35results about How to "Guaranteed time consistency" patented technology

The invention relates to the technical field of sleep aiding, in particular to a method and a system for extracting feature information of a sleep state monitoring model. The method comprises the following steps: carrying out multi-mode physiological signal acquisition on a detected object to obtain original sleep monitoring data; performing noise removal and signal enhancement processing on the original sleep monitoring data, and performing signal segmentation to obtain multi-channel sleep signal fragment data; performing feature extraction based on electroencephalogram, eye movement diagram, electromyogram, electrocardiogram and accelerometer signals on the multi-channel sleep signal fragment data to obtain multi-dimensional feature data; and performing ultrasonic feature and acoustic feature extraction on the multichannel sleep signal fragment data to generate acoustic feature data. According to the method, dynamic modeling and trend prediction are carried out on the conversion process of the sleep state, potential sleep disorder events can be accurately recognized, influence evaluation is carried out on the potential sleep disorder events through deep learning, and support is provided for personalized sleep diagnosis.

The invention relates to the technical field of information synchronization, in particular to a cross-platform electronic communication synchronization system, which comprises a network construction and path optimization module for collecting basic network parameters of communication equipment of a plurality of platform networks, obtaining cross-platform network data according to the basic network parameters, selecting an optimal transmission path according to the cross-platform network data, and transmitting the optimal transmission path to a server; and generating real-time optimized path information. In the invention, the basic network parameters of the communication equipment of the plurality of platform networks are collected, the cross-platform network data are acquired, the edge weight is dynamically updated according to the delay and the bandwidth, and the optimal transmission path is selected based on the network state, so that the effect of efficiently utilizing network resources is achieved, and the real-time performance and the accuracy of synchronous data transmission are remarkably improved. The to-be-synchronized data is classified and subjected to priority setting, and the data processing sequence is adjusted in combination with the real-time network data, so that accurate scheduling of the synchronization task is realized, the delay and conflict problems in data transmission are reduced, and the efficiency and reliability of data synchronization are improved.

The invention discloses a volume video figure rendering method, system and equipment based on double-layer Gaussian splashing, a chip and a medium. The method comprises the following steps: S1, acquiring human body pictures with actions from a plurality of visual angles; s2, capturing global motion by using joint Gauss, capturing appearance details by using skin Gauss, and establishing mapping between the skin Gauss and the joint Gauss; s3, performing double-Gaussian optimization by using a coarse-to-fine optimization strategy, and ensuring time consistency; and S4, respectively providing a residual quantization compression method, a picture coding and decoding compression method and a persistent codebook compression method for different Gaussian attributes. According to the invention, through multi-view RGB video input, a double-layer Gaussian splashing and coarse-to-fine optimization strategy is used, so that the rendering quality with extremely high competitiveness is achieved; different Gaussian point cloud attributes are compressed through residual quantization compression, picture coding and decoding compression and a persistent codebook, and the method is superior to the prior art in the aspects of rendering quality, efficiency and storage efficiency.

The invention relates to a cross-network time synchronization method oriented to AUTBUS and TSN fusion, and belongs to the field of network time synchronization. The invention aims to solve the problems that the traditional Ethernet cannot meet the time-sensitive application requirement and the scale of the TSN is limited and the like. According to the method, a time compensation value prediction algorithm is placed in an AUTBUS terminal, time delay values of all parts in the heterogeneous network are collected and predicted, and finally a prediction result is compensated to a local clock of the AUTBUS terminal, so that end-to-end time synchronization of the AUTBUS and TSN fusion network is realized. The method comprises the four steps of TSN intra-network time synchronization, gateway intra-network time synchronization, AUTBUS intra-network time synchronization and AUTBUS terminal time compensation, time delay data are predicted through a linear regression prediction algorithm, and synchronization precision and efficiency are improved. The method is suitable for the fields of intelligent manufacturing, industrial automation and the like, and an effective solution is provided for time synchronization of the heterogeneous network.

The invention relates to the field of communication, and discloses a vehicle-mounted network time synchronization method and system, and the method comprises the following steps: a master clock periodically broadcasts a synchronization message to all slave clocks in a network, and the synchronization message comprises a current timestamp; the slave clock receives the synchronization message and records the receiving time T1; the slave clock sends a delay request message to the master clock, and the sending time T2 is recorded; after receiving the delay request, the master clock sends a delay response message and records delay request message receiving time T3; the delay response message comprises a timestamp T4 when the master clock receives the delay request message; and the slave clock obtains network transmission delay and clock skew Offset between the slave clock and the master clock according to the time T1, T2, T3 and T4, and the slave clock adjusts the time according to the clock skew. According to the invention, the time height of each node in the system can be ensured to be consistent. According to the invention, by using clock synchronization mechanisms such as IEEE1588 and the like, the timestamp is ensured to be accurate to the nanosecond level.

The invention is suitable for the technical field of automatic measurement, and particularly relates to a time-to-digital conversion method and a time converter, and the method comprises the steps: inputting a to-be-measured signal into a carry chain, and generating a delay signal of the first to-be-measured signal; determining the edge of the to-be-detected signal according to the clock signal and the delay signal of the to-be-detected signal, wherein the edge of the to-be-detected signal comprises a rising edge and a falling edge; determining a coarse time count value of the to-be-measured signal according to the edge of the to-be-measured signal; determining a fine time measurement value of the to-be-measured signal according to the delay signal of the to-be-measured signal; and determining the timestamp of the edge of the to-be-measured signal according to the fine time measurement value of the to-be-measured signal and the coarse time count value of the to-be-measured signal. According to the invention, the rising edge and the falling edge of the first to-be-tested signal are determined to obtain the timestamps of the rising edge and the falling edge on the same time axis, so that the duration time of the to-be-tested signal can be quickly and accurately obtained.

The invention discloses a ship / vehicle-mounted photoelectric universal high-precision servo control system and method, and relates to the technical field of photoelectric system control, and the system comprises a comprehensive control module, a shafting control module, a sensing module, an angle measurement unit, an image processing unit, a servo driving unit, a fiber-optic gyroscope, a power supply module and a man-machine interaction module. The sensing module is used for carrying out information collection on a target and obtaining a target video signal. According to the method, the gyro integral is used as a double-loop control mode of a position closed loop and a gyro speed closed loop, and a simplified linear state observer is added, so that the anti-disturbance performance and the response speed of the photoelectric equipment are improved, the stability precision and the tracking precision of the photoelectric equipment are improved, and through a calibration method, the stability and the tracking precision of the photoelectric equipment are improved. The time delay between the deviation value of the image plate and the speed value of the gyroscope is accurately measured, the time consistency of information required by target tracking is ensured, and the stability and the tracking precision of the system are greatly improved.

The invention relates to the technical field of data asset management, in particular to a data asset management system and method. The method comprises the following steps: acquiring a data asset information set from different data sources in real time and performing tag structure sub-column division to obtain data asset information tag description structured sub-columns, and meanwhile, performing time sequence creation synchronization processing and integrating and storing the data asset information tag description structured sub-columns into a data asset management database; performing use frequency and sensitivity evaluation analysis on each piece of data asset sub-information in the data asset management database, and performing data asset access utility evaluation analysis to obtain data access utility of each piece of data asset sub-information; and performing dynamic access right control and full life cycle management design on each piece of data asset sub-information in the data asset management database, and performing automatic management and report feedback recording to generate a data asset information management report. The transparency, safety and efficiency of data asset management can be improved.

The present invention discloses an intelligent motor fault diagnosis method based on digital twins, belonging to the field of motor fault diagnosis. In the model training stage, the method selects feature quantities through the random forest method to train an extreme learning machine model with an autoregressive cycle function as a digital twin motor. In the open circuit fault diagnosis stage, the method collects the physical entity motor feature quantity and inputs it into the digital twin virtual motor to obtain the digital twin current, and makes a difference between the actual winding current data and the digital twin winding current to obtain the current residual, and uses the difference value of the current residual as a threshold to perform open circuit fault diagnosis, and adopts the sliding average window method to locate the fault; in the turn-to-turn short circuit fault diagnosis stage, the current symmetrical mean absolute error is used as a judgment standard to diagnose the short circuit fault. The present invention does not require precise design parameters and motor fault data of the motor, but only requires data when the motor is in normal operation to quickly and real-time diagnose the motor open circuit fault and turn-to-turn short circuit fault, and has strong robustness.

The invention discloses a hospital-oriented software and hardware collaborative medical data hierarchical processing method and device. According to the method, in a hospital intranet, statistics is carried out on the flow of medical data flow based on a source IP and a target IP two-tuple through a hardware side, a large flow and a small flow of the medical data flow are distinguished according to a dynamic threshold value, and an identifier is added to the large flow. The hardware flow table module carries out short-period quintuple statistics on the identified large-flow medical data message and reports a result with a timestamp; and the software flow table module performs long-period statistics on the small-flow medical data messages, synchronously fuses results of the two parties through timestamps, generates a full-amount medical network flow table, and further optimizes a dynamic threshold value and a processing strategy. According to the invention, through layered flow establishment and double-cycle cooperation, high performance of hardware processing and flexible large capacity of software processing are both considered, the utilization rate of hospital network resources and the consistency of flow data are effectively improved, and accurate support can be provided for hospital intranet monitoring, service awareness, safety protection and strategy automation.

The present invention discloses a motor sound generation method, a vehicle, a storage medium and a computer program product, and belongs to the field of vehicle technology. The method comprises: sampling audio data to obtain an audio sampling signal; determining a motor control signal according to the audio sampling signal; and controlling the motor according to the control signal, so that the motor itself can be controlled to generate a sound corresponding to the audio data, without setting up additional sound generation hardware equipment, which is conducive to reducing the production cost of the vehicle.

The invention relates to the technical field of equipment monitoring and control, and discloses a power take-off wheel real-time energy consumption monitoring method and system and a storage medium. The method comprises the following steps: synchronously acquiring a torque value and a rotating speed value to construct a sampling data record; torque fluctuation gradient setting sampling frequency is calculated, and whether the sampling frequency is switched or not is judged based on the fluctuation gradient change rate and the hysteresis band; calculating instantaneous power and accumulated energy consumption, establishing a power baseline, and generating an energy consumption abnormal event when the deviation degree exceeds a preset number of times; and according to the deviation degree and the duration, determining an alarm level and executing corresponding alarm. According to the invention, the real-time performance of energy consumption monitoring and the utilization efficiency of edge computing resources are improved.

The invention relates to the technical field of power distribution and utilization and communication, in particular to a power distribution and utilization network timing method, device, system and chip based on multi-mode communication, and the timing method comprises the following steps: a timing node and a timed node are respectively located on the same layer, adjacent layer or cross-layer, and first timing information and second timing information are obtained, and then performing time correction on the node to be subjected to time correction based on the first time correction information and the second time correction information. According to the invention, the concept of a reference node is introduced, the reference beacon sent by the reference node and simultaneously received by the time calibration node and the calibrated node is taken as the reference moment, and the time values which are recorded at the reference moment and are counted by the local clock are respectively taken as the first time calibration information and the second time calibration information; or the specified zero-crossing time which is relatively stable in position, predictable, high in repeatability and easy to detect is used as the reference time, so that the time correction precision of the power distribution and utilization network node during clock synchronization is effectively improved, and the reliability and the stability of the whole power distribution and utilization network are improved.

The application discloses a plot quality evaluation and abnormality identification method and device based on multi-source forestry data fusion, relates to the technical field of forestry plot quality evaluation, and comprises the following steps: collecting multi-source forestry data and performing pretreatment, generating a standardized multi-source data set and performing dimension reduction processing, orthogonally decomposing the dimension-reduced data set to extract each principal component direction; projecting the standardized multi-source data set to each principal component direction to obtain each principal component score, performing denoising correction on the principal component score, and performing polarity correction on the corrected score; determining the weight of each principal component based on the polar-corrected principal component score and weighted calculating the comprehensive quality score of each plot; constructing the conditional probability distribution of the signal strength of each principal component and calculating the significance measure; determining whether each plot is abnormal according to the significance measure; and outputting diagnosis prompt information in combination with the comprehensive quality score and the abnormality determination result of each plot. Thus, the objectivity of plot quality comprehensive evaluation and the statistical credibility of abnormality determination are realized.

The invention relates to a learning state monitoring method, system and device based on artificial intelligence and a medium. The method comprises the following steps: collecting signals such as physiological and behavior images of a target object through a multi-source heterogeneous sensor, and performing normalization processing on aligned features to generate a standardized feature vector; calculating a comprehensive cognitive state score of the feature vector by adopting a dynamic weighted fusion algorithm, and judging and outputting a soft label according to a preset threshold value; applying constraint random disturbance based on statistical distribution characteristics of the feature vectors to generate synthetic data, and associating the synthetic data with the soft labels to construct a soft label data set; by taking the feature vector of the data set as input and the soft label as a supervision signal, iteratively calculating loss through a preset loss formula, updating model network parameters to convergence, and obtaining an optimized neural network model; during real-time monitoring, processed sensor signals are input into the model, and quantitative learning state scores are output through end-to-end reasoning. The method can break through the limitation that traditional monitoring is high in subjectivity and insufficient in real-time performance.

The application relates to the technical field of image processing, and particularly discloses a bullet rapid measurement method and system based on high-speed video key frame retrieval. The original video frames are uniformly formatted, and frame events carrying influence weights are generated, so that the time sequence consistency of playback, screen projection and target reporting is ensured. Whether to generate a key section summary is dynamically judged through time sequence accumulation of the weights, and the content of the key section summary is matched according to operation requirements, so that the network transmission burden and recovery delay are reduced, and the terminal full playback and decoding calculation burden are reduced. Four-level differentiated key section summaries and incremental frame playback are adopted, so that the recovery complexity of the key section is reduced, the terminal can quickly and directionally retrieve effective event segments through the key section summary, the retrieval and measurement time consumption is shortened, and the balance between real-time performance, transmission efficiency and resource cost is ensured. Through event interval division, asynchronous sampling and adaptive transmission regulation and control, the number of image collections in invalid intervals and the uplink transmission load are reduced.

The invention discloses a hydrogen damage test device and a detection method thereof.The hydrogen damage test device comprises an electrolyte container, an electrochemical workstation, an acoustic emission probe, an acoustic emission detector and a computer, and a metal sample, an auxiliary electrode and electrolyte are arranged in the electrolyte container; the metal sample and the auxiliary electrode are soaked in the electrolyte and are both connected with the electrochemical workstation, the non-hydrogen-filling surface of the metal sample is provided with the acoustic emission probe, the other surfaces of the metal sample except the hydrogen filling surface are sealed through resin, the acoustic emission probe is connected with the acoustic emission detector, and the electrochemical workstation and the acoustic emission detector are both connected with the computer. According to the method, acoustic emission signals are collected in real time in the electrochemical hydrogen charging process, synchronous analysis is conducted in combination with parameters of the hydrogen charging process, elastic wave signals generated by a local damage event can be captured at the moment of hydrogen-induced microcrack initiation, and therefore real-time recognition of the hydrogen crack initiation moment is achieved; and the accuracy and reliability of hydrogen damage early recognition are improved.

The invention discloses an energy-saving optimization control method and system of an air compression station building, a medium and a product, and belongs to the field of air compression station building energy-saving control, and the method comprises the steps: collecting multi-source operation data of the air compression station building in a current sampling period; based on the multi-source operation data, the real gas consumption of the user in the current sampling period is calculated through the mass conservation relation among the gas supply amount, the gas storage variable amount and the gas consumption; inputting the real gas consumption of the user into a preset gas consumption prediction model, outputting gas consumption prediction data in future preset time, and solving to obtain gas supply distribution of each air compressor based on the gas consumption prediction data and a preset power-gas supply relation model of each air compressor; and on the basis of all the air supply distributions, an operation instruction is generated, all the air compressors are controlled to operate, and energy-saving optimization control is completed. By implementing the method, the problem that in the prior art, due to the fact that the outlet flow of the air compressor is directly adopted as the user gas consumption, gas consumption requirement recognition is not accurate can be solved.

The embodiment of the application provides a real-time acquisition method and system of welding heat input, the method comprises the following steps: perceiving displacement movement of a welding torch or a welding wire through a diffuse reflection photoelectric switch array installed on the surface of a pipeline, and generating a corresponding pulse trigger signal; perceiving current data and voltage data of a welding circuit through a Hall sensor system, and generating a corresponding analog electric signal; synchronously acquiring the pulse trigger signal and the analog electric signal through a multi-channel data acquisition device, and converting the analog electric signal into a digital signal with a time stamp; calculating real-time welding speed data according to the time sequence of the pulse trigger signal and the preset spatial geometric relationship of a plurality of diffuse reflection photoelectric switches; performing multi-stage filtering processing on the current data and the voltage data; determining a unified time stamp, and performing time sequence matching on the filtered current data, the voltage data and the welding speed data based on the unified time stamp; and calculating a welding heat input value.

The invention discloses a power management method and device, and belongs to the technical field of power management, and the method comprises the steps: S1, configuring a traversal instruction triggering condition, a time calibration task and a timing task for a time node of a cycle time wheel; s2, judging whether a traversal instruction triggering condition of a cycle time wheel is reached or not; when a traversal instruction triggering condition is reached, executing S3, otherwise, executing S2; and S3, receiving and executing the time calibration task through the power management equipment, synchronizing the local time with the network time, then matching the execution time of the timing task, and triggering the timer to execute the timing task. According to the scheme, the time node of the cycle time wheel configures the traversal instruction triggering condition, the time calibration task and the timing task, the power management device receives and executes the time calibration task when the traversal instruction triggering condition is met, then the timing task is executed, timing management can be carried out on the power supply of the electrical equipment, and the power management efficiency is improved. And the reliability of power management is obviously improved.

The invention provides a wireless data synchronous acquisition method and system, and relates to the technical field of data transmission, and the method comprises the following steps: a gateway sends a synchronous beacon to a wireless sensor node; when the wireless sensor nodes receive the synchronous beacons, the RTC timestamps in the synchronous beacons are extracted, and an internal RTC clock system is updated; the wireless sensor node optimizes sampling time and a sending time slot; the wireless sensor nodes synchronously acquire sensor data by adopting the optimized sampling time and the transmission time interval; the wireless sensor node sends the collected sensor data to the gateway according to time division multiple access; when the gateway receives the sensor data, a confirmation message is sent to the corresponding wireless sensor node; and when the wireless sensor node does not receive the confirmation message within the preset duration, the same sensor data is retransmitted in the next time slot until the gateway confirms that the receiving is successful. The synchronous acquisition precision of the sensor data can be improved, and the integrity of sensor data transmission is ensured.

In the pain monitoring system, an information collection assembly comprises a pain physiological signal collection device and a subjective pain assessment device; the pain physiological signal collecting device is in signal communication with the monitoring server assembly; the pain physiological signal collecting device is used for collecting pain physiological signals of the testee; the subjective pain assessment device collects subjective pain assessment information of the testee; the information collection assembly sends the pain physiological signal and the subjective pain assessment information to the monitoring server assembly to form pain data; and the monitoring server component performs evaluation analysis according to the pain data and outputs a pain evaluation report. The pain monitoring information collection assembly and a pain physiological signal collection device collect pain physiological signals of a testee, and the pain physiological signals comprise a blood oxygen signal, a heart rate signal and an electroencephalogram signal; the subjective pain assessment device collects subjective pain assessment information of a subject. The pain assessment gives consideration to objectivity and subjective feelings, and the assessment is closer to real experience.

The invention provides an air gun control system. The air gun control system comprises a host, manifold pressure, a network switch, a deck interface unit, a deck power supply unit, a time controller and a subarray, the host is in pressure connection with a manifold through a serial port line and is also connected with the network switch through a network cable, the deck interface unit is connected with the network switch and the deck power supply unit through cables, the time controller is a time receiving and control device, is connected with the network switch and is connected to the host, and the subarrays are connected with the deck interface unit through seismic cables. Each subarray is designed to be an independent module and is located below the water surface, and data interaction between underwater equipment and deck equipment is achieved. The air gun control system provided by the invention has a modular design and a simple structure, and can effectively reduce the system cost and improve the operation convenience.

The invention relates to the technical field of traffic control, in particular to a second-hand car market mixed flow traffic control method and system based on multi-target recognition. The method comprises the following steps: in response to an activation signal of a barrier gate triggering device, collecting multi-dimensional identification original data of vehicles passing through a barrier gate of a second-hand vehicle market through a multi-source identification device; performing cross-device data calibration processing on the multi-dimensional recognition original data, performing feature matching, and generating a vehicle identity recognition result and an identity confidence coefficient parameter; according to the vehicle identity recognition result and the identity confidence coefficient parameter, a dynamic passing strategy engine is called to generate a vehicle passing permission evaluation result and a strategy adaptation coefficient; and generating vehicle passing state record data according to the passing authority evaluation result and the strategy adaptation coefficient, performing classification analysis, generating an intervention processing work order, and feeding back the intervention processing work order to the system optimization module for iteratively updating the identification model and the passing strategy. The barrier gate passing efficiency of the second-hand car market can be greatly improved.

The present application relates to the field of automatic driving sensor calibration, and discloses a sensor fusion calibration method for an unmanned sightseeing vehicle, which comprises the following steps: constructing a micro-displacement model by synchronously collecting a wheel speed meter and IMU data, and calculating an inter-frame pose change quantity in a vehicle coordinate system; filtering dynamic objects in a laser radar point cloud, eliminating dynamic interference in combination with motion prediction of the wheel speed meter and the IMU, and extracting static geometric features; performing motion compensation on the static point cloud based on the pose change quantity, and generating a time-aligned enhanced point cloud map; and minimizing errors between the enhanced point cloud map and a calibration reference, and optimizing an external parameter matrix of the wheel speed meter, the IMU and the laser radar. The algorithm is particularly suitable for a multi-sensor online calibration scene of a low-speed unmanned sightseeing vehicle, effectively solves the problems of tire slip and dynamic interference in a low-speed scene, and significantly improves the perception robustness and positioning accuracy of the unmanned sightseeing vehicle in a complex environment.

The embodiment of the invention discloses a probe card assembly process. The probe card assembly process comprises the following steps: S1, bending a plurality of equilong probe bodies into a Z shape according to set parameters; s2, all the probe bodies are arranged in limiting holes in a fixed seat in a penetrating mode; s3, the fixing base is installed on the jig; s4, adjusting all probe bodies; and S5, the pure copper support and the circuit board are connected with the fixing base, and assembling is completed. Through the probe card assembly process, the positions and postures of all the probe bodies can be ensured to be more accurate, the connection efficiency of all the probe bodies and the circuit board can be improved through the arrangement of the fixed seat, the interference of an ultralow temperature environment can be effectively reduced through the fitting support of the pure copper support to the circuit board, and the reliability of the probe card is improved. The deformation of the circuit board in an ultralow temperature environment is reduced, the flatness of the whole probe card is improved, and the test efficiency is improved; and the time consistency of signal receiving of all test points can be ensured, and the test accuracy of the probe card is ensured.

This invention relates to the field of fault diagnosis technology and discloses a device fault diagnosis method based on causal residual learning and invariant risk minimization. This method acquires multi-channel vibration signals of the target mechanical equipment during operation. Based on causal structure discovery and backdoor adjustment criteria, the vibration signals are decontaminated to eliminate interference components caused by changes in operating conditions, constructing a causal residual sequence that only characterizes the physical mechanism of the equipment fault. The sequence is input into a multi-timescale, multi-channel attention network to achieve recalibration of the causal residual sequence; hierarchical temporal features at different time resolutions are extracted and dynamically weighted and fused using a time-scale attention mechanism to obtain fault feature representations. These fault feature representations are input into a pre-trained fault classifier to output the final fault diagnosis result for the target mechanical equipment. This invention improves the model's cross-domain generalization performance and diagnostic accuracy under unknown operating conditions.

The application relates to the field of parallel heterogeneous computing and simulation, and provides a simulation propulsion method and system based on double-engine fusion and a readable storage medium; the method comprises the following steps: constructing a joint working mechanism of a simulation engine and a rendering engine, the simulation engine is used for logical calculation, and the rendering engine is used for expression presentation; discrete event driving and continuous rendering driving are fused to form a hybrid propulsion mechanism; a real timeline and a simulation timeline are maintained in parallel; a simulation step is calculated through a time management mechanism, and the simulation engine is driven to perform discrete event propulsion, and the rendering engine is driven to perform continuous rendering update at the same time; the time management mechanism dynamically adjusts the simulation step based on frame interval calculation, state judgment and a time acceleration factor. Through double-engine cooperation and unified step driving, efficient synchronization of logical calculation and visual expression is realized, time synchronization error is reduced, CPU and GPU utilization is significantly improved, and the application is suitable for tactical level confrontation simulation and digital twin scenarios.

This application relates to a digital twin data transmission system, method, and device for industrial moving equipment, belonging to the field of data transmission technology. The system includes: adding a unified timestamp to data through a clock synchronization protocol at the edge transmission layer to achieve nanosecond-level clock synchronization across all nodes, ensuring time consistency of multi-source data; uniformly converting heterogeneous protocol data into a target format based on preset mapping rules, eliminating protocol barriers and simplifying the topology; reducing the end-to-end transmission latency of core data to milliseconds through a dual-link redundant transmission mechanism, achieving lossless switching between primary and backup links, and avoiding data loss due to single-point failures; hierarchically and compressing target format data, significantly reducing the amount of uploaded data and effectively saving network bandwidth and cloud storage resources; and sending feedback control commands generated in the cloud to the physical equipment PLC after security verification and priority scheduling, realizing closed-loop control of the digital twin drive and ensuring stable operation in complex industrial environments.

This invention discloses an online deviation calibration method and system for electricity meters, relating to the field of electricity detection technology, including the following steps: S1: Constructing a hierarchical topology measurement relationship for the distribution area and collecting metering data from the main meter and user electricity meters in the distribution area, while simultaneously collecting hierarchical node data from the meter box metering module and the branch box metering module, triggering control for the collection of frozen electricity, and completing meter synchronization before collecting frozen electricity, recording the clock deviation during the synchronization process and forming a unified time reference; S2: Performing time series information compression and anomaly detection based on the multi-dimensional dynamic and static data distribution changes of the distribution area and electricity meters. Based on the energy conservation of hierarchical topology measurement and time-frozen electricity, this invention introduces a decodeable calibration watermark beacon excitation and, through related decoding inversion path loss constraints, combines non-convex sparse multi-objective solution with uncertainty threshold constraints to achieve quantitative calibration output of online deviation of electricity meters.