A reconfigurable magnetic marker tracking system and method for structural deformation monitoring

Abstract

The application discloses a reconfigurable magnetic marker tracking system and method for structural deformation monitoring, and relates to the technical field of engineering structural deformation monitoring. The system comprises a magnetic marker module, a magnetic sensor array module and a magnetic particle marker coordinate inversion module. The magnetic marker module is used for providing displacement information of a marker point of a structure to be monitored during deformation. The magnetic sensor array module is used for recording real-time magnetic field signals in a target region during monitoring through a magnetic sensor array. The magnetic particle marker coordinate inversion module is used for analyzing the collected magnetic field signals based on the spatial coordinates of the magnetic sensor array by using a no-load calibration magnetic particle marker coordinate inversion method, and calculating three-dimensional coordinate changes of magnetic particle markers of the structure to be monitored during monitoring. The application adopts a bar modular subrack architecture to design a reconfigurable magnetic sensor array, and combines the no-load calibration magnetic particle marker coordinate inversion method, so that long-term monitoring of structural deformation can be realized, and the application is especially suitable for real-time monitoring of structural deformation under conditions such as high temperature, high pressure and invisible environment.

Description

Technical Field

[0001] This invention relates to the field of engineering structure deformation monitoring technology, and in particular to a reconfigurable magnetic marker tracking system and method for structural deformation monitoring. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Structural deformation monitoring has a crucial and widespread fundamental need in physical experimental design and engineering safety assurance in fields such as architecture, machinery, and aerospace. Existing contact methods, such as strain gauges, displacement sensors, and fiber Bragg gratings, are prone to failure under extreme environments such as high temperature and high pressure, making it difficult to meet the long-term health monitoring needs of complex engineering structures such as high-temperature pressure vessels. Therefore, technologies that utilize markers and tracking devices to acquire displacement changes at key structural points have advantages such as non-contact, automation, and high efficiency, and have been widely applied, including optical sensing methods such as total stations, photogrammetry, video analysis, and laser trackers. However, because they rely on line-of-sight conditions and are susceptible to interference from environmental factors such as changes in lighting and rain or snow, their reliability is limited in special environments.

[0004] In contrast, magnetic particle tagging and positioning technology possesses characteristics such as resistance to physical damage, immunity to light and severe weather, and adaptability to special environments such as high temperature and high pressure. It has been widely applied in fields such as medicine, robotics, and industrial automation, providing a potential effective approach to solving the long-term structural monitoring challenges in extreme environments. However, existing magnetic particle tagging and positioning methods typically require the acquisition of magnetic field signals as an unloaded reference value when there are no magnetic particles in the space, a condition often difficult to meet in structural deformation monitoring. Measuring the background magnetic field before installing the structure and magnetic particles is not only time-consuming, but the installation of magnetic particles may also disturb the original magnetic field; during long-term monitoring, changes in the background magnetic field over time can also lead to distortion of subsequent measurement results. Furthermore, in many engineering scenarios, the structure itself is fixed and cannot be disassembled; the installation of the structure and magnetic particles must be completed first, followed by sensor deployment. However, in some unseen scenarios, it is difficult to accurately locate the coordinates of the magnetic particles.

[0005] Therefore, there is an urgent need to develop a new method for magnetic particle-marked coordinate inversion that does not require an empty reference and can adapt to structural deformation monitoring in complex environments. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the present invention aims to provide a reconfigurable magnetic marker tracking system and method for structural deformation monitoring. The system employs a strip-shaped modular sub-unit architecture to design a reconfigurable magnetic sensor array. Combined with a no-load calibration magnetic particle marker coordinate inversion method, it can achieve long-term monitoring of structural deformation, and is particularly suitable for real-time monitoring of structural deformation under conditions such as high temperature, high pressure, and invisible environments.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solution: The first aspect of this invention provides a reconfigurable magnetic marker tracking system for monitoring structural deformation, comprising: The magnetic marker module is used to provide displacement information of the marker points of the structure to be monitored during the deformation process. It includes multiple magnetic particle markers, which are pre-fixed to key points inside the structure to be monitored. The magnetic particle markers and the structure to be monitored undergo synchronous displacement. The magnetic sensing array module is used to record real-time magnetic field signals within the target area during monitoring and to calculate the spatial coordinates of the magnetic sensing array. The magnetic particle marker coordinate inversion module is used to analyze the acquired magnetic field signal based on the spatial coordinates of the magnetic sensor array using the unloaded calibration magnetic particle marker coordinate inversion method, and calculate the three-dimensional coordinate changes of the magnetic particle marker of the monitored structure during the monitoring period.

[0008] Furthermore, the magnetic particles are labeled as neodymium iron boron magnets.

[0009] Furthermore, the magnetic particle marker installation method includes: embedding the magnetic particle marker inside the structure to be monitored by drilling, filling the excess space in the drill hole with synthetic resin, and bonding the magnetic particle marker to the surface of the structure to be monitored with an adhesive.

[0010] Furthermore, the magnetic sensing array consists of multiple strip-shaped modular units, each integrating five MMC5983MA triaxial magnetic sensors with a spacing of 50mm between each sensor. The STM32F103C8T6 microcontroller is the core, and parallel magnetic field signal acquisition and timing synchronization are achieved through a shared SPI bus and independent chip select.

[0011] Furthermore, the maximum monitoring distance of a single magnetic particle marker includes at least two central sensing points of the modular strip sub-units.

[0012] Furthermore, in the magnetic sensor array module, different magnetic sensor array combinations are set according to different monitoring scenarios.

[0013] Furthermore, the specific steps for calculating the spatial coordinates of the magnetic sensing array are as follows: Record the initial relative position of the triaxial magnetic sensor during installation; Using the center point of the magnetic sensor array as the origin, the spatial coordinates of each triaxial magnetic sensor are calculated and then verified and corrected.

[0014] Furthermore, the specific steps for analyzing the acquired magnetic field signal based on the magnetic particle marker coordinates using the unloaded calibration magnetic particle marker coordinate inversion method are as follows: A fixed-length data segment is extracted from the magnetic field signal as the inversion signal for the first time period; The magnetic particle marker coordinates were solved by combining the bivariate alternating least squares method with the Levenberg–Marquardt nonlinear least squares fitting method to obtain the inverted coordinate values ​​for the first time period. The magnetic field data in the second half of the extracted data segment is retained, and new magnetic field signal data of the same length is added to form the inversion signal of the second time segment. The changes in magnetic particle marker coordinates during the second time period were calculated using the unloaded calibration magnetic particle marker coordinate inversion algorithm and recorded as the inversion coordinate values ​​for the second time period. The difference between the inverted coordinate values ​​of the first time period and the inverted coordinate values ​​of the second time period that overlap is compared with the preset error threshold, and the inverted coordinate values ​​that meet the conditions are recorded. The inversion coordinate values ​​that meet the conditions in each time period are integrated, and the average value is taken for overlapping time periods to obtain the continuous changes in the coordinates of structural marker points during the monitoring period.

[0015] Furthermore, inversion coordinate values ​​with a difference less than a preset error threshold are considered to meet the conditions. If the difference is greater than or equal to the preset error threshold, the optimization parameters are adjusted and the inversion continues until the difference is less than the preset error threshold.

[0016] A second aspect of the present invention provides a reconfigurable magnetic particle tag tracking method for a reconfigurable magnetic tag tracking system for structural deformation monitoring, comprising the following steps: Magnetic particle markers and magnetic sensor arrays are deployed on the structure to be monitored; The magnetic field signals acquired by the magnetic sensing array are recorded in real time, and the spatial coordinates of the magnetic sensing array are calculated. The non-load calibration magnetic particle marker coordinate inversion method is used to analyze the collected magnetic field signal based on the spatial coordinates of the magnetic sensor array, and calculate the three-dimensional coordinate changes of the magnetic particle marker of the monitored structure during the monitoring period.

[0017] The above one or more technical solutions have the following beneficial effects: This invention discloses a reconfigurable magnetic marker tracking system and method for structural deformation monitoring. The system includes a magnetic marker module, a magnetic sensor array module, and a magnetic particle marker coordinate inversion module. The magnetic sensor array employs a strip-shaped modular sub-unit architecture to adapt to different structural forms and monitoring scenarios. The magnetic particle markers are composed of neodymium iron boron permanent magnets, fixed at key points of the structure, and move synchronously with the structure. Through a no-load calibration magnetic particle marker coordinate inversion algorithm, the three-dimensional coordinates of the magnetic particle markers are directly inverted under unknown or changing background magnetic field conditions, achieving long-term real-time monitoring with millimeter-level accuracy, avoiding errors caused by no-load calibration before installation and background field drift. This invention has advantages such as structural reconfigurability, strong environmental adaptability, and low maintenance costs, and is suitable for engineering structure deformation monitoring in high-temperature, high-pressure, invisible, and harsh environments.

[0018] This invention employs a strip-shaped modular sub-unit architecture magnetic sensor array, which can be combined into planar, square, or circular layouts as needed. It supports structural deformation monitoring of different sizes and shapes, can be deployed in limited spaces, or can be quickly assembled around large-scale structures. It is adaptable to harsh environments such as high temperature, high pressure, and high corrosion, and does not depend on visibility conditions. It can realize real-time monitoring of scenarios such as nuclear power plant reactor pressure vessels, underwater pipelines, and underground cavern linings.

[0019] This invention utilizes a coordinate inversion algorithm based on magnetic particle markers without unloaded calibration, enabling direct positioning inversion under unknown or changing background magnetic field conditions. This eliminates the need for unloaded calibration before installation and avoids disturbances to the reference signal during construction. Simultaneously, it exhibits strong suppression capabilities against sensor zero-point drift and environmental magnetic noise, maintaining millimeter-level positioning accuracy over extended monitoring periods.

[0020] The permanent magnet magnetic particle markers of this invention are made of neodymium iron boron material with high remanence and high coercivity, which can maintain stable magnetic performance over a lifespan of more than 10 years; the sensor array adopts an independent sub-module design, and any damaged module can be quickly replaced to avoid overall downtime; the modular array is reusable and supports rapid migration between different projects, with a long maintenance-free cycle, reducing the labor and time costs caused by equipment replacement and calibration.

[0021] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of the reconfigurable magnetic marker tracking system for structural deformation monitoring in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the reconfigurable magnetic sensing array structure composed of strip-shaped modular sub-units in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the magnetic sensing array module structure composed of strip-shaped modular sub-units in Embodiment 1 of the present invention; Figure 4 This is a flowchart of the algorithm for solving the coordinate inversion of unloaded calibration magnetic particle markers in Embodiment 1 of the present invention; Figure 5 This is a comparison chart of the magnetic particle marker displacement accuracy obtained by the unloaded calibration magnetic particle marker coordinate inversion algorithm and the conventional magnetic particle marker positioning algorithm in Embodiment 1 of the present invention. Among them, 1. Magnetic particle marker, 2. Magnetic sensor array, 3. Strip modular sub-unit, 4. Triaxial magnetic sensor, 5. Microcontroller, 6. Standalone circuit board, 7. Data interface, 8. Signal synchronization processor. Detailed Implementation

[0024] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0025] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof. The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0026] Example 1: Embodiment 1 of the present invention provides a reconfigurable magnetic marker tracking system for structural deformation monitoring, such as... Figure 1 As shown, it includes a magnetic labeling module, a magnetic sensing array module, and a magnetic particle label coordinate inversion module.

[0027] The magnetic marker module is used to provide displacement information of the marker points of the structure to be monitored during deformation. It includes multiple magnetic particle markers, which are pre-fixed to key points inside the structure to be monitored. The magnetic particle markers and the structure to be monitored undergo synchronous displacement.

[0028] In one specific embodiment, the magnetic particle marker 1 is a neodymium iron boron magnet. The magnetic particle marker installation method includes: embedding the magnetic particle marker inside the structure to be monitored by drilling a hole, filling the excess space in the drill hole with synthetic resin, and bonding the magnetic particle marker to the surface of the structure to be monitored with an adhesive.

[0029] Specifically, in this embodiment, multiple neodymium iron boron magnets are pre-fixed at key points inside the square pipe grid structure requiring deformation monitoring through drilling. Excess space in the drilled holes is filled with materials such as synthetic resin. The key points are selected based on actual conditions, as deformation at these points significantly affects the structure being monitored. By placing magnetic particle markers at these locations, the displacement response of the structure during deformation can be more accurately reflected. Generally, the location with the greatest theoretical deformation, the location where significant deformation may occur under stress, the midpoint, or the stress point are selected. In this embodiment, key points are set as areas of concentrated stress in the grid structure, node connections, or weak points that require focused monitoring in the engineering design.

[0030] If the structural points to be monitored do not meet the conditions for drilling, or are not suitable for installing magnetic particle markers by drilling, adhesives such as hot melt adhesive, pressure-sensitive adhesive, and latex can be used to bond the magnetic particle markers to the structural surface. This ensures that the markers move synchronously with the structure, providing displacement information during deformation. Alternatively, a combination of drilling and adhesives can be used to install the magnetic particle markers.

[0031] Specifically, the shape and size of the NdFeB magnet are selected according to the specific application scenario, and can be spherical, cylindrical, or toroidal, etc., based on the principle of stable bonding with the structure. The size can be any size within the range of 10mm to 100mm, based on the principle of coordination with the size of the monitoring structure. In this embodiment, a cylindrical shape is used, with dimensions of φ12mm × d12mm.

[0032] Specifically, the relationship between the size of the magnetic particle marker and the maximum monitoring distance is as follows: .

[0033] in, The maximum monitoring distance is expressed in mm. The diameter of the selected magnetic particle-marked volume equivalent sphere, in mm.

[0034] The magnetic sensing array module is used to record the real-time magnetic field signal in the target area during monitoring through the magnetic sensing array 2, and to calculate the spatial coordinates of the magnetic sensing array.

[0035] In one specific implementation, such as Figure 2 As shown, the magnetic sensor array 2 consists of multiple strip-shaped modular units 3. Each strip-shaped modular unit integrates five MMC5983MA triaxial magnetic sensors 4, with a spacing of 50mm between each triaxial magnetic sensor. It uses an STM32F103C8T6 microcontroller 5 as its core, achieving parallel magnetic field signal acquisition and timing synchronization through a shared SPI bus and independent chip select. Figure 3 As shown, the magnetic sensing array module is powered by a standalone circuit board 6, which is used as the mounting carrier. A data interface 7 is set on the standalone circuit board to output the processed magnetic field signal to the signal synchronization processor 8.

[0036] Specifically, the magnetic sensor array is installed as follows: a sensor frame is customized according to the monitoring scenario, and the sensors are fixedly installed on the frame according to the monitoring requirements. Each sensor is connected to the signal synchronization processor 8 through a data transmission line.

[0037] Specifically, the no-load calibration magnetic particle marker coordinate inversion algorithm analyzes the spatial coordinates of magnetic particles by combining magnetic field data from multiple sensors. Since the magnetic field signal of a magnet attenuates with increasing distance, a sufficient number of sensors are required to effectively acquire the magnet's magnetic field signal to meet the inversion accuracy requirements. Each unit has five sensors (50mm spacing). In this embodiment, the maximum monitoring distance of a single magnetic particle marker includes at least two central sensing points of the modular strip units. This ensures that data from at least ten sensors can be used for the magnet coordinate inversion, providing sufficient inversion data for joint calculation and guaranteeing the stability and accuracy of the inversion. In this embodiment, the spacing between the modular strip units is 5cm, and the vertical spacing between the center points of the sensing planes and the magnetic particle markers is 9cm.

[0038] Specifically, the number of modular strip units is selected based on the specific application scenario. While adhering to the principle of unit spacing, they should be deployed as evenly as possible to maximize coverage of the monitoring area. In this embodiment, the width of the square pipe sensing surface is 30cm, the magnetic particle marker projection is located at the center of this surface, and the deformation range of the magnetic particle marker does not exceed ±10cm. Therefore, the number of modular strip units is selected as 5, the spacing between the modular strip units is 5cm, and the sensing surface coverage area is 20cm × 20cm.

[0039] Specifically, in the magnetic sensor array module, different combinations of magnetic sensor arrays are set according to different monitoring scenarios, such as planar, square, and circular types. In this embodiment, a planar type combination is selected for the monitoring scenario inside a square pipe.

[0040] Specifically, the steps for calculating the spatial coordinates of the magnetic sensor array are as follows: Step a1: Record the initial relative position of the triaxial magnetic sensor during installation.

[0041] During the sensor frame customization stage and by pre-controlling the placement of each strip modular unit on the frame, the relative positions between each sensor are initially obtained.

[0042] Step a2: Using the center point of the magnetic sensor array as the origin of the coordinate system, calculate the spatial coordinates of each triaxial magnetic sensor, correlate the spatial coordinates of each sensor with the acquired real-time magnetic field signal, and perform verification and correction.

[0043] After the sensor frame is installed, the spatial coordinates of each sensor are calculated based on the frame design drawings, using the center point of the frame as the origin. The coordinates are then checked and corrected using equipment such as rulers, lasers, and total stations. This process is standard operating procedure for those skilled in the art, used to ensure that the actual installation coordinates of the sensors match the theoretical coordinates, thereby improving the accuracy of subsequent inversion calculations; therefore, it will not be elaborated further.

[0044] The magnetic particle marker coordinate inversion module is used to analyze the acquired magnetic field signal based on the spatial coordinates of the magnetic sensor array using the unloaded calibration magnetic particle marker coordinate inversion method, and calculate the three-dimensional coordinate changes of the magnetic particle marker of the monitored structure during the monitoring period.

[0045] like Figure 4 As shown, the specific steps are as follows: Step b1: Extract a fixed-length data segment from the magnetic field signal as the inversion signal for the first time period.

[0046] Specifically, the magnetic particle marker coordinate inversion module receives and stores the magnetic field signal transmitted by the signal synchronization processor. In this embodiment, a data segment of at least 1 minute in length (i.e., a data set of at least 1200 time points) is extracted from the stored magnetic field signal and saved separately. The magnetic field signal contained in this data segment conforms to the magnetic dipole field theory, that is, when the magnetic particle marker can be equivalent to a magnetic dipole, the magnetic field distribution generated by it at any position in space is determined by the magnetic dipole field equation, and the magnetic field strength at the observation point is equal to the superposition of the magnetic field generated by the magnetic particle at that point and the original background magnetic field at that point. When the distance d from the measurement point to the magnet is much larger than the magnet size r, the magnetic field distribution generated by the magnet at the spatial measurement point P can be expressed by the magnetic dipole field formula: , , .

[0047] in,( , , ( ) represents the xyz triaxial magnetic field signal acquired by the j-th sensor in the magnetic sensing array at time ti; , , Let be the background magnetic signal corresponding to the j-th sensor in the xyz direction. It is assumed to be short-term stable, that is, it is a constant during the calculation process and does not change with time. Let be the vacuum permeability, and take . H / m; Let be the position vector of the magnetic particle marker to sensor j at time i; , , )for The components along the xyz directions, where , , , ( , , ) represents the spatial coordinates of the magnetic particle at time i. , , The spatial coordinates of the j-th sensor; Let be the magnetic moment vector of the magnetic particle at time i. , , ) represents the xyz direction components of the magnetic moment vector.

[0048] Generally, the background magnetic field needs to be removed first, that is... , It equals 0. However, in this embodiment, it is difficult to obtain an accurate value of the background magnetic field for the structural deformation monitoring conditions, so it cannot be treated as 0 here, but is directly treated as an unknown for inversion later.

[0049] Specifically, if the magnetic sensing array used has N strip-shaped modular sub-units, and in this embodiment N equals 5, then there are 15N measurement values ​​at each time i, corresponding to 15N equations; among them, the known quantities are the triaxial magnetic field signals collected by each sensor. , , The spatial coordinates of each sensor ( , , The unknown quantity is the position of the magnetic particle marker at each moment. , , ), magnetic moment ( , , ), background magnetic field of each sensor ( , , ).

[0050] In a data segment lasting M minutes, there are 18000×M×N equations. The background magnetic field signal remains constant and can be shared and jointly estimated using data from various time points. The corresponding unknowns are 7200M+3. In this embodiment, a data segment lasting 5 minutes contains 450000 equations, with 36003 unknowns. The number of equations is much greater than the number of unknowns, therefore, the data from the continuous period can be jointly solved to obtain the coordinates of the magnetic particle markers at each time point within the period.

[0051] Step b2: The magnetic particle marker coordinates are solved using a combination of bivariate alternating least squares (ALS) and Levenberg-Marquardt (LM) nonlinear least squares fitting methods to obtain the inverted coordinate values ​​for the first time period. Based on the bivariate alternating least squares (ALS) optimization concept, the complexity of solving the magnetic particle marker coordinate problem can be reduced by splitting the joint nonlinear optimization into two sub-problems, thereby improving convergence efficiency and increasing solution stability.

[0052] This step follows the bivariate alternating least squares (ALS) optimization approach, which involves fixing one set of variables, transforming the multivariate optimization problem into a single-variable least squares problem to solve for the other set of variables, and then alternating between fixing and optimizing until convergence. In this embodiment, this algorithm can be used to decompose the joint nonlinear optimization into two subproblems, resulting in a more stable solution and improved convergence efficiency.

[0053] Specifically: (1) Input a guessed initial state (position, magnetic moment) of a magnetic particle marker and substitute it into the data set at the first time step to obtain the initial background field distribution, which serves as the starting point for iteration. The initial state of the magnetic particle marker includes the position and magnetic moment of the magnetic particle marker. In this embodiment, an initial state of the magnetic particle marker is input, with the position (0,0,0) and the magnetic moment direction (0,0,1).

[0054] .

[0055] in, Let j be the initial background field, and j be the sensor number. For measured values, This is the dipole field calculated based on the initial state marked by magnetic particles.

[0056] (2) Fix the background field and perform alternating iterative optimization of the magnetic particle label state.

[0057] For each time i, solve the nonlinear least squares problem: .

[0058] in, This represents the solution to minimize the state Pi of the magnetic particle, where Pi is the nth state. i A set of magnetic particle-labeled states at a given time point, including position ( , , ) and magnetic moment vector ( , , ); Indicates the first i The squared error between the measured magnetic field and the theoretical magnetic field at each time point ( (represents the square of the Euclidean norm), the smaller the value, the better the fit between the magnetic particle state and the measurement data; Here, λ represents the magnetic moment amplitude constraint term, and λ is the weighting coefficient. This represents the magnetic moment amplitude during the current optimization. The magnetic moment amplitude of the preset magnetic particles is generally obtained through magnetic measurement or selected empirically. In this embodiment, the magnetic moment amplitude of the φ12mm×d12mm neodymium iron boron magnet can be set to 2A˙m. 2 .

[0059] (3) Fix the magnetic particle label state and update the background field.

[0060] For sensor j, iterate through all times i and calculate the theoretical dipole field generated by the magnetic particle marker at that time. The background field estimate is obtained by averaging the residuals (measured value - dipole field) over time. .

[0061] in, This represents the updated background field, and T represents the total number of sampling points in the current time period.

[0062] In this embodiment, each moment represents a sampling point. Therefore, with a frequency of 20 Hz and a sampling time of t seconds, there are 20 sampling points T = 20 * t. This step involves iterating through the data at each sampling moment within the data segment, averaging the residuals over time, and obtaining the updated background field.

[0063] (4) If the background field changes If the value is less than 10⁻⁹T, then convergence is considered; otherwise, update. Continue iterating until the maximum number of iterations is reached.

[0064] .

[0065] in, The Frobenius norm represents the square root of the sum of squares of all elements in the background field matrix, used to quantify the overall change in the background field before and after a single iteration update.

[0066] (5) Output the background magnetic field when convergence or when the maximum number of iterations is reached, as well as the spatial coordinates of the magnetic particle markers at each time step.

[0067] Step b3: Retain the latter half of the magnetic field data in the extracted data segment, and then add new magnetic field signal data of the same length to form the inversion signal of the second time segment.

[0068] In this embodiment, the magnetic field data of the last 30 seconds of the extracted 1-minute data segment is retained, and then a new 30-second magnetic field data is added to form the inversion signal of the second time segment.

[0069] Step b4: Calculate the changes in magnetic particle marker coordinates during the second time period using the no-load calibration magnetic particle marker coordinate inversion algorithm (i.e., step b2 above). Record these changes as the inversion coordinate values ​​for the second time period.

[0070] Step b5: Compare the difference between the overlapping portion of the inverted coordinate values ​​of the first time period and the inverted coordinate values ​​of the second time period with the preset error threshold, and record the inverted coordinate values ​​that meet the conditions.

[0071] Specifically, inversion coordinate values ​​with a difference less than a preset error threshold are considered valid inversion coordinate values. If the difference is greater than or equal to the preset error threshold, the optimization parameters (initial guess value of the magnetic particle marker and number of iterations, etc.) are adjusted and the inversion continues until the difference is less than the preset error threshold. In this embodiment, the preset error threshold is set to 1 mm.

[0072] Step b6: Integrate the inversion coordinate values ​​that meet the conditions in each time period, take the average value of overlapping time periods, and obtain the continuous changes in the coordinates of structural marker points within the monitoring time.

[0073] Figure 5 The comparison between the deformed trajectories of the marker points obtained by the coordinate inversion algorithm of the magnetic particle marker without empty load calibration in this embodiment and the traditional magnetic positioning method is shown. It can be seen that the method of this embodiment is more accurate. In the traditional method, since the background magnetic field collected already includes the magnetic field generated by the magnetic particle marker, the magnetic field signal obtained by subtracting the background signal from the monitoring signal in the subsequent inversion process is much smaller than the theoretical magnetic signal of the magnetic particle marker, which leads to the deviation and shortening of the monitoring trajectory.

[0074] Example 2: Embodiment 2 of the present invention provides a reconfigurable magnetic particle tag tracking method for the reconfigurable magnetic tag tracking system for structural deformation monitoring in Embodiment 1, comprising the following steps: Step 1: Deploy magnetic particle markers and magnetic sensor arrays on the structure to be monitored. Specifically, based on the monitoring scenario, determine the number of modular strip units required and the spacing between them, and customize planar, square, or circular sensing frames. Install the sensing frames around the structure, combine the magnetic sensor arrays, and connect them all to the signal synchronization processor. After signal synchronization processing, the signals collected by each sensor are transmitted to the magnetic particle marker coordinate inversion module at a frequency of 20Hz.

[0075] Step 2: Record the magnetic field signals acquired by the magnetic sensor array in real time and calculate the spatial coordinates of the magnetic sensor array. Specifically, correlate the spatial coordinates of each sensor with the acquired real-time magnetic field signals, and run the no-load calibration magnetic particle marker coordinate inversion algorithm to obtain the real-time spatial coordinates of the magnetic particle markers inside the structure.

[0076] Step 3: Using the unloaded calibration magnetic particle marker coordinate inversion method, the acquired magnetic field signal is analyzed based on the spatial coordinates of the magnetic sensor array to calculate the three-dimensional coordinate changes of the magnetic particle markers on the monitored structure during the monitoring period. Specifically, the system runs continuously during the monitoring period, and the unloaded calibration magnetic particle marker coordinate inversion algorithm is run in time segments to record the structural deformation during the monitoring period.

[0077] The steps involved in the above embodiment two correspond to those in embodiment one. For specific implementation details, please refer to the relevant description section of embodiment one.

[0078] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application. In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)). The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A reconfigurable magnetic marker tracking system for structural deformation monitoring, characterized in that, include: The magnetic marker module is used to provide displacement information of the marker points of the structure to be monitored during the deformation process. It includes multiple magnetic particle markers, which are pre-fixed to key points inside the structure to be monitored. The magnetic particle markers and the structure to be monitored undergo synchronous displacement. The magnetic sensing array module is used to record real-time magnetic field signals within the target area during monitoring and to calculate the spatial coordinates of the magnetic sensing array. The magnetic particle marker coordinate inversion module is used to analyze the acquired magnetic field signal based on the spatial coordinates of the magnetic sensor array using the unloaded calibration magnetic particle marker coordinate inversion method, and calculate the three-dimensional coordinate changes of the magnetic particle markers on the monitored structure during the monitoring period. The specific steps are as follows: A fixed-length data segment is extracted from the magnetic field signal as the inversion signal for the first time period; The magnetic particle marker coordinates were solved by combining the bivariate alternating least squares method with the Levenberg–Marquardt nonlinear least squares fitting method to obtain the inverted coordinate values ​​for the first time period. The magnetic field data in the second half of the extracted data segment is retained, and new magnetic field signal data of the same length is added to form the inversion signal of the second time segment. The changes in magnetic particle marker coordinates during the second time period were calculated using the unloaded calibration magnetic particle marker coordinate inversion algorithm and recorded as the inversion coordinate values ​​for the second time period. The difference between the inverted coordinate values ​​of the first time period and the inverted coordinate values ​​of the second time period that overlap is compared with the preset error threshold, and the inverted coordinate values ​​that meet the conditions are recorded. The inversion coordinate values ​​that meet the conditions in each time period are integrated, and the average value is taken for overlapping time periods to obtain the continuous changes in the coordinates of structural marker points during the monitoring period.

2. The reconfigurable magnetic marker tracking system for structural deformation monitoring as described in claim 1, characterized in that, The magnetic particles are labeled as neodymium iron boron magnets.

3. The reconfigurable magnetic marker tracking system for structural deformation monitoring as described in claim 1, characterized in that, The magnetic particle marker installation method includes: embedding the magnetic particle marker inside the structure to be monitored by drilling, filling the excess space in the drill hole with synthetic resin, and bonding the magnetic particle marker to the surface of the structure to be monitored with an adhesive.

4. The reconfigurable magnetic marker tracking system for structural deformation monitoring as described in claim 1, characterized in that, The magnetic sensing array consists of multiple strip-shaped modular units. Each strip-shaped modular unit integrates five MMC5983MA triaxial magnetic sensors. The spacing between each triaxial magnetic sensor is 50mm. The core is an STM32F103C8T6 microcontroller. Parallel magnetic field signal acquisition and timing synchronization are achieved through a shared SPI bus and independent chip select.

5. The reconfigurable magnetic tag tracking system for structural deformation monitoring as described in claim 4, characterized in that, The maximum monitoring distance of a single magnetic particle marker includes at least two central sensing points of the modular strip sub-units.

6. The reconfigurable magnetic marker tracking system for structural deformation monitoring as described in claim 1, characterized in that, In the magnetic sensor array module, different magnetic sensor array combinations are set according to different monitoring scenarios.

7. The reconfigurable magnetic marker tracking system for structural deformation monitoring as described in claim 5, characterized in that, The specific steps for calculating the spatial coordinates of the magnetic sensor array are as follows: Record the initial relative position of the triaxial magnetic sensor during installation; Using the center point of the magnetic sensor array as the origin, the spatial coordinates of each triaxial magnetic sensor are calculated and then verified and corrected.

8. The reconfigurable magnetic marker tracking system for structural deformation monitoring as described in claim 1, characterized in that, Inversion coordinate values ​​with a difference less than the preset error threshold are considered to meet the conditions. If the difference is greater than or equal to the preset error threshold, the optimization parameters are adjusted and the inversion continues until the difference is less than the preset error threshold.

9. A reconfigurable magnetic particle tag tracking method for a reconfigurable magnetic tag tracking system for structural deformation monitoring as described in any one of claims 1-8, characterized in that, Includes the following steps: Magnetic particle markers and magnetic sensor arrays are deployed on the structure to be monitored; The magnetic field signals acquired by the magnetic sensing array are recorded in real time, and the spatial coordinates of the magnetic sensing array are calculated. The non-load calibration magnetic particle marker coordinate inversion method is used to analyze the collected magnetic field signal based on the spatial coordinates of the magnetic sensor array, and calculate the three-dimensional coordinate changes of the magnetic particle marker of the monitored structure during the monitoring period.

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