775 results about "Clock synchronization" patented technology

The invention discloses a building engineering progress automatic identification early warning system based on computer vision, which relates to the field of building engineering informatization and comprises a synchronous calibration module, a joint calibration module, a pose generation module, a mapping construction module, a resampling module, a mapping registration module and a comparison early warning module. Clock synchronization and rolling readout calibration are carried out on a camera and an inertial measurement unit, a continuous time pose is established in a frame, sampling is carried out according to rows, and an equivalent global shutter frame is generated in combination with plane and pixel-level geometric mapping; outputting a camera pose track and a local measurement map by adopting back-end optimization containing a rolling mechanism, and registering with the building information model; component detection, instance segmentation and state discrimination are completed on an equivalent global shutter frame, pixel domain measurement is unified into engineering quantity under pose and registration constraints, the engineering quantity is mapped to a work decomposition structure and a progress plan, deviation is calculated, and graded early warning is output according to a multi-threshold rule. Long-term stable and reliable operation and evidence traceability of the system are guaranteed through whole-course quality monitoring and threshold grading.

The invention relates to the technical field of intelligent manufacturing decisions, in particular to a digital twinning-based manufacturing system decision analysis method and system, and the method comprises the steps: deploying a plurality of Internet of Things sensors on a physical manufacturing system, and collecting a physical real-time data stream of equipment in real time; the method comprises the following steps: establishing a virtual data acquisition channel aligned with a physical manufacturing system clock, injecting a physical real-time data stream into a digital twinning creation model, and performing data preprocessing based on distributed edge calculation to delay and compress original data acquisition of the physical real-time data stream to 10ms level, the time sequence database and the NTP / GPS clock are synchronized to ensure the state alignment error lt of the physical-virtual system; compared with the prior art, the deep space-time prediction network is fused with a CNN-LSTM-attention mechanism, the accuracy of multivariable coupled KPI prediction is improved, in addition, model failure is recognized in real time through Page-Hinkley inspection, and a prediction error reaches a relatively stable state through an adaptive retraining mechanism.

The invention discloses a multi-mode optical signal transmission method and device, electronic equipment and a storage medium, and relates to the technical field of computers.The transmitted data stream is divided into a control signal and a data signal, the control signal is a visible light wave band, the data signal is an infrared wave band, and the control signal and the data signal are combined to a single multi-core optical fiber through a combiner; the optical network controller allocates subcarrier resources as required according to the change of network flow in a spectrum dynamic allocation mode to perform data transmission, so that the subcarrier resource allocation adapted to the change of network flow improves the dynamic adaptability, and the allocation of the subcarrier resources as required improves the equipment cooperation efficiency, and in the data transmission process, the data transmission efficiency is improved. Clock synchronization and signal encryption are realized through a quantum key distribution mode, and the security is improved.

The invention belongs to the technical field of production monitoring systems, and discloses a numerical control machine tool dynamic fault diagnosis method and system. The method comprises the following steps: generating a global time reference signal through a main shaft encoder and a clock synchronization protocol; the method comprises the following steps: collecting vibration data of a main shaft bearing in each unit time, current data of an electric cabinet and process parameters, and generating a preprocessed data sequence through transmission delay compensation and multi-rate frequency raising processing; inputting the vibration data and the current data into a preset mechanical-electrical transfer function model, and calculating a time delay parameter; performing phase alignment on the preprocessed data sequence based on the time delay parameter to generate an aligned data sequence; inputting the aligned data sequence into a time sequence neural network, and outputting a fusion feature vector; calculating a cross correlation coefficient of the fusion feature vector, and generating a fault diagnosis result based on a preset cross correlation threshold value; the problem of failure of fault feature extraction caused by data asynchronization in the prior art is solved.

The invention relates to the technical field of integrated circuits, and provides a clock domain crossing synchronization circuit and method based on a multiphase clock, and the circuit comprises a selector, an asynchronous clock synchronization module and a digital signal processor. Wherein serial data to be transmitted and a low-frequency clock are input into the selector, and the selector is used for outputting corresponding RX parallel data to the asynchronous clock synchronization module according to the serial data and the low-frequency clock; the asynchronous clock synchronization module is used for outputting corresponding alignment data to the digital signal processor according to the input RX parallel data, the clock of the digital signal processor and the low-frequency clock; the asynchronous clock synchronization module is used for performing phase alignment on the RX parallel data and a clock of the digital signal processor; and the digital signal processor is used for carrying out data processing on the alignment data. According to the invention, stable transmission of low-delay cross-clock domain data can be realized.

The invention relates to the technical field of combustion equipment state monitoring, in particular to a combustion state monitoring method and system based on vibration and noise fusion analysis, and the method comprises the steps: collecting a combustion signal in real time through a vibration sensor and a broadband noise sensor, extracting a characteristic frequency band through noise reduction and filtering, and obtaining a combustion state; fPGA hardware-level clock synchronization is adopted to realize time alignment of bimodal signals, a vibration-noise joint feature matrix is constructed and multidimensional coupling is carried out, a combustion state feature vector is generated through a mixed deep learning model, a combustion state is determined based on a bimodal confidence weighting decision, and a linkage control instruction is generated during interruption. The system comprises a signal acquisition synchronization unit, a feature fusion and modeling unit, a state decision and instruction generation unit and a safety linkage execution unit, executes a method and activates a standby safety system, solves the problems of asynchronous bimodal data and insufficient monitoring precision, and improves the combustion state monitoring accuracy and safety response efficiency.

The invention discloses a multi-mode fusion time service method and system based on dynamic calibration of DCP equipment. The method comprises the following steps: completing initial time reference data acquisition based on a multi-mode satellite signal; meanwhile, time data of a ground time service network are collected, and motion parameters of DCP equipment are monitored in real time through an inertial navigation unit; establishing a correlation model of the motion parameter and the time service error; quantitative analysis of error sources is completed based on the correlation model; fusing the multi-source time data; dynamically adjusting the fusion weight of each data source according to the real-time motion state of the DCP equipment; redundant time slots are automatically distributed to high-error equipment; outputting the calibrated time signal to DCP equipment through an interface to complete clock synchronization; and continuously monitoring the time deviation of the DCP equipment, and dynamically updating the calibration parameters to form closed-loop optimization. And the environmental adaptability and the precision stability of the timing system are improved.

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 relates to the technical field of on-load voltage regulation, in particular to a transformer on-load voltage regulation control method. According to the technical scheme, the transformer on-load voltage regulation control method comprises the following steps that S1, a transformer cluster running in parallel is decomposed into distributed intelligent nodes, and each node executes local voltage prediction and constraint condition management; s2, adopting a distributed model prediction control framework, and cooperatively solving a voltage regulation optimization target through an edge calculation unit; s3, a harmonic disturbance signal with a preset amplitude is injected into the transformer, equivalent impedance is dynamically identified based on response data, and virtual impedance compensation is triggered; and S4, establishing a hierarchical cooperative control architecture, and realizing clock synchronization, dynamic weight distribution and multi-objective optimization decision among nodes. Through a cooperative mechanism of distributed predictive control and dynamic impedance compensation, the response speed and the regulation precision of the on-load voltage regulation system to the power grid voltage fluctuation are remarkably improved, and the voltage out-of-limit problem under the complex working conditions of new energy grid connection, load sudden change and the like is effectively solved.

The invention discloses a pump set vibration monitoring method and system based on distributed sensing. The method comprises the steps that vibration collection signals and real-time working condition parameters of distributed sensing nodes are obtained, multi-node clock synchronization correction is executed, and synchronous vibration data frames are formed; time-frequency feature extraction is carried out on the multi-channel vibration data set, abnormal channels are identified through inter-channel consistency analysis, a local fault correlation frequency band is extracted, and a vibration feature vector is constructed; associating the vibration feature vector with a real-time working condition parameter to form a working condition-feature mapping table, identifying a feature mutation rotating speed point for the feature baseline, adaptively dividing a rotating speed interval to generate an adaptive working condition threshold value, and implementing out-of-limit detection to generate an abnormal trigger identifier; determining a traceability analysis window based on the abnormal trigger identifier, and executing multi-measuring-point coherence calculation and energy attenuation gradient analysis to construct an energy transfer link diagram; and finally, vibration source position positioning is performed to form fault source probability distribution, a fault mode label is matched, pump set vibration monitoring is completed, and quantitative positioning of a fault source is realized.

The invention discloses a cross-chain meteorological and hydrological data consistency verification method oriented to multi-block-chain collaboration, which effectively solves the problem of data alignment caused by inconsistent time standards in a multi-chain environment by collecting multi-source data and generating a data tuple with a geographic identifier and distributing a unified reference timestamp for the data in combination with a physical clock synchronization mechanism. And furthermore, the time deviation is extracted through a layered verification structure and inter-chain cross check, and the timestamp weight is dynamically adjusted, so that the time synchronization precision of the cross-chain data is improved. Finally, a standardized time sequence is generated through segmented aggregation of the data, cross-chain storage is completed, regular backtracking verification is performed in combination with a supervision chain, time consistency and content credibility of the meteorological and hydrological data in the cross-chain circulation process are guaranteed, and efficient collaboration and traceability between heterogeneous block chain systems are achieved.

The invention discloses a wind power generation energy storage load intelligent prediction and power distribution management method, and relates to the technical field of new energy power generation, and the method comprises the steps: generating a clock synchronization signal when a phase gradient quantity exceeds a stable threshold value, correcting the node voltage phase deviation of a power distribution network according to the clock synchronization signal, and outputting a whole network synchronization voltage waveform; inputting an energy storage charging and discharging control instruction into the power flow optimization model, and generating a voltage suppression control vector through a dynamic power deviation compensation algorithm; and extracting stability parameters in the wind power operation data, carrying out weight distribution and state matching on the energy storage charging and discharging control instruction and the voltage suppression control vector, and outputting a cooperative control instruction. According to the method, heterogeneous data such as wind speed, power and voltage are fused into multi-dimensional sequence parameters through a space-time dynamic coupling method, the phase gradient quantity is generated through phase field gradient extraction, a quantitative correlation model of wind speed fluctuation and power grid response is established, and the load prediction accuracy is improved.

The invention provides a signal decoding method based on a PSI5 interface, and relates to the technical field of signal decoding, and the decoding method comprises the following steps: processing and adjusting a received PSI5 signal to obtain an accurate identification signal; and extracting a clock signal from the PSI5 signal, designing a clock compensation algorithm according to the quantum neural network, and dynamically adjusting the clock signal to obtain clock synchronization data. And determining a data frame boundary, and decoding the accurate identification signal to obtain original data. And performing comparative analysis on the original data and the PSI5 signal to obtain comparative difference data, judging whether the comparative difference data accords with a preset error type or not, and performing corresponding processing. According to the invention, fractional calculus processing is carried out on the received signal, then signal distortion is corrected by using a channel equalization method, and the quantum neural network is constructed to dynamically adjust the clock signal, so that clock synchronization is realized, a reliable time reference is provided for accurate processing of the signal, and the accuracy of signal decoding is improved.

This application relates to the field of communication technologies, and discloses a communication method and apparatus. A first communication apparatus receives capability information, where the capability information indicates that a second communication apparatus supports at least one of encrypting or decrypting a first message. The first communication apparatus encrypts the first message to obtain a second message, and sends the second message with a first timestamp, where the first timestamp indicates the sending time of the second message. According to the foregoing method, the first communication apparatus sends an encrypted message (that is, the second message) and the timestamp when the encrypted message is sent to the second communication apparatus, so that encrypted transmission can be performed on a message (for example, a clock synchronization message) that needs to be stamped, thereby improving security of the message transmission.

The invention relates to the field of physiological parameter detection and medical diagnosis measurement, in particular to a multi-mode psychological state quantitative evaluation method and device and a medium thereof. The method comprises the following steps: acquiring multi-source physiological and behavior signals and situation metadata, performing clock synchronization and equipment identifier mapping processing, performing quality feature extraction, artifact detection and slice completion processing, and generating a quality passing fragment set; de-noising normalization, time windowing and feature stack construction, modal gating and attention weighting processing are executed, and unified time sequence embedding is generated; through domain alignment parameter estimation, double-domain drift correction and multi-task inference, a psychological state quantitative index and uncertainty thereof are output; and finally, generating a structured evaluation report and updating parameters through consistency comparison, online self-distillation updating and individual baseline refreshing. According to the method, the anti-interference performance, the individual suitability and the result credibility of psychological state assessment in a natural scene are effectively improved.

The invention provides a digital twinborn monitoring, regulating and controlling method for a copepod bait biological domestication process. The method comprises the following steps: establishing a micro-ecology and population dynamics coupled twinborn model, and defining a monitoring parameter and control object unified term system; collecting multi-source sensing data at an edge end, and performing clock synchronization, signal denoising and state estimation to obtain a micro-ecology, group and water body state joint estimation result; executing parameter online identification based on state estimation, and constructing a safety constraint set of ammonia nitrogen, dissolved oxygen, death rate, environment change rate and the like; the breeding efficiency improvement and the system stability balance are realized through a multi-objective optimization function; and generating a micro-ecological pulse and environment gradual change cooperative control action set according to a solving result, and when a set condition is met, outputting a domestication prescription and terminating the process. Intelligent, low-stress and high-stability regulation and control of a copepod domestication process are realized through digital twin modeling, rolling predictive control and a self-evolution updating mechanism.

The invention discloses an electricity utilization information acquisition device of an electric energy meter metering pulse simulation system, and relates to the technical field of monitoring analysis, and the method comprises the steps: carrying out the ripple disturbance simulation of an initial pulse characteristic data set, and generating an interference pulse waveform matrix; performing multi-source interference signal separation processing on the waveform matrix with the interference pulses, constructing a three-dimensional clock error compensation network, generating a clock synchronization calibration pulse set, and extracting dynamic characteristic parameters corresponding to the clock synchronization calibration pulse set; performing multi-modal data fusion processing on the dynamic characteristic parameters to form compressed pulse characteristic data; establishing a simulation load feature matching model, outputting a simulation load adaptation parameter group, and converting the simulation load adaptation parameter group into a wireless transmission data frame; and carrying out transmission protocol self-adaptive packaging on the wireless transmission data frame, dynamically adjusting a data packaging strategy based on a channel quality evaluation index, and executing remote power utilization information acquisition and transmission. The method has the effect of improving the power utilization information acquisition efficiency.

The embodiment of the invention provides a time-space synchronization method and device, electronic equipment and a medium, which are used for solving the problem of inaccuracy of a local clock in related technologies. In the embodiment of the invention, the electronic equipment combines the average deviation pseudo-range, the RTT jitter and the target frequency offset into the multi-dimensional observation vector, so that the error source of clock synchronization is fully covered. The time deviation and the frequency deviation of the clock are accurately and effectively determined through a Kalman filtering algorithm, recursive processing of observation vectors and dynamic estimation of the time deviation and the frequency deviation of the clock, and high-precision synchronization of the local clock in a complex environment is achieved in combination with the optimization capability of the Kalman filtering algorithm. And the time of the local clock is the time determined according to the time of the multiple clocks, so that the clocks are more accurate.

The invention relates to the technical field of artificial intelligence, in particular to an information interaction method and system for an intelligent robot with a body, and the method comprises the steps: achieving the precise time alignment of multi-source sensor data through a hardware clock synchronization protocol, carrying out the cross-modal feature fusion through a self-adaptive weight distribution mechanism, and constructing a unified environment state expression; analyzing the user instruction in combination with the language model and the dynamic knowledge graph, and generating an execution intention containing environmental adaptation parameters; and generating an action strategy considering a task target and environmental adaptability based on a multi-target optimization algorithm, and converting the action strategy into a control instruction through a hierarchical execution mechanism. The problems that in the prior art, multi-source sensing data synchronization precision is insufficient, and heterogeneous data fusion efficiency is low are effectively solved, and the interaction accuracy, the response speed and the self-adaptive capacity of the robot in the complex dynamic environment are remarkably improved.

The invention relates to the technical field of data processing, in particular to a multi-modal sensor data real-time fusion processing method for a smart community. According to the method, a sensor network topological graph is constructed, a connection weight is optimized, distributed clock synchronization is realized by using a graph Laplacian matrix, and clock drift prediction and compensation are performed in combination with a fractional Brownian motion model; performing wavelet transform decomposition on the sensor data after time sequence alignment, calculating each scale Hurst index, predicting a load trend through a fractal prediction model, and outputting an optimal resource allocation scheme through hybrid evolution calculation; the method comprises the following steps: constructing multi-modal sensor data into a graph structure, extracting node features by using a graph convolutional neural network, obtaining global feature representation by using a self-attention mechanism, and performing anomaly detection classification in combination with a resource utilization rate and a prediction error; an anomaly detection feedback mechanism is established, and Laplacian matrix eigenvalues and weight parameters are dynamically adjusted; the real-time performance, the accuracy and the robustness of data fusion processing are improved.

The invention provides a multi-source clock synchronization method and device based on a long short-term memory network, and the method comprises the steps: collecting multi-source clock signals outputted by a plurality of clock sources, and carrying out the timestamp alignment of the multi-source clock signals; the multi-source clock signals subjected to timestamp alignment are preprocessed; performing feature extraction based on the preprocessed multi-source clock signal to obtain a multi-source clock feature; inputting the multi-source clock characteristics into a double-layer LSTM network obtained by pre-training, and outputting a predicted time deviation result; and performing judgment based on the predicted time deviation result, and performing time compensation on a local clock according to a judgment result. The method can effectively improve the synchronization precision, is more suitable for non-stationary error characteristics in a complex electromagnetic environment, and improves the reliability of clock synchronization.

The invention provides a real-time synchronous control method and system based on an EtherMAC bus, and the method comprises the steps: obtaining an original transmission frame sequence in a bus transmission channel through a monitoring unit; calculating a path topology priority factor and a clock offset compensation value according to a preset topological structure rule; obtaining a to-be-transmitted data frame sequence based on a calculation result, and adjusting a phase synchronization pulse in the monitoring unit to obtain an adjusted phase synchronization pulse; performing redundancy check on the to-be-transmitted data frame sequence to generate a check state code; when the value reaches a preset error threshold value, extracting a to-be-marked frame from the to-be-transmitted data frame sequence, and generating a synchronization signal set containing a high-reliability identifier; generating a real-time synchronization control instruction for driving the execution terminal based on the phase synchronization pulse and the adjusted phase synchronization pulse; according to the technical scheme provided by the invention, real-time monitoring, frame reconstruction and clock synchronization adjustment of data transmission are realized, and high-precision synchronization response of terminal control is improved.

The invention relates to the technical field of cooperative control, in particular to a multi-compartment NVR (Network Video Recorder) state reporting and cooperative control system based on multicast communication, which comprises a state sensing aggregation module, a communication load evaluation module, a cache scheduling release module, a synchronous boundary correction module and a cooperative control configuration module. According to the invention, the node group in the frequently activated state can be identified through the normalization quantization processing of the starting frequency of the video channel in the carriage, the reading of the temperature sensor and the writing rate of the hard disk, and the load evaluation is carried out by combining the message data volume and the channel transmission capability of the node in the historical multicast period. A conflict early warning mark can be formed before a state conflict occurs, correction of time migration among multiple nodes is completed based on comparison of a node receiving timestamp difference value and a clock synchronization tolerance, a control instruction set for time alignment is constructed based on a unified time correction result, a trigger control task is broadcast and executed in a time window packaging mode, and the time correction efficiency is improved. And the communication resource use efficiency is improved.

The invention discloses a power frequency phase adaptive acquisition device, and relates to the technical field of electric power signal measurement, the device acquires electric field data at a gap through an electric field sensor integrated on an edge shell, calculates electric field intensity fluctuation, and generates interference diagnosis information in combination with a preset interference determination threshold value; when the interference diagnosis information shows that effective interference exists, the electric field intensity variable quantity is calculated, a mapping model is established based on a proportionality coefficient obtained through an experiment so as to obtain zero crossing point offset, and the sampling trigger moment of a zero crossing point detection module is corrected; the clock synchronization module calculates a phase difference by taking the corrected trigger moment as a reference, dynamically adjusts a calibration frequency by combining a phase difference threshold value, and outputs a synchronized system clock signal; and the control system takes the synchronized system clock signal as a trigger signal, collects power frequency phase data according to a power frequency period, and stores the power frequency phase data to a database through a transmission unit, thereby realizing high-precision power frequency phase collection.

The invention discloses a vehicle driving simulation test method and system based on digital twinning, belongs to the technical field of vehicle driving, and realizes real interaction of a driving behavior model and a control algorithm in a virtual scene by constructing a digital twinning body highly corresponding to an actual vehicle and a driving environment. Time stamps and coordinate information of all the modules are collected, time differences and space residual errors are extracted, a space-time semantic consistency index model is constructed, and the loading process is intelligently judged and optimized; when inconsistency is detected, adjustment is performed through clock synchronization and coordinate recalibration, a closed-loop optimization mechanism is formed, and high collaboration of the model and the environment is ensured, so that the accuracy, the stability and the credibility of the simulation system are improved, and the method is suitable for complex and changeable automatic driving test scenes.

The invention provides an intelligent control method and system for discrete event simulation of an aluminum template production line, and relates to the technical field of data processing.The method comprises the steps that a material transfer path instruction and a cutting process key point coordinate sequence are analyzed from a dynamic anti-interference scheduling strategy, the key point coordinate sequence is input into a curve driving algorithm, and a curve driving algorithm is obtained; a parameterized continuous cutting path curve is generated according to the aluminum template contour precision requirement and the cutting head dynamics constraint; the method comprises the following steps: performing equal-bow-height error discretization processing on a continuous cutting path curve to generate a discrete pose point set with a timestamp, superposing AGV dynamic constraints to generate a speed look-ahead control instruction set, splitting the instruction set into independent control units according to process sections, packaging the independent control units into a time trigger message through an industrial bus protocol, and sending the time trigger message to a server; and the simulation clock synchronization signal is injected into a physical execution unit. According to the invention, intelligent and accurate control of the aluminum template production process is realized, and the production efficiency is effectively improved.

The invention provides a fault positioning method and system for an overhead line of a power distribution network, and a storage medium. The method comprises the steps of obtaining a plurality of fault traveling wave magnetic field signals; performing the following steps on any signal: performing phase-mode transformation on the signal, extracting and decomposing a line mode component, determining a modulus maximum point, and determining the time corresponding to the point as a first fault traveling wave head arrival moment; carrying out clock synchronization on the moment, and obtaining a wave head arrival moment of a second fault traveling wave; obtaining a to-be-detected fault point and a line parameter; based on the wave head arrival moments of the plurality of second fault traveling waves, extracting a head end arrival moment and a tail end arrival moment; and performing fault positioning on the overhead line of the power distribution network based on the head end arrival time, the tail end arrival time and the fault line parameters. According to the fault positioning method for the overhead line of the power distribution network, interference to normal operation of the power distribution network can be avoided, and high-precision non-intrusive positioning of the overhead line of the power distribution network is realized through the tunneling magnetoresistive sensor.

The invention relates to the technical field of intelligent control, and discloses an intelligent control method for an etching process of a PCB (Printed Circuit Board), which comprises the following steps of: acquiring an image of an object to be processed, generating a discretized virtual load sequence, establishing a virtual shift register synchronized with a feedback pulse trigger clock of a transmission device encoder, driving the virtual load sequence to execute logic displacement of physical displacement phase locking; comparing the theoretical torque with the actual torque to obtain a torque residual error; a dynamic gain correction coefficient is calculated based on the torque residual error, the basic feed-forward gain is weighted and modulated in real time, and a control instruction is generated, and a time sequence error caused by transmission speed fluctuation is avoided by constructing a rigid space-time synchronization architecture based on a virtual shift register; a torque residual error is used as a non-intrusive observation variable, and a gain scheduling mechanism is combined, so that self-adaptive compensation for impedance drift of a controlled medium under the condition of no physical sensor is realized.

The invention relates to an FPGA-based GPR ground penetrating radar electromagnetic signal synchronous high-speed data acquisition system and method. The system comprises a front-end signal processing module, a high-speed ADC sampling module, a clock synchronization control module, an FPGA real-time processing module, a target detection and feature extraction module, a mechanism data storage module and a remote data transmission module. On the engineering safety level, the service life of equipment in a strong electromagnetic environment is prolonged by three times through the multi-stage protection design, and the annual failure rate is reduced to 0.1% or below; an ultra-high-speed sampling system (83.2 GS / s) is combined with femtosecond-level clock synchronization, so that 0.5 mm-level thin-layer structure recognition becomes possible, and a technical foundation is provided for geological disaster early warning; a pioneering photoelectric double-channel transmission mechanism is adopted, the electromagnetic interference suppression is improved by 12dB while the 1ps synchronization precision is kept, and the traditional contradiction between high-speed sampling and signal fidelity is broken.

The invention relates to the technical field of digital audio signal processing, and discloses an audio synchronization multipoint PTS correction method and system, a storage medium and a device, and the method comprises the steps: setting PTS calibration points at a plurality of key nodes on an audio processing link of a master device and a slave device, and carrying out the systematic initialization of an initial PTS value of each calibration point; a clock synchronization mechanism between the master device and the slave device is established, and dynamic calibration of a slave device clock is achieved by periodically interacting time synchronization signals and calculating clock offset; performing multi-stage dynamic adjustment and compensation on the PTS value of the corresponding calibration point according to the network transmission delay fluctuation of the audio frame and the received actual coding duration and time deviation; the filling state and the PTS deviation value of the playing buffer area are monitored in real time, audio output synchronization between the master device and the slave device is maintained through a playing speed fine tuning strategy, optimization is carried out aiming at a lossy coding scene, and the limitation of a traditional single-point synchronization method is effectively solved.