Eddy current sensor for high-temperature environment and calibration method thereof

Abstract

The invention belongs to the technical field of eddy current sensor calibration, and discloses an eddy current sensor for a high-temperature environment and a calibration method thereof. The method comprises the following steps: synchronously acquiring working current, voltage, surface position, temperature, standard displacement signals and original output voltage of an eddy current sensor, constructing an oxide layer equivalent circuit model, and optimizing to obtain thickness distribution; building a thickness increase model, and building a correlation model to calculate time-varying impedance; calculating a sensitivity coefficient function, and designing a piecewise calibration function to obtain a calibration parameter set; and finally, dynamically compensating the original output voltage in combination with the calibration parameter set to obtain the calibrated displacement. A temperature field, a standard displacement signal and an original voltage signal are collected, a temperature-oxide layer-impedance three-dimensional dynamic model is established, and the nonlinear influence of oxide layer growth and temperature gradient is compensated in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of eddy current sensor calibration. More specifically, the present invention relates to an eddy current sensor for high-temperature environments and a calibration method therefor. Background Art

[0002] In high-temperature environments, the calibration technology of eddy current sensors needs to be systematically optimized for performance degradation problems under extreme working conditions.

[0003] Chinese Patent with the authorization announcement number CN116989651B discloses an eddy current displacement sensor for offshore platforms and a calibration method therefor. When calibrating the eddy current displacement sensor, calibration is first performed, a three-dimensional surface of the eddy current displacement sensor for three coordinates of ambient temperature, spacing distance, and output voltage for different metal objects to be measured is plotted, and it is converted into a calibration function for storage. During the use of the eddy current sensor, first, the material of the metal object to be measured is determined according to the initial spacing distance and ambient temperature, so that the calibration function to be used can be determined. Furthermore, during the detection process of the eddy current sensor, the ambient temperature and output voltage detected in real time are input into the calibration function for calculation to calibrate the error, eliminating the error caused by different seawater temperatures or the materials of the metal objects to be measured, and greatly improving the detection accuracy of the eddy current displacement sensor, meeting the usage requirements of the eddy current displacement sensor in the automation system of offshore platforms.

[0004] Although the above method can meet the application scenarios of offshore platforms, through research and practical application of the above method and the existing technology, it is found that the above method and the existing technology have at least the following partial defects: Factors such as salt spray corrosion, water pressure change, and biological attachment in the marine environment will change the interface characteristics between the sensor and the metal object to be measured. For example, salt spray easily causes a decrease in the insulation performance of the sensor surface or a change in the conductivity of the material to be measured, and water pressure change easily affects the stability of the mechanical structure of the sensor, and it is extremely easy to introduce additional measurement errors for the sensor; the metal objects to be measured in offshore platforms are exposed to seawater for a long time, and electrochemical corrosion or biological fouling may occur, resulting in changes in the conductivity and magnetic permeability of the material over time. The existing technology relies on the three-dimensional surface function preset at the factory and is difficult to track the degradation of material characteristics in real time.

[0005] In view of this, the present invention proposes an eddy current sensor for high-temperature environments and a calibration method therefor to solve the above problems. Summary of the Invention

[0006] To overcome the above defects of the existing technology and to achieve the above object, the present invention provides the following technical solution: An eddy current sensor calibration method for high-temperature environments, comprising the following steps: Synchronously collect the working current and working voltage of the eddy current sensor that reaches the preset temperature and process them to obtain impedance spectrum data; collect the surface position and corresponding temperature data of the eddy current sensor, and splice them to obtain two-dimensional temperature field data; collect the standard displacement signal and the original output voltage of the sensor; Construct an equivalent circuit model of the oxide layer based on the impedance spectrum data and the two-dimensional temperature field data, build an objective function based on a nature-inspired optimization algorithm to optimize the equivalent circuit model of the oxide layer, and obtain the oxide layer thickness distribution; Build a thickness growth model of the oxide layer based on the oxide layer thickness distribution and the two-dimensional temperature field data to obtain the time-varying oxide layer thickness. Based on the thickness growth model, establish relationship models between the time-varying oxide layer thickness and conductivity, and between the time-varying oxide layer thickness and permittivity respectively, and calculate to obtain the time-varying impedance; Calculate the sensitivity coefficient function based on the time-varying impedance. According to the predefined critical time, design a piecewise calibration function by combining the time-varying impedance and the standard displacement signal, and splice the sensitivity coefficient function, the critical time, and the piecewise calibration function to obtain a calibration parameter set; Perform dynamic compensation on the original output voltage of the sensor in combination with the calibration parameter set to obtain the calibrated displacement.

[0007] Furthermore, the method for obtaining the oxide layer thickness distribution includes: Calculate the equivalent impedance according to the equivalent circuit model of the oxide layer. Taking the minimization of the weighted residuals of the real and imaginary parts between the equivalent impedance and the impedance as the objective function, perform iterative optimization based on a nature-inspired optimization algorithm to obtain an optimized parameter set. The optimized parameter set includes the optimized substrate metal resistance, the optimized oxide layer resistance, the optimized substrate metal capacitance, the optimized oxide layer capacitance, and the optimized Warburg diffusion impedance; Discretize the surface oxide layer of the eddy current sensor into N×M grid cells. Each grid cell corresponds to an independent oxide layer resistance and oxide layer capacitance, where N and M are the number of rows and columns of the grid cells respectively; according to the optimized parameter set, allocate the locally optimized oxide layer resistance, the locally optimized oxide layer capacitance, and the locally optimized Warburg diffusion impedance to each grid cell; Based on the locally optimized oxide layer resistance, combine the oxide layer resistivity and the effective area of the electrode to inversely obtain the first local oxide layer thickness; Based on the locally optimized oxide layer capacitance, combine the vacuum permittivity and the relative permittivity of the oxide layer to inversely obtain the second local oxide layer thickness; Based on the locally optimized Warburg diffusion impedance, combine the Warburg coefficient to inversely obtain the third local oxide layer thickness; The thicknesses of the first local oxide layer, the second local oxide layer, and the third local oxide layer are weighted and fused to obtain the local oxide layer thickness; wherein, the resistivity and relative dielectric constant of the oxide layer are corrected by the Arrhenius equation. Calculate the local oxide layer thickness of each grid cell to obtain the oxide layer thickness distribution.

[0008] Furthermore, the method for obtaining the time-varying impedance includes: Initialize the oxidation kinetic parameters based on a preset material database. The oxidation kinetic parameters include the oxidation rate constant, activation energy, limiting thickness of the oxide layer, and oxidation inhibition factor. Obtain the N×M grid cells divided on the oxide layer surface of the eddy current sensor, and extract the local temperature and time-varying oxide layer thickness in each grid cell. Solve the oxidation kinetic equation for each grid cell. Use the oxide layer thickness distribution as the true value and optimize the oxidation kinetic parameters by the least squares method. Calculate the updated value of the time-varying oxide layer thickness based on the optimized oxidation kinetic parameters. Combine the porosity correction factor to establish a relationship model between the conductivity and the time-varying oxide layer thickness, and combine the oxide layer thickness threshold to establish a relationship model between the dielectric constant and the time-varying oxide layer thickness. Substitute the updated value of the time-varying oxide layer thickness to obtain the conductivity field and dielectric constant field for each grid cell. According to the conductivity field and dielectric constant field of each grid cell, calculate the corresponding resistance component, capacitance component, and Warburg impedance. Establish the time-domain Maxwell equation based on the conductivity field and dielectric constant field of each grid cell. Solve the time-domain Maxwell equation by the finite-difference time-domain method to calculate the port time-domain voltage and current of the eddy current sensor at the current moment. According to the port time-domain voltage and current of the eddy current sensor at the current moment, calculate the time-varying impedance by the short-time Fourier transform.

[0009] Furthermore, the method for obtaining the time-varying oxide layer thickness includes: Obtain the N×M grid cells divided on the oxide layer surface of the eddy current sensor. Based on the Arrhenius equation, establish a thickness growth model for the oxide layer of each grid cell. Obtain the model parameters in the thickness growth model by fitting the oxide layer thickness distribution and the two-dimensional temperature field data by the least squares method. Substitute the obtained model parameters into the thickness growth model to obtain the time-varying oxide layer thickness; wherein, the division of the grid cells is dynamically adjusted according to the growth of the oxide layer.

[0010] Furthermore, the method for obtaining the calibration parameter set includes: According to the time-varying impedance and the distribution of the oxide layer thickness, an initial sensitivity coefficient function composed of the initial sensitivity coefficient, the oxide layer thickness attenuation coefficient, the oxide layer thickness distribution, the imaginary part and the real part of the time-varying impedance is constructed. The parameters to be determined in the initial sensitivity coefficient function, including the initial sensitivity coefficient and the oxide layer thickness attenuation coefficient, are obtained through the regression analysis method, and the sensitivity coefficient function is updated according to the parameters to be determined obtained in the initial sensitivity coefficient function; According to the oxidation rate equation, the critical time corresponding to half of the maximum oxide layer thickness is obtained, a piecewise calibration function is constructed, and the parameters to be measured in the piecewise calibration function are fitted according to the critical time by the least squares method. The piecewise calibration function is obtained according to the parameters to be measured obtained; The sensitivity coefficient function, the piecewise calibration function and the critical time are spliced to obtain a calibration parameter set.

[0011] Furthermore, the method for obtaining the calibrated displacement includes: Obtain the real-time impedance of the eddy current sensor and the corresponding time, and calculate the real-time effective impedance according to the real-time impedance; Calculate the real-time effective oxide layer thickness through the real-time effective impedance; calculate the critical time according to the real-time effective oxide layer thickness, calculate the real-time effective displacement signal according to the real-time effective impedance through the preset conversion function of the eddy current sensor, and calibrate the real-time effective displacement signal through the piecewise calibration function to obtain the calibrated displacement.

[0012] Furthermore, the method for constructing the oxide layer equivalent circuit model includes: Obtain the first material data of the base metal and the oxide layer from the preset material database. The first material data includes conductivity, length and cross-sectional area. According to the first material data, the base metal resistance and the oxide layer resistance are calculated by combining the two-dimensional temperature field data. Obtain the second material data of the base metal and the oxide layer. The second material data includes dielectric constant, plate area and plate spacing. According to the second material data, the base metal capacitance and the oxide layer capacitance are calculated by combining the two-dimensional temperature field data; Obtain the diffusion coefficient from the preset material database, and calculate the Warburg diffusion impedance by combining the two-dimensional temperature field data; Based on the base metal resistance, the oxide layer resistance, the base metal capacitance, the oxide layer capacitance and the Warburg diffusion impedance, the oxide layer equivalent circuit model is constructed.

[0013] Furthermore, the method for obtaining the impedance spectrum data includes: Calculate the ratio of the working voltage to the working current to obtain the impedance, synchronously measure the amplitudes and the phase difference of the working voltage and the working current, calculate the complex impedance, and add the impedance and the complex impedance to obtain the impedance spectrum data.

[0014] Further, the method for obtaining two-dimensional temperature field data includes: Using Kriging interpolation or finite element thermal simulation method to convert discrete temperature measurement points into a continuous two-dimensional temperature field, and obtaining two-dimensional temperature field data.

[0015] An eddy current sensor for high-temperature environment, applied to the calibration method for the eddy current sensor for high-temperature environment, includes: Data acquisition module: Synchronously acquiring the working current and working voltage of the eddy current sensor reaching the preset temperature and processing them to obtain impedance spectrum data; acquiring the surface position and corresponding temperature data of the eddy current sensor, and splicing them to obtain two-dimensional temperature field data; acquiring the standard displacement signal and the original output voltage of the sensor; Model equivalent module: Constructing an oxide layer equivalent circuit model based on the impedance spectrum data and two-dimensional temperature field data, and optimizing the oxide layer equivalent circuit model by building an objective function based on a nature-inspired optimization algorithm to obtain the oxide layer thickness distribution; Time-varying analysis module: Building a thickness growth model of the oxide layer based on the oxide layer thickness distribution and two-dimensional temperature field data to obtain the time-varying oxide layer thickness, respectively establishing relationship models between the time-varying oxide layer thickness and conductivity, and between the time-varying oxide layer thickness and dielectric constant based on the thickness growth model, and calculating to obtain the time-varying impedance; Calibration analysis module: Calculating the sensitivity coefficient function based on the time-varying impedance, designing a segmented calibration function by combining the time-varying impedance and the standard displacement signal according to the predefined critical time, and splicing the sensitivity coefficient function, critical time and segmented calibration function to obtain a calibration parameter set; Sensor calibration module: Dynamically compensating the original output voltage of the sensor in combination with the calibration parameter set to obtain the calibrated displacement.

[0016] Technical effects and advantages of the eddy current sensor for high-temperature environment and its calibration method of the present invention: The present invention synchronously acquires the temperature field, standard displacement signal and original voltage signal, establishes a three-dimensional dynamic model of temperature-oxide layer-impedance, and compensates the non-linear effects of oxide layer growth and temperature gradient in real time; uses two-dimensional temperature field data to map the non-uniformity of the oxide layer thickness distribution to realize differential calibration of different regions on the sensor surface. Also based on the time-varying impedance, combines real-time data to update compensation parameters to adapt to the changes in material conductivity and zero drift under high-temperature working conditions; breaks through the problems such as changes in material conductivity and zero drift in high-temperature environments; provides key technical support for the health monitoring of high-temperature equipment such as aero-engine blades and nuclear reactor components. Description of the drawings

[0017] Figure 1 It is a schematic flow chart of the calibration method for the eddy current sensor for high-temperature environment of the present invention; Figure 2 Schematic diagram of data flow of the present invention; Figure 3 Schematic flowchart of the method for obtaining time-varying impedance of the present invention; Figure 4 Schematic flowchart of a method for calculating a temperature field based on quantum thermal sensing in Embodiment 2 of the present invention; Figure 5 Structural diagram of an eddy current sensor for high-temperature environment in Embodiment 3 of the present invention. Detailed implementation manners

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0019] Embodiment 1

[0020] Please refer to Figure 1 and Figure 2 As shown, this embodiment provides a calibration method for an eddy current sensor for high-temperature environment, including the following steps: Synchronously collect the working current and working voltage of the eddy current sensor at a preset temperature (which can be defined manually) and process them to obtain impedance spectrum data; collect the surface position and corresponding temperature data of the eddy current sensor, and splice them to obtain two-dimensional temperature field data; collect the standard displacement signal and the original output voltage of the sensor.

[0021] The working current and working voltage can be directly measured by an impedance analyzer. By monitoring the frequency-domain response characteristics of the impedance spectrum in real time, the electrical parameter changes caused by the growth of the oxide layer (such as increased resistance and decreased capacitance) can be accurately captured, providing core data support for subsequent establishment of an oxide layer equivalent circuit model, inversion of thickness distribution, prediction of time-varying impedance, and dynamic compensation, and ensuring the measurement accuracy and long-term stability of the sensor under high-temperature complex working conditions.

[0022] The surface position of the eddy current sensor and the corresponding temperature data can be collected by an array of temperature sensors. Multiple temperature measurement points are arranged on the surface of the eddy current sensor or the measured area, and spatial positioning is achieved through position coordinate mapping. By collecting spatial temperature distribution data, the oxidation layer growth kinetic parameters (such as activation energy, rate constant) can be accurately mapped, and the non-uniform influence of the temperature gradient on the oxidation layer thickness distribution can be captured, providing key inputs for establishing a three-dimensional coupling model of temperature-thickness-impedance, thereby realizing the spatial differential inversion of the equivalent circuit parameters of the oxidation layer, improving the prediction accuracy of time-varying impedance, and ultimately ensuring the adaptability of the dynamic compensation algorithm to temperature drift and oxidation layer heterogeneity, and ensuring the measurement reliability of the sensor in a complex high-temperature environment.

[0023] The standard displacement signal is obtained by measurement with a laser interferometer. By providing a reference input with a known displacement amount, it helps to establish a mathematical model of the temperature-displacement response characteristics in the later stage and compensate for the zero drift and sensitivity attenuation caused by high temperature in real time. At the same time, combined with the temperature field distribution data, the non-linear influence of the temperature gradient on the displacement measurement is separated, and the linearity and range stability of the sensor under extreme working conditions are verified, providing key parameter support for the dynamic compensation algorithm, and ultimately realizing high-precision displacement measurement and long-term reliability of the sensor in a high-temperature environment.

[0024] The original output voltage of the sensor is collected through the output port of the preamplifier. The original output voltage of the sensor directly reflects the coupling state between the sensor and the measured object, and contains the comprehensive influence of multi-physical field parameters such as oxidation layer thickness, temperature gradient, and material conductivity, which is the core input for later displacement calibration. By real-time analyzing the amplitude, phase, and waveform characteristics of the original output voltage, combined with the temperature field data and the standard displacement signal, the interference of temperature drift and oxidation layer growth can be separated, and a non-linear mapping relationship between voltage-displacement-temperature can be established, providing data support for generating the sensitivity coefficient function and piecewise calibration parameters, and ultimately realizing the self-adaptive calibration of the sensor under high-temperature complex working conditions, and ensuring the displacement measurement accuracy and long-term reliability.

[0025] The methods for obtaining impedance spectrum data include: Calculate the impedance by obtaining the ratio of the working voltage to the working current, synchronously measure the amplitude and phase difference of the working voltage and the working current, calculate the complex impedance, and add the impedance and the complex impedance to obtain the impedance spectrum data.

[0026] The methods for obtaining two-dimensional temperature field data include: Use the Kriging interpolation or finite element thermal simulation method to convert the discrete temperature measurement points into a continuous two-dimensional temperature field to obtain the two-dimensional temperature field data.

[0027] Construct an equivalent circuit model of the oxide layer based on impedance spectrum data and two-dimensional temperature field data, build an objective function based on a nature-inspired optimization algorithm to optimize the equivalent circuit model of the oxide layer, and obtain the oxide layer thickness distribution.

[0028] The method for constructing the equivalent circuit model of the oxide layer includes: Obtain the first material data of the base metal and the oxide layer from a preset material database. The first material data includes conductivity, length, and cross-sectional area. According to the first material data, combined with the two-dimensional temperature field data, calculate the base metal resistance and the oxide layer resistance. Obtain the second material data of the base metal and the oxide layer. The second material data includes dielectric constant, plate area, and plate spacing. According to the second material data, combined with the two-dimensional temperature field data, calculate the base metal capacitance and the oxide layer capacitance; Obtain the diffusion coefficient from a preset material database, and calculate the Warburg diffusion impedance combined with the two-dimensional temperature field data; Construct an equivalent circuit model of the oxide layer based on the base metal resistance, the oxide layer resistance, the base metal capacitance, the oxide layer capacitance, and the Warburg diffusion impedance.

[0029] The method for obtaining the oxide layer thickness distribution includes: Calculate the equivalent impedance according to the equivalent circuit model of the oxide layer. Taking the minimization of the weighted residuals of the real and imaginary parts between the equivalent impedance and the impedance as the objective function, perform iterative optimization based on a nature-inspired optimization algorithm to obtain an optimized parameter set. The optimized parameter set includes the optimized base metal resistance, the optimized oxide layer resistance, the optimized base metal capacitance, the optimized oxide layer capacitance, and the optimized Warburg diffusion impedance; Discretize the surface oxide layer of the eddy current sensor into N×M grid cells. Each grid cell corresponds to independent oxide layer resistance and oxide layer capacitance, where N and M are the number of rows and columns of the grid cells respectively; According to the optimized parameter set, assign the locally optimized oxide layer resistance, the locally optimized oxide layer capacitance, and the locally optimized Warburg diffusion impedance to each grid cell; According to the locally optimized oxide layer resistance, combined with the oxide layer resistivity and the effective area of the electrode, invert the first local oxide layer thickness; According to the locally optimized oxide layer capacitance, combined with the vacuum permittivity and the relative permittivity of the oxide layer, invert the second local oxide layer thickness; According to the locally optimized Warburg diffusion impedance, combined with the Warburg coefficient, invert the third local oxide layer thickness; Perform weighted fusion on the first local oxide layer thickness, the second local oxide layer thickness, and the third local oxide layer thickness to obtain the local oxide layer thickness; Among them, correct the oxide layer resistivity and the relative permittivity of the oxide layer through the Arrhenius equation; Calculate the local oxide layer thickness of each grid cell to obtain the oxide layer thickness distribution.

[0030] Based on the oxide layer thickness distribution and two-dimensional temperature field data, establish a thickness growth model of the oxide layer to obtain the time-varying oxide layer thickness. Based on the thickness growth model, establish relationship models between the time-varying oxide layer thickness and conductivity, and between the time-varying oxide layer thickness and dielectric constant respectively, and calculate the time-varying impedance; The method for obtaining the time-varying oxide layer thickness includes: Obtain N×M grid cells divided on the oxide layer on the surface of the eddy current sensor. Based on the Arrhenius equation, establish a thickness growth model of the oxide layer for each grid cell. Through the least squares method, combine the oxide layer thickness distribution and two-dimensional temperature field data to fit the model parameters in the thickness growth model, and substitute the obtained model parameters into the thickness growth model to obtain the time-varying oxide layer thickness; among them, the division of grid cells is dynamically adjusted according to the growth of the oxide layer. For example, when the oxide layer thickness exceeds the preset thickness threshold, the grid cells are refined (such as refined from 10μm to 5μm).

[0031] Please refer to Figure 3 , the method for obtaining the time-varying impedance includes: Initialize the oxidation kinetic parameters based on a preset material database. The oxidation kinetic parameters include oxidation rate constant, activation energy, oxide layer limit thickness, and oxidation inhibition factor. Obtain N×M grid cells divided on the oxide layer on the surface of the eddy current sensor, and extract the local temperature and time-varying oxide layer thickness in each grid cell; Solve the oxidation kinetic equation for each grid cell (such as using the fourth-order Runge-Kutta method for time integration); Take the oxide layer thickness distribution as the true value and optimize the oxidation kinetic parameters by the least squares method; Calculate the updated value of the time-varying oxide layer thickness based on the optimized oxidation kinetic parameters; Combine the porosity correction factor to establish a relationship model between conductivity and time-varying oxide layer thickness, and combine the oxide layer thickness threshold to establish a relationship model between dielectric constant and time-varying oxide layer thickness. Substitute the updated value of the time-varying oxide layer thickness to obtain the conductivity field and dielectric constant field for each grid cell; According to the conductivity field and dielectric constant field of each grid cell, calculate the corresponding resistance component, capacitance component, and Warburg impedance; Based on the conductivity field and dielectric constant field of each grid cell, establish the time-domain Maxwell equation; The finite-difference time-domain method is used to solve the Maxwell's equations in the time domain, and the port time-domain voltage and current of the eddy current sensor at the current moment are calculated. According to the port time-domain voltage and current of the eddy current sensor at the current moment, the time-varying impedance is calculated through the short-time Fourier transform.

[0032] Based on the time-varying impedance, the sensitivity coefficient function is calculated. According to the predefined critical time, combining the time-varying impedance and the standard displacement signal, a piecewise calibration function is designed, and the sensitivity coefficient function, the critical time, and the piecewise calibration function are concatenated to obtain the calibration parameter set.

[0033] The method for obtaining the calibration parameter set includes: According to the time-varying impedance and the oxide layer thickness distribution, an initial sensitivity coefficient function composed of the initial sensitivity coefficient, the oxide layer thickness attenuation coefficient, the oxide layer thickness distribution, the imaginary part and the real part of the time-varying impedance is constructed. The parameters to be determined in the initial sensitivity coefficient function, including the initial sensitivity coefficient and the oxide layer thickness attenuation coefficient, are obtained through the regression analysis method, and the sensitivity coefficient function is updated according to the parameters to be determined obtained in the initial sensitivity coefficient function; According to the oxidation rate equation, the critical time corresponding to half of the maximum oxide layer thickness is obtained, a piecewise calibration function is constructed, the parameters to be measured in the piecewise calibration function are fitted according to the critical time by the least squares method, and the piecewise calibration function is obtained according to the parameters to be measured obtained; The sensitivity coefficient function, the piecewise calibration function and the critical time are concatenated to obtain the calibration parameter set.

[0034] Combined with the calibration parameter set, the original output voltage of the sensor is dynamically compensated to obtain the calibrated displacement.

[0035] The method for obtaining the calibrated displacement includes: Obtain the real-time impedance of the eddy current sensor and the corresponding time, and calculate the real-time effective impedance according to the real-time impedance; Calculate the real-time effective oxide layer thickness through the real-time effective impedance; calculate the critical time according to the real-time effective oxide layer thickness, calculate the real-time effective displacement signal through the preset conversion function of the eddy current sensor according to the real-time effective impedance, and calibrate the real-time effective displacement signal through the piecewise calibration function to obtain the calibrated displacement.

[0036] Embodiment 2

[0037] Please refer to Figure 4 As shown, this embodiment provides a method for calculating the temperature field based on quantum thermal sensing applied to Embodiment 1, including the following steps: In a diamond substrate that is stable at high temperatures, a nitrogen-vacancy color center array is embedded through ion implantation and annealing processes to form nanoscale temperature-sensitive units; among them, each nitrogen-vacancy color center generates a fluorescence signal through laser excitation, and its zero-field splitting effect varies with temperature.

[0038] Use a 532 nm laser pulse to initialize the electron spin state of the nitrogen-vacancy color centers, and apply a dynamic decoupling microwave sequence to suppress magnetic noise and lattice vibration interference in a high-temperature environment, extending the coherence time from the microsecond level at room temperature to the nanosecond level at high temperatures (such as 800 °C).

[0039] Use entangled photon pairs to prepare adjacent nitrogen-vacancy color centers into a quantum entangled state, and synchronously measure the zero-field splitting frequency shifts of multiple color centers through quantum state tomography technology. Correlated measurements can cancel out local thermal fluctuation noise, enabling the single-point temperature measurement accuracy to break through the classical limit.

[0040] Discretize the unsteady heat conduction equation into the form of a quantum Hamiltonian, solve the eigenstates through the quantum phase estimation algorithm, and map them to the temperature field distribution. Reduce the complexity of the traditional finite element method through quantum parallel computing, achieve a thousand-fold acceleration on a quantum simulator, and output a two-dimensional temperature field with sub-micron resolution in real time.

[0041] Fuse the quantum temperature measurement results with the data of an infrared thermal imager, and eliminate the systematic error introduced by the thermal expansion of the diamond substrate through Kalman filtering.

[0042] Example 3

[0043] Please refer to Figure 5 As shown, an eddy current sensor for a high-temperature environment described in this embodiment includes: Data acquisition module: Synchronously acquire the working current and working voltage of the eddy current sensor that reaches the preset temperature and process them to obtain impedance spectrum data; acquire the surface position and corresponding temperature data of the eddy current sensor, and splice them to obtain two-dimensional temperature field data; acquire the standard displacement signal and the original output voltage of the sensor. Model equivalent module: Build an equivalent circuit model of the oxide layer based on the impedance spectrum data and two-dimensional temperature field data, and optimize the equivalent circuit model of the oxide layer by building an objective function based on a nature-inspired optimization algorithm to obtain the oxide layer thickness distribution. Time-varying analysis module: Build a thickness growth model of the oxide layer based on the oxide layer thickness distribution and two-dimensional temperature field data to obtain the time-varying oxide layer thickness, and establish relationship models between the time-varying oxide layer thickness and conductivity, and between the time-varying oxide layer thickness and dielectric constant based on the thickness growth model, and calculate the time-varying impedance. Calibration analysis module: Based on the calculation of time-varying impedance, obtain the sensitivity coefficient function. According to the predefined critical time, combine the time-varying impedance and the standard displacement signal to design a piecewise calibration function, and splice the sensitivity coefficient function, the critical time, and the piecewise calibration function to obtain a calibration parameter set; Sensor calibration module: Dynamically compensate the original output voltage of the sensor in combination with the calibration parameter set to obtain the calibrated displacement.

[0044] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

[0045] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An eddy current sensor calibration method for high-temperature environments, characterized in that, The method includes the following steps: Synchronously collect the working current and working voltage of an eddy current sensor that has reached a preset temperature, and process them to obtain impedance spectrum data; collect the surface position and corresponding temperature data of the eddy current sensor, and splice them to obtain two-dimensional temperature field data; collect a standard displacement signal and the original output voltage of the sensor; Construct an equivalent circuit model of the oxide layer based on the impedance spectrum data and the two-dimensional temperature field data, build an objective function based on a nature-inspired optimization algorithm to optimize the equivalent circuit model of the oxide layer, and obtain the oxide layer thickness distribution; Build a thickness growth model of the oxide layer based on the oxide layer thickness distribution and the two-dimensional temperature field data to obtain the time-varying oxide layer thickness. Based on the thickness growth model, establish relationship models between the time-varying oxide layer thickness and conductivity, and between the time-varying oxide layer thickness and permittivity respectively, and calculate to obtain the time-varying impedance; Calculate the sensitivity coefficient function based on the time-varying impedance, design a piecewise calibration function according to a predefined critical time, combining the time-varying impedance and the standard displacement signal, and splice the sensitivity coefficient function, the critical time, and the piecewise calibration function to obtain a calibration parameter set; Perform dynamic compensation on the original output voltage of the sensor in combination with the calibration parameter set to obtain the calibrated displacement.

2. The eddy current sensor calibration method for high-temperature environment according to claim 1, wherein, The method for obtaining the oxide layer thickness distribution includes: Calculate the equivalent impedance according to the equivalent circuit model of the oxide layer. Taking the minimization of the weighted residuals of the real and imaginary parts between the equivalent impedance and the impedance as the objective function, perform iterative optimization based on a nature-inspired optimization algorithm to obtain an optimized parameter set. The optimized parameter set includes the optimized substrate metal resistance, the optimized oxide layer resistance, the optimized substrate metal capacitance, the optimized oxide layer capacitance, and the optimized Warburg diffusion impedance; Discretize the surface oxide layer of the eddy current sensor into N×M grid cells, each grid cell corresponding to an independent oxide layer resistance and oxide layer capacitance, where N and M are the number of rows and columns of the grid cells respectively; according to the optimized parameter set, assign a locally optimized oxide layer resistance, a locally optimized oxide layer capacitance, and a locally optimized Warburg diffusion impedance to each grid cell; Invert the first local oxide layer thickness based on the locally optimized oxide layer resistance, combining the oxide layer resistivity and the effective electrode area; Invert the second local oxide layer thickness based on the locally optimized oxide layer capacitance, combining the vacuum permittivity and the relative permittivity of the oxide layer; Invert the third local oxide layer thickness based on the locally optimized Warburg diffusion impedance, combining the Warburg coefficient; Perform weighted fusion on the first local oxide layer thickness, the second local oxide layer thickness, and the third local oxide layer thickness to obtain the local oxide layer thickness; wherein, the oxide layer resistivity and the relative permittivity of the oxide layer are corrected by the Arrhenius equation; Calculate the local oxide layer thickness of each grid cell to obtain the oxide layer thickness distribution.

3. A calibration method for an eddy current sensor used in a high-temperature environment according to claim 2, characterized in that, The method for obtaining the time-varying impedance includes: Initialize the oxidation kinetic parameters based on a preset material database. The oxidation kinetic parameters include the oxidation rate constant, activation energy, limiting thickness of the oxide layer, and oxidation inhibition factor. Obtain N×M grid cells divided on the oxide layer surface of the eddy current sensor, and extract the local temperature and time-varying oxide layer thickness in each grid cell. Solve the oxidation kinetic equation for each grid cell. Take the oxide layer thickness distribution as the true value, and optimize the oxidation kinetic parameters by the least squares method. Calculate the updated value of the time-varying oxide layer thickness based on the optimized oxidation kinetic parameters. Combine the porosity correction factor to establish a relationship model between the conductivity and the time-varying oxide layer thickness, and combine the oxide layer thickness threshold to establish a relationship model between the dielectric constant and the time-varying oxide layer thickness. Substitute the updated value of the time-varying oxide layer thickness to obtain the conductivity field and dielectric constant field for each grid cell. Calculate the corresponding resistance component, capacitance component, and Warburg impedance according to the conductivity field and dielectric constant field of each grid cell. Establish the time-domain Maxwell's equation based on the conductivity field and dielectric constant field of each grid cell. Solve the time-domain Maxwell's equation by the finite-difference time-domain method to calculate the port time-domain voltage and current of the eddy current sensor at the current moment. Calculate the time-varying impedance by the short-time Fourier transform according to the port time-domain voltage and current of the eddy current sensor at the current moment.

4. A method for calibrating an eddy current sensor for a high-temperature environment according to claim 3, characterized in that, The method for obtaining the time-varying oxide layer thickness includes: Obtain N×M grid cells divided on the oxide layer surface of the eddy current sensor. Establish a thickness growth model of the oxide layer for each grid cell based on the Arrhenius equation. Obtain the model parameters in the thickness growth model by fitting the oxide layer thickness distribution and the two-dimensional temperature field data by the least squares method. Substitute the obtained model parameters into the thickness growth model to obtain the time-varying oxide layer thickness. Among them, the division of the grid cells is adjusted according to the growth dynamics of the oxide layer.

5. A method for calibrating an eddy current sensor for a high-temperature environment according to claim 4, characterized in that, The method for obtaining the calibration parameter set includes: According to the time-varying impedance and the oxide layer thickness distribution, establish an initial sensitivity coefficient function composed of the initial sensitivity coefficient, the oxide layer thickness attenuation coefficient, the oxide layer thickness distribution, the imaginary part and the real part of the time-varying impedance. Obtain the parameters to be determined in the initial sensitivity coefficient function, including the initial sensitivity coefficient and the oxide layer thickness attenuation coefficient, by the regression analysis method. Update the sensitivity coefficient function according to the parameters to be determined obtained in the initial sensitivity coefficient function. According to the oxidation rate equation, obtain the critical time corresponding to half of the maximum oxide layer thickness. Establish a piecewise calibration function, and fit the parameters to be measured in the piecewise calibration function by the least squares method according to the critical time. Establish the piecewise calibration function according to the obtained parameters to be measured. Splice the sensitivity coefficient function, the piecewise calibration function, and the critical time to obtain the calibration parameter set.

6. A calibration method for an eddy current sensor used in a high-temperature environment according to claim 1, characterized in that, The method for obtaining the calibrated displacement includes: Obtain the real-time impedance of the eddy current sensor and the corresponding time, and calculate the real-time effective impedance according to the real-time impedance. Calculate the real-time effective oxide layer thickness through real-time effective impedance; calculate the critical time according to the real-time effective oxide layer thickness, obtain the real-time effective displacement signal by presetting a conversion function with an eddy current sensor based on the real-time effective impedance, and calibrate the real-time effective displacement signal through a piecewise calibration function to obtain the calibrated displacement.

7. A calibration method for an eddy current sensor used in a high-temperature environment according to claim 1, characterized in that, The method for constructing an equivalent circuit model of an oxide layer includes: Obtain the first material data of the substrate metal and the oxide layer from a preset material database. The first material data includes conductivity, length, and cross-sectional area. According to the first material data, calculate the substrate metal resistance and the oxide layer resistance in combination with two-dimensional temperature field data. Obtain the second material data of the substrate metal and the oxide layer. The second material data includes dielectric constant, plate area, and plate spacing. According to the second material data, calculate the substrate metal capacitance and the oxide layer capacitance in combination with two-dimensional temperature field data; Obtain the diffusion coefficient from a preset material database and calculate the Warburg diffusion impedance in combination with two-dimensional temperature field data; Construct an equivalent circuit model of the oxide layer based on the substrate metal resistance, the oxide layer resistance, the substrate metal capacitance, the oxide layer capacitance, and the Warburg diffusion impedance.

8. A calibration method for an eddy current sensor used in a high-temperature environment according to claim 1, characterized in that, The method for obtaining impedance spectrum data includes: Calculate the impedance by calculating the ratio of the working voltage to the working current, synchronously measure the amplitude and phase difference of the working voltage and the working current, calculate the complex impedance, and add the impedance and the complex impedance to obtain the impedance spectrum data.

9. A calibration method for an eddy current sensor used in a high-temperature environment according to claim 1, characterized in that, The method for obtaining two-dimensional temperature field data includes: Use the Kriging interpolation or finite element thermal simulation method to convert discrete temperature measurement points into a continuous two-dimensional temperature field to obtain two-dimensional temperature field data.

10. An eddy current sensor for high-temperature environments, which is applied to the calibration method of an eddy current sensor for high-temperature environments according to any one of claims 1-9, characterized in that, Including: Data acquisition module: Synchronously collect the working current and working voltage of an eddy current sensor at a preset temperature and process them to obtain impedance spectrum data; Collect the surface position of the eddy current sensor and the corresponding temperature data, and splice them to obtain two-dimensional temperature field data; collect the standard displacement signal and the original output voltage of the sensor; Model equivalent module: Construct an equivalent circuit model of the oxide layer based on the impedance spectrum data and the two-dimensional temperature field data, build an objective function based on a nature-inspired optimization algorithm to optimize the equivalent circuit model of the oxide layer, and obtain the oxide layer thickness distribution; Time-varying analysis module: Build a thickness growth model of the oxide layer based on the oxide layer thickness distribution and the two-dimensional temperature field data to obtain the time-varying oxide layer thickness. Based on the thickness growth model, establish relationship models between the time-varying oxide layer thickness and conductivity, and between the time-varying oxide layer thickness and dielectric constant, and calculate the time-varying impedance; Calibration analysis module: Calculate the sensitivity coefficient function based on the time-varying impedance, design a piecewise calibration function according to the predefined critical time, in combination with the time-varying impedance and the standard displacement signal, and splice the sensitivity coefficient function, the critical time, and the piecewise calibration function to obtain a calibration parameter set; Sensor calibration module: Dynamically compensate the original output voltage of the sensor in combination with the calibration parameter set to obtain the calibrated displacement.

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