Multi-scale correlation analysis method for micro-discharge suppression

Abstract

The invention discloses a multi-scale correlation analysis method for micro-discharge suppression. The multi-scale correlation analysis method comprises the following steps: S1, calculating and processing parameters from atoms to nanoscale by using a first principle; s2, obtaining and processing the influence of secondary electron emission by obtaining the intrinsic characteristics of each material. The method has the beneficial effects that the key parameters are calculated and the basic physical characteristics of the materials are obtained by using the first principle from the atomic scale to the nanometer scale, and then secondary electron emission simulation of the micrometer scale is carried out; according to the method, the micro-discharge threshold value from the scale of material to the scale of millimeter to centimeter is calculated, cross-scale correlation analysis from material characteristics to device-level performance is achieved through step-by-step parameter transmission and model coupling, occurrence mechanisms and influence factors of the micro-discharge phenomenon under different scales can be accurately grasped, powerful support is provided for deep understanding of micro-discharge causes, and the method is suitable for popularization and application. And an effective way for inhibiting micro discharge can be found fundamentally.

Description

Technical Field

[0001] This invention relates to the field of micro-discharge suppression technology, specifically a multi-scale correlation analysis method for micro-discharge suppression. Background Technology

[0002] In numerous fields such as aerospace, communications, and electronics, the stability and reliability of power systems and other equipment are crucial. Micro-discharge, as a key factor affecting normal equipment operation, has long been a challenging problem hindering the development of related fields. Micro-discharge is a tiny discharge phenomenon that occurs on the surface of electrodes or insulating media in a vacuum or low-pressure environment. When the voltage applied between electrodes exceeds a certain threshold, electrons on the electrode surface escape through field emission or thermionic emission. These electrons are accelerated and collide with the electrode or insulating media surface under the influence of an electric field, triggering secondary electron emission. If the secondary electron emission coefficient is greater than 1, the number of electrons will increase exponentially, ultimately leading to micro-discharge. Micro-discharge not only generates electromagnetic interference, affecting the normal signal transmission and communication quality of equipment, but may also cause localized overheating, accelerating material aging and damage, and in severe cases, even leading to insulation failure. Dielectric breakdown can cause equipment failures, posing a serious threat to the flight safety of aerospace vehicles and the stable operation of communication systems. Although some progress has been made in the study of micro-discharge phenomena, most studies are limited to a single scale or a single link. At the microscale, some studies focus on the influence of the atomic structure and electronic properties of materials on secondary electron emission, obtaining parameters such as the work function and electronic band structure of materials through theoretical calculations and experimental measurements, and analyzing their relationship with the secondary electron emission coefficient to provide a certain basis for material selection. However, they often ignore the comprehensive effect of factors such as device structure and electric field distribution on micro-discharge at the macroscale. At the macroscale, some studies use experimental and simulation methods to optimize the electric field distribution and insulation performance of devices to reduce the risk of micro-discharge, but lack a systematic analysis of the intrinsic relationship between micro-level material properties and macro-level performance. Summary of the Invention

[0003] The purpose of this invention is to provide a multi-scale correlation analysis method for micro-discharge suppression to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a multi-scale correlation analysis method for micro-discharge suppression, comprising the following steps:

[0005] S1: Calculate parameters from the atomic to the nanoscale using first-principles calculations;

[0006] S2. By acquiring the intrinsic properties of each material, the influence of secondary electron emission is processed:

[0007] S3. Obtain the crystal planes of the material by cutting, and perform cell structure modeling on the material using crystallographic modeling software:

[0008] S4. Based on the obtained detection results, analyze and process the causes and induction mechanisms of micro-discharge, and obtain the change law of the insulating medium from the insulating state to the breakdown state;

[0009] S5. Construct a multi-generation model program for secondary electron emission and perform micrometer-scale secondary electron emission simulation;

[0010] S6. Use particle simulation to process the planar structure device, input the secondary electron emission coefficient simulated at the micrometer scale into the software to calculate the micro-discharge threshold, and calculate the critical conditions;

[0011] S7. For complex structural devices, statistical theory or three-dimensional particle simulation software can be used to establish the device structure for direct simulation.

[0012] S8. The orthogonal experimental method was used to obtain the effects of different stirring times, curing times and material ratios on the performance of composite insulating materials.

[0013] S9. Conduct comprehensive performance tests on the prepared samples, measure the key parameters of the samples such as breakdown strength, dielectric constant, and volume resistivity, and analyze the thermal conductivity and insulation performance. By comparing the various performance indicators of the samples under different parameters, find the optimal insulation medium ratio scheme.

[0014] S10. Based on simulation and experimental results, analyze the role mechanism of different material properties in micro-discharge suppression, and select appropriate materials.

[0015] S11. By designing a charge discharge channel with a conductive coating and conductive composite material, and optimizing the encapsulation structure of the insulating material, a specific encapsulation and guidance method is adopted to analyze the influence of different structures and select the best encapsulation scheme.

[0016] S12. By passing parameters step by step, the physical consistency between scales is determined, and cross-scale correlation analysis is performed from material properties to device-level performance.

[0017] S13. Verify the accuracy of the simulated values ​​through experiments to ensure the reliability of the model, and formulate targeted micro-discharge suppression strategies based on the results of multi-scale correlation analysis.

[0018] S14. Through repeated simulation and structural optimization, the insulation between the voltages of the power supply system and between the power supply system and the casing is optimized to achieve the requirement of zero micro-discharge.

[0019] S15. Design a comparative experiment to verify the effect of different insulation medium ratios, electric field and spatial arrangement optimization schemes on the suppression of micro-discharge.

[0020] S16. Analyze the experimental results, compare the experimental data of different optimization schemes, evaluate the actual effect of various suppression strategies, determine the best suppression scheme through statistical analysis, and verify the effectiveness of the multi-scale correlation analysis method.

[0021] Preferably, the calculation of atomic to nanoscale parameters using first principles in S1 specifically includes the following steps:

[0022] A1. Calculate the key parameters of the work function and optical energy loss spectrum of metals and composite materials using first-principles calculations;

[0023] A2. By calculating the electronic structure of materials, the basic physical properties of materials at the atomic to nanoscale are obtained, providing data support for subsequent analysis of the causes of micro-discharge.

[0024] Preferably, the process of obtaining the influence of secondary electron emission by acquiring the intrinsic properties of each material in S2 specifically includes the following steps:

[0025] S21. Obtain the influence mechanism of secondary electron emission by the intrinsic properties of the crystal structure and electronic band structure of the material;

[0026] S22. Establish a quantitative relationship between the intrinsic properties of materials and the secondary electron emission coefficient, and determine the role of different material properties in the micro-discharge process.

[0027] Preferably, the process of cutting to obtain the crystal plane of the material in S3, and then performing cell structure modeling of the material using crystallographic modeling software, specifically includes the following steps:

[0028] S31. Use crystallography modeling software to model the cell structure of the target material;

[0029] S32. Obtain different crystal planes of the material through cutting operations, and obtain the atomic arrangement and electronic structure characteristics of the material surface through the data of each different crystal plane.

[0030] Preferably, the steps in S4, which integrate the acquired detection results, analyze and process the causes and induction mechanisms of micro-discharges, and obtain the change law of the insulating medium from the insulating state to the breakdown state, specifically include the following steps:

[0031] S41. Based on the comprehensive detection results from the atomic to the nanoscale, the effects of voltage, frequency, electrical parameters, environmental factors, and internal parasitic effects of the power supply on the state of the insulating medium are analyzed.

[0032] S42. By establishing physical models and mathematical equations, the change law of the insulating medium from the insulating state to the breakdown state is obtained and processed.

[0033] Preferably, the procedure in S5 for constructing a multi-generation model of secondary electron emission and performing micrometer-scale secondary electron emission simulation specifically includes the following steps:

[0034] S51, Develop a multi-generation model program for secondary electron emission;

[0035] S52. Through the constructed secondary electron emission multi-generation model program, the multiple scattering and emission processes of electrons on the material surface are simulated.

[0036] S53. By inputting the work function and surface morphology parameters of the material, simulate the secondary electron emission coefficient of the material surface.

[0037] Preferably, the step S12 method, which determines the physical consistency between scales through step-by-step parameter transfer and performs cross-scale correlation analysis from material properties to device-level performance, specifically includes the following steps:

[0038] S121. Transfer the material parameters obtained from atomic to nanoscale calculations to the micrometer-scale simulation as input parameters for the secondary electron emission simulation.

[0039] S122. Then, the secondary electron emission coefficient obtained from the micrometer-scale simulation is transferred to the calculation of the micro-discharge threshold at the millimeter to centimeter scale.

[0040] S123. Through model coupling, simulation results at different scales are organically combined and processed.

[0041] S124. Analyze the occurrence mechanism and influencing factors of micro-discharge phenomena at different scales to provide a comprehensive basis for the formulation of micro-discharge suppression strategies.

[0042] Preferably, step S13, which involves experimentally verifying the accuracy of the simulated values ​​to ensure model reliability and formulating a targeted micro-discharge suppression strategy based on multi-scale correlation analysis results, specifically includes the following steps:

[0043] S131. Measure the key parameters of the device's micro-discharge threshold and secondary electron emission coefficient under different operating conditions;

[0044] S132. Compare and analyze the results with the simulation results, adjust and optimize the model parameters based on the experimental results, and improve the accuracy through repeated iterations.

[0045] S133. Based on the research results on material optimization, electric field and spatial arrangement optimization, and insulation treatment optimization, comprehensive suppression measures are proposed.

[0046] S134. Optimize the insulation dielectric ratio, adjust the electric field arrangement, improve the packaging structure, and set the working mechanism and expected effect of each suppression strategy.

[0047] Preferably, the step S14, which involves repeated simulations and structural optimization to achieve optimal insulation between different voltages in the power supply system and between the power supply system and the casing, thus fulfilling the requirement of zero micro-discharge, specifically includes the following steps:

[0048] S141. Use electromagnetic field simulation software to perform multiple simulation analyses on the optimized design scheme.

[0049] S142. Evaluate the micro-discharge suppression effect, further adjust the structural parameters and optimization measures based on the simulation results, continuously improve the scheme, and iterate repeatedly until the requirement of no micro-discharge is achieved.

[0050] Preferably, the design comparison experiment in S15, which verifies the effect of different insulating medium ratios, electric fields, and spatial arrangement optimization schemes on the suppression of micro-discharge, specifically includes the following steps:

[0051] S151. Prototypes with different optimization schemes are manufactured and tested under the same experimental conditions;

[0052] S152. Using the Wiesmann test system equipment, the key performance indicators of the high-voltage power supply, such as output voltage, ripple, and stability, are tested and evaluated.

[0053] S153. Monitor the micro-discharge status of the prototype under different operating conditions and record the number and intensity of micro-discharges.

[0054] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.

[0055] Compared with existing technologies, the beneficial effects of this invention are as follows: This method starts from the atomic to the nanoscale, uses first-principles calculations to obtain key parameters and the basic physical properties of materials, then performs secondary electron emission simulations at the micrometer scale, and then calculates the micro-discharge threshold at the millimeter to centimeter scale. Through step-by-step parameter transfer and model coupling, it achieves cross-scale correlation analysis from material properties to device-level performance, which can accurately grasp the occurrence mechanism and influencing factors of micro-discharge phenomena at different scales, providing strong support for a deeper understanding of the causes of micro-discharge and helping to find effective ways to suppress micro-discharge from the root. This method comprehensively utilizes multiple means such as material optimization, electric field and spatial arrangement optimization, and insulation treatment optimization. It obtains the influencing factors of composite insulation material performance through orthogonal experimental methods, finds the optimal ratio scheme, optimizes the design of charge discharge channels for device structure, and repeatedly simulates and optimizes the structure to achieve the best state of power system insulation. It can suppress micro-discharge from multiple angles, effectively reduce the risk of micro-discharge, and improve the stability and reliability of the system. Detailed Implementation

[0056] Example 1:

[0057] A multi-scale correlation analysis method for micro-discharge suppression according to an embodiment of the present invention includes the following steps:

[0058] S1: Calculate parameters from the atomic to the nanoscale using first-principles calculations;

[0059] S2. By acquiring the intrinsic properties of each material, the influence of secondary electron emission is processed:

[0060] S3. Obtain the crystal planes of the material by cutting, and perform cell structure modeling on the material using crystallographic modeling software:

[0061] S4. Based on the obtained detection results, analyze and process the causes and induction mechanisms of micro-discharge, and obtain the change law of the insulating medium from the insulating state to the breakdown state;

[0062] S5. Construct a multi-generation model program for secondary electron emission and perform micrometer-scale secondary electron emission simulation;

[0063] S6. Use particle simulation to process the planar structure device, input the secondary electron emission coefficient simulated at the micrometer scale into the software to calculate the micro-discharge threshold, and calculate the critical conditions;

[0064] S7. For complex structural devices, statistical theory or three-dimensional particle simulation software can be used to establish the device structure for direct simulation.

[0065] S8. The orthogonal experimental method was used to obtain the effects of different stirring times, curing times and material ratios on the performance of composite insulating materials.

[0066] S9. Conduct comprehensive performance tests on the prepared samples, measure the key parameters of the samples such as breakdown strength, dielectric constant, and volume resistivity, and analyze the thermal conductivity and insulation performance. By comparing the various performance indicators of the samples under different parameters, find the optimal insulation medium ratio scheme.

[0067] S10. Based on simulation and experimental results, analyze the role mechanism of different material properties in micro-discharge suppression, and select appropriate materials.

[0068] S11. By designing a charge discharge channel with a conductive coating and conductive composite material, and optimizing the encapsulation structure of the insulating material, a specific encapsulation and guidance method is adopted to analyze the influence of different structures and select the best encapsulation scheme.

[0069] S12. By passing parameters step by step, the physical consistency between scales is determined, and cross-scale correlation analysis is performed from material properties to device-level performance.

[0070] S13. Verify the accuracy of the simulated values ​​through experiments to ensure the reliability of the model, and formulate targeted micro-discharge suppression strategies based on the results of multi-scale correlation analysis.

[0071] S14. Through repeated simulation and structural optimization, the insulation between the voltages of the power supply system and between the power supply system and the casing is optimized to achieve the requirement of zero micro-discharge.

[0072] S15. Design a comparative experiment to verify the effect of different insulation medium ratios, electric field and spatial arrangement optimization schemes on the suppression of micro-discharge.

[0073] S16. Analyze the experimental results, compare the experimental data of different optimization schemes, evaluate the actual effect of various suppression strategies, determine the best suppression scheme through statistical analysis, and verify the effectiveness of the multi-scale correlation analysis method.

[0074] This method analyzes micro-discharge suppression from multiple scales and stages, comprehensively and systematically covering all aspects involved in micro-discharge research. It provides a complete framework for a deeper understanding of micro-discharge phenomena and effective suppression. Through comprehensive analysis from the micro to the macro level, it can accurately locate the causes and influencing factors of micro-discharge, and then formulate more targeted and effective suppression strategies to improve the stability and reliability of power supply systems and other equipment.

[0075] Example 2

[0076] Specifically, the calculation of atomic to nanoscale parameters using first-principles calculations in S1 includes the following steps:

[0077] A1. Calculate the key parameters of the work function and optical energy loss spectrum of metals and composite materials using first-principles calculations;

[0078] A2. By calculating the electronic structure of materials, the basic physical properties of materials at the atomic to nanoscale can be obtained, providing data support for subsequent analysis of the causes of micro-discharge;

[0079] By using first-principles calculations to obtain key parameters of metals and composite materials from the atomic to the nanoscale, we can obtain the basic physical properties of materials and provide accurate basic data for subsequent analysis of the causes of micro-discharges. This will help us understand the relationship between micro-discharges and material properties at the microscopic level.

[0080] Specifically, S2 involves obtaining the influence of the intrinsic properties of various materials on secondary electron emission, which includes the following steps:

[0081] S21. Obtain the influence mechanism of secondary electron emission by the intrinsic properties of the crystal structure and electronic band structure of the material;

[0082] S22. Establish a quantitative relationship between the intrinsic properties of materials and the secondary electron emission coefficient, and determine the role of different material properties in the micro-discharge process;

[0083] By obtaining the intrinsic properties of materials, we explored their influence mechanism on secondary electron emission and established a quantitative relationship between intrinsic properties and secondary electron emission coefficient. This clarified the role of different material properties in the micro-discharge process and provided a theoretical basis for material selection and optimization.

[0084] Specifically, the process of obtaining the material's crystal planes through cutting in S3, and then performing unit cell structure modeling on the material using crystallographic modeling software, includes the following steps:

[0085] S31. Use crystallography modeling software to model the cell structure of the target material;

[0086] S32. Obtain different crystal planes of the material through cutting operations, and obtain the atomic arrangement and electronic structure characteristics of the material surface through the data of each different crystal plane;

[0087] By using crystallographic modeling software and cutting operations to obtain material crystal plane data, and then obtaining the atomic arrangement and electronic structure characteristics of the material surface, we can gain a deeper understanding of the influence of material surface properties on micro-discharge and provide direction for optimizing material surface structure to suppress micro-discharge.

[0088] Specifically, S4 involves integrating the acquired detection results, analyzing and processing the causes and induction mechanisms of micro-discharges, and obtaining the change law of the insulating medium from the insulating state to the breakdown state. This includes the following steps:

[0089] S41. Based on the comprehensive detection results from the atomic to the nanoscale, the effects of voltage, frequency, electrical parameters, environmental factors, and internal parasitic effects of the power supply on the state of the insulating medium are analyzed.

[0090] S42. By establishing physical models and mathematical equations, the change law of insulating medium from insulating state to breakdown state is obtained and processed.

[0091] By integrating multi-scale detection results, the influence of various factors on the state of insulating media is analyzed. By establishing physical models and mathematical equations, the change law of insulating media from insulating state to breakdown state is obtained, providing key information for predicting and preventing the breakdown of insulating media and suppressing micro-discharge.

[0092] The S5 program for constructing multi-generational secondary electron emission models and performing micrometer-scale secondary electron emission simulations includes the following steps:

[0093] S51, Develop a multi-generation model program for secondary electron emission;

[0094] S52. Through the constructed secondary electron emission multi-generation model program, the multiple scattering and emission processes of electrons on the material surface are simulated.

[0095] S53. Simulate the secondary electron emission coefficient of the material surface by inputting the work function and surface morphology parameters of the material;

[0096] The development of a multi-generation model program for secondary electron emission, which simulates the multiple scattering and emission processes of electrons on the material surface and the secondary electron emission coefficient of the material surface, helps to gain a deeper understanding of the secondary electron emission mechanism and provides an important simulation tool for micro-discharge simulation and suppression.

[0097] Specifically, S12 involves determining the physical consistency across scales through step-by-step parameter transfer, and performing cross-scale correlation analysis from material properties to device-level performance, which includes the following steps:

[0098] S121. Transfer the material parameters obtained from atomic to nanoscale calculations to the micrometer-scale simulation as input parameters for the secondary electron emission simulation.

[0099] S122. Then, the secondary electron emission coefficient obtained from the micrometer-scale simulation is transferred to the calculation of the micro-discharge threshold at the millimeter to centimeter scale.

[0100] S123. Through model coupling, simulation results at different scales are organically combined and processed.

[0101] S124. Analyze the occurrence mechanism and influencing factors of micro-discharge phenomena at different scales to provide a comprehensive basis for the formulation of micro-discharge suppression strategies;

[0102] By combining simulation results at different scales through stepwise parameter transfer and model coupling, the occurrence mechanism and influencing factors of micro-discharge phenomena at different scales are analyzed, providing a comprehensive basis for formulating integrated micro-discharge suppression strategies and breaking the limitations of single-scale analysis.

[0103] Specifically, S13 involves experimentally verifying the accuracy of the simulated values ​​to ensure model reliability, and formulating targeted micro-discharge suppression strategies based on multi-scale correlation analysis results. This includes the following steps:

[0104] S131. Measure the key parameters of the device's micro-discharge threshold and secondary electron emission coefficient under different operating conditions;

[0105] S132. Compare and analyze the results with the simulation results, adjust and optimize the model parameters based on the experimental results, and improve the accuracy through repeated iterations.

[0106] S133. Based on the research results on material optimization, electric field and spatial arrangement optimization, and insulation treatment optimization, comprehensive suppression measures are proposed.

[0107] S134. Optimize the insulating dielectric ratio, adjust the electric field arrangement, improve the packaging structure, and set the working mechanism and expected effect of each suppression strategy;

[0108] The accuracy of the simulated values ​​was verified by experiments to ensure the reliability of the model. Based on the results of multi-scale correlation analysis, targeted micro-discharge suppression strategies were formulated. Combined with multi-faceted optimization studies, comprehensive suppression measures were proposed, clarifying the mechanism of action and expected effects of each strategy, making the suppression strategy more reliable and effective.

[0109] Specifically, S14 involves repeated simulations and structural optimization to achieve optimal insulation between different voltage levels in the power supply system and between the power supply system and the casing, thus fulfilling the requirement of zero micro-discharge. This includes the following steps:

[0110] S141. Use electromagnetic field simulation software to perform multiple simulation analyses on the optimized design scheme.

[0111] S142. Evaluate the micro-discharge suppression effect, further adjust the structural parameters and optimization measures based on the simulation results, continuously improve the scheme, and iterate repeatedly until the requirement of no micro-discharge is achieved.

[0112] The optimized design scheme was simulated and analyzed multiple times using electromagnetic field simulation software. Based on the results, the structural parameters and optimization measures were adjusted. Through repeated iterations, the insulation of the power supply system was brought to its optimal state, achieving the requirement of zero micro-discharge and effectively improving the insulation performance and stability of the power supply system.

[0113] The design comparison experiment in S15 verifies the effect of different insulation medium ratios, electric field, and spatial arrangement optimization schemes on the suppression of micro-discharges. Specifically, it includes the following steps:

[0114] S151. Prototypes with different optimization schemes are manufactured and tested under the same experimental conditions;

[0115] S152. Using the Wiesmann test system equipment, the key performance indicators of the high-voltage power supply, such as output voltage, ripple, and stability, are tested and evaluated.

[0116] S153. Monitor the micro-discharge of the prototype under different operating conditions and record the number and intensity of micro-discharges.

[0117] By designing comparative experiments, fabricating prototypes of different optimization schemes, and testing them under the same conditions, and using professional equipment to evaluate key performance indicators, monitor micro-discharge conditions, and record relevant information, we can accurately verify the suppression effect of different optimization schemes on micro-discharge and provide reliable experimental basis for determining the best suppression scheme.

[0118] Example 3

[0119] A multi-scale correlation analysis method for micro-discharge suppression, characterized by comprising the following steps:

[0120] S1: Using first-principles calculations, key parameters of the work function and optical energy loss spectrum of metals and composite materials are obtained. By calculating the electronic structure of materials, the basic physical properties of materials at the atomic to nanoscale are acquired, providing data support for subsequent analysis of the causes of micro-discharge.

[0121] S2. By understanding the influence mechanism of secondary electron emission on the intrinsic properties of the material's crystal structure and electronic band structure, a quantitative relationship between the material's intrinsic properties and the secondary electron emission coefficient is established, and the role of different material properties in the micro-discharge process is determined:

[0122] S3. Use crystallography modeling software to model the unit cell structure of the target material, obtain different crystal planes of the material through cutting operations, and obtain the atomic arrangement and electronic structure characteristics of the material surface through the data of each different crystal plane:

[0123] S4. Based on the comprehensive detection results from the atomic to the nanoscale, the effects of voltage, frequency, electrical parameters, environmental factors, and internal parasitic effects of the power supply on the state of the insulating medium are analyzed. By establishing physical models and mathematical equations, the change law of the insulating medium from the insulating state to the breakdown state is obtained and processed.

[0124] S5. Construct a multi-generation model program for secondary electron emission. Through the constructed multi-generation model program for secondary electron emission, simulate the multiple scattering and emission process of electrons on the material surface. By inputting the work function and surface morphology parameter information of the material, simulate the secondary electron emission coefficient of the material surface.

[0125] S6. Use particle simulation to process the planar structure device, input the secondary electron emission coefficient simulated at the micrometer scale into the software to calculate the micro-discharge threshold, and calculate the critical conditions;

[0126] S7. For complex structural devices, statistical theory or three-dimensional particle simulation software can be used to establish the device structure for direct simulation.

[0127] S8. The orthogonal experimental method was used to obtain the effects of different stirring times, curing times and material ratios on the performance of composite insulating materials.

[0128] S9. Conduct comprehensive performance tests on the prepared samples, measure the key parameters of the samples such as breakdown strength, dielectric constant, and volume resistivity, and analyze the thermal conductivity and insulation performance. By comparing the various performance indicators of the samples under different parameters, find the optimal insulation medium ratio scheme.

[0129] S10. Based on simulation and experimental results, analyze the role mechanism of different material properties in micro-discharge suppression, and select appropriate materials.

[0130] S11. By designing a charge discharge channel with a conductive coating and conductive composite material, and optimizing the encapsulation structure of the insulating material, a specific encapsulation and guidance method is adopted to analyze the influence of different structures and select the best encapsulation scheme.

[0131] S12. The material parameters calculated at the atomic to nanoscale are transferred to the micrometer-scale simulation as input parameters for the secondary electron emission simulation. Then, the secondary electron emission coefficients obtained from the micrometer-scale simulation are transferred to the micro-discharge threshold calculation at the millimeter to centimeter scale. Through model coupling, the simulation results at different scales are organically combined and processed to analyze the occurrence mechanism and influencing factors of micro-discharge phenomena at different scales, providing a comprehensive basis for the formulation of micro-discharge suppression strategies.

[0132] S13. Measure the key parameters of the device's micro-discharge threshold and secondary electron emission coefficient under different operating conditions, compare and analyze them with the simulation results, adjust and optimize the model parameters based on the experimental results, improve the accuracy through repeated iterations, and combine the research results on material optimization, electric field and spatial arrangement optimization, and insulation treatment optimization to propose comprehensive suppression measures, optimize the insulation dielectric ratio, adjust the electric field arrangement, improve the packaging structure, and set the action mechanism and expected effect of each suppression strategy.

[0133] S14. Using electromagnetic field simulation software, perform multiple simulation analyses on the optimized design scheme to evaluate the micro-discharge suppression effect. Based on the simulation results, further adjust the structural parameters and optimization measures, continuously improve the scheme, and iterate repeatedly until the requirement of no micro-discharge is achieved.

[0134] S15. Prototypes with different optimization schemes are manufactured and tested under the same experimental conditions. The key performance indicators of the high voltage power supply, such as output voltage, ripple, and stability, are tested and evaluated using the Wiseman test system equipment. The micro-discharge of the prototype under different operating conditions is monitored, and the number and intensity of micro-discharges are recorded.

[0135] S16. Analyze the experimental results, compare the experimental data of different optimization schemes, evaluate the actual effect of various suppression strategies, determine the best suppression scheme through statistical analysis, and verify the effectiveness of the multi-scale correlation analysis method.

[0136] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

[0137] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope of this disclosure is indicated by the following claims.

Claims

1. A multi-scale correlation analysis method for micro-discharge suppression, characterized in that, Includes the following steps: S1: Calculate parameters from the atomic to the nanoscale using first-principles calculations; S2. By acquiring the intrinsic properties of each material, the influence of secondary electron emission is processed: S3. Obtain the crystal planes of the material by cutting, and perform cell structure modeling on the material using crystallographic modeling software: S4. Based on the obtained detection results, analyze and process the causes and induction mechanisms of micro-discharge, and obtain the change law of the insulating medium from the insulating state to the breakdown state; S5. Construct a multi-generation model program for secondary electron emission and perform micrometer-scale secondary electron emission simulation; S6. Use particle simulation to process the planar structure device, input the secondary electron emission coefficient simulated at the micrometer scale into the software to calculate the micro-discharge threshold, and calculate the critical conditions; S7. For complex structural devices, statistical theory or three-dimensional particle simulation software can be used to establish the device structure for direct simulation. S8. The orthogonal experimental method was used to obtain the effects of different stirring times, curing times and material ratios on the performance of composite insulating materials. S9. Conduct comprehensive performance tests on the prepared samples, measure the key parameters of the samples such as breakdown strength, dielectric constant, and volume resistivity, and analyze the thermal conductivity and insulation performance. By comparing the various performance indicators of the samples under different parameters, find the optimal insulation medium ratio scheme. S10. Based on simulation and experimental results, analyze the role mechanism of different material properties in micro-discharge suppression, and select appropriate materials. S11. By designing a charge discharge channel with a conductive coating and conductive composite material, and optimizing the encapsulation structure of the insulating material, a specific encapsulation and guidance method is adopted to analyze the influence of different structures and select the best encapsulation scheme. S12. By passing parameters step by step, the physical consistency between scales is determined, and cross-scale correlation analysis is performed from material properties to device-level performance. S13. Verify the accuracy of the simulated values ​​through experiments to ensure the reliability of the model, and formulate targeted micro-discharge suppression strategies based on the results of multi-scale correlation analysis. S14. Through repeated simulation and structural optimization, the insulation between the voltages of the power supply system and between the power supply system and the casing is optimized to achieve the requirement of zero micro-discharge. S15. Design a comparative experiment to verify the effect of different insulation medium ratios, electric field and spatial arrangement optimization schemes on the suppression of micro-discharge. S16. Analyze the experimental results, compare the experimental data of different optimization schemes, evaluate the actual effect of various suppression strategies, determine the best suppression scheme through statistical analysis, and verify the effectiveness of the multi-scale correlation analysis method.

2. The multi-scale correlation analysis method for micro-discharge suppression according to claim 1, characterized in that, The calculation and processing of atomic to nanoscale parameters using first-principles calculations in S1 specifically includes the following steps: A1. Calculate the key parameters of the work function and optical energy loss spectrum of metals and composite materials using first-principles calculations; A2. By calculating the electronic structure of materials, the basic physical properties of materials at the atomic to nanoscale are obtained, providing data support for subsequent analysis of the causes of micro-discharge.

3. The multi-scale correlation analysis method for micro-discharge suppression according to claim 2, characterized in that, The process of acquiring the influence of secondary electron emission by obtaining the intrinsic properties of each material in S2 specifically includes the following steps: S21. Obtain the influence mechanism of secondary electron emission by the intrinsic properties of the crystal structure and electronic band structure of the material; S22. Establish a quantitative relationship between the intrinsic properties of materials and the secondary electron emission coefficient, and determine the role of different material properties in the micro-discharge process.

4. The multi-scale correlation analysis method for micro-discharge suppression according to claim 3, characterized in that, The process of cutting to obtain the material's crystal planes in S3, and then performing cell structure modeling on the material using crystallographic modeling software, specifically includes the following steps: S31. Use crystallography modeling software to model the cell structure of the target material; S32. Obtain different crystal planes of the material through cutting operations, and obtain the atomic arrangement and electronic structure characteristics of the material surface through the data of each different crystal plane.

5. The multi-scale correlation analysis method for micro-discharge suppression according to claim 4, characterized in that, The steps in S4, which integrate the acquired detection results, analyze and process the causes and induction mechanisms of micro-discharges, and obtain the change law of the insulating medium from the insulating state to the breakdown state, specifically include the following steps: S41. Based on the comprehensive detection results from the atomic to the nanoscale, the effects of voltage, frequency, electrical parameters, environmental factors, and internal parasitic effects of the power supply on the state of the insulating medium are analyzed. S42. By establishing physical models and mathematical equations, the change law of the insulating medium from the insulating state to the breakdown state is obtained and processed.

6. The multi-scale correlation analysis method for micro-discharge suppression according to claim 5, characterized in that, The procedure in S5 for constructing a multi-generation model of secondary electron emission and performing micrometer-scale secondary electron emission simulation specifically includes the following steps: S51, Develop a multi-generation model program for secondary electron emission; S52. Through the constructed secondary electron emission multi-generation model program, the multiple scattering and emission processes of electrons on the material surface are simulated. S53. By inputting the work function and surface morphology parameters of the material, simulate the secondary electron emission coefficient of the material surface.

7. The multi-scale correlation analysis method for micro-discharge suppression according to claim 6, characterized in that, The step S12 step, which involves determining the physical consistency across scales through step-by-step parameter transfer and performing cross-scale correlation analysis from material properties to device-level performance, specifically includes the following steps: S121. Transfer the material parameters obtained from atomic to nanoscale calculations to the micrometer-scale simulation as input parameters for the secondary electron emission simulation. S122. Then, the secondary electron emission coefficient obtained from the micrometer-scale simulation is transferred to the calculation of the micro-discharge threshold at the millimeter to centimeter scale. S123. Through model coupling, simulation results at different scales are organically combined and processed. S124. Analyze the occurrence mechanism and influencing factors of micro-discharge phenomena at different scales to provide a comprehensive basis for the formulation of micro-discharge suppression strategies.

8. The multi-scale correlation analysis method for micro-discharge suppression according to claim 7, characterized in that, The steps in S13, namely verifying the accuracy of the simulated values ​​through experiments to ensure the reliability of the model and formulating a targeted micro-discharge suppression strategy based on the results of multi-scale correlation analysis, specifically include the following steps: S131. Measure the key parameters of the device's micro-discharge threshold and secondary electron emission coefficient under different operating conditions; S132. Compare and analyze the results with the simulation results, adjust and optimize the model parameters based on the experimental results, and improve the accuracy through repeated iterations. S133. Based on the research results on material optimization, electric field and spatial arrangement optimization, and insulation treatment optimization, comprehensive suppression measures are proposed. S134. Optimize the insulation dielectric ratio, adjust the electric field arrangement, improve the packaging structure, and set the working mechanism and expected effect of each suppression strategy.

9. The multi-scale correlation analysis method for micro-discharge suppression according to claim 8, characterized in that, The steps in S14, which involve repeated simulations and structural optimization to achieve optimal insulation between different voltage levels in the power supply system and between the power supply system and the casing, thus fulfilling the requirement of zero micro-discharge, specifically include the following: S141. Use electromagnetic field simulation software to perform multiple simulation analyses on the optimized design scheme. S142. Evaluate the micro-discharge suppression effect, further adjust the structural parameters and optimization measures based on the simulation results, continuously improve the scheme, and iterate repeatedly until the requirement of no micro-discharge is achieved.

10. The multi-scale correlation analysis method for micro-discharge suppression according to claim 9, characterized in that, The design comparison experiment in S15 verifies the effect of different insulation medium ratios, electric fields, and spatial arrangement optimization schemes on the suppression of micro-discharges. Specifically, it includes the following steps: S151. Prototypes with different optimization schemes are manufactured and tested under the same experimental conditions; S152. Using the Wiesmann test system equipment, the key performance indicators of the high-voltage power supply, such as output voltage, ripple, and stability, are tested and evaluated. S153. Monitor the micro-discharge status of the prototype under different operating conditions and record the number and intensity of micro-discharges.