Method for increasing magnetic leakage field of internal defects of ferromagnetic material based on ac-dc composite magnetization

Abstract

The application discloses a method for increasing the magnetic leakage field of internal defects of ferromagnetic materials based on AC-DC composite magnetization, which comprises the following steps: fixing a workpiece at the center of a composite excitation coil, and synchronously applying DC and high-frequency AC currents; locking the current after pure DC magnetization to saturation, establishing a basic magnetic leakage field; superimposing an AC current to dynamically reduce the surface permeability and weaken the magnetic shielding effect; scanning and collecting the magnetic leakage field signals through a differential Hall sensor array, and performing background magnetic field subtraction, peak value comparison and adaptive filtering processing; and using the gradient descent method and the Bayesian optimization to determine the optimal magnetization parameter combination. The system integrates a composite excitation coil and a signal conditioning unit, realizes synchronous excitation, signal acquisition and real-time analysis, enhances the magnetic leakage field signals of deep defects through AC-DC composite magnetization, solves the problem of signal weakening caused by traditional DC saturation, improves the defect detection sensitivity and efficiency, and is suitable for the nondestructive testing scene of ferromagnetic materials.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nondestructive testing, and in particular to a method for increasing the magnetic leakage field of internal defects of ferromagnetic materials based on alternating current and direct current composite magnetization. BACKGROUND

[0002] The existing technology has two bottlenecks in enhancing the magnetic leakage field of internal defects of ferromagnetic materials: 1. Saturation suppression contradiction: the direct current magnetic field needs to reach magnetic saturation to excite the maximum basic magnetic leakage signal, but strong saturation will significantly suppress the magnetic permeability disturbance Δ of the internal defects, resulting in weakening of the internal defect signal; 2. Magnetic shielding effect: the high-μ surface layer forms a "magnetic short circuit" effect, and the magnetic leakage field of internal defects deeper than 5mm attenuates by more than 60%.

[0003] Limitations of existing enhancement techniques: 1. Patent CN211603029U discloses a magnetic field increasing device for improving the sensitivity of magnetic flux leakage detection, which uses a permanent magnet and an electromagnetic coil to superimpose a magnetic field. Although the field strength can be adjusted, the direct current magnetic field still operates in the saturation region, and the Δ attenuation problem is not solved, and an alternating current desaturation mechanism is not designed; 2. Patent CN201810182149.4 discloses an internal defect detection circuit for ferromagnetic materials based on low-frequency magnetic flux, which improves the penetration depth by exciting at 20Hz. However, the lowest frequency (20Hz) still cannot avoid the magnetic shielding effect; 3. Patent CN115189494A discloses a centrifugal variable magnetic flux permanent magnet motor and a method for increasing and decreasing the magnetic flux of the motor permanent magnet, which adjusts the magnetic resistance of the magnetic leakage path through a mechanical structure. However, this solution is only applicable to motor permanent magnet structures and cannot be transferred to the ferromagnetic material defect detection scenario. 4. Patent CN102590328A discloses a permanent magnet and alternating current composite magnetic flux leakage detection method. Although it also uses alternating current and direct current composite magnetization, it has two defects due to the time-sharing excitation mechanism: (1) Efficiency loss: the step-by-step scanning of direct current followed by alternating current leads to repeated detection of the same area, resulting in a reduction in efficiency of ≥50%; (2) Signal attenuation: the permanent magnet and electromagnetic coil cooperate to reach the optimal operating point during the direct current phase, but the direct current component is removed during the alternating current phase, leaving only the permanent magnet bias, resulting in a decrease in total direct current field strength, a shift in the operating point, and attenuation of the deep defect magnetic leakage field. The alternating current magnetic field can only locate the defect due to the skin effect limitation, but cannot maintain or enhance the deep signal. SUMMARY

[0004] The present application overcomes the shortcomings of the prior art and provides a method for increasing the magnetic leakage field of internal defects of ferromagnetic materials based on alternating current and direct current composite magnetization.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present application is as follows: a method for increasing the magnetic leakage field of internal defects of ferromagnetic materials based on alternating current and direct current composite magnetization, comprising the following steps:

[0006] S1: the ferromagnetic workpiece to be detected is fixed at the center of the composite excitation coil through a support, the coil is connected to a direct current power supply and a high-frequency alternating current power supply, system initialization and workpiece positioning are completed;

[0007] S2: the pure direct current magnetization mode is to turn on the direct current power supply, gradually increase the current until the output signal amplitude of the Hall sensor array no longer increases, lock the direct current value, realize saturation direct current magnetization locking, and establish the maximum basic magnetic leakage field;

[0008] S3: the alternating current and direct current composite magnetization mode is to synchronously apply a high-frequency alternating current on the basis of locking the direct current, so that the surface layer permeability of the workpiece is periodically reduced, and the magnetic shielding layer is dynamically weakened;

[0009] S4: a linear Hall sensor is used to scan the surface of the workpiece at a speed of 5-10 mm / s, and the magnetic leakage field signal under the action of the alternating current and direct current composite field is collected in real time;

[0010] S5: the collected signal is subjected to background magnetic field deduction and peak value comparison processing, the background magnetic field interference is eliminated through a double-sample difference method, the leakage field peak value curve changing with the magnetization current or alternating current parameter is drawn, the optimal magnetization condition is determined, and the signal gain effect is verified.

[0011] In a preferred embodiment of the present application, the composite excitation coil is wound with a plurality of enameled copper wires, the coil type is a composite excitation coil assembly, the direct current value ranges from 0 to 30 A, the frequency of the high-frequency alternating current ranges from 500 to 1500 Hz, and the amplitude ranges from 1 to 6 A.

[0012] In a preferred embodiment of the present application, the Hall sensor array adopts a differential pair tube structure, two Hall sensors are vertically installed at a distance of 8-10 mm, and the geomagnetic field interference is eliminated through a differential amplifier; the sensor output signal is sampled through a 24-bit ADC, the sampling rate is set to 10 kHz, the power frequency interference and high-frequency noise are filtered through a digital filter; the original signal and the background magnetic field signal are subjected to real-time subtraction processing through an FPGA, and the net magnetic leakage field data is sent to an upper computer for storage through a wireless transmission module.

[0013] In a preferred embodiment of the present application, the background magnetic field deduction adopts a double Hall sensor dynamic calibration technology, the sensor sensitivity difference is automatically corrected through correlation analysis of the signals of the two sensors; an adaptive filtering algorithm is introduced in the signal conditioning stage, the filtering parameters are dynamically adjusted according to the real-time noise level, and the effective signal retention rate is ensured to be not less than 95%; the determination of the optimal magnetization current adopts a gradient descent method, the second derivative of the magnetic leakage field signal amplitude and the current value is calculated through iteration, and the current value corresponding to the maximum gradient point is located.

[0014] In a preferred embodiment of the present application, the original signal is derived under the pure DC magnetization mode and the background magnetic field is subtracted to obtain the reference magnetic leakage field; under the AC-DC composite magnetization mode, the optimal magnetization current is added to the AC current, the original signal is derived and the background magnetic field is subtracted to obtain the enhanced magnetic leakage field; the optimal parameter combination is determined by comparing the peak value changes of the reference and enhanced magnetic leakage fields.

[0015] In a preferred embodiment of the present application, the determination of the optimal parameter combination is based on the curve of the change of the magnetic leakage field peak value with the magnetization current, the AC amplitude and the frequency.

[0016] In a preferred embodiment of the present application, a magnetization system based on the AC-DC composite magnetization of the ferromagnetic material internal defect magnetic leakage field enhancement method is provided, based on the ferromagnetic material internal defect magnetic leakage field enhancement method, comprising: a composite excitation coil assembly and a signal conditioning unit; the coil assembly is simultaneously connected with a direct current and a high-frequency alternating current to realize synchronous excitation; the signal conditioning unit performs background magnetic field subtraction and peak value comparison analysis.

[0017] In a preferred embodiment of the present application, the signal conditioning unit integrates a Hall sensor array and a data processing module; the sensor array is linearly arranged with a lift-off value of 0.4-0.6 mm and a scanning speed of 5-10 mm / s; the data processing module performs original signal acquisition, background magnetic field subtraction, peak extraction and curve fitting.

[0018] The present application solves the defects in the background art and has the following beneficial effects:

[0019] (1) The composite excitation coil is simultaneously connected with a direct current and a high-frequency alternating current, the pure DC magnetization mode is used to lock the saturated direct current value, the current is gradually increased until the Hall sensor output signal amplitude no longer rises, and the maximum basic magnetic leakage field is locked; the synchronous application of the high-frequency alternating current makes the workpiece surface permeability periodically decrease, while suppressing the magnetic shielding effect, the internal defect magnetic permeability disturbance Δ is selectively retained, thereby effectively enhancing the magnetic leakage field signal at the internal defect under the background of maintaining the maximum basic magnetic leakage field, and solving the contradiction between signal weakening and magnetic shielding coexistence caused by strong saturation in the traditional DC saturation magnetization.

[0020] (2) The magnetic field generated by the high-frequency alternating current periodically changes the workpiece surface permeability, combined with the linear Hall sensor array differential pair structure, the alternating current magnetic field dynamically reduces the high μ surface permeability, reducing the "magnetic short circuit" effect; the differential pair structure realizes effective detection of deep defects through differential processing of the signals of two Hall sensors, eliminating common-mode interference such as the geomagnetic field.

[0021] (3) The dynamic parameter optimization algorithm is introduced, the dynamic parameter optimization algorithm adopts Bayesian optimization, the gradient descent method is combined to determine the optimal magnetization condition, the second derivative of the leakage magnetic field signal amplitude and the current value is calculated through iteration, the current value corresponding to the maximum gradient point is located, the direct current, the alternating current frequency and the scanning speed parameters are dynamically adjusted, the objective function is the weighted sum of the maximum signal gain and the minimum detection time, the weight coefficient is adjustable, the detection efficiency is significantly improved, and the repeated detection and signal attenuation problems caused by time-sharing excitation are avoided. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0023] Figure 1 It is a ferromagnetic material internal defect leakage magnetic field increasing method detection flow chart of the preferred embodiment of the present application;

[0024] Figure 2 It is a magnetization system schematic diagram of the preferred embodiment of the present application;

[0025] Figure 3 It is a direct current magnetization minus background magnetic field data graph of the preferred embodiment of the present application;

[0026] Figure 4 It is a leakage magnetic field peak value graph under different magnetization currents under pure direct current excitation of the preferred embodiment of the present application;

[0027] Figure 5 It is a different amplitude graph of the original data of alternating current and direct current composite magnetization after subtracting the background magnetic field of the preferred embodiment of the present application;

[0028] Figure 6 It is a different frequency graph of the original data of alternating current and direct current composite magnetization after subtracting the background magnetic field of the preferred embodiment of the present application;

[0029] Figure 7 It is a peak value of alternating current and direct current composite magnetization original data changes with alternating current amplitude and frequency graph of the preferred embodiment of the present application.

[0030] In the figure: 101, composite excitation coil assembly; 104, workpiece to be detected; 105, defect; 106, Hall sensor array; 108, direct current magnetization area; 109, alternating current and direct current magnetization area. DETAILED DESCRIPTION

[0031] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work belong to the protection scope of the present application.

[0032] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can be practiced in other ways different from those described herein, therefore, the scope of protection of the present application is not limited by the specific embodiments disclosed below.

[0033] In the description of the present application, it should be understood that the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, therefore, it cannot be understood as a limitation on the scope of protection of the present application. In addition, the terms "first", "second" and the like are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second" and the like can explicitly or implicitly include one or more features. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0034] In the description of the present application, it should be noted that, unless otherwise specified and limited, the terms "mounting", "connecting", "connecting" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood through specific circumstances.

[0035] As Figure 1 shown, based on the method for increasing the internal defect leakage magnetic field of ferromagnetic material based on AC-DC composite magnetization, the following steps are taken:

[0036] S1: the ferromagnetic workpiece to be detected is fixed on the center of the composite excitation coil through the support, the coil is connected to the DC power supply and the high-frequency AC power supply, and the system initialization and workpiece positioning are completed.

[0037] Further, the composite excitation coil is wound with multiple strands of enameled copper wire, and the coil type is a composite excitation coil assembly. The direct current value ranges from 0 to 30 A, and the high-frequency alternating current frequency ranges from 500 to 1500 Hz, and the amplitude ranges from 1 to 6 A.

[0038] In another embodiment, the coil surface is embedded with a PT100 platinum resistance temperature sensor, which triggers a PID control algorithm to reduce the direct current amplitude when the temperature exceeds 85℃, ensuring that the working temperature is stable at 60-85℃. The Keens LK-H050 laser displacement sensor is used to calibrate the core-workpiece spacing, and the calibration process includes reference spacing collection and dynamic deviation compensation verification stage. The compensation formula of the dynamic deviation compensation verification stage is: .

[0039] The dual power supply redundancy design adopts Schneider NSX400N circuit breaker, the main and standby power supply voltage difference is less than or equal to 2%, the switching time is less than or equal to 20ms, and the super capacitor group maintains power supply during switching. The material identification algorithm collects the reflected spectrum through the Ocean Optics USB4000 spectrometer, inputs the SVM model after Savitzky-Golay filtering, matches the 12-class material library, forms a complete temperature-permeability mapping, spacing calibration log, power switching record and material identification report closed-loop evidence chain.

[0040] S2: The pure direct current magnetization mode is to turn on the direct current power supply, gradually increase the current until the output signal amplitude of the Hall sensor array no longer increases, lock the direct current value, realize the saturation direct current magnetization locking, and establish the maximum basic magnetic leakage field.

[0041] Further, the linear Hall sensor array adopts a differential pair tube structure, two Hall sensors are installed vertically at a distance of 8-10mm, and the geomagnetic field interference is eliminated through a differential amplifier. The sensor output signal is sampled by a 24-bit ADC with a sampling rate of 10kHz, and the power frequency interference and high-frequency noise are filtered through a digital filter. The original signal and the background magnetic field signal are processed in real time by FPGA, and the net magnetic leakage field data is sent to the upper computer for storage through the wireless transmission module.

[0042] In another embodiment, the three-dimensional magneto-resistive sensor reconstruction algorithm is extended with a deep learning defect identification system. A HMC1053L magneto-resistive sensor with a sensitivity of 0.7 mV / V / Gs and a range of ±6Gs is used to construct an 8x8 sensor array with a pitch of 5mm. The three-dimensional leakage magnetic field distribution is iteratively reconstructed by the gradient descent method, and the iteration termination condition is RMSE < 0.001Gs. The deep learning model uses an improved U-Net architecture, with an input of 64x64 pixel leakage magnetic field grayscale image, a convolution kernel of 3x3, a step of 1, and a ReLU activation function. The training data set contains 10,000 simulated defect images and 5,000 real measured images, labeled as a bounding box + class label. The model training uses the Adam optimizer, and the test set accuracy is ≥95%, otherwise adjust the network depth or the number of convolution kernels. The system components include a NI USB-6361 data acquisition card, a NVIDIA Jetson TX2 edge computing module, and a LabVIEW 2021 visualization software. The operation process covers data preprocessing, model training, verification deployment, and real-time defect identification output, forming a complete detection closed loop.

[0043] S3: The AC-DC magnetization mode is to apply a high-frequency alternating current synchronously on the basis of locking the direct current, so that the permeability of the workpiece surface layer is periodically reduced, and the magnetic shielding layer is dynamically weakened.

[0044] S4: A linear Hall sensor is used to scan the workpiece surface at a speed of 5-10mm / s, and real-time leakage magnetic field signals under the action of AC-DC composite field are collected.

[0045] Further, the AC-DC composite magnetization mode realizes the synergistic enhancement of the surface and deep defect signals of ferromagnetic materials by synchronously applying a direct current and a high-frequency alternating magnetic field. The physical essence lies in breaking through the suppression effect of traditional direct current saturation magnetization and the skin effect limitation of high-frequency alternating magnetization. The direct current magnetic field establishes the basic leakage magnetic field through the Ampere loop theorem. When the current increases to 25A, the Hall sensor output signal is saturated, indicating that the material reaches the magnetic saturation state. At this time, the permeability perturbation Δ of the internal defects is suppressed by the strong direct current field. The high-frequency alternating magnetic field (500-1500Hz) generates a periodic permeability change in the workpiece surface layer through Faraday's law of electromagnetic induction, so that the surface layer permeability μ is periodically reduced. This dynamic modulation weakens the surface "magnetic short circuit" effect and reduces the attenuation of the deep leakage magnetic field in the conduction process. Mathematical derivation shows that the μ change caused by the alternating magnetic field satisfies where Let μ be the modulation depth and f be the AC frequency. As μ decreases, the magnetoresistance of the leakage magnetic field generated by deep defects increases during conduction at the surface, which in turn enhances the leakage magnetic field signal acquired by the sensor. Experimental data show that when detecting a 20mm thick steel plate with a sensor on one side and a defect on the other, the defect signal gain under composite magnetization reaches 26.47%; under the same arrangement conditions on a 10mm thick steel plate, the defect signal gain reaches 47.2%, verifying the physical effectiveness of this mode. This mode enhances the deep defect signal by dynamically adjusting the surface permeability, solving the problem of difficult deep defect detection in traditional methods.

[0046] The Hall sensor array employs a differential pair structure, consisting of two vertically mounted linear Hall elements spaced 8-10 mm apart. Its operating principle is based on the Hall effect: when a current I passes through a semiconductor placed in a magnetic field B, a potential difference is generated perpendicular to both the current and the magnetic field. The differential pair eliminates common-mode interference such as that from the Earth's magnetic field by subtracting the signals from the two sensors. For example, when the Earth's magnetic field... When present, both sensors output After difference Effectively inhibited The anti-interference design also includes 24-bit ADC sampling (sampling rate 10kHz) and digital filters. The former reduces quantization error through high-resolution quantization, while the latter eliminates 50Hz power frequency interference and high-frequency noise through bandpass filtering (0-2kHz). An FPGA-implemented real-time background magnetic field subtraction algorithm subtracts the original signal from the background magnetic field signal calibrated by the dual Hall sensors, further improving signal purity. Experiments show that this design achieves an effective signal retention rate of no less than 95%. The differential pair structure improves signal detection accuracy by eliminating common-mode interference, while the high-resolution ADC and digital filters ensure the quality of signal acquisition.

[0047] S5: Perform background magnetic field subtraction and peak value comparison processing on the acquired signal, eliminate background magnetic field interference by using the two-sample difference method, plot the leakage magnetic field peak value as a function of magnetization current or AC parameters, determine the optimal magnetization conditions, and verify the signal gain effect.

[0048] The two-sample difference method eliminates background magnetic field interference by comparing leakage magnetic field signals in pure DC magnetization mode and AC / DC composite magnetization mode. The specific procedure is as follows: In pure DC mode, the leakage magnetic field signal on the workpiece surface is acquired. The signal is collected and stored as a background magnetic field reference; in the composite magnetization mode, the signal is acquired. Real-time subtraction achieved through FPGA The net leakage magnetic field signal is obtained. Mathematical derivation shows that this method is equivalent to frequency domain filtering, i.e. where f is the frequency component. Since the background field mainly contains low frequency components (such as the geomagnetic field), while the defect signal contains high frequency components (such as the harmonics generated by the alternating modulation), the low frequency interference is suppressed after the difference, and the high frequency defect signal is retained. Experimental data show that this method improves the signal-to-noise ratio by 12 dB, and the defect detection rate is increased to 95%. The double-sample difference method improves the accuracy of defect detection by eliminating the interference of the background magnetic field, and solves the problem of the influence of background interference on the detection result in the traditional method.

[0049] Further, the background magnetic field deduction adopts a double Hall sensor dynamic calibration technology, which automatically corrects the sensitivity difference of the two sensors through correlation analysis of the signals of the two sensors; an adaptive filtering algorithm is introduced in the signal conditioning stage, which dynamically adjusts the filtering parameters according to the real-time noise level, ensuring that the effective signal retention rate is not less than 95%; the determination of the optimal magnetizing current uses the gradient descent method, which locates the current value corresponding to the maximum gradient point by iteratively calculating the second derivative of the magnetic leakage field signal amplitude and the current value.

[0050] The adaptive filtering algorithm dynamically adjusts the filtering parameters by monitoring the noise level in real time. The core is the least mean square error (LMS) algorithm, and the filter coefficient update rule is where is the current coefficient, is the step factor, is the error signal (the difference between the expected signal and the filter output), is the input signal. The step factor is adjusted dynamically according to the noise power. When the noise power increases, decreases to reduce the convergence speed but improve the stability; when the noise power decreases, increases to speed up the convergence. Experiments show that this mechanism can maintain an effective signal retention rate of not less than 95% when the noise power changes ±20 dB. The adaptive filtering algorithm adjusts the filtering parameters dynamically to adapt to different noise environments, improving the robustness of signal processing and solving the problem of fixed filtering parameters in traditional methods that cannot adapt to environmental changes.

[0051] The original signal is derived under the pure DC magnetization mode and the background magnetic field is subtracted to obtain the reference magnetic leakage field; under the AC-DC composite magnetization mode, the optimal magnetizing current is added to the AC current, the original signal is derived, and the background magnetic field is subtracted to obtain the enhanced magnetic leakage field; by comparing the peak value changes of the reference and enhanced magnetic leakage fields, the optimal parameter combination is determined.

[0052] The determination basis of the optimal parameter combination is the curve of the change of the magnetic leakage field peak value with the magnetizing current, the AC amplitude and the frequency.

[0053] In another embodiment, a dynamic parameter optimization algorithm is introduced, and the objective function is set as the weighted sum of maximum signal gain and minimum detection time, with adjustable weight coefficients; the Bayesian optimization uses a Gaussian process regression model, and the search space includes direct current (0-30 A), alternating frequency (500-1500 Hz), and scanning speed (5-10 mm / s); the optimization process includes an initialization stage (random sampling of 20 groups of parameters), an iterative optimization stage (selection of the optimal parameter each time), and a convergence judgment (gain increase of less than 1% for three consecutive iterations); the real-time monitoring module collects the signal-to-noise ratio of the magnetic flux leakage field, the detection time, the temperature, and other parameters as optimization feedback; the user-defined module supports setting the priority target (priority of accuracy or speed) and adjusting the optimization weight; the optimization results are stored in the parameter database, and the historical optimal parameters can be called; the system supports online optimization, and the optimization model is automatically updated every 10 workpieces; the algorithm parameters include population size 50, iteration number 100, crossover probability 0.8, mutation probability 0.1 (genetic algorithm part), inertia weight 0.7, individual learning factor 1.5, and social learning factor 1.5 (particle swarm optimization part); the objective function , and the constraint conditions are direct current ≤ 30 A, alternating frequency 500-1500 Hz, and alternating amplitude 1-6 A; the edge computing module uses NVIDIA Jetson AGX Xavier to run the algorithm, and the host computer software is developed and verified using MATLAB R2021b, forming a complete dynamic parameter optimization closed loop.

[0054] The dynamic parameter optimization algorithm aims to maximize the signal gain and minimize the detection time, and constructs an optimization objective function , where , is the weight coefficient, and are the peak values of the magnetic flux leakage field before and after the composite magnetization, and T is the detection time. The Bayesian optimization framework is used to establish the mapping relationship between the parameter space (direct current 0-30 A, alternating frequency 500-1500 Hz, and scanning speed 5-10 mm / s) and the objective function through the Gaussian process regression model. The optimization process includes an initialization stage (random sampling of 20 groups of parameters) and an iterative optimization stage (selection of the parameter with the maximum posterior probability for evaluation each time). The gradient descent method is used to accurately locate the optimal parameter, and the second-order derivative of the objective function with respect to the direct current I is calculated to locate the value corresponding to the maximum gradient. For example, when , the iteration is terminated, and I at this time is the best magnetization current. Experiments show that this algorithm improves the detection efficiency by 60% and the signal gain by 47.2%. The dynamic parameter optimization algorithm balances the detection efficiency and accuracy by automatically adjusting the parameters, and solves the problem of parameter setting relying on experience in traditional methods.

[0055] As Figure 2As shown, the detection system is composed of a composite excitation coil assembly 101, a workpiece 104 to be detected, a defect 105, and a Hall sensor array 106. The composite excitation coil has an inner diameter of 200 mm, is wound with multiple strands of enameled copper wire, has 1000 turns, and is connected to the workpiece surface through a hydraulic support for stepless adjustment (adjustment range 0~50 mm). The Hall sensor array has an 8*8 layout, a pitch of 5 mm, a sensitivity of 13 mV / T, and scans the workpiece surface synchronously with the coil.

[0056] By using high-frequency alternating current to generate a magnetic field that adheres to the DC magnetized area 108 on the workpiece surface under the condition of obtaining the optimal leakage magnetic field of internal defects under DC excitation, the μ of the AC magnetized area 109 on the workpiece surface is periodically reduced, which has little effect on the leakage magnetic field generated by the defect. Although the permeability disturbance leakage magnetic field is reduced, the magnetic shielding leakage magnetic field is reduced more, thereby obtaining a stronger leakage magnetic field for sensor acquisition.

[0057] Key component parameters

[0058] DC power module: 0~30A adjustable, step 0.5A, accuracy ±0.1A.

[0059] High-frequency AC power module: 500~1500Hz adjustable, preferably 800Hz; amplitude 1~6A adjustable, preferably 3A.

[0060] Scanning system: servo motor drive, speed 5~10mm / s adjustable, positioning accuracy ±0.1mm.

[0061] Signal acquisition module: 24-bit ADC, sampling rate 10kHz, bandwidth 0~2kHz.

[0062] Data processing unit: NVIDIA Jetson TX2 edge computing module, running signal conditioning algorithm.

[0063] The detailed steps of the detection method include:

[0064] System initialization and workpiece positioning

[0065] A 10mm thick steel plate (size 300x200x10mm) to be detected is fixed on the center of the composite excitation coil by a mechanical arm. The coil is connected to the DC power supply and the high-frequency AC power supply, and the system parameters are initialized: scanning speed 8mm / s, lift-off value 0.5mm, DC current upper limit 30A, AC frequency 800Hz, amplitude 3A.

[0066] Saturated DC magnetization locking

[0067] Turn on the DC power supply and gradually increase the current from 0A in 0.5A increments. Monitor the leakage magnetic field signal in real time using a Hall sensor array. When the current increases to 25A, the signal amplitude no longer increases with the current, indicating that the workpiece has reached magnetic saturation. Lock the DC current value at 25A and establish the maximum basic leakage magnetic field.

[0068] High-frequency AC modulation

[0069] A high-frequency alternating current of 800Hz and 3A is synchronously applied to the coil, generating a high-frequency magnetic field that periodically reduces the permeability of the workpiece surface. The distance between the coil and the workpiece is monitored in real time by a laser displacement sensor. When the deviation exceeds ±0.3mm, the height of the coil support is automatically adjusted by a stepper motor, with a compensation amount Δh = 0.5 × the measured deviation value.

[0070] Signal dynamic acquisition

[0071] A Hall sensor array is used to scan the workpiece surface at a speed of 8 mm / s to acquire leakage magnetic field signals under the combined AC and DC fields in real time. After the signals are digitized by a 24-bit ADC, the background magnetic field is subtracted in real time through an FPGA, and the net leakage magnetic field data is transmitted to a cloud database via a 5G module.

[0072] Signal Conditioning and Analysis

[0073] Multi-dimensional processing of the acquired raw signals:

[0074] Background magnetic field subtraction: A dual Hall sensor differential method is used, and the sensor sensitivity difference is automatically corrected through correlation coefficient analysis.

[0075] Spectrum analysis: The FFT transform is applied to analyze the frequency domain characteristics of the signal, filtering out 50Hz power frequency interference and high-frequency noise above 2kHz.

[0076] Peak detection: The peak value of the leakage magnetic field is extracted by the sliding window method, and the curve of the peak value as a function of magnetizing current / AC parameters is plotted.

[0077] Determining the optimal magnetization conditions: The second derivative of the leakage magnetic field signal amplitude and the current value is calculated using the gradient descent method, and the current value corresponding to the maximum gradient value is located.

[0078] Experimental Data and Results Analysis

[0079] like Figures 3-4 As shown, peak leakage magnetic field analysis under DC magnetization

[0080] Under DC magnetization, the peak value of the leakage magnetic field increases logarithmically with the increase of the magnetizing current. In the range of 0~25A, the peak value increases from 0.016T to 0.0546T, with an increase rate of 241.25%. When the current exceeds 25A, the signal increase slows down, verifying the accuracy of the determination of magnetic saturation state.

[0081] AC-DC composite magnetization effect verification

[0082] By comparing the signal amplitude of single coil DC magnetization and AC-DC composite magnetization, the defect signal enhancement effect is verified:

[0083] 20mm deep defect: single DC magnetization signal amplitude 0.016T, after composite magnetization increased to 0.0204T, gain 26.47%.

[0084] 10mm deep defect: single DC magnetization signal amplitude 0.0371T, after composite magnetization increased to 0.0546T, gain 47.2%.

[0085] AC parameter optimization experiment

[0086] As shown in Figures 5-7 , the influence of AC frequency and amplitude on the peak value of magnetic leakage field is analyzed by orthogonal experiment:

[0087] Frequency effect: within the range of 500~1500Hz, the signal gain is optimal at 800Hz, which is 18.7% higher than that at 500Hz.

[0088] Amplitude effect: within the range of 1~6A, the signal gain is optimal at 3A, which is 12.3% higher than that at 1A.

[0089] Parameter coupling effect: response surface method is used to establish a peak prediction model, and the determination coefficient R²=0.963, which verifies the reliability of the model.

[0090] System self-check and fault diagnosis

[0091] A closed-loop self-checking system is constructed, including:

[0092] Power system self-check: real-time monitoring of DC / AC power output voltage fluctuation (threshold value ±3%).

[0093] Sensor calibration verification: standard Helmholtz coil is used for periodic calibration, with error requirement <±1%.

[0094] Communication link detection: 5G / Wi-Fi 6 communication delay is monitored by heartbeat packet mechanism (threshold value <100ms).

[0095] Fault diagnosis expert system: 100 diagnostic rules are built in, supporting remote expert consultation function.

[0096] This embodiment is suitable for internal defect detection of ferromagnetic components such as pressure vessels, pipelines and bearings. Compared with traditional technology, it has the following advantages:

[0097] Improved detection accuracy: deep defect detection capability breaks through 20mm, signal gain reaches 47.2%.

[0098] Detection efficiency is improved: single piece detection time is shortened to 5 minutes, which is improved by 60% compared with the traditional method.

[0099] Non-contact detection: avoid mechanical contact damage to the workpiece, suitable for in-service equipment detection.

[0100] Intelligent analysis: integrate deep learning defect recognition module to realize automatic classification of defect types.

[0101] The embodiment completely describes the structure composition, detection method, signal processing flow and experimental verification result of the ferromagnetic material internal defect detection system based on AC-DC composite magnetization. Through the "saturation DC locking + high-frequency AC breaking shield" mechanism, the double bottleneck problem in the traditional detection technology is effectively solved, and the magnetic leakage field signal is significantly enhanced, which provides an innovative technical solution for the field of industrial nondestructive testing.

[0102] According to the ideal embodiments of the application, through the above description, relevant personnel can make various changes and modifications without deviating from the technical idea of the application. The technical scope of the application is not limited to the contents of the specification, and the technical scope must be determined according to the scope of claims.

Claims

1. A method for increasing the magnetic leakage field of internal defects in ferromagnetic materials based on AC-DC hybrid magnetization, characterized in that, The method comprises the following steps: S1: the ferromagnetic workpiece to be detected is fixed at the center of the composite excitation coil through a support, the coil is connected to a direct current power supply and a high-frequency alternating current power supply, system initialization and workpiece positioning are completed; S2: the pure direct current magnetization mode is to turn on the direct current power supply, gradually increase the current until the output signal amplitude of the Hall sensor array no longer increases, lock the direct current value, realize saturation direct current magnetization locking, establish the maximum basic magnetic leakage field; S3: the alternating current and direct current composite magnetization mode is to apply a high-frequency alternating current on the basis of locking the direct current, periodically reduce the surface layer permeability of the workpiece and dynamically weaken the magnetic shielding layer; S4: a linear Hall sensor is used to scan the surface of the workpiece at a speed of 5-10 mm / s, and real-time collection of the magnetic leakage field signal under the action of the alternating current and direct current composite field is realized; S5: background magnetic field deduction and peak value comparison processing are performed on the collected signal, background magnetic field interference is eliminated through a double sample difference method, a leakage field peak value curve changing with magnetization current or alternating current parameter is drawn, the optimal magnetization condition is determined, and the signal gain effect is verified; The Hall sensor array adopts a differential pair tube structure, two Hall sensors are installed vertically at a distance of 8-10 mm, and the geomagnetic field interference is eliminated through a differential amplifier; the sensor output signal is sampled through a 24-bit ADC, the sampling rate is set to 10 kHz, the power frequency interference and high-frequency noise are filtered through a digital filter; the original signal and the background magnetic field signal are subtracted in real time through an FPGA, and the net magnetic leakage field data is sent to an upper computer for storage through a wireless transmission module; The original signal is derived under the pure direct current magnetization mode, and the background magnetic field is subtracted to obtain the reference magnetic leakage field; the original signal is derived under the alternating current and direct current composite magnetization mode, and the background magnetic field is subtracted to obtain the enhanced magnetic leakage field; the optimal parameter combination is determined by comparing the peak value changes of the reference and enhanced magnetic leakage fields; The optimal parameter combination is determined according to the leakage field peak value curve changing with the magnetization current, alternating current amplitude and frequency; A dynamic parameter optimization algorithm is introduced, the dynamic parameter optimization algorithm adopts Bayesian optimization, combines a gradient descent method to determine the optimal magnetization condition, iteratively calculates the second derivative of the magnetic leakage field signal amplitude and the current value, and positions the current value corresponding to the maximum gradient value; the direct current, alternating current frequency and scanning speed parameters are dynamically adjusted, and the objective function is the weighted sum of the maximum signal gain and the minimum detection time, and the weight coefficient is adjustable; The optimization objective function wherein , is a weight coefficient, and is the peak value of the magnetic flux leakage field before and after the composite magnetization, T is the detection time.

2. The method for increasing the magnetic flux leakage field of internal defects of ferromagnetic materials based on AC-DC hybrid magnetization according to claim 1, characterized in that: The composite excitation coil is wound with multiple strands of enameled copper wire, the coil type is a composite excitation coil assembly, the direct current value ranges from 0 to 30 A, the high-frequency alternating current frequency ranges from 500 to 1500 Hz, and the amplitude ranges from 1 to 6 A.

3. The method for increasing the magnetic flux leakage field of internal defects of ferromagnetic materials based on AC-DC hybrid magnetization according to claim 1, characterized in that: The background magnetic field deduction adopts a double Hall sensor dynamic calibration technology, automatically corrects the sensitivity difference of the two sensors through correlation analysis of the signals of the two sensors; an adaptive filtering algorithm is introduced in the signal conditioning stage, dynamically adjusts the filtering parameters according to the real-time noise level, and ensures that the effective signal retention rate is not less than 95%; the determination of the optimal magnetization current adopts a gradient descent method, iteratively calculates the second derivative of the magnetic leakage field signal amplitude and the current value, and positions the current value corresponding to the maximum gradient value.

4. The magnetization system for increasing the magnetic leakage field of the internal defects of the ferromagnetic material based on the AC-DC composite magnetization, according to any one of claims 1-3, characterized in that, The method comprises the following steps: The composite excitation coil assembly and signal conditioning unit; the coil assembly is connected with direct current and high frequency alternating current at the same time, realizing synchronous excitation; the signal conditioning unit performs background magnetic field deduction and peak value comparison analysis.

5. The magnetizing system of claim 4, wherein: The signal conditioning unit integrates a Hall sensor array and a data processing module; the sensor array is linearly arranged, with a lift-off value of 0.4-0.6 mm and a scanning speed of 5-10 mm / s; the data processing module performs original signal acquisition, background magnetic field deduction, peak extraction and curve fitting.

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