30 results about "Clock drift" patented technology

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.

This invention relates to the field of power system distribution network line loss management technology, and discloses a multi-source data preprocessing method and readable storage medium for transformer area line loss analysis. A local reference clock is constructed in an intelligent fusion terminal, which receives multi-source heterogeneous data from distributed nodes. The local timestamps and arrival timestamps of each multi-source heterogeneous data are obtained to construct transmission delay models between each distributed node and the intelligent fusion terminal, as well as clock drift models for each distributed node. The local timestamps of the data to be processed are input into the transmission delay model and the clock drift model to obtain the corresponding transmission delay compensation and clock deviation compensation. These are added to the local timestamps of the data to be processed to obtain a standard timestamp aligned with the local reference clock, completing the timing alignment of the data to be processed. This fundamentally eliminates line loss calculation errors caused by timing misalignment and achieves sub-second high-precision timing alignment.

The embodiment of the utility model provides a circuit board structure and electronic equipment, and relates to the technical field of smart watches, and the circuit board structure comprises a mainboard; the second circuit board is electrically connected with the main board, the second circuit board comprises a first part, and the projection of the first part is located outside the outline range of the main board in the direction perpendicular to the main board; and the temperature compensation crystal is electrically connected with the first part. According to the embodiment of the first aspect of the application, the second circuit board is a flexible circuit board. According to the circuit board structure and the electronic equipment provided by the embodiment of the invention, the first part of the second circuit board is located at the position outside the mainboard, so that the first part is far away from the mainboard, and the first part is provided with the temperature compensation crystal, so that the temperature compensation crystal is far away from the mainboard, and the purpose of being far away from a heat source on the mainboard is achieved; and the risk of clock drift of the temperature compensation crystal can be reduced.

This invention discloses a multi-node collaborative electromagnetic ultrasonic online monitoring method and system. The invention relates to the technical field of online monitoring, introducing orthogonal code demodulation into multiple electromagnetic ultrasonic probes to ensure complementary interference between the probes and the same object under test. It collects detection data output from each monitoring node and extracts the echo timestamp of the object under test. Clock drift of each monitoring node is compensated in reverse along this echo timestamp to trigger spatiotemporal alignment of the detection data. An attention mechanism is then used to construct a corresponding multi-node collaborative detection system, improving its accuracy. Based on the dynamic identification of multiple electromagnetic ultrasonic online monitoring contents, corresponding suspected defect data is determined. This suspected defect data is loaded into the online monitoring finite element module, and the corresponding online monitoring defect path is determined by combining the corresponding multi-physics coupling relationship, improving the accuracy of the online monitoring defect path.

The application discloses a high-confidence data situation expression method based on timestamp cooperation, and relates to the technical field of data situation expression.The method comprises the following steps: multi-source timestamp cooperation calibration, timestamp-driven heterogeneous data dynamic fusion, time synchronization precision correlation confidence evaluation and situation generation, and high-confidence data situation visual expression.Through the construction of a hierarchical cascading timestamp cooperation calibration network, the absolute and relative time models are fused, the time alignment of multi-source heterogeneous data is realized at the microsecond level, the space-time dislocation problem caused by clock drift and network delay is fundamentally solved, the fusion efficiency and accuracy are significantly improved by taking the accurate timestamp as the driving force, dynamically dividing the fusion granularity and checking the time sequence consistency, the time synchronization precision is quantified as the confidence weight, and the dynamic confidence interval is generated by integrating the situation analysis, so that the evaluation result is changed from the subjective experience judgment to the objective and measurable reliable basis.

An adaptive crystal oscillator specification velocity measurement method, a GNSS receiver, and a storage medium are disclosed. The method includes: acquiring quality characteristic data of signals from N satellites; determining clock drift estimation characteristic data based on the current satellite signals, assuming the current signal quality meets set quality requirements based on the quality characteristic data; determining an additional clock drift constraint equation based on the clock drift estimation characteristic data, including a first velocity and clock drift solution equation set of N+1 equations, and solving for the receiver velocity and clock drift values; wherein the weights of the clock drift constraint equations in the first velocity and clock drift solution equation set are negatively correlated with the estimated jitter variance of the clock drift. This disclosed scheme, with its adaptive crystal oscillator specification, employs a first velocity and clock drift solution equation set with an added clock drift constraint equation for velocity calculation, enhancing the compatibility of the GNSS receiver / chip calculation method with various crystal oscillator specifications and performance variations caused by usage conditions, and improving the accuracy of receiver velocity calculation.

This invention relates to a method for creating a customer profile map and intelligent attribution analysis based on omnichannel data fusion. The method includes: obtaining a first feature set from multi-source heterogeneous raw data; extracting the time offset baseline and clock drift coefficient of nodes, compensating for discrepancies in conflicting timestamps, and obtaining a unified time-series benchmark through constraint propagation; extracting service commitment subjects and business process elements, using link association to obtain implicit associations between commitment elements and business nodes, and embedding business data under the unified time-series benchmark with the commitment link to obtain a second feature set; obtaining implicit associations and transmission paths between nodes to generate associated data for customer profile nodes; identifying abnormal nodes in complaint feedback and problem representation through cross-dimensional fusion; and tracing the source of the problem through reverse link tracing to obtain intelligent attribution results based on cause deconstruction. This method achieves a customer profile map and intelligent attribution analysis based on omnichannel data fusion.

This invention belongs to the field of tunnel detection technology and provides a method and system for identifying tunnel structural defects based on multispectral sensing and SLAM. Based on multiple response timestamp data, a residual squared sum objective function is constructed to represent the difference between the theoretically predicted clock vector and the actual measured timestamp matrix. Through iterative optimization, the optimal smooth estimate of the clock drift rate is determined, reducing the combined effects of electromagnetic interference and temperature / humidity variations. A three-dimensional point cloud map is constructed based on the coupling of axial integrals of inertial data and radial constraints of laser data, achieving long-distance, high-precision passive positioning under tunnel corridor effects. Furthermore, a lightweight identification model using a multidimensional knowledge distillation architecture and geometrically guided fraction fusion reduces edge memory consumption. By combining the reduction of electromagnetic interference and temperature / humidity variations, overcoming positioning drift under the dual constraints of corridor effects, and breaking through edge computing power limitations, the tunnel defect identification effect is improved.

The application discloses a kind of multi-modal neural signal synchronous acquisition methods and systems for Chinese speech brain-computer interface, electronic equipment and storage medium.The method comprises: configuring multiple heterogeneous data sources, each data source realizes unified data source interface;For each data source, create an independent data acquisition pipeline;Multi-data source is realized by global synchronization controller Three-stage synchronous start;When data arrives, use host high-precision timer to mark microsecond-level timestamp, unify heterogeneous data to the same time reference, and execute clock drift compensation algorithm;Data is distributed to consumer by lock-free queue.The application realizes sub-millisecond cross-modal synchronization accuracy by three-stage synchronous start protocol, host high-precision timestamp marking, clock drift compensation algorithm;By supporting the lock-free queue of multiple consumer subscriptions, high-throughput and low-latency data transmission is realized;Through unified data source interface, good system scalability is realized.

A method, system, and device for secure communication in environments without synchronized clocks. Using a clock-skew server, devices embed clock-skew certificates in MIKEY-SAKKE messages to compute and verify message generation times. These certificates facilitate secure message exchange, including peer-to-peer scenarios and applications requiring intermediary servers, by addressing clock drift without relying on external time references. Embodiments support mission-critical communication while mitigating replay attacks and resource inefficiencies inherent in traditional synchronization-dependent methods.

The application relates to the technical field of data synchronization, and particularly discloses a multi-channel instrument data synchronization method and system. Time sequence data and time stamps of each channel of a multi-channel instrument are acquired first, then a data sampling period and a clock drift rate are calculated according to the time sequence data and the time stamps, so as to quantize a time synchronization deviation, then transient energy ratio and spectral distortion degree of the time sequence signal are extracted to measure signal stability, after normalization processing, a dynamic drift risk index of the three is combined to judge whether a preset threshold is exceeded, low-risk data is grouped into a synchronization group, high-risk data is isolated and corrected and then merged into the synchronization group, and synchronization data is formed, through dynamic risk assessment and hierarchical processing, the influence of single-channel abnormality on overall synchronization is avoided, clock and signal stability are taken into account, and synchronization reliability is improved.

This invention proposes a method, device, and readable storage medium for testing the time consistency of digital therapy applications. Addressing the issues of the inability to simulate the time effects of real devices and the lack of clinical constraint verification in long-term digital therapy testing, this method parses configuration information to obtain a set of time attributes for treatment tasks; constructs a virtual timeline engine to run an independent simulated clock, using acceleration factors and superimposed clock drift to simulate time base deviation; employs system API hooks and middleware proxies to construct a transparent proxy layer, intercepting and redirecting the clock interface to achieve decoupled injection of the simulated clock and the absolute reference clock; and synchronously collects application-aware timestamps and real timestamps of trigger events during operation, automatically verifying time consistency based on clinical time-series constraint rules. This invention is primarily used for reliability verification and compliance certification of time-sensitive medical digital therapy software.

The application discloses a kind of water and electricity scheduling multi-source data management method, equipment and medium, it is related to water and electricity data management technical field, including, obtain water and electricity scheduling multi-source measurement data, parse event occurrence time and access time combination, form double-time event stream;Double-time event stream is implemented to deduplicate and clock drift calibration, and with event occurrence time as standard constructs water level line and late boundary, carries out hierarchical merging and shunt, obtains re-calculation window data and supplementary data;To main value sequence according to time window granularity generates version snapshot, and associated comparable data, same window candidate set and water and electricity scheduling scoring type, form blood chain.The application is deduplicated and clock drift calibration to double-time event stream, and based on event occurrence time dynamically constructs water level line and late boundary, realizes the hierarchical merging and shunt of event, stable demarcation re-calculation window and convergence late supplementary data, improve the time sequence consistency and re-calculation of multi-source scheduling data.

This 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, from a network entity, positioning configuration that indicates positioning operations to be performed to gather training data to train an ML positioning model to account for UE clock drift. The UE may monitor for 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 simulated clock drift measurements. Alternatively, the UE may transmit clock drift information with the positioning measurements to the training entity. Alternatively, the UE may utilize a hybrid approach that combines multiple positioning measurements with augmentation or providing clock drift information. Other aspects and features are also claimed and described.

This invention discloses a data synchronization acquisition method and system within a ring main unit, comprising the following steps: S1, acquiring operational data, recording sampling time identifiers, and constructing an operational data sequence; S2, performing time evolution processing on the sampling time identifiers, extracting the synchronization time center, and constructing a time deviation sequence; S3, performing continuous time compensation on the sampling time identifiers, and performing time remarking processing on the operational data sequence to obtain a calibration data sequence; S4, calculating the clock drift based on the calibration data sequence, performing correlation attention calculation and collaborative decision-making to form a sampling control sequence; S5, performing synchronization sampling triggering and frame structure reassembly processing to generate a data frame sequence as the synchronization result; S6, updating the algorithm parameters when a preset trigger condition is met. This invention employs neural control differential equations, etc., and possesses advantages such as high synchronization accuracy, good dynamic compensation effect, and high consistency of acquisition results.

The application discloses a kind of synchronous storage playback systems for multi-source data stream, including data acquisition module, time synchronization module, data encapsulation storage module, time index generation module and playback alignment module;Data acquisition module is used to obtain multi-source data stream and attach local timestamp;Time synchronization module is used to obtain global time;Data encapsulation storage module is used to store medium;Time index generation module is used to build entry in real time;Playback alignment module is used to obtain the alignment data of each stream.Through the data encapsulation format of multilayer time axis, combined with segmented linear time mapping model and interpolation and buffer alignment algorithm, the unequal sampling rate, clock jitter and clock drift of different data streams are effectively handled, so that multi-source data millisecond level synchronization under long-time recording scene is realized, and fast random access and playback are supported through multi-level time index structure.

The application discloses a ship distributed clock drift prediction and self-healing synchronization method suitable for long-time disconnection. The method can comprise: constructing a node self-calibration topology in a normal communication stage; collecting original clock data and drift characteristic data of each node in a normal communication or short-time disconnection stage, and constructing a clock behavior model; when a satellite time service star loss is detected and a ship-shore network is disconnected, triggering a long-time disconnection self-healing synchronization mode, and performing drift prediction and feedforward compensation; in the long-time disconnection self-healing synchronization mode, performing topology self-adaptive adjustment, drift dynamic monitoring, data buffering and time stamp correction; and after network recovery and reconnection, performing precision calibration. The clock synchronization method disclosed by the application does not depend on external time service, is based on node self-calibration and historical drift modeling, solves the problem of drift out of control under satellite star loss and network disconnection, and realizes sub-millisecond synchronization precision under long-time disconnection.

This invention provides a method and system for constructing high-quality datasets for non-ferrous metal production processes, belonging to the field of industrial big data processing technology. This invention fundamentally eliminates timing errors caused by clock drift and communication delays by extracting natural physical anchor points from the coordinated abrupt changes in furnace temperature and pressure to replace absolute clocks, achieving robust alignment of multi-source heterogeneous data. Simultaneously, it utilizes the synchronous transition states of vibration and current signals to construct survival markers, automatically distinguishing between real material events and suspected sensor failures, avoiding interference from data noise in event detection under harsh operating conditions. Furthermore, it employs a composite tracking code composed of sampling location, container number, and operation sequence to achieve full-chain physical traceability from sampling to testing and forced re-attachment of test results, ensuring high-precision correlation between process parameters and quality indicators.

This invention discloses a trustworthy determination method for cold chain IoT data based on deep learning and pattern recognition. To address the problems of inaccurate event association verification caused by time asynchrony due to clock drift, sampling differences, and transmission delays in multi-source time-series data, as well as the difficulty in identifying adversarial events caused by human intervention such as supplementation, deletion, and replacement, this invention achieves the technical effect of trustworthy category and trustworthy output by using time correction and alignment based on gateway reference time, event recognition, construction of event state time-series graphs with time lag edge attributes, calculation of graph representation and consistency score using time-series graph neural network, and fusion with similarity of prototype vector library.

The application discloses a kind of phase-locked loop hundred picoseconds level clock regulation method, device and system and storage medium, first, after receiving the clock difference parameter of big dipper differential precise time transfer solution, by analyzing and processing these parameters, the accurate estimation of clock drift and bias and other states can be carried out.Then, according to the estimated clock state, the corresponding control quantity is generated by regulator, and the control quantity is converted into voltage quantity and applied to oven-controlled crystal oscillator OCXO, to realize the frequency regulation of crystal oscillator.Therefore, the clock precision regulator can realize the accurate control of clock frequency, so that it is consistent with the reference time introduced by DPT.The clock state after regulation will be reflected in the next epoch in the big dipper differential precise time transfer solution, to realize closed-loop control, and finally output high-precision time and frequency signal consistent with reference clock.

This application discloses a method for synchronously acquiring IMU and ECG signals. The method includes: providing a unified clock reference for the ECG and IMU acquisition units by outputting a clock signal from the same source; synchronously configuring the sampling rate, range, and filtering parameters of both units; generating a synchronous trigger pulse signal with a period matching the sampling rate; establishing hardware synchronous trigger conditions by inputting the start-up terminals of the two units; after triggering sampling, marking the dual-channel raw data with the same high-precision timestamp; detecting clock drift by timestamp deviation verification; and adjusting the trigger pulse period to compensate for errors. Implementing the embodiments of this application can solve the problem of eliminating clock frequency difference and drift between the two acquisition links at the hardware level, achieving precise timing alignment of ECG and IMU signals, and improving the artifact removal effect and monitoring reliability of ECG signals under motion conditions.

The application belongs to the technical field of computer software and virtual simulation, and relates to a flight simulation data acquisition method and system capable of preventing clock drift and high concurrency; the method is used for solving the problems of data time sequence disorder and monitoring blind area in large-scale concurrent experiments, adopts a passive and active hybrid reporting mechanism capable of preventing clock drift, forcibly strips local time stamps when a client triggers a physical anchor to actively report progress JSON data, and unifies time distribution by a server, and simultaneously cooperates with a message queue to issue instructions to realize passive polling of instantaneous progress; in addition, online student identifiers are stored by using a Redis-based set data structure, traditional database lock table updating is abandoned, and microsecond-level online number lock-free statistics are realized; the application guarantees consistency of experimental data, overcomes defects such as calculation blocking and high-concurrency lock competition, and improves concurrent bearing capacity and rendering fidelity of the system.

This invention discloses a distributed CNC system based on a PC and a System-on-a-Chip (SoC), relating to the field of CNC technology. The system connects a host computer and a slave computer via a PCIe link. The host computer uses XDMA to write motion commands into the slave computer's DDR circular buffer. The slave computer's CNC unit monitors the buffer data level in real time, dynamically generating a time scaling factor and modulating the execution speed after smoothing and filtering, thus transforming discrete communication jitter into smooth speed changes. Furthermore, the system observes clock frequency differences and adjusts the slave computer's hardware timer reload value to synchronize the time base. The host computer then uses a pre-distortion scaling factor to correct the position increment, offsetting the physical speed deviation caused by the time base adjustment. This invention effectively solves the communication fluctuations and heterogeneous hardware clock drift problems of non-real-time operating systems, ensuring the continuity and accuracy of the machining process.

The application discloses a ground surface deformation monitoring method and system based on distributed millimeter wave radar, relates to the technical field of geological disaster monitoring, and comprises the following steps: cross-node closed-loop observation calibration is carried out based on distributed monitoring initialization configuration, phase bias, clock drift and installation angle error are corrected, and a closed-loop self-calibration monitoring frame is obtained; phase timing arrangement is carried out on the closed-loop self-calibration monitoring frame, and propagation environment disturbance separation is carried out in combination with micro-meteorological observation records and stable reference scattering point residuals, so that a disturbance decoupling displacement candidate set is obtained; same-name monitoring point matching and cross-node space-time alignment are carried out according to the disturbance decoupling displacement candidate set, deformation trajectory solving is carried out based on cross-node closed-loop phase self-consistent constraints, and a cross-node fusion deformation time sequence set is obtained; and the application realizes the collaborative correction of phase bias, clock drift and installation angle error by carrying out closed-loop consistency verification on cross-node observation relationship data and carrying out cross-node observation consistency influence evaluation and iterative compensation.

The application discloses a kind of multi-screen display synchronous display optimization methods.This method includes: obtaining the extended display identification data of each display and timing parameter;Based on the actual time stamp of the vertical synchronization signal of each display clock monitor, construct timing drift characteristic model;Select timing reference source or generate virtual reference clock;Delay compensation instruction is inserted in GPU rendering command stream, and the scanning start offset address of the frame buffer of secondary display is adjusted dynamically, and the physical clock phase difference between each display is compensated.In addition, for the mixed refresh rate scene, a proactive double buffering queue is established, and a complete frame is selectively output based on the tear risk index.The application can achieve microsecond-level accurate synchronization of multi-screen display at the software level without external Genlock hardware, effectively eliminating the tearing phenomenon caused by heterogeneous screen clock drift and the periodic stutter caused by mixed refresh rate.

This invention belongs to the field of multimodal data management technology. It provides a course management and analysis system for multimodal data, comprising: synchronously transmitting physical feature signals carrying pseudo-random codes through a physical reference source; acquiring visual image streams and non-visual physical perception streams, extracting coded phases and time-domain feature points; performing time-domain mapping and calculating nonlinear deviations to construct a dynamic second-order clock drift compensation function; using this function to correct timestamps and normalize the time axis to achieve multimodal data alignment; and finally generating a training course continuity analysis and evaluation report based on the aligned data. This invention can suppress clock drift and transmission jitter under strong electromagnetic interference, achieving high-precision multimodal time alignment and ensuring the timing consistency and evaluation accuracy of training data.

The application provides a clock synchronization method and device of a distributed device network, a terminal and a medium, the method comprising the following steps: determining a coordination center node with the minimum time-varying clock drift change rate in the current distributed device network, constructing an initial cluster network comprising multiple clusters by using other nodes in the network except the coordination center node, modeling a virtual clock of each node, initializing and synchronizing all clusters with the coordination center node, determining the relative clock drift between all nodes and the coordination center node, applying a spatial clustering algorithm based on hierarchical density noise, and clustering all nodes in the initial cluster network according to the relative clock drift, and assigning different synchronization frequencies to each target cluster in the target cluster network obtained by clustering, so as to realize distributed clock synchronization of the cluster network. The application re-divides the network into clusters by applying the spatial clustering algorithm based on hierarchical density noise, constructs a robust synchronization topology structure, and ensures the stability of the synchronization frequency allocation.