Nondestructive testing method for magnet coil copper conductor of fusion device and computer product

Abstract

The invention discloses a fusion device magnet coil copper conductor nondestructive testing method and a computer product, and relates to the technical field of nondestructive testing, the method comprises the following steps: obtaining original eddy current testing signals of a to-be-tested object or a plurality of areas of the to-be-tested object under specific physical conditions; preprocessing the original eddy current detection signal, wherein the preprocessing comprises denoising and signal correction; extracting features from the preprocessed signals and carrying out normalization processing; on the basis of a pre-established multi-parameter model related to the physical conditions of the to-be-tested object, theoretical signals of the to-be-tested object under various physical conditions are predicted through finite element simulation; and performing matching estimation on the normalized signal and a theoretical signal to obtain an estimated signal, and evaluating the defect existence probability based on the estimated signal. Based on an eddy current testing technology, a probe scans a sample and obtains a signal, and a finite element analysis method is combined to simulate and evaluate defects such as cracks possibly existing in a material.

Description

Technical Field

[0001] This application relates to the field of nondestructive testing technology, specifically to a nondestructive testing method for copper conductors in magnet coils of a fusion device and a computer product. Background Technology

[0002] Ensuring the integrity and safety of copper conductor components is crucial in nuclear fusion devices and other high-performance engineering structures. Eddy current testing (ECT), a non-destructive testing method, is widely used for detecting cracks and defects in steel blocks, welds, and electromechanical equipment. Its working principle is based on the generation of eddy currents in a conductor within a changing magnetic field, thereby detecting defects in the material. Specifically, the basic steps of eddy current testing technology include:

[0003] (1) Sensors and data acquisition: The eddy current probe is moved on the surface of the material being tested, and the signal is obtained by sensing the eddy current generated by the probe;

[0004] (2) Signal processing and analysis: The acquired signals are processed to remove noise and enhance the characteristics of defects for subsequent analysis;

[0005] (3) Defect assessment: The signal is interpreted using standardized indicators to assess the nature of the crack (such as depth, length, etc.).

[0006] Although eddy current testing has the advantages of non-contact, rapid scanning and high efficiency in practical applications, it also has some obvious defects and shortcomings: (1) Single parameter dependence: Current eddy current testing methods usually rely on a single parameter (such as crack depth or length) to judge the detection capability. This single parameter evaluation cannot reflect the complexity of the crack and its impact on structural integrity. For example, in some cases, microcracks may not significantly affect a single detection parameter, leading to misjudgment or missed detection. (2) Insufficient sensitivity: Existing technologies have low sensitivity when detecting microcracks and small defects, especially in high-noise environments or when the conductivity of the sample is non-uniform, the signal may be buried in noise. This may lead to safety hazards, because failure to accurately detect potential defects means that the equipment may be at risk of failure during operation. (3) Complex signal processing: Eddy current detection signals are complex and easily affected by multiple factors such as geometry and material properties, making processing and analysis difficult. For operators, the reliability and accuracy of signal analysis depend on experience, which may lead to uncertainty in the results. (4) Lack of comprehensive evaluation model: Existing methods usually lack comprehensive consideration of global defect evaluation. For example, defect detection results often vary under different conditions, making it impossible to fully assess the safety of materials under actual operating conditions. Therefore, the actual safety of equipment in use cannot be fully guaranteed. Summary of the Invention

[0007] To overcome the shortcomings of existing technologies, this application proposes a non-destructive testing method and computer product for copper conductors in magnet coils of fusion devices. Based on eddy current testing technology, this application sets multiple measurement parameters (such as the depth, location, and length of cracks), scans the sample with a probe and acquires signals, and uses finite element analysis to simulate and evaluate defects such as cracks that may exist in the material.

[0008] This application is achieved through the following technical solution:

[0009] A non-destructive testing method for the copper conductor of a fusion device magnet coil includes:

[0010] Acquire the raw eddy current detection signals of the object under test or multiple regions of the object under test under specific physical conditions;

[0011] The original eddy current detection signal is preprocessed, including noise reduction and signal correction;

[0012] Features are extracted from the preprocessed signal and then normalized.

[0013] Based on a pre-established multi-parameter model related to the physical conditions of the object under test, theoretical signals of the object under test under various physical conditions are predicted through finite element simulation.

[0014] The normalized signal is matched with the theoretical signal to obtain the estimated signal, and the probability of the existence of the defect is evaluated based on the estimated signal.

[0015] In some embodiments, acquiring the raw eddy current detection signal of the object under test or multiple regions of the object under test under specific physical conditions includes:

[0016] An eddy current probe is used to scan the surface of the object under test to obtain the original eddy current detection signal. During the scanning process, the detection sensitivity is optimized by adjusting the distance between the eddy current probe and the surface of the object under test. The specific process includes:

[0017] A significant defect-free area is selected on the object to be tested as a baseline, and a defect-free statistical threshold is established.

[0018] The eddy current probe is raised by gradation using non-metallic thin sheets, and the flat area of ​​signal-to-noise ratio versus distance is identified as the optimal detection distance.

[0019] The frequency is initially selected based on the target depth. Then, a short scan is performed on the multiple initially selected frequency points to select the frequency point with the highest signal-to-noise ratio as the optimal detection frequency.

[0020] The probe is fixed at the optimal detection distance and the optimal detection frequency to scan the object under test and obtain the original eddy current detection signal.

[0021] In some embodiments, the method of using non-metallic thin-film graded elevation of the eddy current probe to find the flat region of signal-to-noise ratio-distance as the optimal detection distance includes:

[0022] The eddy current probe is gradually raised to change the distance between the eddy current probe and the surface of the object to be measured;

[0023] Measure the signal-to-noise ratio (SNR) at different lift-off distances, find the flat region of the SNR curve, and the corresponding lift-off distance is the optimal detection distance.

[0024] In some embodiments, the preprocessing of the original eddy current detection signal includes:

[0025] Select the section that has been confirmed to be free of defects as the reference section to form the subsequent correction benchmark;

[0026] The original eddy current detection signal is filtered and subjected to power frequency notch filtering, and baseline drift is eliminated by detrending / background subtraction.

[0027] By observing the response direction with a slightly raised eddy current probe and adjusting the phase, the distance change is concentrated on one axis, and the main defect response is concentrated on the criterion axis.

[0028] By utilizing the correlation of the reference segment, interference components originating from the same source as the distance change axis are subtracted from the criterion axis signal;

[0029] Amplitude / phase correction is performed based on temperature records and reference channel readings to eliminate time-varying drift and gain differences;

[0030] The criterion axis and the distance variation axis are two orthogonal coordinate axes on the dual-channel or complex signal impedance plane in eddy current testing. The distance variation axis refers to the direction of the signal response caused by the change in the gap between the eddy current probe and the surface of the object under test, and the criterion axis is the direction of the signal response caused by the defect.

[0031] In some implementations, the process of establishing the multi-parameter model includes:

[0032] Establish governing equations related to the physical conditions of the measured sample. These governing equations are divided into two aspects: equations in the conductor and equations in the air, wherein the equations in the conductor are... The equation for air is ;in, It is a magnetic vector potential. It is an electric scalar potential. It is conductivity. It is the permeability. It is a current density, It is a vector differential operator;

[0033] By solving the governing equations, the distribution of the electromagnetic field inside the material is calculated, thereby obtaining the conductivity and current distribution. A multi-parameter model under different defect properties is established to simulate and predict the theoretical signal that the eddy current probe should output under various physical conditions.

[0034] In some implementations, the step of matching and estimating the normalized signal with the theoretical signal to obtain an estimated signal, and then assessing the probability of the existence of a defect based on the estimated signal, includes:

[0035] By combining the principle of normal distribution in statistics, the normalized signal is matched with the theoretical signal to obtain the estimated signal and its mean and variance;

[0036] Based on the mean and variance of the estimated signal, calculate the confidence interval of the signal, including the theoretical confidence level and the 95% confidence level;

[0037] Defect assessment is performed based on the theoretical confidence level and the 95% confidence level.

[0038] In some implementations, the step of matching and estimating the normalized signal with the theoretical signal to obtain the estimated signal and its mean and variance includes:

[0039] Statistical model for estimating signals:

[0040] ;

[0041] in, This is the actual detected signal; It is a multiplicative random term; These are the mean and variance of the multiplicative uncertainty, respectively, obtained by statistically analyzing the ratio of the measured signal to the theoretical signal in the calibration experiment; The theoretical signal predicted by the model; It is an additive random term; These are the mean and variance of the additive uncertainty, obtained through residual statistics of the calibration experiment;

[0042] Based on the statistical model, the optimal parameters and their corresponding estimated signals are obtained by searching the candidate parameter set.

[0043] Using normal distribution estimation, calculate the mean of the estimated signal. and variance :

[0044] , .

[0045] In some implementations, calculating the confidence interval of the signal based on the mean and variance of the estimated signal includes:

[0046] Calculate the theoretical confidence level based on the mean and variance of the signal. :

[0047] ;

[0048] in, The threshold signal represents the critical signal value for determining the existence of a crack or defect; It represents a small change in the integral and is used to calculate the probability of a signal.

[0049] Based on the standard error of the mean The 95% confidence lower bound of the mean was obtained. :

[0050] ;

[0051] in, For degrees of freedom of One-sided quantiles of the distribution;

[0052] Calculate the 95% confidence level based on the 95% lower confidence limit of the mean. :

[0053] .

[0054] Secondly, this application proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any of the above-described embodiments of the nondestructive testing method.

[0055] Thirdly, this application proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the embodiments of the above-described nondestructive testing methods.

[0056] This application proposes a non-destructive testing method for copper conductors in magnet coils of fusion devices. By comprehensively considering multiple crack parameters, the accuracy of crack detection is significantly improved. Compared with traditional methods, this application can more comprehensively reflect the actual state of the material. The improved detection method can effectively detect microcracks and minor defects, significantly reducing the rate of missed and false detections under various operating conditions. The optimized signal processing algorithm reduces the dependence on operator experience and improves the reliability of the results. This application can quickly and accurately provide evaluation results, facilitating timely preventive measures by relevant personnel, thereby strengthening the safety of the equipment.

[0057] Accordingly, the electronic device and computer-readable storage medium proposed in this application also possess the same technical effects as described above. Attached Figure Description

[0058] The accompanying drawings, which are included to provide a further understanding of the embodiments of this application and form part of this application, do not constitute a limitation on the embodiments of this application. In the drawings:

[0059] Figure 1 This is a flowchart of the non-destructive testing method proposed in the embodiments of this application;

[0060] Figure 2 This is a block diagram illustrating the principle of the non-destructive testing device proposed in the embodiments of this application;

[0061] Figure 3 This is a schematic diagram of the nondestructive testing system architecture proposed in an embodiment of this application;

[0062] Figure 4 This is a schematic diagram of the electronic device proposed in the embodiments of this application;

[0063] Figure 5 This is a schematic diagram of a computer-readable storage medium proposed in an embodiment of this application;

[0064] Figure reference numerals and corresponding component names:

[0065] 200-Nondestructive testing device, 201-Acquisition unit, 202-Correction unit, 203-Feature extraction and normalization unit, 204-Simulation prediction unit, 205-Statistical analysis unit, 206-Output unit, 300-Nondestructive testing system, 301-Input device, 302-Output device, 303-Processor A, 304-Memory A, 400-Electronic device, 410-Memory B, 420-Processor B, 411-Computer program A, 500-Computer-readable storage medium, 511-Computer program B. Detailed Implementation

[0066] In the following, the terms “comprising” or “may include” as used in the various embodiments of this application indicate the presence of a function, operation, or element of the invention and do not limit the addition of one or more functions, operations, or elements. Furthermore, as used in the various embodiments of this application, the terms “comprising,” “having,” and their cognates are intended only to indicate a specific feature, number, step, operation, element, component, or combination of the foregoing and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing, or adding one or more combinations of the foregoing.

[0067] In various embodiments of this application, the expression "or" or "at least one of A and / or B" includes any combination or all combinations of the words listed simultaneously. For example, the expression "A or B" or "at least one of A and / or B" may include A, may include B, or may include both A and B.

[0068] The terms used in the various embodiments of this application (such as "first," "second," etc.) may modify various constituent elements in the various embodiments, but do not limit the corresponding constituent elements. For example, the above terms do not limit the order and / or importance of the elements. The above terms are only used for the purpose of distinguishing one element from other elements. For example, a first user device and a second user device refer to different user devices, although both are user devices. For example, without departing from the scope of the various embodiments of this application, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.

[0069] It should be noted that if a description is made of "connecting" one component to another, then the first component can be directly connected to the second component, and a third component can be "connected" between the first and second components. Conversely, when a component is "directly connected" to another component, it can be understood that there is no third component between the first and second components.

[0070] The terminology used in the various embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the various embodiments of this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. The terms (such as those defined in a generally used dictionary) are to be interpreted as having the same meaning as in the context of the relevant technical field and are not to be interpreted as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0071] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the embodiments and accompanying drawings. The illustrative embodiments and descriptions of this application are only for explaining this application and are not intended to limit this application.

[0072] This application proposes a non-destructive testing method for the copper conductor of a fusion device magnet coil, thereby improving the safety of key structures such as nuclear fusion equipment.

[0073] like Figure 1 As shown, the non-destructive testing method proposed in this application includes the following steps:

[0074] Step 1: Obtain the original eddy current detection signals of the object under test or multiple regions of the object under test under specific physical conditions; applicable to single-piece or batch testing.

[0075] Step 2: Preprocess the original eddy current detection signal, including noise reduction and signal correction;

[0076] Step 3: Extract features from the preprocessed signal and perform normalization.

[0077] Step 4: Based on the pre-established multi-parameter model related to the physical conditions of the object under test, the theoretical signals of the object under test under various physical conditions are predicted by finite element simulation.

[0078] Step 5: Match the normalized signal with the theoretical signal to obtain the estimated signal, and evaluate the probability of the existence of the defect based on the estimated signal.

[0079] Furthermore, the non-destructive testing method proposed in this application embodiment also includes:

[0080] Generate inspection reports, outputting the probability of defects and maintenance recommendations to provide a basis for decision-making.

[0081] Furthermore, in step 1 of this application embodiment, sample data collection involves scanning the surface of the object under test using an eddy current probe to obtain raw eddy current detection signals (raw detection signals at different locations). During the scanning process, the detection sensitivity is optimized by adjusting the distance between the probe and the surface of the object under test. The core of optimizing the detection sensitivity is to maximize the defect signal / noise ratio (i.e., signal-to-noise ratio SNR) rather than simply pursuing the amplitude. The specific process is as follows:

[0082] Select a significantly defect-free area on the object to be tested as a baseline and establish a defect-free statistical threshold.

[0083] Then, non-metallic thin films (such as 50-200μm thick polyimide films) are used to raise the probe in stages to find the flat area of ​​the SNR-distance curve (i.e., the curve of signal-to-noise ratio changing with distance) as the optimal detection distance. Specifically, the probe is raised step by step to change the distance between the probe and the surface of the object under test (the distance between the probe and the object under test, i.e., the vertical gap between the bottom surface of the eddy current probe coil and the surface of the object under test). The signal-to-noise ratio (SNR) is measured at different lift-off distances to find the flat / optimal area of ​​the SNR curve. The corresponding lift-off distance is the optimal distance. In this embodiment, the probe is finally fixed at a lift-off distance of about 0.20±0.05 mm for subsequent formal scanning and detection.

[0084] The frequency is initially selected based on the target depth, and the optimal SNR point is selected by short scanning at two or three adjacent frequency points. Specifically, short scans are performed on two or three candidate frequency points within the target depth range, and the signal-to-noise ratio (SNR) is calculated at each frequency point. The frequency point with the highest SNR is selected as the optimal frequency.

[0085] The probe is fixed at the optimal detection distance and the optimal detection frequency is used to scan and acquire the original eddy current detection signal for subsequent signal processing.

[0086] Furthermore, in step 2 of this embodiment, the original eddy current detection signal simultaneously includes defect response and a large number of background / system terms, such as conductivity and temperature changes, geometric edge / hole effects, and instrument and coil impedance drift. These background / system terms can alter amplitude and phase, masking or falsifying crack features, leading to problems such as unstable threshold and increased false alarm / missed detection rates. Therefore, it is necessary to denoise and correct the original eddy current detection signal to correct the signal difference with the defect-free sample. The specific denoising and signal correction process includes:

[0087] Select the section that has been confirmed to be free of defects as the reference section to form the subsequent correction benchmark;

[0088] The original eddy current detection signal is subjected to low / bandpass filtering and power frequency notch filtering, and baseline drift is eliminated by detrending / background subtraction to ensure signal stability;

[0089] By slightly raising and lowering the probe to observe the response direction, the phase is adjusted so that the distance change is concentrated on one axis and the main defect response is concentrated on the criterion axis.

[0090] By utilizing the correlation of the reference segment, interference components originating from the same source as the distance change axis are subtracted from the criterion axis signal;

[0091] Amplitude / phase corrections are performed based on temperature records and reference channel readings to eliminate time-varying drift and gain differences.

[0092] The criterion axis and the distance variation axis are two orthogonal coordinate axes on the dual-channel / complex signal impedance plane in eddy current testing, used to separate signal components from different physical sources. The distance variation axis (lift-off axis) refers to the direction of the signal response caused by the change in the gap between the probe and the surface of the object under test (lift-off distance change). When the probe is slightly lifted or pressed down, the signal mainly moves along this axis. This axis reflects the change in coupling strength, not defect characteristics, and is an interference term that needs to be suppressed or subtracted in the correction. The specific method of determination is as follows: in a defect-free reference section, slightly lift or press the probe and observe the direction of the signal trajectory on the impedance plane. This trajectory defines the direction of the distance variation axis. Through phase rotation / coordinate transformation, this trajectory direction is aligned to a certain coordinate axis (usually the horizontal axis or the real part axis). The criterion axis (defect response axis) is the direction of the main signal response caused by defects such as cracks. It is the decision axis for judging whether a defect exists. Ideally, the defect signal and the lift-off signal are approximately orthogonal on the impedance plane. The magnitude of the signal amplitude on this axis is directly related to the geometric parameters such as the depth and length of the defect. It is the basis for subsequent threshold setting and probability calculation. The specific determination method is as follows: After a complete phase rotation, the criterion axis is usually another coordinate axis (such as the vertical axis or the imaginary axis) orthogonal to the distance change axis. The features extracted on this axis (such as peak value and integral amplitude) are used for subsequent defect evaluation and probability detection.

[0093] Furthermore, in step 3 of this application embodiment, features such as amplitude, phase, and frequency are extracted from the preprocessed signal; then, the features of each frequency point are mapped to the same scale using the statistics of the defect-free reference segment, and dimensionless features (such as amplitude ratio, phase difference, etc.) are preferentially used to enhance comparability and robustness.

[0094] Furthermore, in step 4 of this embodiment, the process of establishing the multi-parameter model includes:

[0095] The governing equations related to the physical conditions of the measured sample are established using the finite boundary element method. The governing equations are divided into two aspects: equations in a conductor and equations in air. The equations in a conductor are as follows: The equation for air is ;in, It is a magnetic vector potential. It is an electric scalar potential. It is conductivity. It is the permeability. It is the current density. It is a vector differential operator used to represent spatial differential operations such as gradient, divergence, curl, and Laplace.

[0096] By solving the above governing equations, the distribution of the electromagnetic field inside the material can be calculated, thereby obtaining the conductivity and current distribution. A multi-parameter model (defect parameter-signal model) under different defect properties (size, depth, location, and probe lift-off distance, etc.) can be established. The theoretical signal that the probe should output under specific physical conditions can be predicted through simulation.

[0097] Furthermore, in step 5 of this embodiment, a probability model is used to calculate the probability of the detected signal relative to the threshold signal, i.e., the probability of the defect existing. The specific process is as follows:

[0098] Using the principle of normal distribution in statistics, the mean and variance of the signal are estimated. Specifically, the statistical model for estimating the signal is as follows:

[0099]

[0100] in, This is the actual detected signal; It is a multiplicative random term; These are the mean and variance of the multiplicative uncertainty, respectively, obtained by statistically analyzing the ratio of the measured signal to the theoretical signal in the calibration experiment. They reflect the proportionality error and its fluctuation caused by probe calibration error, coupling fluctuation, material parameter deviation, etc. The theoretical signal predicted by the model; It is an additive random term; These are the mean and variance of the additive uncertainty, obtained through residual statistics from the calibration experiment, reflecting background interference unrelated to the signal amplitude, such as system baseline bias and electronic noise.

[0101] Based on the statistical model: Using the maximum likelihood / Bayes method on the candidate parameter set The optimal parameters are obtained by searching for the best possible signal, and the subsequent defect probability is evaluated based on the estimated signal.

[0102] Specifically, the mean of the signal is estimated using a normal distribution, which can be expressed as follows:

[0103]

[0104] The variance of a signal can be calculated as follows:

[0105]

[0106] Then based on the estimated signal The mean and variance are used to calculate the confidence interval of the signal. Specifically, this includes the calculation of the theoretical POD (theoretical confidence level), using the following formula:

[0107]

[0108] in, , These are the mean and variance of the estimated signal, respectively. The threshold signal represents the critical signal value for determining the existence of a crack or defect; It represents a small change in the integral and is used to calculate the probability of a signal.

[0109] Due to the limited number of calibration samples, point estimation It inherently contains statistical error, and its standard error is:

[0110]

[0111] in, For finite element simulation in the same The theoretical signal obtained below; For use in fitting (calibration / online self-calibration) The theoretical signal of a sample; For all samples The arithmetic mean; For use in fitting , The number of sample pairs; The standard deviation (root mean square error, RSE) of the regression residuals is calculated from the root mean square error of the regression fit during the calibration phase.

[0112] in, For the first The scalar feature values ​​(such as amplitude or peak-to-peak value) extracted on the criterion axis after filtering, phase correction, baseline subtraction and normalization of a sample at the optimal frequency and optimal extraction. These are the simulation prediction eigenvalues ​​for the corresponding conditions, used to estimate the multiplicative and additive uncertainty parameters and calculate the residual standard deviation. .

[0113] Based on this, the signal mean can be obtained. 95% confidence lower limit This is a conservative estimate considering parameter uncertainty:

[0114]

[0115] in, For degrees of freedom of One-sided quantiles of the distribution.

[0116] Therefore, considering the uncertainty of parameter estimation, the embodiments of this application can also calculate a 95% confidence level:

[0117]

[0118] use Calculated The curve is more conservative and suitable for safety-critical assessments.

[0119] In this embodiment of the application, the result is obtained through calculation. and . The theoretical POD curve, based on the mean, reflects the average detection performance under conditions where all parameters are known. This represents a conservative POD curve based on a 95% confidence lower bound, taking into account the parameter estimation uncertainty caused by a finite sample size. This hyperbolic method ensures the rigor of statistical evaluation and the safety of engineering applications, and provides recommendations for evaluation and maintenance.

[0120] The non-destructive testing method proposed in this application comprehensively evaluates cracks through multiple parameters, including crack depth, length, and distance from the sample edge, thereby improving the comprehensiveness and accuracy of the detection. This method is not only applicable to crack detection in nuclear fusion equipment, but can also be extended to structural health monitoring in aerospace, automobile manufacturing, shipbuilding and other fields. This method has universal applicability to the multi-dimensional evaluation capabilities of equipment.

[0121] Based on the same technical concept described above, this application also proposes a non-destructive testing device for the copper conductor of a fusion device magnet coil, such as... Figure 2 As shown, the non-destructive testing device 200 includes:

[0122] The acquisition unit 201 is used to acquire the original eddy current detection signals of the object under test or multiple regions of the object under test under specific physical conditions. The specific signal acquisition method is as described in step 1 above, and will not be repeated here.

[0123] The correction unit 202 is used to preprocess the original eddy current detection signal, including denoising and signal correction. The specific denoising and signal correction process is as described in step 2 above, and will not be repeated here.

[0124] The feature extraction and normalization unit 203 is used to extract features from the preprocessed signal and perform normalization processing. The specific feature extraction and normalization process is as described in step 3 above, and will not be repeated here.

[0125] The simulation prediction unit 204 is used to predict the theoretical signals of the object under various physical conditions based on a pre-established multi-parameter model related to the physical conditions of the object under test through finite element simulation. The specific model establishment process is as described in step 4 above, and will not be repeated here.

[0126] Furthermore, the statistical analysis unit 205 is used to match and estimate the normalized signal with the theoretical signal to obtain an estimated signal, and to assess the probability of the existence of a defect based on the estimated signal. The specific assessment process is as described in step 5 above, and will not be repeated here.

[0127] Furthermore, the non-destructive testing device 200 proposed in this application embodiment also includes:

[0128] Output unit 206 is used to generate inspection reports, outputting the probability of defects and maintenance suggestions to provide a basis for decision-making.

[0129] Based on the same technical concept described above, this application also proposes a non-destructive testing system for the copper conductor of a fusion device magnet coil, such as... Figure 3 As shown, the nondestructive testing system 300 proposed in this application embodiment includes:

[0130] The system comprises an input device 301, an output device 302, a processor A303, and a memory A304; wherein the number of processors A303 and memory A304 can be one or more. Figure 3 The following description uses a processor A303 and a memory A304 as an example. The input device 301, output device 302, processor A303, and memory A304 can be connected via a bus or other means. Figure 3 Taking the example of a connection between China and Israel via a bus.

[0131] Specifically, by calling the operation instructions stored in memory A304, processor A303 executes the following steps:

[0132] Acquire the raw eddy current detection signals of the object under test or multiple regions of the object under test under specific physical conditions;

[0133] The original eddy current detection signal is preprocessed, including noise reduction and signal correction;

[0134] Features are extracted from the preprocessed signal and then normalized.

[0135] Based on a pre-established multi-parameter model related to the physical conditions of the object under test, theoretical signals of the object under test under various physical conditions are predicted through finite element simulation.

[0136] The normalized signal is matched with the theoretical signal to obtain the estimated signal, and the probability of the existence of the defect is evaluated based on the estimated signal.

[0137] Optionally, by calling the operation instructions stored in memory A304, processor A303 is also used to execute any of the embodiments in the corresponding examples of the above-described nondestructive testing method.

[0138] Based on the same technical concept described above, this application also proposes an electronic device, such as... Figure 4 As shown, the electronic device 400 includes: a memory B410, a processor B420, and a computer program A411 stored in the memory B410 and executable on the processor B420. When the processor B420 executes the computer program A411, it performs the following steps:

[0139] Acquire the raw eddy current detection signals of the object under test or multiple regions of the object under test under specific physical conditions;

[0140] The original eddy current detection signal is preprocessed, including noise reduction and signal correction;

[0141] Features are extracted from the preprocessed signal and then normalized.

[0142] Based on a pre-established multi-parameter model related to the physical conditions of the object under test, theoretical signals of the object under test under various physical conditions are predicted through finite element simulation.

[0143] The normalized signal is matched with the theoretical signal to obtain the estimated signal, and the probability of the existence of the defect is evaluated based on the estimated signal.

[0144] Optionally, when processor B420 executes computer program A411, it can implement any of the embodiments in the corresponding examples of the above-described nondestructive testing method.

[0145] It should be noted that the electronic device proposed in this application embodiment is a device used to implement the above-mentioned non-destructive testing method. Therefore, based on the above-mentioned non-destructive testing method proposed in this application embodiment, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this application embodiment. Therefore, the specific implementation of the above-mentioned non-destructive testing method by the electronic system will not be described in detail here. Any electronic device used by those skilled in the art to implement the above-mentioned non-destructive testing method is within the scope of protection of this application.

[0146] Based on the same technical concept described above, embodiments of this application also propose a computer-readable storage medium, such as... Figure 5 As shown, the computer-readable storage medium 500 stores a computer program B511, which, when executed by a processor, performs the following steps:

[0147] Acquire the raw eddy current detection signals of the object under test or multiple regions of the object under test under specific physical conditions;

[0148] The original eddy current detection signal is preprocessed, including noise reduction and signal correction;

[0149] Features are extracted from the preprocessed signal and then normalized.

[0150] Based on a pre-established multi-parameter model related to the physical conditions of the object under test, theoretical signals of the object under test under various physical conditions are predicted through finite element simulation.

[0151] The normalized signal is matched with the theoretical signal to obtain the estimated signal, and the probability of the existence of the defect is evaluated based on the estimated signal.

[0152] Optionally, when the computer program B511 is executed by the processor, it can implement any of the embodiments corresponding to the above-described non-destructive testing method.

[0153] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0154] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0155] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0156] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0157] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0158] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above description is only a specific embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A non-destructive testing method for the copper conductor of a fusion device magnet coil, characterized in that, include: Acquire the raw eddy current detection signals of the object under test or multiple regions of the object under test under specific physical conditions; The original eddy current detection signal is preprocessed, including noise reduction and signal correction; Features are extracted from the preprocessed signal and then normalized. Based on a pre-established multi-parameter model related to the physical conditions of the object under test, theoretical signals of the object under test under various physical conditions are predicted through finite element simulation. The normalized signal is matched with the theoretical signal to obtain an estimated signal, and the probability of the existence of the defect is evaluated based on the estimated signal.

2. The non-destructive testing method for the copper conductor of a fusion device magnet coil according to claim 1, characterized in that, The acquisition of the raw eddy current detection signal of the object under test or multiple regions of the object under test under specific physical conditions includes: An eddy current probe is used to scan the surface of the object under test to obtain the original eddy current detection signal. During the scanning process, the detection sensitivity is optimized by adjusting the distance between the eddy current probe and the surface of the object under test. The specific process includes: A significant defect-free area is selected on the object to be tested as a baseline, and a defect-free statistical threshold is established. The eddy current probe is raised by gradation using non-metallic thin sheets, and the flat area of ​​signal-to-noise ratio versus distance is identified as the optimal detection distance. The frequency is initially selected based on the target depth. Then, a short scan is performed on the multiple initially selected frequency points to select the frequency point with the highest signal-to-noise ratio as the optimal detection frequency. The probe is fixed at the optimal detection distance and the optimal detection frequency to scan the object under test and obtain the original eddy current detection signal.

3. The non-destructive testing method for the copper conductor of a fusion device magnet coil according to claim 2, characterized in that, The method of using non-metallic thin-film graded elevation of the eddy current probe to find the flat region of signal-to-noise ratio-distance as the optimal detection distance includes: The eddy current probe is gradually raised to change the distance between the eddy current probe and the surface of the object to be measured; Measure the signal-to-noise ratio (SNR) at different lift-off distances, find the flat region of the SNR curve, and the corresponding lift-off distance is the optimal detection distance.

4. The non-destructive testing method for the copper conductor of a fusion device magnet coil according to claim 1, characterized in that, The preprocessing of the original eddy current detection signal includes: Select the section that has been confirmed to be free of defects as the reference section to form the subsequent correction benchmark; The original eddy current detection signal is filtered and subjected to power frequency notch filtering, and baseline drift is eliminated by detrending / background subtraction. By observing the response direction with a slightly raised eddy current probe and adjusting the phase, the distance change is concentrated on one axis, and the main defect response is concentrated on the criterion axis. By utilizing the correlation of the reference segment, interference components originating from the same source as the distance change axis are subtracted from the criterion axis signal; Amplitude / phase correction is performed based on temperature records and reference channel readings to eliminate time-varying drift and gain differences; The criterion axis and the distance variation axis are two orthogonal coordinate axes on the dual-channel or complex signal impedance plane in eddy current testing. The distance variation axis refers to the direction of the signal response caused by the change in the gap between the eddy current probe and the surface of the object under test, and the criterion axis is the direction of the signal response caused by the defect.

5. The non-destructive testing method for the copper conductor of a fusion device magnet coil according to claim 1, characterized in that, The process of establishing the multi-parameter model includes: Establish governing equations related to the physical conditions of the measured sample. These governing equations are divided into two aspects: equations in the conductor and equations in the air, wherein the equations in the conductor are... The equation for air is ;in, It is a magnetic vector potential. It is an electric scalar potential. It is conductivity. It is the permeability. It is a current density, It is a vector differential operator; By solving the governing equations, the distribution of the electromagnetic field inside the material is calculated, thereby obtaining the conductivity and current distribution. A multi-parameter model under different defect properties is established to simulate and predict the theoretical signal that the eddy current probe should output under various physical conditions.

6. A non-destructive testing method for the copper conductor of a fusion device magnet coil according to any one of claims 1-5, characterized in that, The method of matching and estimating the normalized signal with the theoretical signal to obtain an estimated signal, and then assessing the probability of the existence of a defect based on the estimated signal, includes: By combining the principle of normal distribution in statistics, the normalized signal is matched with the theoretical signal to obtain the estimated signal and its mean and variance; Based on the mean and variance of the estimated signal, calculate the confidence interval of the signal, including the theoretical confidence level and the 95% confidence level; Defect assessment is performed based on the theoretical confidence level and the 95% confidence level.

7. The non-destructive testing method for the copper conductor of a fusion device magnet coil according to claim 6, characterized in that, The process of matching and estimating the normalized signal with the theoretical signal to obtain the estimated signal and its mean and variance includes: Statistical model for estimating signals: ； in, This is the actual detected signal; It is a multiplicative random term; These are the mean and variance of the multiplicative uncertainty, respectively, obtained by statistically analyzing the ratio of the measured signal to the theoretical signal in the calibration experiment; The theoretical signal predicted by the model; It is an additive random term; These are the mean and variance of the additive uncertainty, obtained through residual statistics of the calibration experiment; Based on the statistical model, the optimal parameters and their corresponding estimated signals are obtained by searching the candidate parameter set. Using normal distribution estimation, calculate the mean of the estimated signal. and variance : ， 。 8. The non-destructive testing method for the copper conductor of a fusion device magnet coil according to claim 7, characterized in that, The method of calculating the confidence interval of a signal based on the mean and variance of the estimated signal includes: Calculate the theoretical confidence level based on the mean and variance of the signal. : ； in, The threshold signal represents the critical signal value for determining the existence of a crack or defect; It represents a small change in the integral and is used to calculate the probability of a signal. Based on the standard error of the mean The 95% confidence lower bound of the mean was obtained. : ； in, For degrees of freedom of One-sided quantiles of the distribution; Calculate the 95% confidence level based on the 95% lower confidence limit of the mean. : 。 9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the non-destructive testing method according to any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the non-destructive testing method according to any one of claims 1-8.

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