16 results about "Coverage density" patented technology

The invention discloses a geological structure three-dimensional reconstruction and analysis system based on multi-modal data fusion, and relates to the technical field of geological exploration information. The method comprises the following steps: acquiring and normalizing multi-source heterogeneous geological observation data through a preprocessing module, and generating basic data and a data coverage density map; the adaptive fusion module performs analysis to generate a dynamic adaptive weight field, and performs weighted fusion on the data to obtain a primary three-dimensional geological data volume; the construction and optimization module constructs a three-dimensional space residual field in a vector form based on the difference between the fusion body and the original data, and deduces the geometric morphology of the geological interface; the reconstruction module ensures the consistency between model layers through hierarchical bidirectional belief propagation processing; the quantification module calculates an uncertainty index; and the visualization module finally generates a three-dimensional geological scene. According to the method, the problems of conflict resolution and reliability evaluation in multi-source geological data fusion are effectively solved, and the precision of the three-dimensional geological model and the engineering decision support capability are improved.

The invention provides a wetland ecological restoration effect comprehensive evaluation method and system, and belongs to the technical field of big data analysis. According to the method, real-time data of multi-dimensional ecological elements such as water turbidity, vegetation coverage density and soil acidity and alkalinity are collected, a multi-dimensional element correlation matrix based on time sequence correlation is constructed, and the dynamic change frequency of each element is captured. Core influence factors are screened by quantifying the contribution degree of each element to ecological restoration, weight distribution corresponding to clustered element clusters is determined, and then an accurate quantitative score is generated and mapped into a clear restoration condition level through multiplication and summation of inter-cluster correlation coefficients and weights item by item. Meanwhile, an evolution track is compared and analyzed by combining historical time sequence data, and the weight is dynamically adjusted to ensure that evaluation adapts to an actual repair process. The comprehensive, dynamic and accurate evaluation of the wetland ecological restoration effect is realized, scientific support is provided for the accurate adjustment of the restoration strategy, and the fine management of the wetland and the sustainable development of the natural environment are guaranteed.

An image collection method and an image capturing device. The method comprises: obtaining first coverage density data of one or more first images based on captured first images of a target object to determine one or more re-shooting positions; rendering one or more shooting position suggestion marks corresponding to the one or more re-shooting positions in an image corresponding to a real space displayed in real-time by the image capturing device; and when a current position and a current viewing angle of the image capturing device match a target shooting position suggestion mark, automatically capturing a target second image corresponding to the target shooting position suggestion mark toward the target object. Thereby, the present disclosure provides a method that can effectively guide users to complete image collection required for 3D object modeling.

This invention provides a dust pollution detection method and system based on image recognition, belonging to the field of image processing technology. The method includes: acquiring a group of dust images of a region to be detected, and determining a target image from the dust image group based on a preset filtering rule; performing preprocessing on the target image to obtain a binarized dust image; determining an improved grayscale mean to characterize the global coverage density of the dust based on the binarized dust image, and determining a fractal dimension to characterize the local morphological complexity of the dust using an improved box counting method based on the binarized dust image; constructing a pollution factor based on the improved grayscale mean and the fractal dimension, and assessing the dust pollution level based on the pollution factor. This invention achieves a rapid, stable, and structurally discriminative quantitative assessment of dust pollution status in semi-enclosed environments such as tunnels.

The present application relates to the technical field of underground pipe network monitoring and early warning, and particularly relates to an underground pipe network partition visualization and safety early warning method and system. The method comprises: obtaining a map service source, an underground pipeline service, GIS data, a BIM model, equipment data, historical monitoring data, historical maintenance records, inspection logs and accident reports, performing data alignment and data standardization processing to obtain pipe network topology structure information; performing key node, valve, connection relationship and monitoring coverage density correlation processing to obtain partition objects; performing connection processing to obtain multi-source heterogeneous monitoring data, and performing time sequence feature coding, spatial feature coding, semantic text data feature coding and cross-modal fusion processing to obtain fusion feature vectors; and then performing confidence interval, intelligent alarm instruction, mutation alarm instruction, maximum clustering distance and connection relationship joint processing to obtain correlation alarm state information. The present application can effectively improve the accuracy and timeliness of safety early warning.

The invention relates to an RGB terrain loading method and device for Cesium and electronic equipment. The method comprises the steps of converting RGB tile data into height data, generating a geometric error graph based on the height data, screening out control points from the geometric error graph, generating a terrain triangulation network based on the control points, and performing terrain drawing according to the terrain triangulation network. The control points are screened out from the generated geometric error graph, and the more accurate terrain triangulation network is generated based on the screened control points, so that the defect of data distortion in the prior art is overcome, in addition, the coverage density is improved by increasing the number of the terrain triangulation networks, the inclination angle between the terrain triangulation networks is reduced, and the accuracy of the terrain triangulation network is improved. Therefore, the problems of sharpness and unsmooth transition of the existing triangulation network are solved.

The invention provides a nanometer quick-freezing fresh-locking method based on a superposed space electric field, and relates to the technical field of freezing fresh-locking, and the method comprises the following steps: obtaining a three-dimensional space arrangement of muscle fibers in a nanometer quick-freezing liquid, and identifying a fiber arrangement included angle and a fiber coverage density of the muscle fibers, collecting the initial electric field direction of the superposition space electric field and the polarization intensity of each area to obtain a polarization intensity mean value; determining a one-way electric field coverage rate according to whether the fiber arrangement included angle exceeds a preset one-way electric field coverage range threshold value or not, and determining polarization intensities of fibers with different orientations according to the one-way electric field coverage rate and the fiber coverage density; and an electric field switching period is generated based on the adjusted polarization intensity distribution, the difference value change trend of the energy storage value in the fiber and the energy storage value in the fiber gap after the electric field switching period is executed is analyzed, the balance degree of energy storage inside and outside the fiber is evaluated, and whether cold energy storage exceeds a preset range or not is monitored.

This invention belongs to the field of agricultural image processing technology and discloses a sensor distribution optimization method, a plant stem diameter measurement method, and a device for optical tomography of plant stems. The optimization method mainly involves determining the optimal detection range, and then measuring the plant stem diameter within this range. The specific steps are: 1. Acquiring the background light signal without placing the plant; 2. Acquiring the light signal from the plant stem; 3. Constructing a projection data matrix, obtaining the column vector of the projection data matrix through the background light signal and the plant stem light signal; 4. Performing image reconstruction to obtain a cross-sectional image of the plant stem; 5. Filtering and thresholding the cross-sectional image, calculating the total gray area, and then calculating the equivalent diameter of the plant stem using the total gray area. This method not only improves the light coverage density and distribution uniformity of the measurement area but also enhances measurement accuracy.

This invention provides a method for scene reconstruction and automatic correction using unmanned aerial vehicles (UAVs), belonging to the field of scene reconstruction and correction technology. It involves comprehensive data acquisition across different sub-regions, synchronously recording flight trajectory information for each round, and aligning sensor data with timestamps. A dynamic error compensation model is constructed, combining the dynamic parameter set of each round of random flight by the UAV to correct motion blur, environmental interference, and trajectory deviation errors in the acquired data. The corrected multi-round data is integrated to establish a spatial mapping between sub-region textures and point clouds, generating an initial 3D model. A closed-loop correction mechanism is constructed based on the UAV's GNSS absolute coordinates and high-precision ground control points to calculate the deviation of the initial 3D model. If the deviation exceeds a threshold, the random flight coverage density, flight rounds, and error compensation coefficients are adjusted in reverse until the deviation meets the standard. This improves the accuracy of scene reconstruction and correction.

The invention discloses a monitoring point layout method, device and equipment, a medium and a product. The method comprises the following steps: acquiring a monitoring point data set and an event data set corresponding to a target area; determining a monitoring thermal grid map corresponding to the target area according to the monitoring point data set; the monitoring heating power is used for representing the coverage density of monitoring points in the grid units; determining an event thermal grid map corresponding to the target area according to the event data set; the event heat is used for representing the risk level intensity of the event occurring in the grid unit; performing intersection negation operation on the monitoring thermal grid map and the event thermal grid map to obtain a to-be-monitored area corresponding to the target area; and determining a monitoring point layout scheme corresponding to the target area according to the to-be-deployed and controlled area. Through the technical scheme of the invention, the monitoring point location layout can be optimized based on the thermal grid map, and the event risk area is reasonably covered while the investment of redundant equipment is reduced.

The invention provides a design method, system, equipment and medium based on a residual gas well underground combined mining three-dimensional observation system, and belongs to the technical field of petroleum geophysical exploration. According to the method, aiming at the problems of complicated geological conditions and insufficient resolution of a conventional observation system in residual gas exploration, observation points are arranged by comprehensively analyzing geological condition factors and technical parameters of the observation system and adopting a multi-dimensional optimization strategy. The method specifically comprises the following steps: constructing a fitness function based on wave field energy coverage maximization, reflection interface coverage and geological parameter mean square error minimization, and carrying out adaptive observation point position design; according to the dimension difference of well-ground combined mining, ground excitation points are finely adjusted to make up a well periphery covering density gap; and on the basis of a static correction principle, according to topographic relief and reservoir heterogeneity characteristics, excitation and receiving parameters are adjusted in a partitioned manner. The method can effectively improve the signal-to-noise ratio and imaging precision of seismic data under complex geological conditions, accurately depicts the residual gas distribution, and improves the exploration efficiency.

The invention discloses a method and system for constructing a space-air-ground three-dimensional cooperative monitoring network system, and relates to the technical field of environment monitoring, and the method specifically comprises the following steps: dividing a monitoring grid aggregation task coordinate calculation density interpolation assignment generation block, correcting a coverage radius to normalize a node attribute generation capability list, and generating a monitoring grid aggregation task coordinate calculation density interpolation assignment generation capability list; screening efficient nodes to construct cost matrix bilateral matching, extracting feature vectors, calculating distances, identifying redundant nodes, removing redundancy, and supplementing candidate output space-ground-air collaborative configuration tables. According to the method, the monitoring block is dynamically generated based on the geographic grid, the coverage radius is corrected in combination with the node direction and the hot area distance, the normalization ability list is constructed, the task grid and the node are matched through the Hungary algorithm, the cost matrix is constructed to recognize the redundant node, self-adaptive matching of the node block is achieved, the resource allocation efficiency is improved, and parameter dependence is reduced; the monitoring blind area is reduced, the coverage density and the energy consumption level are balanced, and the emergency response sensitivity is enhanced.

The application provides a seismic visual early warning method combining monocular depth estimation and an optical flow method. The method realizes inversion of ground acceleration at a base of a street lamp type device by fusing monocular depth estimation and a robust optical flow algorithm suitable for a traffic scene, and can construct a distributed seismic monitoring network based on inversion data, solves the industry pain points of high deployment cost and insufficient coverage density of a traditional seismograph, and provides a high cost-effective solution for city-level earthquake early warning.

The embodiment of the invention provides a dust pollution detection method and system based on image recognition, and belongs to the technical field of image processing. The method comprises the following steps: acquiring a dust image group of a to-be-detected area, and determining a target image from the dust image group based on a preset screening rule; performing preprocessing on the target image to obtain a dust binary image; determining an improved gray average value used for representing the global coverage density of the dust based on the dust binary image, and determining a fractal dimension used for representing the local form complexity of the dust by adopting an improved box counting method based on the dust binary image; and constructing a pollution factor based on the improved gray average and the fractal dimension, and evaluating the dust pollution level according to the pollution factor. According to the scheme provided by the invention, the dust pollution state of the tunnel type semi-closed environment can be rapidly and stably quantitatively evaluated with structural discrimination.

The invention relates to the technical field of intelligent detection, in particular to an unmanned aerial vehicle cluster scanning method for autonomous detection of road invisible cracks, which comprises the following steps of: according to a scanning task block, identifying a track curvature mutation point and an attitude angle jump interval, extracting a flight direction and attitude angle change curve, and analyzing spatial orientation consistency; screening out blocks deviating from the course, analyzing image coverage density and course overlapping rate, screening out blocks with abnormal matching, evaluating elevation change trend and deviation degree, and outputting an unmanned aerial vehicle cluster dynamic re-planning instruction set. According to the invention, a dynamic flight path and attitude angle recognition mechanism is introduced to ensure that the scanning task still has high accuracy in a complex environment, and the flight path between task blocks is dynamically adjusted by analyzing the flight direction vector and attitude angle change to ensure that the image coverage is uniform, and the scanning accuracy and integrity are improved. The cluster scanning cooperation efficiency can be evaluated in real time, and the task execution efficiency and accuracy are remarkably improved.

The invention provides a road bridge bearing capacity detection method and device. The method comprises the following steps: identifying stress wave propagation characteristics of sensing paths in stress wave propagation data of stress wave sensors on a target road bridge; determining the coverage density of all sensing paths to the detection area, and determining the speed confidence of the stress wave of each detection grid unit according to all stress wave propagation characteristics, the coverage density and the stress wave propagation time in each stress wave propagation data; determining the speed distribution characteristics of the stress waves in the target road bridge detection area according to the speed correlation characteristics of the stress waves between the adjacent detection grid units and all the speed confidence coefficients; and distinguishing a healthy area, a bearing capacity attenuation area and a dangerous area of the target road bridge based on the speed distribution characteristics of the stress waves. By adopting the scheme of the invention, the bearing capacity of the road bridge can be detected based on the intrinsic mechanical association and performance conduction characteristics of the road bridge.