168 results about "Time deviation" patented technology

The invention provides an AGC signal intelligent correction and control method, device, equipment and medium, and the method comprises the steps: collecting an AGC instruction signal of a power grid dispatching side, an actual power feedback signal of a power plant side and a unit operation state parameter, and constructing multi-source heterogeneous data; inputting the multi-source heterogeneous data into a pre-trained digital twinborn model to obtain a predicted value of the real power of the unit; calculating a real-time deviation between the predicted value of the real power and the actual power feedback signal, and dynamically compensating the AGC instruction signal based on the real-time deviation to generate a corrected AGC instruction signal; and on the basis of the corrected AGC instruction signal, a feedforward control signal is generated, and is superposed to a basic control instruction of a unit distributed control system (DCS) in an increment form, so that full-load section accurate control is realized, and the problems of accurate correction of the AGC signal, accurate prediction of real power and dynamic compensation are solved.

The invention discloses a cosmic ray muon-based time synchronization system and synchronization method, and relates to the field of digital information transmission. The system comprises a time detector and a track detector which are arranged corresponding to a standard clock, and a case matching module, a time difference calculation module, a time adjusting module, a time detector and a track detector which are arranged corresponding to a clock to be calibrated, the case matching module is used for matching the cosmic ray muons according to the track information of the cosmic ray muons detected by the two track detectors and determining whether the cosmic ray muons penetrating through the two time synchronization devices belong to the same muon case or not, and if the cosmic ray muons penetrating through the two time synchronization devices belong to the same muon case, the time difference calculation module is used for obtaining theoretical flight time according to the track information detected by the track detectors; actual flight time is obtained according to a time detector; the time deviation is calculated according to the actual flight time and the theoretical flight time, the time adjusting module calibrates the clock to be calibrated according to the time deviation, and the precision and reliability of time synchronization in complex environments such as underwater and underground environments are improved.

The embodiment of the invention provides a digital video monitoring data transmission synchronization method and system, and relates to the technical field of digital video monitoring data transmission synchronization, and the method comprises the steps: receiving a video data stream and an external sensor data stream which is related to the content of the video data stream and has an independent stable time synchronization mechanism; identifying a visual event from the video data stream, and identifying a physical event associated with the visual event from the external sensor data stream; taking the timestamp of the physical event as a time anchor point, obtaining a visual original timestamp of the visual event, and calculating the time deviation of the video data stream according to the time anchor point and the visual original timestamp; based on the time deviation, correcting the frame timestamp of the video data stream by adopting an adaptive weighted average or filtering strategy to obtain a corrected timestamp; and fusing the corrected timestamps to obtain a global time reference. The reliability of the monitoring data and the accuracy of the analysis result can be improved.

The invention provides a multi-station cooperative control method based on event triggering and look-ahead synchronization. The multi-station cooperative control method comprises the following steps: S1, defining nominal motion parameters for each station; s2, when the physical completion event of the current station is detected, calculating to obtain an accumulated time deviation up to the current station; s3, on the basis of the cumulative time deviation, executing online optimization calculation in a prediction time domain containing a plurality of stations in the future so as to determine an optimal target operation duration used for compensating the cumulative time deviation; and S4, according to the optimal target operation duration, generating and issuing a new motion curve for a first station in the prediction time domain, taking the station as a new current station, and circularly executing the steps S2 to S4. According to the method, the system can actively eliminate tiny time deviation caused by uncertainty factors such as material difference and mechanical wear, and the accumulative effect of errors is avoided.

The invention belongs to the technical field of time synchronization, and provides a multi-sensor time synchronization method and system and application, and the method comprises the steps: carrying out the calibration of a local clock of each sensor based on a reference clock signal provided by a dual-mode reference clock, so as to correct the time deviation; measuring the original transmission delay of data transmission of each sensor in real time, and generating a dynamic compensation coefficient based on a delay fluctuation model; based on the calibrated local clock and the dynamic compensation coefficient, performing correction and alignment verification on the timestamps of the sensor data, and calculating an alignment error; and if the alignment error exceeds a preset threshold value, reversely adjusting the dynamic compensation coefficient and / or the reference clock signal to form closed-loop control. According to the method, the problems of low synchronization precision, poor flexibility and insufficient real-time performance of the existing multi-sensor time synchronization method under complex working conditions can be solved, and the space-time matching reliability of a multi-sensor fusion system is improved.

The invention discloses a subcarrier-level diversity combining method and subcarrier-level diversity combining equipment for multi-frequency diversity, and relates to the technical field of wireless communication. The method comprises the following steps: receiving a plurality of frequency points bearing the same service, and respectively carrying out orthogonal frequency division multiplexing demodulation on each frequency point to obtain a symbol estimation value; calculating a soft decision log-likelihood ratio and a reliability vector according to the symbol estimation value; aligning the time deviation, the carrier frequency deviation and the sampling rate deviation generated by frequency crossing of each frequency point based on each symbol estimation value; performing decorrelation processing on the aligned soft decision log-likelihood ratio to obtain a decorrelated soft decision log-likelihood ratio, and performing merging operation on the decorrelated soft decision log-likelihood ratio according to the aligned reliability vector to obtain a merged soft decision log-likelihood ratio; and decoding the merged soft decision log-likelihood ratio to obtain a decoding result, and adjusting the merging operation according to the decoding result. By implementing the technical scheme provided by the invention, the diversity combining accuracy can be improved.

The invention discloses a power grid time frequency change trend prediction method and system based on intelligent electric meter data fusion, and the method comprises the steps: measuring the network transmission delay and time deviation between a master clock and a slave clock of a power grid, obtaining an initial time frequency deviation sequence, carrying out the error calibration, carrying out the data fusion after time domain alignment, and carrying out the prediction of the time frequency change trend. Generating a fusion time sequence; performing recursive estimation on the fusion time sequence, outputting an optimal time frequency deviation sequence, and performing synchronous estimation to obtain a clock phase error, a frequency error and frequency drift as state characteristic quantities; and training a preset machine learning prediction model by taking the optimal time frequency deviation sequence as a supervision signal and taking the state characteristic quantity of the corresponding moment as input, and obtaining a prediction result of the power grid time frequency change trend in the future period based on the trained time frequency change trend prediction model. According to the method, the power grid time synchronization precision and prediction capability are remarkably improved, and reliable technical guarantee is provided for stable operation of a power system.

The invention relates to the technical field of data processing, and discloses a salt cavern gas storage brine discharging pipeline operation data processing method and system, and the method comprises the steps: periodically receiving a link detection data packet which is transmitted by a collection device and is provided with a transmission timestamp, and recording the arrival time of the link detection data packet; according to the sending timestamp and the arrival time, transmission characteristics of the link detection data packet are analyzed, and the transmission characteristics comprise transmission delay, jitter dispersion and out-of-order conditions; adaptively predicting a time offset pattern based on the transmission characteristics; generating a real-time calibration parameter according to the time migration mode; and receiving an actual data packet, and adjusting the timestamp of the actual data packet by using the real-time calibration parameter. According to the method, the limitation of traditional fixed compensation parameters is overcome, the time alignment precision of pressure and flow data flow is remarkably improved, leakage misinformation caused by time deviation is avoided, and the reliability and the operation and maintenance efficiency of a salt cavern gas storage brine discharging pipeline operation monitoring system are improved.

The invention discloses a dynamic correction timing method, device and system and a storage medium, and belongs to the technical field of kitchen appliances. The dynamic correction timing method is applied to the range hood. The range hood comprises a micro-control unit. The dynamic correction timing method comprises the following steps: networking to obtain standard network time; after the standard network time is successfully obtained, determining a time deviation value according to the standard network time and the current timing time of the micro-control unit; calculating a current time compensation coefficient according to the time deviation value and the networking calibration time interval; and before the standard network time is obtained through next networking, the timing time of the micro-control unit is corrected by using the current time compensation coefficient. Therefore, long-term accurate timing of the range hood can be achieved, and the problem that the long-time accumulated timing deviation of the range hood is large is effectively solved.

The invention relates to a prospective control method of a multi-axis linkage machine tool in the field of intelligent manufacturing, which comprises the following steps: by analyzing the time difference distribution of each axis in a compensation time sequence, establishing a dynamic compensation matrix of multi-axis linkage, the matrix comprising the advanced starting time and speed regulation coefficient of each axis in different motion stages, determining personalized motion control parameters of each axis; according to the updated delay characteristic data and the curvature radius information of the track corner, the position deviation trend of each axis in the corner machining process is predicted, whether the motion time sequence of each axis needs to be adjusted or not is judged by comparing the deviation degree of the predicted position and the theoretical track, and an optimized multi-axis cooperative motion instruction is obtained; and the optimized multi-axis cooperative motion instruction is input into a servo controller of each axis, an actual position feedback signal of each axis is monitored at the same time, and the response consistency of each axis is ensured by calculating the real-time deviation value of an actual track and a theoretical track and dynamically correcting compensation parameters in an electromechanical coupling delay model.

The invention discloses a signal processing method and system of an aviation intelligent flow sensor. The method comprises the following steps: collecting real-time signal data and generating a flow characteristic data set; determining an initial measurement parameter based on a preset flow signal model; the real-time deviation between the initial parameter and the actual operation state is obtained, the initial parameter is subjected to self-adaptive optimization through a normalized weighted deviation correction formula, and an optimized measurement parameter is obtained; and performing dynamic intelligent processing on the sensor based on the optimized parameters, evaluating a measurement error variance and a precision fluctuation rate through working condition segmentation and a fuzzy control algorithm, and generating measurement stability information. According to the method, through non-dimensionalized deviation correction and dynamic working condition segmentation processing, the flow metering precision and the signal stability in the aviation complex environment are effectively improved.

The invention discloses a front-feedback combined burst signal fast symbol synchronization method, which relates to the technical field of digital signal processing and satellite communication, and comprises the following steps: firstly, sampling a received signal subjected to matched filtering processing according to a 4-time symbol rate by using an initial NCO (Network Controlled Oscillator), then dividing a sampling value into two paths, sending one path to an FIFO (First In First Out) register for caching, and using Oamp in the other path; the method comprises the following steps of: firstly, performing timing deviation estimation by using an FIFO (First In First Out) register and an M algorithm, secondly, determining a moment when the FIFO register starts to read data, an oscillation initial value of an interpolation control NCO and an initial value of an interpolation coefficient according to a timing deviation estimation result, starting the interpolation control NCO, and then, sending the data read by the FIFO register into a Farrow structure interpolation filter for interpolation processing according to the initial value of the interpolation coefficient. And finally, a Gardner loop is started, feedback control is carried out on the interpolation control NCO, and an interpolation result is output, so that the fast symbol synchronization speed and precision of the burst signal are improved, and the stability and timeliness of fast symbol synchronization of the burst signal are guaranteed.

Data inaccuracy and insufficiency are critical aspects to be analyzed to improve batch predictions, specifically in context of SLA jobs as they are foremost in affecting deliverables. Embodiments of the present disclosure provide a method and system for enhancing batch predictions by localizing jobs contributing to time deviation and generating fix recommendations by fixing data inaccuracy and insufficiency. The term fix recommendation refers to recommending a list of plausible fixes to identified causes that reduce batch prediction errors enhancing accuracy of predictions. The localization is performed by bottom-up traversing of a batch graph representing a batch process, if the batch process has a Service level Agreement (SLA) job, by narrowing down to the SLA job that has end time inaccuracies. The localization enables identifying the origin or real contributors and root cause analysis is performed for the localized jobs to generate effective fix recommendations by fixing data inaccuracy and insufficiency.

This application provides an adaptive time synchronization compensation method, a terminal device, a gateway device, and a system. The adaptive time synchronization compensation method includes: receiving a beacon frame from a gateway; parsing a timestamp, an actual beacon period value, and an over-the-air transmission time value carried in the beacon frame, wherein the timestamp represents the absolute time at which the gateway begins sending the beacon frame, and the actual beacon period value is the actual interval between the start times of two adjacent beacon frame transmissions, as measured by the gateway based on its hardware clock; recording the local reception completion time of the beacon frame on the terminal device side; calculating a first time deviation between the local clock of the terminal device and the gateway clock based on the timestamp, the over-the-air transmission time value, and the local reception completion time; correcting the local clock of the terminal device according to the first time deviation; and calculating and determining subsequent periodic reception time slots of the terminal device based on the corrected local clock, the actual beacon period value, and predefined reception time slot parameters.

The invention discloses an aperture error and non-linear cooperative calibration circuit and method for a pipeline ADC, and relates to the technical field of mixed signal integrated circuits, the circuit comprises a pipeline ADC basic circuit and a calibration circuit integrated with the pipeline ADC basic circuit, and the calibration circuit comprises an aperture error calibration module and a non-linear error calibration module. And the aperture error calibration module dynamically adjusts the sampling clock phase of the first-stage Sub-ADC by counting a post-stage output code value histogram and combining an SAR logic feedback mechanism so as to compensate the sampling moment deviation between the first-stage Sub-ADC and the MDAC. The nonlinear error calibration module extracts errors by injecting pseudo-random jitter and utilizing double-threshold window crossing statistics, and after EWMA smooth filtering is carried out, a polynomial compensation coefficient is updated in a self-adaptive mode through an LMS algorithm, and harmonic distortion is restrained. According to the method, the linearity under high-speed and high-bandwidth application is remarkably improved, and the method has good robustness for PVT fluctuation.

The invention relates to the technical field of life cycle management, in particular to a full life cycle management system and method based on a PCB, and the system comprises a stage record generation module, a stage interval analysis module, a fracture node recognition module, an equipment sequence verification module and a path sequence construction module. According to the method, process node numbering, step numbering and equipment numbering are completed for a production line and a detection and storage terminal around PCB serial numbers, a data set with sequence semantics is formed, time deviation interference is eliminated through sequence smoothing, stage continuous state judgment is achieved, missing and repeated stages are recognized, and the reliability of the system is improved. Extracting equipment numbers and execution sequences to perform cross check, ensuring stage sequence consistency, recombining stage and equipment combinations according to a path sequence after node check is completed, and generating a life cycle path sequence table capable of reflecting process continuity, sequence consistency and abnormal distribution; and a dynamic computable data basis is provided for abnormity tracing, process optimization and quality risk prediction.

The invention provides a polling interval adjustment method, device and equipment based on a time synchronization request. Comprising the following steps: acquiring a synchronization result of a time synchronization request and index values of a plurality of time synchronization indexes; wherein the time synchronization request is a request which is initiated by a network time protocol (NTP) server and is used for calibrating local time; determining a synchronization polling interval adjustment strategy according to the synchronization result and the index values of the plurality of time synchronization indexes; generating a new polling interval according to a polling interval adjustment strategy; and sending a time synchronization request to the NTP server according to the new polling interval, so that the NTP server calibrates the local time. According to the method provided by the invention, the waste of bandwidth and computing resources is reduced, and the time deviation is calibrated in time.

The application discloses a time synchronization method and system based on direct current IRIG-B code time source positioning, and the time source identity of a clock device is determined according to a direct current IRIG-B code containing an identity; the clock device identity of a time report message used by a time-served device is acquired to determine the time source information used by the time-served device; the time deviation of the clock device and the time-served device is acquired; the time synchronization state monitoring result is determined according to the time source identity of the clock device, the clock device identity of the time report message used by the time-served device and the time deviation; and the time synchronization state monitoring result and the time source information are used to generate a total station time synchronization state time service and monitoring topological graph with the total station SCD configuration file acquired in advance as a static data source. Advantage: Convenient for troubleshooting when a time service fault occurs. The time deviation result and the time source information of the total station time-served device can be used for advanced application of total station time synchronization monitoring and fault troubleshooting.

The invention discloses a multi-clock-source dynamic synchronization method and device, equipment and a medium, and relates to the technical field of computers. Comprising the following steps: packaging a plurality of heterogeneous clock sources into a plurality of clock source objects with a unified management interface and a data structure, and acquiring source time data and corresponding quality attribute data of the plurality of clock source objects by utilizing the management interface; dynamically evaluating the clock source objects based on the quality attribute data and a preset initial evaluation period by using a preset quality evaluation model to generate a real-time quality score, and determining a current reference clock source from the plurality of clock source objects; and determining a time deviation between the system clock and the source time data provided by the current reference clock source, and selecting a corresponding time synchronization strategy based on the time deviation so as to synchronize the system clock to the current reference clock source based on the time synchronization strategy. Therefore, dynamic clock source quality evaluation and clock synchronization can be realized in a multi-clock-source environment.

The invention relates to the technical field of internal clock correction of an intelligent fusion terminal, in particular to a self-adaptive clock synchronization method for the intelligent fusion terminal, which comprises the following steps: S1, acquiring a plurality of clock synchronization sources and corresponding quality characteristic parameters thereof; s2, calculating a corresponding comprehensive quality score, and selecting a clock synchronization source with the highest comprehensive quality score as a main clock source; s3, calculating the time deviation between the internal clock of the intelligent fusion terminal and the main clock source, and if the time deviation exceeds a deviation threshold value, correcting the internal clock of the intelligent fusion terminal through the main clock source; s4, calculating a clock drift rate between a current corrected value and a previous corrected value of the internal clock of the intelligent fusion terminal, if the clock drift rate exceeds a drift rate threshold value, triggering main clock source switching, and returning to the step S2; and S5, periodically executing the step S2, and dynamically updating the main clock source. According to the invention, the flexibility, reliability and stability of clock synchronization of the intelligent fusion terminal can be improved.

The invention relates to the technical field of rotating machinery fault detection, and discloses a centrifugal machine unbalance double-threshold collaborative detection method and a corresponding system. According to the method, a load mass distribution state real-time monitoring sequence of a centrifugal machine rotor is constructed, and dynamic reference data sets matched with different mass distribution modes are established according to the sequence and comprise a vibration characteristic baseline spectrum and a rotating speed fluctuation tolerance interval. Performing point-by-point comparison on vibration and rotating speed signals collected in real time and a dynamic reference to generate a real-time deviation track; and carrying out multi-time scale analysis on the trajectory, and extracting and fusing short-term deviation characteristics and long-term deviation trends to form a comprehensive deviation index. The core innovation lies in that the index is input into a quick response and confirmation verification dual-threshold channel in parallel, and a final imbalance judgment signal is generated only when the outputs of the two channels meet trigger conditions at the same time. According to the method, the accuracy and robustness of judging the unbalanced state of the centrifugal machine are improved.

The invention discloses a loopback test module data flow monitoring method and system, and belongs to the technical field of computers. The method comprises the following steps: intercepting an original data stream at a loopback sending end bypass, generating a sending end characteristic fingerprint with a fixed length, associating the sending end characteristic fingerprint with a sending clock label, and writing the sending end characteristic fingerprint into an asynchronous ring buffer area in sequence; intercepting a return data stream in a loop-back receiving end bypass, generating a receiving end feature fingerprint by adopting the same algorithm, and capturing a receiving clock label; the matching engine determines a sliding window range based on a receiving clock label and a preset time delay parameter, reads a plurality of sending end feature fingerprints in a window in parallel, and compares the sending end feature fingerprints with receiving end feature fingerprints after effective screening according to time deviation; and if yes, judging that the operation is normal, otherwise, starting an exception handling process. According to the method, through feature fingerprint compression storage and an asynchronous ring buffer and sliding window parallel matching mechanism, low-resource-overhead, non-intrusive and high-real-time data flow monitoring is achieved, and the method effectively adapts to a high-speed loopback test scene.

A training method of a marketing prediction model for eliminating time deviation and a precision marketing method relate to the technical field of data processing, samples are grouped by setting time stamps and marketing scheme stamps, experimental samples and contrast samples in the same time group are ensured to be comparable in average value, and the accuracy of marketing prediction is improved. Therefore, the time deviation problem when historical samples are adopted is eliminated, meanwhile, purchase rate target pre-training is carried out on the model to solve the problem that high-latitude features cannot be effectively utilized due to the fact that the unbiased sample size is small, and finally the overall loss is calculated in a multi-task training mode, so that the accuracy of the model is improved. The marketing prediction model can achieve better prediction accuracy under the condition that biased samples and a small number of unbiased samples are adopted, so that the sampling cost caused by only using the unbiased samples is greatly reduced, and both the cost and the effect are achieved. By using the marketing prediction model, accurate putting of marketing schemes can be further realized, and the marketing prediction model has a good practical value.

The application discloses a kind of to time data processing method and system, it is related to data processing technical field, the method includes: based on local environment data, acquisition acquisition cycle, collect high-precision time data and local perception data;Data characteristics of the same batch crystal are analyzed, and based on the high-precision time data and the local perception data, obtain time deviation;Based on the data characteristics analysis rationality of time deviation, obtain rationality analysis result, adjust the acquisition cycle, obtain optimized acquisition cycle;Based on the local environment data is combined mapping table to obtain correction value, and based on the time deviation and crystal data characteristics and the mutual influence correlation of time deviation, the mapping table is dynamically revised, to obtain revised mapping table, for the time data processing of next cycle.The application solves the technical problem that the prior art exists and time data processing effect is not good.

The invention belongs to the field of precise time synchronization, and discloses a precise time protocol-based time synchronization method and a related system, which adopt a timestamp calculation mechanism between a master node and a slave node in the traditional PTP and introduce a multi-message sampling and normalized clustering analysis mechanism. Through extraction, calculation and normalization of sending and receiving timestamps in a plurality of message sampling periods, time deviation fluctuation caused by network jitter, asynchronous delay, random message congestion and other factors can be effectively eliminated, so that clock synchronization is more stable and accurate. According to the method, on the basis of calculating the clock skew and the link transmission delay, K-means residual error clustering optimization is further introduced. By grouping and clustering the time offset or the link delay data, abnormal deviation data and network burst delay data can be automatically identified, so that the robustness of synchronization parameter estimation is improved.

The invention relates to the technical field of water-turbine generator sets, and discloses a water-turbine generator set key frequency modulation parameter optimization method, system and device, a medium and a product. Minimizing the average absolute error, the power peak time deviation and the peak power deviation of the real-time active power recording and the simulation active power recording of the water-turbine generator set is taken as an optimization target, and the optimization target is optimized and solved in combination with the limit value constraint of the frequency modulation parameter, so that the frequency modulation parameter corresponding to the minimum result value of the optimization target is obtained; therefore, the frequency modulation parameter can be quickly identified and updated under the frequency modulation response of the water-turbine generator set, and the frequency modulation response error can be reduced.

The invention provides a super-large scale metering device layered clock synchronization method based on working condition adaptation, and the method comprises the steps: if the deviation between a fused reference time value and a local clock exceeds a preset deviation threshold value, carrying out the layered clock synchronization based on a grouped working condition cluster, a differential time signal distribution protocol is generated in combination with a hierarchical communication architecture from a top-layer high-precision time server to a middle-layer region coordinator to a terminal metering device; sending a time signal to the terminal equipment through the adjusted distribution protocol, monitoring the clock skew degree of a receiving end, and judging whether the skew is within a preset acceptable range; if the deviation is within an acceptable range, applying the signal to perform clock synchronization, and if the deviation exceeds the range, activating standby time source switching according to a preset priority to obtain an effective signal after switching; and according to the switched signal, calculating time deviation, applying a Kalman filtering deviation correction model, fusing local sensor data to carry out iterative correction, and determining a corrected time value.

The invention discloses a power load prediction method based on polymorphic data fusion. Comprising the following steps: S1, acquiring multi-source heterogeneous driving data in a target prediction area; s2, performing data treatment and feature engineering processing on the multi-source heterogeneous driving data, and constructing a model training sample set containing multi-dimensional state information; s3, mining a nonlinear mapping relationship between the multi-source heterogeneous driving data and load change to form a fusion prediction engine with a multi-task output capability; s4, generating a multi-granularity prediction result based on the real-time environment state input of the to-be-predicted time period; s5, performing intra-day rolling correction on the multi-granularity prediction result based on a load measured value acquired in real time and ultra-short-term meteorological update data, and generating a scheduling decision auxiliary signal; according to the method, the deep neural network is used as a fusion engine, and a rolling correction closed loop of real-time deviation feedback is combined, so that high-precision, structured and dynamic self-adaptive prediction of the power load is realized.

The invention provides a power load prediction method and device based on order driving, a medium and a product, and the method comprises the following steps: obtaining historical power load data and production business data corresponding to a target time period, the production business data comprising an order material list and a workshop production scheduling plan of a manufacturing execution system; according to the process operation time window and the equipment energy consumption reference, constructing a pre-scheduling production feature sequence aligned with the historical load time; generating a time sequence input tensor through multi-dimensional splicing, and inputting the time sequence input tensor into the recurrent neural network model to obtain an initial predicted value; and monitoring the time deviation between the actual production progress and the production scheduling plan in real time, correcting the feature sequence based on the actual progress and inputting the model again when the deviation exceeds a threshold value, and outputting a corrected predicted value. By implementing the technical scheme provided by the invention, dynamic coupling of load prediction and production rhythm is realized, and the prediction precision is remarkably improved.

The application discloses a power grid time frequency real-time correction method and system based on dynamic monitoring, comprising: capturing a continuous timestamp sequence from a power grid node, obtaining a time deviation signal; using an adaptive dispersion compensation algorithm to process the time deviation signal, obtaining a restored time frequency characteristic; through feature comparison, obtaining a parasitic interference index from the restored time frequency characteristic; if the parasitic interference index exceeds a preset interference threshold, processing the restored time frequency characteristic through a parasitic component suppression filter to obtain pure main frequency data; according to the comparison between the pure main frequency data and the time deviation signal, obtaining an adjustment instruction sequence; and according to the adjustment instruction sequence, performing real-time correction on the power grid time frequency. Through the fusion of multi-stage sampling, dispersion compensation and closed-loop control, the application significantly improves the power grid time synchronization accuracy and stability, effectively suppresses parasitic interference, and realizes real-time correction.