734 results about "Fiber network" patented technology

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 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 a preparation method and application of a composite leakage-proof agent while drilling, and belongs to the technical field of petroleum drilling engineering. The composite leakage-proof agent while drilling is prepared from the following components in percentage by mass: 20-45% of nano composite particles, 15-35% of a multi-stage fiber reinforced network material, 10-20% of an intelligent response blocking agent, 5-10% of a high-temperature-resistant additive, 1-5% of a dispersing agent and the balance of deionized water, wherein the sum of the contents of all the components is 100%. According to the composite leak-proof agent while drilling provided by the invention, the temperature-sensitive resin with a core-shell structure is introduced, so that a three-dimensional synergistic mechanism of nano-composite particle filling-multistage fiber network bridging-intelligent response curing is realized, and efficient and environment-friendly plugging of an ultrahigh-temperature and high-pressure stratum is realized. The success rate of one-time plugging is increased from 45% to 92%, the average operation time is shortened by 60%, and an efficient solution is provided for deep and ultra-deep drilling.

The invention relates to the technical field of electric forklifts and energy storage, and discloses an intelligent battery management system and prediction method based on optical fiber sensing, the system comprises a distributed optical fiber sensing network, a data acquisition and processing module, an intelligent analysis decision module, a battery management control module and a cloud platform interaction module; the method comprises the following steps: collecting a battery signal through a snakelike-spiral optical fiber network, reconstructing a temperature / strain field through noise reduction and filtering, extracting multi-modal features, inputting the multi-modal features into an LSTM model to predict thermal runaway, generating a risk level in combination with an improved equation, dynamically adjusting charging, discharging and heat dissipation strategies, and realizing three-dimensional visual monitoring through a cloud platform. According to the invention, high-precision distributed monitoring of the temperature / strain field of the battery pack is realized through the BOTDR optical fiber sensing network, the LSTM prediction model is constructed by fusing multi-physical field characteristics, and thermal runaway is warned in advance. The improved algorithm reduces the false alarm rate, charging and discharging parameters are dynamically adjusted to prolong the service life of the battery, and a three-dimensional visual platform improves the operation and maintenance efficiency.

The invention discloses an optical fiber line fault detection method and system, and the method comprises the steps: employing broadband light sources at the two ends of an optical fiber in an optical fiber network at the same time, and carrying out the frequency coding of a signal in the broadband light sources, and obtaining an optical signal; collecting optical fiber sensing data; performing multi-mode acquisition on the optical signal to obtain multi-mode optical signal data; preprocessing the multi-mode optical signal data and the optical fiber sensing data to obtain clear signal data; analyzing and fusing the clear signal data to obtain fused data; and inputting the fusion data into a pre-purchased fault identification model, and outputting a fault type. According to the method, through technologies of multi-modal data fusion, high-frequency signal extraction, physical model constraint, feature compression and the like, the problems that the complex fault recognition capability is insufficient and the stability of the model is weakened by environmental interference are effectively solved, and the precision, robustness and generalization capability of optical fiber line fault detection are remarkably improved.

A fiber-optic network that uses as a hybrid telecommunication and sensing system when telecommunication signals and probe signals are transmitted across a shared fiber strand in either a co-propagated or counter-propagated direction is disclosed. Probe signals generated by a sensing termination system and / or by one or more end devices are used to analyze conditions affecting network hardware and / or events occurring within the fiber distribution area.

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 multi-point spectrum confocal measurement method, which comprises the following steps of: transmitting broadband light to an optical fiber light-emitting aperture through an optical fiber network by using a group of broadband light sources to form multi-point irradiation; the broadband light is dispersed through a dispersion lens and is decomposed into dispersion light rays with different wavelengths, and a plurality of groups of dispersion light rays form focused multi-point light beams to irradiate different positions of the workpiece to be measured; receiving reflected light rays from the surface of the workpiece to be detected through at least three optical fiber channels of the multi-channel spectrum analysis device, and analyzing a spectrum signal of each return channel; on the basis of the spectral signals of at least three measurement points, the inclination angle of the plane of the measured workpiece is calculated by adopting the relative height difference between multiple point positions and combining the triangular geometrical relationship with the light path reflection angle; in the whole operation process, the measurement device does not need to be moved, the measurement precision and stability are kept, the method effectively avoids errors caused by a moving shaft in a traditional method, and the measurement efficiency and precision are integrally improved.

The invention relates to a composite phase-change film based on liquid metal and PBO fiber and a preparation method thereof, and belongs to the technical field of phase-change material preparation, and the preparation method comprises the following steps: the composite phase-change film comprises a poly (p-phenylbenzobisoxazole) fiber (PBO) base material, a phase-change material and a heat-conducting filler, the phase-change material is composed of phase-change microcapsules (PM) which are prepared by taking polyurethane (PU) as a wall material and organic solid-liquid phase-change materials (OPCMs) as a core material through a Pickering emulsion polymerization method. The prepared PM has a core-shell structure, and leakage of OPCMs is effectively prevented. The PM and the PBO fiber network are combined, so that the dual packaging of the OPCMs is realized, and the leakage of the OPCMs is further prevented. Meanwhile, dispersion and interaction of the OPCMs in a PBO matrix are optimized, and formation of a network structure with a limited domain is promoted. The composite phase change film prepared by the invention has relatively high mechanical properties, remarkable heat conductivity, excellent and stable flexibility and excellent heat storage capacity.

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 relates to the technical field of optical fiber networks, in particular to an optical fiber network failure judgment method and device based on a feedback decision mechanism, and the method comprises the steps: constructing an optical fiber network, setting an intelligent optical fiber distribution device at an intermediate node of the optical fiber network, and setting a service probe at a tail end node of the optical fiber network; feedback information is obtained; performing multi-source feature extraction on the obtained feedback information, wherein the multi-source feature extraction comprises optical power data feature extraction, OTDR data feature extraction and service probe data feature extraction; and analyzing the extracted multi-source features by adopting a rule-based and model-based dual failure judgment mechanism to obtain a judgment result of the current network state. Therefore, multi-source information fed back by the optical fiber network is comprehensively analyzed by a rule-based and model-based dual failure judgment mechanism, the comprehensiveness, accuracy and efficiency of failure judgment are improved, corresponding repair measures are given according to a fault judgment result of the decision tree model, the response time is greatly shortened, and the network availability is improved.

The invention relates to the technical field of network fault detection, in particular to an optical fiber network fault automatic positioning system and method, and the method comprises the steps: collecting optical signal transmission parameters of an optical fiber link; analyzing the transmission parameters of the received optical signal, and identifying an abnormal reflection signal; determining a fault type and a corresponding fault position by adopting a support vector machine according to the characteristics of the abnormal reflection signal; and matching a corresponding maintenance suggestion based on the fault type and the fault position. According to the automatic positioning method for the optical fiber network fault, efficient and accurate identification and positioning of the optical fiber network fault are realized by integrating a data acquisition technology, intelligent data analysis and a machine learning algorithm, and the efficiency and quality of network maintenance are greatly improved.

The invention provides an optical network communication method and a communication device, the method is applied to an optical fiber network, the optical fiber network comprises a master device and at least one slave device, and the at least one slave device comprises a first slave device. Wherein in the initialization phase, after receiving the authentication encryption capability of the slave device, the master device can indicate a determined authentication encryption mode (e.g., a first authentication encryption mode) to the slave device, so that the authentication encryption capability of the slave device is enhanced in a subsequent process (e.g., a roaming parameter configuration process). The master device does not need to configure security-related parameters such as an authentication encryption mode for the slave device, so that the configuration efficiency is improved, and the configuration overhead is saved.

The invention discloses a panel vertical seam water stop structure repair effect evaluation method, which comprises the following steps of: firstly, synchronously obtaining surface crack and internal defect data through cooperative detection of infrared thermal imaging and ultrasonic flaw detection; and carrying out space alignment on point cloud data generated by three-dimensional laser scanning and an ultrasonic detection result, and establishing a BIM model containing a crack three-dimensional form. A practical engineering environment is simulated in a laboratory to carry out material accelerated aging and test key indexes such as an elastic recovery rate, a base surface state is evaluated through a temperature and humidity sensor array in a construction stage, a six-axis grouting robot is adopted to execute accurate filling, a curing process is monitored by a synchronous pre-embedded optical fiber sensor, and after aging is simulated by combining a hydraulic test with climate, a construction period is shortened. A distributed optical fiber network is used for continuously collecting deformation data, a comprehensive evaluation model is constructed based on mechanics, durability and sealing indexes, and finally material selection and process parameters are optimized through machine learning.

The invention discloses an edge calculation optimization and compression algorithm based on distributed optical fiber sensing data, and the algorithm achieves the full-section continuous monitoring of an embankment through the layering burying of a distributed optical fiber network along the axis of the embankment, and eliminates the blind area of a conventional point sensor. Strain data and temperature data are analyzed by using Brillouin scattering and Raman scattering, time sequence characteristics are analyzed through an LSTM neural network, and piping and crack hidden dangers are identified. External environment parameters such as water level and rainfall are fused to construct a multiple regression model, and the seepage risk level is evaluated. Through combination of BIM three-dimensional modeling and a seepage simulation algorithm, hidden dangers are accurately positioned, and spatial distribution of the hidden dangers is visualized. Based on edge calculation optimization, a data compression technology is adopted to reduce transmission requirements, a self-repairing material injection and high-pressure plugging scheme is triggered through a grading early warning system, closed-loop management from monitoring to repairing is formed, the real-time performance and accuracy of hidden danger recognition are improved, and efficient and reliable monitoring support is provided for dike engineering.

The invention discloses a multi-operator optical fiber network fault diagnosis method and device, equipment and a medium, and relates to the technical field of deep neural networks, and the method comprises the steps: constructing a three-dimensional digital twin model, and carrying out the parameter correction of the three-dimensional digital twin model; acquiring open source library data and operation and maintenance data of a plurality of operators to generate a cross-operator network asset database; respectively deploying the corrected three-dimensional digital twin model to each operator so that the operator can calculate corresponding model training parameters; acquiring all model training parameters, training the graph neural network model based on the model training parameters, and judging whether the trained graph neural network model is converged or not; if convergence occurs, inputting the cross-operator network asset database into the trained graph neural network model to predict an optical fiber network fault point; the fault report and the repair scheme are generated based on the optical fiber network fault points, the accuracy of multi-operator optical fiber network fault diagnosis is improved, and the cross-operator cooperation efficiency and the user experience feeling are improved.

A fiber sensing control device (FSCD) is provided for protecting a network infrastructure in an optical fiber network against intrusive fiber sensing. The FSCD resides on an optical fiber cable at a boundary between the first network segment containing the network infrastructure that is to be protected and a neighboring network segment. The FSCD comprises at least one blocking element that can block sensing of backscattered light on at least one optical fiber of the optical fiber cable.

The invention is suitable for the technical field of toll station management, and provides an expressway toll station remote seat guarding and special situation vehicle handling system, which comprises a front-end sensing layer, a rear-end sensing layer and a control layer, the lane equipment comprises a photoelectric sensor, an infrared height limit alarm, a license plate recognition camera, an ETC antenna, an acousto-optic warning ball and a self-service equipment sensor; the network transmission layer is connected with lane equipment, a sentry box cabinet, a machine room core switch and a monitoring center through an optical fiber network; the remote control layer is composed of a remote seat center, and the remote seat center can carry out video monitoring, visual intercom and remote control; and the abnormity alarm layer is used for carrying out early warning on vehicle detention, vehicle height exceeding, ETC passing faults, toll evasion vehicles and handrail abnormity. The vehicle state can be sensed in real time, data are gathered to a remote seat center through a network transmission layer, an information island is broken, and special conditions can be automatically processed.

The invention discloses an underground gas storage gas monitoring method and system based on optical fiber spectrum analysis. The method comprises the following steps: S1, optical fiber network deployment: arranging a corrosion-resistant optical fiber sensor network in a gas storage; s2, spectral data acquisition: transmitting light with a specific wavelength to a gas chamber at the tail end of an optical fiber through a Fourier transform infrared spectrometer, and acquiring a transmitted spectrum after interaction of gas and light; s3, spectrum decoupling and concentration calculation: based on a peak pattern fitting algorithm of the Lambert-Beer law, decoupling the infrared spectrum characteristics of the mixed gas, matching a standard spectrum database, and calculating the concentration of each gas component; s4, constructing a three-dimensional gas model: according to the position of the optical fiber sensor and the gas concentration data, establishing a gas migration model to predict a leakage position and a movement direction; according to the method, the trend, the component distribution, the concentration change and the potential leakage risk of the gas in the storage are effectively evaluated, and technical support is provided for the safety, the effectiveness and the economical efficiency of operation of the gas storage.

The invention discloses a zirconium-based metal organic framework (Zr-MOF) composite semi-solid electrolyte material prepared based on an electrostatic spinning technology and application of the zirconium-based metal organic framework (Zr-MOF) composite semi-solid electrolyte material. The material is composed of a three-dimensional polymer fiber network, surface-coated Zr-MOF nanoparticles and an organic liquid electrolyte solution, a polymer matrix provides mechanical support, and Zr-MOF micropores and a liquid electrolyte form a multistage ion transmission channel. The preparation method comprises the processes of electrostatic spinning forming, in-situ Zr-MOF synthesis and gradient pressure electrolyte infiltration. The ionic conductivity of the material at 25 DEG C reaches 1.2 * 10 S / cm, the lithium ion transference number is 0.65, the capacity retention ratio after 500 cycles is greater than or equal to 90%, and the material is suitable for high-energy-density lithium ion batteries and flexible energy storage devices through acupuncture safety tests.

The invention discloses an optical fiber network port resource checking method and system based on big data, and the method comprises the steps: collecting the real-time data of a port, obtaining a preliminary data set, extracting key features in the preliminary data set, obtaining the abnormal change of the operation state of the port through the key features, and checking the abnormal change of the operation state of the port. Therefore, abnormal ports are identified and communication quality evaluation is carried out. The contribution degree of rate change to communication quality abnormity is further judged, a high-risk port set is obtained, a data visualization technology is applied to generate a resource checking report, the future bottleneck probability is dynamically updated, and a basis is provided for port resource optimization. According to the method and the system, the abnormal port in the optical fiber communication network can be effectively identified, the potential bottleneck can be effectively predicted, and data support is provided for port resource allocation, so that the network operation efficiency is improved, the port resources are dynamically allocated, and the communication quality is improved.

The invention relates to the technical field of optical transmission, in particular to a high-efficiency optical transmission line protection system and method.A standby transmission line is used for switching to a main transmission line for data transmission when the main transmission line breaks down and has a regular self-checking function; the real-time fault detection module is used for continuously monitoring the optical signal strength and quality of a main transmission line, and automatically triggering a protection mechanism when abnormality is detected; the fault positioning module is used for positioning a fault position of a main transmission line based on a GIS platform to obtain position information; and the alarm module is used for notifying maintenance personnel of the position information. Therefore, all-around protection of the optical fiber network is realized, the stability and the operation and maintenance efficiency of the network are greatly improved, and high quality and high reliability of data transmission service are ensured.

In some embodiments, a fiber optic cable may be monitored while reducing false positives from disturbances in trusted areas. In some embodiments, a system includes a light source, a first remote termination unit in a trusted area, and a second remote termination unit in another trusted area. The light source emits light through the fiber optic cable, which passes through the first remote termination unit, an untrusted area, and then the second remote termination unit. The remote termination units reflect portions of the light back towards the light source. The system uses a prediction model to detect disturbances in the untrusted area based on the reflected light data.

The invention discloses a power distribution communication network fault positioning method and system based on deep learning, and the method comprises the steps: carrying out the fitting processing of obtained time series data of an optical fiber link, and obtaining an actual power attenuation curve; calculating an absolute difference value between the actual power attenuation curve and the theoretical power attenuation curve to obtain standardized difference data; inputting the standardized difference data into a nonlinear attenuation model to obtain nonlinear change characteristic data; inputting the topological characteristic data and the nonlinear change characteristic data of the power distribution network into a fault identification model to obtain a fault probability value of each optical fiber link; comparing the fault probability value with a preset fault probability threshold value to obtain a potential fault link, and performing feature extraction and abrupt change node identification on the potential fault link to obtain attenuation abrupt change node data; and processing the attenuation abrupt change node data, and determining fault point data based on the obtained stress value data. According to the method provided by the invention, the loss fault in the optical fiber network can be quickly positioned.

In some embodiments, local intensity extrema at different wavelengths of a wavelength range reflected across a first cable of a first mode may be determined, the wavelength range being reflected by a second cable of a second mode different from the first mode. Reference locations for sampling windows of the wavelength range may be determined based on the local intensity extrema. A signal reflected across a cable of the first mode may be monitored based on the reference locations for the sampling windows. An activity related to the cable may be detected via a prediction model and based on the monitoring.

Methods and systems are described herein for monitoring fault events at a fiber optical network. In particular, a system may receive, from components of an optical network, corresponding component data structures comprising optical measurements. The system may extract, from a component data structure, a set of component metrics for light transmission signals being transmitted or received via fiber optic transmission lines at a corresponding component and input the component data structure into a first machine learning model to obtain an indication of an occurrence of an event at one or more components. The system may generate a prompt for input into a second machine learning model configured to identify corrective actions for addressing any events within optical networks to obtain one or more corrective actions for addressing the occurrence of the event.

The invention discloses an optical network unit (ONU) and a registration method thereof, and the registration method comprises the following steps: in a standby state, judging whether network parameter setting information broadcasted by an optical line terminal (OLT) is received or not; in response to judging that the network parameter setting information is received, entering a serial number state, and starting timing to generate timing time; in the serial number state, receiving at least one piece of serial number requirement information from the OLT; in the serial number state, when the timing time does not exceed the exploration time and when the serial number requirement information is received each time, a serial number response message is sent out, whether the identification code distribution information is received or not is judged, and the exploration time is not smaller than the time interval of the ONU receiving the serial number requirement information for at least two times; and when the timing time does not exceed the exploration time, responding to the judgment that the identification code distribution information is received, and entering a distance measurement state.

The invention relates to the technical field of spectrum allocation, and discloses a spectrum allocation method applied to a hybrid optical fiber network and a readable storage medium, and the method comprises the steps: building a plurality of spectrum window planes in a modulation format based on the hybrid optical fiber network topology by taking the number of frequency slots required by a to-be-transmitted service as the spectrum width, selecting the shortest path to construct an optical fiber selection scheme, and calculating the transmission cost to select a candidate scheme; and obtaining candidate schemes according to a sequence of modulation format spectrum efficiency from high to low and spectrum window planes from front to back until available routes exist in the obtained candidate schemes, establishing an optical channel, and performing service transmission on the to-be-transmitted service. According to the method, different optical fibers are selected to establish the optical channels, spectrum allocation is more efficiently carried out, the utilization rate and flexibility of spectrum resources are improved, the influence caused by ultra-low loss optical fibers is fully considered, and under the situation of a hybrid optical fiber network, spectrum fragments are reduced, the network blocking rate is effectively reduced, and the network performance is improved.

The invention provides a carbon nanotube modified high-thermal-conductivity and high-strength carbon fiber network body with gradient pore and hierarchical pore characteristics and a preparation method and application thereof, and belongs to the technical field of structure and function integrated composite materials. The preparation method comprises the following steps: blowing carbon fibers and hot-melt polymer fibers into a net through gas to obtain a two-dimensional fiber network body; laying the two-dimensional fiber network body according to the surface density gradient of'low-high-low ', and introducing fibers in the thickness direction for fixing to obtain a three-dimensional carbon fiber network body; sequentially carrying out carbon phase densification and graphitization treatment on the three-dimensional carbon fiber network body to obtain a high-thermal-conductivity three-dimensional carbon fiber network body; and dispersing the high-thermal-conductivity three-dimensional carbon fiber network body into the composite dispersion liquid, and sequentially performing freezing, vacuum drying and magnetic field-assisted induced carbonization to obtain the high-thermal-conductivity three-dimensional carbon fiber composite material. By reasonably designing the pore structure, the mechanical and thermal performance of the carbon fiber network body is improved, and the micro-area heat exchange efficiency of the phase change energy storage composite material is optimized.