148 results about "Acquisition Scheme" patented technology

The invention discloses a marine environment real-time monitoring and early warning system based on machine learning, and relates to the technical field of machine learning. Comprising the steps that an ocean multi-source sensing module collects ocean environment data in real time through a sensor and a combined collection scheme; the multi-source feature extraction module performs time domain, change rate and frequency domain feature analysis on the data to construct a unified multi-dimensional feature vector; the multi-model fusion prediction module outputs a marine environment state vector through dynamic weighting and deviation correction based on a parallel learning architecture of a deep neural network, a long-short-term memory network and a one-dimensional convolutional neural network; and the ocean risk identification and early warning module generates graded and classified early warning information through double study and judgment of a sea condition classifier and an abnormal event detector. According to the method, comprehensive acquisition, deep feature mining, high-precision prediction and accurate early warning of marine environment data are realized, the problems of low prediction precision, risk identification lag and the like in the prior art are effectively solved, and reliable guarantee is provided for marine operation safety.

The invention discloses a dangerous behavior recognition method and device based on multi-source physiological signal fusion, and aims to generate a physiological synchronization value reflecting a heart-brain coupling state by monitoring electroencephalogram and electrocardiosignals and calculating a phase locking value. Strong coupling signal pairs are screened based on physiological synchronization values, abnormal delay propagation paths and cascade mutation points are extracted, and dangerous trigger nodes and high-risk accumulation areas are identified through energy density analysis; the abnormal gradient field is subjected to rotation modulation innovatively through electroencephalogram signals, and a dynamic gradient field is generated to determine a dangerous behavior boundary; establishing an electrocardio resonance matching mechanism to generate a self-adaptive monitoring sequence and a grading early warning strategy; dynamically optimizing resource configuration and constructing a danger convergence field by adopting an adaptive acquisition scheme triggered by rhythm variability; and finally, early warning information is converted into a specific dangerous behavior category based on an accurate identification window, and an omnibearing intelligent monitoring solution is provided for high-risk operation safety management.

The invention discloses a diabetic patient data management method and system based on big data. The method comprises the steps that basic information and stable blood glucose data of a patient are collected, similar cases are matched through a cloud database to obtain influence factors, and a personalized data collection scheme is generated; customizing a user terminal and establishing a data management container, adaptively acquiring blood glucose and influence factor data, calculating a change degree through a sliding window algorithm and performing early warning; and dynamically updating influence factor weights by adopting a time-varying weight model, and generating an intervention strategy according to the weights. The system comprises a cloud server, a comprehensive management terminal, a user terminal and other modules, and realizes data acquisition-analysis-intervention closed-loop management. According to the scheme, through big data analysis and the dynamic weight model, personalized accurate management of the diabetic patient is realized, the acquisition strategy and the intervention scheme can be adjusted according to individual differences, and the risk early warning accuracy and the management efficiency are improved.

The invention provides an edge heterogeneous Internet of Things operation and maintenance chassis data processing method and system. The method comprises the following steps: firstly, according to the types of the multi-source heterogeneous terminals, formulating a unified data acquisition scheme, defining a unified acquired data format, respectively managing and executing a data acquisition task of each multi-source heterogeneous terminal by adopting an asynchronous multi-thread scheduling mechanism, and acquiring and generating corresponding acquired original data; and performing standardization processing on the collected original data in the normal sampling state to generate a multi-source collected data set. And then, according to the type of each multi-source heterogeneous terminal, for the corresponding multi-source acquisition data set, calculating a standardized anomaly score, performing weighted comprehensive processing, generating a comprehensive anomaly score, and determining an anomaly level according to the comprehensive anomaly score. And finally, correspondingly matching the exception level of the multi-source heterogeneous terminal with a preset local protection strategy, executing a local exception protection action based on a matching result, recording exception information and reporting exception alarm information to a remote center platform.

According to the electrically-closed high-power precision gear energy-saving transmission intelligent test bed, a whole set of design is carried out on the test bed from the aspects of function requirements, motion control, loading modes, data acquisition and the like, the test bed is completely built, software and hardware debugging is carried out, and finally the test shows that the test bed has good performance. The test bed is composed of an electromechanical energy-saving transmission system, a control system and a test system, an application and implementation method of an electric sealing technology on the test bed is constructed, and a moving part strain acquisition scheme and a design and installation method of a device are provided. The test bench can provide driving force for the gear transmission system and can simulate loads under different working conditions; different gear transmission systems can be tested; expansibility and extensibility are achieved, a motion function, a test function and a data acquisition function are achieved, and high precision and accuracy are achieved; a friendly and easy-to-operate man-machine interaction interface is provided; and the purposes of energy conservation and environmental protection are achieved.

The invention discloses a teaching implementation method based on combination of motion perception and AI driving, and relates to the technical field of education and teaching. The implementation of the teaching method comprises the steps of multi-modal data expansion and acquisition, cross-dimensional dynamic evaluation and cognitive diagnosis, emotion adaptive feedback and intervention, cross-scene learning map construction and capability migration, and whole-process data closed loop and systematic evolution. And the multi-modal data expansion acquisition comprises the steps of dynamic data acquisition, physiological data acquisition, environmental behavior data acquisition and data preprocessing. The method has the advantages that a multi-modal data acquisition scheme of a common mobile phone camera and a built-in sensor is adopted; the system replaces the traditional dance teaching which depends on special three-dimensional modeling equipment and sensor gloves for boxing teaching, reduces the hardware cost, can realize full scene coverage of families, classrooms, outdoors and the like without professional site deployment, and solves the core problems of high hardware cost and limited scenes in the prior art.

The invention discloses a method for constructing a computable road network. Road data in the vector map are extracted, line string data or line segments obtained by splitting the line string data are used as connecting edges, geographic feature codes containing Geohash information are given to starting points and ending points of the connecting edges, and therefore a basic road network map is constructed. And extracting a middle vertex set of the basic road network diagram and an edge attribute set of middle vertex connection edges, and carrying out road network vertex optimization based on edge attributes to obtain an optimized computable road network. Geographic feature codes adopted by the method comprise spatial geographic information and have the characteristics of graph vertex coding, and the constructed road network graph can be used for graph calculation and verification and restoration of road connection relations. Furthermore, in combination with a representation point acquisition scheme provided by the invention, a road network map fusing facilities and equipment can be constructed, so that the application range of the computable road network is expanded. The computable road network constructed by the method is high in operation efficiency and suitable for different production environments.

The invention relates to the field of neuroscience experiments, and discloses a method for accurately adjusting the precision of targeted light and calibrating neuron sampling images, which comprises the following steps of: 1, acquiring image data containing neuron activity information; step 2, preprocessing the image data to remove artifact noise; step 3, modeling the deformation of the nervous tissue based on the image data; step 4, regulating and controlling optical system parameters for targeted light stimulation according to a deformation modeling result; and 5, closed-loop updating is performed on the modeling result and the regulation and control parameters based on feedback image data, the image data in the step 1 comprises a calcium imaging image and a targeted light feedback image which are synchronously acquired, the calcium imaging image is used for reflecting neuron activity, and the targeted light feedback image is used for calibrating a light spot position. By adopting an accurate calcium imaging technology and a targeted light feedback image synchronous acquisition scheme, real-time synchronization of neuron activity and light spot position is realized.

The invention discloses a tidal flat vegetation pattern information extraction method based on unmanned aerial vehicle photogrammetry. The method roughly comprises the following steps of (1) task planning, (2) data acquisition, (3) data preprocessing, (4) feature extraction, (5) classification and identification, (6) pattern analysis and (7) precision verification. According to the method, a multi-spectrum and RGB fused unmanned aerial vehicle image acquisition scheme is adopted, the acquisition opportunity is optimized in combination with tide forecast data, accurate extraction of multi-level information such as tidal flat vegetation types, coverage and biomass can be achieved through integration of deep learning and a traditional remote sensing classification method, and the method is high in pertinence, easy to operate and suitable for popularization.

The invention provides a plant phenotype platform three-dimensional imaging method and device based on multi-sensor fusion, and the method comprises the steps: collecting the original three-dimensional point cloud data of a plant through a plurality of heterogeneous imaging sensors carried on a plant phenotype platform, and carrying out the time synchronization processing and space registration processing. And dynamically calculating the confidence coefficient weight of each data point according to the environment illumination condition, the measurement attribute of each data point in the registration point cloud set and the characteristics of the imaging sensor to which the data point belongs, and obtaining a point cloud set with a point-level confidence coefficient weight. Performing adaptive weighted fusion processing according to the spatial distribution of the point cloud set to generate a preliminary fusion point cloud model; and according to a quality index of the model and a real-time environment illumination condition, dynamically adjusting and calculating a weight parameter of a confidence coefficient weight, and finally outputting an optimized three-dimensional point cloud model after iterative optimization. The defect that a fusion result of an existing plant three-dimensional phenotype accurate acquisition scheme is insufficient in stability and precision in a complex and changeable field environment is overcome.

The invention relates to the technical field of civil engineering detection, and discloses an automatic standard penetration data acquisition system based on the Internet of Things, which comprises a data acquisition module used for acquiring acceleration and vibration data in a test process through a sensor mounted on a standard penetration hammer; the data transmission module is used for transmitting the collected original data to a remote server or a cloud through a wireless communication technology for storage and processing; the data processing module is used for carrying out denoising, normalization, feature extraction and nonlinear dynamic modeling on the acquired signal data to obtain dynamic features of the standard penetration test process; and the data analysis and prediction module is used for analyzing the data based on a deep learning algorithm and predicting the soil bearing capacity and abnormal conditions occurring in the test process. A standard penetration data automatic acquisition scheme based on the Internet of Things is adopted, full automation of data acquisition, transmission and processing is achieved, and the test efficiency and accuracy are remarkably improved.

A digital twinning monitoring method for the full-life health state of a service aircraft structure belongs to the related technical field of digital twinning, and comprises the following steps: firstly, designing a health state data acquisition scheme to obtain health state data in a real flight state; secondly, performing screening extraction and optimization treatment on the health state data, and constructing a flight data-mechanical response data health state data set of a service aircraft structure; thirdly, establishing a flight data-mechanical response data-life monitoring digital twinborn model, and realizing high-precision prediction of the fatigue residual life of a service aircraft structure; and finally, making an inspection and maintenance task intelligent planning scheme, and dividing inspection and maintenance grades based on the fatigue residual life and the fatigue reliability coefficient. According to the method, fatigue residual life prediction and inspection and maintenance task intelligent planning of the service aircraft structure can be realized, a service aircraft structure full-life health state digital twin monitoring process is formed, and full-life health state monitoring and management can be conveniently carried out for the service aircraft.

The invention relates to the technical field of fusion terminals, and particularly provides a fusion terminal data reporting missing rereporting method and system and a medium, and the method comprises the steps: through a reporting task initialization mechanism, when a fusion terminal is started or a task scheme and a table file change, emptying historical data and carrying out initialization again; adopting an acquisition scheme matching strategy based on the matching degree and the interrogation interval to accurately select a target acquisition scheme; in combination with a two-stage compensation mechanism of self-compensation and failure linked list compensation, compensation is scheduled according to protocol timeout in the self-compensation stage, and periodic compensation, forced compensation and redundant data cleaning are executed in the failure linked list stage. Through the above steps, the integrity and reliability of data reporting of the fusion terminal are effectively improved, and the accuracy of collection success rate statistics of the master station is guaranteed.

The invention relates to the technical field of oil and gas pipeline valve inner leakage online diagnosis, and discloses an oil and gas pipeline valve inner leakage online diagnosis method based on voiceprint analysis. According to the method, valve operation voiceprint data are obtained through a distributed interface to construct a feature database, a diagnosis framework is designed according to the database, and a multi-source voiceprint collection scheme is determined. And the voiceprint acquisition terminal acquires a multi-dimensional voiceprint signal according to the scheme, inputs the multi-dimensional voiceprint signal into a model after feature extraction to complete inner leakage level judgment and abnormal mode recognition, and outputs a diagnosis result. A diagnosis result is transmitted to the management optimization module, and diagnosis strategy adjustment is achieved through timestamp calibration, mapping table construction and the like. And a three-level evaluation sub-frame is also constructed to assist diagnosis. According to the method, accurate diagnosis and strategy optimization of oil and gas pipeline valve inner leakage are realized, and the diagnosis management level is improved.

The invention discloses a defect detection method and system for a semiconductor sample, relates to the technical field of semiconductors, and solves the technical problem of low recognition efficiency of partial defects on the surface of a semiconductor caused by an inherent detection scheme of existing semiconductor surface defect detection. Comprising the following steps: acquiring a first image group of a to-be-detected semiconductor sample, and sequentially inputting each detection image in the first image group into a defect identification model to obtain a corresponding identification type and confidence; the defect identification model is obtained through artificial intelligence model training; generating a secondary acquisition scheme based on the identification type and confidence of each detection image; the secondary acquisition scheme comprises a plurality of second camera coordinates and a second shooting direction; acquiring a second image group of the semiconductor sample to be detected; generating an identification result based on the detection images in the first image group and the second image group; and the accuracy of semiconductor surface defect detection is improved.

The invention discloses a distributed intelligent well logging system and a well logging method, and relates to the technical field of intelligent well logging. The distributed intelligent well logging system comprises an intelligent well logging module, a ground intelligent control module and a communication module; the number of the intelligent logging modules is N, and N is an integer larger than 1; the intelligent well logging module is arranged underground and used for collecting, processing and uploading well logging data. The ground intelligent control module is arranged on the ground and is used for receiving and analyzing data uploaded by the intelligent logging module and sending an acquisition scheme to the intelligent logging module; the intelligent well logging module and the ground intelligent control module are in two-way communication through the communication module. The intelligent logging module comprises a data acquisition unit, a first processing unit and a first communication interface unit; the ground intelligent control module comprises a second communication interface unit, an intelligent analysis unit and a control instruction generation unit, underground intelligent preprocessing and ground real-time analysis are achieved through deep fusion of a distributed architecture and an artificial intelligence technology, and an acquisition strategy can be dynamically optimized according to an analysis result.

The invention discloses an inter-device data acquisition method supporting multi-protocol unified acquisition. A node browser, a protocol library, a node model, a protocol packaging interface and a data container are included. Wherein the node model comprises a root node, a protocol node and a data item node; according to the invention, an integral node model is constructed based on a three-layer node model architecture, so that unified acquisition and management of equipment data are realized; the system firstly uses a root node to represent equipment, and automatically matches and connects to a corresponding protocol; the protocol node encapsulates different protocols supported by different devices, and realizes protocol connection through dynamic loading; the data item node defines a specific acquisition item of the equipment data and performs acquisition according to a unified data format; a data container is also constructed to realize uniform format storage of the collected data; by adopting an innovative node model design, a multi-protocol acquisition scheme is integrated, the equipment access can be simplified, the data acquisition efficiency is improved, and the consistency and efficient storage of data are ensured.

The invention relates to the technical field of data processing, particularly provides a data acquisition system, method and equipment based on an authorized webpage resource access level and a medium, and aims to solve the problem of low network data processing efficiency. In order to achieve the purpose, the data acquisition system comprises a resource access level acquisition module used for acquiring a resource access level based on webpage response data and webpage serialization characteristics of an authorized target webpage, and a data acquisition module used for acquiring the resource access level if the resource access level is greater than a preset access level. If yes, generating a robot process automation data collection script based on the webpage response data, the webpage serialization features and the resource access level, and obtaining target data of the authorized target webpage based on the robot process automation data collection script; if the resource access level is smaller than or equal to the preset access level, the target data of the authorized target webpage is obtained based on the automatic browser frame and / or the preset data collection interface, and the optimal collection scheme can be dynamically selected.

The invention discloses a gravity dam safety risk management and control method based on a knowledge graph and a large model, and the method comprises the steps: constructing a gravity dam safety risk space-time knowledge graph which comprises an entity layer, a relation layer, an attribute layer and a time-space mapping layer, and achieving the full-life-cycle multi-source data structured association; constructing a knowledge enhanced large model, and embedding the space-time knowledge graph into a reasoning process; real-time and historical data of the gravity dam are collected and preprocessed, and the large model is input; calling a map association relationship and an evolution rule through a large model to complete risk anomaly identification, cause positioning and evaluation; historical cases and industry specifications in the atlas are retrieved, and a management and control decision scheme matched with the current working condition is generated; and collecting scheme execution data, extracting new knowledge and updating the graph. According to the invention, a closed-loop management and control mode is constructed, and the intelligent and refined level of risk management and control is improved.

The invention discloses a while-drilling azimuth acoustic logging data acquisition method, and belongs to the technical field of while-drilling logging. The invention discloses a while-drilling azimuth acoustic logging data acquisition method. The method comprises the following steps: S1, acquiring natural gamma intensity, formation resistivity, three-axis vibration signals and a tool face angle of a current depth formation; s2, geological events of the current stratum are recognized according to the natural gamma intensity, the stratum resistivity and the three-axis vibration signals, and the geological events comprise a first geological event and a second geological event; s3, a first collection strategy is executed on the first geological event to collect waveform data, a second collection strategy is executed on the second geological event to collect waveform data, the first collection strategy and the second collection strategy both adopt an equal azimuth interval collection scheme, and the azimuth interval of the first collection strategy is larger than that of the second collection strategy; and S4, transmitting the waveform data acquired by the first acquisition strategy to a time difference statistical value, compressing the waveform data acquired by the second acquisition strategy, and preferentially transmitting the waveform data.

The application discloses a cooperative flight control method and device based on a weather station and a base station, and a computer readable storage medium, wherein the method comprises the following steps: when an aircraft flies along a preset route, first station position and first station attribute of a weather station are queried and acquired according to current weather data request; when the first station position is in the range of the preset route and the first station attribute is a co-construction station of weather communication, the weather data request is sent to the co-construction station, so that the co-construction station sends the collected weather data to the aircraft; or the weather data request is sent to the independent base station, so that the independent base station acquires the weather data collected by the weather station in the communication range of the independent base station and forwards the weather data to the aircraft. The application realizes an aircraft weather data acquisition scheme based on a weather station and a base station, so that the aircraft can effectively acquire the weather data along the route and ensure flight safety.

The application is specifically a naked eye 3D virtual reality display system and method, and relates to the technical field of naked eye 3D display and virtual reality, comprising: a test pattern generation module; a photoelectric signal acquisition module; a signal phase analysis module; and a rendering parameter compensation module.In the application, the traditional external camera acquisition scheme is abandoned, a photosensitive sensor is attached to the inner side of a display module glass cover plate through optical glue, and a light shielding film and a frame wrapping design are matched, so that external environmental light can be isolated, signal distortion caused by environmental light reflection can be eliminated from the hardware structure; at the same time, a preprocessing circuit and the sensor are integrated at a zero distance, a tunable gain transimpedance amplifier band-pass filter is used to effectively filter out power frequency and high frequency noise, and a sinusoidal gray scale stripe design reduces spectral aliasing.

This application provides an adaptive seismic acquisition scheme generation method and system. The method includes acquiring a high-density seismic acquisition scheme corresponding to the area to be surveyed; calculating the redundancy of each physical point in the high-density seismic acquisition scheme; determining the maximum redundancy of each physical point based on the redundancy and acquisition cost; selecting a target redundancy less than or equal to the maximum redundancy from the redundancy of all physical points, and using the physical points corresponding to the target redundancy as acquisition points; and generating an adaptive seismic acquisition scheme based on the acquisition points. This application calculates the redundancy distribution of seismic data, omitting physical points with high redundancy in high-density acquisition, allowing for better recovery through subsequent reconstruction algorithms. By acquiring only essential key physical points with low redundancy, it significantly reduces the cost of high-density seismic acquisition while achieving high-density acquisition results, which is of great significance for high-precision seismic exploration.

The invention discloses an OBN seismic acquisition excitation point pitch and OBN point pitch parameter determination method, electronic equipment, a storage medium and a device. The method comprises the following steps: acquiring seismic data of a target area; constructing a three-dimensional fine geological model based on the seismic data; calculating a space sampling interval of each target stratum based on the three-dimensional fine geological model; determining a surface element grid of the target area based on the spatial sampling interval; calculating excitation point pitch and OBN point pitch parameters based on the surface element grid to obtain a plurality of excitation point pitch and OBN point pitch parameter combinations; and comprehensively analyzing the plurality of excitation dot pitch and OBN dot pitch parameter combinations, and determining an optimal excitation dot pitch and OBN dot pitch parameter combination. According to the method, the problem of determining the excitation dot pitch and OBN dot pitch parameters in the OBN acquisition scheme design process can be solved, the acquisition parameters are optimized, the imaging precision of OBN acquisition data is improved, and the OBN acquisition cost is reduced.

The present invention relates to the field of computer vision and discloses a method and system for collecting camera motion data sets, including: First, obtain the initial parameters of the camera, determine the shooting range trajectory and analyze its motion pattern and trajectory trend, obtain the trajectory feature sequence through trajectory analysis, and calculate the motion speed value. Then, analyze the shooting scene based on this, extract key scene elements after evaluation, and further determine the acquisition path. Detect and optimize the acquisition control parameters based on path interference items, calculate the acquisition optimization ratio, and finally generate data acquisition seeds according to this ratio, query the detailed parameters and acquisition identifiers, so as to generate a data acquisition plan. The present invention can improve the acquisition efficiency of camera motion data.

The invention discloses an intangible cultural heritage digital display method, and relates to the technical field of data processing, and the method comprises the following steps: building a quantitative evaluation system, classifying intangible cultural heritage to obtain classification results which are specifically divided into a class A, a class B and a class C. The class A is a dynamic class, the class B is a contextual class, and the class C is a static class; differentiated data acquisition schemes are deployed according to categories, data acquisition is carried out on the intangible cultural heritage, knowledge graph construction is carried out on the acquired data, and digitization of the intangible cultural heritage is completed; by performing quantitative evaluation and classification on the intangible cultural heritage, the classification accuracy can be increased, the repeated purchase cost of equipment can be reduced, a classified multi-modal acquisition scheme can be designed, heterogeneous data right confirmation and sharing can be realized by adopting a block chain cross-chain protocol, and the cultural context of the intangible cultural heritage can be completely restored. Cross-mechanism data islands are broken, the microcosmic feature digitization precision is improved, and a multi-branch narrative system is constructed.

The embodiment of the invention provides a rendering instruction processing method and device, electronic equipment and a storage medium. The method comprises the steps that an original rendering instruction sequence sent by an engine layer to a target interface layer is obtained, and the target interface layer is used for shielding the interface difference of different graph driving interfaces and sending corresponding rendering instructions to the different graph driving interfaces; parameters corresponding to rendering instructions in the original rendering instruction sequence are obtained, and the parameters and the rendering instructions are stored in an associated mode; determining a target rendering instruction in the original rendering instruction sequence, obtaining rendering target content corresponding to the target rendering instruction, and associatively storing the rendering target content and the target rendering instruction; and updating parameters associated with the rendering instruction based on the rendering target content and the target rendering instruction to optimize the rendering instruction. According to the embodiment of the invention, the universality of the rendering instruction acquisition scheme is improved, and the rendering instruction acquisition scheme and the optimization scheme are simplified.

The invention discloses a front-end information acquisition method, a front-end information acquisition device and computer equipment. The method comprises the steps that plug-in types loaded in a software development kit SDK are obtained, and plug-ins of different types are used for being matched with collection events of different types; receiving an operation instruction of the front-end interface, triggering a target collection event corresponding to the operation instruction, and obtaining a target element in a document object model DOM operated by the operation instruction; and collecting event data corresponding to the target element by adopting a target type plug-in matched with the target collection event. According to the invention, the technical problem of low flexibility caused by a fixed acquisition scheme in the prior art is solved.

The invention provides a method and system for quantitatively evaluating desert area vibroseis acquisition parameters, and the method comprises the steps: determining an appropriate vibroseis targeted processing flow through the high-density three-dimensional seismic test data of a desert area vibroseis, carrying out the data recombination of original full data through designing a plurality of different degradation acquisition schemes, and carrying out the quantitative evaluation of the desert area vibroseis acquisition parameters. And then data processing is carried out by using the same processing flow and corresponding parameters, analysis in the aspects of signal-to-noise ratio, fracture and reservoir is carried out on the processed post-stack data, and the effects of several different schemes are compared to determine an appropriate acquisition observation system, so that accurate quantitative evaluation of the acquisition parameters of the vibroseis in the desert area is realized. And powerful technical support is provided for further popularization of a controllable seismic source exploration technology in the area in the future.