284 results about "Data packing" patented technology

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 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 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 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 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 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 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.

The invention provides a high-speed serial communication system physical coding layer circuit oriented to D2D interconnection between integrated chip core particles. Based on the characteristics of short D2D transmission distance and reliable transmission environment, a simple link management mechanism is adopted, efficient flow control is realized through a specific training sequence, and a data reliability guarantee mechanism is arranged in other control layers. A modular design idea is adopted, and the system comprises a coding and decoding module, a multi-channel data processing module and an APB interface module. A user configures a register through the APB interface module to realize switching of two coding schemes and monitor the working state of the circuit. The coding module is responsible for data coding and training sequence sending, the decoding module completes data decoding and training sequence identification, and the multi-channel data processing module is responsible for channel training control and multi-channel data packing and unpacking. In the training process, a two-stage training strategy is adopted, based on a training result, a circuit selects a working mode according to the number of available channels, and channel self-adaptive fault tolerance is achieved.

In some implementations, the techniques described herein relate to a system including: a vehicle interface adapter, the vehicle interface adapter communicatively connected to a diagnostic port of a vehicle via a first cable; and a vehicle gateway, the vehicle gateway communicatively coupled to the vehicle interface adapter via a second cable, wherein the vehicle interface adapter is configured to receive vehicle data via the first cable, packetize the vehicle data into vehicle packets, and transmit the vehicle packets to the vehicle gateway, and the vehicle gateway is configured to receive the vehicle packets and manage a power state of the system.

The invention relates to the technical field of computers, and discloses a multi-FPGA collaborative deep neural network parallel acceleration method. According to the method, unified compiling and automatic calculation graph segmentation mapping based on a dynamic programming algorithm are carried out on a deep neural network model through a host control node, a heterogeneous strategy fusing data, the model and assembly line parallel is generated, and the problems of single FPGA computing power resource limitation and memory wall are effectively solved; direct communication between the FPGAs is achieved through a high-speed point-to-point internet, an asynchronous assembly line execution mechanism and a hardware-level data packaging technology are combined, communication delay is reduced, assembly line bubbles are eliminated, and a multi-FPGA cluster reaches a near-linear speed-up ratio; computing distribution is optimized in real time through a global load balancing unit, and the equipment utilization rate is increased; and meanwhile, a transparent deployment interface is provided through the hardware abstraction layer, so that the super-large-scale neural network can efficiently run on a multi-FPGA platform with low delay, and the overall calculation efficiency is improved.

The invention provides a tower internet-of-things monitoring device and a monitoring method thereof, and the device comprises a tilt angle sensor, a vibration sensor, a control module, a storage module and a wireless communication module, and the tilt angle sensor and the vibration sensor are used for collecting tilt angle data and vibration data of a tower. The control module is electrically connected with the tilt angle sensor and the vibration sensor, obtains data output by the tilt angle sensor and the vibration sensor and is used for monitoring the sensor data to judge that the state of the tower is abnormal, and when an abnormal event is detected, the sensor data related to the event is packaged and stored in the storage module; and the packaged abnormal data is uploaded to a remote server through the wireless communication module. And the control module has a data package integrity verification function, so that the data package is accurately and reliably uploaded.

The invention relates to the field of system engineering modeling, and particularly discloses a SysML-based modeling method, system and product, and in the modeling method, a functional architecture design step comprises the following steps: creating a functional architecture document, sequentially creating each functional module, and defining a subordination relationship of the functional modules; defining the input and output function data of the function module, and defining the function data and the direction at the same time; reading and identifying the functional architecture document, and creating a module definition diagram and an internal block diagram; the physical architecture design step specifically comprises the following steps: defining a software module for realizing each functional module; defining a physical data type and a data packaging mode for realizing each piece of functional data; and generating a state machine diagram for describing an interaction relationship and state driving logic of corresponding physical data when the software module runs, and defining a data transmission channel by determining a port and a protocol. According to the method, the problem of low efficiency of modeling design and communication cooperation caused by semantic limitation and structural mixing of a traditional SysML modeling method can be solved.

The invention discloses an SOQPSK demodulation performance monitoring method and system based on upper computer visual feedback. An SOQPSK signal is demodulated by adopting a maximum likelihood sequence detection method based on a Viterbi algorithm; removing the influence of a phase pulse function through matched filtering processing, extracting I / Q data of a fixed sampling point in each symbol period, carrying out time domain superposition, and generating eye pattern data in real time; based on the mapping relation between the grid state variable of the SOQPSK demodulator and the CPM phase state, the maximum survival state in the Viterbi algorithm is used as a phase value, and constellation diagram data is generated in real time in combination with the survival path measurement increment; and packaging the eye diagram data and the constellation diagram data to an upper computer for display, performing performance parameter evaluation and feeding back to a demodulator. The FPGA generates eye diagram and constellation diagram data in real time and sends the eye diagram and constellation diagram data to the upper computer for display and performance evaluation, and visual performance monitoring is provided. And parameters of the demodulator are adjusted in real time, so that a closed loop is integrally formed.

The invention provides an electronic device and a processing method of the electronic device. An electronic device includes: one or more scanning modules, each of the one or more scanning modules being respectively connected to a respective one of the one or more peripheral devices and a first bus in the electronic device, and configured to receive respective configuration information through the first bus, acquiring data of the corresponding peripheral equipment based on the corresponding configuration information; and a data packing module, which is connected to the one or more scanning modules and a second bus in the electronic device, and is configured to assemble the collected data of the one or more peripheral devices into a data packet in a first format, and directly transmitting the data packet to the memory of the electronic device through the second bus.

A system and method are disclosed for generating personalized motivational, wellness, educational, and entertainment multimedia content using multimodal artificial intelligence. The system constructs an Emotion State Vector (ESV) from user inputs, diaries, biometric data, and context. A Modality Script Generator (MSG) defines time-coded orchestration across music, narration, captions, and visuals. Scripts execute via a Model-Agnostic Adapter Layer (MAAL) across heterogeneous Al engines. A Synchronization Graph (SyncGraph) maintains acceptable inter-modal drift, while a Dynamic Media Formatter (DMF) applies bounded repair policies and packages synchronized outputs with timed metadata. A Policy / Constraint Graph enforces rights and provenance, logged in a Transform Manifest.

The present application provides a kind of data distribution device, data distribution system and data distribution program.Data distribution device (2) has: update data acquisition unit (9a), obtains the multiple update data corresponding to multiple write object electronic control device;Reorganization information acquisition unit (9b), obtains the reorganization information for by main device parallel execution to multiple write object electronic control device transfer update data transfer processing;Data packet generation unit (9c), multiple update data are segmented based on reorganization information to generate segmented data, and the segmented data of multiple update data generated are packed to generate multiple data packets;And distribution control unit (9e), multiple data packets are distributed to main device.

The invention relates to the technical field of electric power detection equipment, and discloses a communication method and system for dynamic networking of an SF6 remote transmission density meter, and the method comprises the steps: building wireless connection with a started field sensor, and obtaining the signal strength and position information; calculating a signal intermediate value as a screening value, and dynamically adjusting a screening condition in combination with a position distribution uniform value until the distribution meets the requirement; position intervals are divided, networking sensors are selected, and field sensors are controlled to be networked with the networking sensors; and the networking sensor responds to the acquisition instruction, generates data and awakens the field sensor to acquire the data, and the data are packaged, uploaded and jointly dormant. The scheme adapts to different scenes through dynamic networking, improves data transmission reliability, reduces energy consumption, and is suitable for remote transmission density monitoring of a power system.

Methods and systems providing a holistic approach to error data collection in a complex system, such as a distributed storage system, are disclosed. Telemetry data across a number of system components and their operational attributes is collected, structured and used to generate a correlation matrix. The correlation matrix is used to generate a graph. The graph includes a plurality of nodes corresponding to the plurality of attributes and a plurality of edges corresponding to a correlation between at least two nodes. The graph indicates correlated attributes such that, upon detection of an error, attribute data relating to correlated nodes is packaged and transmitted for error analysis.