CN116562053A - Method and device for determining broadband material parameters - Google Patents
Method and device for determining broadband material parameters Download PDFInfo
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Abstract
The application provides a method and a device for determining broadband material parameters, wherein the method comprises the following steps: testing a test board made of a material to be tested through a network analyzer to obtain test data; constructing a simulation model corresponding to the material to be tested; simulating the simulation model to obtain simulation data; constructing a target optimization design model according to the test data, the simulation model and the simulation data; performing global exploration on variables of the target optimal design model to determine an optimal design scheme; performing consistency verification processing on the optimal design scheme according to the test data to obtain a target change curve of dielectric constant and loss factor along with frequency change; and determining the frequency-dependent characteristic parameters of the material to be measured according to the target change curve. Therefore, the method and the device can combine simulation and test to obtain the material parameters of the broadband material, the material parameters can accurately represent the performance of the material, the accuracy of simulation results is improved, and the consistency of simulation and actual test is ensured.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a method and a device for determining broadband material parameters.
Background
At present, for signal integrity simulation, the accuracy of material parameters directly determines the reliability and engineering value of simulation results. In the prior art, the dielectric constant (Dk) and dielectric loss (Df) of a plastic material are parameters which change along with frequency, but often material manufacturers can only provide material parameters of single or a plurality of frequency points, and the frequency-dependent characteristics and causal relation of the material cannot be accurately represented, so that the requirement of high-speed circuit simulation precision cannot be met; and with the increase of frequency, the influence of the roughness of the copper foil on the performance is not negligible, so that the correction and fitting of the frequency-dependent Dk and Df parameters and the roughness model of the material are vital links of simulation design.
Disclosure of Invention
The embodiment of the application aims to provide a method and a device for determining broadband material parameters, which can be used for acquiring the material parameters of a broadband material by combining simulation and test, wherein the material parameters can accurately represent the performance of the material, are beneficial to improving the accuracy of simulation results, and ensure the consistency of simulation and actual test.
The first aspect of the present application provides a method for determining broadband material parameters, including:
testing a test board made of a material to be tested through a network analyzer to obtain test data; wherein the test data includes insertion loss and return loss;
constructing a simulation model corresponding to the material to be tested;
simulating the simulation model to obtain simulation data;
constructing a target optimization design model according to the test data, the simulation model and the simulation data;
performing global exploration on the variables of the target optimal design model to determine an optimal design scheme;
performing consistency verification processing on the optimal design scheme according to the test data to obtain a target change curve of dielectric constant and loss factor along with frequency change;
and determining the frequency-dependent characteristic parameters of the material to be measured according to the target change curve.
Further, the constructing a simulation model corresponding to the material to be tested includes:
obtaining an EDA design file for manufacturing the test board by using the material to be tested;
constructing a simulation model based on the EDA design file; the simulation model comprises a frequency-dependent parameter model and a copper foil roughness model.
Further, the constructing a target optimization design model according to the test data, the simulation model and the simulation data includes:
reading parameter variables and simulation data of the simulation model through parameter optimization software; the simulation data at least comprises a simulation insertion loss amplitude value, a simulation insertion loss phase and a simulation return loss;
setting the parameter variable of the simulation model as a preset variable range, and defining a design space according to the parameter variable;
analyzing the test data to obtain processed parameter data; wherein the parameter data includes insertion loss amplitude, insertion loss phase and return loss;
adding the parameter data into the parameter optimization software to obtain a target optimization reference model;
and establishing a target optimization design model according to the simulation model, the simulation data, the design space and the target optimization reference model.
Further, the global exploration is performed on the variables of the target optimal design model, and an optimal design scheme is determined, including:
determining an optimization target according to the simulation data and a target optimization design model;
performing global exploration on variables of the target optimal design model according to the optimal target to obtain a plurality of optimal design schemes;
and determining an optimal design scheme from the plurality of optimal design schemes.
Further, the consistency verification processing is performed on the optimal design scheme according to the test data to obtain a target change curve of dielectric constant and loss factor along with the change of frequency, including:
performing result verification on the optimal design scheme according to the test data to obtain a verification result;
and carrying out post-processing on the verification result to obtain a target change curve of dielectric constant and loss factor along with the change of frequency.
Further, the determining the frequency-dependent characteristic parameter of the material to be measured according to the target change curve includes:
generating form parameters according to the target change curve;
and determining the frequency-dependent characteristic parameters of the material to be tested according to the table parameters.
A second aspect of the present application provides a broadband material parameter determining apparatus, including:
the test unit is used for testing the test board made of the material to be tested through the network analyzer to obtain test data; wherein the test data includes insertion loss and return loss;
the first construction unit is used for constructing a simulation model corresponding to the material to be tested;
the simulation unit is used for simulating the simulation model to obtain simulation data;
the second construction unit is used for constructing a target optimization design model according to the test data, the simulation model and the simulation data;
the first processing unit is used for globally exploring the variables of the target optimal design model to determine an optimal design scheme;
the second processing unit is used for carrying out consistency verification processing on the optimal design scheme according to the test data to obtain a target change curve of dielectric constant and loss factor along with frequency change;
and the determining unit is used for determining the frequency-dependent characteristic parameters of the material to be detected according to the target change curve.
Further, the first building unit includes:
the obtaining subunit is used for obtaining EDA design files for manufacturing the test board by using the material to be tested;
a building subunit for building a simulation model based on the EDA design file; the simulation model comprises a frequency-dependent parameter model and a copper foil roughness model.
Further, the second building unit includes:
the reading subunit is used for reading the parameter variables and the simulation data of the simulation model through parameter optimization software; the simulation data at least comprises a simulation insertion loss amplitude value, a simulation insertion loss phase and a simulation return loss;
the setting subunit is used for setting the parameter variable of the simulation model as a preset variable range and defining a design space according to the parameter variable;
the analysis subunit is used for analyzing the test data to obtain processed parameter data; wherein the parameter data includes insertion loss amplitude, insertion loss phase and return loss;
an adding subunit, configured to add the parameter data to the parameter optimization software to obtain a target optimization reference model;
and the establishing subunit is used for establishing a target optimization design model according to the simulation model, the simulation data, the design space and the target optimization reference model.
Further, the first processing unit includes:
the first determining subunit is used for determining an optimization target according to the simulation data and the target optimization design model;
the first processing subunit is used for globally exploring the variables of the target optimal design model according to the optimization target to obtain a plurality of optimal design schemes;
the first determining subunit is further configured to determine an optimal design from the plurality of optimal designs.
Further, the second processing unit includes:
the verification subunit is used for verifying the result of the optimal design scheme according to the test data to obtain a verification result;
and the second processing subunit is used for carrying out post-processing on the verification result to obtain a target change curve of dielectric constant and loss factor along with the change of frequency.
Further, the determining unit includes:
a generating subunit, configured to generate a table parameter according to the target change curve;
and the second determination subunit is used for determining the frequency-dependent characteristic parameters of the material to be measured according to the table parameters.
A third aspect of the present application provides an electronic device comprising a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to perform the method of determining broadband material parameters of any one of the first aspects of the present application.
A fourth aspect of the present application provides a computer readable storage medium storing computer program instructions which, when read and executed by a processor, perform the method of determining a wideband material parameter as claimed in any one of the first aspects of the present application.
The beneficial effects of this application are: the method and the device can combine simulation and test to obtain the material parameters of the broadband material, the material parameters can accurately represent the performance of the material, the accuracy of simulation results is improved, and the consistency of simulation and actual test is ensured.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a method for determining wideband material parameters according to an embodiment of the present application;
FIG. 2 is a flow chart of another method for determining wideband material parameters according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a device for determining wideband material parameters according to an embodiment of the present application;
FIG. 4 is a schematic structural diagram of another device for determining wideband material parameters according to an embodiment of the present application;
FIG. 5 is a schematic diagram of test data according to an embodiment of the present application;
FIG. 6 is a schematic diagram of a simulation model according to an embodiment of the present application;
fig. 7 is a schematic diagram of frequency-dependent parameter setting in a frequency-dependent parameter model according to an embodiment of the present application;
FIG. 8 is a schematic diagram of a copper foil roughness setting in a copper foil roughness model according to an embodiment of the present application;
FIG. 9 is a schematic diagram showing the comparison of simulation and actual measurement results of an optimal optimization scheme according to the embodiment of the present application;
fig. 10 is a schematic diagram of DK and DF frequency-dependent curves provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of a method for determining wideband material parameters according to the present embodiment. The method for determining the broadband material parameters comprises the following steps:
s101, testing a test board made of a material to be tested through a network analyzer to obtain test data.
In this embodiment, the test data includes insertion loss and return loss.
S102, constructing a simulation model corresponding to the material to be tested.
S103, simulating the simulation model to obtain simulation data.
S104, constructing a target optimization design model according to the test data, the simulation model and the simulation data.
S105, performing global exploration on variables of the target optimal design model, and determining an optimal design scheme.
S106, carrying out consistency verification processing on the optimal design scheme according to the test data to obtain a target change curve of dielectric constant and loss factor along with the change of frequency.
S107, determining the frequency-dependent characteristic parameters of the material to be measured according to the target change curve.
In this embodiment, the execution subject of the method may be a computing device such as a computer or a server, which is not limited in this embodiment.
In this embodiment, the execution body of the method may be an intelligent device such as a smart phone or a tablet computer, which is not limited in this embodiment.
Therefore, by implementing the method for determining the broadband material parameters described in the embodiment, a method combining simulation and test can be used, meanwhile, the frequency-dependent characteristic and the copper foil roughness characteristic of the material are considered, and a global exploration method of parameter optimization software is utilized, so that the obtained material parameters can accurately represent the material characteristics, the accuracy of simulation results is further improved, and the consistency of simulation and actual test is ensured.
Example 2
Referring to fig. 2, fig. 2 is a flow chart of a method for determining wideband material parameters according to the present embodiment. The method for determining the broadband material parameters comprises the following steps:
s201, testing a test board made of a material to be tested through a network analyzer to obtain test data.
In this embodiment, the test data includes insertion loss and return loss.
In this embodiment, the method may design and process a test board, and test the test board using a network analyzer, so as to obtain parameters such as insertion loss and return loss.
In this embodiment, the method may use EDA software to design a test board (the test board uses a material to be tested), and use a network analyzer to test the test board after the processing is completed, so as to obtain the insertion loss and the return loss, and then save the test data as a touchtone format.
Referring to fig. 5, fig. 5 shows a schematic diagram of test data.
S202, acquiring EDA design files for manufacturing the test board by using the material to be tested.
S203, constructing a simulation model based on the EDA design file.
In this embodiment, the simulation model includes a frequency-dependent parameter model and a copper foil roughness model.
Referring to fig. 6, fig. 6 shows a schematic diagram of a simulation model.
Referring to fig. 7, fig. 7 shows a schematic diagram of the frequency-dependent parameter setting in the frequency-dependent parameter model.
Referring to fig. 8, fig. 8 shows a schematic view of the copper foil roughness setting in the copper foil roughness model.
S204, simulating the simulation model to obtain simulation data.
In this embodiment, the material parameters DK (dielectric constant) and DF (dissipation factor) of the PCB insulating substrate in the simulation model may be set as parameters that vary with frequency. The frequency-dependent parameter model uses Djordjevic-Sarkar model, and the specific formula is as follows:
；
wherein ε is the complex dielectric constant;
ε ∞ is a high-frequency dielectric constant;
delta epsilon is the difference between the DC dielectric constant and the high frequency dielectric constant;
m 1 and m 2 Is a constant;
below this frequency, the dielectric constant is close to its dc dielectric constant;
above this frequency, the dielectric constant is close to its high frequency dielectric constant;
f is the frequency;
i is an imaginary unit.
The method can characterize the material requirement epsilon of a frequency change according to the formula ∞ 、Δε、m 1 、m 2 Four parameters. Wherein the method uses epsilon in a simulation model ∞ ，Δε，m 1 ，m 2 The complex dielectric constant epsilon is set as a variable and described in the simulation model according to the above formula.
In this embodiment, since the copper foil roughness has a large influence on the loss in the high frequency band, the method sets the copper foil roughness parameter to the metal part in the simulation model. Wherein, the roughness of the copper foil uses a Huray model, and two parameters of 'Nodule Radius' and 'Hall-Huray Surface Ratio' which represent snowball size and snowbank size are set as variables.
At this time, the simulation model is calculated to obtain the simulated insertion loss amplitude, insertion loss phase and return loss.
S205, reading parameter variables and simulation data of the simulation model through parameter optimization software.
In this embodiment, the simulation data includes at least a simulated insertion loss amplitude, a simulated insertion loss phase, and a simulated return loss.
S206, setting the parameter variable of the simulation model as a preset variable range, and defining a design space according to the parameter variable.
S207, analyzing the test data to obtain processed parameter data.
In this embodiment, the parameter data includes an insertion loss amplitude, an insertion loss phase, and a return loss.
S208, adding the parameter data into the parameter optimization software to obtain a target optimization reference model.
S209, establishing a target optimization design model according to the simulation model, the simulation data, the design space and the target optimization reference model.
S210, determining an optimization target according to the simulation data and the target optimization design model.
S211, performing global exploration on variables of the target optimization design model according to the optimization target to obtain a plurality of optimization design schemes.
In this embodiment, the method may use parameter optimization software to build an optimal design model, define a design space, an optimal reference model and an optimal target, and obtain an optimal design scheme.
In this embodiment, the method may select the calculated simulation model engineering in the parameter optimization software, and automatically read the parameter variables of the simulation model and the processed data result.
Specifically, the method can set the parameter variable in the read simulation model as a reasonable variable range and define a design space; the obtained test data is then analyzed and processed using circuit simulation software. Wherein the starting frequency and step size of the sweep setting are consistent with the previous setting. And adding the processed insertion loss amplitude value, insertion loss phase and return loss parameter data into an optimal design model after analysis is completed, and taking the optimal design model as a target optimal reference model.
Thereafter, the method re-uses the insertion loss amplitude, insertion loss phase and return loss parameters as optimization targets; the insertion loss amplitude is constrained by mean square error of simulation and test data, the insertion loss phase is constrained by maximum difference of the simulation and test data, and the return loss is constrained by mean value of the simulation and test data.
Finally, analysis is performed based on the information to obtain a plurality of optimal design schemes.
S212, determining an optimal design scheme from a plurality of optimal design schemes.
And S213, verifying the result of the optimal design scheme according to the test data to obtain a verification result.
Referring to fig. 9, fig. 9 shows a comparison of the best-effort simulation and the measured results.
S214, post-processing is carried out on the verification result to obtain a target change curve of dielectric constant and loss factor along with the change of frequency.
Referring to fig. 10, fig. 10 shows a schematic diagram of DK and DF frequency-dependent curves.
S215, generating table parameters according to the target change curve.
In this embodiment, the method may select an optimal design scheme from the optimization schemes obtained in the above steps, and verify consistency of simulation and test of insertion loss amplitude, insertion loss phase and return loss parameters under the scheme.
After that, a curve of dielectric constant DK and loss factor DF with respect to frequency is obtained by post-processing, and table parameters are generated.
It can be seen that the method can obtain DK and DF parameters which change with frequency.
S216, determining the frequency-dependent characteristic parameters of the material to be tested according to the table parameters.
In this embodiment, the method may first design and process a test board using a material to be tested, and then test the test board using a network analyzer, thereby obtaining curves and data such as insertion loss and return loss. The data provides optimization criteria for subsequent optimization and demonstrates the accuracy of the subsequently derived optimization design.
In this embodiment, after obtaining the design file, the method may build a simulation model according to the design file. In order to characterize the true nature of the material, the method requires setting the substrate material as a frequency-dependent parameter, and if a constant is set, the results of the simulation will be distorted. In addition, the roughness of the metal part is also a factor influencing the loss, and the roughness of the copper foil is required to be optimally designed for more accurate analysis. After the simulation model is established, the simulation model can be analyzed, then the insertion loss amplitude, the insertion loss phase and the return loss are obtained in a data post-processing mode, and a constraint target is provided for subsequent optimization definition.
In this embodiment, the method may further establish an optimization design model, where the optimization design model includes defining a design space, an optimization reference model and an optimization target, and may utilize optimization software to globally explore the frequency-dependent parameters defined in the steps and variables of the copper foil roughness model with the performance parameters obtained by the previous step test as optimization criteria and with the insertion loss amplitude, the insertion loss phase and the return loss as constraint targets, to finally obtain a plurality of optimization design schemes.
In this embodiment, the method may select an optimal solution from the optimal design solutions for result verification, and then obtain a curve of the dielectric constant DK and the loss factor DF along with the frequency change through post-processing, and further generate table parameters, thereby obtaining the frequency-dependent characteristic parameters of the material to be tested.
Based on the method, when the material is used for the subsequent products, the parameters can be directly used for simulation, so that the method can improve the accuracy of the simulation result and shorten the simulation period.
In this embodiment, the execution subject of the method may be a computing device such as a computer or a server, which is not limited in this embodiment.
In this embodiment, the execution body of the method may be an intelligent device such as a smart phone or a tablet computer, which is not limited in this embodiment.
Therefore, by implementing the method for determining the broadband material parameters described in the embodiment, a method combining simulation and test can be used, meanwhile, the frequency-dependent characteristic and the copper foil roughness characteristic of the material are considered, and a global exploration method of parameter optimization software is utilized, and multiple parameters including insertion loss amplitude, insertion loss phase and return loss are used as constraint targets, so that the obtained material parameters can accurately represent the material characteristics, the accuracy of simulation results is further improved, and the consistency of simulation and actual test is ensured.
Example 3
Referring to fig. 3, fig. 3 is a schematic structural diagram of a broadband material parameter determining apparatus according to the present embodiment. As shown in fig. 3, the device for determining the broadband material parameters includes:
the testing unit 310 is configured to test a test board made of a material to be tested through a network analyzer to obtain test data; wherein the test data includes insertion loss and return loss;
a first construction unit 320, configured to construct a simulation model corresponding to the material to be tested;
the simulation unit 330 is configured to simulate the simulation model to obtain simulation data;
a second construction unit 340, configured to construct a target optimization design model according to the test data, the simulation model, and the simulation data;
the first processing unit 350 is configured to globally explore variables of the target optimal design model, and determine an optimal design scheme;
the second processing unit 360 is configured to perform consistency verification processing on the optimal design scheme according to the test data, so as to obtain a target variation curve of dielectric constant and loss factor along with frequency variation;
a determining unit 370, configured to determine the frequency-dependent characteristic parameter of the material to be measured according to the target variation curve.
In this embodiment, the explanation of the device for determining the wideband material parameter may refer to the description in embodiment 1 or embodiment 2, and the description is not repeated in this embodiment.
Therefore, the device for determining the broadband material parameters described in the embodiment can use a method of combining simulation and test, considers the frequency-dependent characteristic of the material and the roughness characteristic of the copper foil, and uses the global exploration method of parameter optimization software to use the insertion loss amplitude, the insertion loss phase and the return loss as constraint targets, so that the obtained material parameters can accurately represent the material characteristics, further improve the accuracy of simulation results, and ensure the consistency of simulation and actual test.
Example 4
Referring to fig. 4, fig. 4 is a schematic structural diagram of a wideband material parameter determining apparatus according to the present embodiment. As shown in fig. 4, the device for determining the broadband material parameters includes:
the testing unit 310 is configured to test a test board made of a material to be tested through a network analyzer to obtain test data; wherein the test data includes insertion loss and return loss;
a first construction unit 320, configured to construct a simulation model corresponding to the material to be tested;
the simulation unit 330 is configured to simulate the simulation model to obtain simulation data;
a second construction unit 340, configured to construct a target optimization design model according to the test data, the simulation model, and the simulation data;
the first processing unit 350 is configured to globally explore variables of the target optimal design model, and determine an optimal design scheme;
the second processing unit 360 is configured to perform consistency verification processing on the optimal design scheme according to the test data, so as to obtain a target variation curve of dielectric constant and loss factor along with frequency variation;
a determining unit 370, configured to determine the frequency-dependent characteristic parameter of the material to be measured according to the target variation curve.
As an alternative embodiment, the first construction unit 320 includes:
an obtaining subunit 321, configured to obtain an EDA design file for manufacturing a test board using a material to be tested;
a build subunit 322 for building a simulation model based on the EDA design file; the simulation model comprises a frequency-dependent parameter model and a copper foil roughness model.
As an alternative embodiment, the second construction unit 340 includes:
a reading subunit 341, configured to read, by using parameter optimization software, parameter variables and simulation data of the simulation model; the simulation data at least comprises a simulation insertion loss amplitude value, a simulation insertion loss phase and a simulation return loss;
a setting subunit 342, configured to set a parameter variable of the simulation model to a preset variable range, and define a design space according to the parameter variable;
an analysis subunit 343, configured to analyze the test data to obtain processed parameter data; wherein the parameter data includes insertion loss amplitude, insertion loss phase and return loss;
an adding subunit 344, configured to add the parameter data to the optimization software to obtain a target optimization reference model;
the establishing subunit 345 is configured to establish a target optimization design model according to the simulation model, the simulation data, the design space and the target optimization reference model.
As an alternative embodiment, the first processing unit 350 includes:
a first determining subunit 351, configured to determine an optimization target according to the simulation data and the target optimization design model;
the first processing subunit 352 is configured to globally explore the variables of the target optimization design model according to the optimization target, so as to obtain a plurality of optimization design schemes;
the first determining subunit 351 is further configured to determine an optimal design from the plurality of optimal designs.
As an alternative embodiment, the second processing unit 360 includes:
a verification subunit 361, configured to perform result verification on the optimal design according to the test data, to obtain a verification result;
the second processing subunit 362 is configured to post-process the verification result to obtain a target variation curve of the dielectric constant and the loss factor with the frequency.
As an alternative embodiment, the determining unit 370 includes:
a generating subunit 371, configured to generate table parameters according to the target change curve;
a second determining subunit 372 is configured to determine the frequency-dependent characteristic parameter of the material to be measured according to the table parameter.
In this embodiment, the explanation of the device for determining the wideband material parameter may refer to the description in embodiment 1 or embodiment 2, and the description is not repeated in this embodiment.
Therefore, the device for determining the broadband material parameters described in the embodiment can use a method of combining simulation and test, considers the frequency-dependent characteristic of the material and the roughness characteristic of the copper foil, and uses the global exploration method of parameter optimization software to use the insertion loss amplitude, the insertion loss phase and the return loss as constraint targets, so that the obtained material parameters can accurately represent the material characteristics, further improve the accuracy of simulation results, and ensure the consistency of simulation and actual test.
An embodiment of the present application provides an electronic device, including a memory and a processor, where the memory is configured to store a computer program, and the processor is configured to execute the computer program to cause the electronic device to execute a method for determining a broadband material parameter in embodiment 1 or embodiment 2 of the present application.
The present embodiment provides a computer-readable storage medium storing computer program instructions that, when read and executed by a processor, perform the method of determining broadband material parameters in embodiment 1 or embodiment 2 of the present application.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other manners as well. The apparatus embodiments described above are merely illustrative, for example, flow diagrams and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely exemplary embodiments of the present application and is not intended to limit the scope of the present application, and various modifications and variations may be suggested to one skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application. It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A method for determining a wideband material parameter, comprising:
testing a test board made of a material to be tested through a network analyzer to obtain test data; wherein the test data includes insertion loss and return loss;
constructing a simulation model corresponding to the material to be tested;
simulating the simulation model to obtain simulation data;
constructing a target optimization design model according to the test data, the simulation model and the simulation data;
performing global exploration on the variables of the target optimal design model to determine an optimal design scheme;
performing consistency verification processing on the optimal design scheme according to the test data to obtain a target change curve of dielectric constant and loss factor along with frequency change;
and determining the frequency-dependent characteristic parameters of the material to be measured according to the target change curve.
2. The method for determining wideband material parameters according to claim 1, wherein said constructing a simulation model corresponding to the material to be measured includes:
obtaining an EDA design file for manufacturing the test board by using the material to be tested;
constructing a simulation model based on the EDA design file; the simulation model comprises a frequency-dependent parameter model and a copper foil roughness model.
3. The method of determining wideband material parameters according to claim 1, wherein the constructing a target optimization design model from the test data, the simulation model, and the simulation data comprises:
reading parameter variables and simulation data of the simulation model through parameter optimization software; the simulation data at least comprises a simulation insertion loss amplitude value, a simulation insertion loss phase and a simulation return loss;
setting the parameter variable of the simulation model as a preset variable range, and defining a design space according to the parameter variable;
analyzing the test data to obtain processed parameter data; wherein the parameter data includes insertion loss amplitude, insertion loss phase and return loss;
adding the parameter data into the parameter optimization software to obtain a target optimization reference model;
and establishing a target optimization design model according to the simulation model, the simulation data, the design space and the target optimization reference model.
4. The method for determining broadband material parameters according to claim 1, wherein the global exploration of the variables of the target optimal design model is performed to determine an optimal design scheme, including:
determining an optimization target according to the simulation data and a target optimization design model;
performing global exploration on variables of the target optimal design model according to the optimal target to obtain a plurality of optimal design schemes;
and determining an optimal design scheme from the plurality of optimal design schemes.
5. The method for determining wideband material parameters according to claim 1, wherein said performing a consistency verification process on the optimal design according to the test data to obtain a target variation curve of dielectric constant and loss factor with frequency variation, comprises:
performing result verification on the optimal design scheme according to the test data to obtain a verification result;
and carrying out post-processing on the verification result to obtain a target change curve of dielectric constant and loss factor along with the change of frequency.
6. The method for determining a wideband material parameter according to claim 1, wherein determining the frequency-dependent characteristic parameter of the material to be measured according to the target variation curve includes:
generating form parameters according to the target change curve;
and determining the frequency-dependent characteristic parameters of the material to be tested according to the table parameters.
7. A broadband material parameter determining apparatus, wherein the broadband material parameter determining apparatus includes:
the test unit is used for testing the test board made of the material to be tested through the network analyzer to obtain test data; wherein the test data includes insertion loss and return loss;
the first construction unit is used for constructing a simulation model corresponding to the material to be tested;
the simulation unit is used for simulating the simulation model to obtain simulation data;
the second construction unit is used for constructing a target optimization design model according to the test data, the simulation model and the simulation data;
the first processing unit is used for globally exploring the variables of the target optimal design model to determine an optimal design scheme;
the second processing unit is used for carrying out consistency verification processing on the optimal design scheme according to the test data to obtain a target change curve of dielectric constant and loss factor along with frequency change;
and the determining unit is used for determining the frequency-dependent characteristic parameters of the material to be detected according to the target change curve.
8. The apparatus for determining a wideband material parameter of claim 7, wherein the first building unit comprises:
the obtaining subunit is used for obtaining EDA design files for manufacturing the test board by using the material to be tested;
a building subunit for building a simulation model based on the EDA design file; the simulation model comprises a frequency-dependent parameter model and a copper foil roughness model.
9. An electronic device comprising a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to perform the method of determining wideband material parameters of any one of claims 1 to 6.
10. A readable storage medium, characterized in that it has stored therein computer program instructions which, when read and executed by a processor, perform the method of determining wideband material parameters according to any of claims 1 to 6.
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