146 results about "Clock drift" patented technology

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 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 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 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 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 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 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.

The invention relates to the technical field of electric power systems, and discloses an electric power measurement data management system and method based on an intelligent terminal and an RPA, and the method comprises the steps: obtaining clock synchronization topological structure data, an original timestamp sequence and measurement data of intelligent terminals of a whole network; extracting a clock synchronization dependency relationship of the terminal based on a graph structure analysis algorithm, and generating a directed dependency graph; inputting the timestamp sequence and the dependency graph into a causal discovery algorithm, and identifying a clock error propagation path and causal intensity; constructing a graph neural network, taking an intervention effect prediction matrix as node feature input, and predicting a whole network cascade correction effect by minimizing a weighted square error between a corrected inter-node timestamp difference value and a reference difference value; according to the invention, systematic elimination of clock drift cascade influence in a power system is realized, and time sequence consistency of whole network measurement data is ensured.

The invention discloses a clock synchronization method and device for multi-modal human factor data acquisition, edge computing equipment and a medium, which are used for improving the accuracy of data alignment. The system controls a first human factor data acquisition device to send a periodic wave signal to each second human factor data acquisition device; each human factor data acquisition device carries out sampling according to the periodic wave signal; a human factor data receiving end in the system receives data packets sent by each human factor data acquisition device, and each data packet carries a packet number; determining absolute time corresponding to each data packet according to the packet number carried by each data packet; and performing data alignment processing on each data packet according to the absolute time corresponding to each data packet. According to the invention, since the data acquisition devices all take the moment of sending the periodic wave signals as the starting moment of data acquisition, a local real-time clock crystal oscillator is not needed, so that strict synchronization of data acquisition is realized, and the problem of data asynchronization caused by clock drift between the devices is eliminated.

The invention relates to a cycle slip processing method, device, equipment and medium, and the method comprises the steps: obtaining the observation error data of each satellite according to the difference between the double-difference carrier observation data of each satellite in a plurality of satellites of a target carrier frequency and the double-difference satellite-to-earth distance data of each satellite based on a current epoch and a previous epoch for a reference station and a monitoring station; the receiver clock drift deviation between the base station and the monitoring station is estimated based on the observation error data of the two first satellites, clock drift deviation data is obtained, and the two first satellites are the two satellites with the minimum observation error data difference value in the multiple satellites; and on the basis of the double-difference carrier observation data of a second satellite in the plurality of satellites, subtracting the double-difference satellite-ground distance data and the clock drift deviation data of the second satellite, and determining single-difference ambiguity incremental data so as to perform single-frequency cycle slip processing on the target carrier frequency of the current epoch on the base station and the monitoring station. According to the invention, single-frequency cycle slip processing can be efficiently and jointly carried out on double stations without the help of an external sensor.

The present disclosure provides systems, methods, and devices for wireless communication that support machine learning (ML)-based positioning that mitigates user equipment (UE) clock drift. In some aspects, a UE may receive a positioning configuration from a network entity that indicates positioning operations to be performed to collect training data to train an ML positioning model to account for UE clock drift. The UE may monitor positioning reference signals from a transmit / receive point and transmit positioning measurements to a training entity. The positioning measurements may include multiple measurements at a fixed location, or the UE may augment the positioning measurements based on analog clock drift measurements. Alternatively, the UE may send clock drift information to the training entity along with the positioning measurements. Alternatively, the UE may utilize a hybrid approach that combines multiple positioning measurements with augmentation or provision of clock drift information. Other aspects and features are also claimed and described.

The application discloses a power distribution network distributed measurement synchronization method and device based on Beidou satellite timing, and belongs to the technical field of power distribution network measurement, which comprises the following steps: acquiring Beidou satellite signals to calibrate local clock sources and generate a standard time reference; when continuously monitoring the quality parameter of the Beidou satellite signals is lower than a quality threshold, collecting clock working environment parameters of the local clock sources and combining the standard time reference to generate a short-term clock offset prediction value; generating a topological correction amount according to the topological connection relationship of the power distribution network; and fusing the short-term clock offset prediction value and the topological correction amount to generate a dynamic compensation time reference, time marking the collected electrical quantity measurement data of the power distribution network, and generating time-stamped synchronous measurement data. The technical scheme of fusing the local clock drift prediction value and the adjacent node topological correction amount to generate the dynamic compensation time reference when the Beidou signal is lost can significantly improve the precision and robustness of the measurement data synchronization of the power distribution network in a complex environment.

The invention discloses a method and a device for testing embedded software of airborne equipment. The method comprises the following steps: calculating a current clock skew drift rate according to time information in a synchronization message sent by target equipment; calculating a predicted clock skew with the target device according to the current clock skew drift rate; dynamically adjusting the clock frequency according to the preset clock skew, and synchronizing with the target equipment; and executing the test case to test the to-be-tested software on the target equipment. According to the high-precision time synchronization method based on the drift adaptive synchronization algorithm, the problems of real-time verification and time synchronization in embedded software testing are solved, the requirement for high time precision of civil aircraft airborne equipment is met, and the precision and robustness of test cases are improved.

This disclosure provides systems, methods, and apparatus for on-demand pilot signals (ODPS) for paging synchronization. The UE (110) may send a request (140) to the network entity (120) during the RRC idle or RRC inactive state. The request (140) may include an explicit ODPS request, clock drift information, one or more suggested parameters for ODPS, or any combination thereof. The network entity sends an ODPS configuration (150) to the UE to configure the ODPS. The ODPS configuration may indicate an ODPS pilot pattern, number of symbols, frequency, or other information to inform the UE how to receive the ODPS. A network entity transmits an ODPS (170) during a time period prior to a paging indication or wake-up signal (WUS) (180). The UE implements time and frequency synchronization using ODPS prior to receiving a paging indication or a WUS.

The invention relates to a frequency conversion clock calibration system for a repeater, and the system comprises a reference frequency deviation obtaining module which obtains the reference frequency deviation range of remote equipment and sets the initial parameters of a frequency deviation calibration experiment during the initialization calibration of a repeater system; the frequency offset calibration experiment module is used for determining a reference frequency offset value of the remote equipment through an experiment; the frequency offset period calculation module is used for calculating the frequency offset period according to the offset value, determining the total number of sampling points according to a preset sampling interval and then calculating a sampling time interval; the historical frequency offset data acquisition module is used for acquiring historical frequency offset data and calculating a frequency offset value by combining the historical frequency offset data with the current sampling time interval; the clock drift detection module is used for detecting clock drift caused by environment temperature, synthesizing a frequency deviation value and a drift degree, and selecting direct calibration or delay compensation; according to the system and the method, the problems of frequency deviation, clock drift, delay compensation and the like are solved through modular design and real-time calibration capability, and the clock precision can be efficiently and accurately ensured in a variable environment.

The invention discloses a physical training load regulation and control method and system based on self-adaptive physiological coupling, and the method comprises the steps: collecting an electrocardiosignal, a light volume pulse signal, a respiration signal, a surface electromyographic signal and a body surface temperature signal, and generating a multimode sequence with a time mark; self-adaptive time alignment is executed, a timestamp graph is constructed, clock drift estimation is carried out, segmented monotonic reversible time transformation is established, and a multimode sequence is mapped to a unified time axis; reconstructing the missing section and the artifact section, establishing a mask auto-encoder with physiological priori constraints, combining time domain consistency constraints and frequency domain consistency constraints, and outputting a continuous differentiable reconstructed sequence. According to the method, by introducing adaptive time alignment, cross-modal signal reconstruction and dual-time scale state modeling, coordinated recognition and dynamic load regulation and control of multi-source physiological signals are achieved, coupling analysis in the training process is more stable, and an individual model can be continuously and adaptively updated.