404 results about "Digital mapping" patented technology

The invention discloses an intelligent control and optimization system and method for the whole process of a photovoltaic power station. The method comprises the following steps: constructing a component-level high-fidelity digital twin through multi-source heterogeneous data fusion and an attention enhancement deep learning model; injecting annotated historical fault data, carrying out joint training by combining a feature embedding layer and an adversarial generative network, and generating a digital mapping body with fault evolution deduction capability; a three-layer architecture is introduced, reinforcement learning and a multi-objective optimization algorithm are fused, and autonomous decisions of power station level power output maximization, equipment loss minimization and maintenance cost optimization are realized in a virtual simulation environment constructed by a digital mapping body. According to the method, accurate dynamic mapping of the physical entity and the virtual space, fault pre-judgment and deduction and closed-loop control of global autonomous optimization are realized, the intelligent level and the full-life-cycle economy of the photovoltaic power station are improved, and the problems of insufficient fidelity, lack of fault deduction capability and low global optimization efficiency in the prior art are solved.

The invention relates to the technical field of power system monitoring, in particular to a power system parameter dynamic verification method, system and device based on digital twinning and a storage medium. Constructing a digital twinborn model of the power system, establishing a state mapping relation between a physical system and a digital model, realizing bidirectional dynamic mapping between the physical system and the digital model through a digital mapping mechanism, and obtaining system operation characteristics; constructing a parameter verification model based on the operation characteristics, obtaining a verification objective function by fusing physical constraints and data driving, and dynamically adjusting parameter values to generate parameter correction values by evaluating model errors in real time by adopting an adaptive parameter correction algorithm; based on a dynamic optimization mechanism of multi-objective optimization, an optimization strategy is adaptively adjusted according to the running state, and the verification process is continuously optimized; and performing multi-dimensional evaluation on the verification result through the verification precision evaluation system to generate a parameter verification result. The technical problems that a traditional method is inaccurate in modeling, low in response speed and poor in adaptability are effectively solved.

The invention relates to the technical field of petroleum drilling engineering, and particularly discloses an analysis and prediction system based on petroleum drilling and production data, which realizes virtual reconstruction of a physical drilling system by constructing a digital mapping body, and adopts a multi-source sensor network to collect drill string vortex frequency and wellbore temperature field gradient data. Forming a time sequence feature set through time sequence alignment and fusion processing; performing differential transformation and modal decomposition on the feature set to extract transient response feature vectors and generate a risk distribution diagram; establishing a parameter-risk correlation model, and decoupling mechanical vibration and thermal stress interference by solving a physical equation to obtain a dynamic risk index; the risk indexes and the process parameters are mapped to a three-dimensional grid to construct a multi-dimensional feature space, a feature fusion grid is adopted to achieve information aggregation and reconstruction, and comprehensive risk assessment indexes are generated; a dynamic early warning threshold value is established according to the evaluation indexes, and drilling parameters are optimized in real time through closed-loop control.

The invention relates to an automatic printing calibration method and system combining vision and AI and a storage medium, a multi-mode sensing unit integrated on a printing head assembly synchronously collects two-dimensional images, three-dimensional shapes and working spacing data of a printing area in real time, and data fusion is carried out by using a model based on a neural radiation field; generating a high-fidelity multi-dimensional digital mapping; carrying out defect identification and positioning by adopting a pre-trained convolutional neural network CNN model, and predicting an optimal adjustment parameter according to the defect information and the historical sequence through a long short-term memory network LSTM model; the edge calculation and control unit is combined with a material characteristic database to generate a hierarchical calibration instruction in a millisecond level, adopts fuzzy PID self-optimization control to dynamically set PID control parameters, and is combined with feed-forward compensation of the inertial measurement unit to perform accurate, smooth and robust control on an execution mechanism, so that the accuracy of calibration is improved. And full-automatic, high-precision and real-time online calibration of the printing process in a complex industrial environment is realized.

The invention relates to the technical field of power equipment management, in particular to a digital low-voltage cabinet full life cycle data management method and system, and the method comprises the steps: distributing a global unique digital identity identifier for a low-voltage cabinet and key components, and constructing a standardized digital mapping model based on an OPCUA framework; gathering full-process multi-source heterogeneous data to a cloud edge collaboration platform by taking the digital identity as an index to form a data consanguinity chain; creating a digital twinborn body, dynamically updating the model through real-time data and iteratively calibrating parameters; carrying out abnormity identification, health assessment and residual life prediction by using an AI algorithm, and generating an operation and maintenance instruction; and feeding back the instruction to an upstream system. According to the method, a data island is broken, predictive maintenance is changed into full-period optimization, and the equipment safety and the operation efficiency are improved.

The invention discloses a heavy crane multi-task intelligent collaborative scheduling and path optimization control system, which is characterized in that by collecting operation state data, environment perception data and task queue data of a plurality of heterogeneous cranes, a time-space unified modeling module constructs and updates a collaborative operation digital map in real time; the collaborative operation digital map and the task queue are input into a multi-task dynamic collaborative scheduling module, a task-equipment allocation mapping relation and a plan time window are output, and then the collaborative operation digital map is combined to be input into a layered collaborative path planning module to generate a real-time motion control instruction sequence; and finally, issuing to a crane bottom layer control system through a protocol adapter to drive collaborative operation. According to the method, the problems of insufficient global optimization and high conflict risk when a plurality of heterogeneous cranes cooperatively work in a dynamic complex environment are solved, intelligent scheduling and safe planning are realized, and the working efficiency and safety are improved.

The invention discloses a fire scene area rapid estimation method based on passive positioning. Relates to the technical field of image processing, in particular to a method for calibrating laser optical axis deviation through target positioning in the air. According to the method, a digital map and a digital elevation model file of an actually measured image of a target area are loaded, orthographic transformation is carried out on the image in combination with pose data corresponding to a single-frame image, and the work of foreground extraction and fire scene area estimation is completed on the basis. The method comprises the following steps: making a digital elevation model data set of an area to be measured; shooting an actual measurement image of the to-be-measured area; resolving the central position of the field of view; finding out a digital elevation model file corresponding to the actually measured image according to the central position of the field of view; performing orthographic transformation to obtain an image of a right downward view angle; calculating the area of the to-be-measured region based on the digital elevation model file according to the image of the right downward view angle; and extracting an image foreground to estimate the fire scene area.

The invention belongs to the field of industrial control, particularly relates to a workshop production line whole-process data processing and intelligent monitoring method and system, and aims to solve the problem that the whole production process is difficult to effectively monitor in related technologies. The method comprises the following steps: collecting asynchronous data streams from different sources in the whole production process; mapping each data point in the asynchronous data stream to a unified space-time reference framework; constructing a knowledge graph; inputting the knowledge graph into the space-time diagram convolutional network model to obtain an abnormal probability score of each node in the knowledge graph; and determining an abnormal probability node, carrying out reverse backtracking along a relation edge in the knowledge graph, positioning a source abnormal node, carrying out feature attribution analysis on state data of the source abnormal node, and generating a root cause interpretation report of an abnormal working condition. According to the method, the knowledge graph with the work order as the entity and the process flow as the relation chain is constructed, digital mapping and unified representation of the whole production flow are achieved, and the whole production flow can be effectively monitored.

A system is provided for localizing an autonomous work vehicle within mapped agricultural environments when GPS may be unavailable. Range sensors capture LiDAR images that are segmented by a trained model into features such as trunks and canopy. Trunk points are clustered to compute centroids, which are used to estimate left and right tree lines and a lane centerline relative to the vehicle. This sensor-derived centerline is compared with georeferenced lane and row geometry stored in a digital map. A particle filter maintains multiple pose hypotheses, propagates them using vehicle odometry, and weights them according to alignment between the lane centerline relative to the vehicle and the mapped lane geometry for the particle. Resampling and averaging of high-weight hypotheses produces an adjusted pose that corrects for lateral and heading errors. The adjusted pose serves as input to a navigation controller that issues steering and speed commands, enabling accurate autonomous operation.

The invention discloses a distributed waterlogging and ponding digital map prediction system based on edge calculation, and relates to the technical field of urban flood prevention intelligent decision making. The system comprises a distributed intelligent acquisition module, an edge integrated processing module, a multi-stage collaborative analysis module and a visualization and decision output module. Collecting multi-source heterogeneous data through multiple types of sensing equipment; calling a local digital elevation map slice and a lightweight hydrological model, generating local waterlogging state information and self-calibrating model parameters; key information is screened based on double threshold values of information entropy change and accumulated water depth change rate, multi-monitoring-point data and a drainage pipe network topological relation are fused, and regional-level inland inundation situation analysis and accumulated water and recessive water trend prediction are achieved; and generating and updating a whole-region distributed ponding digital map, and outputting graded early warning and auxiliary decision information. According to the method, distributed acquisition and edge calculation are combined, the monitoring real-time performance and precision are improved, and the problems that traditional monitoring is high in delay, low in precision, fuzzy in decision and the like are effectively solved.

The invention discloses a cage rearing broiler chicken multi-level epidemic situation early warning and prevention and control optimization method, which comprises the following steps: S1, constructing a data support system; S2, constructing a cross-level epidemic situation propagation simulation system, and realizing multi-scale digital mapping from a coop to a region; s3, according to the epidemic situation simulation result in the S2, early warning grades are divided; and S4, according to the early warning level in the S3, an association rule base addition and deletion measure is called, a candidate prevention and control measure combination is generated, and dual-target optimal measure combination screening with the maximum control effect and the minimum total cost is realized. According to the method, multi-scale accurate simulation of epidemic situation propagation and quantitative optimization of prevention and control measures can be realized, the control effect and cost are balanced, the scientificity and operability of prevention and control decisions are improved, and the method is adaptive to different early warning levels and breeding scenes and is high in robustness and practicability.

The invention provides a riding navigation blind area track correction method and system based on stopwatch inertial navigation, electronic equipment and a storage medium, and the method comprises the steps: obtaining the angular velocity and acceleration information of a stopwatch and the direction information of an earth magnetic field, and carrying out the calculation to obtain a riding course angle and a real-time riding speed; when it is detected that a satellite positioning signal is interrupted, the last credible satellite positioning coordinate before interruption serves as an estimated coordinate point of a first operation period, and in each operation period, a relative displacement vector is calculated by combining the course angle of the current period, the real-time riding speed and the time interval of the operation period; iteratively determining the estimated coordinate point of the current period by taking the estimated coordinate point of the previous period as a reference, and forming a continuous extension track; and finally, matching the extended continuous coordinate points with a road network of a preset digital map, calculating and accumulating the distance between adjacent coordinate points based on the matched real road coordinates, and completing accurate correction of the track and the distance.

The invention relates to a robot control technology, and discloses a robot cluster control method and system and a storage medium, and the method comprises the steps: receiving motion state data, network link state data and service type information of each robot; predicting a motion track of each robot in a future preset time period based on the motion state data in combination with a digital map, and predicting a communication quality change trend of a current network link of each robot in the future preset time period based on the network link state data; determining a target network link of each robot based on the motion trail, the communication quality change trend, the digital map, the service type information and the received node operation state information of each edge relay node, and generating a network switching instruction containing the target network link and the switching opportunity, and the corresponding robot executes network link switching according to the network switching instruction. According to the invention, global prediction and active switching of robot cluster communication can be realized.

The invention discloses a large-burial-depth pipeline nondestructive detection method and system, and relates to the technical field of pipeline positioning. The system combines a region feasibility identification module, an initial positioning module, a multi-type nondestructive detection unit, a multi-path anomaly identification module, an underground structure matching module, an intelligent obstacle avoidance compensation module and a signal fusion module, and adopts a multi-source information fusion and intelligent path planning technology. And high-precision and non-intrusive nondestructive detection of the metal pipeline with the burial depth exceeding 5 meters is realized. Through comprehensive evaluation of ground obstacles and underground interference sources, the detection path layout is optimized, and the problems of signal interference, multi-path reflection and detection blind areas in the urban complex underground environment are effectively solved. The system can accurately reject non-target structure reflection signals, dynamically generate an obstacle avoidance compensation path, and improve the detection coverage rate and the signal integrity. And finally, three-dimensional space positioning and digital map coordinate output are realized, and the accuracy of pipeline positioning and the reliability of depth estimation are remarkably improved.

The invention relates to the technical field of new energy power grid coordination control, and discloses a wind storage combined frequency modulation control method based on model prediction control and deep learning. The method comprises the following steps of: driving a high-frequency updated system feature library, constructing dynamic digital mapping of a wind storage system, performing multi-level scene evolution and collaborative optimization according to the dynamic digital mapping, and generating a control instruction. And the control instruction is verified and decomposed and then issued to physical equipment for execution. And synchronously acquiring system response data, performing frequency domain feature extraction and mode matching, and triggering closed-loop self-adaptive adjustment of dynamic digital mapping according to the frequency domain feature extraction and the mode matching. According to the method, online dynamic updating of the control model and accurate correction for the frequency domain characteristics of the system are realized, so that the model can closely track the change of an actual object, and the control precision and the dynamic response quality of wind storage combined frequency modulation are improved.

The invention discloses a pipeline detection method and system based on an intelligent pipeline robot with a body, and relates to the technical field of pipeline detection. The method comprises the following steps: acquiring pose, environment and pipe wall sensing data acquired by a multi-mode sensor; a pipeline three-dimensional digital map is constructed, and real-time self-positioning is achieved; identifying a pipe wall defect based on the pipe wall sensing data, generating a defect data packet, and binding the defect data packet with a map space position for storage; when an adjacent robot is detected, constructing a temporary communication link; exchanging detection information containing a map abstract and task state information with an adjacent robot through the link; updating the three-dimensional digital map by using the map abstract of the adjacent robot; performing task negotiation by combining the task state information and the updated map; and adjusting the target operation area and the motion path according to the negotiation result. According to the invention, full-automatic high-precision detection and intelligent operation and maintenance decision-making in a complex pipeline environment can be realized.

The invention relates to the technical field of agricultural robot path planning, and discloses an autonomous navigation and intelligent operation path planning method for an agricultural robot. The method comprises the following steps: delimiting a target area in a digital map according to an operation intention instruction, and carrying out multi-dimensional scene deconstruction to generate an operation scene map; real-time information is obtained through multi-source sensing hierarchical scanning and is fused with a scene map, and a three-dimensional environment dynamic model containing trafficability, operation value and dynamic risk weight is constructed. And the strategy decision engine outputs a global strategy skeleton through multi-target solution space exploration and compromise solution according to the model and the operation instruction. And under skeleton constraint, performing local fine path generation to obtain an executable track sequence of the robot, and deducing the executable track sequence into a driving control instruction. In the execution process, the environment model and the strategy framework are dynamically updated through a backtracking correction thread. According to the invention, intelligent self-adaptive operation of the agricultural robot in a complex farmland environment with consideration of safety, efficiency and operation quality is realized.

The invention discloses an electrical equipment maintenance management system and method adaptive to electric power engineering, and relates to the technical field of electrical equipment maintenance management. The electrical equipment maintenance management system comprises a digital twin modeling module, a multi-dimensional data acquisition module, a life prediction module, a predictive maintenance early warning module, a resource scheduling module and a spare part management module. The digital twinborn modeling module is used for constructing a digital twinborn body of the equipment, and digital mapping and operation behavior simulation of the power equipment are realized through geometric modeling, physical attribute integration and behavior simulation. According to the invention, digital mapping of equipment is constructed through the digital twin modeling module, geometric modeling, physical attributes and behavior simulation are integrated, and operation parameters, environmental parameters and state information are acquired in real time in combination with the multi-dimensional data acquisition module, so that full-dimensional dynamic simulation and data-driven state sensing of the equipment are realized; the problems that fault pre-judgment is lagged and internal hidden defects are difficult to recognize due to data patch or model staticization are solved.

The invention relates to the field of data fusion, in particular to an RFID and Bluetooth fusion positioning method and system for material storage location navigation, and the method comprises the steps: obtaining the RFID tag information of a target material; according to the RFID tag information, querying a preset material storage area mapping relationship, and according to a query result, determining a target storage area where the target material is located and target shelf coordinates where the target material is located; generating a Bluetooth scanning instruction according to a determination result of the target reservoir area; broadcast signals from at least three Bluetooth beacons in the target reservoir area are received, and signal intensity parameters of the broadcast signals are analyzed; on the basis of the known position coordinates of the at least three Bluetooth beacons and the corresponding signal intensity parameters, the current accurate coordinates of the mobile terminal are calculated through a positioning algorithm; and generating and displaying a navigation path from the current position of the mobile terminal to the target shelf in real time according to the current accurate coordinate and the target shelf coordinate. And the optimal navigation path is dynamically generated and displayed on the digital map, so that intuitive visual guidance is provided for the user.

The invention discloses an error real-time compensation method for GNSS (Global Navigation Satellite System) dynamic positioning, which relates to the field of GNSS dynamic positioning and comprises the following steps of: obtaining a to-be-corrected track fragment with a continuous motion trend; calling the digital map data of the corresponding area from a local storage and / or a cloud server; determining one or more candidate matching roads according to the matching degree of the track course change features and the road curvature features; performing short-time dead reckoning to obtain a predicted position at the current moment; based on the road traffic direction constraint and the connectivity constraint, the projection points are verified; and taking the final corrected positioning result as a reference point of dead reckoning at the next moment, and continuously and progressively correcting the GNSS dynamic positioning error. The method has the advantages that through short-time dead reckoning prediction, dynamic positioning errors and inertia accumulation drifting are restrained, a positioning result is forced to be reasonably attached to a real road network all the time, and high-reliability, low-cost, continuous and stable dynamic positioning is achieved.

The invention relates to the technical field of machine vision, and provides a concrete vibration operation real-time guidance method, device and equipment and a storage medium, and the method comprises the steps: generating a digital map and a monitoring grid with a physical proportion relation, dynamically detecting the change of a concrete bin surface in construction, and automatically updating the digital map and the monitoring grid, thereby achieving the real-time guidance of the concrete vibration operation. Vibrating personnel and a vibrating rod are recognized through an instance segmentation model to judge whether the vibrating rod is in an effective vibrating state or not, equivalent vibrating points are extracted and positioned to a digital map, the vibrating coverage amount in a monitoring grid is counted and compared with a preset construction standard, and an under-vibration or over-vibration area is automatically recognized; and further generating directional guide information or early warning prompt information with spatial directivity. According to the method, self-adaptive perception and accurate operation guidance of the dynamic construction surface are realized by a low-cost monocular vision scheme.

The invention discloses a hydrothermal type geothermal efficient exploitation and irrigation intelligent operation maintenance system, and the system comprises a data processing module which is used for carrying out the multi-dimensional and multi-physical-field precise digital mapping of a geothermal reservoir to ground equipment, and obtaining the dynamic change process of the geothermal reservoir and the ground equipment under different working conditions; the data processing module comprises a thermal reservoir geologic model, a THMC coupling simulation model and a ground facility system model, the thermal reservoir geologic model is used for representing a three-dimensional space structure and initial physical property parameter distribution of a geothermal reservoir, and the THMC coupling simulation model is constructed based on the geologic model. The ground facility system model simulates fluid flow, heat transfer, rock mechanics and chemical reaction processes and is used for simulating the working state of ground equipment from a wellhead of a production well to a wellhead of a recharge well; and the execution module is used for driving the variable frequency pump to perform stepless speed regulation so as to change the total flow and pressure of the system, and driving the regulating valve to perform opening regulation so as to realize flow distribution and pressure control, thereby forming an intelligent control loop.

The invention discloses a public area intelligent management method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a video stream through a camera monitoring network; performing character detection and behavior recognition on the video stream to obtain an individual coordinate of each character and an individual behavior sequence corresponding to each character; mapping the individual coordinates and the individual behavior sequence to a public area digital map to obtain a people flow density prediction value of each sub-area in the next time period; and based on the people flow density predicted value and a preset threshold value, generating a resource allocation instruction and a tourist path guide instruction to perform public area management, thereby remarkably reducing the instantaneous people flow gathering degree and shortening the congestion duration during the peak period of festivals and holidays.

The invention discloses a hospital building equipment intelligent operation and maintenance method and system based on multi-source identification fusion, and belongs to the technical field of hospital building equipment management, and the method comprises the steps: configuring and deploying multi-source identification hardware; acquiring equipment position data and equipment operation state data; performing space-time alignment and data fusion on the equipment position data and the equipment operation state data by adopting a fusion algorithm integrated with medical data time sequence compensation and space conflict pre-judgment; constructing a ternary association data model of space-equipment-operation and maintenance ternary association digital mapping based on the fused data; driving four-dimensional binding of physical space-virtual model-equipment entity-operation and maintenance process based on the ternary associated data model, carrying out view angle loading, dynamic operation and maintenance board visualization and multi-terminal synchronization, and adapting to a hospital multi-terminal collaborative operation and maintenance scene; the method can be combined with an advanced data fusion algorithm, and achieves the precise positioning of the hospital building equipment.

The invention discloses a composite material forming defect closed-loop correction method and system based on digital twinning, and the method comprises the steps: collecting material characteristic data, equipment operation parameters and real-time sensing data in a composite material forming process, and generating a composite material digital twinning body capable of reflecting a forming state in real time; generating a correlation map of defect types and influence factors based on a dynamic process of composite material digital twinborn re-forming; according to the association map, calling a process optimization module of the digital twin, and generating a process parameter correction scheme for specific defects; and the process parameter correction scheme is issued to forming equipment to be executed, corrected forming quality data is collected and fed back to the composite material digital twin, the defect elimination effect is verified, the physical-digital mapping relation of the twin is updated, and a closed-loop correction mechanism of the composite material forming defects is formed. By utilizing the embodiment of the invention, the forming defects can be efficiently eliminated, the quality consistency of composite material products is improved, and the production efficiency is improved.

A method for predicting a state of an environment of a vehicle includes determining an occupancy grid, a digital map, and a list of objects. The method further includes encoding the occupancy grid to a first occupancy grid representation in a latent space for the occupancy grid, the digital map to a first map representation in a latent space for the digital map, and the list of objects to a first object list representation in a latent space for the list of objects. The method further includes predicting, for each of one or more future points in time of the environment of the vehicle, a respective further occupancy grid representation, a respective further map representation, and a respective object list representation.

A method for assisting an automated vehicle in vehicle control, the method including continuously checking whether the automated vehicle is leaving its operational design domain and whether a comparison metric of the deviation of current environmental conditions from the associated information on a digital map is exceeded. If so, the method further includes requesting an authorization to enter a vehicle-following mode at a control center; and rejecting the request or granting the request by the control center, wherein when the request is granted by the control center, a start of the vehicle-following mode and the road user to be followed are determined. The method additionally includes carrying out a vehicle-following mode by the vehicle at the start determined by the control center behind the road user determined by the control center.

The invention provides an airport surrounding intrusion detection method and system based on satellite positioning, and the method comprises the steps: building an electronic fence geographic boundary based on an airport digital map; the method comprises the following steps: acquiring satellite original observation data in an airport monitoring range in real time, and preprocessing the satellite original observation data to obtain a standard data frame; performing real-time dynamic differential calculation on the standard data frame to obtain a target terminal position coordinate in the airport monitoring range; performing geographic relationship calculation on the position coordinates of the target terminal and the geographic boundary of the electronic fence, judging the current area of the target terminal, and obtaining a judgment result; and performing trajectory tracking and threat evaluation on the target based on a judgment result, and completing satellite positioning-based airport surrounding intrusion detection. According to the technical scheme, the problems that a traditional technical prevention system is high in false alarm rate and depends on manual discrimination are fundamentally solved, the operation and maintenance cost is greatly reduced, and the alarm accuracy is improved.

The application discloses a kind of determination methods and program products of core reactivity state, the method includes: the key state parameter in the process of core reaction is collected, key state parameter includes at least one of core power distribution parameter, coolant temperature, coolant density, control rod position, boric acid concentration and burnup;Determine the burnup step of fuel, the evolution process of fissile nuclide and fission product in core is modeled based on the burnup step of fuel and burnup model, to obtain the reactivity parameter related to the burnup of fuel, the burnup model is used to describe the nuclide transmutation and consumption logic of fuel during the operation of core;Corresponding digital twin is constructed with the reactivity state of the core, the reactivity state of the core is mapped by the digital twin based on the reactivity parameter and the key state parameter driving, can realize high-precision, real-time, full life cycle dynamic digital mapping and intelligent detection of core reactivity state.

The embodiment of the application provides a geological exploration method and device based on the radiation characteristics of the intrinsic subatomic wave of a substance, which comprises the following steps: obtaining remote sensing satellite data by setting the specific range of a target mining area, a scale, a shooting angle, a time period and a wave band, and determining the original negative of the remote sensing satellite corresponding to the exploration area; performing radiation operation on the original negative according to a preset subatomic field generator, performing image enhancement processing on the target substance radiation image according to a nonlinear algorithm, and determining the corresponding target substance digital map; determining the corresponding three directions according to the digital map, determining the corresponding three digital images according to the three directions respectively, performing target substance inversion calculation and target substance model establishment operation according to the three digital images, and determining the corresponding target substance mathematical model to realize the visualization of the target substance. The application can capture the subatomic radiation of the crust mineral elements based on the satellite, detect and visualize the minerals by using the subatomic characteristics, and improve the efficiency and accuracy of geological exploration.