i-th electromagnetic wave and the i-th electromagnetic wave. The reflection loss of the absorbing plate refers to the energy loss of the electromagnetic wave reflected from the surface of the absorbing plate. Since the reflection loss test is one of the most commonly used methods for testing absorbing materials, the absorbing material is then tested for absorbing through the reflection loss test. The test process can be to place the absorbing material on the test bench, then emit electromagnetic waves to the surface of the absorbing plate based on the test instrument, and then measure the power of the reflected electromagnetic waves. In this process, the greater the reflection loss, the better the performance of the absorbing material.

[0027] Furthermore, the absorbing adaptability obtained by calculating the absorbing optimization function is multi-dimensionally optimized on the processing parameters of the absorbing layer based on the limitation of the absorbing parameter range and the test results, thereby outputting multiple absorbing parameter sets, thereby ensuring the optimization of the processing parameters of the absorbing plate.

[0028] Furthermore, step A220 of the present application includes:

[0029] Step A221: randomly generating a plurality of first absorbing parameters within the absorbing parameter range;

[0030] Step A222: Based on the plurality of first absorbing parameters, simulated production and testing of the absorbing plate are performed, and a plurality of first absorbing adaptabilities are calculated in combination with the absorbing optimization function;

[0031] Step A223: dividing the plurality of first wave absorbing parameters according to the plurality of first wave absorbing adaptabilities to obtain a plurality of center first wave absorbing parameters and a plurality of edge first wave absorbing parameters;

[0032] Step A224: acquiring a plurality of first absorbing parameter groups, wherein the plurality of first absorbing parameter groups are obtained by clustering a plurality of edge first absorbing parameters according to a plurality of center first absorbing parameters;

[0033] Step A225: performing iterative update optimization of the processing parameters of the absorbing layer within the plurality of first absorbing parameter groups until a preset number of updates is reached to obtain a plurality of preliminary converged absorbing parameter groups;

[0034] Step A226: Calculate the convergence parameters of the absorbing parameters in the plurality of preliminary convergent absorbing parameter groups, and determine whether they are all less than the convergence parameter threshold. If so, obtain a plurality of convergent absorbing parameter groups. If not, continue to update and optimize until the plurality of convergence parameters are all less than the convergence parameter threshold, and obtain a plurality of convergent absorbing parameter groups.

[0035] Step A227: Calculate the sum of the absorbing fitness of the absorbing parameters in the multiple convergent absorbing parameter groups, and output T convergent absorbing parameter groups with the largest sum of absorbing fitness as multiple absorbing parameter sets, where T is an integer greater than 1.

[0036] Furthermore, step A225 of the present application includes:

[0037] Step A2251: in each of the plurality of first absorbing parameter sets, taking the center first absorbing parameter as the updating direction, updating the plurality of edge first absorbing parameters to obtain a plurality of edge second absorbing parameters;

[0038] Step A2252: Based on the plurality of edge second wave absorbing parameters, a plurality of second wave absorbing fitnesses are calculated and judged, and the central wave absorbing parameters and the edge wave absorbing parameters are updated to obtain a plurality of second wave absorbing parameter groups;

[0039] Step A2253: Continue to update and optimize the processing parameters of the absorbing layer within the plurality of second absorbing parameter groups.

[0040] In the present application, within the limitation of the absorbing parameter range, a plurality of first absorbing parameters are randomly generated, and the plurality of first absorbing parameters are different absorbing processing parameters, and then based on the plurality of first absorbing parameters, the simulated production and testing of the absorbing plate are sequentially performed. The simulated generation process of the absorbing plate mainly includes raw material preparation, mixing, molding, drying, processing, testing and the like, and the testing of the absorbing material can be performed by combining the absorbing optimization function to test the reflection loss, and on this basis, a plurality of first absorbing fitnesses are calculated to obtain. Further, according to the mean of the plurality of first absorbing fitnesses, the plurality of first absorbing parameters are divided from large to small, which means that the plurality of first absorbing parameters corresponding to the plurality of absorbing fitnesses closest to the mean of the first absorbing fitnesses are recorded as a plurality of central first absorbing parameters, and the remaining absorbing parameters are recorded as a plurality of edge first absorbing parameters, and then the plurality of edge first absorbing parameters are clustered according to the plurality of central first absorbing parameters, and the plurality of edge first absorbing parameters are divided into a plurality of first absorbing parameter groups consisting of similar objects according to the classification of the plurality of central first absorbing parameters.

[0041] Further, iteratively updating and optimizing the processing parameters of the absorbing layer within the plurality of first absorbing parameter groups refers to, in the plurality of first absorbing parameter sets, taking the central first absorbing parameter as the optimization update direction of the absorbing parameter, updating the plurality of edge first absorbing parameters toward the central first absorbing parameter, recording the updated plurality of edge first absorbing parameters as a plurality of edge second absorbing parameters, taking the plurality of edge second absorbing parameters as reference basic data, performing fitness calculation on the plurality of edge second absorbing parameters to obtain a plurality of second absorbing fitnesses, distinguishing the fitness values ​​of the plurality of first absorbing fitnesses from the plurality of second absorbing fitnesses, optimizing and updating the central absorbing parameter and the edge absorbing parameter according to the rarefaction parameter with a large fitness, obtaining a plurality of second absorbing parameter groups, and continuing to update and optimize the processing parameters of the absorbing layer within the plurality of second absorbing parameter groups, thereby iterating until a preset number of updates is reached to obtain a plurality of preliminary converged absorbing parameter groups.

[0042] At the same time, the convergence parameters of the absorbing parameters in the multiple preliminary convergent absorbing parameter groups are calculated, and the convergence parameters refer to the convergence to a point and approaching the central absorbing parameter. Then, it is judged whether the multiple convergence parameters are all less than the convergence parameter threshold. If so, multiple convergent absorbing parameter groups are obtained. If not, the absorbing parameters are continuously updated and optimized until the multiple convergence parameters are all less than the convergence parameter threshold. On this basis, multiple convergent absorbing parameter groups are obtained, and finally the absorbing fitness of the absorbing parameters in the multiple convergent absorbing parameter groups is calculated and summed to generate the sum of the absorbing fitness of the absorbing parameters in the multiple convergent absorbing parameter groups. At the same time, T convergent absorbing parameter groups with the largest sum of absorbing fitness are output, and T is an integer greater than 1. They are output as multiple absorbing parameter sets, which lays a solid foundation for the subsequent optimization of the processing parameters of the absorbing plate.

[0043] Step A300: Based on the multiple absorbing parameter sets and the electromagnetic parameters of the working environment of the absorbing plate, respectively predict the absorbing temperature and the plate quality of the absorbing plate to obtain multiple plate quality information sets;

[0044] Furthermore, step A300 of the present application also includes:

[0045] Step A310: obtaining M electromagnetic wave parameters of the working environment of the absorbing plate, where M is an integer greater than 1;

[0046] Step A320: Obtain a sample absorption parameter set, a sample electromagnetic parameter set, and a sample temperature set;

[0047] Step A330: using the sample absorption parameter set, the sample electromagnetic parameter set and the sample temperature set to train an absorption temperature prediction branch;

[0048] Step A340: Obtain a set of sample plate quality grades;

[0049] Step A350: using the sample temperature set and the sample plate quality grade set to train a plate quality prediction branch;

[0050] Step A360: connecting the absorbing temperature prediction branch and the plate quality prediction branch, and performing absorbing temperature prediction and plate quality prediction of the absorbing plate based on the M electromagnetic wave parameters and multiple absorbing parameter sets to obtain multiple plate quality information sets.

[0051] In the present application, in order to ensure the optimization effect of the processing parameters of the absorbing plate, and because the absorbing plate converts electromagnetic waves into heat energy during the absorbing process, if the temperature of the absorbing plate is too high, it will affect the quality of the absorbing plate accordingly. Therefore, it is necessary to optimize the processing parameters of the heat dissipation layer of the absorbing plate in the future. First, it is necessary to predict the absorbing temperature and the plate quality of the absorbing plate through the multiple absorbing parameter sets output above and according to the electromagnetic parameters of the working environment of the absorbing plate, which refers to M kinds of electromagnetic wave parameters of the working environment of the absorbing plate, M is an integer greater than 1, and the M kinds of electromagnetic wave parameters can be classified by frequency, including low-frequency electromagnetic wave parameters, medium-frequency electromagnetic wave parameters, and high-frequency electromagnetic wave parameters. The low-frequency electromagnetic wave parameters can be in the frequency range of hundreds of hertz to hundreds of kilohertz, the medium-frequency electromagnetic wave parameters can be in the frequency range of hundreds of kilohertz to thousands of megahertz, and the high-frequency electromagnetic wave parameters can be in the frequency range of thousands of megahertz to hundreds of megahertz. On this basis, a sample absorbing parameter set, a sample electromagnetic parameter set, and a sample temperature set are generated respectively. The sample absorbing parameter set is obtained by all the absorbing materials. The sample absorption parameters are composed of the sample electromagnetic parameter set, the sample electromagnetic parameter set is composed of all sample electromagnetic wave parameters under the working environment of the absorbing material, and the sample temperature set is composed of all sample temperature parameters of the electromagnetic wave converted into thermal energy after the absorbing material absorbs the wave. Furthermore, the sample absorption parameter set, the sample electromagnetic parameter set and the sample temperature set are used to train and obtain the absorption temperature prediction branch, and the absorption temperature prediction branch is obtained by training the training data set and the supervision data set, wherein each group of training data in the training data set includes the sample absorption parameter set, the sample electromagnetic parameter set and the sample temperature set, and the supervision data set is the supervision data corresponding to the training data set one by one. Further, the construction process of the absorption temperature prediction branch is: each group of training data in the training data set is input into the absorption temperature prediction branch, and the output of the absorption temperature prediction branch is supervised and adjusted by the supervision data corresponding to this group of training data. When the output result of the absorption temperature prediction branch is consistent with the supervision data, the training of the current group is completed, and the training of all the training data in the training data set is completed, and the training of the absorption temperature prediction branch is completed.

[0052] In order to ensure the accuracy of the absorption temperature prediction branch, the absorption temperature prediction branch can be tested using a test data set. For example, the test accuracy can be set to 80%. When the test accuracy of the test data set meets 80%, the absorption temperature prediction branch is constructed.

[0053] Similarly, the sample temperature set and the sample plate quality grade set are used to train and obtain the plate quality prediction branch;

[0054] Finally, by connecting the absorbing temperature prediction branch and the plate quality prediction branch, the absorbing temperature and plate quality of the absorbing plate are predicted based on the synchronous input of M electromagnetic wave parameters and multiple absorbing parameter sets as input data, and the data is integrated according to the predicted absorbing temperature and predicted plate quality and recorded as multiple plate quality information sets, which has a limited effect on optimizing the processing parameters of the absorbing plate.

[0055] Step A400: selecting an optimal absorbing parameter set according to the plurality of plate quality information sets;

[0056] Furthermore, step A400 of the present application also includes:

[0057] Step A410: performing weighted calculation to obtain a plurality of comprehensive plate quality information in the plurality of plate quality information sets;

[0058] Step A420: Select the absorbing parameter set corresponding to the maximum comprehensive plate quality information to obtain the optimal absorbing parameter set.

[0059] In the present application, in order to optimize the processing parameters of the absorbing plate more accurately, it is necessary to optimize the multiple plate quality information obtained by the above integration. First, weighted calculation is performed in multiple plate quality information sets. The weighted calculation needs to be based on a large amount of data aggregation and accurate determination of the weights before targeted calculation. Further, the multiple plate quality information sets are serialized in descending order, and their weight ratio is proportional to the plate quality, that is, the better the plate quality, the greater its weight ratio. Multiple comprehensive plate quality information is obtained by multiplying the weights assigned to the multiple plate quality information sets by the corresponding influencing parameters. The comprehensive plate quality information with the first rank at this time is taken as the largest comprehensive plate quality information, and the corresponding absorbing parameter set is extracted at the same time, and it is recorded as the optimal absorbing parameter set for output, so as to be used as reference data for later optimization of the processing parameters of the absorbing plate.

[0060] Step A500: Based on the optimal absorbing parameter set, with the purpose of reducing the absorbing temperature rise, within the heat dissipation parameter range, optimizing the heat dissipation layer processing parameters to obtain the optimal heat dissipation parameter set;

[0061] Furthermore, step A500 of the present application also includes:

[0062] Step A510: randomly generating and obtaining a plurality of first heat dissipation parameters within the heat dissipation parameter range;

[0063] Step A520: Based on the multiple first heat dissipation parameters and in combination with the optimal absorbing parameter set, simulated production and testing of the absorbing plate are performed, and absorbing temperature prediction and plate quality prediction are performed to calculate and obtain multiple first heat dissipation adaptability;

[0064] Step A530: performing division and clustering according to the plurality of first heat dissipation fitnesses to obtain a plurality of first heat dissipation parameter groups;

[0065] Step A540: within the plurality of first heat dissipation parameter groups, continue to update and optimize the heat dissipation layer processing parameters until convergence, and obtain a plurality of converged heat dissipation parameter groups;

[0066] Step A550: Calculate the heat dissipation fitness of the heat dissipation parameters in a plurality of convergent heat dissipation parameter groups, and output the convergent heat dissipation parameter group with the largest sum of heat dissipation fitness as the optimal heat dissipation parameter set.

[0067] In the present application, while obtaining the optimal absorbing parameter set of the absorbing plate, in order to ensure the quality of the absorbing plate, it is also necessary to optimize the heat dissipation parameters, which means that within the range of the heat dissipation parameters, a plurality of first heat dissipation parameters are randomly generated, and the plurality of first heat dissipation parameters are different heat dissipation processing parameters, and then based on the plurality of first heat dissipation parameters combined with the optimal absorbing parameter set, the simulated production and test of the absorbing plate similar to the above are performed, and the absorbing temperature prediction and the plate quality prediction are performed, that is, by combining the heat dissipation parameters and the optimal absorbing parameters to perform simulated production and absorbing tests, the temperature of the absorbing plate after different electromagnetic waves are absorbed is predicted, and the quality grade of the absorbing plate is predicted, which is used as the fitness, and the higher the quality grade, the better the fitness, thereby simultaneously obtaining a plurality of first heat dissipation fitnesses of the plurality of first heat dissipation parameters, and further In the first step, the heat dissipation processing parameters are divided and clustered based on multiple first heat dissipation fitnesses, and the multiple first heat dissipation fitnesses are divided into multiple classes composed of similar objects, and are recorded as multiple first heat dissipation parameter groups. At the same time, in the multiple first heat dissipation parameter groups, the heat dissipation layer processing parameters of the absorbing plate are continuously updated and optimized until convergence, which means that when the heat dissipation layer processing parameters gradually converge to one point, it is considered that convergence is completed, and multiple converged heat dissipation parameter groups are obtained on this basis. Further, the heat dissipation fitnesses of the heat dissipation parameters in the multiple convergent heat dissipation parameter groups are comprehensively calculated, and the heat dissipation fitnesses of the heat dissipation parameters in the multiple convergent heat dissipation parameter groups are respectively added, and finally the convergent heat dissipation parameter group with the largest sum of heat dissipation fitnesses is output as the optimal heat dissipation parameter set, so as to improve the accuracy of optimizing the processing parameters of the absorbing plate in the later stage.

[0068] Step A600: combining the optimal absorbing parameters and the optimal heat dissipation parameters in the optimal absorbing parameter set and the optimal heat dissipation parameter set as a processing parameter optimization result of the absorbing plate.

[0069] In the present application, the optimal absorbing parameter set selected according to multiple plate quality information sets and the optimal heat dissipation parameter set obtained by optimizing the heat dissipation layer processing parameters within the heat dissipation parameter range for the purpose of reducing the absorbing heating temperature based on the optimal absorbing parameter set are combined, and the optimal absorbing parameter sets are sorted from large to small according to the degree of excellence, thereby extracting the first-order absorbing parameters therefrom as the optimal absorbing parameters for output, and then the optimal heat dissipation parameter set is sorted from large to small according to the degree of excellence, thereby extracting the first-order heat dissipation parameters therefrom as the optimal heat dissipation parameters for output, and finally the extracted optimal absorbing parameters and optimal heat dissipation parameters are used as the processing parameter optimization results of the absorbing plate, based on which the processing parameters of the absorbing plate are optimized under the optimal absorbing parameters and the optimal heat dissipation parameters, thereby ensuring better optimization of the processing parameters of the absorbing plate in the later stage.

[0070] In summary, the method for optimizing processing parameters of absorbing plates provided in the embodiments of the present application at least includes the following technical effects, which realizes the rational and accurate optimization of processing parameters of absorbing plates, thereby improving the qualified rate of absorbing plates.

[0071] Embodiment 2

[0072] Based on the same inventive concept as the method for optimizing processing parameters of an absorbing plate in the aforementioned embodiment, Figure 2 As shown, the present application provides a processing parameter optimization system for an absorbing plate, the system comprising:

[0073] A parameter range acquisition module 1, wherein the parameter range acquisition module 1 is used to acquire a processing parameter range for processing the wave absorbing layer in the wave absorbing plate to be prepared, and a processing parameter range for the heat dissipation layer, to obtain a wave absorbing parameter range and a heat dissipation parameter range;

[0074] A first optimization module 2, wherein the first optimization module 2 is used to optimize the processing parameters of the absorbing layer within the absorbing parameter range based on improving the absorbing performance, and obtain multiple absorbing parameter sets;

[0075] A first prediction module 3, the first prediction module 3 is used to predict the absorbing temperature and the quality of the absorbing plate based on the multiple absorbing parameter sets and the electromagnetic parameters of the working environment of the absorbing plate, and obtain multiple plate quality information sets;

[0076] A second optimization module 4, the second optimization module 4 is used to select and obtain an optimal absorbing parameter set according to the multiple plate quality information sets;

[0077] A third optimization module 5, the third optimization module 5 is used to optimize the processing parameters of the heat dissipation layer within the heat dissipation parameter range based on the optimal heat absorption parameter set, with the purpose of reducing the heat absorption temperature rise, to obtain the optimal heat dissipation parameter set;

[0078] The fourth optimization module 6 is used to combine the optimal absorbing parameters and the optimal heat dissipation parameters in the optimal absorbing parameter set and the optimal heat dissipation parameter set as the processing parameter optimization result of the absorbing plate.

[0079] Furthermore, the system also includes:

[0080] Function module, the function module is used to construct an absorption optimization function based on improving the absorption performance, as shown in the following formula:

[0081] abs=∑ i M ＝1 w i K i ;

[0082] Where abs is the absorbing adaptability, M is the number of types of electromagnetic waves in the working environment of the absorbing plate, and w i is the weight of the i-th electromagnetic wave, K i is the reflection loss of the absorbing plate processed according to the absorbing parameters when the ith electromagnetic wave is used to test the absorbing plate;

[0083] A fifth optimization module, the fifth optimization module is used to optimize the processing parameters of the absorbing layer within the absorbing parameter range according to the absorbing optimization function to obtain multiple absorbing parameter sets.

[0084] Furthermore, the system also includes:

[0085] A first random generation module, the first random generation module is used to randomly generate a plurality of first absorbing parameters within the absorbing parameter range;

[0086] A first calculation module, the first calculation module is used to perform simulated production and testing of the absorbing plate based on the plurality of first absorbing parameters, and calculate and obtain a plurality of first absorbing fitnesses in combination with the absorbing optimization function;

[0087] A division module, the division module is used to divide the plurality of first absorbing parameters according to the plurality of first absorbing adaptabilities to obtain a plurality of center first absorbing parameters and a plurality of edge first absorbing parameters;

[0088] A clustering module, wherein the clustering module is used to obtain a plurality of first absorbing parameter groups, wherein the plurality of first absorbing parameter groups are obtained by clustering a plurality of edge first absorbing parameters according to a plurality of center first absorbing parameters;

[0089] An iterative update optimization module, wherein the iterative update optimization module is used to perform iterative update optimization of the processing parameters of the absorbing layer within the plurality of first absorbing parameter groups until a preset number of updates is reached to obtain a plurality of preliminary converged absorbing parameter groups;

[0090] A second calculation module, the second calculation module is used to calculate the convergence parameters of the absorbing parameters in the multiple preliminary convergent absorbing parameter groups, and determine whether they are all less than the convergence parameter threshold. If so, multiple convergent absorbing parameter groups are obtained. If not, update optimization is continued until the multiple convergence parameters are all less than the convergence parameter threshold, and multiple convergent absorbing parameter groups are obtained.

[0091] The third calculation module is used to calculate the sum of the absorbing fitness of the absorbing parameters in the multiple convergent absorbing parameter groups, and output T convergent absorbing parameter groups with the largest sum of absorbing fitness as multiple absorbing parameter sets, where T is an integer greater than 1.

[0092] Furthermore, the system also includes:

[0093] A first updating module, wherein the first updating module is used to update a plurality of edge first absorbing parameters in a plurality of first absorbing parameter sets respectively, taking a central first absorbing parameter as an updating direction, to obtain a plurality of edge second absorbing parameters;

[0094] A second updating module, wherein the second updating module is used to calculate and obtain a plurality of second absorbing fitnesses based on a plurality of edge second absorbing parameters, and to distinguish and update a central absorbing parameter and an edge absorbing parameter to obtain a plurality of second absorbing parameter groups;

[0095] The first updating and optimizing module is used to continue to update and optimize the processing parameters of the absorbing layer within the plurality of second absorbing parameter groups.

[0096] Furthermore, the system also includes:

[0097] A first parameter acquisition module, the first parameter acquisition module is used to obtain M electromagnetic wave parameters of the working environment of the absorbing plate, where M is an integer greater than 1;

[0098] A second parameter acquisition module, the second parameter acquisition module is used to acquire a sample absorption parameter set, a sample electromagnetic parameter set and a sample temperature set;

[0099] A first branch training module, the first branch training module is used to train an absorption temperature prediction branch by using the sample absorption parameter set, the sample electromagnetic parameter set and the sample temperature set;

[0100] A grade acquisition module, the grade acquisition module is used to obtain a set of sample plate quality grades;

[0101] A second branch training module, the second branch training module is used to train a board quality prediction branch by using the sample temperature set and the sample board quality grade set;

[0102] The second prediction module is used to connect the absorbing temperature prediction branch and the plate quality prediction branch, and based on the M electromagnetic wave parameters and multiple absorbing parameter sets, perform absorbing temperature prediction and plate quality prediction of the absorbing plate to obtain multiple plate quality information sets.

[0103] Furthermore, the system also includes:

[0104] A weighted calculation module, the weighted calculation module is used to obtain a plurality of comprehensive plate quality information by weighted calculation in the plurality of plate quality information sets;

[0105] A parameter selection module is used to select the absorbing parameter set corresponding to the maximum comprehensive plate quality information to obtain the optimal absorbing parameter set.

[0106] Furthermore, the system also includes:

[0107] A second random generation module, the second random generation module is used to randomly generate a plurality of first heat dissipation parameters within the heat dissipation parameter range;

[0108] A fourth calculation module, the fourth calculation module is used to perform simulated production and testing of the absorbing plate based on the multiple first heat dissipation parameters and the optimal absorbing parameter set, and perform absorbing temperature prediction and plate quality prediction, and calculate and obtain multiple first heat dissipation adaptability;

[0109] A division module, the division module is used to divide and cluster according to the multiple first heat dissipation fitnesses to obtain multiple first heat dissipation parameter groups;

[0110] A second updating and optimizing module, wherein the second updating and optimizing module is used to continue updating and optimizing the processing parameters of the heat dissipation layer within the plurality of first heat dissipation parameter groups until convergence occurs, thereby obtaining a plurality of converged heat dissipation parameter groups;

[0111] The fifth calculation module is used to calculate the comprehensive heat dissipation fitness of the heat dissipation parameters in multiple convergent heat dissipation parameter groups, and output the convergent heat dissipation parameter group with the largest sum of heat dissipation fitness as the optimal heat dissipation parameter set.

[0112] Through the above detailed description of a method for optimizing processing parameters of an absorbing plate in this specification, those skilled in the art can clearly understand a system for optimizing processing parameters of an absorbing plate in this embodiment. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0113] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing processing parameters of an absorbing plate, characterized in that: The method comprises: Obtaining a processing parameter range for processing the absorbing layer in the absorbing plate to be prepared and a processing parameter range for the heat dissipation layer, and obtaining an absorbing parameter range and a heat dissipation parameter range; Within the absorbing parameter range, based on improving absorbing performance, optimizing the processing parameters of the absorbing layer to obtain multiple absorbing parameter sets; Based on the multiple absorbing parameter sets, and according to the electromagnetic parameters of the working environment of the absorbing plate, respectively predict the absorbing temperature and the plate quality of the absorbing plate to obtain multiple plate quality information sets; Selecting and obtaining an optimal absorbing parameter set according to the plurality of plate quality information sets; Based on the optimal absorbing parameter set, with the purpose of reducing the absorbing temperature rise, within the heat dissipation parameter range, the heat dissipation layer processing parameters are optimized to obtain the optimal heat dissipation parameter set; Combining the optimal absorbing parameters and the optimal heat dissipation parameters in the optimal absorbing parameter set and the optimal heat dissipation parameter set as the processing parameter optimization result of the absorbing plate; Within the absorbing parameter range, based on improving the absorbing performance, the absorbing layer processing parameters are optimized to obtain multiple absorbing parameter sets, including: Based on improving the wave absorption performance, the wave absorption optimization function is constructed as follows: Where abs is the absorbing adaptability, M is the number of types of electromagnetic waves in the working environment of the absorbing plate, and w i is the weight of the i-th electromagnetic wave, K i is the reflection loss of the absorbing plate processed according to the absorbing parameters when the ith electromagnetic wave is used to test the absorbing plate; According to the absorbing optimization function, optimizing the processing parameters of the absorbing layer within the absorbing parameter range, to obtain a plurality of absorbing parameter sets; Based on the multiple absorbing parameter sets and according to the electromagnetic parameters of the working environment of the absorbing plate, the absorbing temperature prediction and the plate quality prediction of the absorbing plate are respectively performed to obtain multiple plate quality information sets, including: Obtaining M electromagnetic wave parameters of the working environment of the absorbing plate, where M is an integer greater than 1; Obtaining a sample absorption parameter set, a sample electromagnetic parameter set, and a sample temperature set; Using the sample absorption parameter set, the sample electromagnetic parameter set and the sample temperature set to train an absorption temperature prediction branch; Get the sample plate quality grade set; Using the sample temperature set and the sample plate quality grade set to train a plate quality prediction branch; The absorbing temperature prediction branch and the plate quality prediction branch are connected, and based on the M electromagnetic wave parameters and the multiple absorbing parameter sets, the absorbing temperature prediction and the plate quality prediction of the absorbing plate are performed to obtain multiple plate quality information sets; Based on the optimal absorbing parameter set and based on reducing the absorbing temperature rise, the heat dissipation layer processing parameters are optimized within the heat dissipation parameter range, including: Randomly generate and obtain a plurality of first heat dissipation parameters within the heat dissipation parameter range; Based on the multiple first heat dissipation parameters and in combination with the optimal absorbing parameter set, simulated production and testing of absorbing panels are performed, and absorbing temperature prediction and panel quality prediction are performed to calculate and obtain multiple first heat dissipation adaptability; Dividing and clustering the multiple first heat dissipation fitnesses to obtain multiple first heat dissipation parameter groups; Continue to update and optimize the heat dissipation layer processing parameters within the plurality of first heat dissipation parameter groups until convergence, and obtain a plurality of converged heat dissipation parameter groups; The heat dissipation fitness of the heat dissipation parameters in a plurality of convergent heat dissipation parameter groups is calculated, and the convergent heat dissipation parameter group with the largest sum of heat dissipation fitness is output as the optimal heat dissipation parameter set.

2. The method according to claim 1, characterized in that According to the absorbing optimization function, the processing parameters of the absorbing layer are optimized within the absorbing parameter range, including: Randomly generating a plurality of first absorbing parameters within the absorbing parameter range; Based on the multiple first absorbing parameters, simulated production and testing of the absorbing plate are performed, and multiple first absorbing adaptabilities are calculated and obtained in combination with the absorbing optimization function; According to the plurality of first wave absorbing adaptabilities, the plurality of first wave absorbing parameters are divided to obtain a plurality of center first wave absorbing parameters and a plurality of edge first wave absorbing parameters; Acquire a plurality of first absorbing parameter groups, wherein the plurality of first absorbing parameter groups are obtained by clustering a plurality of edge first absorbing parameters according to a plurality of center first absorbing parameters; Iteratively updating and optimizing the processing parameters of the absorbing layer within the plurality of first absorbing parameter groups until a preset number of updates is reached to obtain a plurality of preliminary converged absorbing parameter groups; Calculating convergence parameters of the absorbing parameters in the plurality of preliminary convergent absorbing parameter groups, and determining whether they are all less than a convergence parameter threshold, if so, obtaining a plurality of convergent absorbing parameter groups, and if not, continuing to update and optimize until the plurality of convergence parameters are all less than the convergence parameter threshold, and obtaining a plurality of convergent absorbing parameter groups; The sum of the absorbing fitness of the absorbing parameters in the multiple convergent absorbing parameter groups is calculated, and T convergent absorbing parameter groups with the largest sum of absorbing fitness are output as multiple absorbing parameter sets, where T is an integer greater than 1.

3. The method according to claim 2, characterized in that The iterative update optimization of the processing parameters of the absorbing layer is performed within the plurality of first absorbing parameter groups, including: In the plurality of first absorbing parameter sets, respectively, the plurality of edge first absorbing parameters are updated with the center first absorbing parameter as the updating direction to obtain a plurality of edge second absorbing parameters; Based on the plurality of edge second wave absorbing parameters, a plurality of second wave absorbing adaptabilities are calculated and judged, and the central wave absorbing parameters and the edge wave absorbing parameters are updated to obtain a plurality of second wave absorbing parameter groups; Continue to update and optimize the processing parameters of the absorbing layer within the plurality of second absorbing parameter groups.

4. The method according to claim 1, characterized in that According to the plurality of plate quality information sets, an optimal absorbing parameter set is selected, including: In the plurality of plate quality information sets, weighted calculation is performed to obtain a plurality of comprehensive plate quality information; The absorbing parameter set corresponding to the maximum comprehensive plate quality information is selected to obtain the optimal absorbing parameter set.

5. A processing parameter optimization system for an absorbing plate, characterized in that: The system comprises: A parameter range acquisition module, the parameter range acquisition module is used to acquire a processing parameter range for processing the wave absorbing layer in the wave absorbing plate to be prepared, and a processing parameter range for the heat dissipation layer, to obtain a wave absorbing parameter range and a heat dissipation parameter range; A first optimization module, wherein the first optimization module is used to optimize the processing parameters of the absorbing layer within the absorbing parameter range based on improving the absorbing performance to obtain a plurality of absorbing parameter sets; A first prediction module, the first prediction module is used to predict the absorbing temperature and the quality of the absorbing plate based on the multiple absorbing parameter sets and the electromagnetic parameters of the working environment of the absorbing plate, and obtain multiple plate quality information sets; A second optimization module, the second optimization module is used to select an optimal absorbing parameter set according to the multiple plate quality information sets; A third optimization module, the third optimization module is used to optimize the processing parameters of the heat dissipation layer within the heat dissipation parameter range based on the optimal absorbing parameter set, with the purpose of reducing the absorbing temperature rise, to obtain the optimal heat dissipation parameter set; A fourth optimization module, the fourth optimization module is used to combine the optimal absorbing parameters and the optimal heat dissipation parameters in the optimal absorbing parameter set and the optimal heat dissipation parameter set as a processing parameter optimization result of the absorbing plate; The system further comprises: Function module, the function module is used to construct an absorption optimization function based on improving the absorption performance, as shown in the following formula: Where abs is the absorbing adaptability, M is the number of types of electromagnetic waves in the working environment of the absorbing plate, and w i is the weight of the i-th electromagnetic wave, K i is the reflection loss of the absorbing plate processed according to the absorbing parameters when the ith electromagnetic wave is used to test the absorbing plate; A fifth optimization module, the fifth optimization module is used to optimize the processing parameters of the absorbing layer within the absorbing parameter range according to the absorbing optimization function to obtain multiple absorbing parameter sets; The system further comprises: A first parameter acquisition module, the first parameter acquisition module is used to obtain M electromagnetic wave parameters of the working environment of the absorbing plate, where M is an integer greater than 1; A second parameter acquisition module, the second parameter acquisition module is used to acquire a sample absorption parameter set, a sample electromagnetic parameter set and a sample temperature set; A first branch training module, the first branch training module is used to train an absorption temperature prediction branch by using the sample absorption parameter set, the sample electromagnetic parameter set and the sample temperature set; A grade acquisition module, the grade acquisition module is used to obtain a set of sample plate quality grades; A second branch training module, the second branch training module is used to train a board quality prediction branch by using the sample temperature set and the sample board quality grade set; A second prediction module, the second prediction module is used to connect the absorbing temperature prediction branch and the plate quality prediction branch, and perform absorbing temperature prediction and plate quality prediction of the absorbing plate based on the M electromagnetic wave parameters and multiple absorbing parameter sets to obtain multiple plate quality information sets; The system further comprises: A second random generation module, the second random generation module is used to randomly generate a plurality of first heat dissipation parameters within the heat dissipation parameter range; A fourth calculation module, the fourth calculation module is used to perform simulated production and testing of the absorbing plate based on the multiple first heat dissipation parameters and the optimal absorbing parameter set, and perform absorbing temperature prediction and plate quality prediction, and calculate and obtain multiple first heat dissipation adaptability; A division module, the division module is used to divide and cluster according to the multiple first heat dissipation fitnesses to obtain multiple first heat dissipation parameter groups; A second updating and optimizing module, wherein the second updating and optimizing module is used to continue updating and optimizing the processing parameters of the heat dissipation layer within the plurality of first heat dissipation parameter groups until convergence occurs, thereby obtaining a plurality of converged heat dissipation parameter groups; The fifth calculation module is used to calculate the comprehensive heat dissipation fitness of the heat dissipation parameters in multiple convergent heat dissipation parameter groups, and output the convergent heat dissipation parameter group with the largest sum of heat dissipation fitness as the optimal heat dissipation parameter set.

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