Method, apparatus, electronic device, and storage medium for determining material parameter values

Abstract

The present disclosure relates to a method, apparatus, electronic device, and storage medium for determining material parameter values, and pertains to the field of materials. It aims to solve the technical problem of low accuracy of material parameter values of printed circuit boards, and obtain the material parameter values of printed circuit boards at different frequency points. The method includes: obtaining scattering parameters of a target printed circuit board, where the scattering parameters include insertion loss and return loss; obtaining a plurality of clusters; determining a target cluster to which the target printed circuit board belongs from the plurality of clusters according to the plurality of clusters and the scattering parameters of the target printed circuit board; and determining the material parameter values of the target printed circuit board corresponding to a plurality of frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster.

Description

Technical Field

[0001] The present disclosure relates to the field of materials, and in particular, to a method, an apparatus, an electronic device, and a storage medium for determining material parameter values. Background Art

[0002] In circuit design, devices and carriers for signal transmission usually use PCBs (Printed Circuit Boards). The material characteristics of printed circuit boards have a significant impact on the electrical performance of communication systems. In order to accurately use printed circuit boards in engineering and research, it is necessary to obtain the material parameter values of printed circuit boards.

[0003] The material parameter values of printed circuit boards provided by printed circuit board material manufacturers are usually the material parameter values measured under a certain specific environment. However, the material parameter values of printed circuit boards may be different in different environments. In related technologies, a simulation model is built in simulation software to obtain simulation data, and then the simulation data is fitted with test data to obtain the fitted material parameter values of the printed circuit board. However, the accuracy of the simulation model is low, and the fitting process is rough, resulting in low accuracy of the fitted material parameter values of the printed circuit board, and usually only a fixed material parameter value can be fitted, and the material parameter values in different environments cannot be obtained. Summary of the Invention

[0004] To overcome the problems existing in related technologies, the present disclosure provides a method, an apparatus, an electronic device, and a storage medium for determining material parameter values. The technical solutions of the present disclosure are as follows:

[0005] According to a first aspect of an embodiment of the present disclosure, a method for determining material parameter values is provided, including:

[0006] Obtain scattering parameters of a target printed circuit board, where the scattering parameters include insertion loss and return loss;

[0007] Obtain a plurality of clusters, where the plurality of clusters are obtained by clustering a plurality of printed circuit board samples according to their respective scattering parameters, and the material parameter values of each cluster correspond to a multi-dimensional Gaussian distribution, and the dimensions of the multi-dimensional Gaussian distribution include a frequency domain dimension;

[0008] Determine a target cluster to which the target printed circuit board belongs from the plurality of clusters according to the plurality of clusters and the scattering parameters of the target printed circuit board;

[0009] Determine the material parameter values of the target printed circuit board corresponding to a plurality of frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster.

[0010] Optionally, the multiple clusters and the multi-dimensional Gaussian distributions corresponding to the material parameter values of each cluster are determined according to the following steps:

[0011] Obtain the scattering parameters of each of the multiple printed circuit board samples;

[0012] Select multiple scattering parameters as the clustering centers of multiple initial clusters;

[0013] According to the scattering parameters of each of the multiple printed circuit board samples and the clustering centers of the multiple initial clusters, cluster the multiple printed circuit board samples into the multiple initial clusters in sequence, and iterate the clustering centers of the initial clusters when the printed circuit board samples included in each initial cluster change;

[0014] Repeat the above steps until the termination condition is met to obtain the multiple clusters;

[0015] Obtain the material parameter values of each of the multiple printed circuit board samples at the multiple frequency points;

[0016] According to the material parameter values of each of the printed circuit board samples included in each cluster at the multiple frequency points, determine the multi-dimensional Gaussian distribution corresponding to the material parameter value of each cluster.

[0017] Optionally, the dimensions of the multi-dimensional Gaussian distribution include but are not limited to: the temperature dimension and the humidity dimension;

[0018] The material parameter values of each of the multiple printed circuit board samples at the multiple frequency points include: the material parameter values corresponding to the multiple frequency points of each of the multiple printed circuit board samples under different dimensional parameters;

[0019] The determining of the material parameter values of the target printed circuit board corresponding to the multiple frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter value of the target cluster includes:

[0020] According to the multi-dimensional Gaussian distribution corresponding to the material parameter value of the target cluster, determine the material parameter values corresponding to the multiple frequency points of the target printed circuit board under the different dimensional parameters.

[0021] Optionally, the scattering parameters include scattering parameters in multiple dimensions, and the multiple dimensions include but are not limited to: the temperature dimension and the humidity dimension;

[0022] The obtaining of the scattering parameters of each of the multiple printed circuit board samples includes:

[0023] Set different dimensional parameters according to the multiple dimensions;

[0024] Under the different dimensional parameters, obtain the scattering parameters of the multiple printed circuit board samples;

[0025] The selecting multiple scattering parameters as the clustering centers of multiple initial clusters includes:

[0026] Select multiple parameter parameters under the different dimensional parameters as the clustering centers of the multiple initial clusters.

[0027] Optionally, the obtaining the scattering parameters of the target printed circuit board includes:

[0028] Set the different dimensional parameters according to the multiple dimensions;

[0029] Under the different dimensional parameters, obtain the scattering parameters of the target printed circuit board.

[0030] Optionally, the termination condition is any one of the following:

[0031] None or the minimum number of the printed circuit board samples are reassigned to different initial clusters;

[0032] None or the minimum number of the clustering centers of the initial clusters change again;

[0033] The sum of squared errors between the scattering parameters of the printed circuit board samples and the clustering centers of the initial clusters is locally minimum.

[0034] Optionally, the determining the target cluster to which the target printed circuit board belongs from the multiple clusters according to the multiple clusters and the scattering parameters of the target printed circuit board includes:

[0035] Obtain the distances between the clustering centers of the multiple clusters and the scattering parameters of the target printed circuit board;

[0036] Determine the cluster closest to the scattering parameters of the target printed circuit board as the target cluster to which the target printed circuit board belongs.

[0037] Optionally, the material parameter values include: the dielectric constant value of the board and the dielectric loss factor.

[0038] According to the second aspect of the embodiments of the present disclosure, there is provided a device for determining material parameter values, including:

[0039] A parameter acquisition module configured to acquire the scattering parameters of a target printed circuit board, where the scattering parameters include insertion loss and return loss;

[0040] Cluster acquisition module, configured to acquire a plurality of clusters, where the plurality of clusters are obtained by clustering a plurality of printed circuit board samples according to their respective scattering parameters, and the material parameter values of each cluster correspond to a multi-dimensional Gaussian distribution, and the dimensions of the multi-dimensional Gaussian distribution include a frequency domain dimension;

[0041] Target determination module, configured to determine a target cluster to which the target printed circuit board belongs from the plurality of clusters according to the plurality of clusters and the scattering parameters of the target printed circuit board;

[0042] Parameter value determination module, configured to determine the material parameter values of the target printed circuit board corresponding to a plurality of frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster.

[0043] According to a third aspect of the embodiments of the present disclosure, there is provided an electronic device, including: a processor; a memory for storing instructions executable by the processor; wherein, the processor is configured to execute the instructions to implement the method for determining material parameter values as described in the first aspect.

[0044] According to a fourth aspect of the embodiments of the present disclosure, there is provided a non-volatile readable storage medium, when the instructions in the non-volatile readable storage medium are executed by a processor of an electronic device, enabling the electronic device to execute the method for determining material parameter values as described in the first aspect.

[0045] The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects:

[0046] In the embodiments of the present disclosure, each cluster is obtained by clustering a plurality of printed circuit board samples according to their respective scattering parameters. Therefore, the scattering parameters of the plurality of printed circuit board samples included in each cluster are similar. When the scattering parameters of the printed circuit boards are similar, the material parameters of the printed circuit boards are also similar; the material parameter value group corresponding to each cluster is determined based on the Gaussian distribution of the material parameter values of the plurality of printed circuit board samples included in the cluster; therefore, the material parameter value group corresponding to a cluster can accurately reflect the material parameter values of the respective printed circuit board samples included in the cluster. Furthermore, the material parameter values of the target printed circuit board determined according to the material parameter value group corresponding to the target cluster to which the target printed circuit board belongs are relatively accurate. Since the material parameter value group corresponding to the cluster includes the material parameter values corresponding to a plurality of frequency points, the determined material parameter values of the target printed circuit board are the material parameter values corresponding to a plurality of frequency points.

[0047] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. Description of the Drawings

[0048] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure.

[0049] Figure 1 is a flowchart of the steps of a method for determining a material parameter value shown in an embodiment of the present disclosure;

[0050] Figure 2 is a schematic flowchart of a method for determining a material parameter value shown in an embodiment of the present disclosure;

[0051] Figure 3 is a schematic diagram of the composition of a computer device shown in an embodiment of the present disclosure;

[0052] Figure 4 is a block diagram of a device for determining a material parameter value shown in an embodiment of the present disclosure;

[0053] Figure 5 is a schematic diagram of an electronic device shown in an embodiment of the present disclosure. Detailed Embodiments

[0054] In order to enable those of ordinary skill in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0055] The continuous increase in the signal transmission rate of high-speed interconnect links has led to the need to perform signal integrity simulations on the link performance of high-speed interfaces of printed circuit boards during the design and R & D stage. In order to improve the accuracy of signal integrity simulations and achieve a consistent closed-loop verification of signal integrity simulations and tests, an accurate dielectric constant value of the printed circuit board needs to be obtained, so as to perform relevant evaluations such as signal integrity.

[0056] Figure 1 is a flowchart of the steps of a method for determining a material parameter value shown in an embodiment of the present disclosure. As Figure 1 shown, the method for determining the material parameter value includes steps S11 to S14.

[0057] In step S11, scattering parameters of the target printed circuit board are obtained, and the scattering parameters include insertion loss and return loss.

[0058] The target printed circuit board can be any printed circuit board. The scattering parameter (S-parameter) is an important parameter in microwave transmission. The scattering parameter is determined by the information of the material at each frequency point, describes the frequency-domain characteristics of the transmission channel, and through the scattering parameter, almost all the characteristics of the transmission channel can be obtained. Most of the problems concerned with signal integrity, such as signal reflection, crosstalk, and loss, can obtain useful information from the scattering parameter.

[0059] The scattering parameters include insertion loss and return loss. Insertion loss refers to the loss of energy or gain when a device or a branch circuit is added to a certain circuit; insertion loss includes forward transmission coefficient and reverse transmission coefficient. Return loss is the reflection generated by the impedance mismatch of the circuit link, which is the reflection of a pair of lines themselves. Return loss includes input return loss and output return loss. The scattering parameters of the target printed circuit board can be obtained through a VNA (Vector Network Analyser).

[0060] If the scattering parameters of the printed circuit boards are the same, the material parameter values of the printed circuit boards are also the same. The material parameter values of the printed circuit board can include: the dielectric constant value of the board and the dissipation factor of the dielectric.

[0061] Dielectric Constant of the board: It reflects the dielectric properties or polarization properties of the material dielectric under the action of an electrostatic field. The dielectric constant of the board is one of the important parameters when calculating the impedance value and for high-speed transmission; the dielectric constant values of different materials are different, and the dielectric constant value of the material will also change with the change of frequency.

[0062] Dissipation Factor: It is the tangent of the phase difference angle between the strain and stress in the material under the action of an alternating force field, and is also equal to the ratio of the loss modulus to the storage modulus of the material. The dissipation factor will also change with the change of frequency.

[0063] In step S12, multiple clusters are obtained.

[0064] The multiple clusters are obtained by clustering the multiple printed circuit board samples according to their respective scattering parameters. The material parameter value of each cluster corresponds to a multi-dimensional Gaussian distribution, and the dimensions of the multi-dimensional Gaussian distribution include the frequency domain dimension.

[0065] The multiple clusters can be pre-determined. The multiple clusters can be determined according to steps S121 to S121.

[0066] In step S121, the scattering parameters of the multiple printed circuit board samples are obtained.

[0067] The printed circuit board sample can be any printed circuit board, and the scattering parameters of each printed circuit board sample can be obtained. The scattering parameters of each printed circuit board sample can be obtained through a VNA.

[0068] In step S122, multiple scattering parameters are selected as the clustering centers of multiple initial clusters.

[0069] Multiple printed circuit board samples can be randomly selected from multiple printed circuit board samples, and the scattering parameters of each of the selected multiple printed circuit board samples are used as the clustering centers of multiple initial clusters. Multiple scattering parameters can be randomly generated as the clustering centers of multiple initial clusters without selecting from the scattering parameters of multiple printed circuit board samples. Multiple scattering parameters can also be obtained according to a pre-configuration without selecting from the scattering parameters of multiple printed circuit board samples and used as the clustering centers of multiple initial clusters.

[0070] In step S123, according to the scattering parameters of each of the multiple printed circuit board samples and the clustering centers of the multiple initial clusters, the multiple printed circuit board samples are sequentially clustered into the multiple initial clusters, and when the printed circuit board samples included in each initial cluster change, the clustering centers of the initial clusters are iterated.

[0071] After determining the clustering centers of multiple initial clusters, each printed circuit board sample can be sequentially clustered into the initial clusters. When determining which cluster a printed circuit board sample should be clustered into, the scattering parameter of the printed circuit board sample can be obtained, and the latest clustering centers of each initial cluster can be obtained. By calculating the distance between the scattering parameter of the printed circuit board sample and the latest clustering centers of each initial cluster, it is determined that the printed circuit board sample is clustered into the initial cluster with the smallest distance. Optionally, when the distance between the scattering parameter of a printed circuit board sample and the latest clustering centers of each initial cluster is greater than the distance threshold, the printed circuit board sample is not clustered into any initial cluster.

[0072] After each time a printed circuit board sample is clustered into an initial cluster, the clustering center of the initial cluster can be iterated according to each printed circuit board sample included in the initial cluster, and then the next printed circuit board sample is clustered according to the latest clustering center of the iterated initial cluster.

[0073] In step S124, the above steps are repeated until the termination condition is met, and the multiple clusters are obtained.

[0074] Repeat the above steps to cluster each printed circuit board sample. If the termination condition is not met, the next printed circuit board sample is clustered. If the termination condition is met, the clustering of each printed circuit board sample is completed, and the multiple initial clusters at this time are multiple clusters.

[0075] Among them, the termination condition can be any of the following:

[0076] None or the minimum number of the printed circuit board samples are reassigned to different initial clusters;

[0077] There is no change or the minimum number of the cluster centers of the initial clusters changes again;

[0078] The sum of squared errors between the scattering parameters of the printed circuit board samples and the cluster centers of the initial clusters is locally minimized.

[0079] No printed circuit board sample is reassigned to a different initial cluster, indicating that each printed circuit board sample has completed clustering and meets the termination condition.

[0080] When obtaining the scattering parameters of the printed circuit board samples, due to systematic errors, measurement errors, etc., the scattering parameters of the obtained printed circuit board samples may deviate, resulting in the scattering parameters of the printed circuit board samples being unsuitable for assignment to any initial cluster. Therefore, when the minimum number of printed circuit board samples is reassigned to different initial clusters, it indicates that all the printed circuit board samples that can be assigned to each initial cluster have been assigned, meeting the termination condition.

[0081] Since the cluster centers of the initial clusters are determined by the scattering parameters of each printed circuit board sample included in the initial clusters, therefore, when the cluster centers of the initial clusters no longer change, it indicates that each printed circuit board sample has completed clustering and meets the termination condition. When the minimum number of the cluster centers of the initial clusters changes again, it indicates that all the printed circuit board samples that can be assigned to each initial cluster have been assigned, meeting the termination condition.

[0082] The sum of squared errors between the scattering parameters of the printed circuit board samples and the cluster centers of the initial clusters is locally minimized, indicating that each initial cluster converges and meets the termination condition.

[0083] In this way, each of the obtained clusters can contain multiple printed circuit board samples with similar scattering parameters. When the scattering parameters of the printed circuit boards are similar, the material parameters of the printed circuit boards are also similar; furthermore, the material parameter values of each printed circuit board sample included in each cluster are also similar.

[0084] In step S125, obtain the material parameter values of each of the multiple printed circuit board samples at the multiple frequency points.

[0085] Different frequency domain environments can be set to obtain the material parameter values of the multiple printed circuit board samples at different frequency points. Among them, the measurement methods of each material parameter value can refer to the related technologies, and the present disclosure does not limit this.

[0086] In step S126, according to the material parameter values of each printed circuit board sample included in each cluster at the multiple frequency points, determine the multidimensional Gaussian distribution corresponding to the material parameter values of each cluster.

[0087] By fitting the material parameter values of each printed circuit board sample included in each cluster at multiple frequency points, a multi-dimensional Gaussian distribution corresponding to the material parameter values of each cluster can be obtained. The multi-dimensional Gaussian distribution corresponding to the material parameter values of a cluster is essentially the multi-dimensional Gaussian distribution satisfied by the material parameter values of each printed circuit board sample included in that cluster. Since the material parameter values of each printed circuit board sample are the material parameter values at multiple frequency points, one dimension of the multi-dimensional Gaussian distribution is the frequency domain dimension.

[0088] By adopting the technical solution of the embodiment of the present disclosure, multiple clusters can be determined in advance, and the multi-dimensional Gaussian distribution corresponding to the material parameter values of each cluster can be determined. When it is necessary to determine the material parameter values of the target printed circuit board at multiple frequency points, it can be directly determined according to the multiple clusters determined in advance, effectively improving the efficiency and saving time.

[0089] In step S13, according to the multiple clusters and the scattering parameters of the target printed circuit board, the target cluster to which the target printed circuit board belongs is determined from the multiple clusters.

[0090] The smaller the difference between the scattering parameters of the target printed circuit board and the clustering center of the cluster, the more likely the target printed circuit board is to be assigned to that cluster. The difference between the scattering parameters of the target printed circuit board and the clustering center of the cluster can be measured by the distance between the scattering parameters of the target printed circuit board and the clustering center of the cluster.

[0091] Obtain the distances between the clustering centers of the multiple clusters and the scattering parameters of the target printed circuit board, and determine the cluster closest to the scattering parameters of the target printed circuit board as the target cluster to which the target printed circuit board belongs.

[0092] The Euclidean distance between the clustering centers of the multiple clusters and the scattering parameters of the target printed circuit board can be calculated, the cluster closest to the scattering parameters of the target printed circuit board is determined from the multiple clusters, and the cluster with the closest distance is determined as the target cluster to which the target printed circuit board belongs.

[0093] In this way, it can be ensured that the clustering center of the target cluster is the cluster with the smallest difference from the scattering parameters of the target printed circuit board among the multiple clusters. Furthermore, subsequently determining the material parameter values of the target printed circuit board at multiple frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster is relatively accurate.

[0094] In step S14, according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster, the material parameter values of the target printed circuit board at multiple frequency points are determined.

[0095] After determining the target cluster, the material parameter values of the target printed circuit board corresponding to multiple frequency points can be determined according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster. Optionally, the average value of the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster at a certain frequency point can be determined as the material parameter value of the target printed circuit board corresponding to this frequency point.

[0096] Adopting the technical solution of the embodiment of the present disclosure, each cluster is obtained by clustering multiple printed circuit board samples according to their respective scattering parameters. Therefore, the scattering parameters of the multiple printed circuit board samples included in each cluster are similar. When the scattering parameters of the printed circuit boards are similar, the material parameters of the printed circuit boards are also similar; the set of material parameter values corresponding to each cluster is determined based on the Gaussian distribution of the material parameter values of the multiple printed circuit board samples included in this cluster; therefore, the set of material parameter values corresponding to a cluster can accurately reflect the material parameter values of each printed circuit board sample included in this cluster. Furthermore, the material parameter values of the target printed circuit board determined according to the set of material parameter values corresponding to the target cluster to which the target printed circuit board belongs are relatively accurate. Since the set of material parameter values corresponding to the cluster includes the material parameter values corresponding to multiple frequency points, the determined material parameter values of the target printed circuit board are the material parameter values corresponding to multiple frequency points.

[0097] Based on the above technical solution, other dimensions can also be considered, such as the temperature dimension and the humidity dimension. The scattering parameters can be the scattering parameters under multiple dimensions, and the multiple dimensions include but are not limited to: the temperature dimension and the humidity dimension.

[0098] When obtaining the scattering parameters of the target printed circuit board, the scattering parameters of the target printed circuit board can be obtained under different dimension parameters. Different dimension parameters refer to: different temperatures and / or different humidities. For example, different temperatures can be set, and under different temperatures, the scattering parameters of the target printed circuit board under different temperature dimension parameters can be obtained; different humidities can be set, and under different humidities, the scattering parameters of the target printed circuit board under different humidity dimension parameters can be obtained.

[0099] When the scattering parameters of the target printed circuit board are the scattering parameters under multiple dimensions, the scattering parameters of the printed circuit board samples are also the scattering parameters under multiple dimensions. Different dimension parameters are set according to multiple dimensions, and the scattering parameters of multiple printed circuit board samples are obtained under different dimension parameters.

[0100] When the scattering parameters of the printed circuit board samples are the scattering parameters under multiple dimensions, each of the scattering parameters selected as the clustering centers of multiple initial clusters is also the scattering parameters under multiple dimensions.

[0101] Thus, when the scattering parameters of the printed circuit board samples are scattering parameters in multiple dimensions, the cluster centers of the multiple initial clusters are also scattering parameters in multiple dimensions, and the cluster centers of the determined multiple clusters are also scattering parameters in multiple dimensions. Correspondingly, the scattering parameters of the target printed circuit board are scattering parameters in multiple dimensions. Based on the scattering parameters of the target printed circuit board in multiple dimensions and the cluster centers of the multiple clusters, the target cluster to which the target printed circuit board belongs determined from the multiple clusters is also more accurate.

[0102] Based on the above technical solution, the material parameter values of the multiple printed circuit board samples at multiple frequency points can be: the material parameter values corresponding to multiple frequency points of the multiple printed circuit board samples under different dimensional parameters. Different temperatures can be set, and at different temperatures, the material parameter values corresponding to different frequency points of each printed circuit board sample under different temperature dimensional parameters can be obtained; different humidities can be set, and at different humidities, the material parameter values corresponding to different frequency points of each printed circuit board sample under different humidity dimensional parameters can be obtained.

[0103] Thus, the material parameter values of the multiple printed circuit board samples can include the frequency domain dimension, the temperature dimension, and the humidity dimension. Correspondingly, the multi-dimensional Gaussian distribution generated based on the material parameter values of each printed circuit board sample included in each cluster can include the frequency domain dimension, the temperature dimension, and the humidity dimension.

[0104] When determining the material parameter values of the target printed circuit board corresponding to multiple frequency points based on the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster, it can include: determining the material parameter values of the target printed circuit board corresponding to multiple frequency points under different dimensional parameters based on the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster.

[0105] Adopting the technical solution of the embodiments of the present disclosure, the material parameter values of the multiple printed circuit board samples obtained at multiple frequency points are the material parameter values corresponding to multiple frequency points under different dimensional parameters, and the generated multi-dimensional Gaussian distribution also includes multiple dimensions. Furthermore, the determined material parameter values of the target printed circuit board are the material parameter values corresponding to multiple frequency points under different dimensional parameters. Thus, the material parameter values corresponding to the target circuit printed board in different environments can be determined, thereby meeting different engineering and scientific research requirements.

[0106] Figure 2It is a schematic flowchart of a method for determining material parameter values shown in an embodiment of the present disclosure. The method for determining material parameter values can be implemented using an electronic device. The scattering parameters of multiple printed circuit board samples are input into the electronic device, and the electronic device performs clustering analysis on the scattering parameters of the multiple printed circuit board samples to obtain multiple clusters. The material parameter values of each cluster correspond to a multi-dimensional Gaussian distribution. The scattering parameters of the target printed circuit board are input into the electronic device, and the electronic device determines the target cluster to which the target printed circuit board belongs according to the scattering parameters of the target printed circuit board, and thus determines the material parameter values of the target printed circuit board according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster. Among them, the clustering analysis can adopt the K-means clustering algorithm.

[0107] The electronic device can be a computer device, a mobile phone, a tablet computer, etc. Figure 3 It is a schematic diagram of the composition of a computer device in an embodiment of the present disclosure. The computer system can include a memory, a processor, and an out-of-band controller. The processor can process the scattering parameters of the input printed circuit board samples, the scattering parameters of the target printed circuit board, and the material parameter values of the printed circuit board samples. The memory can be used to store the scattering parameters and material parameter values of each printed circuit board sample.

[0108] By performing clustering algorithm analysis on the material parameter values through the scattering parameters, the material parameter values of the printed circuit board can be characterized by multi-frequency point scattering parameters. In this way, when performing K-means clustering algorithm analysis on the target printed circuit board, through the comparison of the wide frequency band composed of multi-frequency points, the overall fitting accuracy of the material parameter values is improved, avoiding the inaccurate problems caused by the establishment of the simulation scale model and manual fitting. At the same time, it can solve the problems such as poor simulation accuracy caused by using the material parameter values at a certain specific frequency provided by the manufacturer for signal integrity simulation of different rate interfaces.

[0109] Adopting the technical solution of the embodiment of the present disclosure can break the limitation of relying on the material parameter values at a single frequency point for signal integrity simulation, improve the accuracy of signal integrity simulation evaluation, solve the problem of low accuracy of the material parameters of the existing printed circuit board caused by inaccurate models and manual fitting, and improve the subsequent test and verification efficiency of the printed circuit board. The technical solution of the embodiment of the present disclosure can be extended to the applicable scenarios of extracting other parameters of the printed circuit board. For example, the technical solution of the embodiment of the present disclosure is used for the extraction of related parameters such as copper foil roughness and the extraction of time domain parameters in signal integrity related tests. When extracting the copper foil roughness, the scattering parameters can be replaced with the parameters related to the copper foil roughness, and the material parameter values of the printed circuit board samples can be replaced with the copper foil roughness, and other steps are modified accordingly.

[0110] It should be noted that, for method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present disclosure are not limited by the described action sequences, because according to the embodiments of the present disclosure, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential for the embodiments of the present disclosure.

[0111] Figure 4 is a block diagram of a device for determining a material parameter value shown in an embodiment of the present disclosure. Referring to Figure 4 this, the device includes a parameter acquisition module, a cluster acquisition module, a target determination module, and a parameter value determination module, where:

[0112] The parameter acquisition module is configured to acquire the scattering parameters of the target printed circuit board, and the scattering parameters include insertion loss and return loss;

[0113] The cluster acquisition module is configured to acquire a plurality of clusters, and the plurality of clusters are obtained by clustering the plurality of printed circuit board samples according to their respective scattering parameters. The material parameter value of each cluster corresponds to a multi-dimensional Gaussian distribution, and the dimensions of the multi-dimensional Gaussian distribution include a frequency domain dimension;

[0114] The target determination module is configured to determine the target cluster to which the target printed circuit board belongs from the plurality of clusters according to the plurality of clusters and the scattering parameters of the target printed circuit board;

[0115] The parameter value determination module is configured to determine the material parameter values of the target printed circuit board at a plurality of frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster.

[0116] Optionally, the plurality of clusters and the multi-dimensional Gaussian distribution corresponding to the material parameter value of each cluster are determined according to the following steps:

[0117] Acquire the scattering parameters of the plurality of printed circuit board samples respectively;

[0118] Select a plurality of scattering parameters as the clustering centers of a plurality of initial clusters;

[0119] According to the scattering parameters of the plurality of printed circuit board samples respectively and the clustering centers of the plurality of initial clusters, cluster the plurality of printed circuit board samples into the plurality of initial clusters in sequence, and when the printed circuit board samples included in each initial cluster change, iterate the clustering centers of the initial clusters;

[0120] Repeat the above steps until the termination condition is met to obtain the multiple clusters;

[0121] Obtain the material parameter values of each of the multiple printed circuit board samples at the multiple frequency points;

[0122] Determine the multi-dimensional Gaussian distribution corresponding to the material parameter values of each cluster according to the material parameter values of each of the printed circuit board samples included in each cluster at the multiple frequency points.

[0123] Optionally, the dimensions of the multi-dimensional Gaussian distribution include, but are not limited to: the temperature dimension and the humidity dimension;

[0124] The material parameter values of each of the multiple printed circuit board samples at the multiple frequency points include: the material parameter values corresponding to the multiple frequency points of each of the multiple printed circuit board samples under different dimensional parameters;

[0125] The determining of the material parameter values of the target printed circuit board corresponding to the multiple frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster includes:

[0126] Determine the material parameter values corresponding to the multiple frequency points of the target printed circuit board under the different dimensional parameters according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster.

[0127] Optionally, the scattering parameters include scattering parameters in multiple dimensions, and the multiple dimensions include, but are not limited to: the temperature dimension and the humidity dimension;

[0128] The obtaining of the scattering parameters of each of the multiple printed circuit board samples includes:

[0129] Set different dimensional parameters according to the multiple dimensions;

[0130] Obtain the scattering parameters of the multiple printed circuit board samples under the different dimensional parameters;

[0131] The selection of multiple scattering parameters as the clustering centers of multiple initial clusters includes:

[0132] Select multiple parameter parameters under the different dimensional parameters as the clustering centers of the multiple initial clusters.

[0133] Optionally, the parameter acquisition module includes:

[0134] A setting unit configured to set the different dimensional parameters according to the multiple dimensions;

[0135] An acquisition unit configured to acquire the scattering parameters of the target printed circuit board under the different dimensional parameters.

[0136] Optionally, the termination condition is any of the following:

[0137] None or the minimum number of the printed circuit board samples are reassigned to different initial clusters;

[0138] None or the minimum number of the cluster centers of the initial clusters change again;

[0139] The sum of squared errors between the scattering parameters of the printed circuit board samples and the cluster centers of the initial clusters is locally minimum.

[0140] Optionally, the target determination module includes:

[0141] A distance acquisition unit configured to acquire the distances between the cluster centers of the respective clusters and the scattering parameters of the target printed circuit board;

[0142] A target determination unit configured to determine the cluster closest to the scattering parameters of the target printed circuit board as the target cluster to which the target printed circuit board belongs.

[0143] Optionally, the material parameter values include: a dielectric constant value of the board and a dielectric loss factor.

[0144] It should be noted that the device embodiments are similar to the method embodiments, so the description is relatively simple. For related parts, please refer to the method embodiments.

[0145] The embodiments of the present disclosure also provide an electronic device. Refer to Figure 5 , Figure 5 is a schematic diagram of an electronic device shown in the embodiments of the present disclosure. As Figure 4 shown, the electronic device 100 includes: a memory 110 and a processor 120. The memory 110 is communicatively connected to the processor 120 through a bus. A computer program is stored in the memory 110, and the computer program can run on the processor 120, thereby implementing the steps in the method for determining the material parameter values disclosed in the embodiments of the present disclosure.

[0146] The embodiments of the present disclosure also provide a non-volatile readable storage medium. When the instructions in the non-volatile readable storage medium are executed by the processor of the electronic device, the electronic device can execute the steps in the method for determining the material parameter values disclosed in the embodiments of the present disclosure.

[0147] Each embodiment in this specification is described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other.

[0148] Those skilled in the art should understand that the embodiments of the present disclosure can be provided as methods, apparatuses, or computer program products. Therefore, the embodiments of the present disclosure can take the form of all-hardware embodiments, all-software embodiments, or embodiments combining software and hardware aspects. Moreover, the embodiments of the present disclosure can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0149] The embodiments of the present disclosure are described with reference to the flowcharts and / or block diagrams of methods, apparatuses, electronic devices, and computer program products according to the embodiments of the present disclosure. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing terminal devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing terminal devices generate a device for implementing the functions specified in Figure 1 one or more of the processes Figure 1 or blocks.

[0150] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device that implements the functions specified in Figure 1 one or more of the processes Figure 1 or blocks.

[0151] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, such that a series of operation steps are executed on the computer or other programmable terminal device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable terminal device provide steps for implementing the functions specified in Figure 1 one or more of the processes Figure 1 or blocks.

[0152] Although some embodiments of the present disclosure have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed as including the preferred embodiments and all changes and modifications falling within the scope of the embodiments of the present disclosure.

[0153] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent in such process, method, article or terminal device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or terminal device comprising said element.

[0154] The above has introduced in detail a method, apparatus, electronic device and storage medium for determining a material parameter value provided by the present disclosure. Specific examples are used in this text to elaborate on the principle and implementation manner of the present disclosure. The description of the above embodiments is only used to help understand the method and its core idea of the present disclosure; at the same time, for those of ordinary skill in the art, according to the idea of the present disclosure, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation on the present disclosure.

Claims

1. A method for determining a material parameter value, characterized in that Including: Obtaining the scattering parameters of a target printed circuit board, where the scattering parameters include insertion loss and return loss; Obtaining a plurality of clusters, which are obtained by clustering a plurality of printed circuit board samples according to their respective scattering parameters, and the material parameter values of each cluster correspond to a multi-dimensional Gaussian distribution, and the dimensions of the multi-dimensional Gaussian distribution include at least one of a frequency domain dimension, a temperature dimension, and a humidity dimension; Determining the target cluster to which the target printed circuit board belongs from the plurality of clusters according to the plurality of clusters and the scattering parameters of the target printed circuit board; Determining the material parameter values of the target printed circuit board corresponding to a plurality of frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster; The plurality of clusters and the multi-dimensional Gaussian distribution corresponding to the material parameter values of each cluster are determined according to the following steps: Obtaining the scattering parameters of the plurality of printed circuit board samples respectively; Selecting a plurality of scattering parameters as the clustering centers of a plurality of initial clusters; According to the scattering parameters of the plurality of printed circuit board samples respectively and the clustering centers of the plurality of initial clusters, clustering the plurality of printed circuit board samples into the plurality of initial clusters in sequence, and iterating the clustering centers of the initial clusters when the printed circuit board samples included in each initial cluster change; Repeating the above steps until a termination condition is satisfied to obtain the plurality of clusters; Obtaining the material parameter values of the plurality of printed circuit board samples respectively at a plurality of frequency points under different dimensional parameters; Determining the multi-dimensional Gaussian distribution corresponding to the material parameter values of each cluster according to the material parameter values of each printed circuit board sample included in each cluster at a plurality of frequency points under different dimensional parameters.

2. The method according to claim 1, wherein The dimensions of the multi-dimensional Gaussian distribution include but are not limited to: the temperature dimension and the humidity dimension; The material parameter values of the plurality of printed circuit board samples respectively at the plurality of frequency points include: the material parameter values of the plurality of printed circuit board samples respectively corresponding to the plurality of frequency points under different dimensional parameters; The determining the material parameter values of the target printed circuit board corresponding to a plurality of frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster includes: Determining the material parameter values of the target printed circuit board corresponding to the plurality of frequency points under the different dimensional parameters according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster.

3. The method according to claim 1, characterized in that, The scattering parameters include scattering parameters in a plurality of dimensions, and the plurality of dimensions include but are not limited to: the temperature dimension and the humidity dimension; The obtaining the scattering parameters of the plurality of printed circuit board samples respectively includes: Setting different dimensional parameters according to the plurality of dimensions; Obtaining the scattering parameters of the plurality of printed circuit board samples under the different dimensional parameters; The selecting a plurality of scattering parameters as the clustering centers of a plurality of initial clusters includes: Selecting a plurality of parameters under the different dimensional parameters as the clustering centers of the plurality of initial clusters.

4. The method according to claim 3, wherein The obtaining the scattering parameters of the target printed circuit board includes: Set the different dimensional parameters according to the multiple dimensions; Obtain the scattering parameters of the target printed circuit board under the different dimensional parameters.

5. The method according to claim 1, wherein The termination condition is any one of the following: None or the minimum number of the printed circuit board samples are reassigned to different initial clusters; The cluster centers of none or the minimum number of the initial clusters change any more; The sum of squared errors between the scattering parameters of the printed circuit board samples and the cluster centers of the initial clusters is locally minimum.

6. The method according to any one of claims 1-5, characterized in that, The determining the target cluster to which the target printed circuit board belongs from the multiple clusters according to the multiple clusters and the scattering parameters of the target printed circuit board includes: Obtain the distances between the cluster centers of the multiple clusters respectively and the scattering parameters of the target printed circuit board; Determine the cluster with the closest distance to the scattering parameters of the target printed circuit board as the target cluster to which the target printed circuit board belongs.

7. The method according to any one of claims 1-5, characterized in that, The material parameter values include: the dielectric constant value of the board and the dielectric loss factor.

8. An apparatus for determining a material parameter value, characterized in that, Comprising: A parameter acquisition module configured to acquire the scattering parameters of a target printed circuit board, where the scattering parameters include insertion loss and return loss; A cluster acquisition module configured to acquire multiple clusters, where the multiple clusters are obtained by clustering the multiple printed circuit board samples according to the scattering parameters of the multiple printed circuit board samples respectively, and the material parameter value of each cluster corresponds to a multi-dimensional Gaussian distribution, and the dimensions of the multi-dimensional Gaussian distribution include at least one of a frequency domain dimension, a temperature dimension, and a humidity dimension; A target determination module configured to determine the target cluster to which the target printed circuit board belongs from the multiple clusters according to the multiple clusters and the scattering parameters of the target printed circuit board; A parameter value determination module configured to determine the material parameter values of the target printed circuit board at multiple frequency points according to the multi-dimensional Gaussian distribution corresponding to the material parameter values of the target cluster; The multiple clusters and the multi-dimensional Gaussian distribution corresponding to the material parameter value of each cluster are determined according to the following steps: Obtain the scattering parameters of the multiple printed circuit board samples respectively; Select multiple scattering parameters as the cluster centers of multiple initial clusters; According to the scattering parameters of the multiple printed circuit board samples respectively and the cluster centers of the multiple initial clusters, cluster the multiple printed circuit board samples into the multiple initial clusters in sequence, and iterate the cluster centers of the initial clusters when the printed circuit board samples included in each initial cluster change; Repeat the above steps until the termination condition is met to obtain the multiple clusters; Obtain the material parameter values of the multiple printed circuit board samples respectively at multiple frequency points under different dimensional parameters; Determine the multi-dimensional Gaussian distribution corresponding to the material parameter value of each cluster according to the material parameter values of each printed circuit board sample included in each cluster at multiple frequency points under different dimensional parameters.

9. An electronic device, characterized in that, Comprising: A processor; A memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method for determining the material parameter value according to any one of claims 1 to 7.

10. A non-volatile readable storage medium, when the instructions in the non-volatile readable storage medium are executed by a processor of an electronic device, enabling the electronic device to execute the method for determining the material parameter value according to any one of claims 1 to 7.

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