65 results about "Continuous field" patented technology

The invention discloses a construction project whole-process management system and method with a BIM3D-6D technology as a base, and relates to the technical field of construction project management, and the method comprises the steps: loading a 3D building information model through a BIM lightweight calculation server, extracting the spatial topological relation and IFC semantic attributes of geometric components, and carrying out the calculation of the 3D building information model through a BIM lightweight calculation server; spatial topology analysis and semantic attribute mapping are carried out on the spatial topology relation of the geometric components and the IFC semantic attributes, and a three-dimensional data topology network packet based on a graph structure is generated; performing multi-dimensional deduction operation on the three-dimensional data topology network packet based on the graph structure to obtain a deviation compensation strategy containing an optimal cost control path; and carrying out dimension expansion and data fusion on the 3D building information model to generate a 5D cost dimension data set. Discrete decisions are converted into a continuous field model through mathematical transformation, so that a resource flow path has spatial relevance and time continuity, and the beneficial effect of dynamically optimizing a construction process is achieved.

The invention discloses a goaf collapse risk assessment data fusion system based on big data processing, and particularly relates to the technical field of geological disaster assessment, and the system comprises three core modules: a multi-source data adaptive weighted fusion module which establishes a unified space-time coordinate system, converts non-raster data into a continuous field through Kriging interpolation, and performs data fusion on the continuous field; combining the information entropy and the correlation coefficient to dynamically distribute weights, and generating an enhanced feature field through self-supervised pre-training; the physical-space-time neural network dynamic prediction module is integrated with elastic-plastic mechanical constraint loss and multi-task learning, and outputs a future multi-time step risk probability field and a deformation prediction field through a space-time convolution-memory network; and the risk field three-dimensional subdivision and emergency response module is used for clustering three-dimensional voxels in a high-risk area, automatically calculating risk body parameters, generating an emergency scheme in combination with DEM data and an A * algorithm, and improving evaluation accuracy and emergency scheme practical operability through digital twinborn deduction evaluation.

The invention provides a three-dimensional shape generation method, which comprises the following steps of: extracting condition characteristics of a two-dimensional image by using an image encoder; sampling an initial noise vector from the standard normal distribution based on the condition features; under the guidance of the condition features, the trained generative model generates potential representation based on the initial noise vector; a decoder of the trained 3D VAE model reconstructs a continuous field function according to the potential representation; and extracting a three-dimensional triangular mesh model from the continuous field function. The smoothness of the generated surface and the integrity of the three-dimensional structure can be realized by the 3D VAE model, so that the aims of eliminating stepped artifacts and broken thin shells are fulfilled.

The invention relates to a geomechanical modeling method and system based on artificial intelligence and a medium, and the method comprises the steps: carrying out the space-time alignment and feature decoupling processing of continuous field data and discrete structure data, and generating a continuous-discrete mixed feature tensor of a unified space-time reference; the method comprises the following steps: constructing a multi-scale physically coupled hybrid neural network, realizing cross-scale bidirectional interaction through an adaptive physical interface to obtain a dynamically coupled geomechanical prediction model, and performing parameter optimization on the geomechanical model by adopting a physical-data dual-driven dynamic training strategy; performing stratum parameter online inversion based on real-time monitoring data and the trained geomechanical prediction model to generate an uncertainty quantification result; and mapping the uncertainty quantification result to the three-dimensional geologic model, and outputting a visual risk thermodynamic diagram. According to the method, real-time updating and uncertainty evaluation of geological parameters are realized, a quantitative basis is provided for engineering decision making through a visual visualization mode, and scientificity and reliability of decision making are enhanced.

The invention relates to the technical field of vehicle trajectory analysis, in particular to a vehicle trajectory anomaly detection method and system based on deep learning, and the method comprises the following steps: obtaining trajectory coordinates and boundary distance to generate symbol offset, constructing a road offset continuous field through interpolation and spatial embedding, calculating the ratio of instantaneous speed to reference speed, and obtaining a vehicle trajectory anomaly detection result. And generating an unbalance degree parameter, executing vector dimension stretching, extracting a trajectory embedding vector and an abnormal score by using a long short-term memory network, executing square summation and difference operation, and generating a trajectory energy gradient value. According to the method, migration characteristics are mapped to a continuous field to achieve track and road geometric constraint association, unbalance degree parameters are used for remarking directional quantity scales to enhance speed dynamic perception, energy gradient modulation scoring is cooperated, a confidence probability curved surface is constructed by using trilinear interpolation, and a curved surface peak value is positioned to output a detection result. Positioning noise is suppressed; and abnormal precision under sparse sampling is improved.

The invention relates to the field of conveyor state monitoring, and discloses a conveyor running state monitoring system based on edge calculation, which is used for running state monitoring and fault early warning of an industrial conveyor system. The conveyor operation state monitoring system based on edge calculation comprises a sensing module, a prediction module, an identification module, a decision module and an optimization module. The sensing module constructs a virtual sensing field by deploying a multi-physical-quantity sensor, and continuous field description of the running state of the conveyor is established; the prediction module performs multi-state parallel deduction based on a quantum superposition principle to generate a prediction result; the identification module uses a biological field resonance principle to realize abnormity identification and fault positioning; the decision module generates a control strategy according to the abnormity severity and the resource state; and the optimization module forms a closed-loop system by adjusting resources. Accurate monitoring, early warning and intelligent decision making of the running state of the conveyor are achieved, and the reliability and efficiency of equipment monitoring are improved.

The invention discloses a shape memory alloy multi-physics field analysis method based on an expansion depth operator network, belongs to the technical field of material science and engineering calculation, solves the problem of phase field dynamics analysis of multi-physics field coupling under various initial conditions, and comprises the following steps: S1, constructing the expansion depth operator network, the expansion depth operator network comprises a branch network and a backbone network; and S2, determining the total error of the neural network according to the data information error and the physical information error, optimizing the parameters of the neural network by adopting an AdamW optimizer and a Minibatch technology, training the neural network, and completing the shape memory alloy multi-physical field analysis based on the extended depth operator network. According to the method, the expansion depth operator network is used for replacing a finite element method, the solving process of the multi-physical field phase field equation is accelerated, field quantity distribution continuous in time and space is obtained, the solving process is accelerated, and continuous field distribution is obtained.

The invention relates to a phased array radar reflectivity factor simulation method based on sparse sounding data, belongs to the field of radio, designs a sparse reconstruction simulation scheme based on acquired multi-point multi-height-layer sparse sounding data, and realizes high-quality restoration and three-dimensional continuous field construction of original sparse observation data. A multivariate dictionary base matrix is constructed; through a sparse representation theory and a Bayesian optimization model, a sparse coefficient reflecting rainfall essential characteristics is obtained, and high-spatial-resolution reconstruction of a temperature and humidity field and a rainfall micro-physical parameter field is realized. Thereafter, a meteorological parameter-driven phase judgment and probability field calculation model is constructed, and three-dimensional simulation of liquid, solid and mixed rainfall echoes is realized. And finally, calculating a unit direction vector and an azimuth guidance coding matrix of a beam ray of the phased array radar, introducing a radar volume scanning data implicit sampling simulator, and realizing high-precision reflectivity factor simulation of the phased array radar in a three-dimensional scanning mode.

The invention discloses an unmanned sweeper-oriented real-time working condition three-dimensional dynamic visual monitoring system, which relates to the technical field of unmanned sweeper working condition monitoring and comprises a modeling monitoring module, a region division module, a feature evaluation module, a strategy regulation and control module and a visual recording module. The region division module is used for extracting a space region with model shielding residues under the condition that the model shielding residues exist in continuous scene updating, and uniformly dividing the space region to generate a plurality of structure calibration regions; and the feature evaluation module is used for extracting the spatial modeling quality information of each structure calibration area, analyzing and evaluating the coverage distortion degree of each structure calibration area after extraction, and classifying each structure calibration area according to an evaluation result. According to the method, the problems that shielding distortion cannot be recognized and mistaken updating cannot be achieved in continuous modeling are solved, and accurate evaluation and dynamic regulation and control of local model updating are achieved.

The invention discloses a spatial interpolation method based on an FC-ResNet neural network model, and the method comprises the steps: training a neural network model through sample point data, enabling the model to learn a mapping relation between an interpolation attribute value and a coordinate, and recovering continuous distribution characteristics of a two-dimensional space and even a three-dimensional region from sparse observation data, and spatial continuous field reconstruction is realized. By introducing the residual block, the expression ability of the deep network is enhanced, the model training stability is improved, and gradient disappearance and network degradation are avoided, so that two-dimensional and three-dimensional space interpolation tasks are adapted; a physical information regularization constraint is fused into a loss function, so that the interpolation result is ensured to have spatial smoothness and physical consistency (such as geologic body continuous gradual change characteristics), and the phenomena of'block artifacts' and the like which do not conform to actual rules are reduced; finally, accurate reconstruction of space structures (such as submarine topography and oilfield porosity distribution) is realized, and an efficient tool is provided for complex space field data modeling.

The invention provides a laser communication device for rapid link establishment and networking and a satellite internet constellation. The device utilizes the wavelength division multiplexing unit and the pre-aiming unit to realize beam combination of receiving and transmitting optical path signals so as to improve the coaxiality of receiving and transmitting branches; an optical fiber displacement device arranged on the transmitting-receiving lens is used for adjusting the relative position of the beam combining optical fiber and the focal point of the transmitting-receiving lens, and continuous beam changing of a transmitted light path signal within the divergence angle range of 55-1000 microrad is achieved; and a position sensing unit is matched to focus a receiving light path signal, so that a 0.2-1-degree receiving light path continuous field of view is realized. Through 10000 times of offset error estimation simulation, the coverage rate of an uncertain area to a target light spot reaches 99.32%, and about 1mrad beam change can be realized, so that minute-level capture efficiency is realized under the condition of the continuous field of view.

The invention discloses a field operation video violation judgment method and device, terminal equipment and a storage medium, and belongs to the field of video surveillance, and the method comprises the steps: collecting a field operation video, and carrying out the frame extraction processing of the field operation video according to a time sequence, and obtaining a video frame sequence; the video frame sequence comprises a plurality of video frames; detecting a to-be-recognized target in each video frame through a target detection algorithm to obtain target recognition data, and generating a cue word set according to the target recognition data; according to the target identification data, the cue word set and the field operation video, constructing a multi-modal input feature, and inputting the multi-modal input feature to a pre-trained visual language model to obtain a language description of the field operation video; and inputting the language description and a preset judgment logic into the pre-trained large language model to obtain an operation violation judgment result. Therefore, by implementing the method and the device, the problem of low violation phenomenon identification accuracy in the continuous field operation video can be solved.

This invention provides a method for processing streaming data throughout the entire lifecycle of an engineering project, relating to the field of engineering data processing technology. The method includes: constructing permanent spatial anchoring expression units for target structural units during the construction phase of deeply buried structures, generating a set of permanent spatial expressions for concealed components; performing lifecycle flow mapping modeling of the spatial anchoring expression units to generate a set of traceable spatial evolution paths for the concealed phase; performing spatial expression reconstruction and closed-state association processing for the concealed structural phase to generate a continuous field of spatial expression for the concealed structural phase; and performing continuous generation and flow expression modeling of the spatial semantics of streaming data throughout the entire lifecycle of the engineering project to generate a streaming data flow expression model for the entire lifecycle of the engineering project, completing a traceable flow expression of the spatial state of the concealed structural phase. This achieves continuous streaming data flow throughout the entire lifecycle, improves the digital management and safety assurance capabilities of engineering projects, and solves the problem of non-retrospective spatial flow after the closure of deeply buried structures.

The invention discloses an X-ray and NeRF algorithm-based luneberg lens internal structure analysis method, and relates to the technical field of three-dimensional imaging of optical lenses, and the method comprises the following implementation steps: S1, configuring an RGB-X-ray combined imaging system, and carrying out data acquisition, and S2, carrying out the calibration of external parameters of a camera through a calibration plate: carrying out the imaging through a specially-made calibration plate, and carrying out the calibration of the external parameters of the camera through the calibration plate. The method comprises the following steps: acquiring a plurality of frames of RGB (Red, Green, Blue) images to obtain external parameters of an RGB camera under a calibration plate coordinate system, acquiring a plurality of frames of X-ray images to obtain an external parameter matrix of an X-ray camera about the calibration plate coordinate system, performing implicit representation on a continuous field in a lens by utilizing NeRF, mapping three-dimensional coordinates to differentiable density and radiation values, and calculating the calibration plate coordinate system. According to the method, high-fidelity reconstruction from multi-angle X-ray projection to a three-dimensional structure is achieved, detail information in the lens can be effectively reserved, meanwhile, the continuity and symmetry of the structure are guaranteed, and compared with a traditional voxelization or CT reconstruction method, the problems that noise artifacts, fractures and unstable numerical values are likely to be generated in the traditional voxelization method are solved.

Methods and systems integrate digital fingerprint authentication-based identification and location tracking into a single, continuous process in which an authentication-integrated tracking system is simultaneously aware of both the identity and location of each physical object at all times as they move along a conveyance system. Insertion or removal of an object is quickly detected and reported. Rapid reestablishment and continuation of authentication-integrated tracking is enabled in the event of any temporary interruption or failure of tracking in the system. An exemplary system comprises plural tracking units networked together, each tracking unit including a camera or scanner to observe a corresponding field of view, the tracking units arrange to realize a continuous field of view of a physical conveyance system.

The embodiment of the invention provides an automatic driving scene mining method and device, equipment, a medium and a program, and the method comprises the steps: obtaining a mining demand text of an automatic driving scene; target scene features in the demand text are identified and mined, a database is inquired based on the target scene features, the database stores time sequence features related to the automatic driving scene, and the time sequence features are composed of feature frames at different moments; querying a target feature frame and a single-frame moment corresponding to the target scene feature from the time sequence feature, and querying at least one time sequence segment from the time sequence feature based on the single-frame moment of the target feature frame; and generating scene mining data of the automatic driving scene according to all the queried time sequence fragments. Therefore, the problems of low working efficiency, poor flexibility and expandability and the like caused by the fact that continuous scene fragments conforming to complex spatial-temporal logic cannot be efficiently, accurately and automatically mined from massive time series data due to dependence on manual rules and static retrieval in related technologies are solved.

The invention provides a broken shaft protection method for a circuitous wheel of an aerial passenger device, and relates to the field of coal mine safety monitoring. The problems that in the prior art, space-time alignment errors of multi-source data are large, a physical field is distorted, and real-time performance is insufficient are solved. Through dynamic graph structure modeling, heterogeneous sensors such as a vibration sensor, a temperature sensor, a displacement sensor and the like are mapped into space-time association graph nodes, edge connection is constructed based on spatial proximity and time synchronism, and continuity characteristics of an equipment structure are coded. And generating a three-dimensional continuous field and dynamically visualizing the three-dimensional continuous field through a ray casting volume rendering technology. According to the scheme, high-precision and high-real-time technical support is provided for broken shaft fault early warning.

The application discloses an F2 layer critical frequency continuous field reconstruction method and device, equipment and medium, and relates to the ionosphere space parameter prediction field, and comprises the following steps: adding a to-be-predicted space position as a node to an initial heterogeneous graph to obtain a target heterogeneous graph; processing the target heterogeneous graph through a preset graph attention network to obtain an F2 layer critical frequency prediction value corresponding to the to-be-predicted space position; the F2 layer critical frequency prediction value is a prediction value generated based on a scaling relationship between the F2 layer critical frequency and electron density; and performing a continuous field reconstruction operation based on a plurality of F2 layer critical frequency prediction values. Thus, the correlation of different discrete ionosphere sonde stations is utilized by the graph attention network, the F2 layer critical frequency is predicted in combination with the scaling relationship between the F2 layer critical frequency and electron density, the F2 layer critical frequency accuracy and the robustness under disturbance conditions can be improved, and the F2 layer critical frequency of any space position can be predicted, so that the reconstruction of the continuous space field is realized.

This application relates to the technical field of smart blackboards and discloses an interactive resource scheduling and optimization system for a blackboard, comprising a field mapping unit, a field solving unit, a topology unit, a control unit, and an instruction unit connected in sequence. The field mapping unit converts discrete interactive events into a continuous demand density distribution field and a resource capability potential field on the blackboard plane. The field solving unit dynamically obtains the current state of the demand density distribution field and the resource capability potential field by simultaneously solving a system of partial differential equations containing nonlinear coupling terms. The topology unit simultaneously optimizes the resource density distribution and the topology of the resource region by minimizing a preset energy functional. The control unit generates continuous control quantities for resource scheduling accordingly. The instruction unit finally converts these into a real-time sequence of underlying hardware control instructions. By introducing a spatially continuous field description, coupled dynamic system modeling, and topology optimization, the system improves the adaptive capability of resource scheduling, global optimization efficiency, and real-time response performance.

This application relates to a method, system, equipment, and medium for construction site environmental monitoring based on multi-source fusion. The method improves data reliability and consistency at the source by spatiotemporally aligning multi-source sensor data and innovatively calculating a real-time data quality factor to guide the weighted fusion of neighboring data. Furthermore, it uses physical constraints to repair missing values ​​and combines spatial interpolation to generate a refined environmental data cube covering the entire area, achieving data enhancement from discrete points to a continuous field. Finally, it extracts multi-dimensional features based on this cube and constructs a dynamic benchmark model combining construction stages and weather conditions for intelligent comparison and early warning. This fundamentally solves the problems of low data quality, information silos, and delayed early warning, achieving a comprehensive improvement in the reliability, panoramic perception capability, and forward-looking early warning of construction site environmental monitoring.

The invention discloses an IGBT (Insulated Gate Bipolar Translator) chip and a preparation method thereof, the IGBT chip comprises a P-type anode layer, an N-type field stop layer and an N-type substrate layer which are continuously arranged, and an active region, a transition region and a terminal region are arranged on the N-type substrate layer. The non-uniformly distributed field cut-off layer with low doping concentration is formed in the corresponding field cut-off layer of the active region and is matched with the high-concentration anode region, so that higher hole injection efficiency gamma, low conduction loss and better short-circuit tolerance of the chip are realized; the continuous field stop layer with high doping concentration is adopted below the transition region and the terminal region to be matched with the anode region with lower concentration, so that overcurrent failure caused by carrier concentration of the chip in the transition region when large current is turned off is avoided, and the large current turn-off capability of the chip under abnormal working conditions of overcurrent, short circuit and the like is further improved.

The application provides an AIGC card point editing method and system, solves the problems of audio and picture splitting, hard transition, lack of global planning and inability to complete when the material is insufficient caused by the dependence of the prior art on discrete beat point editing. The method comprises the following steps: constructing an audio energy field and a visual energy field based on background audio and video material respectively; establishing a two-field coupled partial differential equation, solving a globally optimal editing path, obtaining an editing point sequence and a segment allocation scheme; for the interval with a matching error exceeding a threshold, calling an AIGC to generate a supplementary video segment, and generating a transition frame sequence according to the visual energy field jump amplitude at the editing point; dynamically adjusting the playing speed according to the ratio of the energy field time gradient; finally, splicing and fusing the variable speed segment, the transition frame and the supplementary segment to output the card point video. The application realizes global optimization editing of continuous field coupling, and improves the card point precision and visual fluency.

The invention discloses a road and bridge construction asphalt pavement segregation layer thickness estimation method based on machine learning. The method comprises the steps that S1, an aligned multi-source nondestructive testing data set is obtained; s2, generating a complex spectral domain tensor; s3, obtaining an initial Fourier neural operator model; s4, obtaining an optimized Fourier neural operator model; s5, generating a thickness heat map, and marking an over-threshold region in the thickness heat map as a suspected segregation region; and S6, after a core drilling measurement result is obtained, comparing the measurement result with the suspected segregation area, triggering a Henry gas solubility optimization algorithm to perform optimization again, updating the Fourier neural operator model, and when the updated Fourier neural operator model converges, outputting a newest segregation layer thickness continuous field, a newest thickness heat map and a suspected segregation area list. And completing thickness estimation of the segregation layer of the asphalt pavement. According to the method, the identification accuracy and the spatial positioning capability of the abnormal thickness region are effectively improved, and a reliable technical basis is provided for rapid routing inspection and accurate reinforcement of a road surface.

The application provides a mine heavy metal pollution simulation prediction method and system based on digital twinning, relates to the technical field of digital twinning, and first acquires a multi-source environmental monitoring data set containing heavy metal concentration sampling values and spatial coordinate information of a target mine, injects the multi-source environmental monitoring data set into a pre-constructed mine digital twinning body, generates a discrete distribution of heavy metal concentration spatial scatter point sets in the digital twinning body according to spatial coordinate information mapping, then performs three-dimensional space continuous field reconstruction processing, generates a heavy metal three-dimensional distribution field, further calls a heavy metal migration and diffusion simulation model based on a physical process drive, performs multi-medium coupling migration and diffusion simulation on the three-dimensional distribution field in the digital twinning body, and generates a space-time evolution prediction result containing heavy metal space distribution prediction fields and pollution diffusion front advancing trajectories of future time periods. The application realizes deep fusion of monitoring data and physical simulation in the digital twinning body, and improves the accuracy of mine heavy metal pollution prediction.

The present application relates to the technical field of agricultural intelligent irrigation and precise pesticide application, and discloses a quantitative pesticide spraying system and method for standardized planting of traditional Chinese medicinal materials. A coordinate system and an equidistant sampling grid are established on the surface of a field, a capacitive soil humidity sensor is laid out and calibrated, real-time voltage data is accurately converted into the soil water content of the grid nodes, and four-point bilinear interpolation is used to realize the acquisition of the soil water distribution of the continuous field in the field. Based on the node difference calculation, the water content spatial gradient and the average gradient of the whole field are calculated, the area is divided according to the number of nozzles, the regional boundary is dynamically adjusted to ensure the data validity, and the average gradient of each area is extracted. Combined with the unit area pesticide spraying demand and the coverage area, the basic pesticide spraying volume is obtained, the adjustment factor is generated by linear mapping of the regional gradient and the global extreme value, the pesticide spraying volume is differentiated and controlled, and the boundary clamping is implemented, and finally the opening time is calculated according to the spraying speed, and the controller executes the operation in sequence.

The application provides a macro-micro conversion individual generation and trajectory fusion method of ghost car fleet vehicles, and relates to the technical field of intelligent transportation. The method comprises the following steps: in a target trajectory generation period in multiple trajectory generation periods, obtaining a traffic state label of a target traffic flow according to a continuous field quantity buffer of the target traffic flow; generating a micro vehicle according to the traffic state label, and obtaining a multidimensional state of the micro vehicle; fusing a target trajectory with the highest candidate weight in multiple candidate trajectories generated in a first area and a pre-acquired measured trajectory to obtain a completed trajectory; taking the completed trajectory and a micro vehicle trajectory as a vehicle trajectory generation result of the target trajectory generation period, and storing the vehicle trajectory generation result in a discrete individual quantity buffer; wherein the micro vehicle trajectory is generated according to the multidimensional state. Compared with a macro-micro conversion method of randomly scattering points, the method can reduce false speed waves and false queues, and improve the consistency of macro-micro conversion, data fusion accuracy and trajectory completion quality.

The invention discloses a water-wind-light complementary space-time scene generation method and device, and the method comprises the steps: discretizing a continuous state space of a multi-dimensional water-wind-light resource into a self-adaptive grid, and constructing a state transition probability matrix in an offline manner; in the online stage, a discrete state sequence is rapidly generated through Markov chain migration, and a continuous scene is reconstructed through kernel density estimation. A layered Markov switching model is introduced to capture long-period features, and smooth interpolation transition is adopted during macroscopic state switching. The device comprises a gridding module, a matrix construction module and a scene generation module, and supports a Z-order curve index and a compressed sparse row format to realize microsecond access. Compared with a traditional VAR iteration method, single-time long-period scene generation time is reduced from an hour level to a millisecond level, and calculation efficiency and scene quality are both considered.

The application discloses a kind of BIM3D-6D technology as pedestal's construction project whole process management system and method, it is related to construction project management technical field, including, through BIM lightweight computing server loads 3D building information model, extracts the space topological relation of geometric component and IFC semantic attribute, and the space topological relation of geometric component and IFC semantic attribute is carried out space topological analysis and semantic attribute mapping, generates three-dimensional data topological network package based on graph structure;Multi-dimensional deduction operation is carried out to three-dimensional data topological network package based on graph structure, obtains the deviation compensation strategy containing optimal cost control path;3D building information model is expanded through dimension and data fusion, generates 5D cost dimension data set.Mathematical transformation is used to convert discrete decision into continuous field model, so that resource flow path has spatial correlation and time continuity, and the beneficial effect of dynamic optimization construction process is achieved.

This invention relates to a time-domain electromagnetic simulation method based on Tree-Cotree decomposition and a hybrid DG-FE / SE domain decomposition. The method includes: dividing the computational domain into a tetrahedral finite element subdomain and a hexahedral spectral element subdomain according to geometric dimensions and electromagnetic properties; constructing a minimum spanning tree and cotree based on mesh edges to apply Gaussian divergence constraints; discretizing both the finite element and spectral element regions using scalar and vector basis functions to obtain Galerkin weak solutions; uniformly processing the interface between the finite element and spectral element subdomains using a topology identification-polygon decomposition-Gaussian integration method, and combining this with upwind flux to achieve continuous field transfer; assembling the spatial discretization matrix of the Galerkin weak solutions, and completing time propagation using an explicit fourth-order Runge-Kutta scheme. Compared with existing technologies, this invention systematically eliminates the low-frequency collapse problem, ensures the non-singularity of the system matrix, and guarantees solution accuracy and efficiency.

The invention provides a method and a device for rapidly generating crop growth vigor information, which are used for monitoring the regular growth vigor condition of crops by utilizing satellite remote sensing inversion and supporting the continuous monitoring of the field growth vigor of crops such as rice, corn, rape, citrus and tea and the monitoring of the growth state of the growth stage. The method comprises the following steps: firstly, performing time sequence optical image reconstruction and data space-time fusion on an obtained multi-temporal optical image to generate high space-time remote sensing data; then, remote sensing parameters related to crop growth are extracted from the high space-time remote sensing image, a plurality of parameters such as a normalized vegetation index and a normalized yellow difference index are calculated, a high space-time crop growth grid result is obtained, and under the spatial constraint of a crop vector plot, elements are converted into grids to serve as mask data; and performing mask extraction on a resampled high-space-time crop growth grid result to obtain spectral characteristics of a corresponding unit of crops, performing wave band set statistical calculation to obtain a growth index mean value of a certain crop, and obtaining a comprehensive evaluation result of the plot-level crop growth.