Near-field scanning method, device, computer equipment, storage medium and program product

Abstract

This application relates to a near-field scanning method, apparatus, computer device, storage medium, and program product. For each grid point to be divided in a two-dimensional uniform network of an electronic device under test (EDT), the offset between the grid point to be divided and a preset starting grid point of the two-dimensional uniform network is determined. Based on a preset exponential function, a first exponential function value is determined, with each parameter within a parameter range corresponding to a target threshold as the exponent. A first ratio between the offset and each first exponential function value is determined, and the parameter corresponding to the largest integer first ratio is determined as the target parameter. The grid points to be divided are then divided into a set according to the target parameter and the target threshold. Based on the set obtained after dividing each grid point, a near-field scan of the EDT is performed. The embodiments of this application employ an equivalence class partitioning method to divide the grid points, allowing multiple grid points to be divided to be processed in parallel, thus improving the efficiency of grid point partitioning.

Description

Technical Field

[0001] This application relates to the field of electronic equipment technology, and in particular to a near-field scanning method, apparatus, computer equipment, storage medium, and program product. Background Technology

[0002] Near-Field Scanning (NFS) is a high-precision, high-resolution spatial physical field distribution detection technique. It constructs a two-dimensional uniform network over the test area of ​​an electronic device under test (EDT), divides the network into grid points, and scans the test area using the resulting set of grid points to obtain an evaluation value for the reliability and performance of the electronic device. For example, NFS can be used to divide the test area of ​​an electronic device, scan the electromagnetic field of the test area using the resulting set of grid points to obtain electromagnetic compatibility (EMC) data, and then evaluate the reliability and performance of the electronic device based on the EMC data.

[0003] However, traditional near-field scanning techniques use a recursive method to divide the grid points in a two-dimensional uniform network, which results in a long near-field scanning time. Summary of the Invention

[0004] Therefore, it is necessary to provide a near-field scanning method, apparatus, computer equipment, storage medium, and program product that can reduce detection time in response to the above-mentioned technical problems.

[0005] In a first aspect, this application provides a near-field scanning method, including:

[0006] For each grid point to be divided in the two-dimensional uniform network of the electronic device under test, determine the offset between the grid point to be divided and the preset starting grid point of the two-dimensional uniform network;

[0007] Based on a preset exponential function, a first exponential function value is determined with each parameter in the parameter interval corresponding to the target threshold as the exponent; the target threshold is determined according to the preset parameter values ​​and the preset exponential function.

[0008] Determine the first ratio between the offset and each of the first exponential function values, and determine the parameter corresponding to the largest first ratio among the integer first ratios as the target parameter;

[0009] The grid points to be divided are divided into a set according to the target parameters and the target threshold. Based on the set obtained after dividing each of the grid points to be divided, the electronic device under test is scanned in the near field.

[0010] In one embodiment, the step of dividing the grid points to be divided into a set according to the target parameters and the target threshold includes:

[0011] When the target parameter is equal to the target threshold, the grid points to be divided are assigned to the initial set corresponding to the preset parameter value;

[0012] If the target parameter is less than the target threshold, a set identifier is determined based on the target parameter and the offset, and the grid points to be divided are assigned to the set corresponding to the set identifier.

[0013] In one embodiment, the offset includes a first offset of the grid point to be divided in a first direction and a second offset of the grid point to be divided in a second direction; determining the set identifier based on the target parameter and the offset includes:

[0014] Based on the preset exponential function, determine the value of the second exponential function with the target parameter as the exponent;

[0015] Determine a second ratio between the first offset and the value of the second exponential function, and determine a third ratio between the second offset and the value of the second exponential function;

[0016] Determine the first product result of the second ratio and the third ratio, and determine the set identifier based on the first product result.

[0017] In one embodiment, determining the set identifier based on the first product result includes:

[0018] Determine a first difference between the target threshold and the target parameter, and determine a second product result between the first difference and a first preset constant value;

[0019] If the first product result is odd, the second difference between the second product result and the second preset constant value is determined as the set identifier.

[0020] In one embodiment, the method further includes:

[0021] If the first product result is even, the second product result is determined to be the set identifier.

[0022] In one embodiment, each parameter in the parameter range is an integer value within a range greater than or equal to 0 and less than or equal to the target threshold.

[0023] Secondly, this application also provides a near-field scanning device, comprising:

[0024] The first determining module is used to determine the offset between each grid point to be divided and the preset starting grid point of the two-dimensional uniform network for each grid point to be divided in the two-dimensional uniform network of the electronic device under test.

[0025] The second determining module is used to determine, based on a preset exponential function, the value of a first exponential function with each parameter in the parameter interval corresponding to the target threshold as the exponent; the target threshold is determined according to the preset parameter values ​​and the preset exponential function.

[0026] The third determining module is used to determine the first ratio of the offset to each of the first exponential function values, and to determine the parameter corresponding to the largest first ratio among the integer first ratios as the target parameter;

[0027] The scanning module is used to divide the grid points to be divided into a set according to the target parameters and the target threshold, and to perform near-field scanning on the electronic device under test according to the set obtained after dividing each of the grid points to be divided.

[0028] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method steps provided in the first aspect.

[0029] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method steps provided in the first aspect.

[0030] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method steps provided in the first aspect.

[0031] The aforementioned near-field scanning method, apparatus, computer equipment, storage medium, and program product, for each grid point to be divided in a two-dimensional uniform network of an electronic device under test, determine the offset between the grid point to be divided and a preset starting grid point of the two-dimensional uniform network. Based on a preset exponential function, determine the value of a first exponential function with each parameter within the parameter interval corresponding to a target threshold as the exponent. Determine a first ratio between the offset and each first exponential function value, and determine the parameter corresponding to the largest of the integer first ratios as the target parameter. Divide the grid points to be divided into a set according to the target parameter and the target threshold. Perform near-field scanning on the electronic device under test based on the set obtained after dividing each grid point. The target threshold is determined according to the preset parameter value and the preset exponential function. In the embodiments of this application, an equivalence class partitioning method is used to divide the grid points to be divided in the two-dimensional uniform network of the scanning plane of the electronic device under test. Multiple grid points to be divided can be processed in parallel, improving the efficiency of grid point division. Moreover, for each grid point to be divided, the target parameters are calculated based on the offset between the grid point to be divided and the starting grid point. The grid points to be divided are then assigned to the set according to the target parameters and the target threshold. The selection of the starting grid point does not affect the calculation of the target parameters. Thus, the complete division of the plane to be scanned is independent of the starting grid point. That is, no matter which starting grid point is selected, the complete division of the plane to be scanned can be achieved. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a diagram illustrating the application environment of a near-field scanning method in one embodiment;

[0034] Figure 2 This is a flowchart illustrating a near-field scanning method in one embodiment;

[0035] Figure 3 This is a flowchart illustrating a method for determining a set identifier in one embodiment;

[0036] Figure 4 This is a first schematic diagram of the set obtained after partitioning in one embodiment;

[0037] Figure 5 This is a second schematic diagram of the set obtained after partitioning in one embodiment;

[0038] Figure 6This is a third schematic diagram of the set obtained after partitioning in one embodiment;

[0039] Figure 7 This is a fourth schematic diagram of the set obtained after partitioning in one embodiment;

[0040] Figure 8 This is a first schematic diagram of performance test results in one embodiment;

[0041] Figure 9 This is a second schematic diagram of performance test results in one embodiment;

[0042] Figure 10 This is a third schematic diagram illustrating the performance test results in one embodiment;

[0043] Figure 11 This is a fourth schematic diagram showing the performance test results in one embodiment;

[0044] Figure 12 This is a structural block diagram of a near-field scanning device in one embodiment;

[0045] Figure 13 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0047] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0048] To improve near-field scanning speed, one approach is to increase the sampling rate of the test equipment and the movement speed of the mobile platform. However, for the area to be scanned of the electronic device under test, it is still necessary to scan all test points in the area to be scanned. Improving the hardware does not significantly accelerate the test speed and also increases the cost of the test hardware.

[0049] Current near-field scanning algorithms preprocess the scanned area of ​​the electronic device under test using a recursive method. The recursive method gradually reduces the step size and performs multiple rounds of division. The disadvantage of this method is that it is necessary to select an appropriate grid point as the starting point in order to completely divide the entire scanned plane. Furthermore, the recursive method can lead to a large time consumption when the scanned plane is large or the division is very fine.

[0050] The near-field scanning method provided in this application embodiment can be applied to, for example... Figure 1 The application environment shown includes a near-field scanning system, which comprises a computer device 11, a spectrum analyzer 12, a displacement system 13, and an electronic device under test (DUT) 14. During near-field scanning, the computer device 11 performs two-dimensional discretization mesh processing on the scanned plane (near-field scanning plane) of the DUT 14 to obtain a two-dimensional uniform network. The size of the two-dimensional uniform network is H×W, and the offset of two grid points in the x-direction is... The offset in the y direction is The idea of ​​equivalent classification is used to process each grid point in the pre-divided two-dimensional uniform network and assign them to different sets. Based on the sets obtained after dividing each grid point, near-field scanning of the electronic device 14 under test is performed using computer equipment 11, spectrum analyzer 12, and displacement system 13.

[0051] In one exemplary embodiment, such as Figure 2 As shown, a near-field scanning method is provided, which is applied to... Figure 1 Taking computer device 11 as an example, the explanation includes the following steps S201 to S204. Wherein:

[0052] S201, for each grid point to be divided in the two-dimensional uniform network of the electronic device under test, determine the offset between the grid point to be divided and the preset starting grid point of the two-dimensional uniform network.

[0053] In this embodiment of the application, the scanning plane of the electronic device under test is discretized to obtain a two-dimensional uniform network. The two-dimensional uniform network is... , where X num Let X be the total number of grid points in the X direction of the two-dimensional uniform network, and Y be the total number of grid points in the X direction. num This represents the total number of grid points in the Y direction of the two-dimensional uniform network. For each grid point to be divided in the two-dimensional uniform network... The points to be divided into grids and the preset starting grid points of the two-dimensional uniform network. The offset between can be .

[0054] S202, Based on the preset exponential function, determine the value of the first exponential function with each parameter in the parameter interval corresponding to the target threshold as the exponent; the target threshold is determined according to the preset parameter values ​​and the preset exponential function.

[0055] In this embodiment, the preset parameter value is the shortest distance between two grid points in a pre-set initial set, and the range of the preset parameter value S0 is: The preset exponential function is a base-2 exponential function. If the preset parameter value is 2, the target threshold is 1; if the preset parameter value is 4, the target threshold is 2; if the preset parameter value is 8, the target threshold is 3.

[0056] In this context, each parameter within the parameter interval is an integer value within a range greater than or equal to 0 and less than or equal to the target threshold. For example, if the target threshold is 2, the parameter interval is greater than or equal to 0 and less than or equal to 2, with each parameter being 0, 1, and 2; if the target threshold is 4, the parameter interval is greater than or equal to 0 and less than or equal to 4, with each parameter being 0, 1, 2, 3, and 4.

[0057] Based on a preset exponential function, the values ​​of the first exponential function are determined, with each parameter within the parameter range corresponding to the target threshold as the exponent. For example, if the preset exponential function is a base-2 exponential function and the parameters are 0, 1, and 2, the values ​​of the first exponential function corresponding to the exponents of 0, 1, and 2 are determined respectively.

[0058] S203, determine the first ratio of the offset to each first exponential function value, and determine the parameter corresponding to the largest first ratio among the integer first ratios as the target parameter.

[0059] In this embodiment, the offset includes a first offset in the X direction and a second offset in the Y direction. For each first exponential function value, a first ratio between the first offset and the first exponential function value, and a function value between the second offset and the first exponent are determined. The largest first ratio is determined from the integer first ratios, and the parameter corresponding to the largest first ratio is used as the target parameter. For example, if the parameters are 0, 1, and 2, the corresponding first exponential function values ​​2 are determined for exponents of 0, 1, and 2, respectively. 0 2 1 2 2 If the first offset is 2 and the second offset is 1, then the first ratio includes 2 and 1 when the parameter is 0, 1 and 0.5 when the parameter is 1, and 0.5 and 0.25 when the parameter is 2. Then, the parameter corresponding to the largest first ratio among 2, 1 and 1 is selected as the target parameter, that is, the target parameter is 0.

[0060] The above steps S202 and S203 yield the target parameter t. i The steps can be represented by the following formula:

[0061] ;

[0062] S204. Divide the to-be-partitioned grid points into sets according to the target parameters and target thresholds, and perform near-field scanning on the electronic device to be measured according to the sets obtained after partitioning each to-be-partitioned grid point.

[0063] For the to-be-partitioned grid points P1 and P2, the target parameter t1 corresponding to the to-be-partitioned grid point P1 and the target parameter t2 corresponding to the to-be-partitioned grid point P2 can be obtained according to the above formula. Define the binary relationship of the to-be-partitioned grid points P1 and P2 as follows (if and only if they satisfy one of the following conditions):

[0064] (1) t1 = t2 = k; (2) t1 = t2 < k, and a1b1 and a2b2 have the same parity. Where, a1 is the second ratio corresponding to the to-be-partitioned grid point P1, b1 is the third ratio corresponding to the to-be-partitioned grid point P1, a2 is the second ratio corresponding to the to-be-partitioned grid point P2, and b2 is the third ratio corresponding to the to-be-partitioned grid point P2. The second ratio and the third ratio are determined based on the offset, the target parameter, and the preset exponential function. Specifically, based on the preset exponential function, determine the value of the second exponential function with the target parameter as the exponent, take the ratio of the first offset in the X direction to the value of the second exponential function as the second ratio, and take the ratio of the second offset in the Y direction to the value of the second exponential function as the third ratio.

[0065] The relative coordinates of any to-be-partitioned grid point are , and according to the above method, the target parameter, the second ratio, and the third ratio are determined. When the to-be-partitioned grid point is compared with itself, it is inevitable that the target parameter of the to-be-partitioned grid point is equal to its own target parameter, and the same is true for the second ratio and the third ratio. Then it can be known that the to-be-partitioned grid point is equivalent to itself, that is, the binary relationship satisfies reflexivity.

[0066] For any two to-be-partitioned grid points, calculate the target parameters, the second ratio, and the third ratio corresponding to the two to-be-partitioned grid points according to the above formula. If the target parameters corresponding to the two to-be-partitioned grid points are equal, and the second ratio and the third ratio are also equal, or the parities of the second ratio and the third ratio of the two to-be-partitioned grid points are the same, because the equal sign naturally satisfies symmetry and transitivity, and the parity of integers also naturally satisfies symmetry and transitivity, it can be proved that the binary relationship satisfies symmetry and transitivity.

[0067] If a binary relation satisfies reflexivity, symmetry, and transitivity, it can be proven that the binary relation is an equivalence relation. According to relevant literature, an equivalence relation can achieve a complete partition of points within a set. Furthermore, for any given point, the partitioning is calculated based on an offset. Due to the arbitrariness of the starting point, the complete partitioning of the plane to be scanned is independent of the starting point; that is, regardless of the chosen starting point, a complete partitioning of the plane to be scanned can be achieved.

[0068] In this embodiment, when the target parameter equals the target threshold, the grid points to be divided are assigned to the initial set corresponding to the preset parameter value. When the target parameter is less than the target threshold, a set identifier is determined based on the target parameter and the offset, and the grid points to be divided are assigned to the set corresponding to the set identifier. The number of sets is determined based on the target threshold, i.e., the number of sets is M = 2k + 1. Therefore, when the target parameter is less than the target threshold, M-1 sets will be obtained.

[0069] In one possible implementation, the ratio of the target parameter to the target threshold can also be obtained. If the ratio is 1, the grid points to be divided are assigned to the initial set corresponding to the preset parameter value. If the ratio is less than 1, the set identifier is determined according to the target parameter and the offset, and the grid points to be divided are assigned to the set corresponding to the set identifier.

[0070] Furthermore, for each set of grid points, only all grid points of the initial set (the set corresponding to t=k) are scanned to quickly locate hotspots; based on the consistency of equivalence class characteristics, after scanning a small number of points of a certain set, the field distribution of similar sets can be inferred without scanning all points of the same type, thereby further reducing the time of near-field scanning.

[0071] In the aforementioned near-field scanning method, for each grid point to be divided in the two-dimensional uniform network of the electronic device under test (DUT), the offset between the grid point to be divided and the preset starting grid point of the two-dimensional uniform network is determined. Based on a preset exponential function, a first exponential function value is determined with each parameter in the parameter interval corresponding to the target threshold as the exponent. A first ratio between the offset and each first exponential function value is determined, and the parameter corresponding to the largest first ratio among the integers is determined as the target parameter. The grid points to be divided are divided into a set according to the target parameter and the target threshold. Based on the set obtained after dividing each grid point, a near-field scan of the DUT is performed. The target threshold is determined according to the preset parameter value and the preset exponential function. In this embodiment, the equivalence class partitioning method is used to divide the grid points to be divided in the two-dimensional uniform network of the scan plane of the DUT. Multiple grid points to be divided can be processed in parallel, improving the efficiency of grid point partitioning. Moreover, for each grid point to be divided, the target parameters are calculated based on the offset between the grid point to be divided and the starting grid point. The grid points to be divided are then assigned to the set according to the target parameters and the target threshold. The selection of the starting grid point does not affect the calculation of the target parameters. Thus, the complete division of the plane to be scanned is independent of the starting grid point. That is, no matter which starting grid point is selected, the complete division of the plane to be scanned can be achieved.

[0072] In an exemplary embodiment, the grid points to be divided are assigned to a set based on target parameters and a target threshold, including the following two cases:

[0073] The first case: When the target parameter is equal to the target threshold, the grid points to be divided are assigned to the initial set corresponding to the preset parameter values.

[0074] In the embodiments of this application, for example, when the target threshold k=2 and the target parameter is also 2, it is proven that the distance between the grid point to be divided and one of the grid points is equal to the preset parameter value, and the grid point to be divided is directly divided into the initial set corresponding to the preset parameter value.

[0075] The second scenario: When the target parameter is less than the target threshold, the set identifier is determined based on the target parameter and the offset, and the grid points to be divided are assigned to the set corresponding to the set identifier.

[0076] In this embodiment, a second exponential function value with the target parameter as the exponent can be determined based on a preset exponential function. A second ratio between the first offset and the second exponential function value is also determined, as well as a third ratio between the second offset and the second exponential function value. A first product of the second and third ratios is determined, and a set identifier is determined based on this first product. The grid points to be divided are then assigned to the set corresponding to the set identifier.

[0077] In one possible implementation, the parity of the second and third ratios can be directly obtained, the set identifier can be determined based on the parity, and the grid points to be divided can be assigned to the set corresponding to the set identifier.

[0078] In another possible implementation, the quotient of the second ratio and the third ratio can be determined, and the set identifier can be determined based on the quotient result. The grid points to be divided can then be assigned to the set corresponding to the set identifier.

[0079] In this embodiment, when the target parameter equals the target threshold, the grid points to be divided are assigned to the initial set corresponding to the preset parameter value. When the target parameter is less than the target threshold, a set identifier is determined based on the target parameter and the offset, and the grid points to be divided are assigned to the set corresponding to the set identifier. This embodiment divides the grid points based on the two different cases in the above equivalence relation, thus improving the accuracy of grid point division.

[0080] Figure 3 This is a flowchart illustrating a method for determining a set identifier in one embodiment, such as... Figure 3 As shown, this application embodiment relates to a possible implementation of how to determine a set identifier based on target parameters and offsets, including the following steps:

[0081] S301, based on a preset exponential function, determine the value of a second exponential function with the target parameter as the exponent.

[0082] S302, determine a second ratio of the first offset to the second exponential function value, and determine a third ratio of the second offset to the second exponential function value.

[0083] In the embodiments of this application, according to Determine the second ratio 'a' between the first offset and the value of the second exponential function. i ,according to Determine the third ratio.

[0084] S303, determine the first product result of the second ratio and the third ratio, and determine the set identifier based on the first product result.

[0085] Specifically, determining the set identifier based on the first product result includes: determining a first difference between the target threshold and the target parameter, and determining a second product result between the first difference and a first preset constant value; if the first product result is odd, determining the second difference between the second product result and the second preset constant value as the set identifier; if the first product result is even, determining the second product result as the set identifier.

[0086] In this embodiment of the application, if the first product of the second ratio and the third ratio is an odd number, the set identifier is 2(kt).i -1; if the result of the first product is even, the set identifier is 2(kt) i For example, if the target threshold k is 3, the target parameter t corresponding to the grid points to be divided... i The value is 2. If the result of the first product is odd, the set identifier is 1; if the result of the first product is even, the set identifier is 2.

[0087] Similarly, if the quotient of the second and third ratios is odd, then the set identifier is 2(kt). i -1; if the quotient is even, the set identifier is 2(kt) i ).

[0088] In this embodiment of the application, based on a preset exponential function, a second exponential function value with the target parameter as the exponent is determined, a second ratio of the first offset to the second exponential function value is determined, and a third ratio of the second offset to the second exponential function value is determined, a first product result of the second ratio and the third ratio is determined, and a set identifier is determined based on the first product result.

[0089] In this embodiment, based on a preset exponential function, a second exponential function value with the target parameter as the exponent is determined, a second ratio between the first offset and the second exponential function value is determined, and a third ratio between the second offset and the second exponential function value is determined. A first product result of the second ratio and the third ratio is determined, and a set identifier is determined based on the first product result, thereby improving the efficiency of set identifier determination.

[0090] In one exemplary embodiment, such as Figure 4 As shown - Figure 7 As shown, Figure 4 This is a first schematic diagram of the set obtained after partitioning in one embodiment. Specifically, the starting grid point S is (0, 0), the preset parameter value is 2, and the total number of grid points to be partitioned in the X direction of the two-dimensional uniform network is 4, and the total number of grid points to be partitioned in the Y direction is also 4. According to Figure 4 It can be seen that the grid points in the two-dimensional uniform network are divided into three different sets: set 1, set 2, and set 0, which includes the starting grid point S. Figure 5 This is a second schematic diagram of the set obtained after partitioning in one embodiment. Specifically, the starting grid point is (2, 1), the preset parameter value is 2, and the total number of grid points to be partitioned in the X direction of the two-dimensional uniform network is 4, and the total number of grid points to be partitioned in the Y direction is also 4. According to Figure 5 It can be seen that the grid points in the two-dimensional uniform network are divided into three different sets. Figure 6This is a third schematic diagram of the set obtained after partitioning in one embodiment. Specifically, the starting grid point is (0, 0), the preset parameter value is 4, and the total number of grid points to be partitioned in the X direction of the two-dimensional uniform network is 4, and the total number of grid points to be partitioned in the Y direction is also 4. According to Figure 6 It can be seen that the grid points in the two-dimensional uniform network are divided into 5 different sets. Figure 7 This is a fourth schematic diagram of the set obtained after partitioning in one embodiment. Specifically, the starting grid point is (2, 3), the preset parameter value is 4, and the total number of grid points to be partitioned in the X direction of the two-dimensional uniform network is 4, and the total number of grid points to be partitioned in the Y direction is also 4. According to Figure 7 It can be seen that the grid points in the two-dimensional uniform network are divided into 5 different sets.

[0091] As can be seen from the above, different starting grid points and preset parameter values ​​can all achieve complete partitioning of the plane to be scanned, thus verifying the effectiveness of the algorithm proposed in this application. The performance tests of the algorithm are shown in Table 1 below. Figures 8-11 As shown.

[0092] Table 1

[0093]

[0094] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0095] Based on the same inventive concept, this application also provides a near-field scanning device for implementing the near-field scanning method described above. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more near-field scanning device embodiments provided below can be found in the limitations of the near-field scanning method described above, and will not be repeated here.

[0096] In one exemplary embodiment, such as Figure 12As shown, a near-field scanning device is provided, comprising: a first determining module 1211, a second determining module 1212, a third determining module 1213, and a scanning module 1214, wherein:

[0097] The first determining module 1211 is used to determine the offset between each grid point to be divided and the preset starting grid point of the two-dimensional uniform network for each grid point to be divided in the two-dimensional uniform network of the electronic device under test.

[0098] The second determining module 1212 is used to determine the value of a first exponential function based on a preset exponential function, with each parameter in the parameter interval corresponding to the target threshold as the exponent; the target threshold is determined according to the preset parameter values ​​and the preset exponential function.

[0099] The third determining module 1213 is used to determine the first ratio of the offset to each first exponential function value, and to determine the parameter corresponding to the largest first ratio among the integer first ratios as the target parameter;

[0100] The scanning module 1214 is used to divide the grid points to be divided into a set according to the target parameters and the target threshold, and to perform near-field scanning on the electronic device under test based on the set obtained after dividing each grid point.

[0101] In an exemplary embodiment, the scanning module 1214 is specifically used to divide the grid points to be divided into an initial set corresponding to a preset parameter value when the target parameter is equal to the target threshold; and to determine a set identifier based on the target parameter and the offset when the target parameter is less than the target threshold, and to divide the grid points to be divided into the set corresponding to the set identifier.

[0102] In an exemplary embodiment, the scanning module 1214 is specifically configured to: determine a second exponential function value with the target parameter as the exponent based on a preset exponential function; determine a second ratio between a first offset and the second exponential function value; determine a third ratio between the second offset and the second exponential function value; determine a first product result of the second ratio and the third ratio; and determine a set identifier based on the first product result.

[0103] In an exemplary embodiment, the scanning module 1214 is specifically used to determine a first difference between the target threshold and the target parameter, and to determine a second product result between the first difference and a first preset constant value; if the first product result is odd, the second difference between the second product result and the second preset constant value is determined as a set identifier.

[0104] In an exemplary embodiment, the scanning module 1214 is specifically configured to determine the second product result as a set identifier if the first product result is even.

[0105] In one exemplary embodiment, each parameter within the parameter range is an integer value within a range greater than or equal to 0 and less than or equal to the target threshold.

[0106] Each module in the aforementioned near-field scanning device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0107] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 13 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores relevant data for near-field scanning. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a near-field scanning method.

[0108] Those skilled in the art will understand that Figure 13 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0109] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the above method embodiments.

[0110] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above method embodiments.

[0111] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of any of the above method embodiments.

[0112] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0113] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0114] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0115] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A near-field scanning method, characterized in that, The method includes: For each grid point to be divided in the two-dimensional uniform network of the electronic device under test, determine the offset between the grid point to be divided and the preset starting grid point of the two-dimensional uniform network; Based on a preset exponential function, a first exponential function value is determined with each parameter in the parameter interval corresponding to the target threshold as the exponent; the target threshold is determined according to the preset parameter values ​​and the preset exponential function. Determine the first ratio between the offset and each of the first exponential function values, and determine the parameter corresponding to the largest first ratio among the integer first ratios as the target parameter; The grid points to be divided are divided into a set according to the target parameters and the target threshold. Based on the set obtained after dividing each of the grid points to be divided, a near-field scan is performed on the electronic device under test.

2. The method according to claim 1, characterized in that, The step of dividing the grid points to be divided into a set according to the target parameters and the target threshold includes: When the target parameter is equal to the target threshold, the grid points to be divided are assigned to the initial set corresponding to the preset parameter value; If the target parameter is less than the target threshold, a set identifier is determined based on the target parameter and the offset, and the grid points to be divided are assigned to the set corresponding to the set identifier.

3. The method according to claim 2, characterized in that, The offset includes a first offset of the grid point to be divided in a first direction and a second offset of the grid point to be divided in a second direction; Determining the set identifier based on the target parameter and the offset includes: Based on the preset exponential function, determine the value of the second exponential function with the target parameter as the exponent; Determine a second ratio between the first offset and the value of the second exponential function, and determine a third ratio between the second offset and the value of the second exponential function; Determine the first product result of the second ratio and the third ratio, and determine the set identifier based on the first product result.

4. The method according to claim 3, characterized in that, Determining the set identifier based on the first product result includes: Determine a first difference between the target threshold and the target parameter, and determine a second product result between the first difference and a first preset constant value; If the first product result is odd, the second difference between the second product result and the second preset constant value is determined as the set identifier.

5. The method according to claim 4, characterized in that, The method further includes: If the first product result is even, the second product result is determined to be the set identifier.

6. The method according to claim 1, characterized in that, Each parameter within the parameter range is an integer value within a range greater than or equal to 0 and less than or equal to the target threshold.

7. A near-field scanning device, characterized in that, The device includes: The first determining module is used to determine the offset between the grid point to be divided and the preset starting grid point of the two-dimensional uniform network for each grid point to be divided in the two-dimensional uniform network of the electronic device under test. The second determining module is used to determine, based on a preset exponential function, the value of a first exponential function with each parameter in the parameter interval corresponding to the target threshold as the exponent; the target threshold is determined according to the preset parameter values ​​and the preset exponential function. The third determining module is used to determine the first ratio of the offset to each of the first exponential function values, and to determine the parameter corresponding to the largest first ratio among the integer first ratios as the target parameter; The scanning module is used to divide the grid points to be divided into a set according to the target parameters and the target threshold, and to perform near-field scanning on the electronic device under test according to the set obtained after dividing each of the grid points to be divided.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.

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