A magnetic sensor-based multi-layer metal structure gap detection system and method

Abstract

The application discloses a kind of multi-layer metal structure gap detection system and method based on magnetic sensing, including the multi-layer metal of gap to be detected, sensor detection probe, permanent magnet, mounting seat, data acquisition card, computer PC end, signal transmission line, USB data transmission line;Multi-layer metal includes outer metal, inner metal, outer metal, inner metal between being provided with elastoplasticity connecting layer, elastoplasticity connecting layer is located in the upper end surface of inner metal;Sensor detection probe, permanent magnet are respectively installed on the outer wall of outer metal, the inner wall of inner metal;Sensor detection probe is electrically connected with data acquisition card by signal transmission line, and data acquisition card is electrically connected with computer PC end by USB data transmission line.The application has the advantages of high detection precision, equipment is suitable for the detection in small gap, high efficiency, high degree of automation, easy operation, etc., provides a kind of multi-layer metal structure gap high-precision detection system, and application prospect is wider.

Description

Technical Field

[0001] This invention relates to a system and method for detecting gaps in multilayer metal structures based on magnetic sensing, belonging to the field of magnetic positioning nondestructive testing. Background Technology

[0002] Multilayer metal structures possess high specific strength and fatigue resistance, making them widely used in many important fields such as aerospace and nuclear industry. Multilayer metal structures typically consist of two or more metal shells and locally filled with polymers such as rubber. The outer and inner metal shells are usually made of materials with low coefficients of thermal expansion and corrosion resistance, such as lead. The middle metal layer is made of aluminum, which has a high coefficient of thermal expansion and low strength. The polymers, such as rubber, fill the sub-millimeter gaps between the metal shells, providing connection and support. During manufacturing and assembly, large gaps between layers can reduce performance; small gaps can create safety hazards. During long-term service, the gaps between the layers of multilayer metal structures continuously change due to the influence of complex environmental factors such as vibration and extreme temperatures. Furthermore, the mechanical properties of the polymers used as connecting and supporting materials degrade over time under long-term radiation, vibration, and thermal stress, causing changes in the gaps between the layers and reducing the stability, reliability, and safety of the multilayer metal structure. Therefore, monitoring the interlayer gaps of multilayer metal structures throughout their entire lifecycle, from manufacturing and assembly to decommissioning, and controlling them within a reasonable range, is of great significance for improving the performance of multilayer metal structure materials and ensuring the safe operation and maintenance of equipment.

[0003] Methods such as ultrasonic testing, laser optical measurement, and X-ray measurement have been used to detect gap distances, but all have limitations when applied to the interlayer gaps of multi-layer metal structures. Ultrasonic testing has a wide applicability and allows for non-contact measurement, but its error fluctuates significantly when measuring gaps between two-sided tubes, failing to meet the requirements for accurate gap measurement in multi-layer metal structures. Laser optical measurement requires fiber optics and has high operating conditions, making it unsuitable for gap measurement in the complex conditions of multi-layer metal structures. X-ray measurement requires high relative positional accuracy and is expensive, limiting its application. Although many gap measurement methods exist, most suffer from limitations in meeting the practical requirements and accuracy for measuring interlayer gaps in multi-layer metal structures, such as the inability to achieve non-contact measurement, the inability to place measuring equipment inside the gap, and insufficient measurement accuracy. However, high-precision detection of gaps in multi-layer metal structures has significant breakthrough potential for aerospace, nuclear industry, and other fields.

[0004] In summary, there is a need to invent a gap detection system and method for multi-layer metal structures to achieve high-precision real-time monitoring of gaps in multi-layer metal structures, providing reliable assurance for the installation, use, and performance improvement of multi-layer metal structures. Summary of the Invention

[0005] In order to overcome the shortcomings of the existing technology, the present invention aims to provide a system and method for detecting gaps in multilayer metal structures based on magnetic sensing.

[0006] The technical solution provided by this invention to solve the above-mentioned technical problems is: a multi-layer metal structure gap detection system based on magnetic sensing, including a multi-layer metal gap to be detected, a sensor detection probe, a permanent magnet, a mounting base, a data acquisition card, a computer PC, a signal transmission line, and a USB data transmission line;

[0007] The multilayer metal includes an outer metal layer and an inner metal layer, with an elastic-plastic connecting layer between the outer and inner metal layers, the elastic-plastic connecting layer being located on the upper end face of the inner metal layer; the sensor detection probe and the permanent magnet are respectively mounted on the outer wall of the outer metal layer and the inner wall of the inner metal layer, and the sensor detection probe and the permanent magnet are coaxial; the inner metal layer is mounted on a mounting base;

[0008] The sensor detection probe is electrically connected to the data acquisition card via a signal transmission line, and the data acquisition card is electrically connected to the computer PC via a USB data transmission line.

[0009] A further technical solution is that the number of sensor detection probes and permanent magnets are both four, and they are evenly distributed around the outer metal layer and the inner metal layer.

[0010] A further technical solution is that the permanent magnet is a cylindrical permanent magnet, and its material is neodymium iron boron.

[0011] A further technical solution is that the mounting base is a non-ferromagnetic base.

[0012] A further technical solution is that the elasto-plastic connecting layer is a polymer layer.

[0013] A further technical solution is that the data acquisition card is a USB-6361 data acquisition card, with a maximum single-channel sampling rate of 2.00Ms / s and a maximum multi-channel sampling rate of 1.00Ms / s.

[0014] A method for detecting gaps in multilayer metal structures based on magnetic sensing, the method specifically includes the following steps:

[0015] Step S1: Distribute four permanent magnets evenly around the inner wall of the inner metal layer to be tested;

[0016] Step S2: Assemble the outer metal layer to be tested with the inner metal layer. After assembly, fix the inner metal layer to the mounting base.

[0017] Step S3: Perform in-situ calibration of the sensor detection probe and the permanent magnet to make the magnetic field output in the X and Y directions measured by the sensor detection probe zero;

[0018] Step S4: In the MATLAB software on the PC, the equivalent current method is used to establish a three-dimensional magnetic field distribution mathematical model of the permanent magnet, and then a nonlinear optimization algorithm is used to construct an error function containing target information.

[0019] Step S5: A loading force is applied to the upper surface of the outer metal layer. The interlayer gap between the outer and inner metal layers changes. The sensor detects the current magnetic field strength and transmits the data as voltage in the form of a voltage signal to the data acquisition board after filtering and amplification. The data acquisition board performs analog-to-digital conversion on the amplified data and transmits it to the MATLAB software on the PC. The MATLAB software substitutes the received voltage data value into the mathematical model of the three-dimensional magnetic field distribution of the permanent magnet, and then obtains the minimum value of the error function through decoupling algorithm iteration. This minimum value is the displacement result of the current gap. The current output value is denoted as u1.

[0020] Step S6: Repeat step S5 four times to obtain output values ​​u2-u5 respectively. Finally, take the average value u0 of the output values ​​u1-u5 as the final measurement result and output it.

[0021] A further technical solution is that the centering operation in step S2 is specifically as follows:

[0022] First, fix the sensor detection probe on the precision fine-tuning platform, and then install it in the predetermined position to achieve the initial alignment of the sensor detection probe and the permanent magnet;

[0023] Then turn on the circuit control power supply to make each circuit module work normally. Check the output voltage of the X and Y axes on the PC software. Rotate the X and Y direction adjustment knobs of the precision fine-tuning platform to make the output voltage zero. Record the current sensor position coordinates as the reference zero point and input this coordinate value into the MATLAB software as the initial coordinate value of the mathematical model of the three-dimensional magnetic field distribution of the permanent magnet.

[0024] The present invention has the following advantages: it has high detection accuracy, the equipment is suitable for detection in small gaps, high efficiency, high degree of automation, and simple operation. It provides a system for high-precision detection of gaps in multi-layer metal structures and has broad application prospects. Attached Figure Description

[0025] Figure 1 This is a schematic diagram illustrating the gap detection principle of a triaxial magnetoresistive sensor.

[0026] Figure 2 This is a schematic diagram of a multilayer metal structure gap detection system based on magnetic sensing.

[0027] Figure 3 This is a schematic diagram showing the installation positions of the sensor probe and permanent magnet in a multi-layer metal structure gap detection system.

[0028] Figure 4 This is a flowchart of the detection module of a multi-layer metal structure gap detection system;

[0029] Figure 5 This is a diagram of the Matlab mathematical model;

[0030] Figure 6 This is a diagram of Biot-Savart's law.

[0031] As shown in the figure: 1-Sensor detection probe, 2-Permanent magnet, 3-Outer metal layer, 4-Inner metal layer, 5-Elastic-plastic connecting material, 6-Signal transmission line, 7-USB data transmission line, 8-Data acquisition card, 9-PC terminal, 10-Mounting base, 11-External force applied, S01-Triaxial magnetoresistive sensor, S02-Magnetic lines of force. Implementation

[0032] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] like Figure 2 and Figure 3 As shown, the present invention provides a multi-layer metal structure gap detection system based on magnetic sensing, comprising a multi-layer metal gap to be detected, four sensor detection probes 1, four permanent magnets 2, a mounting base 10, a data acquisition card 8, a computer PC terminal 9, a signal transmission line 6, and a USB data transmission line 7.

[0034] The multilayer metal includes an outer metal layer 3 and an inner metal layer 4. An elastic-plastic connecting layer 5 (made of a high molecular polymer such as rubber) is provided between the outer metal layer 3 and the inner metal layer 4. The elastic-plastic connecting layer 5 is located on the upper end face of the inner metal layer 4. The sensor detection probe 1 and the permanent magnet 2 are respectively installed on the outer wall of the outer metal layer 3 and the inner wall of the inner metal layer 4, and the sensor detection probe 1 and the permanent magnet 2 are coaxial. The inner metal layer 4 is mounted on the mounting base 10.

[0035] The sensor detection probe 1 is electrically connected to the data acquisition card 8 via the signal transmission line 6, and the data acquisition card 8 is electrically connected to the computer PC 9 via the USB data transmission line 7.

[0036] In this embodiment, the sensor detection probe 1 contains a triaxial magnetoresistive sensor (using Honeywell's HMC1043 triaxial magnetoresistive sensor), a power supply circuit, a reset circuit, an operational amplifier circuit, and a bias adjustment circuit.

[0037] The triaxial magnetoresistive sensor is used to detect the three-dimensional magnetic field change caused by the displacement of the magnetic source (the triaxial magnetoresistive sensor outputs a mV-level output voltage corresponding to the magnetic field change caused by the displacement change in three directions).

[0038] The power supply circuit ensures a constant supply current while also requiring the sensor to operate within the linear range.

[0039] Bias adjustment circuit: The bias current input pins on the HMC1043 are OFF+XY, OFF-XY and OFF+Z, OFF-Z. Connect a sliding rheostat to the XY and Z-axis bias input ports. Adjust the resistance of the rheostat to adjust the bias current. Simultaneously connect a zero-resistance resistor to the front of the rheostat. When it is determined that the required background magnetic field no longer needs adjustment and the sensitivity is appropriate, the rheostat can be replaced with a fixed resistor to ensure that the background magnetic field remains unchanged.

[0040] Set / Reset Circuit: The set / reset circuit design uses a CMOS switch IRF7105. The IRF7105 is turned on and off by a clock signal to generate set / reset pulses. Set / reset signals need to be applied to two set / reset pins in different directions during the set / reset process.

[0041] Since the internal structure of the set / reset current band is the same, and the magnetic field information in different directions of the same external magnetic field is measured in use, the set / reset pins in the two directions can be connected in series. A set / reset circuit generates a set / reset current pulse, which is input from the S / R+(A) pin, output from the S / R-(A) pin, input to S / R+(B) again, and finally output from S / R-(B). One set / reset circuit pulse signal completes a set / reset operation on the magnetic field signals in both directions at the same time.

[0042] The operational amplifier circuit module needs to amplify the output voltage (mV level) of the triaxial magnetoresistive sensor to the voltage range (V level) of the analog input of the data acquisition card. It uses the OPA4197IDR operational amplifier chip to amplify the original output voltage signal, with a specific amplification factor of 200 times. At the same time, a low-pass filter circuit is added to the pre-amplifier circuit of the operational amplifier circuit to remove noise interference from the original output signal.

[0043] In this embodiment, the permanent magnet is an axially magnetized cylindrical permanent magnet made of neodymium iron boron, grade N35, with a diameter of 5 mm and a thickness of 0.4 mm.

[0044] In this embodiment, the mounting base 10 is made of a non-ferromagnetic material. The outer metal layer is typically made of lead (but other non-ferromagnetic metals are also acceptable), with a thickness of 5 mm. The inner metal layer is typically made of aluminum (but other non-ferromagnetic metals are also acceptable), and its thickness is not limited. The gap between the inner and outer metal layers is 1 mm. (The gap distance is adjustable, but generally in the millimeter range; the required gap change accuracy is 0.01 mm, or 10 μm.)

[0045] The cross-sectional shape of the inner and outer metal structures is not limited to square; it can also be a combination of a ring and a square, a sphere and a shell, etc.

[0046] In this embodiment, the software system of the computer PC 9 is NI LabVIEW 2021 SP1 (32-bit) software. The computer PC includes a data processing unit (Matlab 2019a software) and a visualization display unit. The data processing unit processes the voltage data transmitted from the acquisition card to the computer through a decoupling algorithm (in Matlab 2019a software) to restore it into displacement data. Then, the visualization display unit (NI LabVIEW 2021 software) displays the real-time displacement data and historical displacement data on the developed user interface so that the user can observe the changes in the gaps of the multi-layer metal structure in real time.

[0047] In this embodiment, data acquisition card 8 is a USB-6361 data acquisition card with a maximum single-channel sampling rate of 2.00 Ms / s and a maximum multi-channel sampling rate of 1.00 Ms / s. The analog input resolution is 16 bits, and the analog input absolute accuracy is 1660 uV. A high-precision data acquisition card is used during the detection process to ensure the accuracy of the measurement data conversion. The data acquisition card performs analog-to-digital conversion on the voltage data output from the sensor probe before inputting it to the PC.

[0048] The principle of this embodiment is as follows: the permanent magnet 2 is fixed on the inner metal layer 4 and generates a stable static magnetic field. The sensor detection probe 1 can detect the three-dimensional information of the static magnetic field generated by the permanent magnet 2. When the relative position of the permanent magnet 2 and the sensor detection probe 1 changes, the three-dimensional magnetic field information collected by the sensor detection probe 1 will change. The relative coordinates of the permanent magnet can be calculated by the different three-dimensional magnetic field information, and then the change of the gap of the multi-layer metal structure can be deduced.

[0049] When the upper surface of the outer metal layer 3 is subjected to a loading force, the uneven deformation of the elastic-plastic connecting layer 5 causes a change in the gap between the outer metal layer 3 and the inner metal layer 4. The permanent magnet 2 fixed on the inner metal layer 4 moves synchronously with the inner metal layer 4. As a magnetic source, the permanent magnet 2 generates a fixed distributed magnetic field. When the relative position of the permanent magnet 2 and the sensor detection probe 1 changes, i.e., the size of the gap in the multi-layer metal structure changes, the resulting magnetic field change will be detected by the sensor detection probe 1 and reflected as voltage change data. The voltage data is then input to the data acquisition card 8 through the signal transmission line 6. After analog-to-digital conversion, it is imported into the computer PC 9. The PC 9 performs algorithmic processing on the voltage data to restore the voltage data to the interlayer gap displacement change data. The visualization platform displays the real-time distance change of the interlayer gap of the multi-layer metal structure, realizing non-contact measurement of the gap of the multi-layer metal structure, and helping technicians to better perform assembly and debugging work.

[0050] Before formal testing, the sensor detection probe 1 and permanent magnet 2 are calibrated in place to align the axis of the triaxial magnetoresistive sensor with the axis of the permanent magnet 2, ensuring that the magnetic field outputs measured by the sensor in the X and Y directions are zero. Then, the triaxial magnetoresistive sensor is reset to subtract the Hall voltage generated by the Earth's magnetic field, ensuring that the sensor operates at the same zero point. Each sensor detection probe 1 corresponds to one permanent magnet 2.

[0051] This embodiment utilizes a detection method that arranges permanent magnet arrays on the workpiece to be measured to comprehensively obtain the three-dimensional displacement information of the gap to be measured. A complex three-dimensional magnetic field distribution mathematical model is established, and a decoupling algorithm is used to precisely calculate the three-dimensional magnetic field information. For gaps to be measured at the millimeter level, the displacement change measurement at the micrometer level is achieved. Hardware development of a triaxial magnetoresistive sensor is carried out to achieve high-precision monitoring of magnetic field information. A complete measurement system for gap detection in multi-layer metal structures is established.

[0052] A method for detecting gaps in multilayer metal structures based on magnetic sensing, specifically including the following steps:

[0053] Step S1: Distribute four permanent magnets 2 evenly around the inner wall of the inner metal layer 4 to be tested;

[0054] Step S2: Assemble the outer metal layer 3 to be tested with the inner metal layer 4. After assembly, fix the inner metal layer 4 on the mounting base 10.

[0055] Step S3: Perform in-situ calibration of sensor detection probe 1 and permanent magnet 2 (i.e., center sensor detection probe 1 and permanent magnet 2 on their axes, and achieve a centering accuracy of 0.01mm after the centering operation is completed), so that the magnetic field output of sensor detection probe 1 in the X and Y directions is zero. Then, reset the triaxial magnetoresistive sensor to subtract the Hall voltage generated by the Earth's magnetic field, so that the sensor works at the same zero point.

[0056] The specific centering process is as follows:

[0057] First, fix the sensor detection probe 1 on the precision fine-tuning platform, and then install it in the predetermined position to achieve the initial alignment of the sensor detection probe 1 and the permanent magnet 2. At this time, the alignment error is about 0.1-0.2mm.

[0058] Then turn on the circuit control power supply to enable each circuit module to work normally. Check the output voltage of the X-axis and Y-axis (XY coordinates on the radial plane perpendicular to the axis) on the PC software. Rotate the X and Y direction adjustment knobs of the precision fine-tuning platform to make the output voltage zero. At this time, the centering error is less than 0.01mm. Record the current sensor position coordinates as the reference zero point and input this coordinate value into the MATLAB software as the initial coordinate value of the mathematical model of the three-dimensional magnetic field distribution of the permanent magnet.

[0059] The principle of centering: According to Biot-Savart's law, such as... Figure 6 As shown, there are

[0060]

[0061] Where B is the magnetic flux density, k is the proportionality constant, Idl is a small current element, r is the distance from the current element to the reference point, and θ is the angle between the current element and the distance r. According to Biot-Savart's law, the magnetic flux density is inversely proportional to the square of the distance; therefore, the distance between the magnetic source and the reference point can be indirectly obtained by measuring the magnitude of the magnetic flux density.

[0062] Step S4: In the MATLAB software on the PC, the equivalent current method is used to establish a three-dimensional magnetic field distribution mathematical model of the permanent magnet, and then a nonlinear optimization algorithm is used to construct an error function containing target information.

[0063] This process involves establishing an accurate mathematical model of the three-dimensional magnetic field of the permanent magnet used, in order to obtain numerical data of the magnetic field at any spatial location of the permanent magnet. A three-dimensional magnetic field distribution mathematical model of the permanent magnet is established in MATLAB to obtain three-dimensional magnetic field data, and a database of magnetic field data for permanent magnets of different specifications is created. Voltage data transmitted from the data acquisition card is processed in MATLAB using an algorithm that calculates the relationship between voltage, magnetic field, and displacement, ultimately converting the voltage data into displacement data.

[0064] The voltage-magnetic field relationship corresponds to the change in the magnitude of the magnetic field, which is the sensor's sensitivity, 1 mV / V / gauss; the magnetic field-displacement relationship satisfies Biot-Savart's law, i.e.

[0065]

[0066] By leveraging the correlation between voltage, magnetic field, and displacement, high-precision detection of gap displacement in multi-layered metal structures at the micrometer level can be achieved. The higher the accuracy of the magnetic field model, the higher the accuracy of displacement calculations using it.

[0067] Then, an optimization algorithm based on complementary filtering and gradient descent is used to solve the problem. Specifically, the model is trained, the initial external magnetic field during measurement is subtracted, and the measurement is repeated multiple times to obtain the average value as the output result.

[0068] Since the correspondence between magnetic field information and sensor output, as well as the correspondence between output voltage signal and displacement, are nonlinear, a nonlinear optimization algorithm is adopted to construct an error function (containing target information). The solution to obtain the minimum value through decoupling algorithm iteration is the final output value of the gap displacement.

[0069] Step S5: Apply an external force 11 to the upper surface of the outer metal layer. The interlayer gap between the outer and inner metal layers changes. The sensor detects the current magnetic field strength and transmits the data as voltage in the form of a voltage signal to the data acquisition board after filtering and amplification. The data acquisition board performs analog-to-digital conversion on the amplified data and transmits it to the MATLAB software on the PC. The MATLAB software substitutes the received voltage data value into the mathematical model of the three-dimensional magnetic field distribution of the permanent magnet, and then obtains the minimum value of the error function through decoupling algorithm iteration. This minimum value is the displacement result of the current gap. The current output value is denoted as u1.

[0070] Step S6: Repeat step S5 four times to obtain output values ​​u2-u5 respectively. Finally, take the average value u0 of the output values ​​u1-u5 as the final measurement result and output it.

[0071] Step S7: On the LabVIEW visualization platform, write a display program to call the final value u0 (i.e., the current relative position coordinates between the sensor and the magnetic source) obtained from the MATLAB solution model and display it; compare it with the initial coordinates to obtain the current relative displacement change value and display it. Store the historical data and print it on the front panel.

[0072] Step S8: Wait for the waiting time (1s) completed by the hardware timer, repeat the above measurement process, and perform the next measurement.

[0073] Step S9: Save the measurement data, measurement complete, turn off the power.

[0074] The innovation of this method lies in:

[0075] 1. Non-contact measurement, long service life, high stability, and high reliability;

[0076] 2. The structural forms can be diversified, resulting in a wide measurement range and convenient installation and maintenance;

[0077] 3. The sensor and permanent magnet have strong adaptability to gaps, making it suitable for a wide range of applications;

[0078] 4. It has strong anti-interference ability and is not affected by various external environmental factors;

[0079] 5. It can accurately detect displacement changes in the interlayer gaps of multi-layer metal structures.

[0080] The above description is not intended to limit the present invention in any way. Although the present invention has been disclosed through the above embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for detecting gaps in multilayer metal structures based on magnetic sensing, characterized in that, The method employs a multi-layer metal structure gap detection system based on magnetic sensing for detection. The system includes a multi-layer metal structure to be detected, a sensor detection probe, a permanent magnet, a mounting base, a data acquisition card, a PC terminal, a signal transmission line, and a USB data transmission line. The multilayer metal includes an outer metal layer and an inner metal layer, with an elastic-plastic connecting layer between the outer and inner metal layers, the elastic-plastic connecting layer being located on the upper end face of the inner metal layer; the sensor detection probe and the permanent magnet are respectively mounted on the outer wall of the outer metal layer and the inner wall of the inner metal layer, and the sensor detection probe and the permanent magnet are coaxial; the inner metal layer is mounted on a mounting base; The sensor detection probe is electrically connected to the data acquisition card via a signal transmission line, and the data acquisition card is electrically connected to the PC via a USB data transmission line. The method specifically includes the following steps: Step S1: Distribute four permanent magnets evenly around the inner wall of the inner metal layer to be tested; Step S2: Assemble the outer metal layer to be tested with the inner metal layer. After assembly, fix the inner metal layer to the mounting base. Step S3: Perform in-situ calibration of the sensor detection probe and the permanent magnet to make the magnetic field output in the X and Y directions measured by the sensor detection probe zero; Step S4: In the MATLAB software on the PC, the equivalent current method is used to establish a three-dimensional magnetic field distribution mathematical model of the permanent magnet, and then a nonlinear optimization algorithm is used to construct an error function containing target information. Step S5: A loading force is applied to the upper surface of the outer metal layer. The interlayer gap between the outer and inner metal layers changes. The sensor detects the current magnetic field strength and transmits the data as voltage to the data acquisition card after filtering and amplification. The data acquisition card performs analog-to-digital conversion on the amplified data and transmits it to the MATLAB software on the PC. The MATLAB software substitutes the received voltage data value into the mathematical model of the three-dimensional magnetic field distribution of the permanent magnet, and then obtains the minimum value of the error function through decoupling algorithm iteration. This minimum value is the displacement result of the current gap. The current output value is denoted as u1. Step S6: Repeat step S5 four times to obtain output values ​​u2-u5 respectively. Finally, take the average value u0 of the output values ​​u1-u5 as the final measurement result and output it.

2. The method for detecting gaps in multilayer metal structures based on magnetic sensing according to claim 1, characterized in that, The sensor detection probe and the permanent magnet are both four in number and are evenly distributed around the outer and inner metal layers.

3. The method for detecting gaps in multilayer metal structures based on magnetic sensing according to claim 1, characterized in that, The permanent magnet is a cylindrical permanent magnet made of neodymium iron boron.

4. The method for detecting gaps in multilayer metal structures based on magnetic sensing according to claim 1, characterized in that, The mounting base is a non-ferromagnetic base.

5. The method for detecting gaps in multilayer metal structures based on magnetic sensing according to claim 1, characterized in that, The elasto-plastic bonding layer is a polymer layer.

6. The method for detecting gaps in multilayer metal structures based on magnetic sensing according to claim 1, characterized in that, The data acquisition card is a USB-6361 data acquisition card, with a maximum single-channel sampling rate of 2.00Ms / s and a maximum multi-channel sampling rate of 1.00Ms / s.

7. The method for detecting gaps in multilayer metal structures based on magnetic sensing according to claim 1, characterized in that, The specific centering operation in step S2 is as follows: First, fix the sensor detection probe on the precision fine-tuning platform, and then install it in the predetermined position to achieve the initial alignment of the sensor detection probe and the permanent magnet; Then turn on the circuit control power supply to enable each circuit module to work normally. Check the output voltage in the X and Y directions on the PC software. Rotate the X and Y adjustment knobs of the precision fine-tuning platform to make the output voltage zero. Record the current sensor position coordinates as the reference zero point and input this coordinate value into the MATLAB software as the initial coordinate value of the mathematical model of the three-dimensional magnetic field distribution of the permanent magnet.

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