Differential evolution underground active detection method based on rotary permanent magnet magnetic beacon

Abstract

The invention discloses a differential evolution underground active detection method based on a rotary permanent magnet magnetic beacon, and belongs to the field of underground target detection and magnetic field signal processing. According to the invention, the problems of low precision of ferromagnetic target positioning and poor robustness of a detection method in the prior art are solved. By utilizing the characteristic that a low-frequency magnetic field signal generated by a magnetic beacon can penetrate through a metal pipeline and soil to reach a target ferromagnetic substance from the ground, an alternating quasi-static magnetic field is applied to a target, the target signal response can be effectively enhanced, and the target ferromagnetic substance can generate a corresponding induced magnetic field, so that the target signal response is enhanced. The magnetic sensor on the ground receives the superposed magnetic field signals and utilizes a differential evolution algorithm to estimate the magnetic moment vector, the relative distance and the relative azimuth information of the target ferromagnetic substance in the denial environment, so that the positioning precision of the target ferromagnetic substance is improved, the robustness of the system in the multi-source interference environment is enhanced, and the positioning accuracy of the target ferromagnetic substance is improved. And the complexity of ferromagnetic detection items is reduced. The method can be applied to ferromagnetic target detection.

Description

Technical Field

[0001] This invention belongs to the fields of underground target detection and magnetic field signal processing, specifically involving a differential evolution underground active detection method based on a rotating permanent magnet magnetic beacon. Background Technology

[0002] With the continuous development of infrastructure construction, the utilization of underground space is becoming increasingly complex. Accurately detecting underground ferromagnetic targets has become a key technical challenge in fields such as underground engineering, geological exploration, and archaeological excavation. During subway construction or underground pipeline renovation, it is necessary to accurately detect the location of existing underground ferromagnetic pipelines to avoid accidental damage during construction. In the field of mineral exploration, detecting the distribution of ferromagnetic minerals in underground veins can help determine the extent and value of ore bodies. However, in some special environments, complex terrain makes traditional detection methods difficult to apply. In archaeological excavation, magnetic detection can be used to detect underground ancient tombs, cultural sites, etc., thereby helping archaeologists determine the direction and scope of excavation.

[0003] Traditional electromagnetic induction-based detection equipment, such as ground-penetrating radar, time-domain electromagnetic methods, and pulse-induction mine detection systems, suffers severe signal attenuation when exposed to highly conductive media such as moist soil and groundwater, making them unsuitable for continuous and reliable detection in complex environments. Traditional magnetic detection methods primarily rely on passively receiving the magnetic field signals generated by the target itself. However, their detection effectiveness is highly dependent on the target's magnetic strength and background magnetic field interference. For ferromagnetic targets, their own magnetic field signals are relatively weak and easily blocked by soil, rocks, and building walls in complex urban electromagnetic environments, making it difficult for radio signals to penetrate these media to reach the target and return to the receiving equipment, or causing them to be interfered with or submerged by noise and environmental magnetic fields. Methods that determine the presence and location of targets based on geomagnetic gradient trends are highly dependent on deployment accuracy and environmental magnetic field models, making deployment difficult and the system susceptible to structural deformation.

[0004] In summary, in order to address the problems of low accuracy in locating ferromagnetic targets and poor robustness of existing detection methods, proposing a new method for detecting ferromagnetic targets is an urgent need. Summary of the Invention

[0005] The purpose of this invention is to solve the problems of low accuracy in locating ferromagnetic targets and poor robustness of existing detection methods, and to propose a differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon.

[0006] The technical solution adopted by this invention to solve the above-mentioned technical problems is: a differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon, the method specifically including the following steps:

[0007] During the preparation stage:

[0008] Step 1: Assemble the rotating permanent magnet beacon on the turntable on the ground, place magnetic sensors at each calibration position, and measure the relative coordinates between the rotating permanent magnet beacon and each magnetic sensor.

[0009] Step 2: After starting the turntable, the rotating permanent magnet beacon rotates at a constant angular velocity and generates a quasi-static magnetic field signal;

[0010] Magnetic field vector data is collected using magnetic sensors at various calibration locations. After filtering the collected magnetic field vector data, the minimum modulus of magnetic induction intensity is extracted based on the filtered magnetic field vector data corresponding to each magnetic sensor. The magnetic moment of the rotating permanent magnet beacon is calibrated based on the extracted minimum modulus of magnetic induction intensity.

[0011] During the work phase:

[0012] Step 3: Place it in any location Each magnetic sensor measures the magnetic beacon of the rotating permanent magnet and... The relative coordinates between each magnetic sensor in the magnetic sensor;

[0013] After the turntable is started, the rotating permanent magnet beacon generates a quasi-static low-frequency magnetic field signal.

[0014] Step 4: The magnetic sensors at each location in Step 3 simultaneously collect magnetic field data. After filtering the collected magnetic field data, the total magnetic induction intensity corresponding to the magnetic sensor at each location is obtained.

[0015] The total magnetic flux density corresponding to the magnetic sensor at each location is generated by the magnetic flux density produced by the rotating permanent magnet beacon. The magnetic induction intensity generated by the target iron block Overlay;

[0016] Then, based on the total magnetic induction intensity corresponding to the magnetic sensor at each position, the true value of the signal amplitude on each axis of the signal collected at each position is calculated;

[0017] Step 5: Based on all The objective function is constructed from the true values ​​of the signal amplitude on each axis of the signals collected at each location.

[0018] Step 6: Solve the objective function constructed in Step 5 to estimate the position of the target iron block and the components of the magnetic moment vector of the target iron block on each axis.

[0019] Furthermore, the relative coordinates between the rotating permanent magnet beacon and each magnetic sensor are measured using a total station.

[0020] Furthermore, the rotating permanent magnet beacon rotates at a constant angular velocity, specifically: the rotating permanent magnet beacon rotates at an angular frequency... Around a spatial rectangular coordinate system The frequency of the quasi-static magnetic field signal generated by the rotation of the axis for ;

[0021] The spatial rectangular coordinate system has its origin at the geometric center of the rotating permanent magnet beacon. Taking any direction on the plane of revolution as axis, shaft and The axis is perpendicular, and The axis is located on the plane of revolution. The positive direction of the axis is perpendicular to the plane of revolution and points vertically upward. axis, shaft and The axes form a right-handed coordinate system.

[0022] Furthermore, the specific process for calibrating the magnetic moment of the rotating permanent magnet beacon based on the extracted minimum modulus of magnetic induction intensity is as follows:

[0023] Calibrate the magnetic moment of a rotating permanent magnet beacon using the least squares method:

[0024] (4)

[0025] Wherein, the modulus vector , They represent the 1st, 2nd, ..., 1st, 2nd, ..., 3rd. The minimum modulus of magnetic induction intensity corresponding to the magnetic sensor at each calibrated position. Let T be the magnetic permeability of air, and the superscript T represents the transpose of the matrix, and the superscript -1 represents the inverse of the matrix. The magnetic moment of the rotating permanent magnet beacon is represented by the relative distance vector. , They represent the 1st, 2nd, ..., 1st, 2nd, ..., 3rd. The distance from the magnetic sensor at each calibrated position to the rotating permanent magnet beacon. This indicates the total number of calibrated positions.

[0026] Furthermore, in step four, the true value of the signal amplitude on each axis of the signal acquired at each position is calculated based on the total magnetic induction intensity corresponding to the magnetic sensor at each position; the specific process is as follows:

[0027] The magnetic flux density generated at each magnetic sensor by the rotating permanent magnet beacon is:

[0028] (5)

[0029] in, The initial phase of the time-varying magnetic moment of the rotating permanent magnet magnetic beacon. Indicates the rotating permanent magnet magnetic beacon in the first... The magnetic induction intensity generated at each magnetic sensor Indicates the rotating permanent magnet magnetic beacon and the first The relative coordinates between the magnetic sensors Indicates the rotating permanent magnet magnetic beacon and the first The distance between the magnetic sensors , Indicates time;

[0030] Let the coordinates of the target iron block in the spatial rectangular coordinate system be denoted as . The components of the magnetic moment amplitude of the induced magnetic field of the target iron block on the three coordinate axes are: The initial phase of the target iron block has the following components on the three coordinate axes: ;

[0031] in, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The initial phase of the target iron block Axial components, The initial phase of the target iron block Axial components, The initial phase of the target iron block Axial components;

[0032] Define intermediate variables intermediate variables intermediate variables Then the intermediate variable ,point Magnetic induction intensity generated by the target iron block at the location for:

[0033] (6)

[0034] The actual measured signal amplitude is:

[0035] (8)

[0036] (9)

[0037] (10)

[0038] in, Indicates the first Signals collected at each location The true value of the signal amplitude on the axis. Indicates the first Signals collected at each location The true value of the signal amplitude on the axis. Indicates the first Signals collected at each location The true value of the signal amplitude on the axis;

[0039] That is, the first The signal amplitude of the signal collected at each location on each axis is related to... Functions:

[0040] (11).

[0041] Furthermore, the specific process of step five is as follows:

[0042] The following system of nonlinear equations is established:

[0043] (12)

[0044] in, Represents a system of nonlinear equations, with state variables... ;

[0045] The objective function is:

[0046] (13)

[0047] in, This represents the 2-norm.

[0048] Furthermore, in step six, the objective function is solved using the differential evolution algorithm.

[0049] Furthermore, the specific process of step six is ​​as follows:

[0050] Step 61: Let the population size in the solution space be... An initial population is randomly generated, and the dimension of each individual in the population is related to the state quantity. same;

[0051] The random generation of the initial population is specifically as follows:

[0052] (14)

[0053] in, Indicates the first in the initial population individual The One portion, Indicates the first The lower bound of each component Indicates the first The upper bound of each component, It is a random number between 0 and 1. ;

[0054] Step 62: Initialize the number of iterations ;

[0055] Step 63, for individuals Perform a mutation operation to generate a new temporary mutated individual:

[0056] (15)

[0057] in, and From Two distinct individuals are randomly selected from the data. express The optimal individual in the process, To control the scaling factor of the parameter, express The corresponding temporary mutated individuals;

[0058] Step Six Four: For Individuals and temporary mutant individuals Cross-recombination was performed to generate experimental individuals. ;

[0059] Step 65: Based on the experimental individuals Individuals to be preserved for the next generation ;

[0060] Step 66: Determine if the iteration stopping condition is met. If the iteration stopping condition is met, take the optimal solution obtained in the last iteration as the final solution result. If the iteration stopping condition is not met, then let... Return to step six three;

[0061] The stopping condition for the iteration is: the fitness value of the optimal solution obtained in the current iteration is less than the preset error precision or the maximum number of iterations is reached.

[0062] Furthermore, the specific process of step six-four is as follows:

[0063] (16)

[0064] in, Indicates the first Each component corresponds to a random number. , Crossover probability factor , A dimension component is randomly assigned.

[0065] Furthermore, the specific process of step six-five is as follows:

[0066] (17)

[0067] in, Indicates the test individual fitness value, Represents an individual The fitness value.

[0068] The beneficial effects of this invention are:

[0069] This invention utilizes the characteristic that low-frequency magnetic field signals generated by magnetic beacons can penetrate metal pipes and soil to reach target ferromagnetic materials from the ground. By applying an alternating quasi-static magnetic field to the target, the signal response of the target can be effectively enhanced. Moreover, the target ferromagnetic material will generate a corresponding induced magnetic field. The magnetic sensor on the ground receives the superimposed magnetic field signals and uses a differential evolution algorithm to estimate the magnetic moment vector, relative distance, and relative orientation information of the target ferromagnetic material in the denied environment. This improves the accuracy of the target ferromagnetic material location, enhances the robustness of the system in multi-source interference environments, and reduces the complexity of ferromagnetic detection projects.

[0070] This invention realizes an active detection method based on a rotating permanent magnet magnetic beacon in the presence of strong underground obstructions. It has the advantages of strong penetration ability, high positioning accuracy, no dependence on initial value, strong global convergence ability and good system robustness. It can provide high-precision and globally convergent detection services in fields such as underground pipeline detection, mineral resource exploration, and archaeological excavation, improve the efficiency and accuracy of target ferromagnetic material detection, and has good engineering application prospects. Attached Figure Description

[0071] Figure 1 This is a flowchart of a differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon, according to the present invention.

[0072] Figure 2 This is a schematic diagram showing the positional relationship between the magnetic beacon, the iron block, and the magnetic sensor;

[0073] Figure 3 This is a comparison chart of relative distance calculation errors obtained using different numbers of sensors;

[0074] Figure 4This is a comparison chart of pitch angle calculation errors obtained using different numbers of sensors;

[0075] Figure 5 This is a comparison chart of yaw angle calculation errors obtained using different numbers of sensors;

[0076] Figure 6 This is a comparison chart of the calculation errors of magnetic moment magnitude obtained using different numbers of sensors;

[0077] Figure 7 This is a comparison chart of the magnetic moment direction calculation errors obtained using different numbers of sensors. Detailed Implementation

[0078] Specific implementation method one: Combining Figure 1 This embodiment describes a differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon. The method specifically includes the following steps:

[0079] During the preparation stage:

[0080] Step 1: Assemble the rotating permanent magnet beacon on the turntable on the ground, place magnetic sensors at each calibration position, and measure the relative coordinates between the rotating permanent magnet beacon and each magnetic sensor.

[0081] It should be noted that the spatial rectangular coordinate system established in this invention has its origin at the geometric center of the rotating permanent magnet beacon. Therefore, the relative coordinates between the rotating permanent magnet beacon and the magnetic sensor are the coordinates of the magnetic sensor in the spatial rectangular coordinate system;

[0082] Step 2: After starting the turntable, the rotating permanent magnet beacon rotates at a constant angular velocity and generates a quasi-static magnetic field signal;

[0083] Magnetic field vector data is collected using magnetic sensors at various calibration locations. After filtering the collected magnetic field vector data, the minimum modulus of magnetic induction intensity is extracted based on the filtered magnetic field vector data corresponding to each magnetic sensor. The magnetic moment of the rotating permanent magnet beacon is calibrated based on the extracted minimum modulus of magnetic induction intensity.

[0084] During the work phase:

[0085] Step 3: Place it in any location One magnetic sensor (taken in this invention) ,and (each magnetic sensor is located at a different position) to measure the magnetic beacon of the rotating permanent magnet and... The relative coordinates between each magnetic sensor in the magnetic sensor;

[0086] After the turntable is started, the rotating permanent magnet beacon rotates at a preset angular rate to generate a quasi-static low-frequency magnetic field signal.

[0087] Step 4: The magnetic sensors at each location in Step 3 simultaneously collect magnetic field data. After filtering the collected magnetic field data, the total magnetic induction intensity corresponding to the magnetic sensor at each location is obtained.

[0088] The total magnetic flux density corresponding to the magnetic sensor at each location is generated by the magnetic flux density produced by the rotating permanent magnet beacon. The magnetic induction intensity generated by the target iron block Superimposed, such as Figure 2 As shown, the total magnetic induction intensity corresponding to the magnetic sensor at point P is the superposition of the rotating permanent magnet beacon at the origin and the target iron block;

[0089] Then, based on the total magnetic induction intensity corresponding to the magnetic sensor at each position, the true value of the signal amplitude on each axis of the signal collected at each position is calculated;

[0090] Step 5: Based on all The objective function is constructed from the true values ​​of the signal amplitude on each axis of the signals collected at each location.

[0091] Step 6: Solve the objective function constructed in Step 5 to estimate the position of the target iron block and the components of the magnetic moment vector of the target iron block on each axis.

[0092] The size of the target iron block can be roughly estimated based on the components of its magnetic moment vector along each axis.

[0093] Specific Implementation Method Two: This implementation method differs from Specific Implementation Method One in that the relative coordinates between the rotating permanent magnet beacon and each magnetic sensor are measured using a total station.

[0094] The other steps and parameters are the same as in Specific Implementation Method 1.

[0095] Specific Implementation Method Three: This implementation method differs from Specific Implementation Method One or Two in that the rotating permanent magnet beacon rotates at a constant angular velocity, specifically: the rotating permanent magnet beacon rotates at an angular frequency... Around a spatial rectangular coordinate system The frequency of the quasi-static magnetic field signal generated by the rotation of the axis for ;

[0096] The spatial rectangular coordinate system has its origin at the geometric center of the rotating permanent magnet beacon. Taking any direction on the plane of revolution as axis, shaft and The axis is perpendicular, and The axis is located on the plane of revolution. The positive direction of the axis is perpendicular to the plane of revolution and points vertically upward. axis, shaft and The axes form a right-handed coordinate system.

[0097] Other steps and parameters are the same as in specific implementation method one or two.

[0098] It should be noted that the position coordinates of the rotating permanent magnet beacon, the magnetic sensor, and the ferromagnetic target in this invention all refer to the coordinates in the spatial rectangular coordinate system established in this embodiment.

[0099] Specific Implementation Method Four: This implementation method differs from Specific Implementation Methods One to Three in that the magnetic moment of the rotating permanent magnet beacon is calibrated based on the extracted minimum modulus of magnetic induction intensity. The specific process is as follows:

[0100] Based on the motion characteristics of rotating permanent magnet beacons, a rotating permanent magnet beacon can be equivalent to two beacons with the same material, cross-sectional area, and number of turns, and with the same amplitude, frequency, and phase difference. Using a sinusoidal current-carrying solenoid and the Biotsafar and magnetic dipole models, the magnetic induction intensity generated by a rotating permanent magnet beacon at any target point is derived. :

[0101] (1)

[0102] in, This indicates the magnitude of the magnetic moment of a rotating permanent magnet magnetic beacon. Let be the magnetic permeability of air. It is the relative distance between the rotating permanent magnet beacon and the target point. These are the relative elevation and azimuth angles between the rotating permanent magnet beacon and the target point, respectively.

[0103] From formula (1), it can be seen that the magnetic flux density generated by the rotating permanent magnet beacon at the target point is... for:

[0104] (2)

[0105] As shown in formula (3), the minimum value of the magnetic flux density modulus is a constant:

[0106] (3)

[0107] Therefore, the magnetic moment of a rotating permanent magnet beacon can be calibrated by extracting the minimum modulus of the magnetic flux density. The magnetic field vector data collected by the magnetic sensor at multiple calibration locations are filtered, and the minimum modulus of the magnetic flux density is extracted for each location. .

[0108] Calibrate the magnetic moment of a rotating permanent magnet beacon using the least squares method:

[0109] (4)

[0110] Wherein, the modulus vector , They represent the 1st, 2nd, ..., 1st, 2nd, ..., 3rd. The minimum modulus of magnetic induction intensity corresponding to the magnetic sensor at each calibrated position. Let T be the magnetic permeability of air, and the superscript T represents the transpose of the matrix, and the superscript -1 represents the inverse of the matrix. The magnetic moment of the rotating permanent magnet beacon is represented by the relative distance vector. , They represent the 1st, 2nd, ..., 1st, 2nd, ..., 3rd. The distance from the magnetic sensor at each calibrated position to the rotating permanent magnet beacon. This indicates the total number of calibrated positions.

[0111] The other steps and parameters are the same as those in one of the specific implementation methods one to three.

[0112] Specific Implementation Method Five: This implementation method differs from Specific Implementation Methods One to Four in that, in step four, the true value of the signal amplitude on each axis of the signal collected at each position is calculated based on the total magnetic induction intensity corresponding to the magnetic sensor at each position; the specific process is as follows:

[0113] According to the magnetic dipole model, the magnetic flux density generated by the rotating permanent magnet beacon at each magnetic sensor is:

[0114] (5)

[0115] in, The initial phase of the time-varying magnetic moment of the rotating permanent magnet magnetic beacon. Indicates the rotating permanent magnet magnetic beacon in the first... The magnetic induction intensity generated at each magnetic sensor Indicates the rotating permanent magnet magnetic beacon and the first The relative coordinates between the magnetic sensors ( That is, the first (Coordinates of each magnetic sensor in the spatial rectangular coordinate system of this invention) Indicates the rotating permanent magnet magnetic beacon and the first The distance between the magnetic sensors , Indicates time;

[0116] Let the coordinates of the target iron block in the spatial rectangular coordinate system be denoted as . The components of the magnetic moment amplitude of the induced magnetic field of the target iron block on the three coordinate axes are: The initial phase of the target iron block has the following components on the three coordinate axes: ;

[0117] in, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The initial phase of the target iron block Axial components, The initial phase of the target iron block Axial components, The initial phase of the target iron block Axial components;

[0118] Define intermediate variables intermediate variables intermediate variables Then the intermediate variable ,point Magnetic induction intensity generated by the target iron block at the location for:

[0119] (6)

[0120] right Two sine waves of the same frequency but different phases and amplitudes. After superposition, a new amplitude of the sine wave is obtained. :

[0121] (7)

[0122] For the three coordinate axes of a Cartesian coordinate system, the components along each axis can be viewed as the superposition of multiple sine waves with different phases and amplitudes. For example, for According to equations (5) and (6), the phases of each sine wave are obtained along the coordinate axes. , , , , The amplitudes of each sine wave are respectively , , , , Substituting the above phases and their corresponding amplitudes into formula (7), we obtain the first phase. Signals collected at each location The true value of the signal amplitude on the axis. Similarly, the first can be calculated separately. Signals collected at each location The true value of the signal amplitude on the axis, the first Signals collected at each location The true value of the signal amplitude on the axis;

[0123] According to equation (7), the actual measured signal amplitude can be obtained as follows:

[0124] (8)

[0125] (9)

[0126] (10)

[0127] in, Indicates the first Signals collected at each location The true value of the signal amplitude on the axis. Indicates the first Signals collected at each location The true value of the signal amplitude on the axis. Indicates the first Signals collected at each location The true value of the signal amplitude on the axis;

[0128] That is, the first The signal amplitude of the signal collected at each location on each axis is related to... Functions:

[0129] (11)

[0130] The other steps and parameters are the same as those in one of the specific implementation methods one to four.

[0131] Specific Implementation Method Six: This implementation method differs from Specific Implementation Methods One to Five in that the specific process of step five is as follows:

[0132] The following system of nonlinear equations is established:

[0133] (12)

[0134] in, Represents a system of nonlinear equations, with state variables... ;

[0135] The objective function is:

[0136] (13)

[0137] in, Let 2 be the norm, and equation (13) represents the calculation of the norm. The state variable whose value reaches the minimum. .

[0138] The other steps and parameters are the same as those in one of the specific implementation methods one to five.

[0139] Specific Implementation Method Seven: This implementation method differs from Specific Implementation Methods One to Six in that, in step six, the objective function is solved using the Differential Evolution (DE) algorithm.

[0140] The other steps and parameters are the same as those in one of the specific implementation methods one to six.

[0141] Specific Implementation Method Eight: This implementation method differs from Specific Implementation Methods One to Seven in that the specific process of step six is ​​as follows:

[0142] Step 61: Let the population size in the solution space be... An initial population is randomly generated, and the dimension of each individual in the population is related to the state quantity. same;

[0143] The random generation of the initial population is specifically as follows:

[0144] (14)

[0145] in, Indicates the first in the initial population individual The One portion, Indicates the first The lower bound of each component Indicates the first The upper bound of each component, It is a random number between 0 and 1. ;

[0146] Step 62: Initialize the number of iterations ;

[0147] Step 63, for individuals Perform a mutation operation to generate a new temporary mutated individual:

[0148] (15)

[0149] in, and From Two distinct individuals are randomly selected from the data. express The optimal individual in the process, To control the scaling factor of the parameter, , express The corresponding temporary mutated individuals;

[0150] It should be noted that, in order to ensure the validity of the solution, it is necessary to judge the temporary mutated individuals separately. Whether each component in the process satisfies the boundary conditions, that is, whether the value of each variable is between its lower and upper bounds. If for a temporary mutant, there are components in the temporary mutant that do not satisfy the boundary conditions, then this component in the temporary mutant is regenerated using a random method to obtain a regenerated temporary mutant. Then, step six-four is executed using the newly generated temporary mutant.

[0151] Step Six Four: For Individuals and temporary mutant individuals Cross-recombination was performed to generate experimental individuals. ;

[0152] Step 65: Based on the experimental individuals Individuals to be preserved for the next generation ;

[0153] Step 66: Determine if the iteration stopping condition is met. If the iteration stopping condition is met, take the optimal solution obtained in the last iteration (Step 65) as the final solution result. If the iteration stopping condition is not met, then let... Return to step six three;

[0154] The stopping condition for the iteration is: the fitness value of the optimal solution obtained in the current iteration (i.e., the objective function value obtained by substituting the optimal solution into the objective function) is less than the preset error precision or the maximum number of iterations is reached.

[0155] The other steps and parameters are the same as those in any of the specific implementation methods one to seven.

[0156] Specific Implementation Method Nine: This implementation method differs from Specific Implementation Methods One to Eight in that the specific process of step six-four is as follows:

[0157] (16)

[0158] in, Indicates the first Each component corresponds to a random number. , Crossover probability factor , A randomly assigned dimension component represents the first element in the experimental individual. Each component.

[0159] The other steps and parameters are the same as those in one of the specific implementation methods one to eight.

[0160] By randomly setting a dimension component, it can be ensured that at least one dimension component of the experimental individuals after crossover is provided by the temporary mutant individuals in the offspring.

[0161] Specific Implementation Method Ten: This implementation method differs from Specific Implementation Methods One to Nine in that the specific process of step six-five is as follows:

[0162] (17)

[0163] in, Indicates the test individual fitness value, Represents an individual The fitness value.

[0164] The other steps and parameters are the same as those in any of the specific implementation methods one to nine.

[0165] Calculate the new individuals obtained after the crossover operation. The fitness value is calculated and compared with the current individual's fitness value. The fitness values ​​of the new individual are compared. If the fitness value is good, then the new individual... It will be preserved to the next generation, the current individual Eliminated, or retained. Through mutation, crossover, and selection operations, the population evolves to the next generation and repeats the cycle until the algorithm iterations reach a predetermined maximum or the optimal solution of the population reaches a predetermined error precision. The algorithm then terminates, calculating the magnetic moment vector, position, and initial phase information of the target iron block.

[0166] Simulation verification

[0167] Simulation verification was performed on a differential evolutionary active underground detection algorithm based on a rotating permanent magnet magnetic beacon. The magnetic moment was set to... The permanent magnet rotates around the z-axis at 240 rpm. The magnetic sensor samples at a frequency of 5000 Hz and introduces an interference magnetic field with a mean of 45000 nT and white noise with an amplitude of 1 nT. The magnetic moment of the target iron block in the quasi-static magnetic field is set to... The magnetic moment direction vector is (1,1,1), and the permeability of air is... Set the scaling factor. Cross factor The predetermined error accuracy is Maximum number of iterations An array of four magnetic sensors was used, and experiments were conducted at ten locations. The estimated value for each location was the average of five estimates. The simulation results are shown in Table 1. Comparative experiments were then conducted using arrays of six and eight sensors, respectively, and the solution results are shown in Table 1. Figures 3 to 7 As shown:

[0168] Table 1. Solution results of the differential evolutionary active subsurface detection algorithm based on rotating permanent magnet magnetic beacons.

[0169]

[0170] Simulation results show that the differential evolutionary active underground detection algorithm based on a rotating permanent magnet magnetic beacon, using four sensors, has the following average errors at 5m: relative distance 0.005m, pitch angle 0.057°, yaw angle 0.213°, magnetic moment magnitude error 0.127%, and magnetic moment direction angle 0.185°; at 10m: relative distance 0.02m, pitch angle 0.225°, yaw angle 0.336°, magnetic moment magnitude error 0.159%, and magnetic moment direction angle 0.381°; and at 15m: relative distance 0.156m, pitch angle 1.343°, yaw angle 0.984°, magnetic moment magnitude error 0.987%, and magnetic moment direction angle 1.624°. The more sensors there are, the smaller the algorithm's error and the stronger its robustness. Therefore, the differential evolutionary active underground detection algorithm based on rotating permanent magnet magnetic beacons can still stably detect underground ferromagnetic targets in environments with strong obstruction. The method of this invention improves the accuracy of underground detection, effectively suppresses the influence of background magnetic fields and low-frequency noise, and the system has strong robustness.

[0171] The above examples of the present invention are merely illustrative of the computational model and process of the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is impossible to exhaustively list all possible implementations here. Any obvious variations or modifications derived from the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A differential evolutionary active underground detection method based on rotating permanent magnet magnetic beacons, characterized in that, The method specifically includes the following steps: During the preparation stage: Step 1: Assemble the rotating permanent magnet beacon on the turntable on the ground, place magnetic sensors at each calibration position, and measure the relative coordinates between the rotating permanent magnet beacon and each magnetic sensor. Step 2: After starting the turntable, the rotating permanent magnet beacon rotates at a constant angular velocity and generates a quasi-static magnetic field signal; Magnetic field vector data is collected using magnetic sensors at various calibration locations. After filtering the collected magnetic field vector data, the minimum modulus of magnetic induction intensity is extracted based on the filtered magnetic field vector data corresponding to each magnetic sensor. The magnetic moment of the rotating permanent magnet beacon is calibrated based on the extracted minimum modulus of magnetic induction intensity. During the work phase: Step 3: Place it in any location Each magnetic sensor measures the magnetic beacon of the rotating permanent magnet and... The relative coordinates between each magnetic sensor in the magnetic sensor; After the turntable is started, the rotating permanent magnet beacon generates a quasi-static low-frequency magnetic field signal. Step 4: The magnetic sensors at each location in Step 3 simultaneously collect magnetic field data. After filtering the collected magnetic field data, the total magnetic induction intensity corresponding to the magnetic sensor at each location is obtained. The total magnetic flux density corresponding to the magnetic sensor at each location is generated by the magnetic flux density produced by the rotating permanent magnet beacon. The magnetic induction intensity generated by the target iron block Overlay; Then, based on the total magnetic induction intensity corresponding to the magnetic sensor at each position, the true value of the signal amplitude on each axis of the signal collected at each position is calculated; Step 5: Based on all The objective function is constructed from the true values ​​of the signal amplitude on each axis of the signals collected at each location. Step 6: Solve the objective function constructed in Step 5 to estimate the position of the target iron block and the components of the magnetic moment vector of the target iron block on each axis.

2. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 1, characterized in that, The relative coordinates between the rotating permanent magnet beacon and each magnetic sensor were measured using a total station.

3. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 2, characterized in that, The rotating permanent magnet beacon rotates at a constant angular velocity, specifically: the rotating permanent magnet beacon rotates at an angular frequency... Around a spatial rectangular coordinate system The frequency of the quasi-static magnetic field signal generated by the rotation of the axis for ; The spatial rectangular coordinate system has its origin at the geometric center of the rotating permanent magnet beacon. Taking any direction on the plane of revolution as axis, shaft and The axis is perpendicular, and The axis is located on the plane of rotation. The positive direction of the axis is perpendicular to the plane of revolution and points vertically upward. axis, shaft and The axes form a right-handed coordinate system.

4. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 3, characterized in that, The magnetic moment of the rotating permanent magnet beacon is calibrated based on the extracted minimum modulus of magnetic induction intensity. The specific process is as follows: Calibrate the magnetic moment of a rotating permanent magnet beacon using the least squares method: (4) Wherein, the modulus vector , They represent the 1st, 2nd, ..., 1st, 2nd, ..., 3rd. The minimum modulus of magnetic induction intensity corresponding to the magnetic sensor at each calibrated position. Let T be the magnetic permeability of air, and the superscript T represents the transpose of the matrix, and the superscript -1 represents the inverse of the matrix. The magnetic moment of the rotating permanent magnet beacon is represented by the relative distance vector. , They represent the 1st, 2nd, ..., 1st, 2nd, ..., 3rd. The distance from the magnetic sensor at each calibrated position to the rotating permanent magnet beacon. This indicates the total number of calibrated positions.

5. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 4, characterized in that, In step four, the true amplitude of the signal collected at each location on each axis is calculated based on the total magnetic induction intensity corresponding to the magnetic sensor at each location; the specific process is as follows: The magnetic flux density generated at each magnetic sensor by the rotating permanent magnet beacon is: (5) in, The initial phase of the time-varying magnetic moment of the rotating permanent magnet magnetic beacon. Indicates the rotating permanent magnet magnetic beacon in the first... The magnetic induction intensity generated at each magnetic sensor Indicates the rotating permanent magnet magnetic beacon and the first The relative coordinates between the magnetic sensors Indicates the rotating permanent magnet magnetic beacon and the first The distance between the magnetic sensors , Indicates time; Let the coordinates of the target iron block in the spatial rectangular coordinate system be denoted as . The components of the magnetic moment amplitude of the induced magnetic field of the target iron block on the three coordinate axes are: The initial phase of the target iron block has the following components on the three coordinate axes: ; in, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The amplitude of the magnetic moment of the induced magnetic field on the target iron block Axial components, The initial phase of the target iron block Axial components, The initial phase of the target iron block Axial components, The initial phase of the target iron block Axial components; Define intermediate variables intermediate variables intermediate variables Then the intermediate variable ,point Magnetic induction intensity generated by the target iron block at the location for: (6) The actual measured signal amplitude is: (8) (9) (10) in, Indicates the first Signals collected at each location The true value of the signal amplitude on the axis. Indicates the first Signals collected at each location The true value of the signal amplitude on the axis. Indicates the first Signals collected at each location The true value of the signal amplitude on the axis; That is, the first The signal amplitude of the signal collected at each location on each axis is related to... Functions: (11)。 6. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 5, characterized in that, The specific process of step five is as follows: The following system of nonlinear equations is established: (12) in, Represents a system of nonlinear equations, with state variables... ; The objective function is then: (13) in, It represents the 2-norm.

7. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 6, characterized in that, In step six, the objective function is solved using the differential evolution algorithm.

8. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 7, characterized in that, The specific process of step six is ​​as follows: Step 61: Let the population size in the solution space be... An initial population is randomly generated, and the dimension of each individual in the population is related to the state quantity. same; The random generation of the initial population is specifically as follows: (14) in, Indicates the first in the initial population individual The One portion, Indicates the first The lower bound of each component Indicates the first The upper bound of each component, It is a random number between 0 and 1. ; Step 62: Initialize the number of iterations ; Step 63, for individuals Perform a mutation operation to generate a new temporary mutated individual: (15) in, and From Two distinct individuals are randomly selected from the data. express The optimal individual in the process, To control the scaling factor of the parameter, express The corresponding temporary mutated individuals; Step Six Four: For Individuals and temporary mutant individuals Cross-recombination was performed to generate experimental individuals. ; Step 65: Based on the experimental individuals Individuals to be preserved for the next generation ; Step 66: Determine if the iteration stopping condition is met. If the iteration stopping condition is met, take the optimal solution obtained in the last iteration as the final solution result. If the iteration stopping condition is not met, then let... Return to step six three; The stopping condition for the iteration is: the fitness value of the optimal solution obtained in the current iteration is less than the preset error precision or the maximum number of iterations is reached.

9. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 8, characterized in that, The specific process of step six-four is as follows: (16) in, Indicates the first Each component corresponds to a random number. , Crossover probability factor , A dimension component is randomly assigned.

10. The differential evolutionary active underground detection method based on a rotating permanent magnet magnetic beacon according to claim 9, characterized in that, The specific process of step six-five is as follows: (17) in, Indicates the test individual fitness value, Represents an individual The fitness value.

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