198 results about "Clock drift" patented technology

The invention discloses a power distribution network distributed measurement synchronization method and device based on Beidou satellite time service, and belongs to the technical field of power distribution network measurement, and the method comprises the steps: obtaining a Beidou satellite signal, calibrating a local clock source, and generating a standard time reference; when it is continuously monitored that the Beidou satellite signal quality parameter is lower than a quality threshold value, clock working environment parameters of a local clock source are collected, and a short-term clock offset predicted value is generated in combination with a standard time reference; generating topology correction according to the topology connection relation of the power distribution network; and fusing the short-term clock offset predicted value and the topology correction quantity to generate a dynamic compensation time reference, performing time marking on the acquired electrical quantity measurement data of the power distribution network, and generating synchronous measurement data with a timestamp. According to the technical scheme, when the Beidou signal is lost, the local clock drift predicted value and the adjacent node topology correction amount are fused to generate the dynamic compensation time reference, so that the measurement data synchronization precision and robustness of the power distribution network in a complex environment can be remarkably improved.

The invention relates to the technical field of software time synchronization, and discloses a software time synchronization method and system for multi-sensor data fusion, and the method comprises the steps: extracting temperature, load and drift frequency characteristics through principal component analysis based on the working state and historical drift data of a sensor, and constructing a confidence evaluation model to calculate the credibility of a timestamp; identifying an abnormal node group by using k-means and an isolated forest algorithm, analyzing a phase deviation fluctuation and network delay interaction effect, extracting a nonlinear drift feature in combination with a Prophet algorithm, and calculating a phase correlation value by using Hilbert cross-correlation; and dynamically adjusting node clock parameters and generating a calibration timestamp according to the network influence weight and the stability evaluation result. According to the method, the problem of time desynchrony caused by clock drift and network delay factors in a distributed system is effectively solved, and the overall time consistency and reliability of the system are improved.

The invention relates to the technical field of high-precision satellite navigation and positioning, and discloses a multi-modal sensor space-time synchronization method for high-precision data acquisition, which comprises the following steps: constructing a hardware delay observation loop to calculate physical response delay in real time; establishing a receiver clock drift model and extracting a clock drift coefficient; generating a phase lead trigger instruction in response to the delay mean value and the clock drift coefficient cumulant based on the GNSS whole-second target moment; according to the method, a feed-forward control closed loop is constructed by using GNSS clock difference parameters, the intrinsic alignment of the heterogeneous sensor physical sampling action and GNSS atomic time is realized, the real-time alignment of the sensor physical sampling action and the GNSS atomic time is realized, and the real-time alignment of the sensor physical sampling action and the GNSS atomic time is realized. And a strict physical time reference is provided for high-dynamic multi-source data fusion.

The invention discloses a data collaborative directory management method and system, and relates to the technical field of government affair informatization, and the method comprises the steps: generating a directory snapshot containing a global hash value; calculating a directory node hash value of each edge directory node based on the directory snapshot identifier; eliminating clock drift interference through time sequence alignment and dynamic tolerance filtering; inputting the Hash difference time sequence into an isolated forest model to judge a substantial change node; based on the difference entry number and the historical calling weight, combining a dual-threshold rule and an online dichotomy model to hierarchically synchronize requirements; according to a grading result, matching an incremental push mode or a full pull mode, and constructing a synchronous transaction context containing an exponential backoff retry mechanism; synchronous operation is executed through the two-stage state model, and compensation rollback is triggered when the synchronous operation fails; and calculating a health index of the substantially changed node, dynamically selecting a self-healing action and optimizing system parameters. The problem of misjudgment caused by time sequence drift is effectively solved, the synchronization efficiency is improved, and the consistency of directory versions is guaranteed.

The invention provides a method for automatically calibrating collected data of high-precision measurement and control deformation monitoring equipment, and belongs to the technical field of wind tunnel inner profile measurement. Multi-equipment clock synchronization is realized by establishing a unified time reference system, and measurement data of different frequencies are processed by adopting a CPU-GPU heterogeneous parallel processing architecture, so that the measurement accuracy is improved. The method comprises the following steps: performing three-level alignment on time, space and precision dimensions by using a multi-level clustering algorithm, eliminating clock differences among equipment by using a clock drift correction equation set, establishing a space coordinate system conversion matrix to unify a global coordinate system, and performing adaptive data fusion according to a precision weight by using a Kalman filtering fusion algorithm. And a data quality evaluation system is established to ensure the accuracy of a calibration result, a high-precision calibration data set is finally output, and the technical problem that the measurement precision is reduced due to space-time inconsistency of heterogeneous data of multiple devices is solved.

The invention discloses an automatic integrated system from an asynchronous pipeline to an asynchronous circuit, which adopts a modular architecture, takes a high-level structure description file in a JSON / XML format as input, and gradually maps to generate a gate-level netlist and a standard delay format file so as to be in butt joint with a commercial back-end design process. According to the method, asynchronous design based on an asynchronous structure can be automatically mapped into an asynchronous circuit, the automatic mapping process can seamlessly process multi-level design representation, the mapping result is stable and cooperatively operated, asynchronous circuit time sequence detection and delay matching are automatically completed, the design efficiency is greatly improved, and the design cost is reduced. An automatic delay matching mechanism enables the circuit to have a good data ready detection and handshake mechanism, and the characteristics of low power consumption, high throughput and no global clock drift sensitivity are realized; in addition, automation of asynchronous design key links such as structure abstraction, time delay modeling and testability insertion is achieved while design readability, hierarchical consistency and time sequence controllability are guaranteed.

The invention discloses a medical device and rehabilitation software information system based on the Internet of Things, and particularly relates to the technical field of communication transmission management, which constructs event-anchored linear alignment on an edge side, takes a real-time channel quality vector as input, and generates a compression strategy through a Pareto multi-arm bandit, so that the compression strategy is compressed, and the communication transmission efficiency is improved. Meanwhile, a dynamic compression offset index is used as a safety gate, so that a self-adaptive compression decision considering distortion and time delay is realized, and the technical problem that the time sequence consistency and the diagnosis integrity of the multi-modal physiological signal are difficult to guarantee simultaneously under the conditions of clock drift and bandwidth limitation is solved; a cross-modal alignment quality monitoring module is arranged and used for recognizing and restraining cross-modal dislocation false correlation in real time, so that it is ensured that rehabilitation evaluation and short-period diagnosis are established on a reliable time sequence corresponding relation, and the dislocation problem existing in electrocardiosignals and action signals is solved.

The invention discloses a machine tool running state collection and evaluation method and system, and relates to the field of intelligent machine tools, and the method comprises the steps: collecting machine tool multi-dimensional data through a multi-channel collection device; performing time alignment on different sampling frequency signals by adopting a dynamic synchronization algorithm of clock drift compensation; executing noise suppression, feature extraction and compressed encoding at the edge computing node to generate local state abstract data; sending the abstract data to a central server through a distributed message queue, and realizing multi-application concurrent access based on load dynamic scheduling; and the central server performs fusion analysis on the abstract data by using a multi-modal fusion deep network model, and outputs a health degree index and an overall operation score of the key parts of the machine tool, thereby realizing intelligent evaluation and health prediction of the operation state of the machine tool. The method realizes global perception and intelligent evaluation of the machine tool operation state, and can be widely applied to operation monitoring and health management of high-end numerical control machine tools, complex machining centers and unmanned production lines.

The invention discloses a foundation pit support deformation real-time monitoring method based on edge calculation, and aims to solve the problems of multi-node time synchronization and clock drift compensation caused by unavailability or poor quality of satellite navigation and precise time protocols in an underground or shielded environment. According to the method, through event dictionary learning, partition time slot scheduling and safety coding micro excitation time synchronization, matched filtering decoding, multi-scale arrival time estimation, paired time difference robust fusion, frequency priority and phase speed limit correction and network disconnection time holding, the time synchronization efficiency is improved; the technical effects that multi-source data alignment, deformation field reconstruction and graded early warning are completed on the unified virtual reference time scale, and high-precision synchronization and online drift compensation are obtained without depending on the external time service condition are achieved.

The invention discloses a power distribution network fault type identification method based on big data, and relates to the technical field of power distribution network fault type identification. Multi-source data time axes are aligned on the premise of keeping original sampling precision through clock drift correction and a self-adaptive interpolation algorithm; the problem of misjudgment faults or missed judgment faults caused by asynchronous voltage / current signal time is thoroughly eliminated; low confidence is marked for communication delay data, participation in calculation is limited, and noise interference feature extraction is avoided; on the basis of a fault type association mechanism of a misjudgment sample, a network layer needing to be adjusted is accurately positioned, and resource overhead of full-model retraining is avoided; the scarce fault data is expanded by combining an adversarial sample generation technology, and the recognition robustness of complex scenes such as high-impedance grounding is improved.

The invention discloses an SLAM-oriented multi-sensor space-time synchronization and online calibration method, and relates to the technical field of computer vision and robot perception. Comprising the steps that S100, initialization is carried out, and an initial pose and an external parameter transformation matrix initial value are obtained through coarse alignment; s200, data acquisition and preprocessing: acquiring IMU data, LiDAR data and Odom data in real time, and performing data filtering, distortion removal, time sequence correction and point cloud downsampling processing on the acquired data; and S300, performing time synchronization processing, estimating the time offset of the LiDAR and Odom data in real time, and performing unified correction to generate a unified timestamp. According to the method, an online time offset estimation and compensation mechanism with an IMU as a main clock is established, accurate synchronization of sensor data of different frequencies is achieved, and the problem of data alignment caused by sampling frequency difference and clock drift is effectively solved; and meanwhile, tight coupling fusion is realized by using an IMU pre-integration factor, a LiDAR residual factor and an Odom constraint factor, so that the space-time consistency of multi-sensor data is remarkably improved.

The invention belongs to the technical field of network live broadcast, and particularly relates to a multi-live-broadcast-room matrix cooperative control system and a control method, a global unified clock reference system is established, and a public time axis covering all participating nodes is generated in a distributed calibration mode, so that audio and video streams of all live broadcast rooms are collected and played based on the same time reference, and therefore, the collection efficiency is improved. The synchronization deviation caused by clock drift is fundamentally eliminated; and a dynamic topology sensing type transmission network is further constructed based on the public time axis, each node periodically detects a link state and generates a score, an optimal transmission path set is generated in real time, and adaptive scheduling of data streams is realized. Therefore, accurate alignment of multiple paths of media streams in the time dimension is ensured, the end-to-end transmission delay is remarkably reduced, the audio and video synchronization precision and transmission stability in a cross-live-broadcasting-room interaction scene are effectively improved, and the overall audio-visual experience of a user is improved.

The invention relates to a data extraction processing method and system for multi-modal simulation of diagnosis and treatment behaviors. The method and system are mainly applied to large-scale, high-frequency and multi-source data processing in a medical scene. Physical connection and protocol adaptation are established through edge computing nodes, diagnosis and treatment equipment and sensors, and data such as physiological parameters, diagnosis and treatment behaviors and case information are collected through a multi-protocol analysis engine. And then constructing a distributed clock synchronization network to carry out cross-device clock calibration, and processing the clock drift problem by adopting a dynamic buffer adjustment strategy. Thirdly, performing three-stage filtering processing and a tensor slicing strategy on the acquired data to realize intra-modal partitioning operation; and finally, integrating multi-dimensional results through a differentiable voting mechanism, and defining a confidence fusion function to calculate a weight coefficient. According to the invention, the problems of clock error between devices, processing capability limitation, algorithm optimization and the like in the prior art can be solved, and the accuracy and high efficiency of data processing are ensured.

The invention discloses a power embedded RTOS-oriented clock management method and related equipment, and the method comprises the steps: collecting the current clock data of a power embedded RTOS system, carrying out the feature extraction of the current clock data, constructing a clock feature library, and constructing a clock data model in a normal clock operation state, generating normal clock data according to the clock data model; the frequency stability, the clock jitter rate and the clock drift rate of the current clock data are calculated, and whether the deviation between the current clock data and the normal clock data exceeds a clock threshold value or not is judged; and when the deviation exceeds the clock threshold value, executing a corresponding exception handling flow according to the frequency stability, the clock jitter rate and the clock drift rate, and dynamically adjusting the range of the clock threshold value. According to the embodiment of the invention, combined judgment and dynamic adjustment can be carried out by combining drift, jitter and frequency stability thresholds, and accurate monitoring and anomaly detection of the clock are realized. The method can be widely applied to the technical field of clock management.

The invention is suitable for the technical field of communication, and provides an equipment control instruction generation method and device, equipment and a medium, and the method comprises the steps: obtaining a plurality of instruction channel sampling data related to a command instruction under the condition that the time sequence initial characteristic quantity of any instruction channel is detected to exceed a preset threshold value; sampling preprocessing and feature fusion processing are carried out on the multiple instruction channel sampling data, and an initial scene block is generated; and performing semantic analysis and entity anchoring processing on the compression vector through a lightweight convolutional network constructed based on the initial scene blocks to obtain a deterministic intention map. And carrying out topological sequence disassembly and sparse dependency matrix expansion on the deterministic intention graph to generate an action account book. And performing parameter completeness verification and hash calculation on the action account book according to a preset device interface rule, generating a device control instruction, and calling a plurality of devices corresponding to the command instruction. False execution caused by clock drift, model uncertainty or resource competition can be eliminated.

The invention discloses a comprehensive pipe gallery operation positioning and visual data processing system and method, belongs to the technical field of intelligent monitoring and management, and aims to solve the problems of poor data synchronization, weak dynamic adaptation, high false alarm rate and the like. According to the system, positioning and visual data are calibrated at a millisecond level through the timestamp alignment module, and multi-source data synchronization is ensured; a graph neural network GNN is used for fusing multi-sensor data, a personnel-equipment-environment space-time correlation graph is constructed, a dynamic digital twinborn body is generated in combination with a BIM model, and real-time monitoring and fault early warning are achieved; the visual optimization module can dynamically correct false detection, significantly reduce false alarm rate and bandwidth occupation, and optimize data transmission; the data processing method based on the system comprises the following steps: calibrating multi-modal data, and compensating clock drift; constructing a space-time correlation graph, and distributing dynamic weights; analyzing a visual result in real time, training and updating model parameters, and compressing data to reduce bandwidth; and the method is suitable for power stations, urban pipe galleries and other scenes.

The embodiment of the invention discloses a time synchronization method and device based on Kalman filtering, a medium and a product. According to the method, the precision and the speed of time synchronization are improved by establishing a double-state model containing clock skew and clock drift; a dynamic suppression factor is introduced to adaptively adjust an observation noise covariance to deal with abnormal noise; distinguishing and independently adjusting the process noise covariance of the clock skew and the clock drift by adopting a block self-adaptive strategy so as to match different noise characteristics of the clock skew and the clock drift; and finally, high-precision and high-robustness time synchronization is realized through Kalman filtering.

The application discloses an EtherCAT master station clock synchronization method and system. The method comprises the following steps: determining whether the current master station clock drift value is less than the clock drift threshold value; in response to the current master station clock drift value being not less than the clock drift threshold value, adjusting the master station clock according to the master station clock drift value until the master station clock drift value is less than the clock drift threshold value; in response to the current master station clock drift value being less than the clock drift threshold value, sending multiple periodic data frames by the master station and calculating the drift values of the multiple periodic data frames; obtaining the predicted periodic data frame drift value based on the drift values of the multiple periodic data frames; and adjusting the period of the master station clock for sending the periodic data frame based on the predicted periodic data frame drift value. By using the scheme, the clock drift between the master station and the slave station can be reduced, and the clock synchronization accuracy can be improved.

The invention relates to the technical field of power distribution terminals, and discloses a power distribution terminal automatic joint debugging function integrity and reliability test system, which comprises a co-simulation module for performing closed-loop coupling on a virtual power grid and a tested terminal through deterministic time control and generating a reproducible working condition; the scene arrangement module is used for realizing automatic switching and rollback of cross-domain scenes based on transactional snapshots; and the communication module is used for executing a consistency test on multiple protocols and injecting delay jitter, packet loss and clock drift. The functional integrity and reliability test system for the automatic joint debugging of the power distribution terminal aims to solve the problems of lack of deterministic time control of cross-domain cooperation and insufficient guarantee of state consistency in a digital twin test method. The problems that a test result cannot be reproduced, crosstalk misjudgment is caused by state non-atomicity consistency during multi-scene switching, and faults are difficult to reproduce due to lack of time determinacy replay capability are solved.

This disclosure describes techniques for managing clock drift compensation in a network of node devices. In some embodiments, such techniques may comprise determining a current status of a network that includes a set of node devices operating in a first mode, determining, based on the current status of the network, a quantity of the set of node devices to be switched to a second mode, determining, based on one or more characteristics of individual node devices in the set of node devices, a subset of the set of node devices including a selection of the quantity of node devices from the set of node devices, and providing, to individual node devices in the subset of the set of node devices, instructions to cause the individual node devices to switch from the first mode to the second mode.

The invention discloses a secondary equipment hidden fault identification method and system based on transient state-steady state data space-time alignment. The method comprises the following steps: collecting transient state recording data and steady state SCADA (Supervisory Control And Data Acquisition) data; unified time service is carried out on transient state and steady state data, and a time mark error is corrected; performing Lagrange interpolation resampling on the transient data to generate a virtual sequence aligned with a time axis of the steady-state data; constructing a cost matrix for the resampled transient sequence and the resampled steady-state sequence, and backtracking a shortest path to obtain an aligned fusion sequence; inputting the fusion sequence into a multi-scale feature fusion network, and outputting a fault type and confidence; the system comprises a data acquisition module, a clock drift correction module, a resampling alignment module, a dynamic time warping module and a fault feature extraction module. According to the method, the fusion problem caused by sampling rate difference, clock drift and dimension difference of transient and steady data is solved, millisecond-level space-time alignment is realized, and the precision of data fusion is remarkably improved.

Described herein is a computer implemented method for correcting for clock drift of a system clock in a signal sampling device comprising the system clock and configured to sample a signal in real time, the method comprising: obtaining data relating to an environmental parameter of an environment of the signal sampling device; matching the data relating to the environmental parameter to an environmental scenario; selecting, from a model set, a model tagged with the matched environmental scenario; and correcting for clock drift of the system clock using the selected model. Also described herein is a method for preparing a model set for clock drift correction, a sampling device, and a computer implemented method for correcting for clock drift of the system clocks of an array of signal sampling devices.

The invention discloses a multi-hop pipeline propagation method based on TDMA time slot level synchronization. The method comprises the following steps: S1, constructing a TDMA frame format; s2, constructing a local pseudo transition time mapping table in an uplink receiving time slot; s3, constructing a local clock drift trend model based on a bat resonance fitting algorithm; s4, predicting the expected arrival time of the next uplink synchronization according to the model, and adjusting a local clock; s5, completing data packet processing operation in the local processing time slot; s6, in a downlink sending time slot, the node completes service data sending and adds local clock drift trend model parameters; s7, entering a low-power-consumption monitoring state in the protection sleep time slot, comparing the difference between the feedback model parameters and the model parameters, and updating the model if the difference exceeds a preset tolerance threshold; and S8, the node injects Gaussian disturbance into a local clock in a set frame period, and the model is updated regularly. According to the method, a bat resonance fitting algorithm and a time slot modeling method are adopted, and multi-hop node autonomous synchronization is achieved.

The invention belongs to the technical field of industrial measurement and control, and discloses a multi-case cascade vibration noise data acquisition clock synchronization method. A clock drift prediction model based on deep learning is constructed by acquiring local clock signals and environment parameters of all cases in real time, and accurate prediction of clock behaviors is achieved. A multi-mode communication strategy combining optical fibers and wireless radio frequency is innovatively adopted, reliable transmission mechanisms which are redundant to each other are formed, and the anti-interference capability is remarkably enhanced. A dynamic compensation mechanism based on the fuzzy logic controller can intelligently adjust compensation parameters according to clock states and environment changes, and accurate correction is achieved. A multi-level verification mechanism including local self-inspection, mutual inspection between cases and global optimization is established, a graph neural network technology is introduced to carry out system-level optimization, and the system has self-learning and self-optimization capabilities. According to the method, the time consistency of the vibration noise data is remarkably improved.

The invention discloses a wireless cooperative control system and method for an equipment cluster, relates to the technical field of equipment cooperative control, and is used for solving the problem of how to realize a PTP-like slave synchronization mechanism and timestamp re-calibration filtering through software so as to eliminate the influence of clock drift, cross-domain time synchronization errors and wireless jitter. By introducing time synchronization middleware, especially a time delay decomposition engine, complex end-to-end wireless communication time delay can be accurately decomposed into a fixed component and a random jitter component, modeling and estimation are carried out based on observable features, the precision and robustness of wireless time synchronization are remarkably improved, and the time synchronization efficiency is improved. And the influence of the uncertainty of the wireless channel on the synchronization performance is overcome.

The invention discloses a special transformer acquisition terminal-oriented time synchronization drift self-correction method, which relates to the technical field of special transformer acquisition terminals, and comprises the following steps of: acquiring condition information based on a special transformer acquisition terminal, and generating a judgment condition according to a size relationship among parameters in the condition information to identify triggering of a self-correction mechanism. Running state data in the special transformer acquisition terminal are monitored in real time, a local clock drift value of the current special transformer acquisition terminal is preliminarily evaluated after correlation analysis, trend tracking and updating of a variable time sequence are realized in combination with historical data and progressive regression, and finally a residual drift residual error is determined. And carrying out dynamic self-correction operation on the time synchronization drift of the special transformer acquisition terminal.

The invention relates to the technical field of data synchronization, and particularly discloses a multichannel instrument data synchronization method and system. The method comprises the following steps: acquiring time sequence data and timestamps of each channel of a multi-channel instrument, calculating a data sampling period and a clock drift rate according to the time sequence data and the timestamps so as to quantify time synchronization deviation, extracting a transient energy ratio and a spectrum distortion degree of a time sequence signal, measuring signal stability, performing normalization processing, and combining dynamic drift risk indexes of the time sequence signal, the spectrum distortion degree and the signal stability so as to obtain a time sequence signal. The low-risk data form a synchronization group, the high-risk data are isolated and corrected and then merged into the synchronization group to form synchronization data, and through dynamic risk assessment and grading processing, the influence of single-channel abnormity on overall synchronization is avoided, the clock and signal stability is considered, and the synchronization reliability is improved.

The invention relates to the field of time synchronization, and discloses a time synchronization method and device based on a base station, communication equipment and a medium, and the time synchronization method based on the base station comprises the steps: obtaining initial clock reference information, transmitting the information to an adjacent base station through an IEEE1588 protocol, and forming a candidate synchronization signal. And based on the candidate synchronization signals, selecting an optimal master clock from the adjacent base stations by adopting an optimal master clock algorithm, and taking the time of the selected master clock as standard time. And based on the selected standard time, the standard time is issued to the whole base station network through cascade transmission among the multiple stages of base stations, so that each base station can perform periodic correction based on the standard time, thereby ensuring unification and accurate synchronization of clocks of the whole network. According to the time synchronization method based on the base stations, the clock synchronization precision between the base stations is effectively improved, clock drift and errors are reduced, and stable operation of the base stations in a complex environment is ensured.

The present disclosure provides techniques for measuring and compensating for clock drift errors in time-aware networks and time-sensitive applications, where a time-aware system (TAS) measures clock drift, and compensates for the measured clock drift, and makes predictions of future clock drift values based on history and other physical measurements. Existing messages used for measuring link delay and / or used for time synchronization can be used for frequency measurement (and thus clock drift measurement), and this measured drift can be applied as a correction factor whenever synchronization is determined and / or used. The predicted clock drift rate can be based on various probability distributions including linear, Kalman filters, and / or others. Other embodiments may be described and / or claimed.

The invention discloses a task synchronization and scheduling method for compensating CAN bus clock drift, which relates to the technical field of industrial automation control, and comprises the following four steps: initializing a system, loading a real-time protocol stack, completing hardware self-inspection and clock calibration, and sending a ready signal after confirming that a link is smooth; performing synchronization parameter configuration and task planning, defining clock synchronization reference parameters, dividing four types of tasks and setting priorities; performing dynamic calibration and data buffering on master and slave clocks, broadcasting a synchronous message with a timestamp by a master station, correcting a local timer by a slave station through a soft phase-locked loop, and constructing an annular buffer area to realize time domain decoupling; task cooperative scheduling and abnormal fault tolerance are carried out, a control task is triggered based on a calibration clock, edge calculation is carried out to reconstruct a motion state and feed-forward compensation is carried out, a multi-dimensional state is monitored in real time, and a fault tolerance mechanism is triggered. According to the method, clock synchronization precision and control stability are greatly improved, bus bandwidth limitation is broken through, high dynamic tracking precision is achieved, and long-term stable operation of the system is guaranteed.