83 results about "Scatter plot" patented technology

The present application relates to the technical field of combustion state monitoring, and discloses a visual analysis method and device for combustion simulation, which comprises the following steps: under different initial conditions of combustion simulation, generating multiple sets of time sequence flow images for each combustion simulation example; encoding each frame of image in each set of time sequence flow images to obtain corresponding multiple high-dimensional embedding vectors; generating a scatter plot after dimension reduction of the multiple high-dimensional embedding vectors after dimension reduction clustering, and generating multiple time sequence trajectories for each combustion simulation example based on the scatter plot after dimension reduction; searching for a similar time sequence trajectory most similar to a specified time sequence trajectory within a preset convergence radius, and analyzing combustion convergence and stability.The present application makes full use of the correlation and similarity between data, can accurately identify similar combustion evolution modes, helps experts more accurately grasp key characteristics such as stability and oscillation in the combustion process, deeply reveals the combustion law, and improves the precision of ramjet combustion simulation.

The invention relates to a computer-implemented method for optically characterizing a textile fiber structure. A plurality of pieces of information on the color at different locations of the textile fiber structure are detected by an optical sensor system. The detected color information is transmitted to a computer (107) and is entered into a color space (2) in the form of a scatter plot (31) by the computer. A frequency density distribution (4) of the scatter plot (31) is determined, and the frequency density distribution (4) is numerically specified. The invention allows a change in the material of the textile fiber structure to be ascertained and optimizes the elimination of foreign materials from the textile fiber structure.

This makes it easier to recognize the correspondence between selected plot points in a scatter plot and the data corresponding to those selected points. [Solution] The processor of the information processing device 1 displays a scatter plot on the display unit 20 in which multiple plot points are plotted based on the input data. When the processor of the information processing device 1 receives an input data display operation to display the input data on the display unit 20, in which case the first data in the input data corresponding to the first plot point is displayed in a display manner that allows it to be identified from other data in the input data.

In virtual assistant platforms that provide access to a plurality of plug-ins, plug-in selection based on comparisons between high-dimensional embeddings of user prompts and high-dimensional embeddings of the example prompts contained in plug-in definitions can cause “collisions”—that is, selection of the wrong plug-ins—if the plug-in-definitions of the intended and erroneously selected plug-ins are too similar. Debugging such collisions or avoiding them in the first place can be aided by visualizing the example prompts of multiple plug-ins, optionally along with the user prompts, in a scatter plot based on mappings of the high-dimensional embeddings onto lower-dimensional vector representations, and analyzing changes in the scatter plot responsive to modifications of the plug-in definitions.

This invention relates to the field of power management and anomaly detection technology, specifically to a method and system for detecting anomalies in multi-port charging power supplies based on current analysis. It is applied to a charging system containing multiple load power supply buses and several branch switching transistors. The method includes: extracting and sampling AC ripple current from the total current signal of the multiple load power supply buses and each branch; performing delay mapping on the AC ripple current to construct a multi-dimensional phase space matrix and calculate a Poincaré cross-section scatter plot; calculating the current topological information entropy based on the scatter distribution probability and comparing it with the baseline information entropy to generate an information entropy residual; comparing the information entropy residual with a safety manifold boundary threshold range, determining a charging anomaly when it exceeds the threshold, outputting a hardware interrupt signal to control the state of the corresponding branch switching transistor, and generating a diagnostic report containing physical feature parameters extracted based on the multi-dimensional phase space matrix. This invention enables early identification of anomalies in multi-port charging systems and rapid hardware-level response.

The invention relates to the technical field of intelligent driving, in particular to a risk early warning method for a heart rate scatter diagram in the driving process. The real-time heart rate scatter diagram is calculated and analyzed in real time through the improved box counting method to obtain the fractal dimension, the dimension and entropy combined feature space is constructed through the improved sample entropy algorithm and the fractal dimension, the primary early warning information is generated through primary early warning judgment, the problems that a traditional method cannot recognize instantaneous risks and early warning is delayed are solved, and the early warning accuracy is improved. The real-time performance and the accuracy of risk identification are improved; the method comprises the following steps: acquiring a heart rate signal, analyzing the heart rate signal through wavelet packet decomposition to obtain a time-frequency feature vector, acquiring a steering wheel grip parameter, carrying out fusion analysis on the steering wheel grip parameter and the time-frequency feature vector to obtain early warning verification information, judging and outputting a risk early warning level through a risk level, and carrying out adaptability early warning through an individual heart rate baseline. The false report and missing report rate is reduced, and an accurate decision basis is provided for an intelligent driving system.

A mask manufacturing method, an anti-glare mask, and a manufacturing method for an anti-glare product. The mask manufacturing method comprises: generating a base scatter plot having random characteristics; on the basis of the base scatter plot, drawing a Voronoi diagram; and clipping a pattern from the Voronoi diagram, and performing two instances of mirroring, edge trimming and arraying on the pattern, in order to obtain an anti-glare mask. The anti-glare mask is manufactured using the mask manufacturing method. The manufacturing method for an anti-glare product comprises steps such as coating, exposure, development, etching, and stripping. A base scatter plot having random characteristics is used to draw a Voronoi diagram, and steps such as pattern clipping, mirroring, edge trimming and arraying are then performed, such that an ultimately obtained anti-glare mask has an anti-glare effect. The manufacturing method avoids optical defects such as Moire patterns and reflected bright lines, so that the mask manufacturing precision is improved, and patterns on masks are also more uniform and delicate, thereby improving the quality and performance of the masks.

A method for improving waste gas collection efficiency of an arc-shaped top suction gas-collecting hood based on an interface mass-energy ratio comprises the following steps: constructing a physical geometric model of the 1: 1 arc-shaped top suction gas-collecting hood by adopting space claim based on an ANSYS 2024 R1 simulation platform; defining the ratio of turbulent kinetic energy to mass flux on the mass-energy ratio interface as an interface mass-energy ratio; sequentially setting a plurality of groups of comparison working conditions by taking the number of the outlet air pipes, the layout of the outlet air pipes and the size of the outlet air pipes as single variables to finish simulation; exporting result data, and drawing a scatter diagram of the collection efficiency, the vortex volume and the interface mass-energy ratio; and the number, layout and size of the outlet air pipes are optimized according to the result, and the collection efficiency is maximized. According to the method, the limitation of relying on subjective judgment in the traditional empirical design is overcome, so that the performance of the flow field has comparability, and a clear scientific basis and a diagnostic tool are provided for subsequent optimization.

This invention relates to the field of image processing technology, specifically to a real-time battery health monitoring system based on an infrared thermal imager. The system includes: acquiring continuous thermal imaging images of the battery and obtaining the battery region for each image; acquiring a grayscale scatter plot of any pixel within the battery region; analyzing the characteristics of all data points in the grayscale scatter plot, the temporal differences in grayscale changes between the pixel and its neighboring pixels, and obtaining normal data points in the grayscale scatter plot; based on all normal data points in the grayscale scatter plot, obtaining the temporal grayscale distribution of the pixel; and based on the grayscale distribution of all pixels within the battery region, obtaining the temperature change index of the battery region; and obtaining the thermal change parameters of the battery region through the temperature change index, thereby monitoring battery health. This invention further improves the accuracy of battery health monitoring.

The invention discloses a query request processing method and system based on a scatter neural network, and relates to the technical field of artificial intelligence and knowledge engineering. According to the method, an original knowledge source of a target domain is obtained, ternary array knowledge scatter points containing a core object, association logic and domain connotation are generated through structured analysis, and ternary array and dense vector double views are adopted for representation and storage; and responding to a query request, performing adaptive multi-path retrieval on the knowledge scatter points based on the semantic type and other characteristics of the query request, and generating a target answer after confidence evaluation and optimization. According to the method, the problems of low analysis efficiency of an original knowledge source in the financial field, poor semantic matching of a single retrieval strategy, insufficient understanding of general and special knowledge and low question and answer accuracy caused by large model illusion can be solved, and the accuracy and efficiency of vertical field query request processing and the dynamic knowledge strengthening capability are improved.

The invention provides a panel defect aggregation analysis method and system based on a multi-modal large model, and relates to the technical field of defect aggregation analysis, and the method comprises the following steps: obtaining defect point coordinate data of a glass panel, and converting the defect point coordinate data into a defect scatter diagram; distinguishing different defect types by combining shape features and spatial distribution features of defect aggregation, and designing cue words according to the different defect types; inputting the defect scatter diagram and the cue words into the multi-modal large model for conjoint analysis, and performing performance evaluation and cue word iterative optimization on the multi-modal large model; and applying the cue words subjected to iterative optimization and the multi-modal large model for performance evaluation to panel defect aggregation analysis to obtain an analysis result. The method solves the problems that a traditional method is insufficient in recognition capability on a complex aggregation mode and high in parameter dependence, and a machine learning or deep learning method needs a large amount of labeled data and complex parameter tuning.

The application discloses a kind of suspended DAS borehole fissure fluid monitoring devices, including DAS demodulator and sensing optical cable suspended in water-filled borehole, sensing optical cable bottom end fixed counterweight, sensing optical cable upper portion is wound on optical cable reel, optical cable reel is set on orifice shock isolation module, sensing optical cable and DAS demodulator are connected.A kind of suspended DAS borehole fissure fluid monitoring method is also disclosed, strain waveform data are collected, and first arrival time of event at different depths is extracted;Depth-first arrival time scatter plot is drawn, inflection point in time period is determined, linear regression is carried out to uplink wave data points and downlink wave data points, and the intersection point of two linear regression fitting straight lines determines focal depth and occurrence time, carries out solid tide modulation analysis and pressure diffusion and permeability evaluation.The application can realize the high sensitivity monitoring and quantitative dynamics analysis of fissure fluid activity, and is suitable for seismic geology research, underground energy development and major engineering safety monitoring and other fields.

The invention relates to the technical field of seismic exploration, in particular to a structure prediction method and device based on incomplete information. The method comprises the following steps: randomly extracting discrete points in an existing structural map of a target work area, and constructing a pseudo well sample database; constructing a prediction model of regional structure and lithology information based on a pseudo well sample database, an existing structural map, and core data and surface road head data of a target work area pseudo well; constructing an incomplete information scatter diagram of the target work area on the basis of the core data of the real well of the target work area, the earth surface road head data information table and the lithology information; and based on the incomplete information scatter diagram of the target work area and the prediction model of the regional structure and lithology information, obtaining a structure prediction map and attribute information of the target work area. According to limited incomplete information such as a logging core and a field geological survey sample, a regional structure map and attributes are predicted, and an important basis is provided for structure prediction of a low-quality data region and a region without three-dimensional seismic data.

The application provides a pilot attention allocation training method, device and equipment and a storage medium, and belongs to the field of flight training. The method comprises the following steps: in the case that a pilot wears a head-mounted eye tracker for training, obtaining a fixation point video of the pilot and recording the triggering conditions of observable items; dividing the fixation point video into interest areas, performing data analysis on the interest areas, and determining the access times, Pearson correlation coefficients, pupil diameter change scatter plots, Markov transition matrices, access sequences and time lengths, in-cabin and out-of-cabin access times, cockpit saccade mode models and the pupil diameter change rates of the pilot; further determining the attention transfer portrait and the attention allocation score of the pilot; and adjusting the attention allocation training bias of the pilot according to the attention allocation score and the attention transfer portrait. In this way, the limitations of traditional subjective judgment can be overcome, and the training evaluation is more scientific and operable.

This invention discloses a method for calculating the effective utilization coefficient of irrigation water based on remote sensing ET (Emergency Thresholding). The method includes: acquiring the evapotranspiration of each pixel in the study area at high spatiotemporal resolution; extracting multi-source remote sensing features of Sentinel-2 multi-temporal spectral features during the study period, and combining them with a trained ensemble learning classification model to obtain a crop planting structure map for each ten-day period; using the evapotranspiration of the pixel as the crop water requirement for the ten-day period, selecting an effective precipitation model based on the cultivated land type of the crop in the pixel, and calculating the effective precipitation for the pixel based on the crop water requirement and precipitation for each ten-day period; using Sentinel-1 imagery of the study period combined with OTSU classification, marking pixels with increased moisture as moisture increase events in each ten-day period, and correcting the moisture increase events using a scatter plot to obtain a ten-day irrigation distribution map; and calculating the effective utilization coefficient of irrigation water in the study area based on the evapotranspiration, crop planting structure map, effective precipitation, irrigation distribution map, and gross irrigation diversion.

The application discloses a method and system for evaluating the quality of airborne hyperspectral images based on a twin network architecture, comprising the following steps: S1, obtaining an airborne hyperspectral image; S2, preprocessing the hyperspectral image; S3, selecting a sample group set from the preprocessed hyperspectral image, taking the average value of the sample group set as a standard group, extracting the spectral index feature vector and the radiation index feature vector of each sample group, and converting them into fan-shaped scatter plot images; S4, sequentially grouping the fan-shaped scatter plot images of the standard group and the fan-shaped scatter plot images of each sample group into image pairs, inputting the image pairs into a twin convolutional network model, and obtaining the similarity evaluation results of each group of image pairs; wherein the twin convolutional network model adopts a twin network and a convolutional neural network; and S5, obtaining the quality evaluation results of the hyperspectral image based on the similarity evaluation results of each group of image pairs. The application provides a simple and convenient no-reference image quality evaluation method based on a twin convolutional network.

This invention discloses a method, system, device, and storage medium for online monitoring and diagnosis of partial discharge in generators. It acquires pulse signals from different parts of the generator casing and uses an adaptive bipolar pulse detection algorithm to determine the start and end points of each pulse. For each pulse, it extracts amplitude, polarity, energy, width, and phase characteristics within the power frequency cycle. Combining pulse rate and average amplitude, it executes a discharge mode classification algorithm to obtain discharge classification results. Based on the discharge severity index, it calculates the insulation fatigue increment within a single monitoring window, updates the cumulative fatigue value using a time decay model, and triggers corresponding alarm levels based on the cumulative fatigue value. It calculates the power frequency phase based on the occurrence time of each pulse, plots a scatter plot, calculates and sorts the discharge intensity based on the number of pulses, energy, and amplitude from each sensor, and generates an activity heatmap. It extracts the recent average daily fatigue increment, estimates the number of days required for the insulation fatigue value to reach the critical threshold, and generates a comprehensive diagnostic report.

The invention relates to a film thickness compensation method and system and a storage medium, and the method comprises the following steps: obtaining the film thickness data of a target deposition material at each deposition time in a historical evaporation process, and calculating the regulation factor proportion of each deposition time according to the film thickness data; drawing a scatter diagram by taking the deposition time as an abscissa and the regulatory factor proportion as an ordinate; curve fitting is conducted according to the scatter diagram, compensation coefficients are determined, a regulation factor proportion compensation function is obtained, y = ax < 3 > + bx < 2 > + cx + d, y represents the regulation factor proportion, x represents the deposition time, and a, b, c and d are all compensation coefficients; and calculating the regulatory factor proportion of each deposition time by using the regulatory factor proportion compensation function, and correcting the initial regulatory factor of the evaporation source in real time. According to the evaporation duration, the regulation factor proportion is corrected in real time or at regular time, the thickness stability of the evaporation film is improved, and the product quality is improved.

This invention relates to the field of energy engineering technology, specifically disclosing a method and system for predicting the power consumption of a gas turbine unit. The method includes: identifying a window of extremely slowly varying operating conditions through a monitoring system, constructing a scatter plot, identifying closed narrow hysteresis loops to determine nonlinear hysteresis effects, completing wall thermal inertia analysis and quantifying the total wall heat flow rate; correcting combustion temperature drift based on the total wall heat flow rate to obtain the true combustion temperature; constructing an air-fuel ratio correction model in the sensitive range of the slightly open gas regulating valve to achieve dynamic matching of gas flow; eliminating gas consumption distortion components to obtain hysteresis-free true gas consumption values, and finally obtaining hourly and daily gas consumption prediction ranges without dynamic interference through cumulative calculation and system deviation calibration. The system includes: a hysteresis identification module, a temperature correction module, an opening degree adjustment module, a gas consumption analysis module, and a prediction output module. The solution effectively improves the accuracy of gas consumption prediction under extremely slowly varying peak-shaving conditions.

The application relates to the field of detection, and discloses an arc detection method based on an interpretable deep learning model and related equipment thereof. The method comprises the following steps: acquiring a current signal under a direct-current arc fault state and image data corresponding to the current signal; performing time-frequency conversion processing on the image data corresponding to the current signal to obtain image time-frequency features; inputting the image time-frequency features into a preset interpretable deep learning model to generate feature density scatter plots corresponding to each observation frequency band; based on model interpretability values in the feature density scatter plots corresponding to each observation frequency band, calculating bandwidth ranges corresponding to the image time-frequency features in each observation frequency band; and based on the bandwidth ranges and the corresponding image time-frequency features, detecting a direct-current arc. According to the application, the image data obtained by a monitoring device is processed to obtain feature density scatter plots corresponding to the image data, the most relevant observation frequency band and the corresponding image features are screened, and a direct-current arc fault is accurately detected.

This system provides an analytical support device, analytical support method, and analytical support program that contribute to improving the accuracy of analysis of members and the organization by providing a list of evaluations of the introspection of multiple members. [Solution] The analysis support device 15 comprises an analyst information acquisition unit 23, a member information storage unit 21, an evaluation acquisition unit 25, and a display control unit 27. The analyst information acquisition unit 23 acquires first to third analysis elements for analyzing each of the multiple members that constitute the organization. The member information storage unit 21 stores the members' answers to each of the multiple items related to introspection, associating them with the items. The evaluation acquisition unit 25, with one member selected, acquires the level of the first to third analysis elements based on the answers of the selected member. The display control unit 27 displays a scatter plot image in which marks corresponding to the levels of each of the multiple members and three axes corresponding to the first to third analysis elements are arranged in a virtual three-dimensional space.

The application discloses an engine working condition data processing and visual analysis method and system, and belongs to the technical field of engine performance analysis and test data processing. The method comprises the following steps: importing a data file and selecting a target data column; performing numerical conversion, missing value elimination and abnormal cleaning on the data; when a power column is missing, calculating the power according to the rotating speed and the torque; generating a colored rotating speed-power scatter plot based on preset power partitions, and counting the data amount and proportion of each partition to generate a column chart and an analysis report; aligning multiple data sets according to a time key to generate a line chart and identify extreme points and comparison data; and exporting statistical results and the analysis report. The application improves the data processing efficiency and power calculation flexibility, and enhances the intuitiveness and accuracy of working condition distribution and multi-data set comparison analysis.

A metal composite compound includes at least Ni. In a scatter plot obtained by measuring a powder of the metal composite compound using a scanning electron microscope-energy dispersive X-ray spectroscopy, with a horizontal axis representing a projected area circle equivalent diameter (μm) of particles of the metal composite compound and a vertical axis representing an Ni content ratio (mol %) of the particles of the metal composite compound, a slope S of an approximate straight line calculated by a least squares method is more than 0.2. When a particle diameter at which a cumulative volume ratio from a small particle side in a volume-based particle size distribution reaches 10% is defined as D10 (μm), a standard deviation X of the Ni content ratio (mol %) in particles having a projected area circle equivalent diameter of the D10 (μm) or less is 1.6 mol % or more.

The application discloses a kind of visualization device, method and application for matrix, it is related to data visualization technical field;Device includes conversion module, for obtaining matrix, the matrix is 01 matrix, matrix is composed of row vector, and row vector is classified, mapped to corresponding area on two-dimensional plane by recursive dichotomy to matrix and obtains scatter plot;Method includes obtaining matrix, and row vector is classified, mapped to corresponding area on two-dimensional plane by recursive dichotomy to matrix and obtains scatter plot;Application includes the use of recursive dichotomy in 01 matrix visualization;It is good by conversion module etc., to realize matrix visualization effect.

The invention discloses a multi-scene diffusion calculation method for a chemical pollution source. The method comprises the following steps: (1) parameter input and verification: inputting pollution source parameters, meteorological parameters, calculation region parameters and pollutant types; performing numerical range, data type and logic consistency verification on the input parameters, filling default values when non-key parameters are missing, and prompting correction when the parameters are abnormal; (2) coordinate conversion and caching; (3) calculating diffusion parameters; (4) single-source concentration calculation; (5) multi-source concentration superposition; and (6) result output: outputting a calculation result in the forms of a data table, a scatter diagram and a JSON file. According to the method, multi-scene unified calculation can be provided, an instantaneous point source, a continuous point source, an instantaneous multi-point source and a moving line source are supported, dynamic weather, terrain and pollutant characteristic correction are introduced to improve precision, calculation logic is optimized, and emergency efficiency is ensured.

The present application relates to the technical field of medical diagnosis, in particular to a flow cytometry T cell subset detection automatic classification method based on machine learning, cell data of multiple blood samples is collected by using a flow cytometer, and a two-dimensional scatter plot is drawn; the cell population in the two-dimensional scatter plot is manually labeled, and the labeling result is mapped to high-dimensional data; the high-dimensional data is standardized to obtain high-dimensional space data; the high-dimensional space data is reduced in dimension based on a uniform manifold approximation and projection algorithm to obtain low-dimensional data; the low-dimensional data is density clustered based on a density-based spatial clustering algorithm, and the classification result is matched with the manual labeling; and the classification result is mapped back to the two-dimensional scatter plot for visual display, which overcomes the problems of strong subjectivity, low efficiency and poor reproducibility in the traditional manual classification method, and significantly improves the accuracy, efficiency and consistency of T cell subset classification.

The invention relates to a method and a device for determining the mixed dyeing proportion of earth crust components in magma. The method comprises the following steps: dating a sample to be detected to obtain the crystallization age t of the magma; performing Nd and Sr isotope testing on the whole rock to obtain an epsilon Nd (t) value and an ISr value, generating a scatter diagram, and determining the epsilon Nd (t) value and the ISr value of the initial magma and the surrounding rock; performing quantitative simulation calculation on the change of the Sr-Nd isotope of the initial magma under the joint control of separation crystallization and surrounding rock mixed dyeing; and generating a scatter diagram by the epsilon Nd (t) values of the magma and ISr under different evolution processes to obtain an AFC evolution trend line of the Sr-Nd isotope of the magma, comparing the AFC evolution trend line with data points of a sample to be detected, and reading the crustal component mixed dyeing proportion according to a calculation result. According to the method, the magma Sr-Nd isotope is taken as a carrier, two magma evolution effects of mineral separation crystallization and crustal mixed dyeing are quantitatively described based on the AFC model, and quantitative estimation of the crustal mixed dyeing proportion in the AFC process is realized.

At least some embodiments of this disclosure relate to a system for processing cardiac information. The system includes a processing unit configured to: receive an activation waveform comprising a set of activation waveform data of multiple signal segments collected at multiple locations; and receive a range of window sizes. For each of the multiple signal segments, the processing unit is further configured to: determine a set of confidence values ​​by traversing the multiple window sizes within the range of the window sizes. For each of the multiple signal segments, the processing unit is further configured to: determine one of a plurality of local cycle lengths based on the selected window size for each of the multiple signal segments; and generate a representation of the multiple local cycle lengths.

The invention discloses a method for predicting the multilayer stacking height of 3D printing fiber concrete, and the method comprises the following steps: 1, collecting fiber parameters, including a volume fraction, a length-diameter ratio and an orientation factor; step 2, printing a single-layer strip and measuring the height of the actually measured single layer; thirdly, multiple layers are printed at a long interlayer interval, and interlayer bonding loss is obtained through linear fitting of total height-layer number; 4, under the target interlayer interval, measuring a scatter diagram of the first-layer settlement amount changing along with the layer number, and performing linear fitting to obtain a first-layer settlement amount model; 5, establishing a total compression settlement model and a bonding loss model; and step 6, obtaining a stacking height analytic expression of any layer number. According to the 3D printing fiber concrete multi-layer stacking height prediction method, parameters needed by the model are few and can be explained, on-site rapid adaptation is facilitated, and accurate prediction and online correction under different fiber types / mixing amounts and printing time intervals are achieved; the calibration process is short, and the recalculation operability is high.

The present application relates to the field of tire mechanical property data processing, in particular to a static tire covering force partition linear fitting method and device, wherein the static tire covering force partition linear fitting method comprises the following steps: performing covering rigidity test on the static tire, obtaining multiple groups of protrusion lifting distance and protrusion load in the load loading stage and the load unloading stage, drawing a test data scatter plot of protrusion load and protrusion displacement with the protrusion lifting distance as the abscissa and the protrusion load as the ordinate; dividing the load loading stage and the load unloading stage of the test data scatter plot according to at least two kinds of preset load intervals respectively and forming multiple partitions, and determining the covering rigidity of each partition according to the protrusion lifting distance and the protrusion load of each partition; and fitting the covering rigidity curve according to the covering rigidity of each partition. Thus, the accuracy of the static tire covering rigidity test is improved, which is conducive to subsequent characteristic analysis of the tire.