3941results about "Electric/magnetic detection" patented technology

The present application relates to PPP-RTK, RTK, SSR, or like correction data based devices and methods to produce geolocation solutions with improved accuracy. Further, such devices and methods may be further employed in various related utility locator devices, utility locating transmitters, and other utility locating and mapping devices.

The invention discloses a multi-source collaborative advanced geological exploration method based on TBM construction, and belongs to the technical field of tunnel engineering geological exploration. A three-dimensional geological model is constructed through multi-scale collaborative operation of directional long exploration drilling, branch short exploration drilling and in-hole transient electromagnetic detection; the directional long exploration adopts a secondary drilling structure and a screw motor directional drilling technology to realize accurate control of a deep stratum, the branch short exploration realizes dynamic and rapid verification through a TBM integrated drilling machine, meanwhile, in-hole transient electromagnetic exploration adopts three-component measurement and an intelligent inversion algorithm to fill the blank of geological information between drill holes, and by means of mutual data correction of the three methods, the detection accuracy is improved. A three-in-one detection system of drilling, geophysical prospecting and intelligent analysis is formed, and then accurate advanced prediction is achieved, so that the problems that a traditional single detection technology is low in precision and insufficient in coverage range are effectively solved, the water inrush risk is remarkably reduced, construction safety is guaranteed, and the method is effectively suitable for deep tunnel TBM safety construction.

The invention discloses a dam termite cave positioning method based on transient electromagnetism carried by an unmanned aerial vehicle. The method comprises the following steps: constructing an unmanned aerial vehicle transient electromagnetic detection system; preprocessing the received secondary induction electromagnetic field signal, and obtaining a comprehensive electromagnetic signal according to the response difference of the multi-frequency signal; inputting the integrated electromagnetic signals into a pre-trained deep learning neural network model, identifying characteristic signals related to termite acupoints in the integrated electromagnetic signals, and outputting position coordinates of suspected termite acupoints; a dam surface thermal imaging image obtained by a thermal imaging module is combined for secondary verification, and termite cave position information is transmitted to a ground control terminal in real time through a communication module carried by the unmanned aerial vehicle. According to the invention, efficient, accurate and lossless positioning of the termite cave of the dam is realized, underground electromagnetic signals and surface heat distribution information of the dam are rapidly obtained, and accurate termite cave position coordinates are output.

Utility locators for providing information about hidden or buried pipes or other cavities are disclosed. A locator may be configured to provide positional information associated with the buried utility based on signals received from a line trace signal and a sonde signal and present the positional information on a visual display or other output device.

The invention discloses an electromagnetic detection data efficient three-dimensional inversion method based on operator learning, and belongs to the technical field of geophysical inversion, and the method comprises the steps: constructing an operator learning data set which comprises a plurality of electromagnetic forward modeling models and forward modeling responses of the electromagnetic forward modeling models; performing aviation electromagnetic frequency domain forward calculation training based on the operator learning data set by using a DeepONet network to obtain a trained aviation electromagnetic three-dimensional forward operator; inputting the initial uniform half-space model, replacing a generator with an aviation electromagnetic three-dimensional positive operator, and constructing a WGAN network by taking a KAN network as a discriminator to carry out aviation electromagnetic three-dimensional inversion; training is carried out based on the loss function and the data fitting difference convergence condition to update the KAN network and the uniform half-space model, and finally the updated uniform half-space model is obtained to serve as an inversion result. According to the method, more efficient and accurate three-dimensional aviation electromagnetic inversion can be realized, and the method is more suitable for geophysical inversion application under complex data distribution.

The invention discloses a magnetotelluric signal noise suppression method and system based on complexity driving, and the method comprises the steps: firstly calculating the complexity feature CS of a signal segment, and then constructing and training a noise reduction model based on a multi-path attention residual denoising network, the network is formed by connecting a plurality of feature recovery modules with heterogeneous structures in parallel to form different main branches, different main branches are respectively provided with a shallow convolution module CBL, a channel structure modeling module MACNet and a global attention modeling module DHVT, each main branch is provided with a complexity sensing gating unit taking a complexity feature CS as input, and an output signal of the complexity sensing gating unit is input into a feature recovery module of the main branch in cooperation with a noisy signal segment; the path scheduling mechanism guides whether the feature recovery module of the main branch participates in data processing or not for an output result of the complexity sensing gating unit on each main branch; and finally, performing noise reduction on the actually measured magnetotelluric signal by using the trained multi-path attention residual denoising network.

The present disclosure provides techniques for obtaining a domain-specific model targeted for a downstream task. A method may include obtaining a plurality of unlabeled geospatially-indexed datasets from different geographic locations representing different subsurface geologic conditions; training a neural network model on the plurality of unlabeled geospatially-indexed datasets in a self-supervised manner to obtain a foundation model that develops generalizable representations capturing shared interrelationships across the different subsurface geologic conditions; obtaining a labeled geospatially-indexed training dataset specific to a designated survey area; adapting parameters of the foundation model through retraining using the labeled geospatially-indexed training dataset to develop a domain-specific model targeted for a prediction task in the designated survey area; and implementing the domain-specific model on new geospatially-indexed input data from the designated survey area to generate predictions tied to locations for the targeted prediction task.

The invention discloses a self-adaptive octree three-dimensional magnetic method inversion method fused with abnormal region recognition, and belongs to the technical field of three-dimensional magnetic method data inversion processing. Comprising the steps that initial inversion is rapidly completed on a coarse grid, the overall contour of an underground structure is obtained, a fuzzy c-means clustering algorithm is introduced, and a target area with significant magnetic anomaly is automatically extracted from a coarse solution; and constructing a multi-level octree grid in the extracted abnormal region to realize fine subdivision of the complex geological boundary, and further executing high-precision inversion by using a fine model as a new starting point. The adaptive octree grid has the characteristics of high efficiency, small grid number and small data fitting difference. The process of coarse inversion, intelligent identification, local refinement and fine inversion can be circularly executed as required, and computing resources are dynamically allocated. Compared with a traditional global fine grid scheme, the inversion process has the advantages that the inversion precision is maintained and even improved, and meanwhile, the number of grid units is remarkably reduced.

The invention discloses an unmanned aerial vehicle detection method based on multi-band radio spectrum analysis, and the method can recognize the flight control behaviors of a target, such as hovering, cruising or hovering, through the extraction of a signal track and the introduction of a behavior modeling mechanism, and effectively overcomes the defect that the prior art lacks the dynamic behavior analysis capability. A multi-node synchronization mechanism and a TDOA positioning method are combined, so that high-precision traceability of a target space position is realized; meanwhile, risk level assessment is carried out based on signal features, a track mode and a space region, so that the system has intelligent early warning capability. According to the whole scheme, a full-link unmanned aerial vehicle detection method from multi-frequency receiving, frequency spectrum identification, behavior judgment, target positioning to risk output is constructed, and the problems of single frequency band, rough identification means, lack of tracking and evaluation capability and the like in the prior art are effectively solved; and the practicability and the accuracy of the unmanned aerial vehicle detection system in a complex airspace environment are remarkably improved.

Apparatus, systems, and methods for mapping utility lines in utility potholing operations are disclosed. Pothole mapping apparatuses, systems, and methods may be employed in utility locator devices and utility locating systems to map potholed utility lines. Data generated via pothole mapping may be used to calibrate utility depth measurements in utility locator devices and systems. Further, information revealed about utility lines during potholing procedures may be used to train neural networks and utilize artificial intelligence in generating predictions regarding the positions and characteristics of utility lines.

The invention relates to the technical field of geophysical exploration, in particular to a multichannel deep learning magnetotelluric inversion method based on physical information constraint. The method comprises the following steps: generating a synthetic data set containing a geoelectric model and forward modeling response thereof, and adding a noise simulation actual observation condition; constructing a hybrid network architecture combining Transform and U-Net, taking apparent resistivity and impedance phase as dual-channel input, extracting global features by using an encoder, gradually recovering spatial resolution through a decoder, and outputting an underground resistivity model; network training adopts a composite loss function fusing model loss and data loss, and an inversion process is constrained by introducing a magnetotelluric forward modeling physical rule, so that a result is ensured to fit observation data and conform to a physical mechanism; after training is completed, preprocessed actual measurement data are input into the model, and a resistivity image can be directly obtained. The method is used for geological structure identification and reservoir interpretation, and the inversion precision and reliability are effectively improved.

An integrated ice detector and ice protection system is provided. The integrated ice detector and ice protection system includes an electric resistance heater element layer, a sensing element, and at least one second electrically insulative layer positioned between the electric resistance heater element layer and the at least one first electrically insulative layer with the sensing element. The sensing element is disposed in at least one first electrically insulative layer and wherein the sensing element is positioned outward from the electric resistance heater element layer.

The invention relates to the technical field of geophysics, and particularly discloses a comprehensive inversion method and system based on bidirectional magnetic susceptibility weighted constraint, and the method comprises the steps: dividing an underground three-dimensional space, and building two different cuboid models; determining a total magnetic field observed on the ground and gradient anomaly thereof based on the observation point coordinates and the cuboid model position, and establishing a kernel function matrix; determining an inversion objective function reflecting the relationship between the total magnetic field and the gradient anomaly thereof and the physical property parameters; adding the bidirectional magnetic susceptibility weighted constraint function into an inversion objective function; the optimal solution of the comprehensive inversion target function is solved based on the conjugate gradient method, the high-level resolution capability of the magnetic gradient data and the deep detection advantage of the total magnetic field data are fused, the precision of fine depiction of the superficial anomalous body boundary and the reconstruction precision of the deep field source structure are remarkably improved, a vector cross multiplication regularization constraint mechanism is introduced, and the method has the advantages of high resolution and high resolution. The inversion multiplicity under the complex geological condition is greatly inhibited, and the reliability of the model result and the geological rationality are enhanced.

The invention relates to the technical field of wireless charging, and provides a foreign matter detection method and system for a wireless charging system and a storage medium. The method comprises the following steps: firstly, calibrating at multiple temperature points and establishing a temperature-parameter comparison table under the condition of no foreign matters; in a no-load standby state, the inversion module sends out detection drive and collects voltage, current and temperature; calculating a real-time quality factor and resonant frequency according to sampling, obtaining a compensation reference according to a temperature look-up table, and solving the variation of the quality factor and the resonant frequency; and performing fusion judgment by adopting dual-condition locking or weighted scoring, and triggering fault protection when a foreign matter is confirmed. Due to the fact that equivalent inductance and resistance changes are caused by metal foreign matters, quality factors are remarkably reduced along with resonant frequency deviation, temperature excursion and foreign matter effects are distinguished through temperature compensation, and dual-condition locking or weighted scoring fusion judgment is combined, the interference immunity and accuracy of detection are improved, false alarms and missing alarms are remarkably reduced, and the detection accuracy is improved. The method is suitable for high-power wireless charging scenes.

The invention belongs to the technical field of large-depth ground-to-air electromagnetic detection, and particularly relates to a light-weight high-power ground-to-air electromagnetic detection power supply system and method and a high-power vehicle-mounted power supply. Two paths of lithium battery units connected in parallel are adopted to provide short-time high-power emission current for a transmitter; the controller is used for acquiring a detection task set by the transmitter and setting a reference voltage according to the detection task; the voltage acquisition module is used for acquiring a direct-current bus voltage and comparing the direct-current bus voltage with a reference voltage to obtain a current modulation signal; and the controller is also used for acquiring the output current of each path of lithium battery unit and outputting a control signal according to the current modulation signal to compensate the output current of each path of lithium battery unit. According to the invention, the stability of a power supply system is realized when different instantaneous high-power outputs in a detection task in a high-power ground-air electromagnetic detection system are realized. When the output voltage and the sudden increase or decrease of the load current are adjusted as required, the stable output of the power supply voltage is realized.

The present disclosure provides various systems and methods for magnetic resonance imaging. In one aspect, a method for magnetic resonance imaging can include receiving k-space data sets acquired by radiofrequency (RF) coils. Each of the k-space data sets can correspond to a different one of the RF coils. Each of the k-space data sets can be truncated and / or under sampled. The method can further include generating partial images of a field of view based on the k-space data sets and generating an initial image based on the partial images. The initial image can be full image of the field of view. The method can further include applying an iterative image reconstruction technique to generate an updated image based on the initial image.

The invention discloses an ocean induced polarization and natural potential combined acquisition device and a data processing method, and solves the technical problem that the sulfide ore form cannot be accurately represented in the prior art. The system comprises a first underwater autonomous robot and a second underwater autonomous robot, the first underwater autonomous robot is provided with an induced polarization emission device, and the second underwater autonomous robot is provided with a natural potential acquisition device; the induced polarization emission device comprises an induced polarization control bin, a first watertight cable, an emission end positive pole and an emission end negative pole, and the natural potential acquisition equipment comprises a natural potential acquisition bin, a second watertight cable and a plurality of pairs of Ag / AgCl non-polarized electrodes. According to the method, the distribution characteristics of submarine sulfides can be more accurately explained, the multiplicity of solutions is reduced, and the exploration accuracy and reliability are improved.

The invention discloses a DeepLabV < 3 + >-based magnetotelluric two-dimensional inversion method, and belongs to the field of geophysical inversion methods, and the method comprises the steps: constructing a plurality of underground resistivity distribution models, and obtaining corresponding apparent resistivity and phase data through forward modeling calculation; designing a deep learning network based on a DeepLabV < 3 + > architecture, and enhancing the capability of capturing multi-scale geological features by using a cavity convolution and improved cavity spatial pyramid pooling (ASPP) module of the deep learning network; di ce Loss is adopted to replace a traditional cross entropy loss function, and the method is more suitable for the characteristics of anomaly and background information imbalance in geophysical observation data; according to the method, the network is trained and verified through the training sample set, and the optimal network parameters are obtained; the trained network is utilized to directly map the apparent resistivity and phase data of a test set into underground resistivity distribution, the end-to-end inversion process is realized, and the multi-scale feature extraction and semantic segmentation capabilities of the DeepLabV3 + network are utilized, so that compared with a traditional inversion method, the method has the advantages of being independent of an initial model, capable of obtaining a global optimal solution and the like.

The invention belongs to the technical field of unmanned aerial vehicle full-aviation electromagnetic detection, and particularly relates to a full-aviation frequency domain electromagnetic emission system and a control method. A broadband frequency mixing and matching circuit is connected in series between an H-bridge power inverter and an emission coil of an unmanned aerial vehicle electromagnetic emission system; the broadband mixing and matching circuit comprises a first resonance unit formed by connecting a fixed capacitor and an adjustable inductor in parallel and a second resonance unit formed by connecting a fixed capacitor and an adjustable inductor in parallel, and the first resonance unit and the second resonance unit are connected in series. The adjustable inductor is matched with the dynamic impedance of the inductive load by adjusting the inductance value, and the broadband frequency mixing and matching circuit can adjust the impedance in real time, so that the matching of different resonant frequencies is realized, and the frequency range of a matching signal can be obviously widened.

The invention relates to the technical field of geophysical exploration, and particularly provides a three-dimensional finite element transient electromagnetic forward modeling calculation method based on an iterative solution method.The method comprises the steps that tetrahedron space discretization is carried out based on a vector finite element method, and an electric field is given to six edges of a space tetrahedron; constructing a back-pushing Euler finite element equation set, and assembling a linear system formed by a large sparse matrix based on the equation set; performing iterative solution on the linear system based on an FGMRES algorithm to obtain an electric field value corresponding to a spatial tetrahedron unit edge; optimizing a spatial tetrahedral mesh based on a quadratic nesting method, and optimizing a time step length based on a third-order backward Euler difference format; a grid pre-encryption method is adopted, the calculation error of iterative solution is reduced, a region decomposition method is used for achieving parallel calculation, and the calculation efficiency is greatly improved. According to the method, the requirements of high precision and high efficiency in three-dimensional transient electromagnetic forward modeling calculation can be met, and an advanced calculation tool is provided for resource exploration in a complex geological environment.

The invention relates to the technical field of electromagnetic inversion, and particularly discloses a transient electromagnetic artificial intelligence inversion method based on physical driving, and the method comprises the steps: generating an equivalent anti-magnetic flux transient electromagnetic signal through an intelligent transmitter controlled by an FPGA, and generating a real-time electromagnetic field data set after noise suppression; according to the real-time electromagnetic field data set, carrying out similarity calculation on adjacent measuring point data to obtain an online quality factor, and further generating a dynamically optimized electromagnetic field data set; based on the dynamically optimized electromagnetic field data set, executing an equivalent anti-flux transient electromagnetic fast inversion algorithm through an edge computing node, and outputting an inversion confidence index; and according to the inversion confidence coefficient index, a launching parameter optimization function is constructed, and a dynamic launching control instruction set is generated, so that the precision and efficiency of electromagnetic detection are improved, the flexibility and the intelligent level of the system are enhanced, and the method has important technical significance and application value in efficient and accurate electromagnetic detection in a complex environment.

The invention discloses an underground anti-seepage structure leakage monitoring method and system based on discrete time, and relates to leakage detection. The method comprises the following steps: collecting transient electromagnetic response data generated by an excitation signal; according to the initial conductivity parameter and the electrode position parameter of the monitoring area, establishing a three-dimensional geophysical model of the monitoring area through a full waveform inversion algorithm; obtaining electromagnetic abnormal data by using a finite element forward modeling algorithm; according to the temperature data, a distributed temperature field analysis method is adopted to calculate the space gradient and the time change rate of the temperature, and temperature abnormal data are obtained; according to the pressure data and time sequence change characteristics of the pressure data, determining pressure abnormal data; fusing the electromagnetic abnormal data, the temperature abnormal data and the pressure abnormal data by using a Bayesian algorithm to obtain fused data; and inputting the fusion data into a pre-trained machine learning model to obtain a leakage detection result. Aiming at the low dynamic leakage monitoring precision of the underground anti-seepage structure, the dynamic monitoring precision is improved.

The invention provides a multi-source geophysical prospecting data fused Zenzenite rock mass contact zone anomaly method and system, and relates to the technical field of geophysical prospecting, the method comprises the following steps: executing joint denoising processing and time-frequency feature enhancement processing on a TFEM data set in a three-dimensional fused data volume, and outputting the optimized three-dimensional fused data volume; and based on the optimized three-dimensional fusion data body, by establishing a mapping relationship between magnetic, electric and polarization anomalies and a geologic body, quantifying the correlation between a multi-parameter combination and a mineralization index and screening an up-to-standard abnormal region, and finally delineating a magnetic anomaly gradient zone, a low-resistance region and a high-polarization anomaly co-occurrence ore prospecting target region three-dimensional distribution diagram. Through multi-source geophysical prospecting method collaboration, data deep fusion, quality optimization and accurate mapping, full-chain technology upgrading from data acquisition to target area delineation is realized, and the high efficiency of mineral exploration is improved.

The invention discloses an ocean-ionized layer ultralow-frequency electromagnetic target detection simulation method based on ADI-FDTD and SIBC, and belongs to the field of computational electromagnetics. The ocean-ionized layer ultralow-frequency electromagnetic target detection simulation method comprises the following steps: introducing a frequency domain surface impedance boundary condition SIBC into an ADI-FDTD model; the ocean-ionosphere simulation model is used for carrying out ocean-ionosphere ultra-low frequency electromagnetic wave attenuation analysis on the ocean-ionosphere ultra-low frequency electromagnetic wave attenuation. According to the method, the frequency domain surface impedance boundary condition (SIBC) is combined with the ADI-FDTD method for the first time, so that the calculation space for analyzing the influence of the seabed on electromagnetic wave propagation is reduced. The calculation requirement is obviously reduced, and the efficiency is improved. In addition, the SIBC model based on the ADI-FDTD method can be used for simulating the scattering effect of electromagnetic waves on a high-conductivity and low-conductivity area interface.

The invention discloses a sea water area karst cave group transient electromagnetic collaborative investigation data processing method and system, and the method comprises the steps: transmitting a wide frequency spectrum excitation signal to the seabed through a shipborne transient electromagnetic transmitting system, and synchronously collecting a secondary field attenuation signal responded by a seabed medium through a pull-type receiving array, meanwhile, a distributed sensor network is arranged at a preset seabed node to collect background noise base data; performing motion attitude compensation on the secondary field attenuation signal to generate transient electromagnetic response data; constructing an adaptive filter based on the background noise base data, performing noise suppression processing on the transient electromagnetic response data, and outputting noise suppression data; and performing space-time alignment on the noise suppression data of the towed array and the seabed node data to form a three-dimensional space sampling data set. According to the method, high-precision fusion of deep and shallow detection data and quantitative evaluation of the stability of the karst cave are realized, and the detection reliability and the engineering risk early warning capability of the complex ocean karst area are remarkably improved.

The invention discloses an underground space time-shifting transient electromagnetic unmanned monitoring device and method. The underground space time-shifting transient electromagnetic unmanned monitoring device comprises a mobile platform, a multifunctional transient electromagnetic detection device and a ground remote control terminal, the multifunctional transient electromagnetic detection device can actively adjust the distance between a transmitting coil and a receiving coil so as to realize a mutual inductance eliminating 8-shaped coil structure, and through cooperation with a calibration algorithm of a control center, the automation level and reliability of detection are remarkably improved, and it is ensured that the 8-shaped coil is in a mutual inductance eliminating state. In addition, the transient electromagnetic monitoring device can perform structure switching between deep layer detection and shallow layer detection, so that a high-efficiency detection mode that one circle has two purposes is realized, and the efficiency and the flexibility of detection operation are remarkably improved. In the actual detection process, the advantages that the 8-shaped coil is small in shallow blind area and large in overlapped loop detection depth are fully played, advantage complementation of two coil modes is achieved, and comprehensiveness and accuracy of a detection result are remarkably improved through a data fusion mode.

The invention provides a semi-aviation transient electromagnetic acquisition device and method for calibrating data drift in real time, and relates to the technical field of data calibration, and the device comprises an electromagnetic data acquisition unit which receives a secondary induction signal generated by a ground transmitting end through a transient electromagnetic hollow induction coil disposed in a coil storage cabin of an unmanned aerial vehicle, and transmits the secondary induction signal to an unmanned aerial vehicle; self-adaptive gain control is carried out according to the signal intensity to obtain real-time electromagnetic data; the flight control unit monitors the swing amplitude and frequency of the coil in real time according to the inclination angle and acceleration data fed back by the sensor in the coil storage cabin, and carries out flight attitude adjustment and control; the drift calibration unit adopts a static reference mode for calibration at the beginning stage of flight; and switching to a dynamic reference mode in the flight process, and carrying out self-adaptive calibration on the real-time data stream based on a sliding window. According to the invention, drift calibration of traditional software post-processing is migrated to a hardware acquisition stage, so that synchronous completion of data acquisition and drift compensation is realized.

The invention belongs to the technical field of geophysics. According to the truncation model space three-dimensional magnetotelluric inversion method and system, a three-dimensional inversion objective function is constructed according to an inversion initial model, the inversion objective function is optimized by adopting a Gaussian-Newton method, and a Gaussian-Newton increment equation is obtained, a sensitivity matrix in the Gaussian-Newton increment equation is a sparse matrix which is obtained after truncation is carried out by adopting a distance truncation threshold value and a sensitivity amplitude truncation threshold value, the Gaussian-Newton increment equation is converted into an unconstrained least square form, and an inversion updating direction is determined according to the least square form; and performing iterative optimization according to the initial inversion model, the inversion updating direction and the model updating step length to obtain an updated inversion model. According to the invention, units with small contribution to inversion updating are effectively cut, and the model space corresponding to each piece of data is reduced.

The invention discloses an underground target imaging method and imaging system based on variable scale deep learning, and belongs to the technical field of geophysical exploration, and the method comprises the following steps: S1, building a multi-scale magnetic survey data set; s2, constructing a UNet + +-based variable-scale deep learning network model, and performing feature fusion on pooled information and information subjected to split convolution by a dynamic information fusion layer so as to adapt to input data of any size and make up for information loss caused by pooling; s3, designing a multi-constraint loss function formed by mean square error and loss weighting; s4, migration learning is adopted, model parameters trained in a fixed size serve as initial weights, progressive training of multi-size data is achieved by freezing and fine tuning of decoder parameters, and finally the effectiveness of the whole network model is verified according to a test set prediction effect, so that the universality and flexibility of the network are improved when data of different sizes are processed, and the network performance is improved. And large-size data features in a specific area can be quickly adapted.

The invention relates to the technical field of quantum sensing and ocean detection, and discloses an ocean magnetic field sensor based on an NV color center and an ocean magnetic field measuring method.The sensor comprises a cylindrical pressure-resistant cabin, an optical platform arranged in the pressure-resistant cabin and a main control panel; a laser, a beam shaping unit, a dichroscope, a beam shaping lens group, an objective lens, a diamond NV color center chip, a plano-convex lens I, a band-pass filter and a photoelectric detector are mounted on the optical platform; two microstrip loop antennas are mounted on the outer side of the diamond NV color center chip; an FPGA + ARM dual-core processor, a digital lock-in amplifier and two microwave signal generators are installed on the main control board, and the microwave signal generators are connected with the microstrip loop antenna and achieve electromagnetic coupling with the diamond NV color center chip. The invention has the advantages of high sensitivity, good long-term stability and strong anti-interference capability, and provides a new generation of quantum sensing solution for applications such as ocean geomagnetic monitoring and underwater target identification.