Method and system for testing immunity of close-range radio frequency electromagnetic field

Abstract

The invention provides a close-range radio frequency electromagnetic field immunity test method and system, and relates to the technical field of communication detection, and the method comprises the steps: collecting near-field electromagnetic field distribution data and near-field frequency spectrum power distribution data formed by a radio frequency interference source on the surface of a tested device; constructing a near-field electromagnetic field distribution model; according to the frequency spectrum overlapping degree between the near-field frequency spectrum power distribution data and the working frequency band of the tested equipment, calculating the interference intensity of a radio frequency interference source on the tested equipment, and calculating the power of a target interference source according to the interference intensity through a dynamic frequency spectrum adaptation algorithm; regulating and controlling a radio frequency interference source to generate a radio frequency interference source signal with target interference source power; and monitoring an electromagnetic coupling coefficient of the tested equipment for the radio frequency interference source signal based on the electromagnetic field intensity distribution model so as to generate an immunity test result. Therefore, an actual interference scene of modern wireless equipment in a near-field environment can be simulated more accurately, and comprehensive evaluation of the equipment immunity under high-frequency and near-field conditions is realized.

Description

Technical Field

[0001] The present application relates to the field of communication detection technology, and in particular to a close-range radio frequency electromagnetic field immunity testing method and system. Background Art

[0002] In recent years, wireless technologies represented by mobile communications, WiFi, Bluetooth and NFC have shown the characteristics of rapid increase in the number of devices, continuous expansion of frequency range and increasingly complex modulation methods. This series of changes makes it difficult for existing electromagnetic compatibility (EMC) test methods to cope with the complex electromagnetic environment of modern wireless devices.

[0003] Specifically, traditional RF applications are usually limited to high-power, low-frequency bands (such as AM / FM broadcasting, shortwave communications, etc.). These RF devices are mainly used in long-distance transmission scenarios, and the number is relatively small. With the popularization of wireless communications and technological upgrades, the application of RF equipment has gradually expanded to higher frequency bands (such as microwaves and millimeter waves), and the use of spectrum has become more intensive and complex. For example, the application frequency of WiFi technology has expanded to 2.4GHz, 5GHz and even higher 60GHz, and mobile communication technology has multiple different frequency bands allocated in the range of 0.8GHz to 6GHz. The wavelength of the energy radiated by these high-frequency devices is relatively short, and the intensity of the electromagnetic field distributed in space fluctuates violently, forming a more complex electromagnetic environment.

[0004] In addition, modern wireless devices are getting smaller and smaller. In pursuit of aesthetics, portability, and low-power design, radiating antennas are gradually changing from external to internal, and the radiation pattern of the antenna is also changing accordingly. Internal antennas usually have a coupling effect with the PCB board and metal casing of the device, resulting in a more complex distribution of the radiated electromagnetic field and a more significant near-field effect. This change in antenna design makes the electromagnetic interference generated by wireless devices particularly obvious when they are only a few centimeters away from other electronic devices. Traditional immunity test methods cannot fully characterize the impact of near-field electromagnetic interference on the immunity of the device.

[0005] At present, the immunity test standards (such as IEC 61000-4-3 and IEC 61000-4-6) issued by the International Electrotechnical Commission (IEC) are mostly based on electromagnetic compatibility tests in far-field environments, and the test distance is usually 1 meter or more. Such a test distance cannot simulate the actual scenario of close-range radio frequency interference, resulting in a large deviation between the test results and the immunity performance in the actual use environment. In addition, in the existing standards, most of the immunity test frequency bands are concentrated below 1GHz, while modern wireless devices usually operate in microwave bands of 2.4GHz, 5GHz and higher frequencies. However, the existing standards cannot fully cover these high-frequency bands, resulting in the inability to effectively evaluate the immunity performance of the equipment in high-frequency bands.

[0006] In response to the above problems, the industry has not yet proposed a better technical solution. Summary of the invention

[0007] The present application provides a close-range radio frequency electromagnetic field immunity test method, system, storage medium, computer program product and electronic device, which are used to at least solve the problem that traditional EMC test methods cannot cope with the complex radio electromagnetic environment and near-field effects of built-in antennas of modern wireless devices.

[0008] In the first aspect, an embodiment of the present application provides a close-range radio frequency electromagnetic field immunity test method, comprising: based on a wide-band probe array and a dynamic spectrum analyzer, collecting near-field electromagnetic field distribution data and near-field spectrum power distribution data formed by a radio frequency interference source on the surface of the device under test; the wide-band probe array covers the device under test and is used to receive radio frequency signals corresponding to the 1GHz to 10GHz frequency band at each probe position; based on the finite-difference time-domain method, the near-field electromagnetic field distribution data is processed to obtain a corresponding near-field electromagnetic field distribution model; the boundary conditions of the finite-difference time-domain method adopt absorption boundary conditions; according to the near-field spectrum power distribution The method comprises the following steps: calculating the interference intensity of the RF interference source on the device under test according to the interference intensity and the spectral overlap between the data and the working frequency band of the device under test, and calculating the target interference source power according to the interference intensity and the spectral overlap through a dynamic spectrum adaptation algorithm; regulating the RF interference source to generate an RF interference source signal with the target interference source power; the digital modulation mode of the RF interference source signal is switched according to the modulation switching time interval; monitoring the electromagnetic coupling coefficient of the device under test for the RF interference source signal based on the electromagnetic field intensity distribution model, and generating an anti-interference test result for the device under test according to the electromagnetic coupling coefficient.

[0009] In a second aspect, an embodiment of the present application provides a close-range radio frequency electromagnetic field immunity test device, comprising: a data acquisition unit, which is used to collect near-field electromagnetic field distribution data and near-field spectrum power distribution data formed by a radio frequency interference source on the surface of a device under test based on a wide-band probe array and a dynamic spectrum analyzer; the wide-band probe array covers the device under test and is used to receive radio frequency signals corresponding to a frequency band of 1 GHz to 10 GHz at each probe position; an electromagnetic field modeling unit, which is used to process the near-field electromagnetic field distribution data based on a finite-difference time-domain method to obtain a corresponding near-field electromagnetic field distribution model; the boundary conditions of the finite-difference time-domain method adopt an absorbing boundary condition; an interference power calculation unit, which is used to calculate the interference power according to the near-field spectrum The method comprises the following steps: calculating the interference intensity of the RF interference source on the device under test according to the interference intensity and the spectral overlap between the power distribution data and the working frequency band of the device under test, and calculating the target interference source power according to the interference intensity and the spectral overlap through a dynamic spectrum adaptation algorithm; an interference source signal control unit, which is used to control the RF interference source to generate an RF interference source signal with the target interference source power; the digital modulation method of the RF interference source signal is switched according to the modulation switching time interval; and an anti-interference test unit, which is used to monitor the electromagnetic coupling coefficient of the device under test for the RF interference source signal based on the electromagnetic field intensity distribution model, and generate an anti-interference test result for the device under test according to the electromagnetic coupling coefficient.

[0010] According to a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the steps of the close-range radio frequency electromagnetic field immunity test method of any embodiment of the present application.

[0011] In a fourth aspect, an embodiment of the present application provides a storage medium on which a computer program is stored, characterized in that when the program is executed by a processor, the steps of the close-range radio frequency electromagnetic field immunity testing method of any embodiment of the present application are implemented.

[0012] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the close-range radio frequency electromagnetic field immunity testing method of any embodiment of the present application.

[0013] The close-range radio frequency electromagnetic field immunity testing method and system provided by this application can produce at least the following technical effects:

[0014] (1) By using a wide-band probe array covering the 1 GHz to 10 GHz frequency band, it is possible to collect RF signals and interference source data in the high-frequency band, significantly improving the breadth of the test frequency band, effectively filling the gap in the existing standards in high-frequency band testing, ensuring that the anti-interference performance of wireless devices in the high-frequency band can be evaluated, and ensuring that the anti-interference performance of modern wireless devices in complex high-frequency environments can be comprehensively tested.

[0015] (2) Through the wide-band probe array, it is possible to collect near-field electromagnetic field distribution data and spectrum power distribution data at close range, and combine the finite-difference time-domain method (FDTD) to generate an accurate near-field electromagnetic field distribution model, so as to truly simulate the near-field interference environment when the device is working, capture the complex electromagnetic coupling effects caused by the built-in antenna design of modern devices, and solve the problem that traditional far-field test methods are difficult to accurately simulate close-range radio frequency interference.

[0016] (3) The power of the RF interference source is adjusted by using the spectrum overlap and interference strength through the dynamic spectrum adaptation algorithm to ensure that the power of the interference source during the test is highly matched with the actual working environment of the device. Not only can the actual impact of the interference source on the device under test be quantified, but the modulation method of the RF interference signal can also be dynamically adjusted to make the interference test more in line with the characteristics of frequent signal switching of wireless devices in actual use scenarios, so that the test can cover a wider range of actual use scenarios, thereby more comprehensively evaluating the anti-interference performance of the device under different modulation interference conditions.

[0017] (4) By real-time monitoring of the electromagnetic coupling coefficient between the device under test and the RF interference source based on the electromagnetic field intensity distribution model, the change in the coupling coefficient reflects the propagation characteristics of the interference source signal in the near-field environment and its impact on the device, which can fully consider the impact of the near-field coupling effect on the immunity test results and more comprehensively evaluate the device's immunity performance. In addition, for devices with built-in antennas with a high degree of coupling, measuring the coupling coefficient effectively solves the problem of difficulty in evaluating electromagnetic interference caused by the small size of the device and the built-in antenna.

[0018] Through this technical solution, combined with multi-dimensional comprehensive considerations of near-field interference, spectrum overlap, real modulation mode and electromagnetic coupling, the generated test results are more authentic and accurate. It not only enhances the ability to capture high-frequency RF signals and improves the frequency band coverage of the test, but also can more accurately simulate the actual interference scenarios of modern wireless devices in near-field environments, and realize a comprehensive evaluation of the device's anti-interference performance under high-frequency and near-field conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flowchart showing an example of a close-range radio frequency electromagnetic field immunity testing method according to an embodiment of the present application is shown;

[0021] Figure 2 An operation flow chart of an example of constructing a near-field electromagnetic field distribution model according to an embodiment of the present application is shown;

[0022] Figure 3 An operation flow chart of an example of calculating the target interference source power according to an embodiment of the present application is shown;

[0023] Figure 4 An operation flow chart of an example of generating an immunity test result according to an electromagnetic coupling coefficient according to an embodiment of the present application is shown;

[0024] Figure 5 A schematic diagram showing a simulation effect of an example of an immunity curve according to an embodiment of the present application is shown;

[0025] Figure 6 A structural block diagram of an example of a close-range radio frequency electromagnetic field immunity test system according to an embodiment of the present application is shown;

[0026] Figure 7 It is a schematic structural diagram of an embodiment of an electronic device of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0028] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved shall comply with the provisions of relevant laws and regulations and shall not violate public order and good morals.

[0029] Figure 1 A flowchart of an example of a close-range radio frequency electromagnetic field immunity testing method according to an embodiment of the present application is shown.

[0030] Regarding the executor of the method of the embodiment of the present application, it can be any controller or processor with computing or processing capabilities. By expanding the test frequency band, accurately simulating the near-field electromagnetic environment, dynamically modulating the interference signal, and monitoring the electromagnetic coupling effect, the accuracy and applicability of the electromagnetic compatibility test of existing wireless devices are significantly improved.

[0031] In some examples, it may be integrated and configured in an electronic device, terminal or server by means of software, hardware or a combination of software and hardware, and the types of the terminal, electronic device or server may be diverse, such as a mobile phone, tablet computer or desktop computer, etc.

[0032] like Figure 1 As shown, in step S110, based on the wide-band probe array and the dynamic spectrum analyzer, the near-field electromagnetic field distribution data and the near-field spectrum power distribution data formed by the radio frequency interference source on the surface of the device under test are collected.

[0033] In some embodiments, a wide-band probe array is used to cover the entire surface of the device under test, and the number and position of the probes need to be optimized according to the size, shape and radiation characteristics of the device under test. The probe array should be able to sensitively receive radio frequency signals in the frequency range of 1 GHz to 10 GHz, and be able to record the electromagnetic field intensity distribution at each probe position. In addition, through the configuration of a dynamic spectrum analyzer, the radio frequency signal received at each probe position can be analyzed in real time, and the near-field spectrum power distribution data can be analyzed according to the frequency band, and instantaneous spectrum changes can be processed to capture the interference power distribution of radio frequency interference sources on electronic devices in different frequency bands.

[0034] In step S120, the near-field electromagnetic field distribution data is processed based on the finite-difference time-domain method to obtain a corresponding near-field electromagnetic field distribution model, and the boundary condition of the finite-difference time-domain method adopts an absorbing boundary condition.

[0035] In some embodiments, the collected near-field electromagnetic field distribution data is input into the FDTD simulation module, and the propagation and change of the electromagnetic field in the time and space dimensions are calculated by numerically solving the Maxwell equations. Exemplarily, the entire calculation area on the surface of the device under test is discretized by the FDTD module, the surface of the device and the surrounding space are divided into grid points, and the electromagnetic field intensity of each grid point is calculated. In addition, since the calculation area is limited, there may be electromagnetic wave reflection phenomena on the boundary that interfere with the simulation results. Therefore, in the FDTD calculation, the absorbing boundary condition (ABC) can absorb the electromagnetic waves reflected back from the boundary, avoid the reflected waves from interfering with the real electromagnetic field distribution during the simulation, and ensure that the model is more accurate.

[0036] In step S130, the interference intensity of the radio frequency interference source on the device under test is calculated according to the spectrum overlap between the near-field spectrum power distribution data and the working frequency band of the device under test, and the target interference source power is calculated according to the interference intensity through a dynamic spectrum adaptation algorithm.

[0037] In some embodiments, the degree of overlap between the two in the frequency domain is calculated based on the working frequency band of the device under test and the near-field spectrum power distribution of the interference source. Therefore, the spectrum overlap reflects the potential risk of interference between the interference source signal and the device working signal. The higher the overlap, the more likely the signal of the interference source is to affect the normal operation of the device. Then, through the dynamic spectrum adaptation algorithm, the power distribution of the interference source signal on the surface of the device and the working frequency band characteristics of the device under test are comprehensively considered, and the appropriate target interference source power is calculated according to the interference intensity, and the interference source power is automatically adjusted to match the actual environmental conditions of the test target.

[0038] In step S140, the RF interference source is regulated to generate a RF interference source signal having a target interference source power, and the digital modulation mode of the RF interference source signal is switched according to the modulation switching time interval.

[0039] Here, the target interference source power reflects the most appropriate interference signal strength under the current test conditions. By adjusting the power of the interference source according to the target interference source power so that it accurately matches the calculated target power, it can ensure that the interference strength remains at an ideal level throughout the test process, avoiding interference from too strong or too weak interference signals to the device test. For example, if the interference power is too large, it may cause the device to fail prematurely and fail to reflect the anti-interference ability under actual working conditions; if the interference power is too small, the test results cannot truly reflect the device's anti-interference ability in a strong interference environment.

[0040] In addition, the RF interference source supports a variety of digital modulation methods, such as QAM (Quadrature Amplitude Modulation), PSK (Phase Shift Keying), etc., and can be switched according to the modulation switching time interval. In this way, it can simulate interference signals of various modulation methods in the modern wireless device environment, simulate the complex signal interference of modern wireless devices, provide a more realistic anti-interference test scenario, and improve the applicability and accuracy of the test.

[0041] It should be noted that, on the one hand, the modulation switching time interval can be a preset fixed value. On the other hand, the modulation switching time interval can also be floating, for example, dynamically adjusted according to the actual operating frequency of the device and signal fluctuations, and more details will be described below in conjunction with other examples.

[0042] In step S150, the electromagnetic coupling coefficient of the device under test to the radio frequency interference source signal is monitored based on the electromagnetic field intensity distribution model, and an immunity test result for the device under test is generated according to the electromagnetic coupling coefficient.

[0043] Here, based on the electromagnetic field strength distribution model generated in step S120, the electromagnetic coupling coefficient between each part of the device under test and the RF interference source is monitored in real time. It should be understood that the coupling coefficient is used to measure the energy transmission efficiency between the device and the interference source, which reflects the degree of influence of the interference on the internal circuits and components of the device. The coupling coefficient can be calculated in a variety of ways, for example, by calculating the relationship between the electric field and magnetic field strength in the space around the device and the time.

[0044] In some implementations, the anti-interference test results are generated based on the monitored electromagnetic coupling coefficient and the working state of the device under test. Based on the change in the coupling coefficient, the impact of the RF interference source on the device is evaluated, and the corresponding anti-interference test results are generated, which can comprehensively evaluate the performance of the device under near-field interference and is also conducive to providing optimization design suggestions, such as antenna position adjustment, shielding material selection, etc.

[0045] Through this embodiment, the electromagnetic coupling coefficient is monitored in real time, and dynamic feedback can be provided on the interaction between the device and the interference source in different near-field electromagnetic environments. The specific anti-interference performance of the device under the influence of the interference source can be accurately captured, and reliable test results can be provided, providing a scientific basis for the electromagnetic compatibility design optimization of the device.

[0046] Regarding the details of the wide-band probe array in the above step S110, the wide-band probe array includes multiple probe nodes. Based on the electric field sensors and magnetic field sensors in each probe node, the electric field strength information and magnetic field strength information of the corresponding probe node position are sampled respectively to obtain the corresponding near-field electromagnetic field distribution data. In this way, the dense layout of the probe array ensures that the details of the electromagnetic field changes on the surface of the device can be fully captured, especially the "hot spot" area of ​​the local electromagnetic field, and the trend of electric and magnetic fields changing with space. In addition, by synchronously collecting electric and magnetic field data, it is possible to track the dynamic changes of the electromagnetic field in the time dimension, providing accurate basic data for subsequent electromagnetic coupling and interference analysis.

[0047] In addition, the dynamic spectrum analyzer is used to scan each probe node one by one, and the signal power of each corresponding probe node position in different frequency bands is sampled to obtain the corresponding near-field spectrum power distribution data. In this way, a wide frequency band from 1GHz to 10GHz can be covered to ensure that the impact of RF interference signals of different frequencies on the device can be fully recorded, covering interference from low frequency to high frequency. Moreover, by collecting the signal power of each frequency band by scanning position by position, the spectrum distribution of different areas on the device surface can be accurately characterized, which helps to identify and capture the local effects of RF interference sources on the device surface.

[0048] In some examples of the embodiments of the present application, the wideband probe array includes a plurality of probe node matrices arranged in different surface areas of the device under test, and each probe node matrix is ​​hexagonal. The first distribution density of the probe nodes in the first probe node matrix is ​​greater than the second distribution density of the probe nodes in the second probe node matrix, the first probe node matrix is ​​arranged in the key module area of ​​the device under test, and the second probe node matrix is ​​arranged in the non-key module area on the surface of the device under test. Here, the key module area includes the antenna area, the processor area and the power supply area, and the non-key module area includes the support structure area and the radiator area.

[0049] It should be noted that the high-density probe layout in key module areas (including antenna areas, processor areas, and power supply areas) enables electromagnetic field changes to be accurately captured in areas where the device is most sensitive and has the highest interference intensity. These areas are usually the core functional areas of the device and are susceptible to external electromagnetic interference. Through the deployment of high-density probes, it is possible to ensure that the electromagnetic fields in these areas are finely collected to reduce missed measurements. In addition, the low-density probe layout in non-critical module areas (such as support structure areas and radiator areas) can optimize the resource allocation of probes. In these areas, the electromagnetic field changes are small, and low-density probes are sufficient to complete the signal acquisition task, thereby effectively saving resources and reducing system complexity.

[0050] Here, by arranging the probe nodes in a hexagonal honeycomb matrix, uniform coverage of the nodes in the sampling area can be ensured. Through the hexagonal arrangement, the distance between the probe nodes remains uniform, avoiding the problem of blank areas that may exist in the matrix grid layout. Therefore, the electromagnetic field distribution on the entire device surface can be collected more comprehensively, especially the coupling effect generated by interference sources in different areas, which can be accurately characterized.

[0051] Through the embodiments of the present application, a non-uniform density adaptive layout combined with a hexagonal probe matrix layout is adopted to achieve comprehensive and accurate collection of the electromagnetic field distribution on the device surface, so that circuit modules of devices that are susceptible to interference can be finely monitored and analyzed, while at the same time effectively reducing resource waste and improving data collection efficiency and overall test performance.

[0052] Figure 2 An operational flowchart of an example of constructing a near-field electromagnetic field distribution model according to an embodiment of the present application is shown.

[0053] It should be noted that the finite-difference time-domain method (FDTD) is a numerical analysis method used to solve Maxwell's equations to simulate the propagation behavior of electromagnetic fields in space and time. The FDTD method discretizes time and space, expresses the changes in electric and magnetic fields with finite difference approximations, and gradually updates the electric and magnetic field values.

[0054] like Figure 2 As shown, in step S210, based on the near-field electromagnetic field distribution data, electric field components and magnetic field components for each surface area of ​​the device under test are constructed.

[0055] Specifically, the updating of the electric field and the magnetic field is performed alternately, for example, in each time step, the electric field is updated first, and then the magnetic field is updated.

[0056]

[0057] In the formula, E n+1 represents the electric field component of the surface area at the n+1th time step in the simulation, n represents the number of iterations of the time step, E n represents the electric field component of the surface area at the nth time step, represents the dielectric constant of the surface area, σ represents the conductivity of the surface area; τ represents the time step in the simulation, which is used to update the changes of the electric and magnetic fields over time; is the magnetic field curl at the nth time step, H n+1 represents the magnetic field component of the surface area at the n+1th time step, H n is the magnetic field component of the surface area at the nth time step, μ is the magnetic permeability of the surface area, is the electric field curl at the n+1th time step.

[0058] In FDTD simulation, it is necessary to define the material properties of the device surface, such as the dielectric constant The conductivity σ and magnetic permeability μ ensure that the behavior of the electromagnetic field on the surface of different materials can be accurately simulated. In each time step τ, the electric field is updated using the magnetic field data at the probe node. After the electric field is updated, the magnetic field is updated using the results of the electric field at the adjacent time.

[0059] Through the embodiments of the present application, the electric field and magnetic field of each surface area of ​​the device under test are updated and constructed, allowing for refined processing based on the material properties of different areas on the device surface, and more accurately capturing the changes in the electromagnetic field of each surface area. In addition, each surface area has different electromagnetic response characteristics. By updating the electric field and magnetic field of each area separately, the differences between these areas can be reflected, and how the electromagnetic interference source affects a specific area can be more clearly shown.

[0060] Preferably, in order to ensure numerical stability, the time step τ used for simulation can also satisfy the CFL (Courant-Friedrichs-Lewy) condition:

[0061]

[0062] In the formula, c is the speed of light, and Δx, Δy, and Δz are the spatial steps. Regarding the spatial step, during the simulation process, the surface of the device under test is discretized according to a fixed grid (such as a three-dimensional cubic grid or a non-uniform grid), and each grid point corresponds to the value of the electric field and magnetic field. Therefore, the space is not continuous, but is divided into several discrete points, called grid points, and the distance between each two adjacent grid points is the spatial step.

[0063] In step S220 , a near-field electromagnetic field distribution model is generated based on the constructed electric field components and magnetic field components of each surface area.

[0064] Through the embodiments of the present application, after multiple iterative updates, an electromagnetic field distribution model of the device surface and its surroundings is finally obtained, which can clearly display the spatial distribution of electric and magnetic fields and their changing trends over time. For example, the near-field electromagnetic field distribution on the device surface is displayed in three dimensions, which can help identify the electromagnetic interference intensity and electromagnetic field fluctuations in different areas of the device surface.

[0065] For example, the electromagnetic field distribution model can accurately identify the "hot spot" area with high electromagnetic field intensity on the device surface, which is usually the part with strong electromagnetic coupling, indicating that this part is susceptible to external interference and needs further optimization design. In addition, the FDTD model can also show the electromagnetic field response of the device in different time periods, especially the changes in the electromagnetic field of the device under interference signals of different frequency bands.

[0066] Through the embodiments of the present application, electromagnetic field models are generated for different surface areas and the electromagnetic field models are constructed area by area. Regional processing allows designers to analyze specific areas more carefully at high resolution, helping designers to perform local optimization or shielding design for hot spots, thereby improving the overall anti-interference ability of the equipment.

[0067] Figure 3 An operational flow chart of an example of calculating the target interference source power according to an embodiment of the present application is shown.

[0068] like Figure 3 As shown, in step S310, the total spectrum overlap is calculated.

[0069] Here, the spectrum overlap refers to the overlap area between the working frequency band of the device under test and the interference source signal in the spectrum, which is one of the key parameters of the interference source's impact on the device. In this embodiment, a comprehensive statistics of multiple interference frequency bands is performed to calculate the corresponding total spectrum overlap.

[0070] For example, it is assumed that the frequency band of the interference source is divided into a plurality of frequency bands D i (where i = 1, 2, ..., N, a total of N frequency bands), each frequency band D i The corresponding power distribution is P i (f). On this basis, the overlap between each frequency band and the device operating frequency band W is calculated O(W,D i ).

[0071]

[0072] Where P i (f) is the near-field spectrum power distribution data, indicating the frequency f of the RF interference source in the i-th interference frequency band i Power distribution under; W and D i Respectively represent the working frequency band of the device under test and the i-th interference frequency band of the RF interference source, O(W,D i ) indicates W and D i The overlap degree, N is the total number of interference frequency bands; w i is the weight coefficient for each interference frequency band, reflecting the sensitivity of the device under test to different interference frequency bands; weighted Represents the total weighted spectrum overlap.

[0073] Here, for N frequency bands, the spectrum overlap O(W,D i ), and then introduce the weighting coefficient w i , the overlap of different frequency bands is weighted and synthesized, taking into account the contribution of all frequency bands.

[0074] In step S320, the total interference intensity of the radio frequency interference source to the device under test is calculated based on the total spectrum overlap.

[0075] Here, when calculating the total interference strength, the independent impact of each sub-band should also be considered, so as to adjust the calculation of the interference strength accordingly. Specifically, based on the overlap degree O(W,D i) and the corresponding average power P avg,i , calculate the interference intensity of each sub-band, and obtain the total interference intensity I through weighted synthesis interference .

[0076]

[0077] In the formula, I interference represents the weighted total interference strength, α i represents the environmental impact adjustment coefficient for the i-th interference frequency band, which is used to describe the degree to which the interference source signal of the i-th interference frequency band is affected by the environment; P avg,i It represents the average near-field power of the RF interference source in the overlapping frequency band. The overlapping frequency band is the overlapping part between the i-th interference frequency band and the working frequency band of the device under test.

[0078] In one example of the embodiment of the present application, the environmental impact adjustment coefficient α i It can be pre-set, for example, by analyzing the interference effects of different interference frequency bands in the test environment, such as indoors, outdoors, or in an environment with obstacles. In this way, by considering the impact of environmental factors on different frequency bands, the test can better simulate the electromagnetic interference situation in the actual application scenario, thereby improving the authenticity of the test and the reliability of the device's anti-interference design. For example, the signal in the high frequency band may be more susceptible to the influence of walls, obstacles, etc. In another example of the embodiment of the present application, the environmental impact adjustment coefficient α i It can also be automatically determined or updated based on the actual environmental test results, for example, by using electromagnetic field simulation software to simulate the propagation of interference signals in the test environment, and obtain the loss values ​​of different frequency bands, thereby determining α i , more details will be expanded below with other examples.

[0079] In step S330, the target interference source power is calculated according to the total interference intensity by using a dynamic spectrum adaptation algorithm.

[0080] P target =I interference β, formula (7)

[0081] Where P target represents the target interference source power, and β represents the power adjustment coefficient.

[0082] Here, the power adjustment coefficient β can be pre-calibrated. Specifically, when the device immunity range is known, the designer or tester can manually set β through the device technical specifications. For example, the test power specified in the industry standard IEC 61000-4-3 is between 3V / m and 10V / m. The tester can set the β value to the corresponding adjustment coefficient to ensure that the output interference power meets the standard requirements.

[0083] Through the power adjustment coefficient β, the power of the target interference source can be flexibly adjusted to meet the test requirements of different devices. For example, according to the needs of the actual test, the power output of the interference source is dynamically changed based on the adjustment coefficient β, which enhances the flexibility of the test and can adjust the interference source power according to the anti-interference capability of different devices to avoid excessive power that damages the device or too low power that cannot trigger sufficient interference.

[0084] Through the embodiments of the present application, multi-band weighted calculation is introduced, and the interference signals of different interference bands can be accurately evaluated. The spectrum overlap, interference intensity and sensitivity of the device to the frequency band of each interference band are fully considered. As a result, the anti-interference ability of the device in different frequency bands can be carefully reflected. For example, some devices may be more sensitive to high-frequency bands and have weaker interference to low-frequency bands. Based on weighted calculation, this difference can be reasonably reflected, thereby generating interference source power suitable for the actual situation of the device. Compared with the traditional single-band test method, the multi-band weighted method can simultaneously evaluate the anti-interference performance of the device in multiple frequency bands, thereby improving the test efficiency.

[0085] About α i According to relevant explanations, in different frequency bands, the propagation characteristics of the signal will be affected by the frequency, especially in the high-frequency band and the low-frequency band, the reflection, attenuation and scattering effects of the signal are significantly different.

[0086] Specifically, α i It can be calculated by the following formula:

[0087]

[0088] Where S0 is the reference power density of the RF interference source, S(d,i) is the power density of the interference source signal in the i-th interference frequency band when the distance is d meters, and λ i is the signal wavelength of the interference source signal in the i-th interference frequency band, L ref,i is the reflection path length of the interference source signal in the i-th interference frequency band in the test environment, G ref,i is the number of reflections of the interference source signal of the ith interference frequency band in the test environment, γ(i) is the reflection loss coefficient of the interference source signal of the ith interference frequency band, η(i) is the near-field interference coefficient of the ith interference frequency band, P near,i is the near-field power value of the interference source signal in the i-th interference frequency band, P total,i is the total transmission power of the interference source signal of the RF interference source for the i-th interference frequency band.

[0089] It should be noted that S(d,i) varies with different frequency bands. As the distance d increases, the signal power density decreases, and the degree of signal attenuation varies in different frequency bands. Especially in high frequency bands, the path loss and attenuation of the signal will be more obvious. In the anti-interference test, the power density of the signal is an important indicator of the strength of the signal received by the test equipment. Especially in high frequency bands, the signal power density decays faster.

[0090] Specifically, it is expressed by the following formula:

[0091]

[0092] Where f0 is the reference frequency, which can be selected as 1GHz, and f i is the frequency of band i, which ensures that the power density change of the high-frequency band signal during propagation is reflected. In addition, the signal wavelength λ under band i i It can reflect the diffraction and reflection characteristics of signals in different frequency bands. The wavelength of high-frequency band signals is shorter, and the influence of scattering and reflection is greater. High-frequency band signals are easily reflected in the laboratory, especially in metal equipment or closed spaces. Therefore, the reflection path lengths in different frequency bands will be different, and the reflection path loss of high-frequency band signals will be more significant. Therefore, L ref,i It decreases as the frequency band increases, and is usually smaller. In the laboratory, the signal may be reflected multiple times from the wall and the surface of the equipment. These reflections will affect the signal propagation path. High-frequency signals have more reflection paths in the laboratory, especially when there are metal equipment surfaces. Therefore, the G ref,i The value is usually higher than that of the low frequency band. In the immunity test, when the distance between the test equipment and the interference source is short, the near-field coupling effect between the antennas will affect the signal strength. The near-field effect of high-frequency signals is usually more significant. i The higher it is, the stronger the near-field interference between signals is, and η(i) increases with the increase of frequency band.

[0093] Here, S0, L ref,i , G ref,i , γ(i) and η(i) can be preset, for example, calibrated by simulation tools according to the test room environment and the output characteristics of the interference source, and can be reused in scenarios where the test environment conditions are relatively stable. near,i , P total,i and S(d,i) are dynamically updated by sampling the near-field electromagnetic field distribution data.

[0094] By introducing the near-field interference coefficient and the reflection loss coefficient, the actual signal impact on the device near the interference source can be accurately calculated in the close-range electromagnetic field interference test. When the distance between the device and the interference source is close, the near-field interference effect is significant. By quantifying the contribution of near-field interference to the total signal power, it is ensured that the device's anti-interference test can accurately reflect its performance in high-power density scenarios. The reflection loss coefficient can quantify the impact of signal reflection loss on different frequency bands, especially in high-frequency bands, and dynamically adjust the adjustment coefficient to effectively capture the propagation characteristics of the signal in a complex reflection environment, reduce errors, and improve the effectiveness of interference testing.

[0095] Through the above α i The calculation process accurately reflects the propagation characteristics of signals of different frequencies in a laboratory or test environment. For low-frequency signals, due to the longer wavelength, fewer reflections, and less near-field interference, the corresponding environmental impact adjustment coefficient will be relatively small. For high-frequency signals, the wavelength is shorter and is easily affected by reflection, multipath effects, and near-field interference. The corresponding environmental adjustment coefficient is higher to quantify the attenuation of high-frequency signals in complex environments. Therefore, the environmental impact adjustment coefficient comprehensively considers the path loss, reflection, and near-field effects of the signal, and through multi-dimensional adjustments, the test system can better adapt to the complex electromagnetic environment in the laboratory or test room. In addition, by accurately distinguishing the propagation characteristics of different frequency bands, the test system can more accurately evaluate the anti-interference ability of the equipment in the high-frequency band, while ensuring that the test results of the signal in the low-frequency band truly reflect the actual situation.

[0096] In some examples of the embodiments of the present application, the modulation switching time interval for switching the digital modulation mode of the RF interference source signal is floating. During the test, the signal power received by the device is monitored through the near-field spectrum power distribution data, and the modulation switching time interval is dynamically updated according to the change of the signal power.

[0097] Specifically, the modulation switching time interval is dynamically updated by the following formula:

[0098]

[0099] Where, ΔT m (T+1) represents the duration of the T+1th modulation switching time interval, ΔT m (T) represents the duration of the Tth modulation switching time interval, P(T) represents the interference source signal power received by the device under test in the Tth modulation switching time interval, Indicates the rate of decrease of signal power during the Tth modulation switching time interval.

[0100] Here, based on the speed of signal power decline, the switching time of digital modulation can be adjusted dynamically. Specifically, if the signal power declines rapidly, it means that the device under test may show weak anti-interference ability under this modulation mode, so the current modulation mode is kept for a longer time to deeply test the tolerance of the device under this interference signal; if the signal power changes slowly, the switching of the modulation mode can be accelerated to cover other interference scenarios faster.

[0101] For example, initially, the system is set to ΔT m (1) Preliminary settings for switching modulation modes, and real-time monitoring of the signal power P(T) received by the device, and calculation of the rate of decrease of signal power Dynamically adjust the modulation switching time ΔT according to the falling speed m (T+1), so that when the signal power decays faster, the duration of the modulation mode is extended, and when the decay is slower, the switching is accelerated.

[0102] It should be noted that the traditional fixed-time modulation switching strategy may lead to low test efficiency, especially when the device has good anti-interference performance for a certain modulation mode, the long duration wastes valuable test time. However, when the device faces interference signals of different modulation modes, its anti-interference performance will be different.

[0103] Through the embodiments of the present application, the changes in the signal power received by the device are monitored in real time, and the modulation switching interval is adjusted according to the speed of power decrease, so that the test process can better match the anti-interference performance of the device. When the interference is strong and the device performance is poor, the duration of the modulation mode is extended to ensure that the device is fully exposed to the interference environment under this condition; when the interference is weak and the device performance is good, the switching is accelerated to save test time. Therefore, based on the adaptive dynamic period adjustment mechanism, through the dynamic monitoring of signal power, the system can automatically identify the adaptability of the device to different modulation modes, speed up the switching of modulation modes when the signal power decays slowly, avoid unnecessary redundant testing, and improve the test efficiency while ensuring the test quality.

[0104] It should be noted that the electromagnetic coupling coefficient is a key parameter to measure the coupling strength between the electromagnetic field formed by the RF interference signal on the surface of the device and the device. Here, the coupling strength can be measured by the electromagnetic field intensity gradient.

[0105] Specifically, the electromagnetic field intensity distribution model provides the spatiotemporal distribution data of the electric and magnetic fields at each probe position on the device surface. The gradient of the electromagnetic field reflects the changes of the electromagnetic field as it propagates in space. Where the local gradient is large, it means that the electromagnetic field changes dramatically in this area, and the device under test is more disturbed by electromagnetic energy in this area. By analyzing this model, the rate of change of the electromagnetic field in different areas of the device surface (i.e., the gradient) is obtained, and the degree of interference in different surface areas of the device surface can be identified. The electromagnetic coupling coefficient K(t) is calculated accordingly. The larger the coupling coefficient K(t), the more susceptible the device under test is to interference in this area.

[0106] More specifically, the electromagnetic coupling coefficient K(t) is calculated by the following formula:

[0107]

[0108] Where K(t) is the electromagnetic coupling coefficient at the tth time step, which indicates the electromagnetic field coupling strength between the device under test and the RF interference source; Ω is the integration area, which indicates the sampling area of ​​the surface of the device under test covered by the wide-band probe array; is the electric field gradient at the tth time step, which represents the rate of change of the electric field E(t) in the surface area with the position of the sampling point in the electromagnetic field intensity distribution model; and are the spatial partial derivatives of the electric field, representing the rate of change of the electric field E(t) in the x, y, and z directions of space respectively; is the magnetic field gradient at the tth time step, which represents the rate of change of the magnetic field H(t) in the surface area with the position of the sampling point in the electromagnetic field intensity distribution model; and are the spatial partial derivatives of the magnetic field, representing the rate of change of the magnetic field H(t) in the x, y, and z directions of space, respectively.

[0109] Here, by integrating the electric field and magnetic field gradient distribution on the entire device surface, the electromagnetic coupling coefficient K(t) can be calculated to comprehensively evaluate the coupling of the device at various spatial locations. By analyzing the electromagnetic field distribution data of each probe node on the device surface, the difference in the anti-interference performance of the device in different areas can be analyzed. This can not only reveal the local coupling strength of the device, but also give the anti-interference degree of the entire device in different areas, helping to identify the weak areas of the device in an interference environment.

[0110] It should be noted that It reflects the change of the electric field on the device surface with the spatial position, which can be calculated based on the electric field data in the electromagnetic field intensity distribution model, such as the electric field data sampled by each probe node on the device surface. It reflects the change of magnetic field at different spatial positions on the device surface, which can be obtained by analyzing the magnetic field data in the electromagnetic field intensity distribution model. The spatial partial derivatives of the electric field and the spatial partial derivatives of the magnetic field can be obtained by numerically differentiating the electric field distribution data and the magnetic field distribution data at different points on the device surface in the electromagnetic field intensity distribution model.

[0111] Through the embodiment of the present application, the calculation method based on the electromagnetic field intensity gradient is adopted to accurately evaluate the electromagnetic coupling effect of the device under the RF interference source. and magnetic field gradient It can accurately capture the electromagnetic interference to the device at a specific time and spatial position. The electromagnetic coupling coefficient K(t) represents the response of the device to the external electromagnetic field at each moment, and can reflect the device's anti-interference ability to interference signals with different modulation modes, frequency bands, and power levels.

[0112] It should be pointed out that the electromagnetic coupling coefficient K(t) changes dynamically with the time step t in the simulation, and the interference intensity of the device at different time points can be monitored in real time. By continuously calculating K(t), the response behavior of the device in the face of a constantly changing electromagnetic environment can be dynamically tracked. For example, when the modulation mode, frequency, and power of the RF interference signal change, the electromagnetic field gradient on the surface of the device will also change accordingly, so that the coupling coefficient can be updated at any time, ensuring the timeliness of the test.

[0113] Figure 4 An operational flow chart of an example of generating an immunity test result according to an electromagnetic coupling coefficient according to an embodiment of the present application is shown.

[0114] like Figure 4 As shown, in step S410, an immunity curve is drawn according to the electromagnetic coupling coefficient of each time step.

[0115] Here, the anti-interference curve is a function curve with time step t as the horizontal axis and electromagnetic coupling coefficient K(t) as the vertical axis. The time step used for simulation has a certain span, and the sampling values ​​of the blank moments of such span can be numerically filled by interpolation. Through the electromagnetic field strength data collected by the probe nodes on the surface of the device during the test, the system can continuously calculate the electromagnetic coupling coefficient at each time point and draw a curve, which can reflect the dynamic changes of the electromagnetic coupling strength of the device during the entire test process. As time goes by and the interference signal changes, the ups and downs of the curve show the anti-interference performance of the device.

[0116] In step S420, the maximum coupling coefficient, the average coupling coefficient and the standard deviation of the coupling coefficient are extracted from the immunity curve to determine the immunity test result for the device under test.

[0117] Here, the maximum coupling coefficient K max It can be the highest point in the immunity curve, representing the maximum electromagnetic coupling strength experienced by the device during the immunity test. Average coupling coefficient K avg It reflects the overall anti-interference ability of the device during the entire test period, which can be obtained by taking a time-weighted average of the anti-interference curve. If the average value is low, it means that the overall anti-interference ability of the device under test is strong. The standard deviation of the coupling coefficient K std , which is used to reflect the fluctuation amplitude of the coupling coefficient in the immunity curve. The larger the standard deviation, the greater the fluctuation of the device's anti-interference ability in different time periods; the smaller the standard deviation, the more stable the device's anti-interference performance. Furthermore, by extracting the above key indicators from the immunity curve, an immunity test report for the device under test is generated.

[0118] Figure 5 A schematic diagram of simulation effect of an example of an immunity curve according to an embodiment of the present application is shown.

[0119] like Figure 5 As shown in the figure, the blue curve represents the anti-interference curve, which shows the trend of the interference coupling coefficient K(t) changing with time, reflecting the coupling strength between the test equipment and the interference source during the whole process, and showing the interference coefficient value at different times, which can reflect the dynamic response of the equipment to the interference signal. The maximum coupling coefficient K max =1.50, which can determine the anti-interference ability of the device under extreme interference conditions. Average coupling coefficient K avg =0.66, providing an evaluation of the immunity of the device under normal conditions. The standard deviation of the coupling coefficient K std =0.28, which expresses the fluctuation of the device's immunity during the test.

[0120] Through the embodiment of the present application, the dynamic performance of the anti-interference ability of the device is provided based on the anti-interference curve. By sampling the electromagnetic coupling coefficient of the device at different time points, the entire response process of the device in the interference test can be clearly depicted, so that the tester can monitor the anti-interference performance of the device in the test process in real time. By analyzing the anti-interference curve, the tester can clearly see the anti-interference performance of the device in a specific frequency band, a specific power, or a specific modulation mode, and the weak links of the device anti-interference can be revealed through the change trend of the maximum coupling coefficient, the average coupling coefficient and the standard deviation. As a result, the performance weaknesses of the device in a specific time period or under an interference signal can be discovered in time, and a targeted device optimization design scheme can be made to help optimize the design and anti-interference strategy of the device. For example, the anti-interference ability of the device can be improved by adjusting the module design or increasing shielding in a specific area, thereby significantly improving the electromagnetic compatibility of the device under test.

[0121] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of actions combined, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application. In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0122] Figure 6 A structural block diagram of an example of a close-range radio frequency electromagnetic field immunity testing system according to an embodiment of the present application is shown.

[0123] like Figure 6 As shown, the short-range radio frequency electromagnetic field immunity testing system 600 includes a data acquisition unit 610 , an electromagnetic field modeling unit 620 , an interference power calculation unit 630 , an interference source signal control unit 640 and an immunity testing unit 650 .

[0124] The data acquisition unit 610 is used to collect near-field electromagnetic field distribution data and near-field spectrum power distribution data formed by the radio frequency interference source on the surface of the device under test based on a wide-band probe array and a dynamic spectrum analyzer; the wide-band probe array covers the device under test and is used to receive radio frequency signals in the 1GHz to 10GHz frequency band corresponding to each probe position.

[0125] The electromagnetic field modeling unit 620 is used to process the near-field electromagnetic field distribution data based on the finite-difference time-domain method to obtain a corresponding near-field electromagnetic field distribution model; the boundary condition of the finite-difference time-domain method adopts an absorbing boundary condition.

[0126] The interference power calculation unit 630 is used to calculate the interference intensity of the radio frequency interference source on the device under test based on the spectrum overlap between the near-field spectrum power distribution data and the working frequency band of the device under test, and calculate the target interference source power based on the interference intensity and the spectrum overlap through a dynamic spectrum adaptation algorithm.

[0127] The interference source signal control unit 640 is used to control the radio frequency interference source to generate a radio frequency interference source signal having the target interference source power; the digital modulation mode of the radio frequency interference source signal is switched according to the modulation switching time interval.

[0128] The anti-interference test unit 650 is used to monitor the electromagnetic coupling coefficient of the device under test for the radio frequency interference source signal based on the electromagnetic field intensity distribution model, and generate an anti-interference test result for the device under test according to the electromagnetic coupling coefficient.

[0129] In some embodiments, an embodiment of the present application provides a non-volatile computer-readable storage medium, which stores one or more programs including execution instructions, and the execution instructions can be read and executed by an electronic device (including but not limited to a computer, a server, or a network device, etc.) to execute the steps of any of the above-mentioned close-range radio frequency electromagnetic field immunity test methods of the present application.

[0130] In some embodiments, the embodiments of the present application also provide a computer program product, which includes a computer program stored on a non-volatile computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the steps of any one of the above-mentioned close-range radio frequency electromagnetic field immunity test methods.

[0131] In some embodiments, an embodiment of the present application also provides an electronic device, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the close-range radio frequency electromagnetic field immunity testing method.

[0132] Figure 7 is a schematic diagram of the hardware structure of an electronic device for performing a close-range radio frequency electromagnetic field immunity test method provided by another embodiment of the present application, such as Figure 7 As shown, the device includes:

[0133] One or more processors 710 and memory 720, Figure 7 A processor 710 is taken as an example.

[0134] The device for performing the short-range radio frequency electromagnetic field immunity test method may further include: an input device 730 and an output device 740 .

[0135] The processor 710, the memory 720, the input device 730 and the output device 740 may be connected via a bus or other means. Figure 7 The example of connecting through bus is taken in the following.

[0136] The memory 720, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules corresponding to the close-range radio frequency electromagnetic field immunity test method in the embodiment of the present application. The processor 710 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 720, that is, the close-range radio frequency electromagnetic field immunity test method of the above method embodiment is implemented.

[0137] The memory 720 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 720 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 720 may optionally include a memory remotely arranged relative to the processor 710, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0138] The input device 730 may receive input digital or character information and generate signals related to user settings and function control of the electronic device. The output device 740 may include a display device such as a display screen.

[0139] The one or more modules are stored in the memory 720, and when executed by the one or more processors 710, the close-range radio frequency electromagnetic field immunity testing method in any of the above method embodiments is executed.

[0140] The above-mentioned product can execute the method provided in the embodiment of the present application, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided in the embodiment of the present application.

[0141] The electronic devices of the embodiments of the present application exist in various forms, including but not limited to:

[0142] (1) Mobile communication equipment: This type of equipment is characterized by having mobile communication functions and its main purpose is to provide voice and data communications. This type of terminal includes: smart phones, multimedia phones, functional phones, and low-end phones.

[0143] (2) Ultra-mobile personal computer devices: These devices belong to the category of personal computers, have computing and processing functions, and generally also have mobile Internet access features. These terminals include: PDA, MID and UMPC devices, etc.

[0144] (3) Portable entertainment devices: These devices can display and play multimedia content. They include audio and video players, handheld game consoles, e-books, smart toys, and portable car navigation devices.

[0145] (4) Other onboard electronic devices with data interaction functions, such as on-board devices installed in vehicles.

[0146] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0147] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0148] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A close-range radio frequency electromagnetic field immunity test method, comprising: Based on a wide-band probe array and a dynamic spectrum analyzer, the near-field electromagnetic field distribution data and near-field spectrum power distribution data generated by the RF interference source on the surface of the device under test are collected; The wide-band probe array covers the device under test and is used to receive radio frequency signals corresponding to a frequency band of 1 GHz to 10 GHz at each probe position; Processing the near-field electromagnetic field distribution data based on the finite-difference time-domain method to obtain a corresponding near-field electromagnetic field distribution model; the boundary condition of the finite-difference time-domain method adopts an absorbing boundary condition; Calculate the interference intensity of the radio frequency interference source on the device under test according to the spectrum overlap between the near-field spectrum power distribution data and the working frequency band of the device under test, and calculate the target interference source power according to the interference intensity through a dynamic spectrum adaptation algorithm; The radio frequency interference source is regulated to generate a radio frequency interference source signal having the power of the target interference source; the digital modulation mode of the radio frequency interference source signal is switched according to a modulation switching time interval; The electromagnetic coupling coefficient of the device under test for the radio frequency interference source signal is monitored based on the electromagnetic field intensity distribution model, and an anti-interference test result for the device under test is generated according to the electromagnetic coupling coefficient.

2. The method according to claim 1, wherein: The wide-band probe array comprises a plurality of probe nodes; The method of collecting near-field electromagnetic field distribution data and near-field spectrum power distribution data formed by the radio frequency interference source on the surface of the device under test based on the wide-band probe array and the dynamic spectrum analyzer includes: Based on the electric field sensor and magnetic field sensor in each probe node, the electric field strength information and magnetic field strength information of the corresponding probe node position are sampled respectively to obtain the corresponding near-field electromagnetic field distribution data; The dynamic spectrum analyzer is used to scan each of the probe nodes one by one, and the signal power of each corresponding probe node position in different frequency bands is sampled to obtain corresponding near-field spectrum power distribution data.

3. The method according to claim 2, wherein: The wide-band probe array comprises a plurality of probe node matrices disposed at different surface areas of the device under test, each of the probe node matrices being hexagonal; Among them, the first distribution density of probe nodes in the first probe node matrix is ​​greater than the second distribution density of probe nodes in the second probe node matrix, the first probe node matrix is ​​arranged in the key module area of ​​the device under test, and the second probe node matrix is ​​arranged in the non-critical module area on the surface of the device under test; the key module area includes the antenna area, the processor area and the power supply area, and the non-critical module area includes the support structure area and the radiator area.

4. The method according to claim 1, wherein: The processing of the near-field electromagnetic field distribution data based on the finite-difference time-domain method to obtain a corresponding near-field electromagnetic field distribution model includes: Based on the near-field electromagnetic field distribution data, construct electric field components and magnetic field components for each surface area of ​​the device under test: In the formula, E n+1 represents the electric field component of the surface area at the n+1th time step in the simulation, E n represents the electric field component of the surface area at the nth time step, represents the dielectric constant of the surface area, σ represents the conductivity of the surface area; τ represents the time step in the simulation, which is used to update the changes of the electric and magnetic fields over time; is the magnetic field curl at the nth time step, H n+1 represents the magnetic field component of the surface area at the n+1th time step, H n is the magnetic field component of the surface area at the nth time step, μ is the magnetic permeability of the surface area, is the electric field curl at the n+1th time step; A near-field electromagnetic field distribution model is generated based on the constructed electric field components and magnetic field components of each surface area.

5. The method according to claim 1, wherein: The step of calculating the interference intensity of the radio frequency interference source on the device under test according to the spectrum overlap between the near-field spectrum power distribution data and the working frequency band of the device under test, and calculating the target interference source power according to the interference intensity by a dynamic spectrum adaptation algorithm includes: Calculate the total spectral overlap: Where P i (f) is the near-field spectrum power distribution data, indicating the frequency f of the RF interference source in the i-th interference frequency band i Power distribution under; W and D i Respectively represent the working frequency band of the device under test and the i-th interference frequency band of the RF interference source, O(W,D i ) indicates W and D i The overlap degree, N is the total number of interference frequency bands; w i is the weight coefficient for each interference frequency band, reflecting the sensitivity of the device under test to different interference frequency bands; weighted Represents the weighted total spectrum overlap; Calculate the total interference intensity of the radio frequency interference source to the device under test based on the total spectrum overlap: In the formula, I interference represents the weighted total interference strength, α i represents the environmental impact adjustment coefficient for the i-th interference frequency band, which is used to describe the degree to which the interference source signal of the i-th interference frequency band is affected by the environment; P avg,i represents the average near-field power of the RF interference source in the overlapping frequency band, where the overlapping frequency band is the overlapping part between the i-th interference frequency band and the working frequency band of the device under test; The target interference source power is calculated according to the total interference intensity by a dynamic spectrum adaptation algorithm: P target =I interference ·b, Where P target represents the target interference source power, and β represents the power adjustment coefficient.

6. The method according to claim 5, wherein: α i It is calculated by the following formula: Where S0 is the reference power density of the RF interference source, S(d,i) is the power density of the interference source signal in the i-th interference frequency band when the distance is d meters, and λ i is the signal wavelength of the interference source signal in the i-th interference frequency band, L ref,i is the reflection path length of the interference source signal in the i-th interference frequency band in the test environment, G ref,i is the number of reflections of the interference source signal of the ith interference frequency band in the test environment, γ(i) is the reflection loss coefficient of the interference source signal of the ith interference frequency band, η(i) is the near-field interference coefficient of the ith interference frequency band, P near,i is the near-field power value of the interference source signal in the i-th interference frequency band, P total,i is the total transmission power of the interference source signal of the RF interference source for the i-th interference frequency band.

7. The method according to claim 1, wherein: The modulation switching time interval is dynamically updated by the following formula: In the formula, ΔT m (T+1) represents the duration of the T+1th modulation switching time interval, ΔT m (T) represents the duration of the Tth modulation switching time interval, P(T) represents the interference source signal power received by the device under test in the Tth modulation switching time interval, Indicates the rate of decrease of signal power during the Tth modulation switching time interval.

8. The method according to claim 4, wherein: The monitoring of the electromagnetic coupling coefficient of the device under test for the radio frequency interference source signal based on the electromagnetic field intensity distribution model includes: Where K(t) is the electromagnetic coupling coefficient at the tth time step, which indicates the electromagnetic field coupling strength between the device under test and the RF interference source; Ω is the integration area, which indicates the sampling area of ​​the surface of the device under test covered by the wide-band probe array; is the electric field gradient at the tth time step, which represents the rate of change of the electric field E(t) in the surface area with the position of the sampling point in the electromagnetic field intensity distribution model; and are the spatial partial derivatives of the electric field, representing the rate of change of the electric field E(t) in the x, y, and z directions of space respectively; is the magnetic field gradient at the tth time step, which represents the rate of change of the magnetic field H(t) in the surface area with the position of the sampling point in the electromagnetic field intensity distribution model; and are the spatial partial derivatives of the magnetic field, representing the rate of change of the magnetic field H(t) in the x, y, and z directions of space, respectively.

9. The method according to claim 8, wherein: The step of generating an anti-interference test result for the device under test according to the electromagnetic coupling coefficient includes: Draw the immunity curve according to the electromagnetic coupling coefficient at each time step; A maximum coupling coefficient, an average coupling coefficient and a standard deviation of the coupling coefficient are extracted from the immunity curve to determine an immunity test result for the device under test.

10. A short-range radio frequency electromagnetic field immunity test device, comprising: A data acquisition unit, for collecting near-field electromagnetic field distribution data and near-field spectrum power distribution data formed by a radio frequency interference source on the surface of the device under test based on a wide-band probe array and a dynamic spectrum analyzer; the wide-band probe array covers the device under test and is used to receive radio frequency signals corresponding to a frequency band of 1 GHz to 10 GHz at each probe position; An electromagnetic field modeling unit, used for processing the near-field electromagnetic field distribution data based on a finite-difference time-domain method to obtain a corresponding near-field electromagnetic field distribution model; the boundary condition of the finite-difference time-domain method adopts an absorbing boundary condition; An interference power calculation unit, used to calculate the interference intensity of the radio frequency interference source on the device under test according to the spectrum overlap between the near-field spectrum power distribution data and the working frequency band of the device under test, and calculate the target interference source power according to the interference intensity and the spectrum overlap through a dynamic spectrum adaptation algorithm; An interference source signal control unit, used for controlling the radio frequency interference source to generate a radio frequency interference source signal having the target interference source power; the digital modulation mode of the radio frequency interference source signal is switched according to a modulation switching time interval; The anti-interference test unit is used to monitor the electromagnetic coupling coefficient of the device under test for the radio frequency interference source signal based on the electromagnetic field intensity distribution model, and generate an anti-interference test result for the device under test according to the electromagnetic coupling coefficient.

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