A method and system for managing an optical fiber device

Abstract

The present application provides a fiber optic device management method and system, which relates to the technical field of device management. Signal transmission characteristics and fault causes of fiber optic links in fiber optic devices are extracted from the operating state information of the fiber optic devices. The loss mode of the fiber optic links is analyzed according to the signal transmission characteristics, and a fault feature correlation matrix for evaluating the operating state of the fiber optic devices is determined through the loss mode and fault causes. The operation and maintenance strategy of the fiber optic devices is determined according to the maintenance requirements in the operation and maintenance demand information, and a management relationship graph of the maintenance requirements of the fiber optic devices is constructed through the operation and maintenance strategy and the topological connection relationship of the fiber optic links. A multi-dimensional confidence evaluation is performed on the operation and maintenance management state of the fiber optic devices based on the fault feature correlation matrix and the management relationship graph, and a confidence evaluation result of the operation and maintenance management state of the fiber optic devices is obtained. Further, the operation and maintenance management parameters of the fiber optic devices are adjusted. The present application can realize the dynamic adjustment of the operation and maintenance management parameters of the fiber optic devices, thereby improving the management efficiency of the fiber optic devices.

Description

Technical Field

[0001] This application relates to the technical field of equipment management. More specifically, this application relates to a fiber optic equipment management method and its system. Background Art

[0002] With the wide application of fiber optic communication technology, especially in the fields of data transmission and communication, the management of fiber optic equipment has become increasingly important. The management of fiber optic equipment not only involves equipment monitoring, troubleshooting, and performance evaluation, but also includes network optimization and resource scheduling. Through efficient management, faults in the fiber optic network can be detected and resolved in a timely manner, reducing the system downtime and improving network reliability. In addition, with the promotion of emerging technologies such as 5G and cloud computing, the complexity of fiber optic networks is also increasing continuously, and the role of equipment management has become more prominent. Through an intelligent and automated equipment management system, the operation efficiency of fiber optic networks can be improved, maintenance costs can be reduced, and at the same time, support can be provided for network expansion and upgrade.

[0003] In the prior art, traditional fiber optic equipment management often relies on manual inspection or conventional signal monitoring. This method is difficult to identify potential fault characteristics of fiber optic equipment in real time, resulting in failures not being warned or located in a timely manner, thus increasing system downtime and maintenance costs. In addition, traditional operation and maintenance management methods usually rely on static data or simple status monitoring, and cannot comprehensively evaluate various dynamic changes and potential risks during the operation of fiber optic equipment. This evaluation method not only cannot accurately reflect the true operation and maintenance status of fiber optic equipment, but also easily misses potential fault hazards, affecting the long-term operation and maintenance efficiency of fiber optic equipment. Therefore, how to achieve dynamic adjustment of operation and maintenance management parameters of fiber optic equipment to improve the management efficiency of fiber optic equipment has become a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides a fiber optic equipment management method and its system, which can realize dynamic adjustment of operation and maintenance management parameters of fiber optic equipment, thereby improving the management efficiency of fiber optic equipment.

[0005] In a first aspect, this application provides a fiber optic equipment management method, and the fiber optic equipment management method includes the following steps:

[0006] Obtain the operation status information and operation and maintenance requirement information of the fiber optic equipment;

[0007] Extract the signal transmission characteristics and fault causes of the fiber optic link in the fiber optic equipment from the operation status information, analyze the loss mode of the fiber optic link according to the signal transmission characteristics, and then determine the fault feature correlation matrix for evaluating the operation status of the fiber optic equipment through the loss mode and the fault causes;

[0008] Determine the operation and maintenance strategy of the optical fiber device according to the maintenance requirements in the operation and maintenance requirement information, and construct a management relationship map of the maintenance requirements of the optical fiber device through the operation and maintenance strategy and the topological connection relationship of the optical fiber link;

[0009] Perform multi-dimensional confidence evaluation on the operation and maintenance management status of the optical fiber device based on the fault feature correlation matrix and the management relationship map, obtain the confidence evaluation result of the operation and maintenance management status of the optical fiber device, and intelligently adjust the operation and maintenance management parameters of the optical fiber device according to the confidence evaluation result.

[0010] In this embodiment, a distributed optical fiber sensor is used to collect the operation status information of the optical fiber device.

[0011] In this embodiment, obtain the operation and maintenance requirement information of the optical fiber device from the historical operation and maintenance logs.

[0012] In this embodiment, extracting the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber device from the operation status information specifically includes:

[0013] Extract the operating parameters of the optical fiber link from the operation status information;

[0014] Determine the signal transmission characteristics of the optical fiber link in the optical fiber device through the operating parameters;

[0015] Extract the abnormal data during the operation of the optical fiber device from the operation status information;

[0016] Perform fault analysis on the abnormal data and extract the fault causes of the optical fiber link in the optical fiber device.

[0017] In this embodiment, the operating parameters specifically include signal attenuation rate, noise level, bandwidth, and optical power.

[0018] In this embodiment, analyzing the loss mode of the optical fiber link according to the signal transmission characteristics specifically includes:

[0019] Initialize a loss model;

[0020] Use the signal transmission characteristics as the input parameters of the loss model;

[0021] Analyze the loss mode of the optical fiber link through the loss model.

[0022] In this embodiment, determining the fault feature correlation matrix for evaluating the operation status of the optical fiber device through the loss mode and the fault cause specifically includes:

[0023] Extract the fault features of the operation of the optical fiber device from the operation status information according to the loss mode;

[0024] Associate each fault feature with each interference factor among the fault causes, and then extract the association values between the fault causes and each fault feature during the operation of the optical fiber device;

[0025] Determine the fault feature association matrix for evaluating the operation state of the optical fiber device through all the association values.

[0026] In this embodiment, constructing the management relationship map of the maintenance requirements of the optical fiber device through the operation and maintenance strategy and the topological connection relationship of the optical fiber link specifically includes:

[0027] Determine the topological connection relationship of the optical fiber link according to the physical connection structure and logical connection information of the optical fiber link;

[0028] According to the topological connection relationship of the optical fiber link, map the maintenance requirements in the operation and maintenance strategy to the optical fiber link in the optical fiber device to obtain the mapping parameters of all the maintenance requirements of the optical fiber link;

[0029] Determine the management relationship map of the maintenance requirements of the optical fiber device through the mapping parameters of all the maintenance requirements.

[0030] In this embodiment, performing a multi-dimensional confidence evaluation on the operation and maintenance management state of the optical fiber device based on the fault feature association matrix and the management relationship map, and obtaining the confidence evaluation result of the operation and maintenance management state of the optical fiber device specifically includes:

[0031] Determine the confidence probability of the occurrence of a fault in the optical fiber device according to the fault feature association matrix;

[0032] Determine the credibility of the response ability in the operation and maintenance management of the optical fiber device based on the management relationship map;

[0033] Evaluate the operation and maintenance management state of the optical fiber device through the confidence probability and the credibility to obtain the confidence evaluation result of the operation and maintenance management state of the optical fiber device.

[0034] In a second aspect, the present application provides an optical fiber device management system for executing an optical fiber device management method, and the optical fiber device management system includes:

[0035] An acquisition module for acquiring the operation state information and operation and maintenance requirement information of the optical fiber device;

[0036] A fault feature association module for extracting the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber device from the operation state information, analyzing the loss mode of the optical fiber link according to the signal transmission characteristics, and then determining the fault feature association matrix for evaluating the operation state of the optical fiber device through the loss mode and the fault causes;

[0037] A relationship graph determination module, configured to determine an operation and maintenance strategy for an optical fiber device according to the maintenance requirements in the operation and maintenance requirement information, and construct a management relationship graph for the maintenance requirements of the optical fiber device through the operation and maintenance strategy and the topological connection relationship of the optical fiber link;

[0038] A management parameter adjustment module, configured to perform a multi-dimensional confidence evaluation on the operation and maintenance management status of the optical fiber device based on the fault feature correlation matrix and the management relationship graph, obtain a confidence evaluation result of the operation and maintenance management status of the optical fiber device, and intelligently adjust the operation and maintenance management parameters of the optical fiber device according to the confidence evaluation result.

[0039] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0040] First, obtain the operation status information and operation and maintenance requirement information of the optical fiber device; extract the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber device from the operation status information, analyze the loss mode of the optical fiber link according to the signal transmission characteristics, and then determine the fault feature correlation matrix for evaluating the operation status of the optical fiber device through the loss mode and the fault causes; determine the operation and maintenance strategy of the optical fiber device according to the maintenance requirements in the operation and maintenance requirement information, and construct a management relationship graph for the maintenance requirements of the optical fiber device through the operation and maintenance strategy and the topological connection relationship of the optical fiber link; perform a multi-dimensional confidence evaluation on the operation and maintenance management status of the optical fiber device based on the fault feature correlation matrix and the management relationship graph, obtain a confidence evaluation result of the operation and maintenance management status of the optical fiber device, and intelligently adjust the operation and maintenance management parameters of the optical fiber device according to the confidence evaluation result.

[0041] It can be seen that the present application performs a multi-dimensional confidence assessment on the operation and maintenance management status of the optical fiber equipment based on the fault feature association matrix and the management relationship map, obtains the confidence assessment result of the operation and maintenance management status of the optical fiber equipment, and then intelligently adjusts the operation and maintenance management parameters of the optical fiber equipment according to the confidence assessment result; firstly, by extracting the signal transmission characteristics and fault inducements of the optical fiber link from the operation status information, and analyzing them in combination with the loss mode, it is ensured that the potential failure risks of the equipment can be fully identified. The core of this analysis is to find out the root causes that affect the performance of the equipment by extracting and analyzing the loss mode of the optical fiber link, which provides a scientific basis for fault warning and positioning, avoids the neglect of potential equipment failures in traditional methods, and reduces the downtime and maintenance costs caused by equipment failures; secondly, by analyzing the topological structure of the optical fiber link, a The management relationship map of fiber optic equipment maintenance needs ensures that under different operating conditions, the operation and maintenance strategy can be adjusted according to actual needs. This personalized operation and maintenance strategy helps managers allocate resources more efficiently and avoids resource waste or over-concentration in traditional management methods. Then, through the multi-dimensional confidence evaluation method, the solution can comprehensively consider various factors of fiber optic equipment and accurately evaluate the operation and maintenance management status of fiber optic equipment based on the fault feature association matrix and management relationship map. This evaluation method not only improves the scientific nature of equipment management, but also realizes the intelligent process of automatically adjusting the operation and maintenance management parameters according to the evaluation results. Finally, through the mechanism of intelligent adjustment of operation and maintenance parameters, fiber optic equipment can maintain the optimal operating state in different environments and conditions, reducing the need for human intervention and improving management efficiency.

[0042] In summary, the present application scheme can realize dynamic adjustment of the operation and maintenance management parameters of optical fiber equipment, thereby improving the management efficiency of optical fiber equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0044] Figure 1 is a flow chart of the optical fiber equipment management method provided by the present application;

[0045] Figure 2 is an exemplary flow chart for determining a fault feature association matrix provided by the present application;

[0046] Figure 3 is an exemplary flow chart for determining a management relationship map provided by the present application;

[0047] Figure 4 It is the module structure diagram of the optical fiber device management system provided according to this application. Specific implementation manners

[0048] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0049] The embodiments of this application provide an optical fiber device management method and its system. The core is to extract the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber device from the operation status information of the optical fiber device, analyze the loss mode of the optical fiber link according to the signal transmission characteristics, and determine the fault feature correlation matrix for evaluating the operation status of the optical fiber device through the loss mode and fault causes; determine the operation and maintenance strategy of the optical fiber device according to the maintenance requirements in the operation and maintenance demand information, and construct a management relationship map for the operation and maintenance requirements of the optical fiber device through the operation and maintenance strategy and the topological connection relationship of the optical fiber link; perform multi-dimensional confidence evaluation on the operation and maintenance management status of the optical fiber device based on the fault feature correlation matrix and the management relationship map to obtain the confidence evaluation result of the operation and maintenance management status of the optical fiber device, and further adjust the operation and maintenance management parameters of the optical fiber device. In summary, this solution can realize the dynamic adjustment of the operation and maintenance management parameters of the optical fiber device, thereby improving the management efficiency of the optical fiber device.

[0050] In Embodiment 1, to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners. Refer to Figure 1 As shown, this figure is an exemplary flowchart of an optical fiber device management method according to this embodiment of this application. The optical fiber device management method includes the following steps:

[0051] In step S1, obtain the operation status information and operation and maintenance demand information of the optical fiber device.

[0052] It should be noted that the operation status information in this application refers to the working condition record data generated during the operation of the optical fiber device, which can be used to evaluate the performance, health status and fault risk of the optical fiber device; the operation and maintenance demand information refers to the maintenance, management and optimization requirements required to ensure the stable operation of the optical fiber device, including periodic maintenance, fault handling and resource scheduling data.

[0053] In specific implementation, first, distributed optical fiber sensing can be used to collect the operating status information of the optical fiber device. The operating status information specifically includes: signal transmission parameters, fault and alarm data, device operation logs, and environmental monitoring data. Among them, the signal transmission parameters specifically include: signal attenuation, noise level, bandwidth, optical power (input / output power), and bit error rate; the fault and alarm data specifically includes: optical fiber link interruption alarm, abnormal optical power, too high / low temperature, optical module fault, and bit error overrun alarm; the device operation logs specifically include: port start / stop records, software / firmware upgrade records, maintenance operation logs, and historical fault records; the environmental monitoring data specifically includes: temperature and humidity in the device machine room, power supply voltage, and electromagnetic interference data. Then, the operation and maintenance requirement information of the optical fiber device can be obtained from the historical operation and maintenance logs.

[0054] In step S2, the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber device are extracted from the operating status information. The loss mode of the optical fiber link is analyzed according to the signal transmission characteristics, and then the fault feature correlation matrix for evaluating the operating status of the optical fiber device is determined through the loss mode and the fault causes.

[0055] In this embodiment, the extraction of the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber device from the operating status information can be implemented by the following steps:

[0056] Extract the operating parameters of the optical fiber link from the operating status information;

[0057] Determine the signal transmission characteristics of the optical fiber link in the optical fiber device through the operating parameters;

[0058] Extract the abnormal data during the operation of the optical fiber device from the operating status information;

[0059] Conduct fault analysis on the abnormal data to extract the fault causes of the optical fiber link in the optical fiber device.

[0060] It should be noted that the operating parameters in this application refer to the key indicators for evaluating the signal transmission quality of the optical fiber link. The operating parameters specifically include signal attenuation, noise level, bandwidth, and optical power; the signal transmission characteristics in this application are indicators for measuring the ability of the optical fiber link to maintain the quality of optical signals during signal transmission; the fault causes in this application refer to the factors that cause the performance of the optical fiber link to decline.

[0061] In specific implementation, first, a fiber optic link can be data (signal) collected by using an optical power monitoring module (with built-in distributed optical fiber sensing in the optical power monitoring module) or an optical time domain reflectometer, and then the signal features are decomposed by using wavelet transform. Furthermore, parameters such as signal attenuation, noise level, bandwidth, and optical power are extracted. Additionally, measurement noise in the signal is removed by Kalman filtering before wavelet transform to ensure data accuracy; second, the vector composed of the extracted signal attenuation, noise level, bandwidth, and optical power can be used as a description vector of the signal transmission characteristics of the fiber optic link in the fiber optic device; then, abnormal data is extracted from the operating state information, and a time series anomaly detection method based on a long short-term memory network (LSTM) is used to perform real-time identification of abnormal conditions such as optical power fluctuations and sudden increases in bit error rate to form abnormal data; finally, a support vector machine is used to classify the abnormal data, and the fault causes are analyzed by combining historical fault modes, such as fiber breakage, connector contamination, or optical amplifier failure, and the occurrence probabilities of different fault causes are calculated through a Bayesian network.

[0062] In this embodiment, analyzing the loss mode of the fiber optic link according to the signal transmission characteristics can be implemented by the following steps:

[0063] Initialize a loss model;

[0064] Use the signal transmission characteristics as input parameters of the loss model;

[0065] Analyze the loss mode of the fiber optic link through the loss model.

[0066] It should be noted that the loss model in this application is a mathematical model used to describe the signal attenuation of optical signals during transmission in a fiber optic link. The core principle of the loss model is to predict the transmission effect of optical signals by considering different types of losses (such as absorption loss, scattering loss, bending loss) and combining the physical properties of the fiber itself (such as material, diameter, refractive index); the loss mode in this application refers to the signal attenuation or distortion law caused by various factors in the fiber optic link, manifested as loss characteristics at different frequencies or transmission distances.

[0067] In specific implementation, first, in the stage of initializing the loss model, an exponential decay model or a fiber optic loss model based on ray propagation can be selected, and the attenuation relationship of optical signals in the fiber is set. The attenuation relationship is as (where is the optical power at the transmission distance , is the initial optical power, (where the attenuation coefficient is), and introduce the key factors affecting fiber optic loss, such as fiber type, connection loss, ambient temperature, etc.; then, in the stage of input signal transmission characteristics, parameters such as signal attenuation, bit error rate (BER), dispersion, signal-to-noise ratio (SNR), etc. collected are used as model inputs, and dimensionality reduction is performed using multiple regression analysis or principal component analysis (PCA) to reduce the impact of redundant information on loss calculation; finally, in the stage of analyzing the loss mode of the fiber optic link, a neural network regression model (such as a BP neural network) is used to train the loss model based on historical data, and the fiber optic loss trend under different operating conditions is output through the loss model, and the frequency domain characteristics are analyzed in combination with Fourier transform to identify whether there is a sudden loss mode, such as high-frequency loss fluctuations caused by micro-bending loss or connector contamination.

[0068] In this embodiment, with reference to Figure 2 As shown, this figure is an exemplary flowchart for determining the fault feature association matrix in the embodiment of the present application. In this embodiment, the fault feature association matrix for evaluating the operating state of the fiber optic device can be implemented by the following steps through the loss mode and the fault cause:

[0069] In step S21, extract the fault features of the operation of the fiber optic device from the operation state information according to the loss mode;

[0070] In step S22, map each fault feature to each interference factor in the fault cause, and then extract the association value between the fault cause and each fault feature during the operation of the fiber optic device;

[0071] In step S23, determine the fault feature association matrix for evaluating the operating state of the fiber optic device through all the association values.

[0072] It should be noted that the fault feature association matrix in the present application refers to a matrix structure formed by associating the relationships between various fault features and fault causes during the operation of the fiber optic device, and is used to quantify the mutual relationships between different fault features and their influence degrees on the cause.

[0073] In specific implementation, first, in the stage of extracting fault features, according to the loss mode, by analyzing parameters such as the attenuation, noise, and bit error rate of the optical fiber link, principal component analysis (PCA) is used to extract the main fault features from the operating state information. These fault features mainly include increased signal attenuation, time delay fluctuation, and increased bit error rate. Secondly, the extracted fault features are associated with the fault causes (such as fiber breakage, connector contamination, temperature change), and decision tree algorithm or support vector machine (SVM) is used to establish the mapping relationship between each fault feature and the cause. By training historical data, the influence degree of each cause on the fault feature is obtained, and the average influence degree of each cause on each fault feature is respectively used as the correlation value between the fault cause and each fault feature during the operation of the optical fiber device. Finally, all the correlation values are summarized by the weighted matrix method, and graph theory algorithms (such as weighted adjacency matrix) are used to form a matrix structure of these correlation values, so as to quantify the mutual relationship between different fault features. Through the above solution, a basis can be provided for the subsequent evaluation of the operating state of the optical fiber device, helping to identify potential fault causes and make accurate operation and maintenance decisions.

[0074] In step S3, according to the maintenance requirements in the operation and maintenance requirement information, the operation and maintenance strategy of the optical fiber device is determined, and a management relationship graph of the maintenance requirements of the optical fiber device is constructed through the operation and maintenance strategy and the topological connection relationship of the optical fiber link.

[0075] It should be noted that in this application, determining the operation and maintenance strategy of the optical fiber device according to the maintenance requirements in the operation and maintenance requirement information means formulating corresponding operation and maintenance strategies according to the operation and maintenance requirement information such as the maintenance plan, fault handling requirements, and resource management requirements of the optical fiber device, including measures such as regular inspection, fault response time, resource scheduling, and spare part management to ensure the stable operation of the optical fiber device and minimize the risk of fault occurrence. In specific implementation, first, analyze the maintenance plan of the optical fiber device to determine the inspection frequency of the device, the regular detection of the optical fiber line, and the replacement cycle of key components. For example, perform planned maintenance according to the device usage years, failure rate, and manufacturer's suggestions. Secondly, based on the fault handling requirements, clarify the fault response time requirements and handling processes, and set priorities. For example, formulate a fast recovery strategy for critical link faults and set a longer response time limit for non-critical link faults. Then, according to the resource management requirements, ensure sufficient spare part inventory, and ensure that the maintenance tools and the skills of operation and maintenance personnel meet the device requirements, and optimize the configuration of operation and maintenance resources through an intelligent scheduling system. Finally, based on historical operation and maintenance data, combined with predictive maintenance strategies, use data analysis and machine learning methods to predict the device state, identify potential faults in advance, and adjust operation and maintenance parameters to reduce the probability of sudden faults.

[0076] In this embodiment, refer to Figure 3As shown, this figure is an exemplary flowchart for determining the management relationship graph in an embodiment of the present application. In this embodiment, the management relationship graph of the maintenance requirements of optical fiber devices can be constructed through the operation and maintenance policies and the topological connection relationship of optical fiber links, which can be implemented by the following steps:

[0077] In step S31, determine the topological connection relationship of the optical fiber link according to the physical connection structure and logical connection information of the optical fiber link;

[0078] In step S32, based on the topological connection relationship of the optical fiber link, map the maintenance requirements in the operation and maintenance policies to the optical fiber link in the optical fiber device to obtain the mapping parameters of all optical fiber link maintenance requirements;

[0079] In step S33, determine the management relationship graph of the maintenance requirements of the optical fiber device through the mapping parameters of all maintenance requirements.

[0080] It should be noted that the topological connection relationship in the present application refers to the physical and logical connection structure between each device and node in the optical fiber link; the management relationship graph in the present application refers to a graph structure formed by visualizing the relationship between optical fiber devices, links, and operation and maintenance requirements through graph theory methods, which shows the maintenance requirements, resource allocation, and their mutual dependencies of each optical fiber device and link, so as to perform efficient operation and maintenance management and decision-making.

[0081] In specific implementation, first, the physical topology structure of the optical fiber device (such as the link and node connection information of the optical fiber network) and the logical topology structure (such as the connection information at the network protocol level) can be used, combined with existing network topology algorithms (such as the Dijkstra algorithm) to identify the dependency relationship between optical fiber links, so as to form a topological graph between the links, and use this topological graph as the description feature of the topological connection relationship of the optical fiber link; then, according to the topological structure of the optical fiber link, the maintenance requirements in the operation and maintenance policies (such as regular inspection, fault response, resource scheduling, etc.) are associated with each node and link on the link through a mapping algorithm (such as a many-to-many mapping model) to obtain the corresponding maintenance requirement mapping parameters for each optical fiber link. For example, a higher maintenance frequency is set for critical links and a lower maintenance frequency is set for secondary links; finally, all the maintenance requirement mapping parameters are integrated through a graph theory algorithm (such as a weighted graph algorithm) to construct a management relationship graph including devices, links, and operation and maintenance requirements. This management relationship graph can help operation and maintenance personnel optimize the maintenance strategy and resource allocation of optical fiber devices from a global perspective, and ensure the stability and efficiency of the optical fiber network.

[0082] In step S4, perform multi-dimensional confidence evaluation on the operation and maintenance management status of the optical fiber device based on the fault feature correlation matrix and the management relationship graph to obtain the confidence evaluation result of the operation and maintenance management status of the optical fiber device, and intelligently adjust the operation and maintenance management parameters of the optical fiber device according to the confidence evaluation result.

[0083] In this embodiment, a multi-dimensional confidence evaluation is performed on the operation and maintenance management status of the optical fiber device based on the fault feature association matrix and the management relationship graph, and the confidence evaluation result of the operation and maintenance management status of the optical fiber device can be realized by the following steps:

[0084] Determine the confidence probability of the occurrence of the optical fiber device fault according to the fault feature association matrix;

[0085] Determine the credibility of the response ability in the operation and maintenance management of the optical fiber device based on the management relationship graph;

[0086] Evaluate the operation and maintenance management status of the optical fiber device through the confidence probability and the credibility, and obtain the confidence evaluation result of the operation and maintenance management status of the optical fiber device.

[0087] Specifically, first, the probability of different fault features occurring can be calculated according to the fault feature association matrix by using a Bayesian network or a Naive Bayes classifier. The confidence of the fault occurrence can be evaluated through a conditional probability model. Based on the relationship between historical fault data and fault causes, the occurrence probability of each fault type is estimated, and this occurrence probability is used as the confidence probability of the occurrence of the optical fiber device fault. Then, based on the management relationship graph, a graph theory algorithm (such as a trust propagation algorithm) can be used to evaluate the response ability of each node in the network, calculate the response ability and recovery time of each device or link when a fault occurs, obtain the corresponding credibility score, and use the credibility score as the credibility of the response ability in the operation and maintenance management of the optical fiber device. Finally, by combining the confidence probability of the fault occurrence and the credibility of the operation and maintenance management response ability, a multi-dimensional confidence evaluation algorithm (such as a fuzzy comprehensive evaluation method) can be used to comprehensively evaluate the operation and maintenance management status of the optical fiber device based on the results of both, and a comprehensive confidence evaluation result can be obtained. The confidence evaluation result can help determine the current operating state of the device and the maintenance requirements that need to be processed first.

[0088] It should be noted that the intelligent adjustment of the operation and maintenance management parameters of the optical fiber device according to the confidence evaluation result in this application means dynamically optimizing and adjusting the device's maintenance strategy, resource allocation, and fault response measures according to the confidence evaluation result of the operation and maintenance management status of the optical fiber device to improve operation and maintenance efficiency and device stability. Specifically, first, determine the fault risk and operation and maintenance requirements of the optical fiber device through the confidence evaluation result, and identify high-risk devices or links. Secondly, according to the evaluation result, use a rule engine or a decision tree model to automatically adjust the operation and maintenance parameters, such as increasing the inspection frequency of devices with frequent faults, optimizing resource allocation, and increasing the priority of key links. Finally, through dynamically adjusting the operation and maintenance strategy, such as allocating more resources or adjusting the maintenance plan, ensure that the device is maintained and managed in a timely manner, thereby improving operation and maintenance efficiency and device reliability.

[0089] It can be seen that the present application performs a multi-dimensional confidence assessment on the operation and maintenance management status of the optical fiber equipment based on the fault feature association matrix and the management relationship map, obtains the confidence assessment result of the operation and maintenance management status of the optical fiber equipment, and then intelligently adjusts the operation and maintenance management parameters of the optical fiber equipment according to the confidence assessment result; firstly, by extracting the signal transmission characteristics and fault inducements of the optical fiber link from the operation status information, and analyzing them in combination with the loss mode, it is ensured that the potential failure risks of the equipment can be fully identified. The core of this analysis is to find out the root causes that affect the performance of the equipment by extracting and analyzing the loss mode of the optical fiber link, which provides a scientific basis for fault warning and positioning, avoids the neglect of potential equipment failures in traditional methods, and reduces the downtime and maintenance costs caused by equipment failures; secondly, by analyzing the topological structure of the optical fiber link, a The management relationship map of fiber optic equipment maintenance needs ensures that under different operating conditions, the operation and maintenance strategy can be adjusted according to actual needs. This personalized operation and maintenance strategy helps managers allocate resources more efficiently and avoids resource waste or over-concentration in traditional management methods. Then, through the multi-dimensional confidence evaluation method, the solution can comprehensively consider various factors of fiber optic equipment and accurately evaluate the operation and maintenance management status of fiber optic equipment based on the fault feature association matrix and management relationship map. This evaluation method not only improves the scientific nature of equipment management, but also realizes the intelligent process of automatically adjusting the operation and maintenance management parameters according to the evaluation results. Finally, through the mechanism of intelligent adjustment of operation and maintenance parameters, fiber optic equipment can maintain the optimal operating state in different environments and conditions, reducing the need for human intervention and improving management efficiency.

[0090] In summary, the present application scheme can realize dynamic adjustment of the operation and maintenance management parameters of optical fiber equipment, thereby improving the management efficiency of optical fiber equipment.

[0091] Embodiment 2: This application provides a fiber optic equipment management system, referring to Figure 4 As shown, this figure is a schematic diagram of an optical fiber equipment management system according to this embodiment of the present application, and the optical fiber equipment management system includes:

[0092] The acquisition module 100 is used to obtain the operation status information and operation and maintenance demand information of the optical fiber equipment;

[0093] A fault feature association module 200 is used to extract the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber device from the operation status information, analyze the loss mode of the optical fiber link according to the signal transmission characteristics, and then determine the fault feature association matrix for evaluating the operation status of the optical fiber device through the loss mode and the fault causes;

[0094] The relationship graph determination module 300 is configured to determine the operation and maintenance strategy of the optical fiber device according to the maintenance requirements in the operation and maintenance requirement information, and construct a management relationship graph of the maintenance requirements of the optical fiber device through the operation and maintenance strategy and the topological connection relationship of the optical fiber link;

[0095] The management parameter adjustment module 400 is configured to perform multi-dimensional confidence evaluation on the operation and maintenance management status of the optical fiber device based on the fault feature correlation matrix and the management relationship graph, obtain the confidence evaluation result of the operation and maintenance management status of the optical fiber device, and intelligently adjust the operation and maintenance management parameters of the optical fiber device according to the confidence evaluation result.

[0096] This application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowcharts and / or block diagrams can be implemented by computer program instructions, and the combination of the processes and / or blocks in the flowcharts and / or block diagrams can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0097] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electrically-erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc memories, a magnetic disk memory, a tape memory, or any other medium that can be used to carry or store data and is readable by a computer.

[0098] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

Claims

1. A method for managing an optical fiber device, characterized in that, The fiber optic device management method includes the following steps: Obtain the operation status information and operation and maintenance requirement information of the fiber optic device; Extract the signal transmission characteristics and fault causes of the fiber optic link in the fiber optic device from the operation status information, analyze the loss mode of the fiber optic link according to the signal transmission characteristics, and then determine the fault feature correlation matrix for evaluating the operation status of the fiber optic device through the loss mode and the fault causes; Determine the operation and maintenance strategy of the fiber optic device according to the maintenance requirements in the operation and maintenance requirement information, and construct a management relationship graph of the operation and maintenance requirements of the fiber optic device through the operation and maintenance strategy and the topological connection relationship of the fiber optic link; Perform multi-dimensional confidence evaluation on the operation and maintenance management status of the fiber optic device based on the fault feature correlation matrix and the management relationship graph, obtain the confidence evaluation result of the operation and maintenance management status of the fiber optic device, and intelligently adjust the operation and maintenance management parameters of the fiber optic device according to the confidence evaluation result; Among them, determining the fault feature correlation matrix for evaluating the operation status of the fiber optic device through the loss mode and the fault causes specifically includes: Extract the fault features of the operation of the fiber optic device from the operation status information according to the loss mode; Perform correlation mapping between each fault feature and each interference factor in the fault causes, and then extract the correlation value between the fault causes and each fault feature during the operation of the fiber optic device; Determine the fault feature correlation matrix for evaluating the operation status of the fiber optic device through all the correlation values; Among them, performing multi-dimensional confidence evaluation on the operation and maintenance management status of the fiber optic device based on the fault feature correlation matrix and the management relationship graph, and obtaining the confidence evaluation result of the operation and maintenance management status of the fiber optic device specifically includes: Determine the confidence probability of the occurrence of a fault in the fiber optic device according to the fault feature correlation matrix; Determine the credibility of the response ability in the operation and maintenance management of the fiber optic device based on the management relationship graph; Evaluate the operation and maintenance management status of the fiber optic device through the confidence probability and the credibility, and obtain the confidence evaluation result of the operation and maintenance management status of the fiber optic device.

2. The optical fiber device management method according to claim 1, characterized in that, Use distributed fiber optic sensing to collect the operation status information of the fiber optic device.

3. The optical fiber device management method according to claim 1, characterized in that Obtain the operation and maintenance requirement information of the fiber optic device from the historical operation and maintenance logs.

4. The optical fiber device management method according to claim 1, characterized in that, Extracting the signal transmission characteristics and fault causes of the fiber optic link in the fiber optic device from the operation status information specifically includes: Extract the operating parameters of the fiber optic link from the operation status information; Determine the signal transmission characteristics of the fiber optic link in the fiber optic device through the operating parameters; Extract the abnormal data during the operation of the fiber optic device from the operation status information; Perform fault analysis on the abnormal data and extract the fault causes of the fiber optic link in the fiber optic device.

5. A method for managing an optical fiber device according to claim 4, characterized in that, The operating parameters specifically include signal attenuation rate, noise level, bandwidth, and optical power.

6. The optical fiber device management method according to claim 1, wherein, Analyzing the loss mode of the fiber optic link according to the signal transmission characteristics specifically includes: Initialize a loss model; Use the signal transmission characteristics as the input parameters of the loss model; Analyze the loss mode of the fiber optic link through the loss model.

7. The optical fiber device management method according to claim 1, characterized in that Constructing a management relationship graph of the operation and maintenance requirements of the fiber optic device through the operation and maintenance strategy and the topological connection relationship of the fiber optic link specifically includes: Determine the topological connection relationship of the fiber optic link according to the physical connection structure and logical connection information of the fiber optic link; According to the topological connection relationship of the optical fiber link, map the maintenance requirements in the operation and maintenance strategy to the optical fiber link in the optical fiber device to obtain the mapping parameters of all optical fiber link maintenance requirements; Determine the management relationship graph of the optical fiber device maintenance requirements through the mapping parameters of all maintenance requirements.

8. An optical fiber device management system for performing an optical fiber device management method according to any one of claims 1 to 7, characterized in that, The optical fiber device management system includes: An acquisition module, configured to acquire the operation status information and operation and maintenance requirement information of the optical fiber device; A fault feature correlation module, configured to extract the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber device from the operation status information, analyze the loss mode of the optical fiber link according to the signal transmission characteristics, and then determine the fault feature correlation matrix for evaluating the operation status of the optical fiber device through the loss mode and the fault causes; A relationship graph determination module, configured to determine the operation and maintenance strategy of the optical fiber device according to the maintenance requirements in the operation and maintenance requirement information, and construct a management relationship graph of the optical fiber device maintenance requirements through the operation and maintenance strategy and the topological connection relationship of the optical fiber link; A management parameter adjustment module, configured to perform multi-dimensional confidence evaluation on the operation and maintenance management status of the optical fiber device based on the fault feature correlation matrix and the management relationship graph to obtain the confidence evaluation result of the operation and maintenance management status of the optical fiber device, and intelligently adjust the operation and maintenance management parameters of the optical fiber device according to the confidence evaluation result.

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