281 results about "Distribution diagram" patented technology

The application relates to the technical field of natural language processing, and particularly discloses a group risk cognitive consensus construction method based on risk metaphor, multi-source interactive texts are collected, and after extraction and filtration, an initial metaphor cognitive set is formed; a dynamic relationship network is constructed based on the set, responsibility is quantified as an attribute quantity transmitted between nodes, and a responsibility distribution graph is generated through iterative calculation; the transmission path is calculated, the dispersion and backtracking features thereof are quantified, and a quantitative analysis report for identifying a high-risk responsibility dilution path is generated; a responsibility anchoring coefficient is calculated according to the report, semantic reconstruction and iterative optimization are performed on the initial metaphor, and multiple candidate consensus expressions are generated; the robustness of the responsibility distribution under each candidate expression is tested by simulating an extreme cognitive bias and a long-time-span stress situation, and an expression that is most stable and satisfies responsibility convergence and traceability conditions is selected as an output of a final consensus framework; the application outputs a consensus framework with clear responsibility anchor points and anti-interference capability.

This invention discloses a method and system for real-time monitoring and optimization of biomass gasifier operating conditions based on machine vision and multi-source data fusion. The method includes: synchronously acquiring gasifier images and sensor data; dynamically generating a thermal field distribution map from temperature data to construct a multimodal dataset; pre-training a cross-modal Transformer and using the thermal field distribution map as a physical prior to guide attention to focus on the high-temperature region, obtaining a cross-modal encoder; constructing a repair adversarial network with a fixed encoder; and using a discriminator to fuse image features, sensor features, and the thermal field distribution map for adversarial collaborative discrimination to achieve unsupervised anomaly detection; inputting the anomaly region into an improved U-Net, initializing attention weights with the thermal field distribution map, and outputting a segmentation mask and morphological features; fusing morphological features and sensor data to output operating condition categories and triggering early warnings; and generating optimization parameters based on the early warnings and triggering incremental learning. This invention achieves accurate monitoring and adaptive control of gasifier operating conditions.

The application relates to a water quality change trend rapid prediction method based on multi-source data fusion and physical constraints, and specifically comprises the following steps: step 1: synchronously collecting data such as spectrum information, DO, COD, temperature and pH at key monitoring sites, constructing a water dynamics-water quality coupling equation, and simulating the space-time dynamic distribution of water quality parameters; step 2: outputting a water quality sensitive area through a water dynamics-water quality model, screening sensor layout points by combining information entropy evaluation and spatial clustering, realizing low-cost water quality sensor network deployment through a multi-objective optimization algorithm, and calculating a water body global water quality distribution map by adopting a spatial interpolation method; step 3: analyzing main pollution sources according to the synchronous collection of spectrum information at key monitoring sites, and adopting principal component analysis and an attention mechanism neural network; step 4: based on real-time optical characteristic value-DO data, combining a spatial topological network, a water quality gradient and a cross-region covariance to capture the spatial correlation of water quality parameters between different points, and constructing an optical characteristic value-DO-COD dynamic prediction model; combining pollution tracing and spectrum characteristic correction to correct the COD prediction value, adopting ensemble Kalman filtering to assimilate multi-source data, and improving the model accuracy.

The application discloses a wafer polishing laser interference closed-loop pressure control method, and relates to the technical field of semiconductor manufacturing, and comprises the following steps: S1: a ceramic plate is triggered to automatically measure a program after being turned over with a wafer; S2: a laser interference measurement head is driven by a six-axis mechanical arm positioning system to non-contact scan T2 / T4 points of the wafer, and thickness distribution data is acquired; S3: a Zernike polynomial is adopted to fit the thickness distribution data to generate a three-dimensional distribution graph, and a pressure correction amount is calculated based on a pressure prediction model constructed by a process kinetics model and a support vector machine regression algorithm; S4: an abnormal processing module is used to detect data outliers in real time, and a device protection strategy is triggered when a deviation exceeds a set threshold; and S5: a pressure control instruction is transmitted to a polishing head by a PLC controller through a PROFINET bus. By means of non-contact laser interference measurement, the laser interference technology is applied to wafer thickness detection after polishing for the first time, and single measurement time is less than 20 seconds, so that the detection efficiency is significantly improved.

The present disclosure provides cathode material, preparation method therefor and battery. The cathode material is a monocrystalline cathode material, which has a chemical formula of LiaNixMyNzO2, where 0.98≤a≤1.05, 0.60≤x<1, 0<y≤0.40, 0≤z<0.1, x+y+z=1; a distribution curve of particles with a particle size ranging from 1 μm to 4 μm has a peak consistent with distribution of a Pulse function and a particle size distribution width of the particles is Span (a) and satisfies that 0.8<Span (a)<1.6; and in a particle size quantity distribution diagram of the cathode material, a distribution curve of particles with a particle size ranging from 0.1 μm to 1 μm and excluding 1 μm has a peak consistent with distribution of a Voigt function; and a particle size distribution width of the particles is Span (b) and satisfies that 0.4<Span (b)<0.8. The cathode material of the present disclosure can achieve higher capacity and rate performance.

The application provides a kind of visual construction management method and system, belong to construction management field.Therein, the method includes: the standardization processing of the multi-source laminated data in construction display area is carried out, and the standardization data structure is constructed;The laminated feature vector of standardization data structure is extracted;According to laminated feature vector, the conflict field calculation of any two laminated in construction display area is carried out, and the laminated conflict intensity distribution diagram is generated;The conflict field feature of laminated conflict intensity distribution diagram is extracted, and the conflict clustering output multiclass conflict level area is carried out;The differential fusion strategy analysis of multiclass conflict level area is carried out, and the multiclass visual fusion expression is obtained, according to multiclass visual fusion expression, visual output management is carried out in construction display area.The application carries out laminated conflict quantitative analysis and differential adaptive fusion, so that multi-source laminated data is clearly and accurately expressed in the same construction display area, and information conflict and expression distortion are eliminated.

This invention discloses a wellbore structure design method and apparatus based on the minimum business unit. The wellbore structure design method includes: obtaining the minimum business unit corresponding to the wellbore structure, wherein the minimum business unit includes configured data resource retrieval rules, tool resource invocation rules, and application scenario affiliation rules; retrieving the corresponding mapping component based on the tool resource invocation rules; extracting the corresponding dataset from a preset data lake based on the data resource retrieval rules; drawing a wellbore structure atlas in a preset drawing area using the mapping component based on the dataset, wherein the wellbore structure atlas includes at least well depth lines and annotations, a formation distribution map, a drilling fluid density distribution map, and a wellbore structure map; and pushing the wellbore structure atlas to a designated file library in the data lake based on the application scenario affiliation rules. This method can solve the problem of difficulty in sharing results and improve the efficiency of wellbore structure design.

This invention relates to the field of single-axis robot technology, and more particularly to an intelligent single-axis robot anomaly monitoring system. The system first acquires mechanism dynamics model data and simultaneously collects real-time monitoring data from the transmission system and the multi-force sensor nodes at the motion execution head. Second, it performs collision identification processing on the data, generating a collision anomaly feature distribution map matching the model's spatial position. Subsequently, combining the map with long-stroke motion constraints, it dynamically and visually reconstructs the dynamics model, outputting an interface with anomaly level markers. Finally, it associates and maps the visualization interface with the real-time data to generate emergency protection and maintenance strategies, triggering a robot protection response through an industrial control port. This invention achieves high-precision positioning and hierarchical visualization of collisions at the motion execution head of a long-stroke single-axis robot, constructs a closed-loop intelligent protection mechanism, and significantly improves equipment safety protection capabilities and operational efficiency.

This invention relates to the field of iron and steel metallurgy technology, and discloses a digital short-process steelmaking quality prediction method and system. The method includes: acquiring standard temperature deviation data and standard chemical fluctuation data; obtaining an initial disturbance distribution map using a correlation propagation model; constructing a global coupling matrix through graph structure mapping; determining the disturbance accumulation trend through time-series analysis and fusing it with chemical fluctuation analysis to obtain a fluctuation state identifier; adaptively correcting the global coupling matrix based on the fluctuation state identifier to obtain an optimized description of the disturbance influence range; and finally determining the final quantified value of steel quality by combining quality index mapping logic. This invention achieves accurate quantification and forward-looking prediction of the dynamic propagation and nonlinear accumulation effects of disturbances in short-process steelmaking by dynamically correcting the coupling matrix.

Embodiments of the present application disclose a method for determining the number of effective particles, the method comprising: obtaining the total number of particles of a detection sample and pulse signals of each particle; performing waveform feature analysis based on the pulse signals to obtain waveform feature parameters of each particle, the waveform feature parameters at least including: a waveform feature type of the particle and a waveform feature value corresponding to the waveform feature type; generating a feature parameter distribution map of the particles in the detection sample according to the waveform feature type of each particle and the waveform feature value corresponding to the waveform feature type; determining an effective area of the feature parameter distribution map and the number of effective particles in the effective area. The waveform feature parameters of all the particles in the detection sample are counted to obtain the feature parameter distribution map, and the number of effective particles in the effective area of the feature parameter distribution map is further obtained, so that the number of particles that are misdetected as effective particles and not in the effective area is excluded, and a more accurate number of effective particles is obtained.

The present application relates to the field of engineering detection technology, in particular to a deep compaction degree nondestructive testing method and system for large-thickness water-stable base course. A multi-source heterogeneous dataset of a to-be-detected area is obtained using an integrated detection device; a construction process compliance index and a process uniformity index of the to-be-detected area are obtained; each data source in the multi-modal nondestructive testing data is deeply corrected to obtain a deep correction compaction degree estimation set of each data source; the deep correction compaction degree estimation set of each data source is input into an adaptive weight fusion model to obtain a preliminary compaction degree distribution map; a fusion compaction degree distribution map of the to-be-detected area and a dynamic confidence score of each spatial point are calculated; the compaction quality of the to-be-detected area is determined, and a detection strategy optimization instruction is generated for the area with a confidence score lower than a confidence threshold. The present application can realize high-precision, high-confidence and engineering-actual nondestructive testing of deep compaction degree of large-thickness water-stable base course.

The application discloses a fault scanning control method and device, a fault scanning equipment and a storage medium. The method comprises the following steps: identifying a key anatomical structure of an initial projection image based on a pre-trained trajectory planning model, generating a probability distribution map, determining a sparse scanning angle sequence and corresponding first scanning parameters, densely sampling and appropriately increasing a radiation dose in a high-weight area, and sparsely sampling and reducing a dose in a low-weight area; controlling the fault scanning equipment to perform scanning, obtaining first projection data and reconstructing the first projection data into a sparse reconstruction image; performing multi-modal fusion and scoring on the sparse reconstruction image and the current scanning parameters through an image quality evaluation model, adaptively optimizing scanning instructions according to the probability distribution map, a fusion feature vector, an image quality score, an equipment state and historical action data, generating second scanning parameters, making the scanning trajectory more continuous and smooth through an artificial intelligence technology, and realizing regional adaptive regulation and control of angles, doses and paths, so that the imaging resolution can be improved.

The application relates to the technical field of data asset exploration, in particular to a data asset intelligent exploration method and system based on a knowledge graph, which comprises the following steps: acquiring enterprise data assets and dynamically labeling to generate a labeled data set; performing semantic analysis based on the labeled data set to obtain a semantic correlation graph; constructing a knowledge graph model, calculating node weights, correlation path lengths and path contribution degrees, and generating a simulated correlation distribution graph; segmenting the semantic correlation graph through node density and relationship strength to obtain an actual correlation distribution graph; and adjusting the knowledge graph model based on the actual and simulated correlation distribution histograms. The application can improve the intelligent level and accuracy of data asset exploration.

The application relates to the technical field of image recognition, and discloses a packaging box damage degree online detection method and system based on image recognition, which comprises the following steps: carrying out spatial phase unfolding on a package phase diagram to obtain an absolute phase distribution diagram; generating a surface geometric deformation phase diagram; carrying out spatial alignment on the surface geometric deformation phase diagram to obtain local three-dimensional point cloud data; taking points with a normal vector mutation exceeding a preset threshold value in the local three-dimensional point cloud data as potential damage edge points, and marking points with a maximum principal curvature and minimum principal curvature difference exceeding a preset threshold value as potential deformation points; taking the potential damage edge points as seed points and taking the potential deformation points as growth constraint conditions to iteratively grow in the local three-dimensional point cloud data, and clustering points with continuity and similar geometric mutation characteristics into a damage area; and outputting a damage judgment result according to geometric parameters of the damage area; and the application can improve the efficiency of the packaging box damage degree online detection based on image recognition.

This invention discloses a method for compiling mineralization center distribution maps based on the spatial distribution patterns of anomalous elements. The method involves collecting stream sediment data from the work area, performing principal component analysis, and extracting principal components with eigenvalues ​​greater than 1. It also distinguishes between medium-high temperature element combinations and medium-low temperature element combinations; calculates the mineralization center factor M; and calculates the outlier value M of the mineralization center factor. c Import the mineralization center factor M into the ZScape software and draw a contour map of the mineralization center factor in the working area; use the outlier value M of the mineralization center factor. c Create a mineralization center distribution map for the boundary; M≥M c The region is represented as the mineralization center; M≤M c The region is represented as the mineralization edge; based on the relationship between elemental zoning and temperature in stream sediments, this invention constructs mineralization center factors for magmatic-hydrothermal related deposits, realizes the quantitative compilation of mineralization center distribution maps, and innovates a new model for map compilation.

The application provides a whole vehicle external flow field joint prediction method based on double-flow fusion and multi-head graph attention, and relates to the technical field of vehicle dynamics analysis. The steps of the method comprise receiving a three-dimensional discrete point set of the whole vehicle shape; constructing a residual feature enhancement network to obtain a geometric high-dimensional feature vector; constructing a coordinate embedding network to obtain a high-dimensional coordinate embedding feature; adaptively weighting and fusing the geometric high-dimensional feature vector and the high-dimensional coordinate embedding feature; constructing a directed graph based on a k-nearest neighbor algorithm, splicing the aggregated features output by the multi-head, and obtaining global coupling features; inputting the global coupling features into a parallel first prediction branch and a second prediction branch; the first prediction branch outputs a three-dimensional pressure coefficient distribution map of the vehicle body surface through point-by-point regression; the second prediction branch fuses the global coupling features and key section embedding features, obtains section flow field prediction values through point-by-point regression, and outputs a key section two-dimensional flow field map.

The application provides a far-infrared-based polyester filament spectral reflectance detection method, and belongs to the technical field of polyester filament spectral reflectance detection. The method comprises the following steps: obtaining enhanced spectral data of a polyester filament sample; performing feature band extraction, calculating a correlation matrix, and obtaining a high-dimensional spectral feature vector; constructing a polyester filament spectral reflectance three-dimensional simulation model, and obtaining a spectral energy distribution diagram; performing matching degree verification, and obtaining a pre-judgment matching index; analyzing a spectral shift type, and obtaining a reflectance defect classification standard; constructing a reflection mode parameter data set, extracting a feature coincidence degree parameter, inputting the feature coincidence degree parameter into a random forest algorithm, and determining a reflectance anomaly grade; and generating a spectral reflectance detection report. The application positions an abnormal interval through three-dimensional simulation simulation, establishes a quantitative correlation between spectral anomalies and process parameters to realize tracing, generates a standardized defect classification and process optimization suggestion to form a closed-loop management and control, can be adapted to detection of multiple types of synthetic fibers, and effectively improves production quality management and control level.

This invention provides a short-term traffic conflict prediction method and early warning system based on RSU group collaboration and spatiotemporal graph neural network. It acquires vehicle trajectory and status data collected collaboratively by roadside unit groups, using the coverage area of ​​each RSU as a spatial analysis unit, and constructs an initial energy field distribution map of traffic conflict based on the spatial density of vehicle distribution and the intensity of speed temporal fluctuations. A pre-constructed spatiotemporal graph neural network is invoked to capture energy transfer paths between units, and a temporal cyclic layer is used to capture the energy change inertia within units, predicting and generating a dynamic evolution map of traffic conflict energy containing an energy evolution path network and peak times. Based on the map, potential conflict outbreak sources and expected affected unit sequences are identified, generating conflict propagation situation prediction information including spatial coordinates and propagation time sequences. Based on this information, differentiated collaborative working mode adjustment instructions are generated and distributed to each RSU. This invention achieves short-term prediction of traffic conflicts and collaborative scheduling of roadside resources.

The application provides an intelligent interaction experience optimization method and system combined with emotional computing, and belongs to the technical field of intelligent interaction. First, original behavior data flow during multi-round task conversation of a user and a smart terminal is collected, including interface touch pressure distribution trajectory, voice instruction frequency spectrum feature sequence and eye gaze heat map change record. Then, the interface touch pressure distribution trajectory and the eye gaze heat map change record are double-mode fusion coded to generate an operation intention focus area distribution graph. The space emotion distribution atlas is obtained by superimposing the voice emotion color label, and the emotional negative experience blind area is identified therefrom. Finally, interface element strengthening prompt instructions are generated according to the blind area position, the blind area interface element is triggered to visually protrude, and the intelligent interaction experience is optimized.

This invention provides a method and system for automatically extracting material elements from scientific and technological literature based on a large language model, belonging to the field of materials science and technology literature data extraction. First, this invention automatically parses documents of different formats to obtain hierarchical documents. Then, based on the large model, it locates all performance names and values ​​related to the target in the entire text using prompt words. Next, based on all performance values, it extracts relevant material composition and process information using prompt words, simplifying the complex extraction task and improving the extraction scope and accuracy, forming structured data containing all elements. Finally, through visualization processing of the complete dataset, it generates an element data distribution map. This invention achieves automatic extraction of target-related material elements from scientific and technological literature with high extraction accuracy and recall, requiring no manual labeling. This method is applicable to data extraction from scientific and technological literature in the field of materials science.

The application discloses a radio frequency fascia layer thermal effect lifting system and method based on an anti-gravity vector, and belongs to the technical field of skin care and beauty. An initial impedance distribution diagram of a target skin area is acquired, a detection radio frequency wave is emitted, and a relative dielectric constant offset of a fascia layer relative to an epidermis layer and a dermis layer is extracted from a reflected wave signal. The offset and a depth arrangement order are input into an anti-gravity vector calculation unit, an anti-gravity vector sequence is calculated and generated, radio frequency waveform parameters matched with the vector sequence are called from a waveform database, and are loaded to a phase control array. The surface temperature and impedance changes of the target skin area are monitored in real time, impedance fluctuation feedback values are generated, and the beam pointing adjustment parameters in the subsequent anti-gravity vector are dynamically corrected accordingly until the thermal effect area construction of all target points is completed. The application accurately controls the radio frequency beam pointing through the anti-gravity vector, realizes accurate and orderly heating of the subcutaneous fascia layer, and has self-adaptive correction capability.

This application discloses a fire early warning method based on multidimensional forest health status analysis, belonging to the field of forest fire prevention technology. The method includes: acquiring multidimensional observable data for each assessment unit in a target forest area; inputting the multidimensional observable data into a pre-constructed hybrid prediction model, outputting a comprehensive flammability risk index for each assessment unit within a specified future time period, and generating a visualized spatiotemporal distribution map on a GIS map; wherein the hybrid prediction model calculates the flammability probability of each tree species using a single-tree physical mechanism model, obtains a stand risk index using a spatial weighted aggregation algorithm, outputs a landscape-level probability through a landscape-level risk prediction network, and performs weighted fusion of three sources of uncertainty based on traditional empirical paths; and issuing early warning information based on the spatiotemporal distribution map. This application combines physical mechanisms with transfer learning to achieve rapid adaptation with few samples and accurate prediction at multiple scales, providing reliable decision support for forest fire prevention.

This invention relates to the field of structural health monitoring and non-destructive testing technology, and discloses a method and system for damage detection of carbon fiber concrete. The method includes acquiring and filtering an initial resistivity value, simultaneously collecting temperature and humidity sequences to construct a coupled environmental dataset; constructing an environmental interference model to correct the resistivity based on this dataset; if the corrected resistivity fluctuation exceeds a threshold, analyzing the temperature and humidity coupling effect and extracting the dominant signal features; mapping to a spatial grid to obtain an initial damage region, and generating a spatial distribution map through accuracy improvement and hierarchical mapping; extracting signal features and then clustering and weighting to obtain a quantitative damage assessment value; finally, comprehensively mapping to generate a damage characteristic distribution map. This invention can effectively distinguish between environmental interference and actual damage, improving the accuracy and visualization effect of micro-crack detection in carbon fiber concrete.

The application relates to the technical field of whole-process tracing, and particularly discloses a culture medium whole-process tracing system for GMP compliance. The application calculates a dynamic performance score based on historical supply data of a supplier to oneself, and when detecting that a supplier qualification is close to an expiration date or the dynamic performance score of the supplier exceeds a warning time limit, the application automatically freezes a new order and triggers a procurement task by an intelligent contract, thereby realizing front-end control of the quality of the supplier; the application compares a defect distribution diagram of a quality inspection management module, equipment alarm records of a production management module and a dynamic performance score of a supplier management module of the supplier, calculates responsibility probabilities of all links by applying a Bayesian network, and outputs a quantifiable responsibility determination report, so that artificial experience errors are eliminated to a certain extent; and the application constructs a graph database forward tracing chain and a reverse tracing chain, can quickly query all finished product batches using the raw material and a customer list, and has a fast recall response.

The application relates to the technical field of touch screens, and discloses a self-adaptive tactile feedback method and system for a touch screen. The self-adaptive tactile feedback method for the touch screen comprises the following steps: acquiring a contact pressure distribution data set; determining a compact contact area; locating a peak point of a contact pressure distribution map, and calculating an offset vector of the peak point relative to a geometric center of the compact contact area; establishing a polar coordinate system and dividing a sector analysis area according to the peak point and the offset vector, and acquiring a pressure attenuation gradient value and a pressure mirror similarity of the compact contact area according to a pressure data sequence; determining a contact position of the compact contact area according to an offset distance, the pressure attenuation gradient value and the pressure mirror similarity, and generating a corresponding contact position label; and matching a corresponding tactile feedback mode according to the contact position label. The scheme can solve the problem of low contact position recognition accuracy of the touch screen, and further improve the matching degree of the feedback mode of the touch screen and the user's intention.

The application discloses a kind of automatic control method and equipment for sweet potato seedling seedling pipeline operation, it utilizes differential pulse modulation to collect the excited state and background state image of vine, through space self-adaptive weighted difference modeling and non-local mean regularization enhancement technology, effectively suppress environmental light noise and retain weak biological fluorescence signal, to generate the high confidence vine node distribution map.On this basis, abandon traditional fixed-length cutting mode, construct dynamic programming model based on agronomic constraints, solve the optimal segmentation strategy of maximum output rate in the whole vine range.Finally, through the space-time fusion of visual coordinates and conveyor encoder, drive multi-axis servo system to track and accurately work the real-time virtual cutting point of dynamic movement, realize the efficient, low-loss automatic production of sweet potato seedling.

The embodiment of the present application provides a transformer defect positioning method, system and storage medium, the method comprises: obtaining the first operation information of the digital twin model of the suspected abnormal transformer, generating defect diagnosis result information in the digital twin model of the transformer according to the first operation information; the generation method of the defect diagnosis result information comprises: obtaining the type number information and the equipment position information of a plurality of high-voltage equipment in the region preset according to the transformer, and determining the radiation region data according to the type number information and the equipment position information; according to the corresponding phase distribution diagram, the amplitude / time trend data, the radiation region data and the position information of the partial discharge sensor of the transformer, the partial discharge reason information and the partial discharge position information are determined; the defect diagnosis result information is determined according to the partial discharge reason information and the partial discharge position information. Through visual man-machine operation, only one click on the abnormal transformer can accurately obtain the defect diagnosis result through the background.

This invention discloses a method and system for identifying the spatial distribution of accumulated water based on multi-classifier collaboration. The method includes: constructing a hierarchical classifier library comprising a preliminary screening layer, an arbitration layer, a re-identification layer, and a verification layer, with each layer containing multiple classifiers of different types. First, the preliminary screening layer performs coarse classification on UAV images, and the results of each classifier are fused using a logical OR operation to determine suspicious areas. Then, the arbitration layer and the re-identification layer sequentially perform refined identification of ambiguous areas, using a logical AND operation to obtain high-confidence accumulated water areas. For the remaining ambiguous areas, the verification layer is activated for final discrimination. The high-confidence accumulated water areas identified by each layer are merged to form a preliminary accumulated water distribution map. Pixel confidence is optimized through weighted fusion, and low-confidence pixels are removed. Finally, post-processing is performed to output the final spatial distribution result of the accumulated water. This application can effectively improve the identification accuracy and robustness of small and irregular accumulated water areas in complex urban scenes.