80results about How to "Accurate description" patented technology

The invention provides a system frequency response estimation method and system based on a fault position, and belongs to the technical field of new energy power grids, and the method comprises the steps: constructing a new energy multi-operation-state model; solving the node voltage of the state model after the fault based on the superposition principle and iterative calculation, establishing a mapping model of the fault position and the low-cross cluster, obtaining the initial value of the active power vacancy, and comprehensively considering the difference between the initial value of the active power vacancy and the active recovery rate between stations at different fault positions. Calculating the system-level total active power vacancy considering the station low-voltage crossing characteristic difference; and constructing a system frequency response model based on the frequency modulation capability difference caused by the fault position, and estimating the system frequency response by adopting the response model. According to the invention, quantitative description of active power vacancy and system equivalent frequency modulation capability loss after disturbance at different fault positions is realized, so that the accuracy of frequency response analysis is improved.

The invention discloses a marine main engine cabin entering simulation method and system based on multi-view measurement. The method comprises the following steps: acquiring cabin space depth image information through multiple view angles, constructing cabin environment three-dimensional point cloud data, and unifying multi-view angle point clouds to the same global coordinate system based on camera calibration; performing accurate fusion on the multi-view point clouds by adopting a point cloud registration algorithm which introduces a dynamic weight and a local rejection mechanism, and extracting a boundary of an effective space of a cabin by utilizing an alpha-shape algorithm; motion trail modeling is carried out on the main engine cabin entering process, meanwhile, rapid real-time calculation of the minimum gap between a main engine envelope body and a cabin boundary is achieved by constructing a gridding distance field of a cabin space, and therefore whether the risk of collision or insufficient space exists in a given cabin entering path of a main engine or not is judged. According to the invention, high-precision, high-efficiency and high-real-time host entry space verification can be realized in a complex and narrow in-cabin environment, and reliable technical support can be provided for optimization and decision-making of a marine host entry scheme.

The invention provides a post-retinal detachment reduction body position management method and system and wearable equipment, and relates to the technical field of medical monitoring. The method comprises the following steps: continuously acquiring head motion data through an inertial measurement unit integrated on head-mounted equipment, resolving the data through an embedded processor to obtain a real-time head posture angle, and comparing the real-time head posture angle with a preset rehabilitation position angle range to generate a posture comparison result; meanwhile, neck strain signals are collected through a flexible strain sensor array, and biomechanical characteristic signals are obtained through signal conditioning; and finally, the two types of data are fused, and a judgment result of the consistency of the overall body position of the user is generated through a classification algorithm, so that multi-modal data fusion analysis is realized, the postoperative body position state can be accurately monitored in real time, immediate feedback is provided, and the accuracy of body position management and patient compliance are effectively improved.

The invention discloses a method for drawing a bottom surface disease distribution diagram of a main arch ring of a two-way curved arch bridge. According to the method, arch rib and arch wave numbers, an arch rib local coordinate system, an arch wave local coordinate system, a disease position recording standard, an overall coordinate system, an arch rib disease position description standard, an arch wave disease position description standard and a disease pattern drawing standard are included. On one hand, a set of independent local coordinate system based on a horizontal projection plane is established for each arch rib and arch wave of the main arch ring of the two-way curved arch bridge, on the other hand, a three-dimensional curved surface is expanded into a two-dimensional curved surface along the bridge direction and the transverse bridge direction, and an overall coordinate system reflecting the actual size of the main arch ring is established; local disease coordinates are reflected in the actual position of the main arch ring of the two-way curved arch bridge through coordinate conversion, and accurate disease drawing of the complex three-dimensional curved surface of the main arch ring of the two-way curved arch bridge is achieved.

The present application belongs to the technical field of parameterized modeling, and discloses a tunnel operation area dynamic parameterized modeling method; comprising: collecting measured data of a tunnel operation area; based on the collected measured data, establishing an initial model of the tunnel operation area; dividing the initial model of the tunnel operation area into a plurality of model regions, taking the model regions as nodes to construct an operation area undirected graph; assigning colors to the nodes in the operation area undirected graph; for each model region, determining a corresponding parameter group according to the assigned color, and updating to obtain an overall parameterized model based on the initial model of the tunnel operation area and the corresponding parameter groups of the model regions; namely, the dynamic parameterized modeling result of the entire tunnel operation area, which provides a scientific decision basis for design optimization, construction scheme formulation, risk assessment and operation management of tunnel projects.

The application discloses a kind of playground soil body constitutive model construction method under the action of latent corrosion, deformation prediction method and equipment, the model construction method steps include: step S01.Obtain the distribution data of latent corrosion rate along the length of sample obtained by carrying out latent corrosion test on sample soil body under different influence factors;Step S02. The distribution data of latent corrosion rate along the length of sample is fitted into a straight line, and the uneven state parameter of fine particle of soil body after latent corrosion is defined;Step S03. Establish the first quantitative relationship model between uneven state parameter and each influence factor;Step S04. Establish the second quantitative relationship model between the critical state parameter of soil body after latent corrosion and uneven state parameter;Step S05. According to the second quantitative relationship model, the constitutive model of soil body after latent corrosion is constructed based on lower yield surface cambridge model.The application can accurately describe the mechanical properties of soil body after latent corrosion, and improve the accuracy of deformation prediction.

The invention provides a protein chromatography process optimization method and system based on reinforcement learning, and relates to the technical field of reinforcement learning, and the method comprises the steps: obtaining multi-source heterogeneous data, carrying out the multi-scale decomposition, building a hierarchical mechanism knowledge base, combining real-time operation data analysis, building a hybrid drive prediction model, and achieving the state prediction of a chromatography process. And dynamically adjusting model parameters by using layered feedback information. The intelligent control of the protein chromatography process can be realized, the separation purity and yield are improved, the process parameter adjustment time is shortened, and the production cost is reduced.

The invention provides a text generation method and related equipment. The method comprises the following steps: performing text recognition on a sample video about a sample object to obtain sample information of the sample object and a corresponding initial text; performing abnormal text correction and text screening on the initial text to obtain a screened text; performing model training based on the sample information and the screened text to obtain a text generation model; the text generation model generates a target text used for recommending the target object based on the target information of the target object.

The invention relates to a spatial position instruction fine tuning method based on a multi-modal large language model, and the method comprises the following steps: S1, converting a spatial position reasoning data set into a visual instruction format through employing a dialogue template, and obtaining a visual spatial position reasoning data set; s2, acquiring a large language model InternVL as a multi-modal large language model, performing pre-training on the general data set to obtain a pre-training model, reasoning the data set based on the visual spatial position, adjusting parameters of the pre-training model by adopting a low-rank adaptation method to obtain a trained large language model, and outputting a description corresponding to a spatial task by the large language model; and S3, introducing a text-based large language model, and optimizing the description corresponding to the space task based on the large language model. Compared with the prior art, the method has the advantages that the ability of the multi-modal large language model in understanding and generating context rich description is fully utilized, and the ability of the model in generating accurate and detailed description is enhanced.

The present application relates to the technical field of atomization numerical simulation, and relates to an atomizer atomization numerical simulation method and system based on temperature variation characteristics, which comprises the following steps: confirming a test atomizer set and an ambient temperature set, obtaining a plurality of normal liquid viscosity sets and a plurality of normal liquid droplet surface tension sets, obtaining an optimized temperature interval, constructing a viscosity surface tension momentum equation, setting a solver parameter, sequentially extracting an optimized temperature value from the optimized temperature interval, simulating a pre-constructed simulation atomizer according to the solver parameter, the optimized temperature value and the viscosity surface tension momentum equation, obtaining a simulation atomization parameter, otherwise, taking the simulation atomization parameter as an optimized atomization parameter, summarizing the optimized atomization parameters, obtaining an optimized atomization parameter set, obtaining an optimal atomization parameter, and completing the atomizer atomization numerical simulation based on the temperature variation characteristics based on the optimal atomization parameter. The present application can improve the performance and atomization effect of the atomizer.

This invention relates to the field of behavioral profile generation technology, specifically disclosing a method for generating user behavior profile content based on machine learning, including the following steps: Step S1: Collect historical behavior logs of multiple users, count the total interaction frequency of a single user, distinguish active and inactive users based on thresholds, and construct frequency vectors for each user's behavior items; Step S2: For a single user, calculate the angle between its frequency vector and the vectors of all active users, select the K active users with the smallest angle, aggregate their vectors and concatenate them with the original vector of the target user to generate an enhanced behavioral feature vector; Step S3: Utilize two sets of linear mapping matrices to operate on the enhanced features respectively to obtain frequency and interest representation vectors, calculate the mean cosine similarity between the two, iteratively optimize the classification based on this value, determine the final interest representation vector, and output the user behavior profile text accordingly.

A method and system for EEG emotion recognition based on multi-task and attention mechanisms is disclosed. The method comprises: S1. Acquiring corresponding EEG signal data according to the locations of emotion-related EEG channels in the international standard 10-20 electrode placement system; S2. Preprocessing the acquired EEG signals using bandpass filtering, power frequency notch filtering, downsampling, baseline correction, artifact removal, and signal segmentation, dividing the signal into windows with a duration of 0.5 seconds; S3. Extracting power spectral density and differential entropy features from the EEG data of each time slice, representing the feature vectors using a two-dimensional brain map to preserve spatial information, and stacking brain maps of all bands and features in three-dimensional space, with each map serving as input to the model; S4. Integrating a convolutional module, a long short-term memory network variant module, and an attention module, employing a multi-task learning strategy to obtain an optimal model capable of accurately identifying both arousal and valence of emotions in EEG signals simultaneously. This invention solves the problem of previous models focusing only on a single feature and a single recognition task, constructing a highly accurate multi-task model in the field of emotion recognition.

This invention discloses a multi-channel UAV pose perception system and method. The system includes a pose perception belt, a digital twin UAV attitude visual interface, and a UAV-side pose sensor. The pose perception belt includes a control unit, a wireless communication module, a vibration motor, a power supply module, and a belt frame. The UAV-side pose sensor collects UAV attitude data in real time and establishes an aerial attitude model of the UAV. The attitude data includes at least the angle and direction of UAV tilt. The angle of UAV tilt is defined as the tilt angle, which is the complementary angle γ between the UAV's XY plane and the ground. The direction of UAV tilt is defined as the drift angle, which is the angle α between the projection of gravitational acceleration on the UAV's XY plane and the X-axis. This invention significantly reduces the operator's cognitive load, enables rapid response to abnormal UAV attitudes, greatly shortens the operator's decision-making time, and reduces the risk of UAV loss of control, rollover, or crash.

This application discloses an analytical method for electrolyte systems based on low-scaling Monte Carlo simulations of electrostatic interactions, relating to the field of molecular simulation technology. The method includes: constructing an initial model of the target system and configuring simulation parameters; initializing local electric displacement auxiliary field variables; using these variables to describe the local electric displacement state of the target system; randomly selecting and updating an object; the updated object being the particle configuration and / or the local electric displacement auxiliary field variables; determining the equivalent local electric field strength at the target spatial location after updating the object; updating the local dielectric constant at the target spatial location based on the equivalent local electric field strength; and after updating the local dielectric constant, determining the various electrostatic interaction energies in the target system and evaluating the total electrostatic energy. This method can accurately describe the complex electrostatic interactions between components caused by local electric fields, high charge density, and the dielectric response properties of the components while ensuring computational efficiency.

This application relates to the field of radar technology, and discloses a radar-based target measurement method, integrated circuit, sensor, and device. The radar-based target measurement method includes: acquiring a radar echo signal; measuring a target based on the radar echo signal to obtain a first measurement value; determining a reference signal transmission model from a preset signal transmission model based on the first measurement value, wherein each signal transmission model corresponds to a type of signal transmission path; and calculating a second measurement value based on the signal transmission model and the radar echo signal. This method is at least beneficial for more accurate and effective target measurement.

This invention proposes a multi-factor coupled comprehensive evaluation method and system for tire friction performance, comprising: S1, conducting a multi-stage progressive load test on the tire and collecting longitudinal force versus longitudinal displacement relationship curve data at each stage; S2, calculating a multi-stage dynamic weighted friction coefficient based on the longitudinal force data at each stage using progressively weighted coefficients; S3, considering the characteristics of the contact surface material, surface roughness, and contaminant coverage; S4, considering the test environment temperature and relative humidity; S5, determining the dynamic stiffness coupling coefficient of the tire-contact surface system based on the slope of the initial linear segment of the longitudinal force versus longitudinal displacement relationship curve; S6, calculating a comprehensive friction performance index based on the multi-stage dynamic weighted friction coefficient and the dynamic stiffness coupling coefficient; S7, calculating a friction performance stability index through repeated loading tests; and S8, comprehensively evaluating the tire friction performance level based on the comprehensive friction performance index and the friction performance stability index.

The application discloses a lightweight feature extraction model and a flotation process running state evaluation method. The model comprises: a first teacher module configured to generate a first roughing image feature and a first scavenging image feature according to the foam image; a second teacher module configured to generate a first data feature according to the foam data; a student module configured to generate a second roughing image feature according to the first roughing image feature, generate a second scavenging image feature according to the first scavenging image feature, and generate a second data feature according to the first data feature; and a fusion module configured to fuse the second roughing image feature, the second scavenging image feature and the second data feature to generate a first fusion feature, and generate a state grade label according to the first fusion feature; and determine the state grade of the current flotation process running state, so as to provide a more lightweight model deployment and a more competitive application in an actual industrial scene.

The application relates to a non-motor vehicle trajectory prediction method, which comprises the following steps: calculating a feasible domain of a terminal point of a non-motor vehicle to be detected based on to-be-predicted scene information, and obtaining a feasible terminal point set through discrete sampling; adopting a deep learning model which is constructed and trained in advance, and generating an alternative trajectory set of the non-motor vehicle to be detected according to the to-be-predicted scene information and the feasible terminal point set; adopting a behavior analysis model of the non-motor vehicle which is constructed in advance, evaluating the alternative trajectory set, and selecting a maximum utility trajectory; and the behavior analysis model is used for calculating trajectory utility, and the trajectory utility is quantified as a sum of expected trajectory risk and trajectory efficiency heterogeneity. Compared with the prior art, the application can adapt to the flexible and changeable behavior characteristics of the non-motor vehicle, has certain advantages in eliminating cumulative errors in iterative prediction and trajectory prediction for sudden behaviors of the non-motor vehicle, and greatly improves the accuracy and reliability of the non-motor vehicle trajectory prediction.

According to the three-dimensional modeling method and system based on the oblique photography technology, by means of a three-dimensional modeling scheme based on the oblique photography technology, an oblique image, POS and ground image control data of a specified measurement area are collected firstly, and then a real scene three-dimensional model is generated according to the process operation of aerial triangulation measurement, multi-view image dense matching, TIN structure construction and texture combined generation. Manual intervention is reduced, the modeling period is shortened, and scenes with high timeliness requirements are met; accurate image exterior orientation elements and ground point coordinates provided by aerial triangulation provide geometric constraints for multi-view image matching, so that the matching is efficient and accurate, a large amount of accurate three-dimensional point cloud data is quickly generated, and the overall efficiency is improved; the automatic process reduces the dependence on professionals and saves the labor cost; the TIN structure can more accurately describe the surface shape of the ground feature, and after the texture is combined, the generated real scene three-dimensional model can better present the geometric features and appearance details of a real scene, and the reality sense and the detail effect are better.

The invention relates to the technical field of power system operation control, in particular to a power distribution network coordination control method and system based on multiple flexible loads, and the method comprises the steps: collecting the power data of each flexible load and each distributed power supply in a power distribution network in real time; equally dividing each day into each time period, acquiring a distribution characteristic array and a power fluctuation degree of each load in each time period, acquiring a reference power utilization difference factor of each load in each time period, and acquiring a characteristic vector of each load in each period; classifying all loads in each period; and acquiring the power demand degree of all flexible loads in each type in all days in each period in each same time period, acquiring the output characteristic value of each distributed power supply in each time period in each day in the next period, and acquiring the power upper limit of each load in the next time period of each time period in each day in the next period. According to the method, the accuracy of flexible load classification is improved, a reasonable power adjustment strategy is formulated for the flexible loads, and the source load matching degree of the power distribution network is improved.

This application proposes a control method, device, electronic device, and storage medium for a cleaning robot. The method includes: acquiring sensor data collected by the cleaning robot during historical cleaning processes, the sensor data including sensor data from at least multiple location points; determining at least one virtual boundary based on the sensor data from the multiple location points; and performing cleaning control on the cleaning robot based on the virtual boundary. The virtual boundary, determined by combining the sensor data collected during historical cleaning processes, accurately describes the location to be cleaned, thereby enabling comprehensive cleaning of all cleanable locations and preventing some cleanable locations from being missed, thus improving cleaning efficiency.

The application discloses a dense optical flow-based optical remote sensing image uniform dense matching method and system, equipment and a storage medium, and belongs to the technical field of satellite remote sensing image processing. The application solves the technical problem that the prior art lacks a dense optical flow-based optical remote sensing image uniform dense matching method which can recognize sufficient and uniformly distributed matching points in various complex scenes and has high positioning accuracy. The application confirms a remote sensing image overlap area, divides the remote sensing image overlap area into a plurality of remote sensing image blocks, constructs a displacement field solving model and a Gaussian image pyramid, obtains a displacement field of the remote sensing image overlap area, acquires a pre-matching matching point pair set, distributes the pre-matching matching point pair set into corresponding remote sensing image overlap area image blocks, and screens a final matching point set. The application is used for realizing a dense optical flow-based optical remote sensing image uniform dense matching method which can recognize sufficient and uniformly distributed matching points in various complex scenes and has high positioning accuracy.

The invention discloses a moisture diffusion-mechanical coupling calculation method based on particle DDA, and the method specifically comprises the steps: carrying out the discretization of a to-be-solved region through the particle DDA, and endowing a control parameter; contact retrieval is carried out between the particles and between the particles and the boundary, the action ranges of mechanics and moisture diffusion are determined, and a force chain and a virtual moisture diffusion channel are established between the action ranges; calculating the mechanical part of the DDA of the particles, and updating the position information of the particles; assembling a moisture diffusion equation set of the particle DDA, solving the equation set and updating particle moisture content information. According to the moisture diffusion-mechanical coupling calculation method based on the particle DDA, an implicit solution strategy is adopted, the time step is large, and calculation is stable; and the influence of cracks on the moisture diffusion process can be fully considered. Benefited from the improvement, the constructed water diffusion model not only improves the calculation efficiency and simplifies the material parameter assignment process, but also can more accurately describe the water migration behavior in the crack-containing structure.

This application discloses a method and apparatus for predicting the dynamic migration of coarse aggregates during the compaction process of asphalt mixtures, relating to the technical field of predicting the dynamic migration of coarse aggregates in asphalt mixtures for road engineering. The method includes: collecting the morphological characteristics of real coarse aggregates to generate a 3D aggregate model containing complex morphological features; establishing a rotary compaction model of asphalt mixtures based on the 3D aggregate model, and selecting multiple typical compaction states to represent the compaction process; determining the coordination number information of each coarse aggregate under each typical compaction state; based on the coordination number information, statistically analyzing the coordination number distribution of coarse aggregates in the initial compaction state, calculating the transition probability of aggregate coordination numbers between adjacent typical compaction states, constructing a multi-step transition matrix, and establishing a prediction model for the dynamic migration of coarse aggregate coordination numbers based on a Markov chain based on the multi-step transition matrix. This predicts the evaluation index of the skeleton structure during the compaction process, which can more accurately and reasonably describe the dynamic migration of coarse aggregates during compaction.

The invention discloses a lithium battery charge state estimation method based on a self-adaptive gray system model, which comprises the following steps: collecting limited data in a battery discharge process, and establishing a self-adaptive real number field gray system model; solving parameters and a recursive formula of the gray system model, and capturing a nonlinear mapping relation between the state of charge and the open-circuit voltage by combining an accumulative effect of the discharge capacity; nonlinear parameters of the model are optimized through a simulated annealing intelligent algorithm; and in combination with an equivalent circuit model and an extended Kalman filtering algorithm, the state-of-charge estimation of the power battery under different driving cycle tests is realized. According to the method, a mining thought without using high-order polynomial fitting is introduced, so that a relatively high lithium battery charge state estimation result can be obtained, and a battery manufacturer and a user can accurately know the residual electric quantity condition of the battery so as to perform reasonable charging plan arrangement.

This invention relates to a system and apparatus for evaluating periodontal tissue inflammation. The system includes: an attachment loss surface area calculation module for calculating the attachment loss surface area based on clinical attachment loss measurements; a recession surface area calculation module for calculating the gingival recession surface area based on gingival recession measurements; a periodontal epithelial surface area calculation module for subtracting the gingival recession surface area from the attachment loss surface area to obtain the periodontal epithelial surface area; a periodontal inflammation surface area calculation module for multiplying the periodontal epithelial surface area by the proportion of sites affected by probing bleeding to obtain the periodontal inflammation surface area; and a periodontal tissue inflammation evaluation module for calculating the sum of the periodontal inflammation surface areas of all teeth. This invention fully quantifies and objectively reflects the periodontal inflammation and periodontal tissue damage, defining the degree of inflammation in periodontitis as a new continuous variable, which can more accurately describe the degree of inflammation and minimize the subjectivity in assessing the severity of the disease.

The present application belongs to the technical field of opto-mechanical thermal coupling analysis, optical system structure optimization, multi-fidelity proxy modeling and high-precision optoelectronic equipment design, and relates to an off-axis expander opto-mechanical thermal coupling performance prediction and structure optimization method. It comprises: establishing an off-axis expander parameterized structure model, constructing high and low fidelity opto-mechanical thermal coupling analysis models, obtaining the node displacement field of the primary mirror and the secondary mirror, decomposing the node displacement field into rigid body motion component and elastic deformation component, and calculating the pointing deviation and wavefront aberration to form a multi-fidelity training data set. Different fidelity responses are used as related tasks to construct a multi-output multi-fidelity Gaussian process proxy model. After training, the proxy model is used to predict the pointing deviation and wavefront aberration under the target high fidelity, and the off-axis expander structure parameters are optimized under the constraints of optical performance and structure size. The present application can reduce the number of high-fidelity simulations, improve the efficiency of opto-mechanical performance prediction and the accuracy of optimization design.

The invention provides a parameter identification method for a proton exchange membrane fuel cell system, belongs to the technical field of fuel cell identification, and solves the technical problem of low parameter identification precision caused by the fact that an internal electrochemical reaction of the proton exchange membrane fuel cell system cannot be accurately described by a traditional modeling method. According to the technical scheme, the method comprises the following steps: 1) establishing a fractional order multiple-input single-output state space model of the proton exchange membrane fuel cell system; and step 2) constructing an identification process of the hierarchical multi-information recursive minimum error entropy algorithm. The hierarchical multi-information recursive minimum error entropy algorithm provided by the invention has relatively high convergence speed and relatively high convergence precision, and can be well suitable for parameter identification of the proton exchange membrane fuel cell system.

A method for improving the accuracy of shale gas reservoir structural models, belonging to the field of unconventional and new energy, includes: conducting detailed interpretation of seismic data to predict small-scale fault development; establishing a fault model through well-seismic integration; identifying feature points on the horizontal sections of completed horizontal wells and converting them into virtual wells; compiling planar maps of different sub-layer thicknesses based on regional geological research results, extracting sub-layer thickness data at virtual wells and converting it into variable-thickness virtual well stratification point data; interpreting structural information of structural surfaces, appraisal wells, and pilot wells using seismic data, and establishing a bedding model under the control of variable-thickness virtual wells at feature points of horizontal wells; inserting small bedding planes into the fault model and bedding model using variable-thickness virtual well stratification point data and sub-layer thickness planar maps to form a shale gas reservoir structural model. The shale gas reservoir structural model established by this invention is more refined and can accurately describe the structural changes and sub-layer thickness variations of underground reservoirs, significantly improving the accuracy of faults and sub-layer bedding planes.

The application discloses a kind of fine modeling methods for single-shaft gas turbine gas path system, including establishing single-shaft gas turbine gas path system's step-by-step compression compressor module, establishing single-shaft gas turbine gas path system's combustion chamber module, establishing single-shaft gas turbine gas path system's step-by-step expansion turbine module, based on the calculation method of compressor module outlet temperature, power consumption, the calculation method of each component mass, temperature of combustion chamber module outlet and the calculation method of turbine module outlet temperature, power, using Python simulation platform establishes single-shaft gas turbine gas path system model, obtains rated operating condition and actual operation data, the data of rated operating condition is input into the single-shaft gas turbine gas path system model built, and the dynamic characteristics of gas turbine are analyzed;It aims at solving the problem of insufficient accuracy caused by neglecting the change of specific heat capacity with temperature and the evolution of combustion product composition in the existing model.