294 results about "Data simulation" patented technology

The invention provides a tunnel deformation early warning method and system based on digital twinborn and data monitoring, and belongs to the technical field of computer data simulation.The method comprises the steps that firstly, entity rock stratum dynamic monitoring data, real-time construction disturbance data and initial digital twinborn model configuration parameters of a tunnel construction area are obtained; and then virtual-real dynamic coupling and feedback iteration processing is carried out on the virtual-real dynamic coupling model to generate an initial virtual-real coupling digital twinborn model, the initial virtual-real coupling digital twinborn model is iteratively optimized based on real-time construction disturbance data to obtain a final virtual-real coupling digital twinborn model, and deduction of the rock stratum deformation linkage effect is carried out according to the final virtual-real coupling digital twinborn model. The method comprises the following steps: generating a rock stratum deformation linkage path set, performing risk linkage mode identification on the rock stratum deformation linkage path set, determining a tunnel rock stratum large deformation risk linkage mode, and finally generating construction early warning information including a risk linkage diffusion area, a risk linkage evolution period and an emergency response priority according to the risk linkage mode, and transmitting the construction early warning information to a tunnel construction management system. And the tunnel construction safety is effectively guaranteed.

The invention relates to the technical field of tunnel engineering safety, in particular to a tunnel fire multi-stage damage collaborative prediction method and system, and the method comprises the steps: constructing a data simulation fusion model, and carrying out the processing of fire and tunnel structure parameter data, and obtaining a multi-working-condition parameter database; constructing a heat conduction equation, a fire plume and wall surface heat exchange relational expression, a boundary layer correction model and a comprehensive damage evaluation model, and analyzing the equation, the relational expression and the model by utilizing a multi-physical field coupling unified boundary condition to obtain a multi-physical boundary constraint condition; obtaining a multi-physical constraint loss function based on a network architecture and a multi-physical boundary constraint condition, and further obtaining a comprehensive constraint loss function of a temperature field-stress field-damage index; constructing a PINN-LSTM network architecture and a damage evolution analysis model based on the fire ending initial state coding vector, the fire course feature vector and the cooling process feature vector; and performing linkage analysis on the function, the frame and the model to predict and monitor the transient damage and the long-term creep damage of the tunnel.

The invention relates to the technical field of digital twinborn and drainage basin environment monitoring simulation, in particular to a drainage basin environment data simulation deduction system based on a digital twinborn technology, which comprises a digital twinborn management center used for calling multi-source heterogeneous monitoring data of a drainage basin environment to obtain an aligned environment data sequence; the causal coupling analysis unit is used for obtaining a steady-state logic signal or a dynamic decoupling signal; when a dynamic decoupling signal is generated, the topology adaptive reconstruction unit is used for performing structural mutation recognition feedback analysis on a calculation map of the digital twin model to obtain a reconstructed topology map; when the steady-state logic signal is generated, the simulation deduction execution unit is used for performing environment evolution deduction analysis on the aligned environment data sequence based on the current calculation map to obtain a simulation deduction result; according to the method, model calculation divergence or misleading output caused by sensor faults is effectively avoided, and the calculation problem caused by multi-source data heterogeneity is solved.

The invention discloses a ventilation cooling optimization method for an all-hydrogen-cooled gas turbine generator, and relates to the technical field of all-hydrogen-cooled generator cooling, and the method comprises the steps: analyzing cooling demands, calculating loss in combination with a high-frequency start-stop peak regulation working condition, and setting a stator RTD temperature, an iron core temperature and a temperature rise target; an end ventilation structure is designed, the diameter of the fan is optimized, and bar gaps, wind shield holes and inner supporting ring ventilation grooves are formed; optimizing variable air ducts of the iron core, and adjusting the width of the air ducts according to thermal load partitions; cFD coupling simulation verification is carried out, and a loss data simulation flow field and a temperature field are imported; carrying out physical test iterative optimization, manufacturing a prototype model, testing, and adjusting parameters until errors are qualified; operation monitoring and dynamic adjustment are carried out, and a sensor is installed to collect data in real time and adapt to working condition requirements. Cooling uniformity and efficiency are improved, peak regulation start and stop working conditions are adapted, hydrogen parameter change influences are balanced, vibration and cooling are cooperatively controlled, operation and maintenance convenience is improved through modular design, and long-term stable operation of the generator is guaranteed.

The invention discloses a data simulation method based on a database function and a timed task. The method comprises the following steps: S1, acquiring source data based on a multi-modal lightweight intelligent acquisition strategy; s2, performing data cleaning and standardization so as to ensure engineering processing of simulation data quality and consistency; s3, creating a user-defined function in the database to package intelligent logic of data simulation; according to a time condition and a data mode in the timed task, intelligently performing simulation trigger judgment and simulation data generation through the user-defined function; s4, performing efficient data injection based on a buffer and batch optimization mechanism of the intermediate table; and S5, performing timed task period regulation and control. The invention further discloses a corresponding system, electronic equipment and a computer readable storage medium.

A method comprising obtaining (611) video data comprising meta-data representative of a level of reliability of a neural network inference process implemented by an analog device, the neural network inference process being applied to decode the video data, an analog device being an electronic circuitry unable to ensure a repeatability of an output result of said electronic circuitry when said electronic circuitry receives same input data; and, decoding (612) the video data, the implementation of the neural network inference process by the analog device depending on the metadata.

The invention discloses an emergency scene driving behavior data processing method based on deep learning, and relates to the technical field of driving behavior data processing methods.The method comprises the steps that at least two data simulation modes are set, the two data simulation modes are a single working condition simulation scene and a comprehensive working condition simulation scene respectively, different driving data generated by different drivers in two working condition simulation scenes are collected, and abnormal samples are intelligently eliminated based on data relevance in the driving data and neural network anomaly detection. Obtaining first target driving data and second target driving data of a database for establishing a driver behavior model; according to the data processing method, the response speed and the safety of the automatic driving system can be effectively improved, and decision optimization and safety performance improvement for the vehicle AI are realized.

The invention discloses a knowledge point intelligent map generation and teaching path planning method and system, and relates to the technical field of teaching path planning. Heterogeneous data from different dimensions are mapped to a vector space by using a heterogeneous data mapping method, and a teaching path in a knowledge map is subjected to state space initialization; a teaching path in a knowledge graph is explored by using a heuristic graph search algorithm, a candidate teaching path set is sorted and clustered, a plurality of teaching path candidate solution sets are constructed, the plurality of teaching path candidate solution sets are sent into a parallel simulation environment, a teaching path execution process is simulated according to historical student data, and a teaching path is obtained. And after evaluating the effect of each teaching path, selecting an optimal teaching path to carry out personalized recommendation on the students. The planning system uniformly embeds complex data into a shared vector space, the generalization ability and semantic reasoning ability of the system are improved, the path with the optimal effect is screened out for recommendation, and the accuracy, flexibility and practicability of personalized teaching recommendation are remarkably improved.

The invention discloses a surrounding rock damage data analysis system and method based on multiple factors, and relates to the technical field of surrounding rock damage data simulation. A to-be-tested rock material is selected to prefabricate a closed crack group to form a stable roadway; setting different fatigue load intensities and cycle times, analyzing data changes of a stress field, a displacement field and acoustic emission under the action of the fatigue load based on an acoustic emission monitoring system, and determining a bearing performance change model; and real working conditions are simulated based on the bearing performance change model, a difference value between simulated data and real data is formed, an output target of fatigue load strength is intelligently corrected, and data compensation is realized for the bearing performance change model. According to the method, original defects such as joints and cracks in the rock mass and damage evolution under cyclic loads are included into an analysis framework, a reliable basis is provided for long-term safety and stability judgment of a roadway under cyclic load working conditions such as compressed air energy storage, and safe and efficient production of a coal mine is effectively supported.

The invention relates to the technical field of data simulation analysis, in particular to a simulation data driving-based loader load process prediction method. The method comprises the following steps that a loading lifting capacity optimization mechanical relation model is established based on structure parameters of the skid steer loader; establishing a multi-domain loader oil way-dynamics simulation coupling model; and carrying out loading machine lifting mechanical collaborative optimization processing on the multi-domain loading machine oil way-dynamics simulation coupling model through the loading lifting capacity optimization mechanical relation model so as to obtain a loading machine working condition multi-domain collaborative simulation model. Transmitting the loading machine working condition multi-source load data to a loading machine working condition multi-domain collaborative simulation model to analyze loading machine multi-domain collaborative simulation load process characteristic data; and based on the loader multi-domain collaborative simulation load history characteristic data, establishing a loader multi-domain collaborative precision optimization load history prediction mapping relationship, and generating an optimized loader multi-domain collaborative load history prediction model. According to the invention, accurate prediction of the loading process of the loader is realized.

The invention provides a mechanical property dynamic prediction method after stent implantation, and the method combines CT image three-dimensional reconstruction, finite element simulation analysis and data-driven modeling to construct a whole-process mapping relation from'stent model structure parameters-new bone growth characteristics-mechanical response '; a training data set is constructed through a large amount of simulation data, a proper analysis method is introduced to establish a prediction model, the performance change trend under different structural designs can be efficiently predicted, stent parameters can be reversely optimized, the individualized adaptability and the function-oriented design capability of the stent are improved, and the method is suitable for large-scale popularization and application. Meanwhile, a complex structure parameter space is covered by combining real bone growth data simulation, and the requirement for rapid optimization design of the stent is met; according to the method, the minimum repetitive unit of the model structure is improved and optimized, and meanwhile, the real growth condition of the new bone tissue is combined, so that the method can be more accurately and truly applied to predicting the mechanical property of the bone tissue in the growth process after the stent is implanted.

The invention discloses a power distribution network fault identification method combining deep learning and attention, and relates to the technical field of power distribution network fault identification, and the method comprises the following steps: collecting real fault data according to a lightning monitoring system, combining a simulation platform to generate simulation fault data, and inputting the real fault data into a preset generative adversarial model, outputting enhanced fault data; real fault data, simulated fault data and enhanced fault data are mixed, and a training set and a test set are constructed; optimizing a preset deep learning network containing a fault loss function and an attention network through the training set, and obtaining a power distribution network fault recognition model; and evaluating the power distribution network fault identification model by using the test set to obtain a fault type identification result. The method is used for solving the problems of small data volume and insufficient recognition precision in power distribution network fault recognition.

The invention provides a chip testing method and device and a medium, and the method comprises the following steps: determining an intermediate performance value of each target clock domain according to the clock frequency and predicted performance value of each target clock domain of a to-be-tested chip; determining a minimum value in the plurality of intermediate performance values as a target performance value; performing a performance test on the to-be-tested chip to obtain an actual performance value of a target clock domain; and if the actual performance value is not less than the target performance value, determining that the to-be-tested chip passes the test. According to the chip test method provided by the invention, whether the to-be-tested chip passes the test can be known only by performing the performance test on the target performance value. In this way, the number of performance values needing to be subjected to performance testing is greatly reduced, and therefore the number of times of data simulation and consumption of analysis resources are reduced.

The present disclosure relates to a model construction method and device, a storage medium and an electronic device, and relates to the technical field of computers. The method comprises: obtaining basic geographic information data from a target data source and performing stereoscopic processing to obtain an initial model; preprocessing the initial model to obtain a first-stage model; performing non-business logic binding on the first-stage model, and performing business logic binding on the first-stage model to generate a target model corresponding to a modeling object; and performing streaming media binding on the target model to push streaming media data corresponding to the target model to a corresponding preset terminal. The present scheme can effectively improve the performance of the model and reduce the modeling cost, and realize data simulation based on digital twinning.

The invention discloses a river ecology small sample enhancement method based on a generative diffusion model, and the method comprises the steps: obtaining observation data in an ecological environment field, and carrying out the data preprocessing; performing time variation diffusion modeling by adopting a generative diffusion model architecture; constructing an ecological constraint function, and solving an optimal solution curve; carrying out data sampling, and outputting ecological time sequence data; and performing data simulation verification and prediction analysis. By introducing a time variation diffusion process and an ecological process modeling constraint mechanism, high-precision interpolation and long-period trend deduction of ecological variables are realized while the model generation capability is maintained.

Systems, methods, and computer program products for generating data according to patterns of missing data. A method for automatically identifying patterns of missing data and generating data accordingly may comprise reading a plurality of values, each associated a subject and a variable; determining a count of missing values for each variable; selecting one or more variables of the plurality of variables based on their respective counts of missing values; identifying a pattern type characterizing a pattern of missing values for each of the one or more selected variables; and generating simulated data for each of the one or more selected variables based on the identified pattern types.

The application provides a spaceborne array laser radar three-dimensional terrain mapping data comprehensive simulation method and system, and the method comprises the steps of: establishing a spaceborne array laser radar three-dimensional terrain mapping simulation link; constructing a spaceborne array laser radar comprehensive simulation model to generate a spaceborne array laser radar three-dimensional terrain simulation dataset; and adopting noise rate, average signal photon number, detection probability, signal-to-noise ratio and elevation accuracy as multiple evaluation indexes to evaluate the quality of the spaceborne array laser radar three-dimensional terrain mapping simulation data under different parameter configurations. The application designs a spaceborne array laser photon cloud data simulation method for the ground laser angle reflection CCR, generates a set of spaceborne array laser radar three-dimensional terrain simulation dataset taking the parameters of a certain type of domestic satellite as an example, adopts multiple evaluation indexes to evaluate the quality of the spaceborne array laser simulation data under different parameter configurations, and provides a solid foundation for the development of array laser three-dimensional terrain mapping satellites.

The invention discloses a drilling blasting explosive energy transfer mode design and a data simulation method thereof, and relates to the technical field of blasting engineering.The drilling blasting explosive energy transfer mode design method comprises the steps that a rock sample is manufactured, mechanical parameters of the rock sample are tested, and the type of the rock is determined; respectively carrying out bursting tests on the multiple groups of rock samples; measuring, contrastively analyzing the average crushing particle size, the boulder rate and the total seismic wave energy of the central areas of the multiple groups of rock samples; establishing an explosive blasting energy transfer evaluation system, and determining an explosive column installation scheme; the data simulation method comprises the following steps: determining a blasting energy attenuation coefficient, an eccentric influence factor and an explosive energy transfer coefficient of a rock sample; establishing a blasting explosive energy transfer model and an explosive explosion energy density calculation formula; verifying and correcting an explosive explosion energy density calculation formula; the blasting effect can be predicted, the on-site trial blasting frequency is reduced, and the cost is reduced.

The application discloses an elevator full-data simulation test system, and relates to the technical field of elevator testing.The scheme comprises a multi-source data acquisition module, a digital twin modeling module, a full-scene simulation test module, a data processing and analysis module, a closed-loop optimization module and a terminal interaction module.The application realizes full-cycle multi-dimensional data coverage of the elevator, integrates mechanical, electrical, environmental, personnel and fault data, improves the completeness of test data, constructs a full-dimensional model based on digital twin technology, realizes multi-element coupling simulation, simulates various working conditions, fits actual operating conditions, iterates the simulation model, outputs optimization schemes, improves test efficiency and optimization effect, supports custom parameters, meets the test requirements of various types of elevators, does not require a physical test platform, greatly reduces test costs and shortens the test cycle, and avoids safety risks in physical tests.

The application relates to the technical field of satellite data processing, and provides a satellite data simulation generation method, system, medium and equipment, which comprises the following steps: parsing an XML configuration file used for defining satellite transmission frames, virtual channel data units, user frames / space packets and load fields to obtain a memory protocol object tree; recursively traversing the memory protocol object tree according to an output period to generate data frames of each layer, writing a configuration value into a fixed value field, increasing a count field by a step, converting a time field into a time code specified by a satellite protocol, continuously intercepting real load data according to a file offset modulo and a tail wrap mode for an external data field, recursively assembling a nested subframe after inheriting a parent frame context, and performing length alignment, check sum output. The protocol structure, dynamic fields and real load injection rules of satellite simulation data are configured, which is different from a scheme only facing communication coding and decoding or protocol packet assembly and analysis, and can generate continuous and high-fidelity satellite simulation data streams.

The present disclosure provides a simulation test method. The method applied to a first device comprises: generating a configuration file according to a navigation device to be tested; sending test data and the configuration file to a second device; receiving simulated sensor data and simulation positioning results sent by the navigation device to be tested; and obtaining a test result of the navigation device to be tested according to the configuration file, the test data, the simulated sensor data and the simulation positioning results. The method applied to the second device comprises: receiving the test data and the configuration file sent by the first device, obtaining a parsing result of the configuration file; processing the test data to obtain simulated sensor data according to the parsing result; and sending the simulated sensor data to the navigation device to be tested through a target data interface. The method applied to the navigation device to be tested comprises: receiving the simulated sensor data sent by the second device; obtaining simulation positioning results according to the simulated sensor data; and sending the simulation positioning results and the simulated sensor data to the first device.

The invention relates to the technical field of interference spectrum data simulation, in particular to an interference spectrum data simulation generation method based on a DFDI system, and the method comprises the steps: extracting an absorption line characteristic parameter from a standard fixed star spectrum database, combining an interferometer fixed optical path difference parameter, and generating interference fringe distribution by using an equal thickness interference principle; carrying out convolution modulation by adopting a spectrograph line spread function to obtain a continuous interference spectrum image, and carrying out discretization sampling to generate a digital data matrix; generating a diversified data set through parameterization adjustment, and adding Poisson distribution noise to simulate a real observation environment; and formatting the noise data into a dual-channel image, and finally realizing the inversion of the radial velocity through the training of the convolutional neural network. According to the method, the problem of insufficient training samples caused by scarcity of real DFDI data is solved, and the phase feature extraction precision of the interference fringes and the inversion reliability of the radial velocity are improved.

The invention discloses a soft soil revetment design method considering wave influence, and belongs to the technical field of coast engineering. The method comprises the following steps: analyzing wave elements and load data by simulating tide and wave propagation, and determining main factors influencing the deformation and stress of a revetment structure; non-linear characteristics of soft soil are simulated, and a stress path of a soil body under the action of a wave load is considered; finite element software is adopted to establish a bank protection structure model, and factors of interaction, large deformation and contact problems of the structure and a soil body are considered; through data simulation, the influence of the wave height and the wave moment on the stress and deformation of the structure is clarified; and dynamic data of the environment where the bank protection project is located is fed back to numerical simulation of the bank protection structure, and input parameters of the model are continuously updated, so that the model can dynamically reflect changes of actual project working conditions. The wave load and soft soil coupling effect can be accurately reflected, the accuracy, safety and economical efficiency of revetment design are improved, and the method is suitable for various soft soil foundation revetment projects.

The invention belongs to the technical field of unmanned aerial vehicle network simulation, and particularly relates to an unmanned aerial vehicle network simulation plug-in which is embedded into an external unmanned aerial vehicle simulation platform in a dynamic library or service form and is used for simulating end-to-end transmission of business data among multiple machines. The plug-in comprises a link state broadcast module, a routing calculation module, a service data simulation module, a fault injection interface and a universal interface module; a composite link cost function is adopted in routing calculation, a distance soft threshold, adaptive normalization delay and packet loss items and HOPCOST are fused, and invalid multi-hop is inhibited; the service module restores the propagation path based on the routing table, accurately accumulates and calculates the total delay and the end-to-end packet loss rate, and executes scheduling or discarding; and cross-platform joint simulation is realized through a plurality of protocols, such as DDS, ROS2, Redis and the like, adapted by depending on injection. According to the method, the problems of business modeling distortion, insufficient dynamics, interface sealing and the like of the existing tool are solved, and the authenticity, the flexibility and the engineering practicability of large-scale unmanned aerial vehicle network simulation are improved.

The application discloses a kind of integrated transmitter systems of multi-protocol sensor data collaborative processing, including microcontroller module, sensor interface module, data collaborative processing module, communication output module, analog output module, linkage control module and display control module, data collaborative processing module includes protocol analysis unit, calibration processing unit and runtime data structure, the data of sensor acquisition of different communication protocols is converted into uniform data format by protocol analysis unit, write into same runtime data structure after calibration offset processing, respectively form communication register data, analog output data, alarm state data and display refresh data in microcontroller module, so that communication output module, analog output module, linkage control module and display control module are collaboratively operated around same data source, with the advantages of easy multi-protocol sensor access, good multi-output channel consistency, stable alarm linkage and strong adaptability to field deployment.

The utility model discloses a train operation scene test platform based on an unmanned driving mode, and relates to the technical field of train data simulation. Comprising a temperature detection simulation module which is composed of an integrated circuit temperature sensor, a diode and a first addition arithmetic unit and is used for detecting the surface temperature of the train diesel engine through communication of the sensor and the diode; the train running speed simulation module comprises a tachometer conversion board and a second addition arithmetic unit, and the voltage signal output by the industrial personal computer is adapted to the display equipment through the conversion board to simulate the train running speed; the disturbance signal simulation module comprises a random number generator chip and an operational amplifier and is used for simulating interference signals in the train running process and inputting the interference signals to the temperature and speed module; and the monitoring display module is composed of a microcontroller and train data display equipment, receives and displays the analog data and provides monitoring of the running state of the train. The platform can accurately simulate key parameters in the operation process of the unmanned train.

The application discloses a kind of ship complex structure no margin fast assembly method, belong to ship and ocean engineering construction technical field, the theoretical assembly position of complex structure and parent structure is sampled respectively in three-dimensional data, and is simulated assembly analysis in computer precision software, the construction deviation of parent structure itself is considered, and according to simulated assembly scheme, pre-cut is implemented, realizes large group stage no margin assembly;Assembly steps are as follows in turn: the formulation of three-dimensional point scheme;The sampling of parent structure assembly area three-dimensional coordinate data;The sampling of complex structure group three-dimensional coordinate data;Three-dimensional data simulation assembly is carried out to complex structure and parent structure;Pre-cut of complex structure;The assembly installation of complex structure.The method is through the process of "three-dimensional data acquisition→simulation assembly analysis→pre-cut→no margin assembly", replaces traditional "experience margin+high-altitude research cut" mode, to realize accurate positioning, reduce margin, reduce the goal of high-altitude operation.

The application discloses a data simulation method based on data visualization, and relates to the technical field of data analysis, comprising: constructing a distributed stream processing framework, performing parallel preprocessing on a target data set to be simulated to generate a time sequence characteristic stream; converting the time sequence characteristic stream into a multi-dimensional visualization model through an adaptive mapping layer, and realizing dynamic rendering in a visualization interface; triggering a simulation engine to execute real-time simulation based on the multi-dimensional visualization model, and jointly optimizing the visualization parameters and the simulation parameters through a feedback optimization mechanism. Through the introduction of a dynamic calculation method of the job level correlation coefficient and the space-time overlap degree, the design of the time-varying adjustment factor and the hierarchical attention mechanism, and the construction of a novel data processing and visualization framework, the application realizes the accurate identification of the talent development path across different levels, the timeliness optimization of data preprocessing, and the effective sharing of the best practices among departments.

The invention provides a big data simulation method, simulation platform and device, and relates to the technical field of simulation computation.The big data simulation method is characterized by comprising the following steps that 1, a reusable operator component library is constructed; step 2, constructing a simulation task process through the graphical interface, receiving operation of a user on the operator component through the graphical interface, and constructing the simulation task process; 3, realizing individualized data association of a multi-data-source product based on the product ID, editing a simulation task process, and realizing association loading and unified output of multi-data-source data; 4, performing parallel task scheduling and distributed calculation execution; and 5, aggregating calculation results and carrying out post-processing. The method has the advantages that the technical threshold and the use cost can be greatly reduced, precise batch modeling simulation of large-batch individuals of products oriented to multiple data sources is realized, meanwhile, efficient cloud parallel computing capability can be provided, and the data simulation modeling and computing efficiency is improved.

The application belongs to the technical field of plugging technology in the petroleum and natural gas drilling industry, and particularly provides a body swelling plugging fluid testing device and a testing method, which comprises a pressure control device, a grouting device, a receiving device, an experimental bin, a heating device and a fixing device; solves the problems that the existing technology cannot realize real well bottom data simulation, cannot solve the problem that the plugging device is blocked after plugging is completed, the plugging device body is easily damaged when being cleaned, and the plugging instrument is scrapped, can truly simulate well bottom data, can be used once or multiple times, can be replaced if damaged or blocked, is simple to operate, has low cost, and thus has high practical value.