125 results about "Magnetic gradient" patented technology

The invention relates to the technical field of magnetic separation, in particular to a magnetic gradient separation fire metal material evidence screening machine and a multistage magnetic field regulation and control method thereof.The magnetic gradient separation fire metal material evidence screening machine comprises a machine body, a feeding pipe and rotating cylinders are rotationally connected to an inner cavity of the machine body, magnetic separation assemblies are installed between the feeding pipe and the rotating cylinders and between the two rotating cylinders, and driven gears are installed on the outer walls of the feeding pipe and the rotating cylinders; according to the multi-stage magnetic separation device, the multi-stage magnetic separation design is adopted, magnetic force sequentially increased from top to bottom of the magnetic separation assembly is combined with centrifugal force generated by rotation of the feeding pipe and the rotating cylinders, and materials are evenly dispersed and make full contact with the magnetic separation assembly; meanwhile, the valve plate assemblies are sequentially opened in the descending process of the abutting blocks, so that the materials sequentially fall down layer by layer, sorting disorder caused by falling of a large number of materials at a time is avoided, the materials can be kept for enough time on each magnetic separation assembly, it is ensured that metal material evidences with different magnetisms are fully adsorbed, and the screening accuracy is greatly improved.

Provided is a magnetic moment measurement system and method, which belong to the technical field of magnetic moment measurement, and solve the problems of insufficient accuracy, low efficiency, and vulnerability to disturbance from an external magnetic field in the existing magnetic moment measurement technique. The magnetic moment measurement method includes the following steps: acquiring a magnetic field vector and a magnetic gradient tensor at a center of a magnetic sensor array through the magnetic sensor array; calculating an angle of a magnetic moment vector; and according to the angle of the magnetic moment vector, selecting a corresponding magnetic moment inversion formula, and calculating the magnetic moment vector. By constructing the magnetic sensor array, and using the advanced inversion algorithm, this application not only significantly improves the magnetic moment measurement accuracy, but also greatly shortens the measurement cycle, simplifies the measurement system, and reduces the measurement error.

The invention relates to the field of magnetic field measurement and sensor error compensation, and provides a magnetic gradient tensor array double-stage calibration method based on direction regularization, which comprises the following steps: acquiring magnetic vector observation data under multiple attitudes; constructing a twelve-parameter error model for explicitly distinguishing an internal error of the sensor from an array attitude error; based on the model, establishing an optimization objective function considering both module value consistency and direction consistency; a two-stage optimization strategy based on a differential evolution algorithm is adopted, in the first stage, all parameters are estimated to achieve coarse calibration, and in the second stage, estimated array attitude error parameters are optimized on the basis of internal error parameters of a fixed sensor; and finally, correcting a magnetic vector observation value according to the estimated calibration parameter, and calculating a magnetic gradient tensor through a symmetric difference method. Under the condition that no external magnetic field reference is needed, the measurement precision is improved by correcting the magnetic vector observation value, the accuracy of magnetic gradient tensor calculation is finally guaranteed, and the method has good engineering adaptability and popularization prospects.

The invention discloses a magnetic target boundary recognition method and system based on a magnetic gradient tensor, and relates to the technical field of geophysical exploration and industrial nondestructive testing, and the method comprises the following steps: collecting spatial magnetic gradient tensor data through a magnetic gradient sensor array, and obtaining nine components of the magnetic gradient tensor; calculating the vertical guide modulus of the vertical component of the magnetic gradient tensor; calculating a Z-direction analysis signal ASAz and a vertical guide thereof; a boundary recognition amount is generated by a ratio operation, and a boundary position of the magnetic target is determined based on a maximum value position of the boundary recognition amount. According to the method, a vertical component derivative and analytic signal derivative dual-derivative coupling mechanism is combined for the first time, the limitation that a traditional method depends on a single parameter is overcome, the vertical component derivative accurately captures the change rate of the boundary in the vertical direction, and the analytic signal derivative effectively suppresses background noise.

The invention belongs to the technical field of magnetic field measurement and instruments, and relates to a magnetic gradient tensor field interpolation method under physical potential field constraint, which comprises the steps of establishing a Gaussian process model of a magnetic gradient tensor field, acquiring a magnetic potential core and performing hyper-parameter optimization. According to the method, multi-component interpolation and curving are fused into a unified Gaussian process regression framework, and the multi-component interpolation and the curving are subjected to potential field physical constraints in a unified manner; a complete potential field physical constraint is used, meanwhile, no-rotation and no-divergence constraints are met, and magnetic gradient tensor measurement data interpolation with measurement errors is more accurate and better in anti-interference capability; by introducing a complete physical constraint fusion Gaussian process regression framework, the magnetic gradient tensor interpolation precision and stability are improved. Based on the magnetic potential core, all magnetic gradient tensor components can be modeled at the same time in the joint probability model, physical constraints among the components are guaranteed, non-planar data which are distributed at will can be processed naturally based on a Gaussian process regression framework, and an additional potential field continuation step is not needed.

The invention discloses a slope monitoring method and system based on an unmanned aerial vehicle, and relates to the technical field of intelligent geological disaster monitoring, and the method comprises the steps: carrying a magnetic gradient measurement unit and a laser radar through the unmanned aerial vehicle, and collecting magnetic gradient tensor collection and slope surface point cloud from multiple heights and multiple routes; on the basis of a gradient adaptive weighted total variation inversion method, slope gradient information extracted by a digital elevation model is introduced into regularization weight adjustment, so that an inversion result can be adaptively adjusted in different gradient areas; based on a magnetic susceptibility distribution model, a magnetic construction adaptive clustering and risk index calculation method is used, and through amplitude density index and gradient constraint search, clustering identification and risk quantitative partitioning of a high-gradient accumulation area are carried out. Therefore, expansion from surface slope deformation monitoring to deep concealed structure detection is realized, and concealed slip zones or fissure zones can be accurately revealed under complex terrain conditions.

The invention belongs to the technical field of magnetic field detection, and discloses a cross-shaped variable baseline magnetic flux gate array and method for measuring a three-order magnetic gradient tensor. The cross-shaped variable baseline magnetic flux gate array comprises a cross-shaped array rack, each supporting arm is provided with a sliding groove with the length of 1, and a sensor is installed on each sliding groove in a clamped mode. A sensor is mounted at the central point of the cross array rack; the baseline distances d between the adjacent sensors are equal, and the sensors slide in the corresponding sliding grooves. According to the adjusting method, the baseline distance is adjusted through the sliding groove. According to the rotation correction method, the surrounding sensors are corrected through the middle sensor, the measurement precision is improved, the zero-order magnetic gradient tensor and the first-order magnetic gradient tensor at the position of each sensor and the second-order magnetic gradient tensor and the third-order magnetic gradient tensor at the position of the center sensor can be measured at the same time, rich target magnetic field information is obtained, and the measurement accuracy is improved. The engineering practical value is realized.

The invention discloses a ferromagnetic material defect identification method and system based on magnetic gradient tensor measurement, and relates to the technical field of nondestructive testing, and the method comprises the following steps: acquiring magnetic gradient tensor data of a to-be-tested piece; calculating a total horizontal derivative based on the magnetic gradient tensor data; calculating a z-direction partial derivative of each component based on the total horizontal derivative and calculating a vertical derivative based on the magnetic gradient tensor data; and identifying a defect boundary by using the magnetic gradient tensor fusion derivative detector and the magnetic gradient tensor anti-noise boundary detector, and outputting a defect profile diagram. According to the invention, the MGTFDED and MGTNRED detectors specially designed for industrial defect detection scenes are provided for the first time, and the problem that a geophysical method is not suitable for direct transplantation is solved. According to the method, the edges of various defects from surface cracks to deep buried holes and the like can be identified with high precision, and the accuracy, noise resistance and intelligent level of detection are remarkably improved.

The invention relates to a single-vector magnetometer motion direction magnetic gradient anomaly detection method, which comprises the following steps: based on a single-sensor magnetic gradient measurement technology, obtaining an x-axis motion direction magnetic gradient signal through spatial sampling; preprocessing the magnetic gradient signal in the x-axis motion direction; presetting an orthogonal basis function of the magnetic gradient in the x-axis motion direction; and carrying out magnetic gradient anomaly detection on the preprocessed signal based on a preset orthogonal basis function. The method is superior to a traditional vertical motion directional array double-sensor column magnetic gradient anomaly OBF detection method under the conditions of low noise ratio and platform shaking, has the advantages of being high in real-time performance, low in cost, small in size and the like, and shows a good application prospect under the scenes of danger detection, explosion removal, intrusion monitoring and the like.

The invention provides a movement control device, and the device comprises a plurality of magnet groups which are fixed at a first side edge of a movable workbench and are arranged in a non-collinear manner, and each magnet group comprises a pair of magnets with opposite polarities, so as to form a gradient magnetic field region; the Hall sensors are fixed to the second side edge of the main substrate, the second side edge of the main substrate is opposite to the first side edge of the movable workbench, and the induction face of each Hall sensor is parallel to the magnetic gradient face of the corresponding magnet set in the magnet sets; and the controller is used for receiving sensing data of the plurality of Hall sensors to form a real-time data matrix and controlling the movable workbench to move to a zero position according to the real-time data matrix. Through the technical scheme, the movable workbench can accurately move to the zero position, the manufacturing cost is reduced, and meanwhile the structure is simplified.

The application discloses a kind of ocean stereo magnetic survey system and method based on unmanned platform, belong to marine detection equipment technical field, including water surface magnetic transverse gradient measurement subsystem, underwater magnetic total field measurement subsystem, ground magnetic diurnal variation observation station and data synchronization and compensation processing center.Processing center, built-in improved 18 items Tolles-Lawson magnetic interference compensation model, real-time solution and eliminate platform constant field, induction field and eddy current field interference.The application is realized through the cooperation of combined navigation and automatic roll reduction device, attitude depth adjustment mechanism, water surface / underwater platform high-precision attitude positioning and attitude keeping;After diurnal variation correction, attitude correction and position calculation, water surface transverse magnetic gradient and vertical magnetic gradient are solved, and water surface-underwater stereo magnetic survey cooperative operation and high dynamic platform magnetic interference real-time compensation are realized, which significantly improves the precision, efficiency and spatial resolution of marine magnetic anomaly detection.

The invention belongs to the technical field of degaussing, and relates to a ship winding degaussing current solving method based on a gradient tensor, which comprises the following steps: acquiring the magnetic gradient tensor of a plane ship when coils are not electrified; respectively performing simulation electrification on the winding coils to obtain the magnetic gradient tensor of the electrified measurement plane; and calculating an efficiency matrix of the magnetic gradient tensor excited by the unit current. The gradient of the geomagnetic field is extremely small, direct detection of the magnetic gradient tensor of the ship and the electrified coil can better reflect the magnetic characteristics of the ship and the coil compared with detection of a magnetic vector, and better resolution is achieved for magnetic field changes caused by magnetic anomalies; under the motion platform, the magnetic gradient tensor is insensitive to the attitude angle error, and more accurate detection data can be obtained; in addition, the gradient tensor is weak in response to time-varying geomagnetic disturbance, and has higher anti-interference capability. Therefore, according to the method, the accuracy of ship magnetic field modeling and degaussing current calculation is improved, and the magnetic stealth performance of a ship facing high-sensitivity magnetic gradient detection equipment is enhanced.

The utility model relates to an unmanned aerial vehicle for underground electromagnetic anomaly detection, and belongs to the technical field of unmanned aerial vehicle detection. Comprising an unmanned aerial vehicle body; the magnetic gradient detection device is carried on the unmanned aerial vehicle body; the magnetic gradient detection device comprises a telescopic supporting arm, a posture switching mechanism and at least two magnetic sensing units. The at least two magnetic sensing units are arranged at intervals in the axial direction of the telescopic supporting arm; the posture switching mechanism is connected with the unmanned aerial vehicle body and the telescopic supporting arm and used for driving the telescopic supporting arm to be switched between the horizontal storage position and the vertical working position. The vertical distance between the at least two magnetic sensing units is obviously increased in the vertical direction, and the requirement of geomagnetic vertical gradient measurement for the length of a sensor base line is met.

The invention discloses an unmanned aerial vehicle magnetic gradient data soft compensation method and system based on semi-supervised learning, and relates to the technical field of aviation geophysical exploration, and the method comprises the steps: designing an octagonal calibration flight scheme, enabling an unmanned aerial vehicle to execute a single maneuvering action in each route, and obtaining the response data of an interference magnetic field to the flight attitude change; actually measuring the high-altitude compensation flight data and the low-altitude survey line flight data based on the high-altitude compensation flight data and the low-altitude survey line flight data in the response data of the interference magnetic field to the flight attitude change, establishing a simulation dynamic measurement noise data set through a forward modeling formula, and dividing the simulation dynamic measurement noise data set into a training set, a verification set and a test set; through an improved octagonal calibration flight scheme and in combination with a Transform-based semi-supervised learning residual error compensation method, the soft compensation precision and efficiency are improved.

The invention discloses a geomagnetic gradient tensor depth representation learning method and system, and belongs to the technical field of information processing, and the method comprises the steps: obtaining a geomagnetic three-component data matrix of a magnetic object, and building an original gradient tensor data set; generating a gradient matrix based on the original gradient tensor data set, and performing orthogonal decomposition on the gradient matrix to obtain mutually independent rotation isovariant features and direction sensitive features; inputting the rotation isovariant features and the direction sensitive features into a rotation isovariant convolutional neural network for feature extraction; constructing a geometric constraint loss function including an angle constraint loss function and a direction constraint loss function, and optimizing the training network; the geomagnetic gradient tensor data is subjected to deep representation based on the trained network, the innovative gradient matrix orthogonal decomposition technology solves the problem that rotation invariance and direction sensitivity are difficult to consider at the same time, the feature representation accuracy is improved by about 30-40%, the processing speed is improved by 2-3 times, and the anti-interference capability is remarkably enhanced.

The invention provides a black box magnetic induction searching device and method.The black box magnetic induction searching device comprises an MCU main control circuit, a data acquisition front-end processing circuit and a magnetic gradient sensor, the magnetic gradient sensor comprises two magnetic probes used for detecting the magnetic field intensity of different positions, and the two magnetic probes form a magnetic gradient difference; the magnetic gradient sensor is connected with the input end of the data acquisition front-end processing circuit, the output end of the data acquisition front-end processing circuit is connected with the MCU main control circuit, and the data acquisition front-end processing circuit is used for converting an acquired analog magnetic signal into a digital signal and then sending the digital signal to the MCU main control circuit for analysis and processing. And the MCU main control circuit matches the acquired magnetic field intensity data with a preset magnetic field intensity threshold value, and determines the position of the black box according to a matching result. According to the invention, accurate positioning and searching of the black box at the depth of 0.5 m from the ground are realized, the problem that the black box cannot be searched and positioned when an airplane crashes on the land is solved, and rapid and effective searching of the black box on the land is realized.

The invention discloses an electromagnetic anomaly detection method based on tensor shrinkage and orthogonal basis function decomposition, and belongs to the technical field of magnetic detection and correction, and the method comprises the steps: enabling a metal target to be equivalent to a magnetic dipole, and building an AC radiation field model; then, deducing a magnetic gradient tensor of a metal target scattered field; next, taking the square of the reduced tensor of the scattering field as a detection quantity, and calculating a primary function of mutual orthogonality of the detection quantity; and finally, establishing an energy function to complete electromagnetic anomaly detection of the metal target. According to the invention, the non-ferromagnetic metal target in the space can be effectively detected based on the electromagnetic emission source, the signal-to-noise ratio of electromagnetic anomaly detection is improved, and the method is of great significance to detection of metal anomalous objects in anti-submarine, anti-mine, anti-landmine and other scenes.

This invention discloses a method and kit for detecting microbial SERS based on superhydrophobic evaporation concentration and magnetically guided enrichment, belonging to the field of in vitro diagnostics and analytical chemistry. The method includes: mixing and incubating the sample to be tested with a magnetic SERS probe modified with targeted recognition molecules to form a complex; adding the mixed droplet to a superhydrophobic surface for evaporation concentration; applying a magnetic field below the detection site during droplet evaporation, using the magnetic gradient force to directionally enrich and pin the complex to the detection site, resulting in a dense solid enrichment spot in situ after drying, creating nanoscale gaps between the metal layers of adjacent probes and exciting SERS hotspots; irradiating the spot with a laser and acquiring the SERS signal to achieve microbial detection. This invention also provides a kit for implementing this method, including a magnetic SERS probe, a superhydrophobic detection card, and a positioning base with an embedded magnet. This invention eliminates the dependence on traditional solid-phase SERS substrates, overcomes the defect of easy droplet rolling on superhydrophobic surfaces through magnetic pinning, achieves self-alignment and high-sensitivity detection, and has advantages such as strong anti-interference, low cost, and ease of automation.

The embodiment of the invention discloses a data compensation method and device, equipment and a storage medium, and the method comprises the steps: building a target interference compensation model of a pod platform for a towed superconducting full-tensor magnetic gradient measurement system, the target interference compensation model comprising an SQUID magnetic gradiometer measurement item, an interference compensation item and a sensor self-interference correction item; wherein the interference compensation item excludes a residual magnetism interference item of the pod platform, and the interference compensation item comprises a magnetic induction interference item represented by a first-order derivative of an earth magnetic field component and an eddy current interference item represented by a second-order derivative of the earth magnetic field component; the self-interference correction item of the sensor is used for representing the self unbalance degree and unknown offset of the SQUID magnetic gradiometer; constructing a target function based on the target interference compensation model; inputting the measured value of the SQUID magnetic gradiometer and the measured value of the SQUID magnetometer into a target function, and solving by adopting a symmetric super-relaxation iteration method to obtain a compensation coefficient; and compensating the towed superconducting full-tensor magnetic gradient measurement system based on the compensation coefficient.

The invention belongs to the technical field of water supply and drainage safety, and particularly relates to a method for recognizing interference signals of ferromagnetic objects around a water supply and drainage pipeline. Comprising the following steps: S1, collecting related data of on-site water supply and drainage pipelines; s2, carrying out interference-free magnetic signal collection on related pipelines; s3, magnetic signal collection is carried out on related pipelines when interference exists; s4, comparing and analyzing the magnetic signal data of the pipeline without interference and the magnetic gradient component signal characteristics of the pipeline in the X, Y and Z directions under the interference signal of the ferromagnetic interferent; s5, judging whether ferromagnetic substance interference exists or not according to the component change condition; and S6, finding out unknown pipeline interference data for verification, and analyzing whether the periphery of the pipeline is interfered by ferromagnetic substances or not by observing component change characteristics. The method has the beneficial effects that the position of an interference signal can be accurately identified, the influence of the interference signal on a pipeline detection signal is eliminated, the health state of the pipeline can be accurately judged, and unnecessary maintenance and intervention can be avoided, so that the maintenance cost is reduced.

According to the method, a target function of three-direction equivalent zero offset and real number deflection matrixes of the strapdown three-axis magnetometer is constructed, an overdetermined equation set related to the Euler angle of the strapdown three-axis magnetometer is constructed, the solving problem of the target function and the overdetermined equation set is converted into a constraint optimization problem, a sequential quadratic programming algorithm is adopted for solving, a telescopic factor is introduced, and the Euler angle of the strapdown three-axis magnetometer is obtained. And calculating a correction value of the magnetic gradient tensor measured by the strapdown three-axis cross magnetic array, and completing self-calibration of the strapdown three-axis cross magnetic array under the condition that the reference magnetic field is unknown. According to the method, all parameters of the strapdown three-axis cross magnetic array measurement model can be automatically and accurately calibrated under the condition that a reference magnetic field vector model is not provided, a calibration link of alignment errors does not exist, and a high-precision three-axis magnetometer or a scalar magnetometer does not need to be used for measuring the reference magnetic field vector model in the calibration process. The method does not have an iterative process and mathematical approximation, so that an iterative calculation initial value does not need to be provided, and the calibration algorithm is rapid and high in precision.

The application discloses a non-magnetic Dewar for aviation and relates to the technical field of aviation full-tensor magnetic gradient measurement. The non-magnetic Dewar comprises a straight-cylinder-shaped shell and an inner container arranged in the shell; a vacuum interlayer is formed between the shell and the inner container; a vacuum-pumping valve is arranged on the top of the shell and communicates with the vacuum interlayer; a glue-rich layer is arranged on the inner wall of the vacuum interlayer; the shell and the inner container are made of epoxy glass steel material; and the glue-rich layer is made of a mixed material of resin and low permeability. The non-magnetic Dewar is made of epoxy glass steel non-magnetic material, has the advantages of non-magnetic interference, high heat preservation, automatic liquid level maintenance and the like, can significantly reduce the volatilization rate of liquid nitrogen, and can fully meet the demand of uninterrupted area flight measurement operation of a high-temperature superconducting full-tensor magnetic gradient sensor system carried by a helicopter in the field on the premise that liquid nitrogen is supplemented once a day.

The present invention discloses an unmanned vessel gravity and magnetic measurement method and system, belonging to the field of geophysical exploration technology. The method comprises acquiring real-time attitude data of the unmanned vessel to generate tilt compensation parameters; adjusting the data acquisition frequency based on the tilt compensation parameters to generate a positioning enhancement signal; triggering the acquisition of operational data based on the positioning enhancement signal to generate raw gravity data and raw magnetic data; extracting magnetic field gradient mutation points in the raw magnetic data to generate wave characteristic parameters; fusing the tilt compensation parameters, wave characteristic parameters, and raw gravity data to generate wave noise compensation values; and correcting the wave noise compensation values ​​to generate target gravity field data. The method utilizes three core technical systems: dynamic tilt closed-loop compensation, magnetic gradient-wave characteristic mapping modeling, and precise time alignment triggering. These systems can effectively overcome the interference effects of wave noise on the gravity field and achieve a significant improvement in the spatiotemporal synchronization of gravity and magnetic measurements.

The invention belongs to the technical field of magnetic field detection, and discloses a three-shaped fluxgate parallel matrix array for measuring the flight speed of a target and a method of the three-shaped fluxgate parallel matrix array. The three-shaped fluxgate parallel matrix array comprises three parallel mounting racks, and a plurality of sensors are respectively clamped on each mounting rack through sliding chutes; a probe of each sensor vertically faces a target; the three-shaped fluxgate parallel matrix array can be expanded along the line, and the baseline distance can be adjusted; the measurement method comprises the following steps: measuring a magnetic induction intensity vector matrix; measuring a second-order magnetic gradient tensor matrix; calculating normalized magnetic source intensity; and calculating the average speed of the target. The method is simple, a second-order magnetic gradient tensor matrix is sequentially calculated through observation points along a middle column sensor, the normalized magnetic source intensity at each observation point is calculated according to the second-order magnetic gradient tensor matrix, and compared with traditional speed measurement methods such as photoelectric detection and radar detection, the method is not influenced by a plasma sheath around a high-speed target and is not influenced by shielding of media such as fire light and smoke. The engineering practical value is realized.

This invention relates to a method for correcting system errors in a full-tensor magnetic gradient system based on position information, comprising the following steps: acquiring full-tensor magnetic gradient measurement data obtained by a full-tensor magnetic gradient measuring device from the detection of a target magnetic source at different relative positions, and magnetic source reference position data obtained by a position sensor; establishing a magnetic source position model including installation error parameters based on a full-tensor invariant magnetic target localization algorithm; inputting the full-tensor magnetic gradient measurement data into the magnetic source position model, and solving for the installation error parameter value that minimizes the error between the magnetic source position model and the corresponding magnetic source reference position data; and using the installation error parameter value to correct the system error of the full-tensor magnetic gradient measuring device. This method enables high-precision correction of the full-tensor magnetic gradient system, with low hardware cost and a simple and easy-to-implement calibration process.

The application provides a static positioning method and positioning device of a magnetic target, comprising: obtaining full tensor magnetic gradient data of a moving magnetic target at n measuring positions within a preset time period based on a static magnetic target positioning device; selecting one of the measuring positions as an initial position of the magnetic target, obtaining each measuring position of the magnetic target based on the initial position and full tensor invariant, and fitting according to the motion trajectory characteristics of the magnetic target to obtain a minimum mean square error after fitting; changing the initial position of the magnetic target and performing the above step cyclically; taking the initial position with the optimal minimum mean square error after fitting as a final solution, obtaining the position information of the magnetic target based on the full tensor invariant and the final solution of the initial position, and realizing the positioning of the magnetic target. The application realizes the positioning of the magnetic target based on the full tensor invariant and the motion trajectory constraint, can simply and quickly realize the positioning of the fixed magnetic moment magnetic source through a set of measuring processes and experimental data post-processing, and has high positioning precision and low cost.

This application discloses an autonomously controlled low-temperature superconducting magnetic gradient readout system and parameter setting method, belonging to the field of geophysical exploration. Before magnetic gradient measurement, the method autonomously sets the SQUID to the optimal operating point based on an adaptive successive optimization algorithm. During measurement, a differential mutation detection algorithm is used to determine in real time whether the system has lost lock and autonomously resets it. If continuous loss of lock occurs, the method autonomously selects the parameter combination of the integrating capacitor and feedback resistor to reduce system sensitivity and relock the measurement. This application solves the problems of tediousness, time consumption, and insufficient accuracy in manually adjusting the optimal operating point of multi-channel readout systems. Simultaneously, by autonomously reducing system sensitivity, it solves the problem of continuous system loss of lock caused by bumps or large magnetic field change rates during dynamic measurements on mobile platforms such as vehicle-mounted, marine, and aerial vehicles. This enables autonomously controlled magnetic gradient measurement under unattended conditions, improving work efficiency and the reliability of magnetic gradient measurement.

The invention relates to the technical field of superconducting weak magnetic detection, and particularly provides an SQUID magnetic gradient tensor probe structure based on a planar cross layout and a measurement system, the SQUID magnetic gradient tensor probe structure comprises a first differential SQUID sensor group and a second differential SQUID sensor group which are arranged in a cross shape, each sensor group comprises a plurality of three-axis SQUID sensors which are symmetrically arranged along an X axis and a Y axis, according to the invention, all independent components of the magnetic gradient tensor can be measured only by using four three-axis SQUID sensors, and compared with a traditional multi-sensor (such as a six-prismatic table structure or an eight-sensor structure) probe, the number of the SQUID sensors and the use amount of liquid helium are obviously reduced, the manufacturing and operation cost of the system is effectively reduced, and the system is suitable for large-scale popularization and application. And meanwhile, the number of each group of sensors can be further adjusted according to a measurement scene, so that the robustness and the sensitivity of gradient tensor precision are improved.

The invention discloses a UUV inertial navigation-electromagnetic fusion positioning method and system based on a magnetic gradient tensor, and relates to the field of underwater navigation positioning, and the method comprises the steps: obtaining an electromagnetic beacon magnetic field signal, a UUV angular velocity signal and a linear acceleration signal, and carrying out the preprocessing; calculating an independent component of the magnetic gradient tensor by adopting a spatial difference method; calculating the motion state of the inertial navigation system to obtain the position, the speed, the attitude and the IMU error of the UUV; based on the magnetic dipole equivalent model, establishing a tight coupling fusion model of the magnetic gradient tensor and the motion state of the inertial navigation system; and performing state estimation on the tight coupling fusion model by using an unscented Kalman filtering algorithm, correcting the state of the inertial navigation system by using an independent component of a magnetic gradient tensor as an observed value, and outputting a fusion positioning result of the UUV. And the inertial navigation-electromagnetic fusion positioning performance is comprehensively improved.

The application discloses a geomagnetic gradient tensor deep characterization learning method and system, and belongs to the technical field of information processing. The method comprises the following steps: acquiring a geomagnetic three-component data matrix of a magnetic object and establishing an original gradient tensor data set; generating a gradient matrix based on the original gradient tensor data set, orthogonally decomposing the gradient matrix, and obtaining mutually independent rotation invariance features and direction sensitive features; inputting the rotation invariance features and the direction sensitive features into a rotation invariance convolutional neural network for feature extraction; constructing a geometric constraint loss function comprising an angle constraint loss function and a direction constraint loss function, and optimizing a training network; and performing deep characterization on geomagnetic gradient tensor data based on the trained network. The innovative gradient matrix orthogonal decomposition technology solves the problem that rotation invariance and direction sensitivity cannot be considered simultaneously, the feature characterization accuracy is improved by about 30-40%, the processing speed is improved by 2-3 times, and the anti-interference capability is significantly enhanced.