3945results about "Electromagnetic transmission" patented technology

The invention provides an optical fiber communication equipment monitoring method and system based on big data and a medium, and belongs to the technical field of optical fiber communication and big data. The method comprises the following steps: synchronously acquiring operating parameters and environmental parameters of optical fiber equipment through a multi-source sensor network, and generating a standard parameter information matrix through space-time alignment and noise suppression; further extracting characteristics such as an optical signal stability index and vibration energy anomaly through time-frequency domain conjoint analysis, and constructing an equipment health state matrix; and predicting a degradation process based on a bidirectional LSTM model of an attention mechanism, and outputting a visual diagnosis result in combination with a dynamic threshold grading alarm mechanism. According to the scheme, the problems of high false alarm rate and insufficient prediction capability of a traditional monitoring method are solved, the false alarm rate is reduced, and the fault prediction accuracy is improved.

The invention discloses a long-distance communication optical cable fault automatic detection and positioning system and method, and the method comprises the steps: collecting optical signal data in an optical fiber link in real time through the deployment of a multi-optical fiber sensor or a distributed optical fiber sensing technology; denoising processing is carried out on the collected data, abnormal fluctuation is analyzed by applying a self-adaptive algorithm, and the type of a fault which is about to occur is identified; classifying the faults by using a machine learning classification algorithm; time domain reflection and wavelength multiplexing technologies are combined, a composite algorithm is adopted to accurately position a fault point, and path optimization and error correction are carried out through sensing node data comprehensive analysis; an environment compensation algorithm is introduced, influences of environment factors on the optical signals are analyzed in real time, and errors are eliminated; and based on a fault positioning and analysis result, an AI algorithm is adopted to evaluate a fault influence range, a repair scheme is automatically generated, and priorities are scheduled for repair.

The invention discloses an optical transmission network hidden danger detection method and device and a computer program product, which can realize dynamic adjustment of differentiated bandwidth requirements by acquiring optical network state information in real time, evaluating service priority and establishing an optical channel resource allocation model. And when a topology anomaly is detected, constructing a service quality evaluation model by using a long-short-term memory neural network, and quantitatively analyzing the influence of the anomaly on the service. When a fault occurs, distributed link fault detection and a fault diagnosis engine based on a decision tree are adopted, and fault hidden dangers are quickly positioned and classified. And then, through an elastic recovery mechanism oriented to service sensitivity, the service quality level of a standby optical path is adjusted, and an optical layer topology connection relationship is optimized. According to the method, the resource utilization efficiency, the fault recovery capability and the service quality of the optical network are remarkably improved, and an innovative solution is provided for intelligent optical network management.

The invention relates to the technical field of communication, and discloses an optical fiber performance automatic test method, system and device based on optical power detection. The method comprises the following steps: carrying out intelligent scanning detection on an optical fiber network, generating optical fiber resource mapping data, obtaining an OTDR measurement configuration table through dynamic analysis, executing optical pulse injection and signal acquisition to obtain a time domain response characteristic curve, obtaining an optical fiber performance parameter set through wavelet denoising and peak value identification processing, and obtaining the optical fiber performance parameter set. And performing fault analysis by using deep learning and expert rules to obtain diagnosis decision data, and finally generating an optical fiber state evaluation report through digital twin modeling. According to the invention, remote automatic testing, intelligent fault diagnosis and visual monitoring management of the optical fiber network can be realized, and the operation and maintenance efficiency and reliability of the optical fiber communication network are improved.

The invention provides a port communication optical cable route detection method and system based on digital twinning. Wherein a high-precision digital twinning model of a port environment and communication optical cable distribution is constructed, consistency is ensured, and a high-precision digital twinning environment is generated; based on the high-precision digital twin environment, predicting performance reduction or fault conditions of the communication optical cable by adopting a long short-term memory network, and generating a potential fault prediction report; based on the potential fault prediction report, searching an optimal inspection path in the high-precision digital twin environment by applying an ant colony algorithm, and generating an optimized inspection path and an inspection task list; and on the basis of the optimized inspection path and the inspection task list, guiding actual inspection and evaluating prediction precision so as to improve operation and maintenance efficiency and system reliability. According to the technical scheme provided by the invention, the communication optical cable state can be monitored, accurately predicted and effectively managed in real time, so that the reliability and the operation and maintenance efficiency of a port communication system are improved.

The embodiment of the invention discloses an optical module health state detection method and device, a storage medium and a program product. The method comprises the following steps: extracting time sequence features from time sequence data of an optical module, and extracting key features from system log data of the optical module; fusing the time sequence features and the key features based on the constructed hybrid model, and generating fused features to obtain a current health degree score of the optical module; collecting a historical health degree score of the optical module in a preset time range; detecting at least one environmental parameter of the environment where the optical module is located; obtaining a dynamic threshold value of the optical module based on the historical health degree score and the environmental parameters; and judging the health state of the optical module based on the relationship between the current health degree score and the dynamic threshold. According to the method, the health state of the optical module can be comprehensively, accurately and efficiently evaluated based on multi-dimensional data features, powerful support is provided for operation and maintenance management of the optical module, and the method is of great significance in guaranteeing service continuity and reducing operation and maintenance cost.

The invention relates to the technical field of network service testing, in particular to a testing method and system based on optical fiber characteristics. The method comprises the following steps: acquiring multi-dimensional optical fiber characteristic data of an optical fiber link through optical fiber characteristic acquisition equipment; performing characteristic data hierarchical integration on the multi-dimensional optical fiber characteristic data to obtain an optical link characteristic vector group; performing temperature-error code wavelet transform association according to the optical link feature vector group to obtain a temperature-error code wavelet feature set; constructing an association prediction matrix according to the temperature-error code wavelet feature set; performing a service delay exception test according to the association prediction matrix to obtain a delay tail exception event set; and performing micro-bend three-dimensional feature recognition according to the delayed tail abnormal event set to obtain micro-bend mode features. According to the invention, the operation and maintenance efficiency, reliability and toughness of the optical fiber network of the data center are improved through full-link test analysis from optical fiber physical characteristics to storage service delay.

The invention relates to the technical field of optical fiber communication, and discloses an optical fiber connector optical loss automatic detection method, device and equipment, and the device comprises a modulation signal dynamic adjustment module, an environment parameter adaptive calibration module and a deep learning prediction model. The modulation signal dynamic adjustment module enhances the separability of optical fiber signals through dynamic phase modulation, and the detection precision is improved; the environmental parameter self-adaptive calibration module compensates the influence of temperature, humidity and vibration on optical signals in real time, and the stability of the system is improved; the deep learning prediction model is based on multi-dimensional data fusion and weight dynamic optimization, high-precision prediction of the performance degradation trend of the optical fiber connector is achieved, closed-loop logic from data collection to real-time prediction is formed, experiments show that the detection precision of the method can reach 99.2%, the prediction accuracy is improved to 93% or above, the optical loss calculation error is reduced to 1%, and the method can be widely applied to the field of optical fiber connectors. And meanwhile, the response speed is increased to millisecond level. The method is suitable for monitoring and predicting the optical fiber performance in a complex environment, and the precision and the real-time processing capability are remarkably improved.

The invention relates to the technical field of optical cable intelligent monitoring, in particular to an optical cable intelligent monitoring method and system based on digital twinning. The method comprises the following steps: obtaining optical cable line design data, querying distribution structure characteristics of an optical cable line, collecting optical cable composition material data, constructing an optical cable operation simulation model based on the data, and detecting an optical cable external load coupling stress effect. Monitoring the evolution characteristics of the optical cable structure loss according to the stress effect and the structure degradation; on the basis of optical cable structure loss evolution characteristics, the optical fiber transmission bandwidth limitation condition is evaluated, the signal attenuation aggravation condition is detected, and the abnormal condition of optical cable communication quality is determined by combining the data; the optical cable operation abnormal condition is evaluated, the abnormal defect position of the optical cable is positioned, and real-time early warning is realized through optical cable operation fault monitoring and data uploading to an optical cable intelligent monitoring cloud platform; the optical cable state is monitored and early warned, so that the optical cable transmission is more stable and efficient.

The invention discloses an optical cable fault positioning method based on an OTDR (Optical Time Domain Reflectometer), and relates to the technical field of optical cable fault positioning. Periodic waveform data of an optical cable is acquired through OTDR equipment, an echo spectrum is generated, a dynamic threshold algorithm is introduced according to the echo spectrum to carry out fault event identification, and a dynamic threshold value is generated; the processing end judges whether a fault point area exists in the echo based on the dynamic threshold value, if yes, the distance between the fault point and the OTDR equipment is calculated through propagation time delay, the spatial position of the fault point is determined, and after multiple fault points are recognized, fault types are classified according to reflection intensity. According to the positioning method, a dynamic threshold algorithm is introduced, so that the system has adaptive capacity to background environment change, the robustness of the system under long-distance, high-loss optical cable or severe noise conditions is remarkably enhanced, and weak reflection fault or hidden fault events neglected by a traditional method can be effectively identified.

The invention discloses an optical fiber passive voltage and current fault diagnosis method, device, equipment and medium, and relates to the technical field of fault diagnosis, and the method comprises the following steps: generating and transmitting a test signal at a transmitting end of an optical fiber communication system, converting the test signal into an electric signal, and carrying out the time domain and frequency domain analysis of the electric signal; performing feature extraction on the electric signal based on a multi-dimensional analysis algorithm to obtain an electric signal multi-dimensional feature data set; monitoring data and fault historical data corresponding to the multi-dimensional feature data set are acquired, a fault evaluation model is constructed, and a fault evaluation coefficient is generated; and obtaining the fault evaluation coefficient of each part of the power transmission line at the same time interval within a period of time, and if the difference value of the maximum and minimum fault evaluation coefficients of each part is greater than a preset threshold value, carrying out monitoring. According to the invention, the early warning of the fault is realized, the fault can be rapidly positioned when the fault occurs, and the reliability and stability of the system are effectively improved.

An apparatus (100) for detecting an Electro-Magnetic, EM, field, said apparatus comprising a: Rydberg-Atom EM Field Detector (107), RAEM-FD, configured to detect an EM field (170) of a given frequency; and Multi-Plate WaveGuide (105), MPWG, comprising: at least three overlapping and non-intersecting plates (180); and at least two waveguides (190), each formed by an adjacent pair of the at least three plates, and wherein each waveguide has a separation distance suitable (h) for supporting propagation of the EM field; and wherein the MPWG is arranged so as to direct the EM field towards the RAEM-FD.

The invention discloses an optical fiber fault detection system and method based on an optical time domain reflectometry (OTDR) technology. According to the method, reflected signals are collected through an OTDR detection module, the signals are decomposed, denoised and reconstructed through wavelet transform, high-frequency noise is removed, key features are reserved, then the processed signals are input into a convolutional neural network (CNN) model for feature extraction and classification, and automatic fault type identification and accurate position positioning are achieved. Wherein in the positioning of the fault point, the threshold value adopts a dynamically adjustable threshold value. The system comprises a light source module, a circulator, an optical fiber to be detected, an OTDR detection module and a data processing module, the light source module emits dual-wavelength light pulses to solve the problem of short-distance blind areas of a traditional OTDR, and the complex environment adaptability is enhanced in combination with a dynamic threshold algorithm. Through intelligent fusion of wavelet transform and CNN, the signal denoising capability, the fault detection precision and the automation level are remarkably improved, the manual analysis cost is reduced, and the high-precision and real-time detection requirements of a modern optical fiber network are met.

The invention relates to the technical field of communication engineering, in particular to a communication optical cable line intelligent inspection fault point rapid positioning method and device, and the method comprises the steps: obtaining optical cable line state data, constructing an intelligent fault detection model, recognizing an abnormal signal through wavelet transform and a threshold determination method, training an LSTM neural network in combination with historical fault data, and pre-judging a fault type. When a fault is detected, an unmanned aerial vehicle inspection unit is triggered, an inspection path is planned based on an improved Dijkstra algorithm according to the fault type and suspected fault area geographic information, an optical cable line is scanned and detected through a laser radar, physical fault features are recognized through a YOLOv5 algorithm, and geographic coordinates of a fault point are calibrated in combination with an inertial navigation system; and fusing sensor data and a detection result, evaluating a fault confidence level by adopting a DS evidence theory, and generating an alarm work order. Therefore, the problems of long positioning time consumption, high omission ratio, difficulty in distinguishing fault types and the like in the prior art are solved.

The invention relates to the technical field of optical cable fault positioning, in particular to an optical cable fault positioning method and system and a storage medium. The method comprises the following steps: constructing an optical cable operation link topological graph by obtaining optical cable communication link operation data and combining optical cable transmission line distribution conditions and operation transmission link parameters; according to the abnormal trend data of the transmission signal of the optical cable and the link topological graph, measuring abnormal transition gradient distribution data of the link, and further detecting the abnormal state of the dynamic operation jump point of the optical cable; according to a detection result, analyzing abnormal data of an optical cable operation jump point structure, and identifying an optical cable transmission load imbalance condition; the optical cable operation performance degradation trend is predicted by evaluating the unbalanced load, finally, optical cable fault type division is performed, fault positioning processing is performed on a link topological graph, and optical cable fault positioning data is obtained; according to the invention, the optical cable fault is positioned, so that the optical cable fault identification is more accurate.

The invention discloses a distributed computing task non-perception migration method and system under optical fiber network interruption. The distributed computing task non-perception migration method comprises the following steps: constructing a distributed task migration system and an output system architecture; collecting network state indexes, constructing a network topological graph, and analyzing the state of an optical fiber link for fault prediction; obtaining a calculation task operation state, establishing a sub-task mapping relation, constructing a directed dependency graph, and generating a state snapshot; analyzing resource requirements, reserving standby resources, and deploying a distributed cache system; analyzing a fault influence range, extracting an influenced calculation sub-graph, and selecting a migration target node; in a target node preloading environment, reconstructing an execution context, and redirecting a communication path; and setting a data change capture mechanism, synchronizing incremental data and executing consistency verification. According to the method, non-perception migration of the computing tasks is realized, task continuity and data consistency are guaranteed, and the reliability of the distributed computing system in an optical fiber network fault scene is improved.

The invention discloses a planning method and system of a power distribution communication access network, particularly relates to the technical field of power distribution communication network dynamic topology management, and is used for solving the problems of fault misjudgment and inaccurate positioning caused by topology update delay in the prior art. A dynamic topological data set is generated by dynamically monitoring the operation state of each optical fiber node and a link transmission signal, a real-time topological view with a dynamic version identifier is generated based on a preset topological planning strategy, and a network change area is quickly locked by combining a topological difference identification technology of an alarm moment and a historical view. Candidate fault links are screened through the conflict relation between link switching frequency and service priority, and the vibration characteristics of the construction machinery are further analyzed by using distributed acoustic sensing data and external force damage interference is eliminated; and finally, optical cable breakage faults are confirmed through optical power interruption verification, heartbeat signal loss detection and redundant optical fiber phase mirror symmetry verification. And multi-dimensional accurate positioning of the topological data fault root cause is realized.

The invention provides a state detection method and system for an OPGW optical cable, and relates to the field of OPGW optical cables, and the method comprises the steps: obtaining a test state data set of the OPGW optical cable corresponding to different test environments through finite element analysis; key state factors and key environment factors corresponding to different optical cable states are determined through a genetic algorithm and a variational mode decomposition algorithm according to the test state data sets of the OPGW optical cable corresponding to different test environments; establishing a state detection model according to the key state factors and the key environment factors corresponding to different optical cable states; obtaining a state data set and an environment data set of the current OPGW optical cable; extracting a state feature set from the state data set and the environment data set of the current OPGW optical cable according to the key state factors and the key environment factors corresponding to different optical cable states; through the state detection model, the real-time state of the current OPGW optical cable is determined according to the state feature set, and the method has the advantage of improving the accuracy of state detection of the OPGW optical cable.

The invention discloses an intelligent optical cable monitoring system and method, and belongs to the technical field of optical cable fault monitoring, and the method specifically comprises the steps: collecting optical cable related data in real time, including temperature and humidity, pressure and vibration, carrying out the preprocessing of the collected optical cable related data, extracting the features of the preprocessed optical cable related data, including frequency domain features and instantaneous frequency, combining the health assessment result of the optical cable power transmission line and the external environment factors to establish an optical cable fault identification model, judging the abnormal condition and the abnormal type of the optical cable, and predicting the fault condition of the optical cable in the preset time; through real-time analysis of various parameters such as transmission data, environmental changes and health states of the optical cable, abnormal conditions in the operation process of the optical cable are found in time, early warning is given out, state changes of the optical cable can be quickly responded, potential fault hidden dangers can be recognized in advance, and the safety of the optical cable is improved. And in the face of complex environment change, load fluctuation and health state change, the evaluation capability can be adaptively adjusted in real time.

The invention relates to the technical field of optical fiber communication, in particular to a digital twin model parameter updating method applied to an optical cable. The method comprises the following steps: collecting optical fiber laying data; performing laying structure division based on the optical fiber laying data to obtain flat structure optical fiber data and layer-stranded optical fiber data; evaluating the tensile strength of the optical cable based on flat structure optical fiber data; detecting the optical signal transmission intensity of the flat-structure optical fiber data based on the tensile property of the optical cable; performing intelligent loss compensation on the flat structure optical fiber data according to the optical signal transmission intensity to obtain signal compensation data; calculating the distribution uniformity based on the layer-stranded optical fiber data; determining optical fiber dislocation based on the distribution uniformity to obtain optical fiber dislocation data; and performing optical fiber Brillouin scattering detection based on the optical fiber dislocation data to obtain Brillouin scattering data. The accuracy and real-time performance of optical cable performance evaluation are improved based on the optical fiber communication technology, and therefore the stability and reliability of optical cable signal transmission are remarkably improved.

The invention provides an optical fiber communication line fault feedback system, which relates to the technical field of optical fiber communication fault diagnosis, and comprises a data acquisition module, a feature extraction module, a feedback module and a fault feedback module, according to the method, the attenuation rate, the reflectivity, the packet loss rate, the temperature, the humidity, the vibration signal, the electromagnetic pulse signal and the radio frequency interference signal of the optical fiber communication line are obtained; compared with the prior art, the method comprehensively considers the influence of communication related parameters and environment related parameters, achieves the comprehensive evaluation of the optical fiber communication line, and improves the evaluation accuracy of the optical fiber communication line. Therefore, the accuracy of subsequent fault diagnosis and fault classification is improved.

The invention provides a fault identification method and system for a buried optical fiber, and relates to the technical field of computers, the polarization mode dispersion change rate and the time-frequency double-domain disturbance coefficient of an optical signal of a to-be-detected buried optical fiber can be obtained, and the time-frequency double-domain disturbance coefficient is determined according to the amplitude fluctuation coefficient and the frequency offset of the optical signal; under the condition that the polarization mode dispersion change rate is greater than a preset first threshold value and the time-frequency double-domain disturbance coefficient is greater than a preset second threshold value, acquiring environment state information and physical excitation parameters of the buried optical fiber; inputting the environment state information, the polarization mode dispersion change rate, the physical excitation parameter and the amplitude fluctuation coefficient into a pre-trained micro-bending strain identification model to obtain a micro-bending strain state index of the buried optical fiber; and inputting the micro-bending strain state index, the environment state information and the time-frequency double-domain disturbance coefficient into a preset optical fiber fault classification model to obtain a fault identification result of the buried optical fiber. And fault identification can be carried out on the buried optical fiber comprehensively and accurately.

The invention provides a hollow-core optical fiber cable fiber breakage detection method based on a reference optical fiber and an optical cable, and belongs to the technical field of optical fiber communication. The method comprises the following steps: acquiring monitoring data of a reference optical fiber in a hollow-core optical fiber cable, and performing quality evaluation on the data to generate a signal quality comprehensive score; when the score is higher than a preset threshold value, feature extraction and dynamic weighted fusion are carried out to generate a comprehensive feature vector; outputting a fiber breakage probability by using the fiber breakage state recognition model, calculating a fiber breakage risk value through a prediction model in combination with time sequence data, and obtaining a fiber breakage risk index through a risk fusion algorithm; and finally, matching and executing a hierarchical response strategy according to the risk index. According to the invention, multi-modal data fusion, intelligent state identification and active early warning are realized, and the reliability, precision and operation and maintenance efficiency of broken fiber detection are significantly improved.

The invention discloses an optical cable topology visualization monitoring analysis system and method, and relates to the technical field of optical cable monitoring. According to the optical cable topology visual monitoring analysis system and method, the complex dependency relationship between optical cable network equipment is accurately captured by using the graph neural network, and the wavelength division multiplexing, OTDR test and optical power measurement technologies are fused, so that online monitoring without interrupting service communication is realized, the real-time performance and efficiency of monitoring are improved, the positioning precision of optical cable broken fibers can be improved, and the optical cable topology visual monitoring analysis system and method are suitable for popularization and application. Through new and old OTDR curve comparison and big data analysis, optical fiber aging and degradation trends are pre-judged in advance, accurate active operation and maintenance are realized, the probability of optical cable fault occurrence is reduced, the reliability and stability of a network are improved, and by cooperating with visual display of a complex power grid optical cable map, the method has the advantages of high accuracy and high reliability. The topological structure and the geographic position of the optical cable are visually displayed by fusing multiple levels, clear visual information is provided for operation and maintenance personnel, and management and decision making are facilitated.

The invention provides a network fault node automatic detection and roundabout path planning method, which comprises the following steps of: acquiring optical power and bit error rate of an optical fiber link, and recording abnormal time point and position information; obtaining a strong electromagnetic interference influence weight map; generating a deterioration trend curve; obtaining a health degree score of each optical fiber segment, and generating a health degree distribution map; probability distribution of fault nodes is determined, whether the nodes are fault points is judged according to the probability distribution, and a fault node position set is generated; obtaining a roundabout path planning scheme; and calculating a global network health state perception score to obtain an optimized global network health state diagram. The invention further discloses a corresponding storage medium. According to the invention, the reliability and stability of the optical fiber network can be effectively improved, and the efficiency and accuracy of fault detection and processing can be improved.

The invention discloses a VGA (Video Graphics Array)-based 5G miniature optical transceiver module self-calibration method, which belongs to the technical field of optical transceiver module self-calibration, and comprises the following steps: S1, establishing a self-calibrated benchmark reference value through an initialization module and collecting environment parameters and benchmark optical parameters; s2, dynamically collecting and receiving optical power and environment change data, and judging whether deviation exceeds a threshold value or not to trigger model retraining by collecting actual operation data of environment parameters and driving parameters and combining a neural network model prediction target value; integration of a new data set and re-fitting of a non-linear relation enable the model to continuously adapt to the influence of long-term factors; key parameters such as a gain coefficient or a temperature compensation curve of a proportional-integral-differential control algorithm are dynamically corrected, long-term precision and reliability of a self-calibration system are guaranteed, and the problem of calibration failure caused by failure of a static model is avoided.

The invention relates to the technical field of electric power communication, in particular to an OSU and ASON-based electric power communication network cooperative protection method and system, and the method comprises the steps: dynamically configuring bandwidth resource granularity for different services, and building an electric layer optical service unit protection mechanism; performing lossless bandwidth adjustment on the abnormal service through an electric layer optical service unit protection mechanism to obtain service bandwidth resource adjustment information; configuring main and standby optical paths for various services based on the service bandwidth resource adjustment information, and determining whether to trigger an optical layer protection switching mechanism based on the real-time state of the main and standby optical paths and the protection state of the electric layer automatic switching optical network; and in response to an optical layer protection switching mechanism trigger signal, constructing and solving a photoelectric collaborative optimization model by taking minimization of photoelectric layer switching delay as an optimization target to obtain a photoelectric collaborative optimization protection strategy. By integrating the protection resources of the electric layer and the optical layer, the service can be quickly recovered when the fault occurs, and the continuity and the stability of the power communication network are guaranteed.

The embodiment of the invention provides a cutover event hierarchical judgment method and device based on a graph database, and the method comprises the steps: taking network elements, ports and channels as nodes, inputting the nodes into the graph database, and constructing a directed incidence relation between the nodes according to hierarchical routing data; according to a cutover object of the cutover event, searching a target hierarchy channel associated with the cutover object in a graph database; constructing a routing topological graph of the target level channel, carrying out shortest path search based on the routing topological graph, judging whether a line is interrupted or not and a minimum cutover event combination causing interruption, and obtaining a judgment result of the target level channel; for the target hierarchy channel with the cutover event conflict, upwards searching a corresponding top layer business channel in a graph database; and based on the punching judgment result of the target level channel, judging whether the line of the top layer service channel is interrupted and the minimum cutover event combination causing the interruption, and obtaining the punching judgment result of the top layer service channel.

The invention provides a broadband tunable low-phase-noise photo-generated microwave signal source and device, and relates to the technical field of photo-generated microwaves. According to the invention, a low-frequency optical pulse and a high-frequency microwave signal are respectively input into the electro-optical sampling phase-locked loop; and the electro-optical sampling phase-locked loop determines the synchronization error of the optical pulse and the microwave signal based on the phase difference between the optical pulse center point and the microwave signal zero crossing point. And taking the synchronization error as a feedback signal, and continuously adjusting the frequency and the phase of the microwave signal by the voltage-controlled oscillation module until the frequency and the phase are synchronized with the Nth harmonic of the optical pulse. By setting different initial frequencies of the voltage-controlled oscillation module, microwave signals with different integral multiple optical pulse frequencies can be obtained, and broadband tuning of photo-generated microwave signals is realized. Furthermore, the repetition frequency of the frequency comb is locked through beat frequency of two beams of reference laser and two adjacent comb teeth, the stability of the reference laser is transmitted to the optical pulse, and the stability of the reference laser is further transmitted to the microwave signal through synchronization of the optical pulse and the microwave signal, so that the phase noise of the photo-generated microwave signal source is reduced.