A method for quickly determining parameters of an inductive conductivity sensor probe

Abstract

The application discloses a method for quickly determining parameters of an inductive conductivity sensor probe, belongs to the technical field of electromagnetic induction probes, and is used for parameter setting of an electromagnetic induction probe.The method comprises the following steps: based on the electromagnetic induction principle and the skin effect characteristics of an inductive conductivity sensor, a quantitative correlation between parameters is established by introducing a probe geometry-frequency comprehensive factor and a thermal-magnetic balance factor, and a multi-physical field simulation is combined to realize quick optimization of the probe parameters.Based on the probe geometry-frequency comprehensive factor and the thermal-magnetic balance factor, the quantitative correlation between the parameters is established through theoretical derivation, the parameters are quickly determined, the parameters such as the excitation frequency, the magnetic ring size, the spacing and the number of turns are matched in a coordinated manner, the sensor performance is stable, the parameters can be flexibly adjusted according to different detection objects and scenes, the applicability is wider, the parameter rationality can be verified before actual production through the introduction of a multi-physical field simulation verification link, and the research and development risk is reduced.

Description

TECHNICAL FIELD

[0001] The application discloses a method for quickly determining parameters of an inductive conductivity sensor probe and belongs to the technical field of electromagnetic induction probes. BACKGROUND

[0002] Electromagnetic induction probes are widely used in industrial nondestructive testing, marine resource exploration, biomedical detection and other fields. The core function implementation of an electromagnetic induction conductivity sensor depends on the probe structure, and the rationality of the design directly determines the measurement accuracy, environmental adaptability and application scenario expansion capability of the sensor. As a key component for interaction between the sensor and the measured medium, the research on the probe is always focused on solving technical bottlenecks in practical applications, and the core performance index directly affects the detection accuracy and equipment reliability. The probe structure is mainly composed of an excitation coil, a detection coil, a magnetic core and a shell, and the design parameters of each part jointly determine the core performance index.

[0003] The traditional probe design relies on the experience of engineers to adjust the number of turns of the coil, the size of the magnetic ring, the excitation frequency and other parameters, and is optimized through the cycle of “physical prototype production → experimental test → parameter iteration”. The single prototype production cycle is about 1 week to 2 weeks, and a single set of experiments needs to test more than 50 parameter combinations, and the complete design cycle generally exceeds 3 months. Moreover, due to the limitations of processing precision and test environment, the repeatability error of experimental data is as high as 15% to 20%.

[0004] Generally, the design mainly relies on experience-based parameter selection and full-range simulation scanning, and the core idea is: based on the experience of engineers, the approximate range of the coil spacing, excitation frequency, coil radius and number of turns is preliminarily set, and then the parameters are scanned through an electromagnetic simulation tool, and finally the parameter combination with the maximum sensor sensitivity or signal strength is selected. The setting of the initial range of parameters depends on the experience of engineers and lacks theoretical support, which easily leads to parameter combination redundancy and increases the simulation cost. The full-range scanning needs to process a large number of parameter combinations, which requires a large amount of computing resources, a long design cycle and low simulation efficiency. SUMMARY

[0005] The purpose of the present application is to provide a method for quickly determining the parameters of an inductive conductivity sensor probe, to solve the problem in the prior art that a large number of experimental verifications are needed to determine the parameters of an inductive conductivity sensor probe, the design cycle is long, the cost is high, and the global optimal parameter combination cannot be automatically searched, and it is difficult to balance multiple indexes such as sensitivity and signal strength.

[0006] A method for quickly determining the parameters of an inductive conductivity sensor probe, comprising:

[0007] S1. Define the probe geometric frequency synthesis factor based on the skin depth formula and the magnetic ring spacing. Determine the maximum sensor sensitivity based on the probe geometric frequency synthesis factor and determine the quantitative relationship between the magnetic ring spacing and the excitation frequency. Define the thermomagnetic balance factor based on the magnetic field energy and heat loss. Calculate the number of coil turns based on the thermomagnetic balance factor. Control the detection depth, optimize the frequency and geometric parameters through the skin depth. The geometric parameters are the magnetic ring size and the number of coil turns. Establish the quantitative relationship between the probe parameters through the probe geometric frequency synthesis factor and the thermomagnetic balance factor to achieve rapid determination of the probe parameters.

[0008] S2. Based on the conductivity range of the measured medium, extract the reference conductivity, and establish preliminary probe parameters by setting the magnetic ring spacing, skin depth and thermal balance factor.

[0009] S3. Electromagnetic induction simulation is achieved based on multiphysics simulation software. A four-layer model architecture is created in the multiphysics simulation software, including a global parameter layer, a geometric parameter layer, a material property layer, and a physical field layer, combined with the initial probe parameters. The electromagnetic induction parameters are analyzed and optimized by combining the four-layer model architecture, frequency domain coupling simulation, and multi-objective optimization to obtain the optimal design scheme.

[0010] S1 includes, S1.1, introducing the skin depth formula:

[0011] ;

[0012] ;

[0013] ;

[0014] In the formula, To reach skin depth, Pi For the excitation frequency, Permeability, For dielectric conductivity, The permeability of free space, Relative permeability;

[0015] Through the magnetic ring spacing and Determine the probe's geometric frequency synthesis factor :

[0016] ;

[0017] pass Optimize probe sensitivity ,when hour, Reaching peak value; after adding noise factor, The optimal interval is ; based on establish and quantitative relationship.

[0018] S1 includes S1.2, defining equilibrium constant:

[0019] ;

[0020] ;

[0021] ;

[0022] In the formula, is the equilibrium constant, is the magnetic field energy, is the magnetic field, is the heat loss, is the inductance, is the current, is the resistance; by setting control the magnetic field strength and temperature rise of the coil, and calculate the number of turns:

[0023] ;

[0024] In the formula, is the number of turns, is the average radius of the magnetic ring, is the resistivity, is the total length of the coil, is the wire radius, is the effective cross-sectional area of the magnetic core; by control the detection depth, optimize the frequency and geometric parameters, optimize the probe sensitivity, optimize the number of turns of the coil, realize the rapid determination of the probe parameters.

[0025] S2 includes obtaining preliminary probe parameters: based on the conductivity range of the measured medium, extracting reference , Take the range median; set , according to get ; set , according to design the size of the magnetic ring, including the outer diameter, inner diameter and height; set , combined with the determined geometric parameters, calculate .

[0026] S3 includes S3.1, based on multi-physical field simulation software to realize electromagnetic induction simulation: in the multi-physical field simulation software, according to the preliminary probe parameters, architecture global parameter layer, set and ;Architectural geometry parameter layer, settings Magnetic ring size , And excitation voltage; construct material property layer, set up three-dimensional models of excitation magnetic ring, induction magnetic ring, magnetic ring coil, probe shell and external field, and define the material of each model;

[0027] S3 includes S3.2, which involves structuring a physical field layer in a multiphysics simulation software, setting up two physical fields, selecting a magnetic field in the components, adding two coils, with coil 1 serving as the excitation coil and using alternating voltage excitation, setting the input direction of coil 1 to match the actual coil winding direction; coil 2 serving as the induction coil and set to an open circuit state; finally, setting up the mesh, using an ultrafine mesh to ensure the accuracy of the results, and adding COMSOL transient studies for alternating calculations.

[0028] S3 includes S3.3, fixed. , and Change the test Record different Induced voltage of the lower receiving coil ,Establish curve, Parsing the expression:

[0029] ;

[0030] In the formula, Proportional to, Angular frequency, is the base of the natural logarithm. To pair the parameters The contributions are integrated into a dimensionless factor.

[0031] S3 includes S3.4, fixed. and By adjusting Change ; different calculations corresponding ,draw curve.

[0032] S3 includes S3.5, and the coupling coil via a multiphysics simulation software circuit module. and calculate The temperature rise of the coil was analyzed using the heat conduction module of multiphysics simulation software; the following was extracted. and ,calculate And record and .

[0033] S3 comprises, S3.6, if curve in and Not positively correlated, by adjusting or To adjust , until and Positive correlation;

[0034] If The curve does not appear peak when , and When Not maintained around the peak, by adjusting or To adjust , until Fall into the optimal interval;

[0035] If Deviation from the set value, and the coil temperature rise exceeds the material tolerance limit, by adjusting To adjust and , until and Balance, according to the adjusted Recalculate , by adjusting and Optimize and Matching.

[0036] S3 comprises, S3.7, the adjusted probe parameters are re-input into the multi-physical field simulation software, the four-layer architecture, the frequency domain coupling simulation and the multi-objective optimization are combined, and the probe parameters are optimized until the probe parameter performance meets the preset;

[0037] S3 comprises, S3.8, if the probe parameter performance meets the preset, the optimal parameters are output, and the optimal design scheme is obtained.

[0038] Compared with the prior art, the present application has the following beneficial effects: the present application is based on the probe geometry-frequency comprehensive factor and the thermal-magnetic balance factor, the quantitative relationship between the parameters is established through theoretical derivation, the parameters are quickly determined, the excitation frequency, the magnetic ring size, the spacing, the number of turns and other parameters are matched, the sensor performance is stable, the parameters can be flexibly adjusted according to different detection objects and scenes, the applicability is wider, the parameter rationality can be verified before actual production through the introduction of the multi-physical field simulation verification link, and the research and development risk is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 for the flow chart of the present application;

[0040] Figure 2 for the sensitivity and probe geometry-frequency comprehensive factor curve;

[0041] Figure 3 for the schematic diagram of the three-dimensional modeling of the probe;

[0042] Figure 4 for the grid distribution diagram of the probe;

[0043] Figure 5 for the magnetic ring magnetic flux density mode cloud diagram at 1 second;

[0044] Figure 6 for the magnetic ring magnetic flux density mode cloud diagram at 1 second;

[0045] Figure 7 for the magnetic ring magnetic flux density mode cloud diagram at 1 second;

[0046] Figure 8 for the linearity diagram of the conductivity and induced voltage. DETAILED DESCRIPTION

[0047] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below. Obviously, the described embodiments are 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 skilled in the art without creative labor fall within the protection scope of the present application.

[0048] A method for quickly determining the parameters of an inductive conductivity sensor probe, comprising:

[0049] S1, defining the probe geometry frequency comprehensive factor according to the skin depth formula and the magnetic ring spacing, determining the maximum sensor sensitivity according to the probe geometry frequency comprehensive factor, and determining the quantitative relationship between the magnetic ring spacing and the excitation frequency, defining the thermal magnetic balance factor according to the magnetic field energy and the heat loss, calculating the coil turns according to the thermal magnetic balance factor, controlling the detection depth through the skin depth, optimizing the frequency and the geometry parameters, the geometry parameters being the magnetic ring size and the coil turns, and establishing the quantitative relationship between the probe parameters through the probe geometry frequency comprehensive factor and the thermal magnetic balance factor, to realize the quick determination of the probe parameters;

[0050] S2, extracting the reference conductivity based on the conductivity range of the measured medium, and establishing the preliminary probe parameters through setting the magnetic ring spacing, the skin depth and the thermal balance factor;

[0051] S3. Electromagnetic induction simulation is achieved based on multiphysics simulation software. A four-layer model architecture is created in the multiphysics simulation software, including a global parameter layer, a geometric parameter layer, a material property layer, and a physical field layer, combined with the initial probe parameters. The electromagnetic induction parameters are analyzed and optimized by combining the four-layer model architecture, frequency domain coupling simulation, and multi-objective optimization to obtain the optimal design scheme.

[0052] S1 includes, S1.1, introducing the skin depth formula:

[0053] ;

[0054] ;

[0055] ;

[0056] In the formula, To reach skin depth, Pi For the excitation frequency, Permeability, For dielectric conductivity, The permeability of free space, Relative permeability;

[0057] Through the magnetic ring spacing and Determine the probe's geometric frequency synthesis factor :

[0058] ;

[0059] pass Optimize probe sensitivity ,when hour, Reaching peak value; after adding noise factor, The optimal interval is ;based on Establish and The quantitative relationship.

[0060] S1 includes S1.2, and the definition of the equilibrium constant:

[0061] ;

[0062] ;

[0063] ;

[0064] In the formula, It is the equilibrium constant. For magnetic field energy, For the magnetic field, For the heat loss, For the inductance, For the current, For the resistance; by setting The magnetic field intensity and temperature rise of the coil are controlled, and the number of turns is calculated:

[0065] ;

[0066] In the formula, The number of turns, The average radius of the magnetic ring, The resistivity, The total length of the coil, The wire radius, The effective cross-sectional area of the magnetic core; by Control the detection depth, optimize the frequency and geometric parameters, Optimize the sensitivity of the probe, Optimize the number of turns of the coil to quickly determine the probe parameters.

[0067] S2 includes obtaining preliminary probe parameters: based on the conductivity range of the measured medium, extracting reference , Taking the range median; setting , according to Obtain ; set , according to Design the size of the magnetic ring, including the outer diameter, inner diameter and height; set , combined with the determined geometric parameters, calculate .

[0068] S3 includes S3.1, realizing electromagnetic induction simulation based on multi-physical field simulation software: in the multi-physical field simulation software, according to the preliminary probe parameters, constructing a global parameter layer, setting And ; construct a geometric parameter layer, set , magnetic ring size, , And excitation voltage; construct a material attribute layer, set the three-dimensional models of the excitation magnetic ring, the induction magnetic ring, the magnetic ring coil, the probe shell and the external field, define the materials of each model;

[0069] S3 includes, S3.2, in the multi-physical field simulation software, the physical field layer is constructed, two physical fields are set, the magnetic field is selected in the component, two coils are added, coil 1 is used as an excitation coil, an alternating voltage is used for excitation, the input direction of coil 1 is set, so that coil 1 conforms to the actual coil winding direction; coil 2 is used as an induction coil and is set to an open circuit state; finally, mesh setting is carried out, super-fine mesh is used to ensure the accuracy of the result, and COMSOL transient study is added for alternating calculation.

[0070] S3 includes, S3.3, fixing , and , changing the measured ; the induced voltage of the receiving coil under different is recorded , a curve is established , and an analytical expression is obtained:

[0071] ;

[0072] wherein, is proportional to, is the angular frequency, is the base of natural logarithm, is the contribution of the parameter pair to the dimensionless factor.

[0073] S3 includes, S3.4, fixing and , changing by adjusting ; the corresponding of different is calculated, and a curve is drawn.

[0074] S3 includes, S3.5, the and of the coupled coil are calculated by the circuit module of the multi-physical field simulation software, the coil temperature rise is analyzed in combination with the heat conduction module of the multi-physical field simulation software; the and are extracted, the is calculated, and the and are recorded.

[0075] S3 includes, S3.6, if the and in the curve are not positively correlated, the or is adjusted to adjust the , until the and It is positively correlated;

[0076] like The curve is No peak was observed at that time, and hour It did not remain near the peak, so adjustments were made. or To adjust until It falls into the optimal range;

[0077] like If the value deviates from the set value and the coil temperature rise exceeds the material's tolerance limit, adjust accordingly. To adjust and until and Balance, based on the adjusted Recalculate By adjusting and optimization and Matching properties.

[0078] S3 includes S3.7, re-entering the adjusted probe parameters into the multiphysics simulation software, and optimizing the probe parameters by combining the four-layer architecture, frequency domain coupling simulation and multi-objective optimization until the probe parameter performance meets the preset.

[0079] S3 includes S3.8, if the probe parameters and performance meet the preset requirements, output the optimal parameters to obtain the optimal design scheme.

[0080] based on Establish and The derivation process of the quantitative relationship is as follows:

[0081] Induced voltage The parsing expression is:

[0082] ;

[0083] S is defined as:

[0084] ;

[0085] In the formula, For partial derivatives; substitute into Expression and differentiation:

[0086] ;

[0087] make :

[0088] ;

[0089] wherein, is the absolute value, wherein:

[0090] ;

[0091] Therefore:

[0092] ;

[0093] Thus:

[0094] ;

[0095] Let , the extreme point can be obtained, approximate analysis shows that when (i.e. ), approaches the maximum value, so define:

[0096] ;

[0097] When , reaches the peak value, considering the noise and other factors in practical application, the optimal interval is , as shown in Figure 2 , in fact, due to different models, different parameters, the optimal value may be biased to 0.8 or 1.2, but the overall peak interval is in ; through this correlation, the parameter range of and can be directly compressed from infinite space to the theoretical optimal interval, avoiding blind selection.

[0098] The derivation process of is as follows: First, calculate the resistance, define the inductance of the coil

[0099] and , the coil is determined by the wire length and material, the total length of the coil is:

[0100] ;

[0101] The cross-sectional area of the wire is:

[0102] ;

[0103] Combining and , we get :​

[0104] ;

[0105] Then, inductance calculation is carried out, the inductance of the coil is proportional to the square of the magnetic core parameters and , and the calculation of :

[0106] ;

[0107] In the formula, is the average radius of the magnetic ring;

[0108] According to the size of the magnetic ring, the value of is determined as:

[0109] ;

[0110] The thermal magnetic equilibrium factor is:

[0111] ;

[0112] Substitute and :

[0113] ;

[0114] Simplify and solve :

[0115] .

[0116] The flowchart of the present application is shown as Figure 1 : first, design the parameter factors and , and derive the parameter factors and , input the probe parameters, combine the parameter factors and to calculate the reference parameters, determine the quantitative relationship between the probe parameters, generate a preliminary parameter combination based on the given parameters, then perform simulation verification based on COMSOL, the process of simulation verification includes geometric modeling, mesh division, physical field setting, solution calculation and result extraction, performance evaluation of the final parameters, if the optimal conditions are not met, the parameter range is fine-tuned, the reference parameter calculation is performed again to the performance evaluation step, until the final parameters meet the optimal conditions, and the optimal parameters are output.

[0117] The embodiment of the present application first determines the probe parameters, Figure 3 is the probe model, based on the conductivity range of the measured medium, the reference (Taking the midpoint of the measurement range, since this invention is based on seawater measurement, a conductivity of 4 S / m is taken.) When the thickness is 10mm to 20mm, according to have to The frequency range is from 3000Hz to 13000Hz; the size of the magnetic ring also varies accordingly. The design outer diameter × inner diameter × height is as follows: (Unit: mm). Since the sensor operates for extended periods, temperature rise control is necessary; therefore, the appropriate temperature range is... The value is 2 (which can be adjusted appropriately), and then, based on the determined geometric parameters, calculations are performed. Required parameters; When the diameter is 10mm, the dimensions of the magnetic ring (outer diameter × inner diameter × height) are 20mm × 10mm × 10mm. The calculation yields 15 turns.

[0118] After obtaining the probe parameters, COMSOL simulation verification was performed. First, the parameters were set before calculation in COMSOL, specifically for the magnetic ring. Magnetic ring size , Configure the excitation voltage parameters by selecting the parameters in the global definition. and The required parameters will be helpful for future calculations.

[0119] Construct a three-dimensional model of the excitation magnetic ring, induction magnetic ring, magnetic ring coil, probe shell, and external field (seawater), and define the materials of each module, where the magnetic ring material is nanocrystal, the coil material is metallic copper, the shell material is POM (plastic: polyoxymethylene resin), and the external field material is seawater.

[0120] Set up two physical fields for the magnetic field. In the components, select Magnetic Field and add two coils. Coil 1 serves as the excitation coil, using alternating voltage excitation. Set its input direction to match the actual coil winding direction. Coil 2 serves as the induction coil and is set to an open-circuit state. Finally, configure the mesh, as follows: Figure 4 As shown, an ultrafine mesh (700,000 meshes, an average element mass of 0.669, indicating that most elements have low skewness and regular shape, and an element volume ratio of 0.001523, indicating good volume consistency and no obvious volume distortion) was used to ensure the accuracy of the results. Transient studies were added for alternating calculations. The ultrafine mesh is a built-in mesh setting function of COMSL used to solve the physical field model, and the alternating calculations are used to calculate the process of the excitation signal changing over time.

[0121] Then, combining a four-layer model architecture, frequency-domain coupled simulation, and multi-objective optimization, the electromagnetic induction parameters are analyzed and optimized. Frequency-domain coupled simulation involves simultaneously solving the governing equations of multiple interacting physical fields in the frequency domain, either directly or iteratively, to obtain the system's steady-state response at a specific frequency. Calculation verification is then performed. and Relationship and Matching The difference from the set value is then analyzed, and performance evaluation and parameter adjustment are performed. The specific steps are as follows:

[0122] If the sensitivity S is not in the peak range (i.e.) ),Depend on It can be seen that adjustments can be made. or make It falls into the optimal range. If It can increase or reduce ;like It can reduce or improve until S approaches its peak value;

[0123] like and The relationship deviates from the theoretical trend and needs to be examined. and Matching properties. If Follow Slow growth may be This leads to reduced detection efficiency, which can reduce or reduce To increase (make );like Too rapid decay may be... It can increase or improve To reduce ;

[0124] like Too high or Insufficient (i.e.) (Deviating from the set value) can be adjusted Achieving equilibrium: If the temperature rise is too high ( (Too large), can be reduced To reduce and The ratio; if the magnetic field strength is insufficient ( (Too small), can be increased .at the same time, It needs to be adjusted according to Recalculations can also be performed by adjusting or optimizing the match with .

[0125] If the performance does not meet the preset, the parameters can be adjusted and the calculation is performed again. If the performance meets the preset, the optimal parameters can be output.

[0126] The above method can quickly determine the parameters of the inductive conductivity sensor probe. By analyzing the physical model of the conductivity sensor, the influence of each parameter on the output voltage is studied, including frequency, core size, number of turns, magnetic permeability, etc. It is proved that the optimal parameters exist, and the optimal parameters are selected. Through simulation verification, the induced voltage, magnetic flux density module, and the distribution of magnetic field lines and current direction are calculated. The magnetic flux density module cloud distribution is uniform at each time, and the magnetic field line and current direction distribution conforms to the actual situation, as shown in Figure 5 、 Figure 6 、 Figure 7 , the excitation frequency is 20KHz, the period is , the magnetic ring magnetic flux density module (the beginning of a frequency period) at seconds, the magnetic ring magnetic flux density module (one quarter of a frequency period) at seconds, and the magnetic ring magnetic flux density module (three quarters of a frequency period) at seconds, it can be seen that the magnetic field directions of the two time points are opposite, which conforms to the actual magnetic field change law: within a frequency period, the magnetic flux density first increases and then decreases, and the cycle is repeated with the period. The spatial distribution of the solenoid magnetic field is that the central region has a strong magnetic field, the outer magnetic field is weak, and the measuring medium passes through the middle cylindrical flow channel, that is, the region with strong magnetic field distribution can better measure the medium through the magnetic field change. As shown in Figure 8 , the conductivity and induced voltage curve formula is , the linearity is 0.99917, which proves that the model has excellent linearity and high measurement accuracy, so that the system achieves the preset goal, and the production of the inductive conductivity sensor is reasonable and reliable; the magnetic flux density module formula is

[0127] ;

[0128] wherein 、 、 is the component of the magnetic field in the direction, is the amplitude of the magnetic field strength.

[0129] The above examples are only used for illustrating the technical solutions of the present application, and are not intended to limit the present application. Although the present application has been described in detail with reference to the foregoing examples, it should be understood by those skilled in the art that the technical solutions recorded in the foregoing examples can be modified, or some or all of the technical features can be replaced by equivalent replacements, and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of rapidly determining parameters of an inductive conductivity sensor probe, characterized by, The method comprises the following steps: S1, defining a probe geometry frequency comprehensive factor according to a skin depth formula and a magnetic ring spacing, determining maximum sensor sensitivity according to the probe geometry frequency comprehensive factor, determining a quantitative relationship between the magnetic ring spacing and the excitation frequency, defining a thermal magnetic balance factor according to the magnetic field energy and the heat loss, calculating the coil turns according to the thermal magnetic balance factor, controlling the detection depth through the skin depth, optimizing the frequency and the geometry parameters, the geometry parameters being the magnetic ring size and the coil turns, establishing a quantitative relationship between the probe parameters through the probe geometry frequency comprehensive factor and the thermal magnetic balance factor, and realizing the rapid determination of the probe parameters; S2, extracting a reference conductivity based on the conductivity range of the measured medium, and establishing preliminary probe parameters through the setting of the magnetic ring spacing, the skin depth and the thermal balance factor; S3, realizing electromagnetic induction simulation based on a multi-physical field simulation software, creating a four-layer model architecture in the multi-physical field simulation software based on the preliminary probe parameters, the four-layer model architecture comprising a global parameter layer, a geometry parameter layer, a material attribute layer and a physical field layer, analyzing and optimizing the electromagnetic induction parameters by combining the four-layer model architecture, the frequency domain coupling simulation and the multi-objective optimization, and obtaining an optimal design scheme.

2. The method for quickly determining parameters of an inductive conductivity sensor probe according to claim 1, characterized in that, S1 comprises S1.1, introducing a skin depth formula: ； ； ； wherein is the skin depth, is the circular constant, is the excitation frequency, is the magnetic permeability, is the medium conductivity, is the vacuum permeability, is the relative permeability; By magnetic ring spacing And Determining probe geometry frequency synthesis factor : ； By optimizing the sensitivity of the probe , when , reached the peak; after adding the noise factor, The optimal interval is ; based on establish and quantitative relationship.

3. A method of quickly determining parameters of an inductive conductivity sensor probe according to claim 2, characterized in that, S1 comprises S1.2, defining a balance constant: ； ； ； wherein is the equilibrium constant, is the magnetic field energy, is the magnetic field, is the thermal loss, is the inductance, is the current, is the resistance; by setting the magnetic field strength and temperature rise of the control coil, and calculating the number of turns: ； wherein, N is the number of turns, R is the average radius of the magnetic ring, ρ is the resistivity, L is the total length of the coil, r is the radius of the wire, A is the effective cross-sectional area of the magnetic core; through controlling the detection depth, optimizing the frequency and geometric parameters, optimizing the sensitivity of the probe, optimizing the number of turns of the coil, and achieving rapid determination of the probe parameters.

4. A method of quickly determining parameters of an inductive conductivity sensor probe according to claim 3, characterized in that, S2 comprises obtaining preliminary probe parameters: based on the conductivity range of the measured medium, extracting a reference , taking the range median; setting , according to obtaining ; setting , according to designing the magnetic ring size, the magnetic ring size comprising an outer diameter, an inner diameter and a height; Setting , in combination with the determined geometric parameters, the calculation .

5. A method of quickly determining parameters of an inductive conductivity sensor probe according to claim 4, characterized in that, S3 comprises S3.1, realizing electromagnetic induction simulation based on multi-physical field simulation software: in the multi-physical field simulation software, according to the preliminary probe parameters, a global parameter layer is constructed, and and ; Architecture geometry parameter layer, set , magnetic ring size, , and excitation voltage; Architecture material attribute layer, set up three-dimensional models of excitation magnetic ring, induction magnetic ring, magnetic ring coil, probe shell and external field domain, define the materials of each model; S3 comprises S3.2, constructing the physical field layer in the multi-physical field simulation software, setting two physical fields, selecting a magnetic field in the component, adding two coils, coil 1 being used as an excitation coil and being excited by an alternating voltage, setting the input direction of coil 1 so that coil 1 conforms to the actual coil winding direction, coil 2 being used as an induction coil and being set as an open circuit state, finally performing mesh setting and adopting super-fine mesh to ensure the accuracy of the results, and adding COMSOL transient study for alternating calculation.

6. A method of quickly determining parameters of an inductive conductivity sensor probe according to claim 5, characterized in that, S3 comprises, S3.3, fixing , and , changing the measured ; recording the induced voltage of the receiving coil under different , establishing curves, analytical expressions: ； wherein is proportional to, is the angular frequency, is the base of the natural logarithm, is the contribution of the parameter pair to be integrated into a dimensionless factor.

7. A method of quickly determining parameters of an inductive conductivity sensor probe according to claim 6, characterized in that, S3 comprises, S3.4, fixing and by adjusting changing ; calculating different corresponding , drawing curves.

8. A method of quickly determining parameters of an inductive conductivity sensor probe according to claim 7, characterized in that, S3 includes, S3.5, coupling the coil by the multi-physics simulation software circuit module and Calculate , analyze the coil temperature rise in combination with the multi-physics simulation software heat conduction module; extract and , calculate and record and .

9. A method of quickly determining parameters of an inductive conductivity sensor probe according to claim 8, characterized in that, S3 comprises, S3.6, if in the curve and not positively correlated, by adjusting or to adjust , until and positively correlated; like The curve is No peak was observed at that time, and hour It did not remain near the peak, so adjustments were made. or To adjust until Falling into the optimal range; If deviates from the set value and the coil temperature exceeds the material tolerance limit, the is adjusted and until and are balanced, the is recalculated , the and are adjusted and to optimize the matching.

10. A method of quickly determining parameters of an inductive conductivity sensor probe according to claim 9, characterized in that, S3 comprises S3.7, re-inputting the adjusted probe parameters into the multi-physical field simulation software, optimizing the probe parameters by combining the four-layer architecture, the frequency domain coupling simulation and the multi-objective optimization until the performance of the probe parameters meets the preset; S3 comprises S3.8, if the performance of the probe parameters meets the preset, outputting the optimal parameters and obtaining the optimal design scheme.

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