Optical fiber equipment management method and system

Abstract

The invention provides an optical fiber equipment management method and system, and relates to the technical field of equipment management, and the method comprises the steps: extracting the signal transmission characteristics and fault causes of an optical fiber link in optical fiber equipment from the operation state information of the optical fiber equipment, and analyzing the loss mode of the optical fiber link according to the signal transmission characteristics; determining a fault feature incidence matrix for evaluating the operating state of the optical fiber equipment through the loss mode and the fault inducement; determining an operation and maintenance strategy of the optical fiber equipment according to a maintenance requirement in the operation and maintenance requirement information, and constructing a management relation graph of the maintenance requirement of the optical fiber equipment through the operation and maintenance strategy and a topological connection relation of an optical fiber link; and performing multi-dimensional confidence assessment on the operation and maintenance management state of the optical fiber equipment based on the fault feature incidence matrix and the management relation graph to obtain a confidence assessment result of the operation and maintenance management state of the optical fiber equipment, and further adjusting the operation and maintenance management parameters of the optical fiber equipment. And the optical fiber equipment management efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of equipment management, and more specifically, to a method and system for managing optical fiber equipment. Background Art

[0002] With the widespread application of fiber-optic communication technology, especially in the field of data transmission and communication, the management of fiber-optic equipment has become increasingly important. Fiber-optic equipment management 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 discovered and resolved in a timely manner, reducing 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, and the role of equipment management is becoming more prominent. Through intelligent and automated equipment management systems, the operating efficiency of fiber-optic networks can be improved, maintenance costs can be reduced, and support can be provided for network expansion and upgrades.

[0003] In the existing technology, traditional fiber optic equipment management often relies on manual inspection or conventional signal monitoring. This method is difficult to identify the potential fault characteristics of fiber optic equipment in real time, resulting in the failure to timely warn or locate the fault, which in turn increases 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 in the operation of fiber optic equipment. This evaluation method not only cannot accurately reflect the actual 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 fiber optic equipment operation and maintenance management parameters to improve the efficiency of fiber optic equipment management has become a difficult problem faced by the industry. Summary of the invention

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

[0005] In a first aspect, the present application provides a method for managing an optical fiber device, the method comprising the following steps: Obtain the operating status information and operation and maintenance demand information of optical fiber equipment; Extracting signal transmission characteristics and fault causes of optical fiber links in optical fiber equipment from the operation status information, analyzing loss patterns of optical fiber links according to the signal transmission characteristics, and then determining a fault feature correlation matrix for evaluating the operation status of optical fiber equipment through the loss patterns and the fault causes; Determine the operation and maintenance strategy of the optical fiber equipment according to the maintenance requirements in the operation and maintenance demand information, and construct a management relationship map of the optical fiber equipment maintenance requirements through the operation and maintenance strategy and the topological connection relationship of the optical fiber link; Based on the fault feature association matrix and the management relationship map, a multi-dimensional confidence assessment is performed on the operation and maintenance management status of the optical fiber equipment to obtain a confidence assessment result of the operation and maintenance management status of the optical fiber equipment, and the operation and maintenance management parameters of the optical fiber equipment are intelligently adjusted according to the confidence assessment result.

[0006] In this embodiment, distributed optical fiber sensing is used to collect the operating status information of the optical fiber equipment.

[0007] In this embodiment, the operation and maintenance requirement information of the optical fiber equipment is obtained from the historical operation and maintenance log.

[0008] 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: Extracting various operating parameters of the optical fiber link from the operating status information; Determine the signal transmission characteristics of the optical fiber link in the optical fiber equipment through various operating parameters; Extracting abnormal data of the optical fiber device during operation from the operation status information; Fault analysis is performed on the abnormal data to extract the fault cause of the optical fiber link in the optical fiber device.

[0009] In this embodiment, the operating parameters specifically include signal attenuation rate, noise level, bandwidth and optical power.

[0010] In this embodiment, analyzing the loss mode of the optical fiber link according to the signal transmission characteristics specifically includes: Initialize a loss model; Using the signal transmission characteristics as input parameters of a loss model; The loss pattern of the optical fiber link is analyzed by the loss model.

[0011] In this embodiment, the fault feature association matrix for evaluating the operation status of the optical fiber device determined by the loss mode and the fault cause specifically includes: extracting the fault characteristics of the operation of the optical fiber device from the operation status information according to the loss mode; Correlation mapping is performed between each fault feature and each interference factor in the fault cause, thereby extracting the correlation value between the fault cause and each fault feature during the operation of the optical fiber device; The fault feature correlation matrix for evaluating the operation status of the optical fiber equipment is determined through all the correlation values.

[0012] In this embodiment, building a management relationship map of optical fiber equipment maintenance requirements through the operation and maintenance strategy and the topological connection relationship of the optical fiber link specifically includes: 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; According to the topological connection relationship of the optical fiber link, the maintenance requirements in the operation and maintenance strategy are mapped to the optical fiber link in the optical fiber device to obtain mapping parameters of the maintenance requirements of all optical fiber links; The management relationship map of the fiber optic equipment maintenance requirements is determined through the mapping parameters of all maintenance requirements.

[0013] In this embodiment, a multi-dimensional confidence assessment is performed on the operation and maintenance management status of the optical fiber equipment based on the fault feature association matrix and the management relationship map, and the confidence assessment result of the operation and maintenance management status of the optical fiber equipment specifically includes: Determining the confidence probability of the occurrence of optical fiber equipment failure according to the failure feature association matrix; Determining the credibility of the response capability in the operation and maintenance management of the optical fiber equipment based on the management relationship map; The operation and maintenance management status of the optical fiber equipment is evaluated by using the confidence probability and the credibility to obtain a confidence evaluation result of the operation and maintenance management status of the optical fiber equipment.

[0014] In a second aspect, the present application provides an optical fiber equipment management system for executing an optical fiber equipment management method, the optical fiber equipment management system comprising: An acquisition module is used to obtain the operation status information and operation and maintenance demand information of the optical fiber equipment; A fault feature association module is used to extract the signal transmission characteristics and fault inducement 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 inducement; A relationship map determination module is used to determine the operation and maintenance strategy of the optical fiber equipment according to the maintenance requirements in the operation and maintenance demand information, and to construct a management relationship map of the optical fiber equipment maintenance requirements through the operation and maintenance strategy and the topological connection relationship of the optical fiber link; A management parameter adjustment module is used to perform 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, obtain a confidence assessment result of the operation and maintenance management status of the optical fiber equipment, and intelligently adjust the operation and maintenance management parameters of the optical fiber equipment according to the confidence assessment result.

[0015] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects: First, the operation status information and operation and maintenance demand information of the optical fiber equipment are obtained; the signal transmission characteristics and fault causes of the optical fiber link in the optical fiber equipment are extracted from the operation status information, and the loss mode of the optical fiber link is analyzed according to the signal transmission characteristics, and then the fault feature association matrix for evaluating the operation status of the optical fiber equipment is determined through the loss mode and the fault causes; the operation and maintenance strategy of the optical fiber equipment is determined according to the maintenance requirements in the operation and maintenance demand information, and a management relationship map of the maintenance requirements of the optical fiber equipment is constructed through the topological connection relationship between the operation and maintenance strategy and the optical fiber link; based on the fault feature association matrix and the management relationship map, a multi-dimensional confidence evaluation is performed on the operation and maintenance management status of the optical fiber equipment to obtain a confidence evaluation result of the operation and maintenance management status of the optical fiber equipment, and the operation and maintenance management parameters of the optical fiber equipment are intelligently adjusted according to the confidence evaluation result.

[0016] 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.

[0017] 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

[0018] 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.

[0019] Figure 1 is a flow chart of the optical fiber equipment management method provided by the present application; Figure 2 is an exemplary flow chart for determining a fault feature association matrix provided by the present application; Figure 3 is an exemplary flow chart for determining a management relationship map provided by the present application; Figure 4 It is a module structure diagram of the optical fiber equipment management system provided in this application. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] The embodiment of the present application provides a fiber optic equipment management method and system thereof, the core of which is to extract the signal transmission characteristics and fault causes of the fiber optic link in the fiber optic equipment from the operation status information of the fiber optic equipment, analyze the loss mode of the fiber optic link according to the signal transmission characteristics, and determine the fault feature association matrix for evaluating the operation status of the fiber optic equipment through the loss mode and the fault cause; determine the operation and maintenance strategy of the fiber optic equipment according to the maintenance requirements in the operation and maintenance demand information, and construct a management relationship map of the maintenance requirements of the fiber optic equipment through the topological connection relationship between the operation and maintenance strategy and the fiber optic link; perform a multi-dimensional confidence evaluation on the operation and maintenance management status of the fiber optic equipment based on the fault feature association matrix and the management relationship map, obtain the confidence evaluation result of the operation and maintenance management status of the fiber optic equipment, and further adjust the operation and maintenance management parameters of the fiber optic equipment. In summary, this solution can realize the dynamic adjustment of the operation and maintenance management parameters of the fiber optic equipment, thereby improving the management efficiency of the fiber optic equipment.

[0022] Embodiment 1: In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown in FIG. 1 , this figure is an exemplary flow chart of a method for managing optical fiber equipment according to this embodiment of the present application, and the method for managing optical fiber equipment includes the following steps: In step S1, the operation status information and operation and maintenance requirement information of the optical fiber equipment are obtained.

[0023] It should be noted that the operating status information in this application refers to the operating condition record data generated by the optical fiber equipment during operation, which can be used to evaluate the performance, health status and failure risk of the optical fiber equipment; the operation and maintenance demand information refers to the maintenance, management and optimization requirements required to ensure the stable operation of the optical fiber equipment, including periodic maintenance, fault handling and resource scheduling data.

[0024] In specific implementation, firstly, distributed optical fiber sensing can be used to collect the operating status information of optical fiber equipment, and the operating status information specifically includes: signal transmission parameters, fault and alarm data, equipment operation log and environmental monitoring data, wherein 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 include: the optical fiber link interruption alarm, optical power abnormality, temperature too high / too low, optical module failure and bit error limit alarm; the equipment operation log specifically includes: port start and stop records, software / firmware upgrade records, maintenance operation log and historical fault records; the environmental monitoring data specifically includes: equipment room temperature and humidity, power supply voltage and electromagnetic interference data; then, the operation and maintenance demand information of the optical fiber equipment can be obtained from the historical operation and maintenance log.

[0025] 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 pattern of the optical fiber link is analyzed according to the signal transmission characteristics, and then the fault feature association matrix for evaluating the operating status of the optical fiber device is determined through the loss pattern and the fault causes.

[0026] 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 can be achieved by using the following steps: Extracting various operating parameters of the optical fiber link from the operating status information; Determine the signal transmission characteristics of the optical fiber link in the optical fiber equipment through various operating parameters; Extracting abnormal data of the optical fiber device during operation from the operation status information; Fault analysis is performed on the abnormal data to extract the fault cause of the optical fiber link in the optical fiber device.

[0027] It should be noted that the various operating parameters in this application refer to key indicators for evaluating the signal transmission quality of optical fiber links, and 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 optical fiber links to maintain the quality of optical signals during signal transmission; the fault causes in this application refer to factors that cause performance degradation of optical fiber links.

[0028] In the specific implementation, firstly, an optical power monitoring module (with a distributed optical fiber sensor built in the optical power monitoring module) or an optical time domain reflectometer can be used to collect data (signals) of the optical fiber link, and then the signal characteristics can be decomposed by wavelet transform to extract parameters such as signal attenuation, noise level, bandwidth and optical power. In addition, the measurement noise in the signal is removed by Kalman filtering before the wavelet transform to ensure the accuracy of the data; secondly, 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 optical fiber link in the optical fiber equipment; then, abnormal data is extracted from the operating status information, and a time series anomaly detection method based on a long short-term memory network (LSTM) is used to identify abnormal situations such as optical power fluctuations and bit error rate surges in real time to form abnormal data; finally, a support vector machine is used to classify the abnormal data, and the fault causes are analyzed in combination with historical fault modes, such as optical fiber breakage, connector contamination or optical amplifier failure, and the probability of occurrence of different fault causes is calculated through a Bayesian network.

[0029] In this embodiment, analyzing the loss mode of the optical fiber link according to the signal transmission characteristics can be achieved by using the following steps: Initialize a loss model; Using the signal transmission characteristics as input parameters of a loss model; The loss pattern of the optical fiber link is analyzed by the loss model.

[0030] 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 optical fiber links. 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 optical 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 optical fiber link, which is manifested as loss characteristics at different frequencies or transmission distances.

[0031] In the specific implementation, first, in the initialization loss model stage, an exponential decay model or a fiber loss model based on ray propagation can be selected to set the attenuation relationship of the optical signal in the optical fiber. The attenuation relationship is as follows: (in Transmission distance The optical power at is the initial optical power, is the attenuation coefficient), and key factors affecting fiber loss are introduced, such as fiber type, connection loss, ambient temperature, etc.; then, in the stage of inputting signal transmission characteristics, the collected signal attenuation, bit error rate (BER), dispersion, signal-to-noise ratio (SNR) and other parameters are used as model input, and multivariate regression analysis or principal component analysis (PCA) is used for dimensionality reduction to reduce the influence of redundant information on loss calculation; finally, in the stage of analyzing the loss pattern of the optical fiber link, a neural network regression model (such as BP neural network) is used to train the loss model based on historical data, and the fiber loss trend under different working 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 microbend loss or high-frequency loss fluctuation caused by connector contamination.

[0032] In this embodiment, reference Figure 2 As shown, this figure is an exemplary flow chart of determining the fault feature association matrix in an embodiment of the present application. In this embodiment, the fault feature association matrix for evaluating the operation status of the optical fiber device determined by the loss mode and the fault inducement can be implemented by the following steps: In step S21, extracting the fault characteristics of the operation of the optical fiber device from the operation status information according to the loss mode; In step S22, each fault feature is associated with each interference factor in the fault cause, and then the association value between the fault cause and each fault feature during the operation of the optical fiber device is extracted; In step S23, a fault feature correlation matrix for evaluating the operation status of the optical fiber device is determined through all correlation values.

[0033] It should be noted that the fault feature association matrix in this application refers to a matrix structure formed by associating the relationship between various fault features and fault causes during the operation of the optical fiber equipment, which is used to quantify the relationship between different fault features and their influence on the causes.

[0034] In the specific implementation, first, in the stage of extracting fault features, the main fault features can be extracted from the operation status information by analyzing the attenuation, noise, bit error rate and other parameters of the optical fiber link according to the loss mode, and the principal component analysis (PCA) can be used. These fault features mainly include increased signal attenuation, delay fluctuation and increased bit error rate; secondly, the extracted fault features are associated with the fault inducement (such as optical fiber breakage, connector contamination, temperature change), and the decision tree algorithm or support vector machine (SVM) is used to establish the mapping relationship between each fault feature and the inducement. By training historical data, the influence of each inducement on the fault feature is obtained, and the average influence of each inducement on each fault feature is used as the correlation value between the fault inducement and each fault feature during the operation of the optical fiber equipment; finally, all the correlation values ​​are summarized by the weighted matrix method, and the graph theory algorithm (such as the weighted adjacency matrix) is used to form a matrix structure with these correlation values, so as to quantify the relationship between different fault features. The above scheme can provide a basis for the subsequent evaluation of the operation status of the optical fiber equipment, help identify potential causes of failures and make accurate operation and maintenance decisions.

[0035] In step S3, the operation and maintenance strategy of the optical fiber equipment is determined according to the maintenance requirements in the operation and maintenance demand information, and a management relationship map of the optical fiber equipment maintenance requirements is constructed through the operation and maintenance strategy and the topological connection relationship between the optical fiber links.

[0036] It should be noted that, in the present application, determining the operation and maintenance strategy of the optical fiber equipment according to the maintenance requirements in the operation and maintenance demand information refers to formulating corresponding operation and maintenance strategies according to the operation and maintenance demand information such as the maintenance plan, fault handling requirements, and resource management requirements of the optical fiber equipment, including regular inspections, fault response time, resource scheduling, spare parts management and other measures to ensure the stable operation of the optical fiber equipment and minimize the risk of failures; in specific implementation, first, analyze the maintenance plan of the optical fiber equipment, determine the inspection frequency of the equipment, regular inspection of the optical fiber line and the replacement cycle of key components, for example, perform planned maintenance according to the service life of the equipment, failure rate and manufacturer's recommendations; secondly, based on the fault handling requirements, clarify the fault response time requirements and processing procedures, set priorities, such as formulating a rapid recovery strategy for critical link failures, and setting a longer response time limit for non-critical link failures; then, based on resource management requirements, ensure that the spare parts inventory is sufficient, the maintenance tools and operation and maintenance personnel skills meet the equipment requirements, and optimize the configuration of operation and maintenance resources through the 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 equipment status, identify potential failures in advance and adjust operation and maintenance parameters to reduce the probability of sudden failures.

[0037] In this embodiment, reference Figure 3As shown, this figure is an exemplary flow chart for determining a management relationship map in an embodiment of the present application. In this embodiment, the management relationship map for building the maintenance requirements of optical fiber equipment through the operation and maintenance strategy and the topological connection relationship of the optical fiber link can be implemented by the following steps: In step S31, the topological connection relationship of the optical fiber link is determined according to the physical connection structure and logical connection information of the optical fiber link; In step S32, the maintenance requirements in the operation and maintenance strategy are mapped to the optical fiber links in the optical fiber equipment according to the topological connection relationship of the optical fiber links, and the mapping parameters of the maintenance requirements of all optical fiber links are obtained; In step S33, a management relationship map of the optical fiber equipment maintenance requirements is determined through mapping parameters of all maintenance requirements.

[0038] It should be noted that the topological connection relationship in this application refers to the physical and logical connection structure between each device and node in the optical fiber link; the management relationship map in this application refers to a graph structure formed by visualizing the relationship between optical fiber equipment, links and operation and maintenance requirements through graph theory methods, which displays the maintenance requirements, resource allocation and interdependence of each optical fiber equipment and link, so as to carry out efficient operation and maintenance management and decision-making.

[0039] In specific implementation, first, the physical topology structure of the optical fiber equipment (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 the existing network topology algorithm (such as the Dijkstra algorithm) to identify the dependency relationship between the optical fiber links, thereby forming a topology map between the links, and the topology map is used as a description feature of the topological connection relationship of the optical fiber link; then, according to the topology structure of the optical fiber link, the maintenance requirements in the operation and maintenance strategy (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 on each optical fiber link, for example, a higher maintenance frequency is set for key links and a lower maintenance frequency is set for secondary links; finally, all maintenance requirement mapping parameters are integrated through a graph theory algorithm (such as a weighted graph algorithm) to construct a management relationship map containing equipment, links, and operation and maintenance requirements. The management relationship map can help operation and maintenance personnel optimize the maintenance strategy and resource allocation of optical fiber equipment from a global perspective to ensure the stability and efficiency of the optical fiber network.

[0040] In step S4, a multi-dimensional confidence assessment is performed on the operation and maintenance management status of the optical fiber equipment based on the fault feature association matrix and the management relationship map to obtain a confidence assessment result of the operation and maintenance management status of the optical fiber equipment, and the operation and maintenance management parameters of the optical fiber equipment are intelligently adjusted according to the confidence assessment result.

[0041] In this embodiment, a multi-dimensional confidence assessment 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 map, and the confidence assessment result of the operation and maintenance management status of the optical fiber device is obtained by the following steps: Determining the confidence probability of the occurrence of optical fiber equipment failure according to the failure feature association matrix; Determining the credibility of the response capability in the operation and maintenance management of the optical fiber equipment based on the management relationship map; The operation and maintenance management status of the optical fiber equipment is evaluated by using the confidence probability and the credibility to obtain a confidence evaluation result of the operation and maintenance management status of the optical fiber equipment.

[0042] In specific implementation, first, the probability of occurrence of different fault features can be calculated using a Bayesian network or a naive Bayesian classifier based on the fault feature association matrix, the confidence of the fault occurrence can be evaluated through a conditional probability model, and the probability of occurrence of each fault type can be estimated based on the relationship between historical fault data and the fault cause, and the probability of occurrence can be used as the confidence probability of the fiber optic device fault occurrence; then, based on the management relationship map, a graph theory algorithm (such as a trust propagation algorithm) can be used to evaluate the response capability of each node in the network, calculate the response capability and recovery time of each device or link when a fault occurs, and obtain the corresponding credibility score, and use the credibility score as the credibility of the response capability in the operation and maintenance management of the fiber optic device; finally, by combining the confidence probability of the fault occurrence and the credibility of the operation and maintenance management response capability, 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 fiber optic device, and a comprehensive confidence evaluation result can be obtained. The confidence evaluation result can help determine the current operating status of the equipment and the maintenance needs that need to be prioritized.

[0043] It should be noted that the intelligent adjustment of the operation and maintenance management parameters of the optical fiber equipment according to the confidence assessment results in the present application refers to dynamically optimizing and adjusting the equipment's maintenance strategy, resource allocation and fault response measures according to the confidence assessment results of the optical fiber equipment's operation and maintenance management status, so as to improve the operation and maintenance efficiency and equipment stability; in specific implementation, first, the failure risk and operation and maintenance requirements of the optical fiber equipment are determined through the confidence assessment results, and high-risk equipment or links are identified; secondly, according to the assessment results, the operation and maintenance parameters are automatically adjusted using a rule engine or decision tree model, such as increasing the inspection frequency of equipment with frequent failures, optimizing resource allocation, and increasing the priority of critical links; finally, by dynamically adjusting the operation and maintenance strategy, such as allocating more resources or adjusting the maintenance plan, it is ensured that the equipment is maintained and managed in a timely manner, thereby improving the operation and maintenance efficiency and equipment reliability.

[0044] 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.

[0045] 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.

[0046] 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: The acquisition module 100 is used to obtain the operation status information and operation and maintenance demand information of the optical fiber equipment; 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; A relationship map determination module 300 is used to determine the operation and maintenance strategy of the optical fiber equipment according to the maintenance requirements in the operation and maintenance demand information, and to construct a management relationship map of the optical fiber equipment maintenance requirements through the operation and maintenance strategy and the topological connection relationship of the optical fiber link; The management parameter adjustment module 400 is used to perform 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, obtain the confidence assessment result of the operation and maintenance management status of the optical fiber equipment, and intelligently adjust the operation and maintenance management parameters of the optical fiber equipment according to the confidence assessment result.

[0047] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0048] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, the storage medium including 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 electronically-erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0049] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A method for managing optical fiber equipment, characterized in that: The optical fiber equipment management method comprises the following steps: Obtain the operating status information and operation and maintenance demand information of optical fiber equipment; Extracting signal transmission characteristics and fault causes of optical fiber links in optical fiber equipment from the operation status information, analyzing loss patterns of optical fiber links according to the signal transmission characteristics, and then determining a fault feature correlation matrix for evaluating the operation status of optical fiber equipment through the loss patterns and the fault causes; Determine the operation and maintenance strategy of the optical fiber equipment according to the maintenance requirements in the operation and maintenance demand information, and construct a management relationship map of the optical fiber equipment maintenance requirements through the operation and maintenance strategy and the topological connection relationship of the optical fiber link; Based on the fault feature association matrix and the management relationship map, a multi-dimensional confidence assessment is performed on the operation and maintenance management status of the optical fiber equipment to obtain a confidence assessment result of the operation and maintenance management status of the optical fiber equipment, and the operation and maintenance management parameters of the optical fiber equipment are intelligently adjusted according to the confidence assessment result.

2. A method for managing optical fiber equipment according to claim 1, characterized in that: Use distributed fiber optic sensing to collect operating status information of fiber optic equipment.

3. A method for managing optical fiber equipment according to claim 1, characterized in that: Obtain the operation and maintenance requirement information of optical fiber equipment from historical operation and maintenance logs.

4. A method for managing optical fiber equipment according to claim 1, characterized in that: 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: Extracting various operating parameters of the optical fiber link from the operating status information; Determine the signal transmission characteristics of the optical fiber link in the optical fiber equipment through various operating parameters; Extracting abnormal data of the optical fiber device during operation from the operation status information; Fault analysis is performed on the abnormal data to extract the fault cause of the optical fiber link in the optical fiber device.

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

6. A method for managing optical fiber equipment according to claim 1, characterized in that: Analyzing the loss mode of the optical fiber link according to the signal transmission characteristics specifically includes: Initialize a loss model; Using the signal transmission characteristics as input parameters of a loss model; The loss pattern of the optical fiber link is analyzed by the loss model.

7. A method for managing optical fiber equipment according to claim 1, characterized in that: The fault feature correlation matrix for evaluating the operation status of the optical fiber device determined by the loss mode and the fault cause specifically includes: extracting the fault characteristics of the operation of the optical fiber device from the operation status information according to the loss mode; Correlation mapping is performed between each fault feature and each interference factor in the fault cause, thereby extracting the correlation value between the fault cause and each fault feature during the operation of the optical fiber device; The fault feature correlation matrix for evaluating the operation status of the optical fiber equipment is determined through all the correlation values.

8. The optical fiber equipment management method according to claim 1, characterized in that: The management relationship map of the optical fiber equipment maintenance requirements is constructed through the operation and maintenance strategy and the topological connection relationship of the optical fiber link, specifically including: 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; According to the topological connection relationship of the optical fiber link, the maintenance requirements in the operation and maintenance strategy are mapped to the optical fiber link in the optical fiber device to obtain mapping parameters of the maintenance requirements of all optical fiber links; The management relationship map of the fiber optic equipment maintenance requirements is determined through the mapping parameters of all maintenance requirements.

9. The optical fiber equipment management method according to claim 1, characterized in that: Based on the fault feature association matrix and the management relationship map, a multi-dimensional confidence assessment is performed on the operation and maintenance management status of the optical fiber equipment, and the confidence assessment result of the operation and maintenance management status of the optical fiber equipment is obtained, which specifically includes: Determining the confidence probability of the occurrence of optical fiber equipment failure according to the failure feature association matrix; Determining the credibility of the response capability in the operation and maintenance management of the optical fiber equipment based on the management relationship map; The operation and maintenance management status of the optical fiber equipment is evaluated by using the confidence probability and the credibility to obtain a confidence evaluation result of the operation and maintenance management status of the optical fiber equipment.

10. An optical fiber equipment management system, used to execute an optical fiber equipment management method according to any one of claims 1 to 9, characterized in that: The optical fiber equipment management system comprises: An acquisition module is used to obtain the operation status information and operation and maintenance demand information of the optical fiber equipment; A fault feature association module is used to extract the signal transmission characteristics and fault inducement 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 inducement; A relationship map determination module is used to determine the operation and maintenance strategy of the optical fiber equipment according to the maintenance requirements in the operation and maintenance demand information, and to construct a management relationship map of the optical fiber equipment maintenance requirements through the operation and maintenance strategy and the topological connection relationship of the optical fiber link; A management parameter adjustment module is used to perform 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, obtain a confidence assessment result of the operation and maintenance management status of the optical fiber equipment, and intelligently adjust the operation and maintenance management parameters of the optical fiber equipment according to the confidence assessment result.

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