Electronic countermeasure digital twinning system and method

Abstract

The invention relates to the technical field of digital twinning, and particularly discloses an electronic countermeasure digital twinning system and method, and the method comprises the following steps: 1, respectively detecting an equipment body and an equipment twinning body, and obtaining a simulation deviation coefficient; 2, based on the simulation deviation coefficient, evaluating whether the digital twin model is qualified, and generating a model evaluation signal; 3, based on the disqualification signal, analyzing the external environment change condition, judging whether the disqualification of the digital twin model is related to the external environment change or not, and generating a relevance evaluation signal; 4, calibrating the real-time simulation environment value based on the correlated signal; according to the method, the accuracy of the digital twinborn model is effectively evaluated, a targeted optimization strategy is provided by deeply analyzing disqualification reasons, the application efficiency of the model in a complex environment is improved, and powerful technical support is provided for industrial intelligent transformation.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and in particular to an electronic countermeasure digital twin system and method. Background Art

[0002] Digital twins make full use of data such as physical models, sensors, and operation history, integrate multi-disciplinary, multi-physical, multi-scale, and multi-probability simulation processes, and complete mapping in virtual space to reflect the entire life cycle of the corresponding physical equipment. Digital twins are a concept that transcends reality and can be viewed as a digital mapping system of one or more important, interdependent equipment systems.

[0003] However, in the existing technology, when evaluating whether the digital twin model is qualified, it is not possible to comprehensively evaluate the complexity and uncertainty of environmental changes through a multi-dimensional combined evaluation method, which leads to inaccurate evaluation results, is not conducive to the subsequent calibration of the digital twin model, and reduces the reliability and practicality of the digital twin model. Summary of the invention

[0004] The purpose of the present invention is to provide an electronic countermeasure digital twin system and method to solve the technical problems in the above background.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] In a first aspect, the present invention provides an electronic countermeasure digital twin method, comprising the following steps:

[0007] Step 1: Test the device body and the device twin respectively to obtain the simulation deviation coefficient;

[0008] Step 2: Based on the simulation deviation coefficient, evaluate whether the digital twin model is qualified and generate a model evaluation signal;

[0009] The model evaluation signals include: qualified signals and unqualified signals;

[0010] Step 3: Based on the unqualified signal, analyze the changes in the external environment, determine whether the failure of the digital twin model is related to the changes in the external environment, and generate a correlation evaluation signal;

[0011] The correlation evaluation signal includes: a correlation signal and an uncorrelated signal;

[0012] Step 4: Calibrate the real-time simulated environment value based on the relevant signal.

[0013] As a further solution of the present invention: the process of obtaining the simulation deviation coefficient is:

[0014] A target period is preset, and the target period includes multiple detection cycles, and the external environment of the device body is detected, and the body environment coefficient of each detection cycle is obtained respectively;

[0015] At the same time, the simulated environment of the equipment twin is tested to obtain the twin environment coefficients of each test cycle;

[0016] By formula: The simulation deviation coefficient FP is calculated, where i is the i-th detection cycle in the target period, N is the total number of detection cycles in the target period, and the value of N is 1, 2, 3, ..., N, BX i is the body environmental coefficient of the ith detection cycle, LX i is the twin environment coefficient of the i-th detection cycle.

[0017] As a further solution of the present invention: the process of obtaining the body environmental coefficient is:

[0018] Based on any detection cycle, the external environment of the device body is detected in real time to obtain the real-time external environment value, and based on the real-time external environment value within the detection cycle, the external environment mean value and the external environment fluctuation value of the detection cycle are calculated respectively;

[0019] The external environment mean and the external environment fluctuation value are multiplied to obtain the entity environment coefficient.

[0020] As a further solution of the present invention: the process of obtaining the external environment fluctuation value is:

[0021] Based on a two-dimensional coordinate system with time as the X-axis and the real-time external environment value as the Y-axis, a curve is drawn to obtain a real-time external environment curve;

[0022] The length of the real-time external environment curve within the detection period is extracted to obtain the external environment fluctuation characterization value, and then the external environment fluctuation characterization value is calculated by ratio with the environmental fluctuation characterization threshold to obtain the external environment fluctuation value.

[0023] As a further solution of the present invention: the process of obtaining the twin environment coefficient is:

[0024] Based on any detection cycle, the simulated environment of the device twin is detected in real time to obtain the real-time simulated environment value, and based on the real-time simulated environment value within the detection cycle, the simulated environment mean value and simulated environment fluctuation value of the detection cycle are calculated respectively;

[0025] The twin environment coefficient is obtained by multiplying the simulated environment mean and the simulated environment fluctuation value.

[0026] As a further solution of the present invention: the process of obtaining the simulated environmental fluctuation value is:

[0027] Based on a two-dimensional coordinate system with time as the X-axis and the real-time simulation environment value as the Y-axis, a curve is drawn to obtain a real-time simulation environment curve;

[0028] The length of the real-time simulated environment curve within the detection period is extracted to obtain a simulated environment fluctuation characterization value, and then the simulated environment fluctuation characterization value is calculated by ratio with the environment fluctuation characterization threshold to obtain a simulated environment fluctuation value.

[0029] As a further solution of the present invention: the process of generating the model evaluation signal is:

[0030] Preset a simulation deviation coefficient threshold, and compare and analyze the simulation deviation coefficient with the simulation deviation coefficient threshold;

[0031] If the simulation deviation coefficient is less than or equal to the simulation deviation coefficient threshold, a qualified signal is generated;

[0032] If the simulation deviation coefficient is greater than the simulation deviation coefficient threshold, a failure signal is generated.

[0033] As a further solution of the present invention: the process of generating the relevance evaluation signal is:

[0034] Based on the main environmental coefficient and the twin environmental coefficient of any two adjacent detection cycles within the target period, the external environmental variation coefficient and the simulated environmental variation coefficient are obtained respectively;

[0035] The simulated environment change coefficient and the external environment change coefficient are calculated to obtain the simulated environment change difference, and then the simulated environment change difference and the external environment change coefficient are calculated to obtain the correlation representation value;

[0036] The variance of the correlation representation values ​​of all adjacent detection cycles in the target period is calculated to obtain the correlation coefficient;

[0037] Preset a correlation coefficient threshold, and compare and analyze the correlation coefficient with the correlation coefficient threshold;

[0038] If the correlation coefficient is ≤ the correlation coefficient threshold, a correlation signal is generated;

[0039] If the correlation coefficient is greater than the correlation coefficient threshold, a no-correlation signal is generated.

[0040] As a further solution of the present invention: the process of calibrating the real-time simulated environment value is:

[0041] Based on the associated signal, the current external environment change coefficient is obtained, and the current external environment change coefficient is multiplied by the associated representation mean value to obtain the twin environment coefficient calibration value;

[0042] By formula: Calculate the real-time simulation environment calibration value SJ, LJ is the twin environment coefficient calibration value, WB is the current external environment change coefficient, and SH is the real-time simulation environment value;

[0043] The real-time simulated environment calibration value is applied to the real-time simulated environment value of the next detection cycle.

[0044] In a second aspect, the present invention provides an electronic countermeasure digital twin system, the system comprising:

[0045] Data acquisition module: detect the device body and the device twin respectively to obtain the simulation deviation coefficient;

[0046] Model evaluation module: Based on the simulation deviation coefficient, it evaluates whether the digital twin model is qualified and generates a model evaluation signal;

[0047] The model evaluation signals include: qualified signals and unqualified signals;

[0048] Relevance evaluation module: Based on the unqualified signal, analyze the changes in the external environment, determine whether the failure of the digital twin model is related to the changes in the external environment, and generate a relevance evaluation signal;

[0049] The correlation evaluation signal includes: a correlation signal and an uncorrelated signal;

[0050] Calibration module: Calibrate the real-time simulated environment value based on the relevant signal.

[0051] Beneficial effects of the present invention:

[0052] (1) The present invention realizes an in-depth analysis of the similarity and consistency between the device body and the twin body by capturing the dynamic changes of key environmental parameters in real time; in each detection cycle, not only the environmental mean is calculated to reflect the overall trend, but also the concept of environmental fluctuation value is introduced. By measuring the curve length of the real-time environmental value in the two-dimensional coordinate system and comparing it with the preset characterization threshold, the complexity and uncertainty of environmental changes are comprehensively evaluated through a two-dimensional combined evaluation method; the present invention not only improves the accuracy of the digital twin model through a real-time and sophisticated evaluation mechanism, but also provides strong support for the continuous optimization of the model, and has broad application prospects and important practical value;

[0053] (2) The present invention compares the changes in the environmental coefficients of the device body and the twin body in adjacent detection cycles, calculates the response difference between the two to the changes in the external environment, and uses this difference to evaluate the correlation between model failure and external environmental changes, generating a correlation evaluation signal, which not only helps to identify the possible causes of model failure, but also provides a direction for subsequent optimization; for cases with significant correlation, that is, model failure is mainly caused by external environmental changes, real-time simulation environment calibration measures are taken, and the real-time simulation environment calibration value is calculated by combining the current external environmental change coefficient and past correlation characteristics, and the real-time simulation environment output of the digital twin model is adjusted accordingly, thereby ensuring that the model can quickly adapt and maintain accuracy when facing external environmental changes, thereby improving the reliability and practicality of the model;

[0054] (3) The present invention not only realizes the effective evaluation of the accuracy of the digital twin model, but also proposes targeted optimization strategies through in-depth analysis of the reasons for failure, which not only helps to improve the application efficiency of the model in complex environments, but also provides strong technical support for the transformation of industrial intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The present invention will be further described below in conjunction with the accompanying drawings.

[0056] Figure 1 It is a flowchart of the present invention;

[0057] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Embodiment 1:

[0060] See also Figure 1 As shown, an electronic countermeasure digital twin method described in an embodiment of the present invention includes the following steps:

[0061] Step 1: Test the device body and the device twin respectively to obtain the simulation deviation coefficient;

[0062] In some implementation schemes, a target period is preset, and the target period includes a plurality of detection cycles, and the external environment of the device body is detected, and the body environment coefficient of each detection cycle is obtained respectively;

[0063] It should be explained that the number of target time periods including detection cycles can be 10 or 30; the duration of the detection cycle can be 1 minute or 5 minutes;

[0064] It is also necessary to explain that the external environment includes but is not limited to: the temperature of the environment in which the device body is located, the wind speed of the environment in which the device body is located;

[0065] At the same time, the simulated environment of the equipment twin is tested to obtain the twin environment coefficients of each test cycle;

[0066] It should be explained that the simulated environment includes, but is not limited to: the temperature of the environment in which the device twin is located, the wind speed of the environment in which the device twin is located;

[0067] It should be noted that when analyzing the external environment and the simulated environment, the same environment needs to be analyzed; for example, the temperature of the environment should be analyzed;

[0068] By formula: The simulation deviation coefficient FP is calculated, where i is the i-th detection cycle in the target period, N is the total number of detection cycles in the target period, and the value of N is 1, 2, 3, ..., N, BX i is the body environmental coefficient of the ith detection cycle, LX i is the twin environment coefficient of the i-th detection cycle;

[0069] First, specifically, the process of obtaining the body environment coefficient is:

[0070] Based on any detection cycle, the external environment of the device body is detected in real time to obtain the real-time external environment value, and based on the real-time external environment value within the detection cycle, the external environment mean value of the detection cycle (the external environment mean value is the average value of the real-time external environment values ​​of the detection cycle) and the external environment fluctuation value are calculated respectively;

[0071] The external environment mean value and the external environment fluctuation value are multiplied to obtain the main body environment coefficient;

[0072] Furthermore, the process of obtaining the external environment fluctuation value is as follows:

[0073] Based on a two-dimensional coordinate system with time as the X-axis and the real-time external environment value as the Y-axis, a curve is drawn to obtain a real-time external environment curve;

[0074] Extract the length of the real-time external environment curve within the detection period to obtain the external environment fluctuation characterization value, and then calculate the ratio of the external environment fluctuation characterization value to the environmental fluctuation characterization threshold to obtain the external environment fluctuation value;

[0075] It should be explained that the environmental fluctuation characterization threshold represents the length of the detection period on the X-axis in the two-dimensional coordinate system;

[0076] Second, specifically, the process of obtaining the twin environment coefficient is:

[0077] Based on any detection cycle, the simulated environment of the device twin is detected in real time to obtain the real-time simulated environment value, and based on the real-time simulated environment value within the detection cycle, the simulated environment mean value of the detection cycle (the simulated environment mean value is the average value of the real-time simulated environment value of the detection cycle) and the simulated environment fluctuation value are calculated respectively;

[0078] The twin environment coefficient is obtained by multiplying the simulated environment mean and the simulated environment fluctuation value;

[0079] Furthermore, the process of obtaining the simulated environmental fluctuation value is as follows:

[0080] Based on a two-dimensional coordinate system with time as the X-axis and the real-time simulation environment value as the Y-axis, a curve is drawn to obtain a real-time simulation environment curve;

[0081] The length of the real-time simulated environment curve within the detection period is extracted to obtain a simulated environment fluctuation characterization value, and then the simulated environment fluctuation characterization value is calculated by ratio with the environment fluctuation characterization threshold to obtain a simulated environment fluctuation value;

[0082] Step 2: Based on the simulation deviation coefficient, evaluate whether the digital twin model is qualified and generate a model evaluation signal;

[0083] The model evaluation signals include: qualified signals and unqualified signals;

[0084] In some implementation schemes, a simulation deviation coefficient threshold is preset, and the simulation deviation coefficient is compared and analyzed with the simulation deviation coefficient threshold;

[0085] If the simulation deviation coefficient is ≤ the simulation deviation coefficient threshold, it means that the simulated environment of the device twin and the external environment of the actual device body have high similarity and consistency within the target period, that is, the digital twin model can more accurately reflect the actual conditions of the environment in which the device body is located when simulating the operation of the device, that is, generate a qualified signal;

[0086] If the simulation deviation coefficient is greater than the simulation deviation coefficient threshold, it means that there is a large deviation between the simulated environment of the device twin and the external environment of the actual device body, and the accuracy and reliability of the digital twin model in the simulation of device operation may be affected, that is, an unqualified signal is generated;

[0087] The technical solution of the embodiment of the present invention is mainly as follows: by capturing the dynamic changes of the key environmental parameters of the device body and the twin in real time, an in-depth analysis of the similarity and consistency between the two is achieved; in each detection cycle, not only the environmental mean is calculated to reflect the overall trend, but also the concept of environmental fluctuation value is introduced, by measuring the curve length of the real-time environmental value in the two-dimensional coordinate system, and comparing it with the preset characterization threshold, so as to comprehensively evaluate the complexity and uncertainty of environmental changes through a two-dimensional combined evaluation method; the embodiment of the present invention not only improves the accuracy of the digital twin model through a real-time and sophisticated evaluation mechanism, but also provides strong support for the continuous optimization of the model, and has broad application prospects and important practical value.

[0088] Embodiment 2:

[0089] Based on Example 1, please refer to Figure 1 As shown, an electronic countermeasure digital twin method described in an embodiment of the present invention further includes the following steps:

[0090] Step 3: Based on the unqualified signal, analyze the changes in the external environment, determine whether the failure of the digital twin model is related to the changes in the external environment, and generate a correlation evaluation signal;

[0091] The correlation evaluation signal includes: a correlation signal and an uncorrelated signal;

[0092] In some implementation schemes, based on the body environment coefficient and the twin environment coefficient of any two adjacent detection periods within the target time period, the external environment change coefficient and the simulated environment change coefficient are obtained respectively;

[0093] It should be explained that the external environment variation coefficient is the difference between the body environment coefficient of the post-detection period and the body environment coefficient of the detection period, and the simulation environment variation coefficient is the difference between the twin environment coefficient of the post-detection period and the twin environment coefficient of the detection period;

[0094] The latter detection cycle is the detection cycle that is later in time sequence among two adjacent detection cycles, and the former detection cycle is the detection cycle that is earlier in time sequence among two adjacent detection cycles;

[0095] The simulated environment change coefficient and the external environment change coefficient are calculated to obtain the simulated environment change difference, and then the simulated environment change difference and the external environment change coefficient are calculated to obtain the correlation representation value;

[0096] The variance of the correlation representation values ​​of all adjacent detection cycles in the target period is calculated to obtain the correlation coefficient;

[0097] Preset a correlation coefficient threshold, and compare and analyze the correlation coefficient with the correlation coefficient threshold;

[0098] If the correlation coefficient is ≤ the correlation coefficient threshold, it means that the correlation between the failure of the digital twin model and the change of the external environment is relatively large, that is, a correlation signal is generated;

[0099] If the correlation coefficient is greater than the correlation coefficient threshold, it means that the correlation between the failure of the digital twin model and the change of the external environment is small, that is, an uncorrelated signal is generated;

[0100] Step 4: Calibrate the real-time simulated environment value based on the associated signal;

[0101] In some implementation schemes, based on the associated signal, the current external environment change coefficient is obtained, and the current external environment change coefficient is multiplied by the associated representation mean value to obtain the twin environment coefficient calibration value;

[0102] By formula: Calculate the real-time simulation environment calibration value SJ, where LJ is the twin environment coefficient calibration value, WB is the current external environment change coefficient, and SH is the real-time simulation environment value (the real-time simulation environment value here is the real-time simulation environment value obtained by the digital twin model in the next detection cycle);

[0103] Apply the real-time simulation environment calibration value to the real-time simulation environment value of the next detection cycle to calibrate the output of the digital twin model, thereby ensuring that the digital twin model can maintain accuracy and reliability when the external environment changes;

[0104] The technical solution of the embodiment of the present invention is mainly as follows: by comparing the changes in the environmental coefficients of the equipment body and the twin in adjacent detection cycles, the response difference between the two to the changes in the external environment is calculated, and this difference is used to evaluate the correlation between model failure and external environmental changes, and a correlation evaluation signal is generated, which not only helps to identify the possible causes of model failure, but also provides a direction for subsequent optimization; for situations where the correlation is significant, that is, the model failure is mainly caused by changes in the external environment, real-time simulation environment calibration measures are taken, and the real-time simulation environment calibration value is calculated by combining the current external environment change coefficient and past correlation characteristics, and the real-time simulation environment output of the digital twin model is adjusted accordingly, thereby ensuring that the model can quickly adapt and maintain accuracy when facing external environmental changes, thereby improving the reliability and practicality of the model.

[0105] Embodiment 3:

[0106] Based on Example 1 and Example 2, please refer to Figure 2 As shown, an electronic countermeasure digital twin system according to an embodiment of the present invention includes:

[0107] Data acquisition module: detect the device body and the device twin respectively to obtain the simulation deviation coefficient;

[0108] Model evaluation module: Based on the simulation deviation coefficient, it evaluates whether the digital twin model is qualified and generates a model evaluation signal;

[0109] The model evaluation signals include: qualified signals and unqualified signals;

[0110] Relevance evaluation module: Based on the unqualified signal, analyze the changes in the external environment, determine whether the failure of the digital twin model is related to the changes in the external environment, and generate a relevance evaluation signal;

[0111] The correlation evaluation signal includes: a correlation signal and an uncorrelated signal;

[0112] Calibration module: Calibrate the real-time simulated environment value based on the relevant signal.

[0113] The above thresholds are set for the convenience of comparison. The thresholds depend on the amount of sample data and the number of bases set by technicians in this field for each set of sample data.

[0114] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An electronic countermeasure digital twin method, characterized in that: The following steps are involved: Step 1: Test the device body and the device twin respectively to obtain the simulation deviation coefficient; Step 2: Based on the simulation deviation coefficient, evaluate whether the digital twin model is qualified and generate a model evaluation signal; The model evaluation signals include: qualified signals and unqualified signals; Step 3: Based on the unqualified signal, analyze the changes in the external environment, determine whether the failure of the digital twin model is related to the changes in the external environment, and generate a correlation evaluation signal; The correlation evaluation signal includes: a correlation signal and an uncorrelated signal; Step 4: Calibrate the real-time simulated environment value based on the relevant signal.

2. The electronic countermeasure digital twin method according to claim 1, characterized in that: The process of obtaining the simulation deviation coefficient is: A target period is preset, and the target period includes multiple detection cycles, and the external environment of the device body is detected, and the body environment coefficient of each detection cycle is obtained respectively; At the same time, the simulated environment of the equipment twin is tested to obtain the twin environment coefficients of each test cycle; By formula: The simulation deviation coefficient FP is calculated, where i is the i-th detection cycle in the target period, N is the total number of detection cycles in the target period, and the value of N is 1, 2, 3, ..., N, BX i is the body environmental coefficient of the ith detection cycle, LX i is the twin environment coefficient of the i-th detection cycle.

3. The electronic countermeasure digital twin method according to claim 2, characterized in that: The process of obtaining the body environmental coefficient is as follows: Based on any detection cycle, the external environment of the device body is detected in real time to obtain the real-time external environment value, and based on the real-time external environment value within the detection cycle, the external environment mean value and the external environment fluctuation value of the detection cycle are calculated respectively; The external environment mean and the external environment fluctuation value are multiplied to obtain the entity environment coefficient.

4. The electronic countermeasure digital twin method according to claim 3, characterized in that: The process of obtaining the external environment fluctuation value is as follows: Based on a two-dimensional coordinate system with time as the X-axis and the real-time external environment value as the Y-axis, a curve is drawn to obtain a real-time external environment curve; The length of the real-time external environment curve within the detection period is extracted to obtain the external environment fluctuation characterization value, and then the external environment fluctuation characterization value is calculated by ratio with the environmental fluctuation characterization threshold to obtain the external environment fluctuation value.

5. The electronic countermeasure digital twin method according to claim 2, characterized in that: The process of obtaining the twin environmental coefficient is: Based on any detection cycle, the simulated environment of the device twin is detected in real time to obtain the real-time simulated environment value, and based on the real-time simulated environment value within the detection cycle, the simulated environment mean value and simulated environment fluctuation value of the detection cycle are calculated respectively; The twin environment coefficient is obtained by multiplying the simulated environment mean and the simulated environment fluctuation value.

6. The electronic countermeasure digital twin method according to claim 5, characterized in that: The process of obtaining the simulated environmental fluctuation value is as follows: Based on a two-dimensional coordinate system with time as the X-axis and the real-time simulation environment value as the Y-axis, a curve is drawn to obtain a real-time simulation environment curve; The length of the real-time simulated environment curve within the detection period is extracted to obtain a simulated environment fluctuation characterization value, and then the simulated environment fluctuation characterization value is calculated by ratio with the environment fluctuation characterization threshold to obtain a simulated environment fluctuation value.

7. The electronic countermeasure digital twin method according to claim 1, characterized in that: The process of generating the model evaluation signal is: Preset a simulation deviation coefficient threshold, and compare and analyze the simulation deviation coefficient with the simulation deviation coefficient threshold; If the simulation deviation coefficient is less than or equal to the simulation deviation coefficient threshold, a qualified signal is generated; If the simulation deviation coefficient is greater than the simulation deviation coefficient threshold, a failure signal is generated.

8. The electronic countermeasure digital twin method according to claim 1, characterized in that: The process of generating the relevance evaluation signal is: Based on the main environmental coefficient and the twin environmental coefficient of any two adjacent detection cycles within the target period, the external environmental variation coefficient and the simulated environmental variation coefficient are obtained respectively; The simulated environment change coefficient and the external environment change coefficient are calculated to obtain the simulated environment change difference, and then the simulated environment change difference and the external environment change coefficient are calculated to obtain the correlation representation value; The variance of the correlation representation values ​​of all adjacent detection cycles in the target period is calculated to obtain the correlation coefficient; Preset a correlation coefficient threshold, and compare and analyze the correlation coefficient with the correlation coefficient threshold; If the correlation coefficient is ≤ the correlation coefficient threshold, a correlation signal is generated; If the correlation coefficient is greater than the correlation coefficient threshold, a no-correlation signal is generated.

9. The electronic countermeasure digital twin method according to claim 1, characterized in that: The process of calibrating the real-time simulated environment value is: Based on the associated signal, the current external environment change coefficient is obtained, and the current external environment change coefficient is multiplied by the associated representation mean value to obtain the twin environment coefficient calibration value; By formula: Calculate the real-time simulation environment calibration value SJ, where LJ is the twin environment coefficient calibration value, WB is the current external environment change coefficient, and SH is the real-time simulation environment value; The real-time simulated environment calibration value is applied to the real-time simulated environment value of the next detection cycle.

10. An electronic countermeasure digital twin system, characterized in that: The system is used to execute the method described in any one of claims 1 to 9, and the system comprises: Data acquisition module: detect the device body and the device twin respectively to obtain the simulation deviation coefficient; Model evaluation module: Based on the simulation deviation coefficient, it evaluates whether the digital twin model is qualified and generates a model evaluation signal; The model evaluation signals include: qualified signals and unqualified signals; Relevance evaluation module: Based on the unqualified signal, analyze the changes in the external environment, determine whether the failure of the digital twin model is related to the changes in the external environment, and generate a relevance evaluation signal; The correlation evaluation signal includes: a correlation signal and an uncorrelated signal; Calibration module: Calibrate the real-time simulated environment value based on the relevant signal.

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