A medium-high frequency magnetic element data analysis system

Abstract

The application discloses a kind of middle-high frequency magnetic element data analysis systems, specifically related to nanocrystalline strip detection field, including radiation environment simulation module, multidimensional characterization module, primary detection module, secondary analysis module, reliability evaluation module;Through establishing multidimensional detection and analysis model, the performance evaluation method of nanocrystalline strip under radiation environment is optimized;Through radiation environment simulation module generates different dose radiation environment and combines with physical structure, magnetic property and high frequency response characteristics, constructs the reliability evaluation system based on actual radiation condition;The evaluation system is used to identify the microstructure change of material in extreme environment, magnetic attenuation and frequency response distortion and other key problems, and then effectively predict the reliability and performance stability of nanocrystalline strip under long time, strong radiation condition, improve the adaptability of material in high requirement, high frequency environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nanocrystalline strip detection, and more particularly to a medium-high frequency magnetic element data analysis system. BACKGROUND

[0002] In the prior art, the study of the magnetic property changes of most magnetic materials in a strong radiation environment is limited to low-frequency applications, and the correlation understanding of the microstructure changes and performance decay mechanism induced by radiation is not comprehensive. However, the sensitivity of medium-high frequency magnetic elements to radiation is particularly critical, especially in extreme scenarios such as aerospace and nuclear energy.

[0003] Nanocrystalline strip has significant advantages in the application field of medium-high frequency magnetic elements due to its high permeability and low loss characteristics. However, there is a lack of systematic research and data support on the magnetic permeability decay, loss increase, and frequency response characteristics of nanocrystalline strip under strong radiation conditions, which has become a problem restricting its widespread application. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a medium-high frequency magnetic element data analysis system, which comprises a radiation environment simulation module, a multi-dimensional characterization module, a primary detection module, a secondary analysis module, and a reliability evaluation module to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme: a medium-high frequency magnetic element data analysis system, comprising a radiation environment simulation module, a multi-dimensional characterization module, a primary detection module, a secondary analysis module, and a reliability evaluation module;

[0006] The radiation environment simulation module simulates different doses of radiation environment through a radiation source, and the simulated radiation environment is used to place the nanocrystalline strip in a simulated scenario;

[0007] The multi-dimensional characterization module is used to characterize and detect the nanocrystalline strip after radiation through three dimensions, which are the first dimension, the second dimension, and the third dimension;

[0008] The primary detection module establishes a primary detection model based on the characterization and detection of the first dimension, the second dimension, and the third dimension. The primary detection module obtains a primary model detection value based on the primary detection model. If the primary model detection value deviates from the system preset primary model detection threshold range, it is listed as an abnormal material, otherwise it is normal;

[0009] The secondary analysis module analyzes the data of the nanocrystalline strip listed as an abnormal material through a secondary detection model. The secondary detection model includes dynamic testing of the magnetic properties of the nanocrystalline strip and evaluation of the frequency response characteristics;

[0010] The reliability evaluation module is used for evaluating the reliability of the nanocrystalline strip material based on the first detection model and the second detection model, and giving material optimization suggestions based on the obtained reliability evaluation in the radiation environment.

[0011] In a preferred embodiment, the first dimension of the first detection model of the first detection module includes physical structure characterization detection; the second dimension of the first detection model of the first detection module includes magnetic performance characterization detection; and the third dimension of the first detection model of the first detection module includes high-frequency response characteristic characterization detection.

[0012] In a preferred embodiment, the required radiation environment is generated by the radiation environment simulation module to test the response of the nanocrystalline strip material under different doses and frequencies; the radiation dose of the radiation source is D, and the energy distribution of the radiation source is E(ω), where ω is the frequency of the radiation source; the response R sim which is expressed by the following formula:

[0013]

[0014] where R sim (D,ω) is the response of the simulated radiation environment, indicating the environmental characteristics of the material under the radiation dose D and the frequency ω; D0 is the standard dose; E(ω) is the energy distribution function of the radiation source; is the ratio of the radiation dose to the standard dose; ω is the frequency of the radiation source; which indicates the integration of all frequencies to obtain the total radiation intensity of the radiation source at each frequency.

[0015] In a preferred embodiment, the characterization results are assumed to be represented as a three-dimensional vector by the multi-dimensional characterization module X1 represents the measurement results of the physical structure characterization; X2 represents the measurement results of the magnetic performance characterization; and X3 represents the measurement results of the high-frequency response characteristic characterization.

[0016] The comprehensive evaluation of X1, X2 and X3 is expressed by the following formula:

[0017] S=w1·f1(X1)+w2·f2(X2)+w3·f3(X3)

[0018] wherein X1 includes the geometric size, shape, thickness of the detection material; X2 includes the magnetic permeability, saturation magnetic flux density of the detection material; X3 includes the loss, frequency response characteristics of the detection material under high frequency; w1, w2, w3 are weight coefficients of each dimension respectively; f1(X1), f2(X2), f3(X3) are data processing functions of each dimension; S is the comprehensive evaluation result.

[0019] In a preferred embodiment, the first-level detection module uses the characterization result to calculate the first-level model detection value S1, and compares it with the first-level model detection threshold T1 to determine whether the material is abnormal. The output S1 of the first-level detection model is represented as:

[0020]

[0021] If S1 exceeds the preset threshold T1, it is determined to be abnormal.

[0022]

[0023] wherein w i is the weight coefficient of each dimension; f i (X i ) is the detection function of each dimension; and T1 is the first-level model detection threshold.

[0024] In a preferred embodiment, for abnormal materials, the second-level analysis module further analyzes the data through magnetic performance dynamic testing and frequency response characteristic evaluation. It is assumed that the result of the second-level analysis is S2.

[0025] S2 = a f mag (B, H) + β f freq (f, P)

[0026] wherein f mag (B, H) represents the dynamic testing function of the magnetic performance, B is the magnetic flux density, and H is the magnetic field strength; f freq (f, P) represents the frequency response characteristic evaluation function, f is the frequency, and P is the power loss; a and β are weight coefficients; S2 is the output value of the second-level detection model; and a, β are two weight coefficients.

[0027] In a preferred embodiment, the reliability evaluation module performs reliability evaluation of the material based on the results of the first-level detection model and the second-level detection model. The reliability evaluation value is denoted as R.

[0028] R = γ1 S1 + γ2 S2

[0029] Wherein S1 and S2 are the output values of the first and second detection models respectively; γ1 and γ2 are weight coefficients, used to reflect the importance of the result analysis of the first and second detection models in the reliability evaluation; the optimization suggestion O is obtained by the evaluation value R and the preset threshold value R thrcshold The comparison is obtained;

[0030]

[0031] Wherein R is the reliability evaluation value of the material; S1 and S2 are the results of the first and second detection respectively; γ1 and γ2 are weight coefficients.

[0032] In a preferred embodiment, X1 includes the geometric size, shape, thickness physical property data of the detected material; X2 includes the magnetic permeability, saturation magnetic flux density magnetic performance data of the detected material; X3 includes the loss, frequency response characteristic data of the detected material under high frequency;

[0033] In X1, it is assumed that the volume V of the material is determined by the thickness d, the width w, and the length l; X2 includes the detection of the magnetic permeability μ, the saturation magnetic flux density B s ; X3 represents the loss and frequency response of the material under high frequency, and it is assumed that the relationship between the loss P and the frequency f follows the Pearson distribution;

[0034]

[0035] Wherein X1 represents the measurement result of the physical structure characterization; f geometry (d, w, l) is a geometric shape function; d is the thickness; w is the width; l is the length; η is the geometric shape coefficient;

[0036] Wherein X2 represents the measurement result of the magnetic performance characterization; f max (μ, B s , H) is a magnetic performance function; μ is the magnetic permeability; B s is the saturation magnetic flux density; H is the magnetic field strength; H sat is the saturation magnetic field strength;

[0037] Wherein X3 represents the measurement result of the high frequency response characteristic characterization; f freq (f, P) is a frequency response characteristic evaluation function; f is the frequency, representing the frequency of electromagnetic wave or magnetic field change; P is the power loss; α is the frequency attenuation index, used to reflect the power relationship between the loss and the frequency; β is the exponential attenuation factor.

[0038] Technical effects and advantages of the present application:

[0039] 1. By establishing a multi-dimensional detection and analysis model, the performance evaluation method of nanocrystalline strip under radiation environment is optimized; the radiation environment simulation module generates different doses of radiation environment and is combined with physical structure, magnetic performance and high frequency response characteristics to construct a reliability evaluation system based on actual radiation conditions;

[0040] The evaluation system is used to identify the key problems such as microstructure change, magnetic decay and frequency response distortion of the material under extreme environment, and then effectively predict the reliability and performance stability of nanocrystalline strip under long-time and strong radiation conditions; through this technology, the adaptability of the material in high requirement and high frequency environment is improved, which provides important support for the design and application of high performance magnetic elements;

[0041] 2. The multi-dimensional characterization module is used to characterize the physical structure, magnetic performance and frequency response characteristics of the material in all directions, so as to avoid the errors or omissions caused by single-dimensional analysis; by analyzing the changes of physical size, surface integrity and chemical composition and the dynamic changes of magnetic performance, loss and frequency response, the multiple effects of radiation environment on the material are effectively captured, so as to provide accurate data support for the subsequent optimization and reliability prediction of the material;

[0042] 3. In addition, based on the cooperative work of the first-level detection model and the second-level analysis model, an efficient fault diagnosis effect is constructed; the first-level detection model can quickly screen out normal or abnormal samples according to the characterization data of physical structure and magnetic performance, if the material is abnormal, the second-level analysis module can perform in-depth analysis on the abnormal material through more detailed dynamic test of magnetic performance and evaluation of frequency response characteristics, and provide data basis for the final material optimization; the system makes the detection process of high frequency magnetic element in radiation environment more systematic and efficient, and has strong application breadth;

[0043] 4. By introducing the comprehensive reliability evaluation module, the application safety and long-term stability of nanocrystalline strip are effectively improved; the reliability evaluation module not only combines the results of first-level and second-level detection, but also evaluates the long-term tolerance of the material according to the experimental data under different radiation environments, and deduces the targeted material optimization suggestion; through this mechanism, the performance degradation problem of the material in radiation environment is avoided, and strong support is provided for fault prevention and material selection in actual application. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 The system flowchart of the present application. DETAILED DESCRIPTION

[0045] Clearly, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0046] With reference to the drawings of the embodiments of the present application, Figure 1 An embodiment of the present application is a middle-high frequency magnetic element data analysis system, which comprises a radiation environment simulation module, a multi-dimensional characterization module, a first-level detection module, a second-level analysis module, and a reliability evaluation module.

[0047] The radiation environment simulation module simulates different dose radiation environments through a radiation source, and the simulated radiation environment is used to place the nanocrystalline strip in a simulated scene.

[0048] The multi-dimensional characterization module is used to characterize and detect the nanocrystalline strip after radiation through three dimensions, i.e., a first dimension, a second dimension, and a third dimension.

[0049] The first-level detection module establishes a first-level detection model based on the characterization and detection of the first dimension, the second dimension, and the third dimension. The first-level detection module obtains a first-level model detection value based on the first-level detection model. If the first-level model detection value deviates from a system preset first-level model detection threshold range, it is listed as an abnormal material, otherwise it is normal.

[0050] The second-level analysis module analyzes the data of the nanocrystalline strip listed as an abnormal material through a second-level detection model. The second-level detection model includes dynamic testing of the magnetic properties of the nanocrystalline strip and evaluation of the frequency response characteristics.

[0051] The reliability evaluation module is used to evaluate the reliability of the nanocrystalline strip that has completed the data analysis of the second-level detection model based on the first-level detection model and the second-level detection model. Based on the reliability evaluation obtained in the radiation environment, the material optimization suggestion is given.

[0052] The first dimension included in the first-level detection model of the first-level detection module includes physical structure characterization detection. The second dimension included in the first-level detection model of the first-level detection module includes magnetic property characterization detection. The third dimension included in the first-level detection model of the first-level detection module includes high frequency response characteristic characterization detection.

[0053] The radiation environment required is generated through the radiation environment simulation module to test the response of the nanocrystalline strip under different doses and frequencies. The radiation dose of the radiation source is D, and the energy distribution of the radiation source is E(ω), where ω is the frequency of the radiation source. The response R of the radiation environment simulated by the radiation environment simulation module is sim which is expressed by the following formula:

[0054]

[0055] wherein R sim (D, ω) is the response of the simulated radiation environment, representing the environmental characteristics of the material at the radiation dose D and the frequency ω; D is the radiation dose, representing the intensity of the radiation; D0 is the standard dose, set as a reference value of the conventional radiation dose, used for standardizing the radiation dose; E(ω) is the energy distribution function of the radiation source, representing the radiation intensity at different frequencies ω; is the ratio of the radiation dose to the standard dose, used for calibrating the relative change of the radiation intensity; ω is the frequency of the radiation source, representing the frequency distribution of the radiation; represents the integration of all frequencies, so as to obtain the total radiation intensity of the radiation source at each frequency; the target of the radiation environment simulation module is to simulate the radiation environment under different frequencies and dose conditions, and to provide basic data for subsequent tests.

[0056] The characterization result assumed by the multi-dimensional characterization module is represented as a vector containing three dimensions X1 represents the measurement result of the physical structure characterization; X2 represents the measurement result of the magnetic property characterization; X3 represents the measurement result of the high-frequency response characteristic characterization;

[0057] The comprehensive evaluation of X1, X2, X3 is represented by the following formula:

[0058] S = w1·f1(X1) + w2·f2(X2) + w3·f3(X3)

[0059] wherein is used to represent the three-dimensional characterization data vector, containing different material characteristic data; X1 includes the physical characteristic data of the detected material, such as geometric size, shape, thickness, etc.; X2 includes the magnetic property data of the detected material, such as permeability, saturation magnetic flux density, etc.; X3 includes the characteristic data of the detected material under high frequency, such as loss, frequency response, etc.; w1, w2, w3 are weight coefficients of each dimension, used to reflect the weight of each dimension in the overall evaluation or determined by engineering experience; f1(X1), f2(X2), f3(X3) are data processing functions of each dimension, which convert the physical structure, magnetic property and frequency response characteristics into comparable values; S is the comprehensive evaluation result, representing the overall performance of the material after radiation; a higher S value indicates that the performance of the material is better, which meets the expected Through the characterization detection of the three dimensions, the performance changes of the material after radiation can be comprehensively evaluated.

[0060] The first detection module uses the characterization result to calculate the first model detection value S1, and compares it with the first model detection threshold T1 to determine whether the material is abnormal. The output S1 of the first detection model is represented as:

[0061]

[0062] If S1 exceeds the preset threshold T1, it is determined to be abnormal;

[0063]

[0064] where S1 is the first model detection value, representing the comprehensive detection value, for evaluating whether the material meets the standard; w i is the weight coefficient of each dimension, reflecting the importance of physical structure, magnetic properties and high-frequency response characteristics in the total detection value; f i (X i ) is the detection function of each dimension, which converts the characterization data of each dimension into digital performance results; T1 is the first model detection threshold, set to a certain standard value, exceeding which determines that the material is abnormal; S1>T1 is when the calculation result S1 exceeds the threshold, it is determined that the material is abnormal; otherwise, the material is normal; The purpose of this step is to screen out materials that meet the requirements through comprehensive detection value, if the performance of the material exceeds the standard threshold, further analysis is needed.

[0065] For abnormal materials, the secondary analysis module further analyzes the data through dynamic testing of magnetic properties and evaluation of frequency response characteristics; assuming the result of secondary analysis is S2;

[0066] S2=α·f mag (B,H)+β·f freq (f,P)

[0067] where f mag (B,H) represents the dynamic testing function of magnetic properties, B is the magnetic flux density, and H is the magnetic field strength; f freq (f,P) represents the frequency response characteristic evaluation function, f is the frequency, and P is the power loss; α and β are weight coefficients, used to determine the influence of magnetic property testing and frequency response evaluation in the total result; S2 is the output value of the second detection model, representing the detailed performance evaluation result of the material; f mag (B,H) is based on the dynamic testing of magnetic properties, representing the relationship between the magnetic flux density B and the magnetic field strength H; B is the magnetic flux density, representing the number of magnetic lines per unit area of the material under the action of the magnetic field; H is the magnetic field strength, representing the strength of the magnetic field in which the material is located, affecting the magnetic response of the material; f freq(f, P) is the frequency response characteristic evaluation, representing the relationship between frequency f and power loss P, mainly evaluating the loss characteristics of the material at high frequencies; f is the frequency, representing the frequency of the radiation or electrical signal; P is the power loss, representing the energy loss of the material at a certain frequency; a, b are two weight coefficients, used to adjust the contribution of magnetic properties and frequency response characteristics in the result, and the secondary analysis module performs more accurate performance analysis on the material through the magnetic properties and frequency response characteristic evaluation.

[0068] The reliability evaluation module evaluates the reliability of the material based on the results of the primary detection model and the secondary detection model; and the reliability evaluation value is R;

[0069] R = γ1·S1+ γ2·S2

[0070] wherein S1 and S2 are the output values of the primary detection model and the secondary detection model respectively; γ1 and γ2 are weight coefficients, used to reflect the importance of the result analysis of the primary detection model and the secondary detection model in the reliability evaluation; the optimization suggestion O is obtained by comparing the evaluation value R with a preset threshold R thrcshold The comparison result is obtained as follows:

[0071]

[0072] wherein R is the reliability evaluation value of the material, representing its adaptability and long-term stability in the radiation environment; S1, S2 are the results of the primary detection and the secondary analysis, respectively, comprehensively evaluating the performance of the material; γ1, γ2 are weight coefficients, respectively representing the importance of the primary detection and the secondary analysis in the evaluation; O is the optimization suggestion, representing whether the material needs to be optimized according to the evaluation result; R thrcshold is the set reliability evaluation threshold, if R is less than R thrcshold , it means that the material needs to be optimized. The reliability evaluation module comprehensively evaluates the detection results of the material to propose a targeted optimization suggestion, ensuring the long-term stability of the material in the radiation environment.

[0073] X1 includes the geometric size, shape, thickness of the material, and physical property data; X2 includes the magnetic permeability and saturation magnetic flux density of the material, and magnetic property data; X3 includes the loss and frequency response characteristic data of the material at high frequencies;

[0074] In X1, it is assumed that the volume V of the material is determined by the thickness d, the width w, and the length l; X2 includes the detection of the magnetic permeability μ and the saturation magnetic flux density B s ; X3 represents the loss and frequency response of the material at high frequencies, and it is assumed that the relationship between the loss P and the frequency f follows the Pearson distribution;

[0075]

[0076] where X1 represents the measurement results of physical structure characterization; f geometry (d, w, l) is the geometric shape function, which combines the geometric dimensions d, w, l of the material; d is the thickness, representing the size of the material in the vertical direction; w is the width, representing the lateral size of the material; l is the length, representing the longitudinal size of the material; η is the geometric shape coefficient, used to adjust the volume calculation under different shapes, suitable for complex geometric shapes (such as non-rectangular, irregular shape supplementary factor); through the formula of X1, the overall geometric size of the material is obtained, and used to evaluate the structural stability and space occupation of the material;

[0077] where X2 represents the measurement results of magnetic performance characterization, indicating the magnetic response ability of the material; f max (μ, B s , H) is the magnetic performance function, which comprehensively considers the magnetic permeability μ, saturation magnetic flux density B s and magnetic field strength H; μ is the magnetic permeability, indicating the magnetic response ability of the material under external magnetic field; B s is the saturation magnetic flux density, indicating the magnetic flux density of the material in the saturation magnetization state; H is the magnetic field strength, indicating the strength of the externally applied magnetic field; H sat is the saturation magnetic field strength, the magnetic field strength when the material reaches saturation magnetization; the formula of X2 integrates the characteristics of magnetic permeability and magnetic flux density, and introduces the nonlinear effect of magnetic field strength on the magnetic performance of the material;

[0078] where X3 represents the measurement results of high-frequency response characterization, indicating the loss and response of the material at different frequencies; f freq (f, P) is the frequency response characteristic evaluation function, indicating the loss change of the material at different frequencies; f is the frequency, indicating the frequency of electromagnetic wave or magnetic field change; P is the power loss, indicating the energy loss of the material at a certain frequency; α is the frequency attenuation index, used to reflect the power relationship between loss and frequency; β is the exponential attenuation factor, indicating how the loss of the material increases exponentially with the increase of frequency; the loss characteristics of the material in high-frequency electromagnetic environment are embodied in the formula of X3, which comprehensively considers the relationship between frequency and loss, and introduces the nonlinear behavior of frequency attenuation.

[0079] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A system for analyzing data of a middle-high frequency magnetic element, comprising a radiation environment simulation module, a multi-dimensional characterization module, a first-level detection module, a second-level analysis module, and a reliability evaluation module, and characterized in that: the radiation environment simulation module simulates different doses of radiation environment through a radiation source, and the simulated radiation environment is used to place a nanocrystalline strip in a simulated scene; the multi-dimensional characterization module is used to characterize and detect the nanocrystalline strip after radiation through three dimensions, which are a first dimension, a second dimension, and a third dimension; the first-level detection module establishes a first-level detection model based on the characterization and detection of the first dimension, the second dimension, and the third dimension; the first-level detection module obtains a first-level model detection value based on the first-level detection model; if the first-level model detection value deviates from a system preset first-level model detection threshold range, the nanocrystalline strip is listed as an abnormal material, otherwise, it is normal; the second-level analysis module performs data analysis on the nanocrystalline strip listed as an abnormal material through a second-level detection model, which includes a dynamic test of magnetic properties of the nanocrystalline strip and a frequency response characteristic evaluation; the reliability evaluation module is used to evaluate the reliability of the nanocrystalline strip that has completed the data analysis of the second-level detection model based on the first-level detection model and the second-level detection model, and give material optimization suggestions based on the reliability evaluation obtained in the radiation environment; the first dimension included in the first-level detection model of the first-level detection module includes physical structure characterization detection; the second dimension included in the first-level detection model of the first-level detection module includes magnetic property characterization detection; and the third dimension included in the first-level detection model of the first-level detection module includes high frequency response characteristic characterization detection. 2.The system of claim 1, characterized in that: 3.The system of claim 2, characterized in that: the comprehensive evaluation of X1, X2, and X3 is represented by the following formula: S=w1·f1(X1)+w2·f2(X2)+w3·f3(X3) wherein X1 includes geometric size, shape, and thickness physical property data of the detected material; X2 includes permeability and saturation magnetic flux density magnetic property data of the detected material; X3 includes loss and frequency response characteristic data of the detected material under high frequency; w1, w2, and w3 are weight coefficients of each dimension; f1(X1), f2(X2), and f3(X3) are data processing functions of each dimension; and S is a comprehensive evaluation result. 4.The system of claim 3, characterized in that: if S1 exceeds a preset threshold T1, it is determined to be abnormal. 5.The system of claim 4, characterized in that: for the abnormal material, the second-level analysis module further performs data analysis through the dynamic test of magnetic properties and the evaluation of frequency response characteristics; and assuming that the result of the second-level analysis is S2. The required radiation environment is generated by the radiation environment simulation module to test the response of the nanocrystalline ribbon under different doses and frequencies; the radiation dose of the radiation source is D, and the energy distribution of the radiation source is E(ω), wherein ω is the frequency of the radiation source; the radiation environment response R simulated by the radiation environment simulation module is represented by the following formula: sim is represented by the following formula: where R sim (D, ω) is the response to the simulated radiation environment, representing the environmental characteristics of the material at a radiation dose D and a frequency ω; D0is the standard dose; E(ω) is the energy distribution function of the radiation source; is the ratio of the radiation dose to the standard dose; ω is the frequency of the radiation source; represents the integration over all frequencies, thus obtaining the total radiation intensity of the radiation source at each frequency. 6.The system of claim 5, characterized in that: The characterization result assumed by the multi-dimensional characterization module is represented as a vector containing three dimensions X1 represents the measurement result of the physical structure characterization; X2 represents the measurement result of the magnetic property characterization; and X3 represents the measurement result of the high-frequency response characteristic characterization. ​ ​ ​ ​ The first level detection module uses the characterization results to calculate a first level model detection value S1, and compares it with a first level model detection threshold T1 to determine whether the material is abnormal. The output S1 of the first level detection model is represented as: ​ where w i is the weight coefficient for each dimension; f i (X i ) is the detection function for each dimension; T1 is the first-level model detection threshold. ​ ​ S2 = a - f mag (B, H) + β - f freq (f, P) where f mag (B, H) represents a dynamic test function of magnetic performance, B is magnetic flux density, and H is magnetic field strength; f freq (f, P) represents a frequency response characteristic evaluation function, f is frequency, and P is power loss; α and β are weight coefficients; S2 is an output value of a second-level detection model; and α and β are two weight coefficients. ​ The reliability evaluation module evaluates the reliability of the material based on the results of the primary detection model and the secondary detection model; and drafts a reliability evaluation value R; R = γ1·S1 + γ2·S2 wherein S1 and S2 are output values of the first detection model and the second detection model, respectively; γ1 and γ2 are weight coefficients for reflecting the importance of the result analysis of the first detection model and the second detection model in the reliability evaluation; the optimization suggestion O is obtained by the evaluation value R and a preset threshold R thrcshold The comparison shows that; wherein R is the reliability evaluation value of the material; S1 and S2 are respectively the results of the primary detection and the secondary analysis; and γ1 and γ2 are weight coefficients.

7. The data analysis system of a medium-high frequency magnetic element according to claim 6, characterized in that: X1 includes the physical characteristic data of the geometric size, shape and thickness of the detected material; X2 includes the magnetic performance data of the magnetic permeability and saturation magnetic flux density of the detected material; and X3 includes the characteristic data of the loss and frequency response of the detected material under high frequency; In X1, the volume V of the material is assumed to be determined by the thickness d, the width w, and the length l; X2 includes detecting the magnetic permeability μ, the saturation magnetic flux density B s ; X3 represents the loss and frequency response of the material at high frequencies, assuming that the relationship between the loss P and the frequency f follows a Pearson distribution; where X1represents a measurement of a physical structural representation; f geometry (d, w, l) are geometry functions; d is thickness; w is width; l is length; η is a geometric shape coefficient. where X2represents a measured result of a magnetic property representation; f max (μ, B s , H) is a magnetic property function; μ is magnetic permeability; B s is saturation magnetic flux density; H is magnetic field strength; H sat is saturation magnetic field strength; where X3represents a measured result of a high frequency response characteristic; f freq (f, P) is a frequency response characteristic evaluation function; f is frequency, indicating the frequency of electromagnetic wave or magnetic field variation; P is power loss; a is a frequency attenuation index, used to reflect the power relationship between loss and frequency; b is an exponential attenuation factor.

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