Defect detection system based on bias alternating current magnetization modulation TMR sensor

Abstract

The invention discloses a defect detection system based on a bias alternating current magnetization modulation TMR sensor, and the system is characterized in that through the cooperation of an alternating current and direct current magnetization module, a TMR sensor and a defect prediction module, the alternating current and direct current magnetization module is used for simulating an alternating current and direct current superimposed magnetic field test environment, and a reverse alternating current and direct current magnetic saturation magnetic field is formed; the TMR sensor obtains defect signal characteristics of a to-be-detected workpiece and sends the obtained defect signal characteristics of the to-be-detected workpiece to the defect prediction module, and the defect prediction module achieves full-scale detection of defects from 20 micrometers to millimeter by analyzing peak values (micron-scale narrow defects) and waveform widths (millimeter-scale defects) of alternating-current waveforms. The balance of high sensitivity and wide range of the same sensor is realized, and meanwhile, the dual requirements on precision and efficiency in actual detection are met. Meanwhile, through alternating current and direct current magnetic field cooperative modulation, the measuring range TMR sensor is expanded to 300 Gs, and the full range from weak magnetic leakage to strong magnetic leakage is covered.

Description

Technical Field

[0001] The present invention relates to the technical field of workpiece defect detection, and in particular to a defect detection system based on a biased AC magnetization modulation TMR sensor. Background Art

[0002] Magnetic flux leakage (MFL) is a non-destructive testing technology based on the magnetic properties of ferromagnetic materials. Its core principles mainly consist of three parts. The first is the magnetization process, in which an external magnetic field is applied to bring the workpiece under test (such as a pipe or steel plate) to a magnetic saturation state. The second is defect magnetic leakage. When there is a defect (crack, corrosion, etc.) in the workpiece, the magnetic permeability at the defect suddenly changes, causing magnetic lines of force to leak to the surface, forming a detectable leakage magnetic field. The last is signal acquisition, in which magnetic sensors (such as Hall elements, induction coils, and TMR sensors) are used to capture the leakage magnetic field signal. The defect location, size, and type are determined by analyzing the signal characteristics (amplitude, gradient, and spectrum).

[0003] The types of current traditional magnetic flux leakage detection methods can be divided into two types based on the magnetization method: DC magnetization and AC magnetization.

[0004] In DC magnetization, a constant magnetic field (static magnetic field) is applied to the ferromagnetic material under test to achieve magnetic saturation. When defects (such as cracks or corrosion pits) are present in the material, the magnetic permeability of the defective area decreases, causing magnetic field lines to leak from the defect to the surface, generating a detectable leakage magnetic field. The excitation source is typically a permanent magnet (such as NdFeB) or a DC electromagnet (which requires a high current supply). The required magnetic field strength must reach 80%-90% of the material's saturation magnetization. This allows for deeper inspection depths. Due to the stability of static magnetic field excitation, DC magnetization also offers a high signal-to-noise ratio.

[0005] In AC magnetization, an alternating magnetic field (sinusoidal, pulsed, etc.) is applied to the material to excite it. The difference in the rate of change of the magnetic field at the defect generates a dynamic magnetic flux leakage signal. The frequency of the alternating magnetic field directly affects the detection depth and sensitivity. The excitation source, an AC power supply, drives the electromagnetic coil, but impedance matching is required to avoid power loss. The dynamic magnetic field enhances the response to tiny defects, resulting in a highly sensitive method.

[0006] Since existing technologies usually use single DC or AC magnetization, it is impossible to simultaneously stimulate the leakage magnetic response of macroscopic (millimeter level) and microscopic (micrometer level) defects. Traditional leakage magnetic detection technology (such as optimized iron core or magnetic bridge circuit design) can only detect millimeter-level defects and is not sensitive enough to micron-level narrow defects (such as fatigue cracks). Although high-sensitivity sensors (such as TMR and GMR) can detect micron-level narrow defects, their range is limited. Millimeter-level defects cause sensor saturation, making it impossible to simultaneously cover micron- to millimeter-level defect detection. Summary of the Invention

[0007] The object of the present invention is to provide a defect detection system based on a biased AC magnetization modulation TMR sensor to solve the problem raised in the above background technology that the same sensor cannot perform cross-scale detection of micron-level narrow defects and millimeter-level defects on the workpiece.

[0008] To achieve the above object, the present invention provides the following technical solutions: A defect detection system based on a biased AC magnetization modulation TMR sensor, comprising an AC / DC superimposed magnetic field testing device, a data storage center, and a computer device; The AC / DC superposition magnetic field testing equipment includes: an AC / DC magnetization module, to which an AC current with a DC bias is applied to generate an AC / DC superposition magnetic field for simulating an AC / DC superposition magnetic field test environment and forming a reverse AC / DC magnetic saturation magnetic field; The TMR sensor is used in an opposite AC / DC saturation magnetic field to obtain defect signal characteristics of the workpiece to be measured and send the obtained defect signal characteristics of the workpiece to be measured to a computer device; the defect signal characteristics include defect signal characteristics of the workpiece to be measured from millimeter level to micrometer level; The data storage center is used to store the current defect signal characteristics and historical test data of the workpiece to be tested; The computer device comprises: A defect prediction module is used to use a preset defect prediction model to determine the defect location, size and type of the workpiece to be tested based on the defect signal characteristics of the workpiece to be tested; the defect prediction model is an artificial intelligence model trained based on historical defect data determined based on the historical test data. In one embodiment, the AC / DC magnetization module includes a magnetic core and an AC coil, and the magnetic core is inserted into the AC coil.

[0009] In one embodiment, the magnetic core has a height of 15 mm and an outer diameter of 8 mm; the AC coil has an outer diameter of 14 mm and an inner diameter of 8 mm.

[0010] In one embodiment, the calculation formula of the total AC / DC superposition magnetic field is: sen =B dc +B ac ∗sin(2πft))where f represents the frequency of the alternating current, B dc : DC magnetic field, B ac : AC magnetic field, B sen is the total magnetic field superimposed by AC and DC.

[0011] In one embodiment, when the AC / DC superposition initial total magnetic field satisfies B dc −B ac_peak ≥B satu. Among them B ac_peak is the peak value of the AC magnetic field, B satu is the saturation threshold of the TMR sensor, and the TMR sensor is always in the reverse AC and DC saturation magnetic field.

[0012] In one embodiment, the defect detection system further includes two bias magnets, and the two bias magnets are symmetrically arranged on both sides of the TMR sensor.

[0013] In one embodiment, the two bias magnets are permanent magnets.

[0014] In one embodiment, the TMR sensor is a TMR sensor array integrated with a flexible substrate.

[0015] In one embodiment, when the TMR sensor measures a micron-level narrow defect on a workpiece, the output value of the TMR sensor is linearly related to a quantitative indicator ΔB of the defect leakage magnetic field.

[0016] In one embodiment, when the TMR sensor detects millimeter-level defects on a workpiece, the quantitative index ΔB of the defect leakage magnetic field is calculated by the positive saturation time output by the TMR sensor; The calculation formula is: Δt=T / π[π / 2-arcsin(B satu -B dc -ΔB / B ac )], Δt: TMR sensor output positive saturation time, T=1 / f, f represents the frequency of AC, B dc : DC magnetic field, B ac : AC magnetic field, B satu is the TMR sensor saturation threshold.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The above-mentioned defect detection system based on the biased AC magnetization modulated TMR sensor is configured through the coordinated setting of the AC / DC magnetization module, the TMR sensor, and the defect prediction module. The AC / DC magnetization module is used to simulate the AC / DC superimposed magnetic field test environment to form a reverse AC / DC magnetic saturation magnetic field. The TMR sensor obtains the defect signal characteristics of the workpiece to be tested and sends the obtained defect signal characteristics of the workpiece to be tested to the defect prediction module. The defect prediction module realizes full-scale detection of defects from 20 microns to millimeters by analyzing the peak value (micron-level narrow defects) and waveform width (millimeter-level defects) of the AC waveform, achieving a balance between high sensitivity and wide range of the same sensor, while meeting the dual requirements of accuracy and efficiency in actual detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1Schematic diagram of the structure of a defect detection system based on a biased AC magnetization modulation TMR sensor in the present invention; FIG2 is a diagram showing the corresponding relationship between the TMR sensor of a defect detection system based on a biased AC magnetization modulation TMR sensor in the present invention and the external magnetic field when the TMR sensor is always in the reverse saturation region, the TMR sensor output peak value gradually increases, and the TMR sensor output pattern width increases; Figure 3 This is a result diagram of different defect sizes of a defect detection system based on a biased AC magnetization modulation TMR sensor in the present invention.

[0019] Reference numerals: AC / DC superimposed magnetic field testing equipment 1 , AC / DC magnetization module 11 , TMR sensor 12 , data storage center 2 , computer equipment 3 , defect prediction module 31 . DETAILED DESCRIPTION

[0020] To make the above-mentioned objects, features, and advantages of the present invention more readily apparent, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. The following description sets forth numerous specific details to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art may make similar modifications without departing from the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0021] It should be noted that when an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element. In contrast, when an element is said to be "directly" connected to another element, there are no intermediate elements.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention pertains. The terms used herein in the specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0023] like Figure 1 As shown: A defect detection system based on a biased AC magnetization modulation TMR sensor, comprising an AC / DC superimposed magnetic field testing device 1, a data storage center 2, and a computer device 3; The AC / DC superposition magnetic field testing device 1 comprises: An AC / DC magnetization module 11 is configured to apply an AC current with a DC bias to the AC / DC magnetization module 11 to generate an AC / DC superposition magnetic field for simulating an AC / DC superposition magnetic field test environment and forming a reverse AC / DC magnetic saturation magnetic field; The TMR sensor 12 is used in an opposite AC / DC saturation magnetic field to obtain defect signal characteristics of the workpiece to be measured and send the obtained defect signal characteristics of the workpiece to be measured to a computer device; the defect signal characteristics include defect signal characteristics of the workpiece to be measured from millimeter level to micrometer level; The data storage center 2 is used to store the current defect signal characteristics and historical test data of the workpiece to be tested; The computer device 3 includes: The defect prediction module 31 is used to use a preset defect prediction model to determine the defect position, size and type of the workpiece to be tested according to the defect signal characteristics of the workpiece to be tested; the defect prediction model is an artificial intelligence model trained based on historical defect data determined based on the historical test data. The AC / DC magnetization module 11 includes a magnetic core and an AC coil. The magnetic core is inserted into the AC coil. The magnetic core has a height of 15 mm and an outer diameter of 8 mm. The AC coil has an outer diameter of 14 mm and an inner diameter of 8 mm.

[0024] The core material is ferrite, with a height of 15 mm and an outer diameter of 8 mm. The AC coil has an outer diameter of 14 mm and an inner diameter of 8 mm. The core is inserted into the AC coil to enhance the alternating magnetic field generated by the AC coil.

[0025] TMR sensor 12, a TMR2905 sensor, utilizes a push-pull Wheatstone full-bridge design, provides a differential voltage output, and boasts excellent temperature stability. Its wide dynamic range is ±500 Gs. A 5V DC power supply is used to power the TMR sensor 12. The TMR sensor 12 is secured to the PCB with a 1.6mm thick backing plate to prevent direct contact between the sensor and the workpiece surface. A 0.2mm lift-off is provided to facilitate securement and ensure that it does not vibrate during testing, potentially affecting the signal.

[0026] The calculation formula of the total AC / DC superposition magnetic field is: sen =B dc +B ac ∗sin(2πft))where f represents the frequency of the alternating current, B dc : DC magnetic field, B ac : AC magnetic field, B sen is the total magnetic field superimposed by AC and DC.

[0027] By adjusting the DC magnetic field (B dc ) and AC magnetic field (B ac ) can control the AC / DC superimposed total magnetic field at the sensor.

[0028] When the initial total magnetic field of AC and DC superposition satisfies Bdc −B ac_peak ≥B satu . Among them B ac_peak is the peak value of the AC magnetic field, B satu is the saturation threshold of the TMR sensor, and the TMR sensor is always in the reverse AC and DC saturation magnetic field.

[0029] To verify whether increasing the AC magnetic field strength can expand the range of the TMR sensor 12 to accommodate environments with higher range requirements, the relationship between the output voltage of the TMR sensor 12 and the applied magnetic field was tested. The magnetizing current was increased from 0A to 30A, and the output value of the TMR sensor 12 was recorded. A Tesla meter was placed at the same location as the TMR sensor 12 to measure the magnetic field strength corresponding to the magnetizing current and compare it with the magnetic field strength output by the TMR sensor 12. The output of the TMR sensor 12 was divided into four phases: 1: the magnetic field generated by the magnetizing coil + the AC modulation field amplitude is weaker than the bias magnet field, remaining in the reverse saturation region; 2: the peak value of the TMR sensor 12 output gradually increases; 3: the width of the TMR sensor 12 output pattern increases; and 4: the valley value of the TMR sensor 12 gradually decreases. As shown in Figure 2, the output data of the TMR sensor 12 in each of the four phases was amplified, filtered, and differentially processed by the signal processing device. The subsequent signal was transmitted to the magnetic field determination module for data comparison to determine whether increasing the AC magnetic field strength could expand the range of the TMR sensor 12. The output values ​​of the TMR sensor 12 at different stages are compared with the measured values ​​of the Tesla meter to determine whether the measuring range of the TMR sensor 12 can be expanded by increasing the AC magnetic field strength.

[0030] FIG2( a ) shows the output value of the TMR sensor 12 when the TMR sensor 12 is in the reverse saturation region; FIG2( b ) shows the output value of the TMR sensor 12 when the output peak value gradually increases; and FIG2( c ) shows the output value of the TMR sensor 12 when the output pattern width increases.

[0031] When detecting micron-sized defects on a workpiece, the TMR sensor 12 temporarily escapes the reverse AC / DC saturation magnetic field, and the output amplitude changes linearly with the defect leakage magnetic field. The peak change of the AC signal at this time directly reflects the quantitative index ΔB of the defect leakage magnetic field. Therefore, when the TMR sensor 12 measures narrow micron-scale defects on a workpiece, the TMR sensor output value is linearly related to the defect leakage magnetic field quantification index ΔB. The defect prediction module 31 can calculate the defect leakage magnetic field quantification index ΔB based on the TMR sensor 12 output value according to preset data. For example, 1 mV → 0.2 Gs, that is, the defect leakage magnetic field quantification index ΔB = 0.2 Gs. The defect location, size, and type of the workpiece to be measured can then be inferred based on the defect leakage magnetic field quantification index ΔB.

[0032] In one embodiment, when the TMR sensor detects millimeter-level defects on a workpiece, the quantitative index ΔB of the defect leakage magnetic field is calculated by the positive saturation time output by the TMR sensor; The calculation formula is: Δt=T / π[π / 2-arcsin(B satu -B dc -ΔB / B ac )], Δt: TMR sensor output positive saturation time, T=1 / f, f represents the frequency of AC, B dc : DC magnetic field, B ac : AC magnetic field, B satu is the TMR sensor saturation threshold.

[0033] For millimeter-level defect detection of workpieces, that is, when the defect leakage magnetic field is large, the total magnetic field exceeds the positive saturation threshold, that is, the total magnetic field of AC and DC superposition meets B sen ≥B satu At this time, the TMR sensor 12 enters the positive saturation region, and the output amplitude no longer changes, but the positive saturation time (zero-crossing width) of the AC waveform increases with the increase of the leakage magnetic field. The leakage magnetic field strength of large defects can be indirectly quantified by measuring the change in waveform width. Therefore, the formula: Δt = T / π[π / 2-arcsin(B satu -B dc -ΔB / B ac )], and inversely deduce the value of ΔB.

[0034] When a defect exists in a workpiece, the quantitative index of the defect leakage magnetic field ΔB will form a magnetic pole pair (positive and negative peaks) at the edge of the defect. Its spatial distribution is strongly correlated with the defect geometry: Position: The extreme value of the leakage magnetic field corresponds to the edge of the defect; a pair of positive and negative magnetic field peaks will be formed on both sides of the defect, and the center point is the defect position; Depth: Peak intensity ΔB peak Increases with the depth of the defect; Depth d and ΔB peak Approximately satisfies the logarithmic relationship (due to magnetic field attenuation); Length: The full width at half maximum (FWHM) of the magnetic field distribution is proportional to the defect size. The workpiece defect length L is proportional to the full width at half maximum of the magnetic field distribution, L = k * FWHM, where K is the calibration factor. For cracks: k ≈ 1.2–1.5 (due to the magnetic field diffusion effect); for circular holes: k ≈ 0.8–1.0.

[0035] ΔB points in the direction of the defect opening (e.g., the magnetic field gradient of a surface crack is perpendicular to the crack direction). When the workpiece is defect-free, ΔB = 0.

[0036] like Figure 3As shown in the figure, 5mm and 10mm thick samples were prepared with macroscopic internal and external defects. The defect sizes were 0.25mm, 0.5mm, 0.75mm, 1mm, 1.25mm, 1.5mm, and 2.0mm, respectively. The magnetization current was adjusted to 4.3A, and the detection results for different defect sizes were analyzed to determine the test accuracy of the defect detection system based on the biased AC magnetization modulation TMR sensor.

[0037] In this way, a defect detection system based on a biased AC magnetization modulated TMR sensor is configured by coordinating an AC / DC magnetization module 11, a TMR sensor 12, and a defect prediction module 31. The AC / DC magnetization module 11 is used to simulate an AC / DC superimposed magnetic field test environment to form a reverse AC / DC magnetic saturation magnetic field. The TMR sensor 12 obtains the defect signal characteristics of the workpiece to be tested and sends the obtained defect signal characteristics of the workpiece to be tested to the defect prediction module 31. The defect prediction module 31 realizes full-scale detection of defects from 20 microns to millimeters by analyzing the peak value (micron-level narrow defects) and waveform width (millimeter-level defects) of the AC waveform, achieving a balance between high sensitivity and wide range of the same sensor, while meeting the dual requirements of accuracy and efficiency in actual detection.

[0038] Dynamic range expansion capability: Existing technologies cannot adapt to large defect leakage magnetic fields (e.g., >10 Gs) due to the narrow linear range of high-sensitivity sensors (e.g., the original range of the TMR2901 is ±10 Gs). This application uses AC and DC magnetic field co-modulation to expand the range of the TMR sensor 12 to 300 Gs (30 times the original range), covering the full range from weak to strong leakage magnetic fields.

[0039] DC magnetic field B dc : Set the initial operating point of the TMR sensor 12 in the reverse AC / DC saturation magnetic field to suppress baseline drift and set the initial saturation point, for example, 150 Gs. ac : AC magnetic field, superimposed high-frequency magnetic field, dynamic regulation of sensor working range, control dynamic range 20Gs–50Gs (adjustable); saturation zone tolerance B 容 = 100 Gs (determined by calibration), saturation tolerance, additional magnetic field range that the TMR sensor 12 can still resolve when deeply saturated.

[0040] Upper limit of the measuring range of the TMR sensor 12 = B dc +B ac +B 容 =150+50+100=300Gs.

[0041] In one embodiment, the defect detection system further includes two bias magnets, which are symmetrically arranged on both sides of the TMR sensor; and the two bias magnets are permanent magnets.

[0042] Thus, existing high-sensitivity sensors are susceptible to background magnetic field interference and need to operate in a zero background magnetic field, limiting their applicability in industrial scenarios. This application utilizes DC bias magnetic field cancellation to adjust the distance between the two bias magnets to return the background magnetic field in the sensor area to zero, preserving the defect leakage magnetic field signal.

[0043] In one embodiment, the TMR sensor 12 is a TMR sensor array integrated with a flexible substrate.

[0044] While the TMR sensor 12 is highly sensitive and can detect objects across multiple scales, in some scenarios, a flexible sensor array can be used instead of a rigid probe. A TMR sensor array probe integrated on a flexible substrate can better adapt to curved or irregularly shaped components (such as turbine blades and curved pipes), improving detection coverage and reducing the risk of missed detections.

[0045] The above is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solutions and inventive concepts of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A defect detection system based on a biased AC magnetization modulation TMR sensor, characterized by: Including AC and DC superposition magnetic field testing equipment, data storage center and computer equipment; The AC / DC superposition magnetic field testing equipment includes: an AC / DC magnetization module, to which an AC current with a DC bias is applied to generate an AC / DC superposition magnetic field for simulating an AC / DC superposition magnetic field test environment and forming a reverse AC / DC magnetic saturation magnetic field; The TMR sensor is used in an opposite AC / DC saturation magnetic field to obtain defect signal characteristics of the workpiece to be measured and send the obtained defect signal characteristics of the workpiece to be measured to a computer device; the defect signal characteristics include defect signal characteristics of the workpiece to be measured from millimeter level to micrometer level; The data storage center is used to store the current defect signal characteristics and historical test data of the workpiece to be tested; The computer device comprises: A defect prediction module is used to use a preset defect prediction model to determine the defect location, size and type of the workpiece to be tested based on the defect signal characteristics of the workpiece to be tested; the defect prediction model is an artificial intelligence model trained based on historical defect data determined based on the historical test data.

2. A defect detection system based on a biased AC magnetization modulation TMR sensor according to claim 1, characterized in that: The AC / DC magnetization module includes a magnetic core and an AC coil, and the magnetic core is inserted into the AC coil.

3. A defect detection system based on a biased AC magnetization modulation TMR sensor according to claim 2, characterized in that: The magnetic core has a height of 15 mm and an outer diameter of 8 mm; the AC coil has an outer diameter of 14 mm and an inner diameter of 8 mm.

4. A defect detection system based on a biased AC magnetization modulation TMR sensor according to claim 1, characterized in that: The calculation formula of the total AC / DC superposition magnetic field is: sen =B dc +B ac ∗sin(2πft))where f represents the frequency of the alternating current, B dc : DC magnetic field, B ac : AC magnetic field, B sen is the total magnetic field superimposed by AC and DC.

5. A defect detection system based on a biased AC magnetization modulation TMR sensor according to claim 4, characterized in that: When the initial total magnetic field of AC and DC superposition satisfies B dc −B ac_peak ≥B satu . Among them B ac_peak is the peak value of the AC magnetic field, B satu is the saturation threshold of the TMR sensor, and the TMR sensor is always in the reverse AC and DC saturation magnetic field.

6. The defect detection system based on the biased AC magnetization modulation TMR sensor according to claim 1, characterized in that: The defect detection system further includes two bias magnets, which are symmetrically arranged on both sides of the TMR sensor.

7. A defect detection system based on a biased AC magnetization modulation TMR sensor according to claim 6, characterized in that: The two bias magnets are permanent magnets.

8. The defect detection system based on the biased AC magnetization modulation TMR sensor according to claim 1, characterized in that: The TMR sensor is a TMR sensor array integrated with a flexible substrate.

9. The defect detection system based on the biased AC magnetization modulation TMR sensor according to claim 1, characterized in that: When the TMR sensor measures a micron-level narrow defect on a workpiece, the output value of the TMR sensor is linearly related to the quantitative index ΔB of the defect leakage magnetic field.

10. The defect detection system based on the biased AC magnetization modulation TMR sensor according to claim 1, characterized in that: When the TMR sensor detects millimeter-level defects on a workpiece, the quantitative index ΔB of the defect leakage magnetic field is calculated by the positive saturation time output by the TMR sensor; The calculation formula is: Δt=T / π[π / 2-arcsin(B satu -B dc -ΔB / B ac )], Δt: TMR sensor output positive saturation time, T=1 / f, f represents the frequency of AC, B dc : DC magnetic field, B ac : AC magnetic field, B satu is the TMR sensor saturation threshold.

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