An electromagnetic eddy current defect imaging method and system based on parameter level sets

Abstract

This invention discloses an electromagnetic eddy current defect imaging method and system based on parameter level sets. The method includes optimizing the parameters of an array of eddy current sensors; acquiring data from the metal component under test to obtain eddy current response signals under different excitation-reception conditions; reconstructing the three-dimensional defects based on a parameter level set reconstruction algorithm; setting the location of discrete point sources, the conductivity values ​​of the metal and defects, and the initial coefficient parameters of the basis functions; inputting the eddy current response signals into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set; calculating the Jacobian matrix and iteratively solving the objective function using the Gauss-Newton method, performing iterative updates, and determining whether the defect reconstruction has converged based on whether the deviation between the reconstruction results before and after the iteration is less than a threshold; and obtaining the final defect imaging result. This invention is easy to implement and does not require a mechanical scanning device; it can acquire information on internal surface defects of metal components through computational imaging.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic eddy current nondestructive testing technology, and in particular to an electromagnetic eddy current defect imaging method and system based on parameter level sets. Background Technology

[0002] The working principle of electromagnetic eddy current detection technology is based on Faraday's law of electromagnetic induction. When an alternating current passes through the detection coil, an alternating magnetic field is generated around it. When the conductive material to be detected is placed in this magnetic field, eddy currents are generated inside the material due to electromagnetic induction. The direction of the eddy currents is opposite to the direction of the magnetic field, weakening the original magnetic field and generating an induced magnetic field inside the material with the opposite direction to the original magnetic field. This induced magnetic field changes the distribution of the original magnetic field, causing a change in the impedance of the detection coil. By measuring and analyzing these impedance changes, it is possible to infer whether there are defects or performance changes inside the material. Quantitative defect imaging can accurately measure parameters such as the size, shape, and location of defects, avoiding the subjectivity and uncertainty that may exist in traditional detection methods and improving the accuracy of detection. This method first optimizes the parameters of the array eddy current sensor through orthogonal experiments and response surface methodology to improve the uniformity of the sensitive field. Subsequently, a parameter level set reconstruction algorithm is used to reconstruct the three-dimensional defects. In the algorithm, the position of the basis function and the initial coefficient parameters are obtained adaptively. By calculating the Jacobian matrix and using the Gauss-Newton method to iteratively solve the inverse problem of electromagnetic parameter distribution imaging based on the parameter level set, the basis function coefficient parameters are continuously iteratively updated to achieve high-precision three-dimensional imaging of defects in metal components. Summary of the Invention

[0003] The present invention aims to at least partially solve one of the technical problems in the related art.

[0004] To address this, the present invention proposes an electromagnetic eddy current defect imaging method based on parameter level sets. By using an array of eddy current sensors to collect data from the metal component under test, eddy current response signals under different excitation-reception conditions are obtained. Based on the parameter level set reconstruction algorithm, the three-dimensional reconstruction of the defect is realized, theoretically achieving three-dimensional imaging and quantitative assessment of defects in the damaged state of the metal component.

[0005] Another objective of this invention is to propose an electromagnetic eddy current defect imaging system based on a parameter level set.

[0006] To achieve the above objectives, this invention proposes an electromagnetic eddy current defect imaging method based on parameter level sets, comprising:

[0007] S1. Construct an array eddy current sensor and optimize its parameters through orthogonal experiments and response surface methodology.

[0008] S2, the optimized array eddy current sensor is used to acquire data of the metal component under test to obtain eddy current response signals under different excitation-reception conditions, and the parameter level set algorithm is used to process the signals to characterize the three-dimensional contour of the defect.

[0009] S3 sets the location of the discrete point source describing the three-dimensional contour of the defect, the metal conductivity value and the defect conductivity value, and the initial coefficient parameters of the basis function.

[0010] S4. Based on the location of the discrete point source describing the three-dimensional contour, the metal conductivity value, the defect conductivity value, and the initial coefficient parameters of the basis function, a level set reconstruction algorithm model is constructed, and the eddy current response signal is input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set.

[0011] S5. The defect imaging results are obtained by calculating the Jacobian matrix and iteratively solving the defect reconstruction objective function using the Gauss-Newton method, and the basis function coefficient parameters are iteratively updated.

[0012] S6, repeat S5, and determine whether the defect reconstruction has converged based on whether the deviation between the two defect imaging results before and after the iteration is less than a preset threshold.

[0013] S7 outputs the final defect imaging result based on the convergence judgment result to obtain information on the location, size and quantity of defects.

[0014] The electromagnetic eddy current defect imaging method based on parameter level sets in this invention may also have the following additional technical features:

[0015] In one embodiment of the present invention, an array eddy current sensor is constructed, and the parameters of the array eddy current sensor are optimized by orthogonal experiments and response surface methodology, including:

[0016] Design a 3×3 planar array eddy current sensor and use finite element numerical solution to calculate the sensitivity matrix;

[0017] Based on the theoretical model of the non-coaxial eddy current sensor, the factors affecting the sensitivity matrix are analyzed, and the parameter range is determined.

[0018] Based on the parameter range, the optimal parameter combination can be obtained using orthogonal experiments;

[0019] Based on the optimal parameter combination, the relationship between the uniformity of the sensitivity matrix and the sensor parameters is obtained through the response surface methodology, so as to obtain the final optimized parameters of the array sensor.

[0020] In one embodiment of the present invention, an optimized array eddy current sensor is used to acquire data from the metal component under test to obtain eddy current response signals under different excitation-reception conditions, and a parameter level set algorithm is used to process the signals to characterize the three-dimensional profile of the defect, including:

[0021] The metal imaging region is equivalent to a test field containing two types of conductivity, where the defect region is the target region R and the metal region is the background region Ω\R. The conductivity changes of the target region R and the background region Ω\R are calculated based on the eddy current response signal; the metal conductivity value Δσ1 and the defect conductivity value Δσ0, and the conductivity change of the entire background region Ω are expressed as:

[0022] σ(x)=σ0(1-H(f(x))-c)+σ1H(f(x)-c)

[0023] Where H(s) is the smoothing Heaviside function, expressed as:

[0024]

[0025] f(x) is a parametric level set function that satisfies:

[0026]

[0027] The level set function f(x) passes through N basis functions p i (x) linear weighted representation:

[0028]

[0029] Where, μ i These are the coefficients of the basis functions.

[0030] In one embodiment of the present invention, the locations of discrete point sources describing the three-dimensional contour of the defect, the metal conductivity value, the defect conductivity value, and the initial coefficient parameters of the basis functions are set, including:

[0031] The location of the defect was initially determined using a linear back projection algorithm;

[0032] Set the position of the basis function to the defect location reconstructed by the linear back projection;

[0033] The electrical conductivity value σ1 of the metal to be tested is determined based on the material, and the initial coefficient parameters [μ1] of the basis function are determined based on the gray values ​​of the defect locations reconstructed by the linear back projection algorithm. * μ2 * ,…,μ n * ].

[0034] In one embodiment of the present invention, the defect imaging result is obtained by calculating the Jacobian matrix and iteratively solving the defect reconstruction objective function using the Gauss-Newton method, including:

[0035] The inverse problem of electromagnetic parameter distribution imaging in eddy current tomography can be expressed as:

[0036]

[0037] Substituting the conductivity distribution σ(x) into the above equation, we obtain the expression for the inverse problem of electromagnetic parameter distribution imaging based on the parameter level set:

[0038] argmin{|λ m -U(σ(x,μ))| 2 +β|I(μ-μ * )|}

[0039] In the formula, λ m The value μ represents the measurement signal from the eddy current sensor. * β represents the initial coefficient parameters of the basis functions, and β is the regularization parameter;

[0040] For the optimization problem, the Newton iterative algorithm is used for solution, and the iterative formula is expressed as:

[0041]

[0042] In the formula, μ k λ is the basis function coefficient during the k-th iteration. k J is the eddy current response signal calculated during the k-th iteration. k The Jacobian matrix at the k-th iteration is expressed as:

[0043]

[0044] In the formula, δ() represents the Dirac function;

[0045] The defect imaging results are obtained based on the iteration coefficient μ.

[0046] To achieve the above objectives, another aspect of the present invention proposes an electromagnetic eddy current defect imaging system based on a parameter level set, comprising:

[0047] The sensor parameter optimization module is used to construct an array eddy current sensor and optimize the parameters of the array eddy current sensor through orthogonal experiments and response surface methodology.

[0048] The three-dimensional contour characterization module is used to acquire data from the metal component under test using an optimized array eddy current sensor to obtain eddy current response signals under different excitation-reception conditions, and to process the signals using a parameter level set algorithm to characterize the three-dimensional contour of the defect.

[0049] The parameter setting module is used to set the location of discrete point sources describing the three-dimensional contour of the defect, the metal conductivity value and the defect conductivity value, as well as the initial coefficient parameters of the basis function.

[0050] The objective function reconstruction module is used to construct a level set reconstruction algorithm model based on the location of discrete point sources describing the three-dimensional contour, the metal conductivity value, the defect conductivity value, and the initial coefficient parameters of the basis function. The eddy current response signal is input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set.

[0051] The defect imaging result solution module is used to obtain the defect imaging result by calculating the Jacobian matrix and iteratively solving the defect reconstruction objective function using the Gauss-Newton method, and to iteratively update the basis function coefficient parameters.

[0052] The deviation judgment module is used to determine whether the defect reconstruction has converged based on whether the deviation between the two defect imaging results before and after the iteration process is less than a preset threshold.

[0053] The final result output module is used to output the final defect imaging result based on the convergence judgment result, so as to obtain information on the location, size and quantity of defects.

[0054] The electromagnetic eddy current defect imaging method and system based on parameter level sets of this invention are easy to implement and do not require mechanical scanning devices. They can obtain information on defects on the inner surface of metal components through computational imaging.

[0055] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0056] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0057] Figure 1 This is a flowchart of an electromagnetic eddy current defect imaging method based on a parameter level set according to an embodiment of the present invention;

[0058] Figure 2 This is a schematic diagram of an array eddy current sensor according to an embodiment of the present invention;

[0059] Figure 3 This is a flowchart of the parameter optimization process for an array eddy current sensor according to an embodiment of the present invention;

[0060] Figure 4 This is a three-dimensional imaging result of a defect according to an embodiment of the present invention;

[0061] Figure 5This is a structural diagram of an electromagnetic eddy current defect imaging system based on a parameter level set according to an embodiment of the present invention. Detailed Implementation

[0062] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0063] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0064] The electromagnetic eddy current defect imaging method and system based on parameter level sets proposed according to embodiments of the present invention are described below with reference to the accompanying drawings.

[0065] Figure 1 This is a flowchart of an electromagnetic eddy current defect imaging method based on parameter level sets according to an embodiment of the present invention, as follows: Figure 1 As shown, the method includes:

[0066] S1. Construct an array eddy current sensor and optimize its parameters using orthogonal experiments and response surface methodology.

[0067] It is understandable that a planar flat plate array eddy current sensor is constructed, and the parameters of the array eddy current sensor are optimized through orthogonal experiments and response surface methodology to improve the uniformity of the sensitive field.

[0068] The overall optimization flowchart of this invention embodiment is as follows: Figure 3 As shown, a 3×3 planar array eddy current sensor is designed, and the sensitivity matrix is ​​calculated using the finite element method. The factors affecting the sensitivity matrix are analyzed based on the theoretical model of the non-coaxial eddy current sensor, and the parameter range is determined. Based on the parameter range, the optimal parameter combination is obtained by orthogonal experiment. Based on the optimal parameter combination, the relationship between the uniformity of the sensitivity matrix and the sensor parameters is obtained by response surface methodology, so as to obtain the final optimized parameters of the array sensor.

[0069] Specifically, a 3×3 planar array eddy current sensor is designed, such as... Figure 2As shown, based on the analytical theoretical model, the main factors affecting the uniformity of the sensitivity matrix of the array eddy current sensor are the coil radius r and lift-off distance l0, the coil height h and coil spacing g, and the excitation frequency f. The ranges for each factor are determined: excitation frequency (500-10kHz), coil outer diameter (5-15mm), coil height (2-4.5mm), lift-off distance (0.25-1mm), and coil spacing (7.5-15mm). The uniformity of the sensitivity matrix can be described and characterized by the variance index. An orthogonal experimental design is used to obtain a better combination of levels. Based on the optimal combination of levels obtained from the orthogonal experiment, the relationship between the uniformity of the sensitivity matrix and the sensor parameters is further obtained using the response surface methodology to obtain the final optimized parameters. The optimized sensor parameters are: excitation frequency set to 1000Hz, coil height 2.5mm and lift-off distance 0.5mm, coil spacing 10mm, and coil radius 5mm.

[0070] S2. The optimized array eddy current sensor is used to acquire data of the metal component under test to obtain eddy current response signals under different excitation-reception conditions, and the parameter level set algorithm is used to process the signals to characterize the three-dimensional contour of the defect.

[0071] It is understandable that by using an optimized array of eddy current sensors to acquire data from the metal component under test, eddy current response signals under different excitation-reception conditions are obtained, and the three-dimensional contour of the defect is characterized by a parameter level set algorithm.

[0072] The metal imaging region is equivalent to a measured field containing two types of conductivity, where the defect region is the target region R and the metal region is the background region Ω\R. The conductivity changes of the target region R and the background region Ω\R are calculated based on eddy current measurement data. The conductivity values ​​are Δσ1 (metal conductivity) and Δσ0 (defect conductivity). The conductivity change of the entire imaging region Ω can be expressed as:

[0073] σ(x)=σ0(1-H(f(x))-c)+σ1H(f(x)-c)

[0074] Where H(s) is the smoothing heaviside function, it can be expressed as:

[0075]

[0076] f(x) is a parametric level set function that satisfies

[0077]

[0078] In the formula, c is a positive number slightly greater than 0, which is set to 0.01 in this embodiment. ε is the Heaviside function smoothing factor, which is set to 0.1 in this embodiment.

[0079] The level set function F(x) can be passed through N basis functions p i (x) linear weighted representation, the basis functions can be Gaussian radial basis function, cubic spline interpolation function, B-spline interpolation function, etc.

[0080]

[0081] μ i These are the coefficients of the basis functions, and different coefficients represent different imaging images. Therefore, by adjusting these coefficients, the reconstructed image can be changed.

[0082] S3 sets the location of the discrete point source describing the three-dimensional contour of the defect, the metal conductivity value, the defect conductivity value, and the initial coefficient parameters of the basis function.

[0083] Specifically, the locations of discrete point sources (basis functions) are set, along with the metal conductivity value σ1 and the defect conductivity value σ0, and the initial coefficient parameters [μ1] of the basis functions. * μ2 * ,…,μ n * ].

[0084] The embodiments of the present invention employ a classic linear back projection algorithm to roughly determine the location of defects;

[0085] In this embodiment of the invention, the basis functions are positioned at the defect locations reconstructed by linear back projection, thereby reducing the number of basis functions.

[0086] The initial coefficient parameters [μ1] of the basis functions in this embodiment of the invention * μ2 * ,…,μ n * The location of the defect is determined based on the gray value of the reconstruction result of the linear back projection algorithm.

[0087] In this embodiment of the invention, the metal conductivity value σ1 is determined based on the material of the metal being tested. In this embodiment, the sample material is copper, and the conductivity is set to 5.8 × 10⁻⁶. 7 S / m. The defect conductivity value σ0 can be set to 1×10. -5 S / m.

[0088] S4. Based on the location of discrete point sources describing the three-dimensional contour, the values ​​of metal conductivity and defect conductivity, and the initial coefficient parameters of the basis function, a level set reconstruction algorithm model is constructed. The eddy current response signal is then input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set.

[0089] Specifically, a level set reconstruction algorithm model is constructed based on the location of discrete point sources describing the three-dimensional contour, the values ​​of metal conductivity and defect conductivity, and the initial coefficient parameters of the basis functions.

[0090] The eddy current response signal is input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set;

[0091] argmin{|λ m -U(σ(x,μ))| 2 +β|I(μ-μ * )|}

[0092] In the formula, λ k This represents the measurement signal from the eddy current sensor, μ. * β represents the initial coefficient parameters of the basis functions, and β is the regularization parameter.

[0093] S5. The defect imaging results are obtained by calculating the Jacobian matrix and iteratively solving the defect reconstruction objective function using the Gauss-Newton method, and the basis function coefficient parameters are iteratively updated.

[0094] The optimization problem described above is solved using the Newton iterative algorithm, and the iterative formula can be expressed as:

[0095]

[0096] In the formula μ k λ is the basis function coefficient during the k-th iteration. k J is the eddy current response signal calculated during the k-th iteration. k The Jacobian matrix at the k-th iteration can be expressed as:

[0097]

[0098] In the formula, δ() represents the Dirac function.

[0099] Based on the iteration coefficient μ, the defect imaging results can be obtained. Throughout the process, the regularization parameter β is set to 0.1 and the iteration step size α is set to 1.

[0100] S6, repeat S5, and determine whether the defect reconstruction has converged based on whether the deviation between the two defect imaging results before and after the iteration is less than a preset threshold.

[0101] Specifically, the convergence of defect reconstruction is determined by whether the deviation between the two reconstruction results before and after the iteration is less than a preset threshold. If it is less than the preset threshold, step S7 is transposed; otherwise, step S6 is transposed.

[0102] S7 outputs the final defect imaging result based on the convergence judgment result to obtain information on the location, size and quantity of defects.

[0103] In this embodiment of the invention, four different defect distributions on the surface of a copper plate are addressed: a central single defect, a non-central single defect, two defects, and four defects. Eddy current detection devices are used to obtain the response signals of different defects. The proposed electromagnetic eddy current defect imaging method based on parameter level sets is used to reconstruct the three-dimensional contour of the defects, and the results are as follows: Figure 4 As shown.

[0104] The electromagnetic eddy current defect imaging method based on parameter level sets according to embodiments of the present invention can realize three-dimensional imaging of defects in metal components based on signals measured by eddy current sensors. A planar flat plate array of eddy current sensors is constructed, and the parameters of the array eddy current sensors are optimized through orthogonal experiments and the response surface methodology to improve the uniformity of the sensitive field. The eddy current response signal is input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set. The position and initial coefficients of the basis functions are adaptively determined using the imaging results of the traditional LBP algorithm. The objective function is solved iteratively by calculating the Jacobian matrix and using the Gauss-Newton method, continuously updating the basis function coefficient parameters to achieve three-dimensional defect imaging. The defect distribution reconstructed by the imaging method proposed in this invention is consistent with experimental results, enabling accurate location and assessment of defect positions in damaged metal materials without the need for mechanical scanning devices, and has broad application prospects.

[0105] To achieve the above embodiments, such as Figure 5 As shown, this embodiment also provides an electromagnetic eddy current defect imaging system 10 based on a parameter level set, including:

[0106] The sensor parameter optimization module 100 is used to construct an array eddy current sensor and optimize the parameters of the array eddy current sensor through orthogonal experiments and response surface methodology.

[0107] The three-dimensional contour characterization module 200 is used to acquire data from the metal component under test using an optimized array eddy current sensor to obtain eddy current response signals under different excitation-reception conditions, and to process the signals using a parameter level set algorithm to characterize the three-dimensional contour of the defect.

[0108] The parameter setting module 300 is used to set the position of the discrete point source describing the three-dimensional contour of the defect, the metal conductivity value and the defect conductivity value, as well as the initial coefficient parameters of the basis function.

[0109] The objective function reconstruction module 400 is used to construct a level set reconstruction algorithm model based on the location of discrete point sources describing the three-dimensional contour, the metal conductivity value and the defect conductivity value, and the initial coefficient parameters of the basis function. The eddy current response signal is input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set.

[0110] The defect imaging result solving module 500 is used to obtain the defect imaging result by calculating the Jacobian matrix and iteratively solving the defect reconstruction objective function using the Gauss-Newton method, and to iteratively update the basis function coefficient parameters.

[0111] The deviation judgment module 600 is used to determine whether the defect reconstruction has converged based on whether the deviation between the two defect imaging results before and after the iteration process is less than a preset threshold.

[0112] The final result output module 700 is used to output the final defect imaging result based on the convergence judgment result, so as to obtain information on the location, size and quantity of defects.

[0113] Furthermore, the sensor parameter optimization module 100 is also used for:

[0114] Design a 3×3 planar array eddy current sensor and use finite element numerical solution to calculate the sensitivity matrix;

[0115] Based on the theoretical model of the non-coaxial eddy current sensor, the factors affecting the sensitivity matrix are analyzed, and the parameter range is determined.

[0116] Based on the parameter range, the optimal parameter combination can be obtained using orthogonal experiments;

[0117] Based on the optimal parameter combination, the relationship between the uniformity of the sensitivity matrix and the sensor parameters is obtained through the response surface methodology, so as to obtain the final optimized parameters of the array sensor.

[0118] Furthermore, the three-dimensional contour representation module 200 is also used for:

[0119] The metal imaging region is equivalent to a test field containing two types of conductivity, where the defect region is the target region R and the metal region is the background region Ω\R. The conductivity changes of the target region R and the background region Ω\R are calculated based on the eddy current response signal; the metal conductivity value Δσ1 and the defect conductivity value Δσ0, and the conductivity change of the entire background region Ω are expressed as:

[0120] σ(x)=σ0(1-H(f(x))-c)+σ1H(f(x)-c)

[0121] Where H(s) is the smoothing Heaviside function, expressed as:

[0122]

[0123] f(x) is a parametric level set function that satisfies:

[0124]

[0125] The level set function f(x) passes through N basis functions p i (x) linear weighted representation:

[0126]

[0127] Where, μ i These are the coefficients of the basis functions.

[0128] Furthermore, the parameter setting module 300 is also used for:

[0129] The location of the defect was initially determined using a linear back projection algorithm;

[0130] Set the position of the basis function to the defect location reconstructed by the linear back projection;

[0131] The metal conductivity value σ1 is determined based on the material of the metal to be tested, and the defect conductivity value σ0 is set to 1×10. -5 S / m, and determine the initial coefficient parameters [μ1] of the basis function based on the gray values ​​of the defect locations reconstructed by the linear back projection algorithm. * μ2 * ,…,μ n * ].

[0132] Furthermore, the defect imaging result solving module 500 is also used for:

[0133] The inverse problem of electromagnetic parameter distribution imaging in eddy current tomography can be expressed as:

[0134]

[0135] Substituting the conductivity distribution σ(x) into the above equation, we obtain the expression for the inverse problem of electromagnetic parameter distribution imaging based on the parameter level set:

[0136] argmin{|λ m -U(σ(x,μ))| 2 +β|I(μ-μ * )|}

[0137] In the formula, λ k This represents the measurement signal from the eddy current sensor, μ. * β represents the initial coefficient parameters of the basis functions, and β is the regularization parameter;

[0138] For the optimization problem, the Newton iterative algorithm is used for solution, and the iterative formula is expressed as:

[0139]

[0140] In the formula, μ k λ is the basis function coefficient during the k-th iteration. k J is the eddy current response signal calculated during the k-th iteration. k The Jacobian matrix at the k-th iteration is expressed as:

[0141]

[0142] In the formula, δ() represents the Dirac function;

[0143] The defect imaging results are obtained based on the iteration coefficient μ.

[0144] The electromagnetic eddy current defect imaging system based on parameter level sets according to embodiments of the present invention can realize three-dimensional imaging of defects in metal components based on signals measured by eddy current sensors. A planar flat array of eddy current sensors is constructed, and the parameters of the array eddy current sensors are optimized through orthogonal experiments and the response surface methodology to improve the uniformity of the sensitive field. The eddy current response signal is input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set. The position and initial coefficients of the basis functions are adaptively determined using the imaging results of the traditional LBP algorithm. The objective function is solved iteratively by calculating the Jacobian matrix and using the Gauss-Newton method, continuously updating the basis function coefficient parameters to achieve three-dimensional defect imaging. The defect distribution reconstructed by the imaging method proposed in this invention is consistent with experimental results, enabling accurate location and assessment of defect positions in damaged metal materials without the need for mechanical scanning devices, and has broad application prospects.

[0145] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0146] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A method for imaging electromagnetic eddy current defects based on parameter level sets, characterized in that, include: S1. Construct an array eddy current sensor and optimize its parameters through orthogonal experiments and response surface methodology. S2, the optimized array eddy current sensor is used to acquire data of the metal component under test to obtain eddy current response signals under different excitation-reception conditions, and the parameter level set algorithm is used to process the signals to characterize the three-dimensional contour of the defect. S3 sets the location of the discrete point source describing the three-dimensional contour of the defect, the metal conductivity value and the defect conductivity value, and the initial coefficient parameters of the basis function. S4. Based on the location of the discrete point source describing the three-dimensional contour, the metal conductivity value, the defect conductivity value, and the initial coefficient parameters of the basis function, a level set reconstruction algorithm model is constructed, and the eddy current response signal is input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set. S5. The defect imaging results are obtained by calculating the Jacobian matrix and iteratively solving the defect reconstruction objective function using the Gauss-Newton method, and the basis function coefficient parameters are iteratively updated. S6, repeat S5, and determine whether the defect reconstruction has converged based on whether the deviation between the two defect imaging results before and after the iteration is less than a preset threshold. S7 outputs the final defect imaging result based on the convergence judgment result to obtain information on the location, size and quantity of defects.

2. The method according to claim 1, characterized in that, An array eddy current sensor was constructed, and its parameters were optimized using orthogonal experiments and response surface methodology, including: Design a 3×3 planar array eddy current sensor and use finite element numerical solution to calculate the sensitivity matrix; Based on the theoretical model of the non-coaxial eddy current sensor, the factors affecting the sensitivity matrix are analyzed, and the parameter range is determined. Based on the parameter range, the optimal parameter combination can be obtained using orthogonal experiments; Based on the optimal parameter combination, the relationship between the uniformity of the sensitivity matrix and the sensor parameters is obtained through the response surface methodology, so as to obtain the final optimized parameters of the array sensor.

3. The method according to claim 1, characterized in that, An optimized array of eddy current sensors was used to acquire eddy current response signals from the metal component under test under different excitation-reception conditions. The signals were then processed using a parameter level set algorithm to characterize the three-dimensional profile of the defects, including: The metal imaging region is equivalent to a test field containing two types of conductivity, where the defect region is the target region R and the metal region is the background region Ω\R. The conductivity changes of the target region R and the background region Ω\R are calculated based on the eddy current response signal; the metal conductivity value Δσ1 and the defect conductivity value Δσ0, and the conductivity change of the entire background region Ω are expressed as: σ(x)=σ0(1-H(f(x))-c)+σ1H(f(x)-c) Where H(s) is the smoothing Heaviside function, expressed as: Where c is 0.01, and ε is the Heaviside function smoothing factor; F(x) is a parametric level set function that satisfies: The level set function F(x) passes through N basis functions p i (x) linear weighted representation: Where, μ i These are the coefficients of the basis functions.

4. The method according to claim 1, characterized in that, Set the locations of discrete point sources describing the three-dimensional profile of the defect, the values ​​of metal conductivity and defect conductivity, and the initial coefficient parameters of the basis functions, including: The location of the defect was initially determined using a linear back projection algorithm; Set the position of the basis function to the defect location reconstructed by the linear back projection; The electrical conductivity value σ1 of the metal to be tested is determined based on the material, and the initial coefficient parameters [μ1] of the basis function are determined based on the gray values ​​of the defect locations reconstructed by the linear back projection algorithm. * μ2 * ,…,μ n * ].

5. The method according to claim 1, characterized in that, The defect imaging results are obtained by calculating the Jacobian matrix and iteratively solving the defect reconstruction objective function using the Gauss-Newton method, including: The inverse problem of electromagnetic parameter distribution imaging in eddy current tomography can be expressed as: Substituting the conductivity distribution σ(x) into the above equation, we obtain the expression for the inverse problem of electromagnetic parameter distribution imaging based on the parameter level set: argmin{|λ m -U(σ(x,μ))| 2 +β|I(μ-μ * )|} In the formula, λ m The value μ represents the measurement signal from the eddy current sensor. * β represents the initial coefficient parameters of the basis functions, and β is the regularization parameter; For the optimization problem, the Newton iterative algorithm is used for solution, and the iterative formula is expressed as: Where α is the iteration step size; In the formula, μ k λ is the basis function coefficient during the k-th iteration. k J is the eddy current response signal calculated during the k-th iteration. k The Jacobian matrix at the k-th iteration is expressed as: In the formula, δ() represents the Dirac function; The defect imaging results are obtained based on the iteration coefficient μ.

6. An electromagnetic eddy current defect imaging system based on parameter level sets, characterized in that, include: The sensor parameter optimization module is used to construct an array eddy current sensor and optimize the parameters of the array eddy current sensor through orthogonal experiments and response surface methodology. The three-dimensional contour characterization module is used to acquire data from the metal component under test using an optimized array eddy current sensor to obtain eddy current response signals under different excitation-reception conditions, and to process the signals using a parameter level set algorithm to characterize the three-dimensional contour of the defect. The parameter setting module is used to set the location of discrete point sources describing the three-dimensional contour of the defect, the metal conductivity value and the defect conductivity value, as well as the initial coefficient parameters of the basis function. The objective function reconstruction module is used to construct a level set reconstruction algorithm model based on the location of discrete point sources describing the three-dimensional contour, the metal conductivity value, the defect conductivity value, and the initial coefficient parameters of the basis function. The eddy current response signal is input into the level set reconstruction algorithm model to obtain the defect reconstruction objective function based on the parameter level set. The defect imaging result solution module is used to obtain the defect imaging result by calculating the Jacobian matrix and iteratively solving the defect reconstruction objective function using the Gauss-Newton method, and to iteratively update the basis function coefficient parameters. The deviation judgment module is used to determine whether the defect reconstruction has converged based on whether the deviation between the two defect imaging results before and after the iteration process is less than a preset threshold. The final result output module is used to output the final defect imaging result based on the convergence judgment result, so as to obtain information on the location, size and quantity of defects.

7. The system according to claim 6, characterized in that, The sensor parameter optimization module is also used for: Design a 3×3 planar array eddy current sensor and use finite element numerical solution to calculate the sensitivity matrix; Based on the theoretical model of the non-coaxial eddy current sensor, the factors affecting the sensitivity matrix are analyzed, and the parameter range is determined. Based on the parameter range, the optimal parameter combination can be obtained using orthogonal experiments; Based on the optimal parameter combination, the relationship between the uniformity of the sensitivity matrix and the sensor parameters is obtained through the response surface methodology, so as to obtain the final optimized parameters of the array sensor.

8. The system according to claim 6, characterized in that, The 3D contour representation module is also used for: The metal imaging region is equivalent to a test field containing two types of conductivity, where the defect region is the target region R and the metal region is the background region Ω\R. The conductivity changes of the target region R and the background region Ω\R are calculated based on the eddy current response signal; the metal conductivity value Δσ1 and the defect conductivity value Δσ0, and the conductivity change of the entire background region Ω are expressed as: σ(x)=σ0(1-H(f(x))-c)+σ1H(f(x)-c) Where H(s) is the smoothing Heaviside function, expressed as: Where c is 0.01, and ε is the smoothing factor of the Heaviside function; F(x) is a parametric level set function that satisfies: The level set function F(x) passes through N basis functions p i (x) linear weighted representation: Where, μ i These are the coefficients of the basis functions.

9. The system according to claim 6, characterized in that, The parameter setting module is also used for: The location of the defect was initially determined using a linear back projection algorithm; Set the position of the basis function to the defect location reconstructed by the linear back projection; The electrical conductivity value σ1 of the metal to be tested is determined based on the material, and the initial coefficient parameters [μ1] of the basis function are determined based on the gray values ​​of the defect locations reconstructed by the linear back projection algorithm. * μ2 * ,…,μ n * ].

10. The system according to claim 6, characterized in that, The defect imaging result solving module is also used for: The inverse problem of electromagnetic parameter distribution imaging in eddy current tomography can be expressed as: Substituting the conductivity distribution σ(x) into the above equation, we obtain the expression for the inverse problem of electromagnetic parameter distribution imaging based on the parameter level set: argmin{|λ m -U(σ(x,μ))| 2 +β|I(μ-μ * )|} In the formula, λ m This represents the measurement signal from the eddy current sensor, μ. * β represents the initial coefficient parameters of the basis functions, and β is the regularization parameter; For the optimization problem, the Newton iterative algorithm is used for solution, and the iterative formula is expressed as: Where α is the iteration step size; In the formula, μ k λ is the basis function coefficient during the k-th iteration. k J is the eddy current response signal calculated during the k-th iteration. k The Jacobian matrix at the k-th iteration is expressed as: In the formula, δ() represents the Dirac function; The defect imaging results are obtained based on the iteration coefficient μ.

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