Magnetic field difference calibration optimization method and device based on disturbance displacement, equipment and medium

Abstract

The invention discloses a magnetic field difference calibration optimization method and device based on disturbance displacement, equipment and a medium, and relates to the field of electron cyclotron radiometer calibration, and the method comprises the steps: obtaining analog electron temperature radial distribution under different annular magnetic field intensities through a physical simulation program; constructing a disturbance displacement probability distribution function based on the plasma displacement control precision of the target magnetic confinement fusion device; aiming at each magnetic field pair and each displacement condition, based on an analog electronic temperature radial distribution function, carrying out calibration reduction and evaluating calibration accuracy, and obtaining a calibration accuracy distribution function of each magnetic field pair; integrating the calibration accuracy distribution function and the disturbance displacement probability distribution function of each magnetic field pair in a displacement space to obtain the final calibration accuracy of each magnetic field pair; and the magnetic field pair with the maximum final calibration accuracy in the plurality of magnetic field pairs is used as a recommended calibration parameter of the target magnetic confinement fusion device, and the method improves the calibration accuracy by fusing the disturbance displacement.

Description

Technical Field

[0001] This invention relates to the field of electronic cyclotron radiometer calibration, specifically to a method, apparatus, equipment, and medium for optimizing magnetic field difference calibration based on perturbation displacement. Background Technology

[0002] In magnetic confinement fusion research, precise diagnosis of plasma core parameters is fundamental to understanding physical processes and optimizing device performance. Among these, the spatial distribution of electron temperature is a key physical quantity characterizing the plasma thermodynamic state and studying energy confinement and transport mechanisms. Electron cyclotron emission (ECE) diagnostic technology, with its non-invasive nature and high spatiotemporal resolution, has become the mainstream method for obtaining electron temperature profiles in magnetic confinement fusion devices such as tokamas. This technology detects the characteristic radiation emitted by electrons in the plasma under the influence of a confinement magnetic field and, based on the theoretical relationship between radiation intensity and electron temperature, inversely derives the radial distribution of electron temperature.

[0003] To establish a quantitative correspondence between ECE measurement signals and electron temperatures, precise amplitude calibration of the diagnostic system is essential. Traditionally, in-situ absolute calibration using blackbody radiation sources is commonly employed. However, this method faces bottlenecks when applied to future fusion reactors, including radiation damage, engineering complexity, vacuum contamination, and difficulty in quantifying calibration errors, ultimately affecting the accuracy of electron temperature diagnostic results.

[0004] In contrast, the magnetic field difference calibration method offers a simpler and more reliable alternative. This method does not rely on a blackbody source; it only requires maintaining the same plasma configuration, current, and electron density during the discharge peak phase while applying slightly different circumferential magnetic field conditions to obtain the relative calibration coefficients of the electron cyclotron radiometer. Compared to the blackbody in-situ calibration method, the magnetic field difference calibration method has significant advantages: its calibration process is simpler and completely avoids the risk of calibration failure in deuterium-tritium radiation environments. However, this method assumes that the temperature distribution remains constant under different magnetic fields and does not fully consider actual plasma displacement control errors, which limits the calibration accuracy in practical applications. Summary of the Invention

[0005] The technical problem to be solved by the present invention is that the existing magnetic field difference calibration method is not accurate enough. The purpose is to provide an optimized method, device, equipment and medium for magnetic field difference calibration based on perturbation displacement, thereby solving the above-mentioned problem.

[0006] This invention is achieved through the following technical solution:

[0007] In a first aspect, the present invention provides a magnetic field difference calibration optimization method based on perturbation displacement, comprising:

[0008] Using a physical simulation program, the radial distribution of simulated electron temperature under different circumferential magnetic field strengths was obtained, and the radial distribution function of simulated electron temperature was obtained by interpolation.

[0009] Based on the plasma displacement control accuracy of the target magnetic confinement fusion device, a perturbation displacement probability distribution function is constructed to characterize displacement uncertainty;

[0010] Within the preset range of circumferential magnetic field strength values, multiple magnetic field pairs to be evaluated are determined, and within the preset range of plasma disturbance displacement, multiple displacement conditions to be simulated are determined.

[0011] For each magnetic field pair and each displacement condition, the calibration coefficients corresponding to each channel are calculated using the magnetic field difference calibration method based on the simulated electron temperature radial distribution function.

[0012] Based on the calibration coefficients corresponding to each channel, the radial distribution of electron temperature is restored, and the calibration accuracy is evaluated. After traversing the multiple displacement conditions, the calibration accuracy distribution function of each magnetic field pair is obtained.

[0013] The calibration accuracy distribution function of each magnetic field pair is integrated with the disturbance displacement probability distribution function in displacement space to obtain the final calibration accuracy of each magnetic field pair.

[0014] The magnetic field pair with the highest final calibration accuracy among the multiple magnetic field pairs shall be used as the recommended calibration parameters for the target magnetic confinement fusion device.

[0015] Optionally, the target magnetic confinement fusion device is a tokamak device; the physical simulation program is the METIS program.

[0016] Optionally, the construction of the perturbation displacement probability distribution function based on the plasma displacement control accuracy of the target magnetic confinement fusion device includes:

[0017] Obtain the root mean square error values ​​of the displacement perturbation of the plasma in the horizontal and vertical directions of the target magnetic confinement fusion device;

[0018] Based on the root mean square error value, a Gaussian probability distribution function is constructed as the probability distribution function of the disturbance displacement.

[0019] Optionally, each magnetic field pair includes a first magnetic field strength and a second magnetic field strength; the calibration coefficients for each channel are calculated using the magnetic field difference calibration method based on the simulated electron temperature radial distribution function for each magnetic field pair and each displacement condition, including:

[0020] For each magnetic field pair and each displacement condition, perform the following operations:

[0021] Based on the simulated electron temperature radial distribution function, the first measurement position of each channel in the discharge of the first magnetic field strength and the second measurement position of each channel in the discharge of the second magnetic field strength are calculated respectively.

[0022] By combining the first measurement position, the second measurement position, the simulated electron temperature radial distribution function, and each displacement condition, the first simulated electron temperature value of each channel under the first magnetic field strength and the second simulated electron temperature value of each channel under the second magnetic field strength are determined.

[0023] The first signal intensity of each channel is randomly generated during the discharge of the first magnetic field strength;

[0024] Based on the first signal strength, the first simulated electron temperature value, and the second simulated electron temperature value, calculate the second signal strength measured in the discharge of the second magnetic field strength for each channel;

[0025] Substituting the first signal strength, the second signal strength, the first measurement position, and the second measurement position into the recursive formula of the magnetic field difference calibration method, we obtain the calibration coefficients corresponding to each channel.

[0026] Optionally, the step of restoring the radial distribution of electron temperature based on the calibration coefficients corresponding to each channel, evaluating the calibration accuracy, and obtaining the calibration accuracy distribution function for each magnetic field pair after traversing the multiple displacement conditions includes:

[0027] Based on the calibration coefficients corresponding to each channel, the first signal strength is calibrated to obtain the first electronic temperature value of each channel after calibration restoration, and the second signal strength is calibrated to obtain the second electronic temperature value of each channel after calibration restoration.

[0028] Based on the first electron temperature value, interpolation reconstruction is performed to obtain the radial distribution of the first electron temperature of each channel after calibration and restoration. Based on the second electron temperature value, interpolation reconstruction is performed to obtain the radial distribution of the second electron temperature of each channel after calibration and restoration.

[0029] Based on the first and second electron temperature radial distributions, the calibration accuracy of each magnetic field pair under each displacement condition is obtained.

[0030] After traversing the multiple displacement conditions, the calibration accuracy distribution function of each magnetic field pair is obtained by combining the calibration accuracy of each magnetic field pair under the multiple displacement conditions.

[0031] Optionally, obtaining the calibration accuracy of each magnetic field pair under each displacement condition based on the first and second electron temperature radial distributions includes:

[0032] After performing maximum value normalization and integral operation on the first and second radial distributions of electron temperature respectively, the first integral value of the first radial distribution of electron temperature and the second integral value of the second radial distribution of electron temperature are obtained.

[0033] Calculate the difference between the first integral value and the second integral value, and divide the absolute value of the difference by the first integral value to obtain the relative deviation value;

[0034] Subtracting the relative deviation value from 1 yields the calibration accuracy of each magnetic field pair under each displacement condition.

[0035] Optionally, the calibration accuracy distribution function for each magnetic field pair is integrated with the disturbance displacement probability distribution function in displacement space to obtain the final calibration accuracy for each magnetic field pair, including:

[0036] The calibration accuracy distribution function of each magnetic field pair at each displacement point is multiplied by the probability density value of the disturbance displacement probability distribution function at the same displacement point to obtain the weighted accuracy value of each displacement point.

[0037] Within the preset plasma displacement range, the weighted accuracy values ​​of all displacement points are subjected to double integration to obtain the final calibration accuracy of each magnetic field pair.

[0038] In a second aspect, the present invention provides a magnetic field difference calibration and optimization device based on perturbation displacement, comprising:

[0039] The simulation module is used to obtain the simulated radial distribution of electron temperature under different circumferential magnetic field strengths using a physical simulation program;

[0040] The function construction module is used to construct a perturbation displacement probability distribution function to characterize displacement uncertainty based on the plasma displacement control accuracy of the target magnetic confinement fusion device.

[0041] The determination module is used to determine multiple magnetic field pairs to be evaluated within a preset range of circumferential magnetic field strength values, and to determine multiple displacement conditions to be simulated within a preset range of plasma disturbance displacement.

[0042] The calibration module is used to calculate the calibration coefficients for each channel based on the simulated electron temperature radial distribution function, using the magnetic field difference calibration method, for each magnetic field pair and each displacement condition.

[0043] The evaluation module is used to reconstruct the radial distribution of electron temperature based on the calibration coefficients corresponding to each channel and evaluate the calibration accuracy. After traversing the multiple displacement conditions, it obtains the calibration accuracy distribution function of each magnetic field pair. The calibration accuracy distribution function of each magnetic field pair is integrated with the perturbation displacement probability distribution function in the displacement space to obtain the final calibration accuracy of each magnetic field pair.

[0044] The parameter selection module is used to select the magnetic field pair with the highest final calibration accuracy among the multiple magnetic field pairs as the recommended calibration parameters for the target magnetic confinement fusion device.

[0045] Thirdly, the present invention provides a computer device, the computer device including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the magnetic field difference calibration optimization method based on perturbation displacement as described in any one of the first aspects.

[0046] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, wherein a processor executes the computer program to implement the magnetic field difference calibration optimization method based on perturbation displacement as described in any one of the first aspects.

[0047] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0048] This application provides a magnetic field difference calibration optimization method based on perturbation displacement. This method directly obtains electron temperature distribution profiles under different circumferential magnetic field strengths by introducing a physical simulation program. This allows the optimization process of calibration parameters to be based on real and verifiable physical evolution data, overcoming the limitation of the traditional assumption of a constant electron temperature distribution, thereby improving the matching between calibration parameters and the actual operating conditions of the magnetic confinement fusion device. By constructing a perturbation displacement probability distribution function based on actual displacement control capability, and using this function to perform probability integration on the calibration accuracy under different displacements, errors caused by plasma displacement are dynamically corrected, further improving the matching between calibration parameters and the actual operating conditions of the magnetic confinement fusion device. Attached Figure Description

[0049] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0050] Figure 1 A flowchart illustrating the magnetic field difference calibration optimization method based on perturbation displacement provided in this application embodiment;

[0051] Figure 2 A schematic diagram of the radial distribution of electron temperature provided in an embodiment of this application;

[0052] Figure 3 A comparative analysis diagram showing the influence of plasma fixed large displacement on magnetic field difference calibration performance provided in the embodiments of this application;

[0053] Figure 4 This application provides a schematic diagram illustrating the distribution of the final calibration accuracy of multiple magnetic field pairs in its embodiments.

[0054] Figure 5 This is a schematic diagram of the structure of the magnetic field difference calibration and optimization device based on perturbation displacement provided in the embodiments of this application. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0056] Traditional blackbody in-situ calibration methods face multiple technical bottlenecks in practical applications, which severely restrict their measurement accuracy and reliability in complex plasma environments.

[0057] First, in the future deuterium-tritium fusion environment, high-energy radiation will lead to significant degradation of the blackbody source material's performance. This radiation damage will not only cause irreversible changes in the blackbody source's emissivity characteristics but may also trigger the malfunction of the entire diagnostic system. Second, from a system integration perspective, the installation of a blackbody source requires limited diagnostic port resources, and its complex mechanical structure and thermal management system pose significant challenges to the spatial layout within the device's vacuum chamber. More seriously, the introduction of a blackbody source may introduce vacuum impurities, which will not only affect the tokamak device's background vacuum but may also alter plasma boundary characteristics, thereby reducing the reliability of diagnostic data. Furthermore, from a metrological perspective, the blackbody calibration process involves multiple error sources, including but not limited to systematic deviations in antenna alignment, drift errors caused by thermo-mechanical deformation, and the non-ideal Gaussian distribution characteristics of the radiation beam. These factors are coupled with each other, making quantitative analysis and precise compensation of calibration errors extremely difficult, ultimately affecting the accuracy of electronic temperature diagnostic results.

[0058] Compared with the in-situ blackbody calibration method, the magnetic field difference calibration method has significant advantages: its calibration process is simpler and completely avoids the risk of calibration failure in deuterium-tritium radiation environments. However, this method assumes that the temperature distribution remains constant under different magnetic fields and does not fully consider the actual plasma displacement control error, which limits the calibration accuracy in practical applications.

[0059] Therefore, this application provides an optimization method for magnetic field difference calibration based on perturbation displacement. Please refer to... Figure 1 This is a schematic flowchart of a magnetic field difference calibration optimization method based on perturbation displacement provided in an embodiment of this application. The following is a description of... Figure 1 The magnetic field difference calibration optimization method based on perturbation displacement is introduced.

[0060] S1. Using a physical simulation program, obtain the simulated radial distribution of electron temperature under different circumferential magnetic field strengths, and obtain the simulated radial distribution function of electron temperature through interpolation.

[0061] In the specific implementation process, the typical operating parameters of the target magnetic confinement fusion device are first determined, including but not limited to plasma current, electron density profile, plasma shape (elongation ratio, triangular deformation, etc.), and heating power distribution. Then, at least two different circumferential magnetic field strengths (e.g., 1.5T, 1.8T, 2.1T) are selected. Under the condition of keeping other operating parameters strictly consistent, the integrated physical simulation program is called to perform simulation calculations, and the distribution data of electron temperature along the radial direction of the device corresponding to each magnetic field strength (i.e., electron temperature profile) is output.

[0062] To further improve the continuity and usability of the data, the electron temperature profile obtained under the discrete magnetic field obtained from the simulation can be interpolated to generate a radial distribution function of electron temperature that varies continuously along the magnetic field dimension. This provides a high-fidelity, dynamic physical input benchmark for subsequent calibration and optimization.

[0063] In one possible embodiment, the target magnetic confinement fusion device is a tokamak device, and the physical simulation program is the METIS simulation program, which is an integrated modeling code for tokamak plasma discharge evolution simulation and experimental prediction.

[0064] It should be noted that the scope of protection of this invention is not limited to the specific devices or programs described above. Besides tokamak devices, the target magnetic confinement fusion device can also be other magnetic confinement fusion devices requiring electron temperature diagnostics and calibration. In addition to the METIS simulation program, the physical simulation program can also be other simulation programs capable of achieving similar functions, as long as the program can output the radial distribution of electron temperature under different circumferential magnetic field strengths under given confinement conditions.

[0065] S2. Based on the plasma displacement control accuracy of the target magnetic confinement fusion device, a perturbation displacement probability distribution function is constructed to characterize the displacement uncertainty.

[0066] In one possible embodiment, the root mean square error values ​​of the displacement perturbation of the plasma in the horizontal and vertical directions of the target magnetic confinement fusion device are obtained; based on the root mean square error values, a Gaussian probability distribution function is constructed as the perturbation displacement probability distribution function.

[0067] In the specific implementation process, firstly, by statistically analyzing the historical discharge data of the target magnetic confinement fusion device, or based on the design performance indicators of its plasma configuration control system, the statistical characteristics of the deviation of the actual plasma position from the preset equilibrium position in the horizontal and vertical directions are extracted. This characteristic is typically quantified as the root mean square error value of the displacement perturbation. .

[0068] Subsequently, the root mean square error value As a core parameter, a two-dimensional joint probability density function describing displacement uncertainty is constructed. Assuming that the displacement disturbances in the two directions are independent and both follow a normal distribution, the constructed disturbance displacement probability distribution function is a two-dimensional Gaussian distribution function, expressed as follows:

[0069]

[0070] in, This represents the probability distribution function of the perturbation displacement, characterizing the specific displacement that occurs in the plasma during actual operation. The probability density; Represents an exponential function; R represents the root mean square error; R represents the displacement in the horizontal direction; Z represents the displacement in the vertical direction.

[0071] In this application embodiment, a Gaussian probability model is constructed based on the actual performance statistical parameters (root mean square error value σ) of the target magnetic confinement fusion device, which quantifies the originally abstract and discrete displacement control capability into a continuous and computable probability density function. This enables the optimization method of this application to systematically absorb and quantify the inherent uncertainties in engineering practice, rather than ignoring or simplifying them into fixed deviations.

[0072] S3. Within the preset range of circumferential magnetic field strength values, determine multiple magnetic field pairs to be evaluated, and within the preset range of plasma disturbance displacement, determine multiple displacement conditions to be simulated.

[0073] In the specific implementation process, according to the safety operation specifications and typical experimental parameters of the target magnetic confinement fusion device, the allowable variation range of the circumferential magnetic field strength is set. Within this range, discrete sampling is performed with a preset step size (such as 0.05T or 0.1T) to generate a series of discrete magnetic field strength values. Any two magnetic field strength values ​​are taken as a magnetic field pair to form multiple magnetic field pairs to be evaluated.

[0074] Furthermore, based on the performance and extreme disturbance analysis of the plasma position control system of the target magnetic confinement fusion device, physical limit consideration ranges for horizontal and vertical displacements are set. Within these displacement ranges, a regular mesh is used (e.g., A series of discrete displacement points are generated using either a grid-based method or a probability distribution-based random sampling method (such as Latin hypercube sampling), which constitute multiple displacement conditions to be simulated.

[0075] S4. For each magnetic field pair and each displacement condition, the calibration coefficients corresponding to each channel are calculated using the magnetic field difference calibration method based on the simulated electron temperature radial distribution function.

[0076] Each magnetic field pair includes a first magnetic field strength. Second magnetic field strength For each magnetic field pair and each displacement condition Perform the following operations:

[0077] S4.1 Calculate the first measurement position of each channel during discharge at the first magnetic field strength and the second measurement position of each channel during discharge at the second magnetic field strength.

[0078]

[0079]

[0080] in, and These represent the first and second magnetic field strengths in a given magnetic field pair, respectively. This indicates that the Nth channel is in the first magnetic field strength The first measurement location in the power generation; This indicates that the Nth channel is in the second magnetic field strength The second measurement position during discharge. The number of electron charges; For electronic quality; The local oscillator frequency of the electron cyclotron radiometer; The intermediate frequency of the Nth channel of the electron cyclotron radiometer; The large radius of the target magnetic confinement fusion device (such as the Tolmac device).

[0081] S4.2. Combining the first measurement position, the second measurement position, the simulated electron temperature radial distribution function, and each displacement condition, determine the first simulated electron temperature value of each channel under the first magnetic field strength and the second simulated electron temperature value of each channel under the second magnetic field strength.

[0082] Considering the influence of displacement, the actual physical location observed by each channel is as follows: and At this location, the radial distribution function of simulated electron temperature... Two-dimensional interpolation is performed to obtain the Nth channel under the first magnetic field strength. The first simulated electronic temperature value And the Nth channel in the second magnetic field strength The second simulated electronic temperature value .

[0083] S4.3 Randomly generate the first signal intensity of each channel measured during the discharge of the first magnetic field strength.

[0084] Assuming the electron cyclotron radiometer has N+1 channels, N+1 signal intensities are randomly generated, representing the first signal intensity measured by each channel during a discharge in the first magnetic field strength.

[0085] S4.4. Based on the first signal strength, the first simulated electron temperature value, and the second simulated electron temperature value, calculate the second signal strength measured in the discharge of the second magnetic field strength for each channel.

[0086] Since the calibration coefficients for different channels do not change with different discharge guns, and the measured electron temperature is equal to the product of the calibration coefficient and the signal strength, therefore for the Nth channel, its second magnetic field strength... The second signal strength measured during the discharge:

[0087]

[0088] in, For the Nth channel at the first magnetic field strength The first simulated electron temperature value during discharge; For the Nth channel in the second magnetic field strength The second simulated electron temperature value during discharge; For the Nth channel at the first magnetic field strength The first signal strength measured during the discharge; For the Nth channel in the second magnetic field strength The second signal strength was measured during the discharge.

[0089] S4.5 Substitute the first signal strength, the second signal strength, the first measurement position, and the second measurement position into the recursive formula of the magnetic field difference calibration method to obtain the calibration coefficients corresponding to each channel.

[0090]

[0091] in, It is the calibration coefficient corresponding to the (N+1)th channel; It is the calibration coefficient corresponding to the Nth channel; For the Nth channel at the first magnetic field strength The first signal strength measured during the discharge; For the Nth channel in the second magnetic field strength The second signal strength measured during the discharge; This indicates that the Nth channel is in the first magnetic field strength The first measurement location in the power generation; This indicates that the Nth channel is in the second magnetic field strength The second measurement position during discharge.

[0092] In this embodiment of the application, through steps S4.1-S4.5, the entire process from physical simulation data to calibration coefficient calculation is automated and quantified under any given magnetic field pair and displacement conditions, providing accurate intermediate results for subsequent accuracy evaluation.

[0093] S5. Based on the calibration coefficients corresponding to each channel, the radial distribution of electron temperature is restored, and the calibration accuracy is evaluated. After traversing multiple displacement conditions, the calibration accuracy distribution function of each magnetic field pair is obtained.

[0094] In one possible embodiment, the specific steps of S5 include:

[0095] S5.1 Based on the calibration coefficients corresponding to each channel, perform calibration calculations on the first signal strength to obtain the first electronic temperature value of each channel after calibration restoration, and perform calibration calculations on the second signal strength to obtain the second electronic temperature value of each channel after calibration restoration.

[0096] Specifically, using the calibration coefficients corresponding to the Nth channel. The first signal strength was respectively Second signal strength Perform calibration calculations:

[0097]

[0098]

[0099] in, The first electron temperature of the Nth channel after calibration and reduction. The second electron temperature of the Nth channel after calibration and reduction.

[0100] S5.2. Based on the first electron temperature value, perform interpolation reconstruction to obtain the radial distribution of the first electron temperature of each channel after calibration and restoration, and based on the second electron temperature value, perform interpolation reconstruction to obtain the radial distribution of the second electron temperature of each channel after calibration and restoration.

[0101] Specifically, with all channels at the first magnetic field strength The first measurement location in the power generation The x-axis represents the first electron temperature value after calibration and reduction. Using the vertical axis as the ordinate, a set of discrete data points is formed. Then, using a preset interpolation method, the radial distribution of the first electron temperature in each channel after calibration and restoration is reconstructed for this set of discrete data points. .

[0102] With all channels at the second magnetic field strength The second measurement location in the power generation The x-axis represents the temperature of the second electron after calibration and reduction. Using the vertical axis as the ordinate, a set of discrete data points is formed. Then, using a preset interpolation method, the radial distribution of the second electron temperature in each channel after calibration and restoration is reconstructed for this set of discrete data points. .

[0103] S5.2. Based on the radial distribution of the first electron temperature and the radial distribution of the second electron temperature, the calibration accuracy of each magnetic field pair under each displacement condition is obtained.

[0104] In one possible embodiment, after normalizing the maximum value and integrating the first and second radial distributions of electron temperature respectively, a first integral value of the first radial distribution of electron temperature and a second integral value of the second radial distribution of electron temperature are obtained; the difference between the first integral value and the second integral value is calculated, and the absolute value of the difference is divided by the first integral value to obtain the relative deviation value; the relative deviation value is subtracted from 1 to obtain the calibration accuracy of each magnetic field pair under each displacement condition.

[0105]

[0106] in, Indicates magnetic field pair Calibration accuracy under current displacement conditions; This indicates the radial distribution of the first electron temperature after calibration and reduction; This indicates the radial temperature distribution of the second electron after calibration and reduction; This represents the integral operation over the radial coordinate R.

[0107] S5.3 After traversing multiple displacement conditions, combine the calibration accuracy of each magnetic field pair under multiple displacement conditions to obtain the calibration accuracy distribution function of each magnetic field pair.

[0108] Specifically, in conjunction with the magnetic field Under multiple displacement conditions The calibration accuracy is improved to obtain the magnetic field pair. Calibration accuracy distribution function The function is based on displacement. As the independent variable, it fully describes the magnetic field pair. The spatial distribution characteristics of how calibration performance changes with plasma position perturbation.

[0109] S6. Integrate the calibration accuracy distribution function and the disturbance displacement probability distribution function of each magnetic field pair in the displacement space to obtain the final calibration accuracy of each magnetic field pair.

[0110] In one possible embodiment, the function value of the calibration accuracy distribution function of each magnetic field pair at each displacement point is multiplied by the probability density value of the disturbance displacement probability distribution function at the same displacement point to obtain the weighted accuracy value of each displacement point; within a preset plasma displacement range, a double integral operation is performed on the weighted accuracy values ​​of all displacement points to obtain the final calibration accuracy of each magnetic field pair.

[0111] The final calibration accuracy is calculated using the following formula:

[0112]

[0113] in, Indicates magnetic field pair The final calibration accuracy; For magnetic field pairs The calibration accuracy distribution function; Let be the probability distribution function of the disturbance displacement; This indicates that within the preset plasma displacement range Double integral operations within.

[0114] In this embodiment, the calibration accuracy distribution function is obtained through probability-weighted integration. (Reflecting how performance changes with displacement) and the probability distribution function of disturbance displacement. (Reflecting the actual probability of displacement) Deep fusion. Due to the perturbation displacement probability distribution function It is based on the actual displacement control capability of the device ( It is constructed with high control precision. In regions with low probability density (smaller areas), calibration accuracy is given greater weight; in regions with poor control accuracy (smaller areas), calibration accuracy is given greater weight. In regions with large (low probability density) areas, calibration accuracy is given less weight. Therefore, the ultimately selected magnetic field pairs are those that perform well within the displacement range where the device operates most frequently in practice.

[0115] S7. The magnetic field pair with the highest final calibration accuracy among multiple magnetic field pairs shall be used as the recommended calibration parameters for the target magnetic confinement fusion device.

[0116] In the specific implementation process, after obtaining the final calibration accuracy of all magnetic field pairs, the magnetic field pair with the largest final calibration accuracy A is selected. These are recommended calibration parameters for the target magnetic confinement fusion device. For example, in subsequent real discharge experiments, it is preferred to select two circumferential magnetic field conditions. and The magnetic field difference relative calibration is performed to obtain the statistically optimal calibration performance in the actual operating environment.

[0117] To make the technical solution of this application clearer, the following will describe this application in further detail with reference to the accompanying drawings, taking a specific medium-sized tokamak device and its electron cyclotron radiation (ECE) diagnostic system as an example.

[0118] Calculate the current of 500kA and the line average density using the METIS simulation program. The radial distribution of electron temperature under heating conditions with circumferential magnetic fields of 1.5, 1.8, and 2.1 T ohms, as shown in the figure. Figure 2 As shown. For Figure 2 Interpolating the radial electron temperature distribution shown, the two-dimensional electron temperature distribution at a horizontal displacement of 3 cm for a radial electron temperature of 1.6 T is as follows: Figure 3 As shown in (a), the electron temperature distribution at 1.5 and 1.6 T is as follows. Figure 3 As shown in (b).

[0119] Assuming the tokamak device operates at frequencies from 61 to 84 GHz, has 24 channels spaced 1 GHz apart, a plasma radius of 1.78 meters (large radius) and 0.65 meters (small radius), the optimal calibration results are obtained by calculating calibration coefficients and reduction temperature distribution. Figure 3 As shown in (c) and (d) in the figure, the corresponding error distribution is as follows: Figure 3 As shown in (e), the calibration error is too large when the plasma displacement reaches 3 cm. However, the actual plasma displacement is related to the plasma control capability of the device. Next, the perturbation displacement probability distribution is used to find the optimal calibration magnetic field.

[0120] Assume the root mean square error of the horizontal and vertical displacement control of this device is _____. =0.2, construct the probability distribution function of the disturbance displacement. Assume the limiting distances for the horizontal and vertical displacement of the plasma are... The diagnostic system operates within a range of 61 to 84 GHz, in 1 GHz increments. The calibration accuracy distribution function is calculated. and the probability distribution function of the disturbance displacement The final calibration accuracy is obtained by multiplying the two and integrating them. .

[0121] By scanning different magnetic field pairs This allows us to obtain the expected accuracy distribution of the system under different magnetic field pairs, considering the plasma displacement control capability of the device, as shown below. Figure 4 As shown. From Figure 4 As can be seen, under the conditions of a large radius of 1.78 meters, a small radius of 0.65 meters, an operating frequency from 61 to 84 GHz, 24 channels, and a spacing of 1 GHz, the root mean square error of the horizontal and vertical displacement control of this device is [value missing]. The optimal calibration magnetic fields when the magnetic field strength is 0.2 are approximately 1.5T and 1.62T, with a calibration accuracy of over 96%. This can effectively guide the relative calibration of magnetic field differences in actual experiments.

[0122] In summary, this application provides an optimization method for magnetic field difference calibration based on perturbation displacement. This method uses the electron temperature distribution provided by the METIS simulation program and constructs a probability distribution function of perturbation displacement considering the actual plasma displacement control capability of the tokamak device, thus more accurately analyzing the accuracy of the magnetic field difference calibration method. It solves the problem that existing optimization methods for magnetic field difference calibration rely on a constant electron temperature distribution and do not consider actual plasma displacement control capability, ultimately leading to deviations between the optimization results and actual results.

[0123] Based on the same inventive concept, please refer to Figure 5 This application also provides a magnetic field difference calibration optimization device based on perturbation displacement, the device comprising:

[0124] The simulation module is used to obtain the simulated radial distribution of electron temperature under different circumferential magnetic field strengths using a physical simulation program, and to obtain the simulated radial distribution function of electron temperature through interpolation.

[0125] The function construction module is used to construct a perturbation displacement probability distribution function to characterize displacement uncertainty based on the plasma displacement control accuracy of the target magnetic confinement fusion device.

[0126] The determination module is used to determine multiple magnetic field pairs to be evaluated within a preset range of circumferential magnetic field strength values, and to determine multiple displacement conditions to be simulated within a preset range of plasma disturbance displacement.

[0127] The calibration module is used to calculate the calibration coefficients for each channel based on the simulated electron temperature radial distribution function and the magnetic field difference calibration method for each magnetic field pair and each displacement condition.

[0128] The evaluation module is used to reconstruct the radial distribution of electron temperature based on the calibration coefficients corresponding to each channel and evaluate the calibration accuracy. After traversing multiple displacement conditions, it obtains the calibration accuracy distribution function of each magnetic field pair. The calibration accuracy distribution function of each magnetic field pair is integrated with the perturbation displacement probability distribution function in the displacement space to obtain the final calibration accuracy of each magnetic field pair.

[0129] The parameter selection module is used to select the magnetic field pair with the highest final calibration accuracy from multiple magnetic field pairs as the recommended calibration parameters for the target magnetic confinement fusion device.

[0130] Optionally, the target magnetic confinement fusion device is a tokamak device; the physical simulation program is the METIS program.

[0131] Optionally, the function building block is specifically used for:

[0132] Obtain the root mean square error values ​​of the displacement perturbation of the plasma in the horizontal and vertical directions of the target magnetic confinement fusion device;

[0133] Based on the root mean square error value, a Gaussian probability distribution function is constructed as the probability distribution function of the disturbance displacement.

[0134] Optionally, the calibration module is specifically used for:

[0135] For each magnetic field pair and each displacement condition, perform the following operations:

[0136] Based on the simulated electron temperature radial distribution function, the first measurement position of each channel in the discharge of the first magnetic field strength and the second measurement position of each channel in the discharge of the second magnetic field strength are calculated respectively.

[0137] By combining the first measurement position, the second measurement position, the simulated electron temperature radial distribution function, and each displacement condition, the first simulated electron temperature value of each channel under the first magnetic field strength and the second simulated electron temperature value of each channel under the second magnetic field strength are determined.

[0138] The first signal intensity of each channel is randomly generated and measured during a discharge at the first magnetic field strength.

[0139] Based on the first signal strength, the first simulated electron temperature value, and the second simulated electron temperature value, the second signal strength measured in the discharge of each channel under the second magnetic field strength is calculated;

[0140] Substituting the first signal strength, the second signal strength, the first measurement position, and the second measurement position into the recursive formula of the magnetic field difference calibration method, we obtain the calibration coefficients corresponding to each channel.

[0141] Optionally, the evaluation module is specifically used for:

[0142] Based on the calibration coefficients corresponding to each channel, the first signal strength is calibrated to obtain the first electronic temperature value of each channel after calibration restoration, and the second signal strength is calibrated to obtain the second electronic temperature value of each channel after calibration restoration.

[0143] Interpolation reconstruction is performed based on the first electron temperature value to obtain the radial distribution of the first electron temperature of each channel after calibration and restoration. Interpolation reconstruction is performed based on the second electron temperature value to obtain the radial distribution of the second electron temperature of each channel after calibration and restoration.

[0144] Based on the radial distribution of the first and second electron temperatures, the calibration accuracy of each magnetic field pair under each displacement condition is obtained.

[0145] After traversing multiple displacement conditions, the calibration accuracy distribution function of each magnetic field pair is obtained by combining the calibration accuracy of each magnetic field pair under multiple displacement conditions.

[0146] Optionally, the evaluation module is specifically used for:

[0147] After normalizing the maximum value and performing integration on the radial distributions of the first and second electron temperatures respectively, the first integral value of the radial distribution of the first electron temperature and the second integral value of the radial distribution of the second electron temperature are obtained.

[0148] Calculate the difference between the first integral value and the second integral value, and divide the absolute value of the difference by the first integral value to obtain the relative deviation value;

[0149] Subtract the relative deviation value from 1 to obtain the calibration accuracy of each magnetic field pair under each displacement condition.

[0150] Optionally, the evaluation module is specifically used for:

[0151] The calibration accuracy distribution function of each magnetic field pair at each displacement point is multiplied by the probability density value of the disturbance displacement probability distribution function at the same displacement point to obtain the weighted accuracy value of each displacement point.

[0152] Within the preset plasma displacement range, the weighted accuracy values ​​of all displacement points are subjected to double integration to obtain the final calibration accuracy of each magnetic field pair.

[0153] It should be noted that each module in the magnetic field difference calibration optimization device based on perturbation displacement in this embodiment corresponds one-to-one with each step in the magnetic field difference calibration optimization method based on perturbation displacement in the aforementioned embodiment. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned magnetic field difference calibration optimization method based on perturbation displacement, and will not be repeated here.

[0154] Based on the same inventive concept, this application also provides a computer device, which includes a processor, a memory, and a computer program stored in the memory. The computer program is executed by the processor to implement the aforementioned magnetic field difference calibration optimization method based on perturbation displacement.

[0155] Based on the same inventive concept, this application also provides a computer storage medium storing a computer program, which is executed by a processor to implement the aforementioned magnetic field difference calibration optimization method based on perturbation displacement.

[0156] In some embodiments, the computer-readable storage medium may be a memory such as ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a device including one or any combination of the above-mentioned memories. The computer may be a variety of computing devices, including smart terminals and servers.

[0157] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0158] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hypertext Markup Language document, in a single file dedicated to the program in question, or in multiple co-located files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0159] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0160] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0161] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0162] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A magnetic field difference calibration optimization method based on perturbation displacement, characterized in that, include: Using a physical simulation program, the radial distribution of simulated electron temperature under different circumferential magnetic field strengths was obtained, and the radial distribution function of simulated electron temperature was obtained by interpolation. Based on the plasma displacement control accuracy of the target magnetic confinement fusion device, a perturbation displacement probability distribution function is constructed to characterize displacement uncertainty; Within the preset range of circumferential magnetic field strength values, multiple magnetic field pairs to be evaluated are determined, and within the preset range of plasma disturbance displacement, multiple displacement conditions to be simulated are determined. For each magnetic field pair and each displacement condition, the calibration coefficients corresponding to each channel are calculated using the magnetic field difference calibration method based on the simulated electron temperature radial distribution function. Based on the calibration coefficients corresponding to each channel, the radial distribution of electron temperature is restored, and the calibration accuracy is evaluated. After traversing the multiple displacement conditions, the calibration accuracy distribution function of each magnetic field pair is obtained. The calibration accuracy distribution function of each magnetic field pair is integrated with the disturbance displacement probability distribution function in displacement space to obtain the final calibration accuracy of each magnetic field pair. The magnetic field pair with the highest final calibration accuracy among the multiple magnetic field pairs shall be used as the recommended calibration parameters for the target magnetic confinement fusion device.

2. The magnetic field difference calibration optimization method based on perturbation displacement according to claim 1, characterized in that, The target magnetic confinement fusion device is a tokamak device; the physical simulation program is the METIS program.

3. The magnetic field difference calibration optimization method based on perturbation displacement according to claim 1, characterized in that, The plasma displacement control accuracy based on the target magnetic confinement fusion device is used to construct the perturbation displacement probability distribution function, including: Obtain the root mean square error values ​​of the displacement perturbation of the plasma in the horizontal and vertical directions of the target magnetic confinement fusion device; Based on the root mean square error value, a Gaussian probability distribution function is constructed as the probability distribution function of the disturbance displacement.

4. The magnetic field difference calibration optimization method based on perturbation displacement according to claim 1, characterized in that, Each magnetic field pair includes a first magnetic field strength and a second magnetic field strength; for each magnetic field pair and each displacement condition, based on the simulated electron temperature radial distribution function, the calibration coefficients corresponding to each channel are calculated using the magnetic field difference calibration method, including: For each magnetic field pair and each displacement condition, perform the following operations: Based on the simulated electron temperature radial distribution function, the first measurement position of each channel in the discharge of the first magnetic field strength and the second measurement position of each channel in the discharge of the second magnetic field strength are calculated respectively. By combining the first measurement position, the second measurement position, the simulated electron temperature radial distribution function, and each displacement condition, the first simulated electron temperature value of each channel under the first magnetic field strength and the second simulated electron temperature value of each channel under the second magnetic field strength are determined. The first signal intensity of each channel is randomly generated during the discharge of the first magnetic field strength; Based on the first signal strength, the first simulated electron temperature value, and the second simulated electron temperature value, calculate the second signal strength measured in the discharge of the second magnetic field strength for each channel; Substituting the first signal strength, the second signal strength, the first measurement position, and the second measurement position into the recursive formula of the magnetic field difference calibration method, we obtain the calibration coefficients corresponding to each channel.

5. The magnetic field difference calibration optimization method based on perturbation displacement according to claim 4, characterized in that, Based on the calibration coefficients corresponding to each channel, the radial distribution of electron temperature is restored, and the calibration accuracy is evaluated. After traversing the multiple displacement conditions, the calibration accuracy distribution function for each magnetic field pair is obtained, including: Based on the calibration coefficients corresponding to each channel, the first signal strength is calibrated to obtain the first electronic temperature value of each channel after calibration restoration, and the second signal strength is calibrated to obtain the second electronic temperature value of each channel after calibration restoration. Based on the first electron temperature value, interpolation reconstruction is performed to obtain the radial distribution of the first electron temperature of each channel after calibration and restoration. Based on the second electron temperature value, interpolation reconstruction is performed to obtain the radial distribution of the second electron temperature of each channel after calibration and restoration. Based on the first and second electron temperature radial distributions, the calibration accuracy of each magnetic field pair under each displacement condition is obtained. After traversing the multiple displacement conditions, the calibration accuracy distribution function of each magnetic field pair is obtained by combining the calibration accuracy of each magnetic field pair under the multiple displacement conditions.

6. The magnetic field difference calibration optimization method based on perturbation displacement according to claim 5, characterized in that, The process of obtaining the calibration accuracy of each magnetic field pair under each displacement condition based on the first and second electron temperature radial distributions includes: After performing maximum value normalization and integral operation on the first and second radial distributions of electron temperature respectively, the first integral value of the first radial distribution of electron temperature and the second integral value of the second radial distribution of electron temperature are obtained. Calculate the difference between the first integral value and the second integral value, and divide the absolute value of the difference by the first integral value to obtain the relative deviation value; Subtracting the relative deviation value from 1 yields the calibration accuracy of each magnetic field pair under each displacement condition.

7. The magnetic field difference calibration optimization method based on perturbation displacement according to claim 1, characterized in that, The calibration accuracy distribution function for each magnetic field pair is integrated with the disturbance displacement probability distribution function in displacement space to obtain the final calibration accuracy for each magnetic field pair, including: The calibration accuracy distribution function of each magnetic field pair at each displacement point is multiplied by the probability density value of the disturbance displacement probability distribution function at the same displacement point to obtain the weighted accuracy value of each displacement point. Within the preset plasma displacement range, the weighted accuracy values ​​of all displacement points are subjected to double integration to obtain the final calibration accuracy of each magnetic field pair.

8. A magnetic field difference calibration and optimization device based on perturbation displacement, characterized in that, include: The simulation module is used to obtain the simulated radial distribution of electron temperature under different circumferential magnetic field strengths using a physical simulation program, and obtain the simulated radial distribution function of electron temperature through interpolation. The function construction module is used to construct a perturbation displacement probability distribution function to characterize displacement uncertainty based on the plasma displacement control accuracy of the target magnetic confinement fusion device. The determination module is used to determine multiple magnetic field pairs to be evaluated within a preset range of circumferential magnetic field strength values, and to determine multiple displacement conditions to be simulated within a preset range of plasma disturbance displacement. The calibration module is used to calculate the calibration coefficients for each channel based on the simulated electron temperature radial distribution function, using the magnetic field difference calibration method, for each magnetic field pair and each displacement condition. The evaluation module is used to reconstruct the radial distribution of electron temperature based on the calibration coefficients corresponding to each channel and evaluate the calibration accuracy. After traversing the multiple displacement conditions, it obtains the calibration accuracy distribution function of each magnetic field pair. The calibration accuracy distribution function of each magnetic field pair is integrated with the perturbation displacement probability distribution function in the displacement space to obtain the final calibration accuracy of each magnetic field pair. The parameter selection module is used to select the magnetic field pair with the highest final calibration accuracy among the multiple magnetic field pairs as the recommended calibration parameters for the target magnetic confinement fusion device.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the magnetic field difference calibration optimization method based on perturbation displacement as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and the processor executes the computer program to implement the magnetic field difference calibration optimization method based on perturbation displacement as described in any one of claims 1-7.

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