370 results about "Data packing" patented technology

The invention provides a data acquisition method and device based on a multi-order queue and electronic equipment, and the method comprises the steps: obtaining production data generated by industrial control equipment; according to the acquisition frequency, the production data is distributed to each level queue of the multi-level queue, the queue number of each level queue is adjusted according to the real-time data volume of each queue in each level queue, and each level queue is used for caching the production data of different acquisition frequencies; according to a data packaging strategy, the production data in the multi-order queue is packaged, and the data packaging strategy comprises a timing packaging strategy and a quantitative packaging strategy; and uploading the packaged production data to an industrial Internet of Things platform. Production data acquisition is performed through the multi-order queue, so that the processing pressure of a single queue can be effectively relieved, the data transmission frequency is reduced, and the resource consumption is reduced, thereby improving the efficiency and reliability of data acquisition.

The invention relates to an elevator fault real-time monitoring and early warning method, system and terminal, and belongs to the technical field of elevator monitoring. The monitoring and early warning method comprises the steps that multi-source sensing data of an elevator are collected, and timestamp synchronization is conducted on the multi-source sensing data; calculating a comprehensive risk value of the elevator based on the multi-source sensing data after timestamp synchronization; judging whether the comprehensive risk value is greater than a risk threshold value or not; if yes, Granger causal test is operated, an abnormal causal event is searched for from a pre-constructed causal graph, and relevant data corresponding to the abnormal causal event is packaged and sent to the elevator digital twinborn body; fault acceleration simulation is carried out in the digital twinborn body, and an abnormal root is positioned; and a health assessment report of the elevator is generated according to the simulation process data and the abnormal root. The method has the beneficial effects that the actual running state of the elevator is truly reflected, so that the running safety and reliability of the elevator are improved.

The invention discloses a distributed supply chain traceability system and method supported by a block chain, and relates to the field of data analysis, and the system comprises a collection module which is used for capturing the original data of a supply chain in real time through an Internet of Things sensor, and cleaning the data; the processing module is used for constructing a distributed account book based on a HyperledgerFabric architecture, performing hash encryption on the data, performing uplink storage on the data, packaging the data into blocks according to a time sequence, and completing data verification between nodes through a BFT consensus mechanism; according to the invention, full-link data of production, logistics and the like are captured in real time through the Internet of Things sensor and encrypted and chained, so that the data cannot be tampered and can be traced in the whole process, and the problems of easy data tampering and many breakpoints in traditional traceability are solved.

The invention belongs to the technical field of blockchain and Internet of Vehicles security management, and relates to an Internet of Vehicles security and credible message sharing method based on blockchain and trust management, comprising: a message providing vehicle records and broadcasts a message, and a message receiving vehicle receives the message, scores the authenticity of the message, and broadcasts the message to a consensus vehicle; the consensus vehicle performs usefulness scoring on each authenticity score s1, i, when the number of high usefulness scores is greater than a threshold value Q, the data (m, s1, i, s2, i, c, t) is uploaded to the accounting node, and s2, i, c are high usefulness scores of the consensus vehicle c on s1, i; the accounting node receives and verifies the data (m, s1, i, s2, i, c, t), packages the verified data into a block and stores the block into a block chain; the RSU calculates the trust value of the vehicle in the area and shares the trust value to an RSU cluster; the RSU cluster makes a trust decision on the vehicle according to the trust value of the vehicle; according to the method, authenticity scoring and usefulness scoring are carried out on the message, the credibility of the shared message in the Internet of Vehicles is improved, and the authenticity and integrity of the message are ensured in combination with the block chain technology.

The invention discloses an audio signal processing method and device based on MOE, a medium and a product, and relates to the field of audio signal processing. According to the technical scheme, firstly, the audio signal processing device decomposes the audio signal into the sub-band signals in different frequency intervals, and the complexity parameter of each sub-band signal is calculated; on the basis of the sub-band signals and complexity parameters corresponding to the sub-band signals, the gating network in the hybrid expert model can intelligently distribute the optimal expert network combination for each sub-band signal, the speciality of each expert network is fully utilized, the processing efficiency is improved, the optimal expert network combination is screened by adopting a processing weight coefficient threshold, and the processing efficiency is improved. And redundant processing is avoided. And finally, the audio signal processing device obtains a structured audio data stream through quantization coding and data packaging. According to the dividing and treating method, the quality and efficiency of audio signal processing are improved, the processing strategy can be flexibly adjusted according to the signal characteristics, and the adaptability is high.

The invention provides an intelligent decision-making method and system for a job progress based on big data, and the method comprises the steps: obtaining a real-time data stream of a job site, and carrying out the unified format processing of the real-time data stream; segmenting and cleaning the data in the unified format to generate cleaned data fragments; performing aggregation processing on the cleaned data fragment set to generate an aggregated data set, and generating an early warning signal and a scheduling instruction according to the aggregated data set; carrying out data packaging on the early warning signal and the scheduling instruction, and generating a preliminary scheduling scheme in combination with historical records; and dynamically comparing the preliminary scheduling scheme with the dynamic input parameter sequence, and if a deviation value is detected to exceed a preset threshold value, optimizing the scheduling scheme based on the deviation value to obtain a final optimized scheduling scheme. The scheduling strategy is continuously optimized through dynamic comparison and a feedback mechanism, intelligent management and continuous optimization of the production process are achieved, and the production efficiency and the resource utilization rate are improved.

The invention belongs to the technical field of electric vehicle platforms, and particularly relates to a system applied to a vehicle-pile-cloud platform and a charging pile wireless communication method. A wireless CAN module is additionally installed on a charging pile, CAN bus getting-on-pile communication data is packaged and then sent to a cloud platform through a wireless communication module, and when the cloud platform monitors that a large model of the operation state of the charging pile sends out a fault early warning, the cloud platform sends an early warning instruction to a local server. When a fault occurs, the local server sends a high-frequency monitoring instruction to the corresponding charging pile, and after the charging pile receives the instruction, the sampling step length is shortened to a millisecond level through the program-controlled variable-step-length sampling module, so that working condition data of the charging pile before the fault occurs can be accurately recorded. Networking transformation of existing charging equipment can be achieved, efficient monitoring and operation and maintenance tasks of a charging operator are achieved, and the program control variable step size sampling module can ensure that working condition data are recorded in detail before a charging pile fault occurs, and follow-up fault attribution analysis is reserved.

The invention is suitable for the technical field of data processing, and provides an illumination lamp data transmission system, which comprises a plurality of illumination lamps, a plurality of PLC concentrators respectively connected with the illumination lamps on an electric power circuit in a region where the illumination lamps are located, LPWAN gateways connected with the PLC concentrators, and a monitoring center communicating with the LPWAN gateways through an LPWAN network. The lighting lamp is provided with a data acquisition module and a PLC module; the PLC concentrator is provided with a modulation-demodulation module, an error detection module and a data forwarding module; the LPWAN gateway is provided with a data coding module, a data packaging module and an LPWAN communication module; the monitoring center comprises a data receiving module, a decoding processing module and a data processing module. The problem that an existing lighting lamp is poor in data transmission signal stability in a special environment where communication is inconvenient is solved.

The invention relates to the technical field of data acquisition, in particular to a multi-source heterogeneous bus data parallel acquisition recording method and system, and the method comprises the steps: initializing a task period and a maximum sampling period; scheduling the tasks in the task queue based on the task cycle, setting a time step length and marking schedulable tasks; setting sampling channels according to the number of schedulable tasks and distributing the sampling channels to sampling threads; packaging the acquired data into an acquired data packet and aligning by taking a timestamp as a reference; offset calculation and compensation are carried out on the collected data packet; controlling a data acquisition thread to start according to the data capacity and the sampling frequency; the time difference and the content similarity of adjacent data packets are detected, and intelligent data merging is executed; storing the processed data packet in real time; through the adaptive task scheduling and precise time alignment technology, efficient parallel acquisition and precise recording of heterogeneous bus data are realized, and the synchronism, integrity and processing efficiency of data acquisition are remarkably improved.

The invention discloses an electrical pipeline fault early warning method and system, and relates to the technical field of electrical pipelines, and the method comprises the steps: collecting electrical pipeline data, carrying out the preprocessing of the collected data, packaging the processed data, transmitting the packaged data to a central processing unit, analyzing the data, extracting characteristic parameters, and combining a predefined rule base, the method comprises the following steps: carrying out fault feature identification and abnormity determination, matching a fault mode based on identification features, evaluating a fault type and a severity degree, predicting a fault probability in combination with a historical data trend, automatically generating an early warning message when real-time data exceeds a preset threshold value, sending structured early warning information through a multi-mode communication channel, and tracking and confirming a state. And triggering preset emergency operation, and meanwhile, providing a manual intervention interface and recording a processing process. By monitoring the parameters of the electrical pipeline in real time and triggering an early warning mechanism, the safety problem is identified and processed before the fault occurs, the downtime is reduced, the reliability of the pipeline is improved, and preventive maintenance is realized so as to reduce the emergency maintenance cost.

The invention discloses a power Internet of Things data transmission method and device and a medium, and belongs to the field of power network networking, and the transmission method comprises the steps: collecting power data such as current, voltage and power in real time based on a sensor, and carrying out the de-noising of the data through Kalman filtering; layering packaging is carried out according to the data type, a data compression algorithm is applied to compress the data, the transmission bandwidth is reduced, the compressed data is encrypted, and integrity verification information is added; dynamically selecting a transmission channel by using a reinforcement learning algorithm according to a real-time network state; the data are packaged and sent to the cloud through the selected transmission channel, the data are received at the cloud, and the power data are stored and managed by using a time sequence database; and analyzing the received data, generating a real-time report, carrying out anomaly detection and load prediction through a random forest algorithm, and carrying out adaptive adjustment according to the real-time monitoring data. By dynamically selecting a transmission channel and a self-adaptive transmission strategy, network instability is dealt with, and timely transmission of data is ensured.

The invention discloses a bedside skin flap blood flow monitoring and early warning device and computing equipment, and the device comprises a skin flap tissue perfusion monitoring module which comprises a probe housing, a microcirculation blood flow velocity sensor, a tissue oxygenation degree sensor and a flexible connecting arm; the data acquisition and transmission module is used for receiving the blood flow velocity data and the oxygenation degree data through a data line and carrying out analog-to-digital conversion and data packaging; the central processing unit comprises a data storage module, a data analysis module and an early warning module; the data analysis module comprises a baseline establishment sub-module, an anomaly detection sub-module and a trend prediction sub-module; and the early warning module is used for displaying a red alarm through a bedside display screen and sending a short message alarm containing the patient name, the bed number, the early warning type and the severity information to a medical staff mobile terminal through the wireless notification module. According to the invention, the abnormal condition of skin flap blood perfusion can be found and predicted in time, and the workload of medical staff is reduced.

The invention discloses a BIM / CIM-based engineering design whole-process auxiliary decision-making method, relates to the technical field of engineering design, and discloses a BIM / CIM-based engineering design whole-process auxiliary decision-making method, which comprises the following steps: responding to a project red line range, obtaining geographic space data, and carrying out preprocessing, model reconstruction and lightweight processing on the geographic space data to obtain a project red line range; generating a macroscopic current situation scene; obtaining at least two candidate schemes, and performing spatial registration and fusion on the BIM models corresponding to the candidate schemes and the macroscopic current situation scene to generate a corresponding fusion decision scene; based on the fusion decision-making scene, carrying out collaborative decision-making on the candidate schemes, and determining a bid-winning scheme; and packaging the BIM model corresponding to the bid winning scheme and associated data, and transmitting the packaged BIM model and associated data to a downstream construction management system through an interface. The scheme collaborative decision-making efficiency is effectively improved, the information fault problem in the design and construction stages is solved, and the whole-process decision-making closed loop of the engineering project is achieved.

The invention provides a charging pile payment settlement and data evidence storage method and system based on a block chain. The method comprises the following steps: building a block chain network comprising a charging pile node, a user terminal node, an operation management node and a supervision node; according to the invention, by using the characteristics of non-tampering and decentralization of the block chain, secure storage and transmission of user information, charging data and payment and settlement data are ensured, and the data are prevented from being tampered and leaked; through the automatic execution of the smart contract and the public transparency of the block chain, the calculation and payment process of the charging cost is public and checkable, human intervention and fraudulent behaviors are avoided, and the fairness and justice of the transaction are ensured; the data is packaged into a block chain structure, so that tampering resistance and traceability of the data are realized, and data support is provided for charging cost accounting, user right and interest guarantee and industry supervision; the calculation and payment of the charging cost are automatically completed through the smart contract, the payment and settlement efficiency is improved, and the user experience is improved.

The invention provides a BIM (Building Information Modeling) full life cycle splitting and cross-model synchronization method and system. The method comprises the steps that BIM model components are coded based on a full life cycle coding rule, private attributes of all engineering stages and component codes of the engineering stages are bound and stored in component extension attributes, and a BIM master model containing multi-stage attribute information is generated; setting a BIM model splitting rule based on a rule engine; the code of each component in the BIM model is analyzed, the codes are compared with screening conditions in the splitting rules according to levels, and component data corresponding to the successfully matched codes are packaged and stored as sub-models; establishing association mapping between the models; and when the source model is modified, the synchronization engine executes synchronous updating of the target model according to the association mapping between the source model and the target model associated with the source model, so that the cross-stage multi-participant cooperation efficiency is improved, and a solid technical support is provided for digital transformation of the construction industry.

The invention discloses a circuit and chip for supporting core particle parallel physical links through a PIPE interface, and the circuit comprises a data processing module which is located between the PIPE interface and a parallel PHY group, and comprises a data packaging module and a data analysis module, the data packaging module is used for generating a receiving direction data signal on the PIPE interface from data from the PIPE interface, compressing and packaging the receiving direction data signal and transmitting the receiving direction data signal to the parallel PHY group; and the data analysis module is used for analyzing the data from the parallel PHY group, recovering and restoring the compressed data, and then transmitting the data to an upper layer through the PIPE interface so as to send the data to a core particle interconnection controller on the PIPE interface. The invention aims to solve the problem of how to drive and use a plurality of parallel physical interfaces to carry out data transmission through a PIPE interface of a core particle interconnection protocol interface compatible with a PIPE interface on a physical layer, and data transmission is carried out through the PIPE interface and the plurality of parallel physical interfaces.

The invention belongs to the technical field of artificial intelligence, and discloses an FPGA fault diagnosis accelerator design method based on a shift module and an AXI cross matrix, and the method comprises the steps: taking GHOSTNETV2 as a backbone network, carrying out the standard 3 * 3 two-dimensional convolution operation of an input content through a first main convolution layer of the network, so as to extract features, and carrying out the calculation of the features; then inputting the features into a subsequent layer for further feature extraction, and independently optimizing the layer; the influence of quantization and data packaging on delay is analyzed, and different quantization methods of different data formats from 32 bits to 8 bits are compared; different quantization strategies are selected for different network layers; an advanced synthesis tool HLS of the Xilinx FPGA is selected; each Xilinx DSP48E1 is decomposed into two 8 * 8 multiplying units, so that computing resources are maximized. According to the method, an optimal mixing precision quantification strategy is obtained through theoretical analysis and experiments, and knowledge distillation is decided to be used for keeping precision, so that the use of hardware resources is remarkably reduced.

The invention discloses an efficient data flow transceiving controller applicable to a multi-core storage and calculation system, which comprises two transmitting controllers and two receiving controllers, and the transmitting controllers and the receiving controllers are arranged on the peripheries of cores and are used for performing data packaging and transmitting and data flow judgment work; wherein the sending controller comprises a configurable asynchronous FIFO (First In First Out), a data packaging unit and an error correction code generating unit; the receiving controller comprises an error correction code decoding unit, a data packet unpacking unit and a microchip detection unit; the flit detection unit is used for detecting information in a head flit to judge whether data meet the calculation requirement of the current core particle or not, and if the data do not belong to the task range of the current core particle, the data are redirected to the sending controller through a bypass transmission mechanism. According to the application, the transmission speed of the data stream among different core particles is improved, and the data stream can be dynamically planned and transmitted according to the preset rule by constructing the efficient data transceiving controller.

The invention discloses a method for improving data transmission bandwidth through an FPGA. The method comprises the steps that a data packaging module of a detector main control board sends data to be transmitted to a multi-channel GTP sending end in parallel; the data acquisition card receives the data of the corresponding channels through the multi-channel GTP receiving end and recovers Data and KCOD of each channel; an FIFO read-write control module of the data acquisition card writes data recovered by multiple channels into asynchronous FIFOs corresponding to the channels through write logic, and data buffering is carried out; the FIFO read-write control module simultaneously reads cache data of a plurality of asynchronous FIFOs through read control logic to realize cross-clock domain synchronization of multi-channel data; performing CRC (cyclic redundancy check) and processing on the read multi-channel data to obtain synchronous effective transmission data; and a single-channel GTP is upgraded to a dual-channel GTP or a multi-channel GTP, so that the data transmission bandwidth is improved, and normal operation of the FPGA chip is ensured.

The invention discloses an intelligent distribution network nuclear phase method and system based on GPS clock synchronization, and relates to the field of power system distribution network operation and maintenance. The intelligent distribution network nuclear phase method and system based on GPS clock synchronization comprise a nuclear phase source reference unit, a non-contact nuclear phase terminal and a cloud server system. According to the intelligent distribution network nuclear phase method and system based on GPS clock synchronization, three-phase voltage waveforms are continuously collected through a nuclear phase source reference unit, and reference waves are formed through GPS clock synchronization, time label adding and cloud real-time synchronization; a non-contact phase checking terminal is used for collecting three-phase voltage waveforms of a measuring end, GPS clock synchronization, time label adding and data packaging are carried out and uploaded to a cloud end, then a cloud server system is used for intercepting the voltage waveforms of the same time period through a GPS clock to carry out phase checking and phase difference analysis, and then feedback signals are generated according to the analysis result and a phase difference threshold value. The single-person non-contact operation is realized, the safety is high, the precision is high, and the nuclear phase structure can be stored.

The invention relates to the technical field of data transmission monitoring, in particular to a data transmission monitoring method and system for a tin-containing sewage treatment unit. The method comprises the following steps: deploying a plurality of sensors in a sewage treatment unit, and respectively collecting tin ion concentration, pH value, ORP and conductivity information as sensor data by using the plurality of sensors; the sensor data are transmitted to a data collector through an RS485 bus, the data collector collects and caches all the sensor data at the frequency of 2-10 seconds per time, and the data are packaged and transmitted to an edge computing device through a Modbus RTU protocol; and carrying out working condition self-adaptive segmentation on the sensor data by utilizing edge computing equipment, and carrying out anomaly judgment to obtain the sensor data after anomaly judgment. The switching conditions of the pickling section, the neutralizing section and the settling section are dynamically judged through working condition self-adaptive segmentation, and it is ensured that the process operation is more accurate and efficient.

The invention discloses an indoor unmanned aerial vehicle positioning and navigation method based on tight coupling of a laser radar and an IMU, and the method comprises the steps: collecting data based on the laser radar and the IMU, and carrying out the down-sampling processing of the data; packaging the radar data to be processed currently and the IMU data, synchronizing the radar data and the IMU data, and confirming that the radar data and the IMU data are aligned in time sequence to obtain radar and IMU data streams; taking the obtained radar and IMU data streams as input to carry out forward propagation and integration to obtain rough pose estimation, then carrying out motion compensation based on back propagation, and removing radar point cloud distortion to obtain a current state; evaluating whether the current state estimation is accurate or not based on residual calculation; and if not, estimating pose transformation by using iterative error Kalman filtering until the increment is smaller than a threshold value, then mapping according to the pose and updating the feature map, and carrying out unmanned aerial vehicle positioning navigation. According to the method, radar and IMU data are fused, and high-precision low-drift tight coupling mapping is realized through time sequence alignment, filtering, motion compensation and iterative optimization.

The invention discloses a self-adaptive three-dimensional flow field reconstruction method, device and system for open channel flow and a medium, and relates to the technical field of open channel flow measurement. The method comprises the following steps: acquiring multi-modal data, and preprocessing the multi-modal data; and performing preliminary three-dimensional flow field prediction on the preprocessed data through a lightweight prediction model, and performing consistency verification and anomaly detection by an anomaly detection module. And when the abnormal event is detected, packaging the multi-modal measurement data in the occurrence time window of the abnormal event and uploading the packaged multi-modal measurement data to a cloud server. And only the metering result and the equipment state data are uploaded under the condition of no abnormal working condition. And the cloud server receives the uploaded data packet, performs three-dimensional flow field reconstruction on the data through a physical prior guide large model, and obtains virtual sensor data of the failed sensor and a three-dimensional uncertainty field. And according to the reconstructed complete three-dimensional flow field, in combination with the real-time water level and the latest riverbed topography, performing numerical integration on the flow cross section to obtain a cross section flow value.

The invention provides an electric power monitoring data credible evidence storage and tracing method, which comprises the following steps of: acquiring state data in real time through an electric power tool integrated with a star flash communication module, and transmitting the monitoring data to an edge gateway in real time by adopting a star flash technology; the edge gateway receives the star flash data from each electric power tool, performs timestamp marking of Beidou clock synchronization, packages the data into blocks through an improved PBFT consensus algorithm, and stores the blocks in a local block chain; when the public network communication is recovered, synchronizing the local block chain data to a cloud block chain network through a wireless network; and carrying out tracing query on the block chain data based on the intelligent contract, and generating a credible tracing report containing a complete operation time sequence through timestamp comparison. The invention further provides a corresponding system. By implementing the method, the real-time performance, the integrity and the traceability of uploading the power monitoring data can be improved, and the traceability efficiency can be improved.

A method for managing data packing in a storage includes: receiving data from a computing device at a first point-in-time; analyzing the data to: determine characteristics of the data, and generate an extent for the data, in which the extent includes sequential tracks; analyzing sequential tracks to infer how a distribution of compression sizes change for the sequential tracks to obtain track-level in the compression sizes; forecasting, based on the characteristics of the data and the track-level changes in the compression sizes, a stability score of the distribution at a second point-in-time, in which the second point-in-time is after the first point-in-time; making a determination, based on the stability score, that the distribution would be the same in the second point-in-time; and placing, based on the determination, the tracks to a first zone in the storage, in which the storage further comprises a second zone and a third zone.

The invention discloses a GCB holographic data acquisition and analysis device and method. The device comprises a power supply module, a data acquisition module, a time sequence synchronization module and a main control module, the power supply module supplies power to the data acquisition module, the time sequence synchronization module and the main control module; the time sequence synchronization module is used for ensuring that the data transmitted from the data module to the main control module is kept in time sequence synchronization; the data acquisition module comprises a stress strain sensor, a current sensor, a stroke sensor, a vibration sensor, a visible light sensor and an SF6 gas sensor; the data acquisition module is used for packing sensor data and sending to the main control module; and the main control module is responsible for processing and storing the transmitted sensor data. According to the GCB state monitoring system, a plurality of physical quantities used for GCB state detection can be collected through standard hardware and a communication interface, the expansibility of the system is improved, the collected data are effectively processed and utilized, and state monitoring of GCB equipment is facilitated.

The invention discloses a redundant data backup method and system, the method is applied to an energy storage system comprising an energy management system (EMS), a storage module is arranged in the EMS, and the method comprises the following steps: the EMS collects operation data of an energy storage bidirectional converter (PCS) and a battery management system (BMS) in the energy storage system; monitoring the stability of the MQTT connection established with the cloud; under the condition that the stability meets a preset condition, the operation data is packaged and sent to a cloud end, and the operation data is stored in the storage module; and under the condition that the stability does not meet a preset condition, storing the operation data in a storage module, and after the connection stability of the MQTT is recovered, uploading the operation data to be continuously uploaded in the storage module to a cloud through a breakpoint continuous transmission mechanism. According to the redundant data backup scheme provided by the invention, dual-channel redundant data backup of the energy storage system can be realized.

The invention provides a tire equipment edge end control system and method. The tire equipment edge end control system is composed of an MES, an MES and edge end middle library and a tire equipment edge end, and comprises a PLC formula parameter module, a cleaning machine head signal module and a PLC production parameter module. The MES system issues a formula to the MES and edge end middle library, the MES and edge end middle library transmits the formula to the production equipment PLC at the edge end of the tire equipment, the edge end intelligent terminal transmits production parameters and action signals to the MES system and edge end middle library, and the MES system and edge end middle library carry out data integration and alignment and then package and send the data to the MES; the functions of yield statistics, product parameter trend, formula switching, glue removing report, formula management, parameter early warning, section graph and yield data statistics and data packaging are achieved, the monitoring timeliness is guaranteed, and the tire production quality is also guaranteed.

The invention relates to a system for reducing delay of summing of multiple GPU card protocols in distributed text reasoning and a method thereof. The system comprises: a data packaging component, which packages the data of a GPU card, which needs to execute a multi-GPU card protocol locally, according to a predetermined size, a first part of each data packet being data to be transmitted segmented in sequence from fragmented data, and a second part being flag bit data; the data transmission component is used for transmitting the packaged data packet from the local GPU card to buffers of other GPU cards at the far end; and the data receiving confirmation component is used for completing polling aiming at corresponding identification bit data when receiving of a data packet with a preset size is completed in the polling waiting execution process, and enabling a stage receiving completion result to be seen by all GPU cards based on the visibility of data transmission and to be confirmed, so that multi-card protocol summation is performed.

The invention provides an automatic evidence obtaining method and device for Internet content, equipment and a storage medium, and the method comprises the steps: obtaining to-be-processed tasks in batches, analyzing the obtained to-be-processed tasks, and obtaining the key task information of each to-be-processed task; based on the task priority and the task type of each to-be-processed task and the resource information of each server node in the server cluster, allocating each to-be-processed task to the corresponding server node; each server node configures a task parameter of a browser instance corresponding to each to-be-processed task based on the task type and evidence obtaining mode of each to-be-processed task to obtain a browser instance adapted to each to-be-processed task; and based on the browser instance adapted to each to-be-processed task, performing loading, screenshot, watermark adding, data packaging and other processing on the target webpage corresponding to each to-be-processed task to obtain an evidence obtaining result of each to-be-processed task. According to the method disclosed by the invention, efficient batch evidence obtaining of the Internet content can be realized.