181 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 relates to the technical field of industrial data acquisition and processing, and discloses a different industrial data optimal acquisition scheme analysis system and method based on an SCADA system, and the system comprises an industrial data acquisition information processing module, an industrial data acquisition scheme analysis module, and an industrial data acquisition optimal scheme generation module. According to client target industrial data acquisition scheme type information, in combination with an intelligent identification algorithm and industrial data acquisition scheme equipment composition information, industrial data acquisition scheme equipment composition information efficient retrieval is carried out, and equipment information used by different types of industrial data acquisition schemes is efficiently and scientifically analyzed; the industrial application applicability of the SCADA system is improved; the unit price information of the client target industrial data acquisition scheme composition equipment and the cost information of the client target industrial data acquisition scheme are scientifically and accurately counted, the cost information of different types of industrial data acquisition schemes is autonomously measured on line, and the scientificity of the industrial application of the SCADA system is improved.

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 discloses a printing machine equipment operation optimization process and system based on multi-vision analysis, and the method comprises the steps: obtaining multiple groups of image data in a printing process through employing a multi-vision collection scheme in a preset production period; main feature data are obtained through texture and contour feature extraction and a PCA analysis method, the recognition rate of solder paste printing is calculated through the recognition model, the recognition rate is judged, and an acquisition scheme is adjusted. And fusing the multi-image feature set by adopting a DCA feature fusion algorithm to generate a plurality of groups of feature maps, and processing the feature maps through a convolutional neural network to obtain a plurality of groups of fused feature data. And meanwhile, equipment operation parameters are obtained, defect identification is conducted on the fused feature data through the identification model, operation evaluation and optimization are conducted on the real-time equipment operation parameters based on defect information, and the printing quality and the production efficiency are ensured. According to the invention, equipment operation analysis and printing defect evaluation can be effectively carried out from multiple visual features, the intelligence of equipment operation is realized, and the production benefit is 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.

The invention provides a land resource management information platform based on cloud computing, and relates to the technical field of data processing, and the method comprises the steps: an obtaining module, which initializes a current solution into a group of land resource information collection schemes; on the basis of the current solution, generating a new land resource information acquisition scheme through random disturbance; calculating an objective function value for the new land resource information acquisition scheme through an objective function; whether a new solution is accepted or not is judged by using a Metropolis criterion, and after the new solution is accepted, the current solution is updated into the new solution; reducing the current temperature according to a preset temperature reduction rate, simulating cooling in the annealing process until a preset number of iterations is reached so as to obtain an optimal solution, and determining a final land resource information acquisition scheme according to the optimal solution; and collecting land resource information according to the final land resource information collection scheme. According to the invention, the information acquisition efficiency is improved.

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 relates to the field of data management, and discloses a full-link data management method and device, computer equipment and a storage medium. According to the full-link data management method, a vehicle repair corpus classification template is designed according to an application scene and a service demand, an acquisition scheme is formulated based on the classification template, vehicle diagnosis and maintenance data are acquired, and the data are managed. The method comprises the following steps: acquiring data of a vehicle, performing first preprocessing on the data to obtain standardized vehicle diagnosis and maintenance data, auditing the standardized vehicle diagnosis and maintenance data to obtain standard vehicle diagnosis and maintenance data, performing second preprocessing on the standard vehicle diagnosis and maintenance data to obtain data meeting requirements, storing the data in a database, and generating a vehicle maintenance corpus. According to the full-link data management method, data collection, cleaning, auditing and storage are covered, a full-link data management process is constructed, duties of all links are clearly divided, the operation process is clear and orderly, efficient development and standard execution of data management work are ensured, and the overall efficiency, quality and usability of data processing are remarkably improved.

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 relates to the technical field of sensor connection, and discloses a connection method and device for a sensor and an acquisition storage medium and computer equipment, and the method comprises the steps: obtaining a sensor with independent identification information, and configuring a plurality of candidate connection interfaces of the acquisition storage medium to obtain a plurality of connection interfaces with unified attributes; the method comprises the following steps: physically connecting a sensor with any connection interface with unified attributes in an acquisition storage medium to obtain an initial connection state; performing identity recognition by adopting a target recognition technology to obtain recognition information; the sensor information is checked, a data collection scheme is generated, the data collection scheme is used for collecting physical change data of valve operation, and the physical change data is stored through a collection storage medium. The method is applied to the field of valve diagnosis and has a reliable and convenient sensor information management mechanism and a super-convenient sensor use mechanism; and a super-wide standby interface strategy is unified, and more types of sensors can be compatible.

A method and middleware for collection and distribution of industrial data, and a storage medium. The middleware comprises: a configuration module, a collection module, a communication message queue module, a data storage and distribution module, and a data query interface, wherein the configuration module is used for receiving a collection scheme and a collection task which are configured by a user; the collection module is used for receiving the collection scheme and the collection task issued by the configuration module, and collecting data; the communication message queue module is used for receiving and publishing the collected data; the data storage and distribution module is used for storing and / or distributing the collected data; and the data query interface is used for querying the stored data for required data in response to a data query instruction. The method for collection and distribution is applicable to various fields of industrial control. A general platform for industrial data is provided, and repeated work of a service end is avoided, thus making collection and distribution of the industrial data convenient, and improving the efficiency of collection and distribution of the industrial data; and a customized query for collected data can be conveniently made.

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 discloses a data storage method for an electric energy meter and a hanging household meter of an electricity utilization information acquisition terminal. The method comprises the following steps: firstly, dividing an available storage space of equipment into N storage blocks, then setting a plurality of storage link variables in one-to-one correspondence with acquisition schemes in a storage area outside the available storage space, recording whether the corresponding storage blocks are allocated to the acquisition schemes or not, the storage link variables including N bits in one-to-one correspondence with the storage blocks. And according to the storage link variables of all the started acquisition schemes, determining the storage blocks which are not allocated for allocation, wherein the storage blocks allocated by the same acquisition scheme are regarded as a continuous storage space to be operated by the system. According to the method, a basis is laid for rapid storage and indexing of data by storing the storage blocks occupied by the link variable records and the link acquisition scheme, so that storage and query of the user meter data are realized under the condition that the system does not have a file management function.

The invention relates to the technical field of data processing, and discloses a bridge construction violation behavior monitoring method, device and equipment and a storage medium, and the method comprises the steps: determining an effective monitoring time period of a construction monitoring point through obtaining a planned time period of executing each construction process in each bridge construction section; according to the monitoring type information and the monitoring risk level of each construction monitoring point, taking an image acquisition distance interval corresponding to the monitoring type information and an image acquisition frequency interval corresponding to the monitoring risk level as constraints, taking a flight distance as an optimization target, and optimizing and solving an unmanned aerial vehicle image acquisition path planning strategy; according to the method, the unmanned aerial vehicle is controlled to execute flight, image acquisition and bridge construction violation judgment, and an unmanned aerial vehicle image acquisition scheme meeting different monitoring distances and different monitoring frequencies of different construction procedures is provided, so that the bridge construction violation behavior monitoring accuracy and efficiency are improved; the monitoring duration of the illegal behavior monitoring unmanned aerial vehicle is prolonged, and the method has good scene adaptability.

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 government and enterprise solution automatic assembling method and system based on intelligent arrangement, and the method comprises the steps: carrying out the initialization of a large model, including the initialization of a resource library, the setting of a rule and an algorithm, the development of the algorithm, data collection, the initialization of a scheme, and the generation of a large model case; analyzing government and enterprise business requirements through the initialized large model; based on the analyzed government and enterprise business requirements and the resource library, formulating an assembly rule, selecting matched resources from the resource library, and generating an assembly scheme; and performing algorithm optimization through a genetic algorithm, and optimizing the assembly scheme to obtain an optimal assembly scheme. According to the invention, various resources can be reasonably allocated, and while business requirements of government and enterprise customers are met, resource waste is avoided, the cost of a solution is reduced, and the resource utilization efficiency is improved.

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 voucher processing method and device, and the method can dynamically adjust a voucher collection scheme according to the characteristics of a user, thereby flexibly providing a more personalized service. Meanwhile, according to the method, the collected voucher data can be pre-verified, so that the user is guided to submit the voucher data meeting the auditing standard, the overall period of voucher auditing is shortened, and the user experience is optimized. The voucher processing device provided by the embodiment of the invention also has the above beneficial effects.

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.