Optical fiber transmission management system and method based on data analysis

Abstract

The application discloses a fiber transmission management system and method based on data analysis, relates to the technical field of fiber transmission management, and predicts whether the future of a fiber transmission path will be abnormal based on fiber path model analysis data after real-time monitoring of data related to the stability of the fiber transmission path and preprocessing of the data, replaces the second fiber transmission path in the initial ranking table to continue communication without interrupting communication when predicting that the future of the current fiber transmission path will be abnormal, continues to monitor data related to the stability of the fiber transmission path and make abnormal predictions, dynamically updates the ranking of all fiber transmission paths when periodically managing all fiber transmission paths, and manages all fiber transmission paths according to the management ranking table. The management system can effectively predict the abnormality of the fiber transmission path, so that other fiber transmission paths can be replaced in time before the fiber transmission path fails, and the stability of network communication is ensured.

Description

Technical Field

[0001] This invention relates to the field of optical fiber transmission management technology, and more specifically to an optical fiber transmission management system and method based on data analysis. Background Technology

[0002] A communication network is a system that transmits information from one location to another. This process involves the transmission, exchange, and sharing of data to connect people, devices, and systems in different geographical locations. The development of communication networks has gone through several stages, from simple person-to-person communication to today's complex global digital communication networks. Multiple optical fibers are widely used in long-distance communication networks, such as optical cable transmission in fiber optic communication networks. Optical fiber transmission offers higher bandwidth and lower signal attenuation than traditional copper cables.

[0003] The existing technology has the following shortcomings:

[0004] Since communication networks typically contain multiple fiber optic transmission paths, in practical applications, the system usually switches communication to another fault-free fiber optic transmission path only when it detects a fault in the currently operating fiber optic transmission path. Existing systems lack the ability to predict fiber optic transmission path anomalies and handle path switching in advance. For some communication networks with high requirements for real-time performance and stability, a fault in the currently operating fiber optic transmission path can lead to communication interruption, potentially causing unexpected losses and severely limiting its applicability. Summary of the Invention

[0005] The purpose of this invention is to provide a data analysis-based optical fiber transmission management system and method to address the shortcomings of the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a fiber optic transmission management method based on data analysis, the management method comprising the following steps:

[0007] S1: The management system port obtains the optical fiber transmission paths in the communication network system through the system log, numbers the optical fiber transmission paths, and performs an initial sorting of all optical fiber transmission paths according to their usage frequency, generating an initial sorting table.

[0008] S2: When communicating through a communication network system, the first-ranked optical fiber transmission path is selected for communication. During the communication process, data related to the stability of the optical fiber transmission path is monitored in real time. After preprocessing the data, the optical fiber path model is used to analyze the data and predict whether the optical fiber transmission path will experience anomalies in the future.

[0009] S3: When it is predicted that the current fiber optic transmission path will become abnormal in the future, the fiber optic transmission path will be switched to the second ranked fiber optic transmission path in the initial ranking list without interrupting communication, and communication will continue to be carried out. Data related to the stability of the fiber optic transmission path will continue to be monitored and anomaly prediction will be made.

[0010] S4: After obtaining the anomaly analysis status of all fiber optic transmission paths through the management system logs, dynamically update the sorting of all fiber optic transmission paths and generate a management sorting table.

[0011] S5: When managing all fiber optic transmission paths periodically, the administrator manages all fiber optic transmission paths according to the management sorting table.

[0012] In a preferred embodiment, step S2, predicting whether future anomalies will occur in the optical fiber transmission path based on optical fiber path model analysis data, includes the following steps:

[0013] The anomaly coefficient yCx is calculated after normalizing the signal quality index, attenuation rate, bandwidth fluctuation coefficient, and network load rate. The calculation expression is as follows: In the formula, XHZ is the signal quality index, SJ is the attenuation rate, DKF is the bandwidth fluctuation coefficient, FZ is the network load rate, and α, β, γ, and δ are the proportional coefficients of the signal quality index, attenuation rate, bandwidth fluctuation coefficient, and network load rate, respectively, and α, β, γ, and δ are all greater than 0.

[0014] Anomaly coefficient yc x The larger the value, the more likely the photovoltaic transmission path will experience anomalies in the future. The obtained anomaly coefficient yc... x The value is compared with a preset abnormal threshold;

[0015] If the abnormal coefficient yc x If the value is greater than the abnormal threshold, it indicates that the photovoltaic transmission path will experience abnormalities in the future. If the abnormality coefficient yc x If the value is less than or equal to the abnormal threshold, it is predicted that the photovoltaic transmission path will not experience any abnormalities in the future.

[0016] In a preferred embodiment, in step S3, when it is predicted that the current optical fiber transmission path will experience an anomaly in the future, communication is continued by switching to the second-ranked optical fiber transmission path in the initial ranking list without interrupting communication. Continuing to monitor data related to the stability of the optical fiber transmission path and making anomaly predictions includes the following steps:

[0017] When the anomaly detection model triggers an anomaly, it automatically switches to the second-ranked fiber optic transmission path in the initial sorting table according to preset logic. Based on the defined switching logic, it switches to the backup path, including slow switching, data caching, and user notification policies. After switching to the backup path, it continuously monitors the stability and performance of the backup path.

[0018] In a preferred embodiment, step S4 involves obtaining the anomaly analysis status of all fiber optic transmission paths through the management system logs, dynamically updating the sorting of all fiber optic transmission paths, and generating a management sorting table, which includes the following steps.

[0019] After obtaining the historical anomaly coefficients of all photovoltaic transmission paths, the average anomaly coefficient Gavg of the photovoltaic transmission paths is calculated, and the historical usage frequency Pjl of the photovoltaic transmission paths is obtained. The average anomaly coefficient Gavg and the historical usage frequency Pjl are combined to calculate the management assignment GLz. The calculation expression is: GLz = 0.7 * Gavg + 0.3 * Pjl, where GLz is the management assignment, Gavg is the average anomaly coefficient of the photovoltaic transmission paths, and Pjl is the historical usage frequency of the photovoltaic transmission paths.

[0020] Then, all photovoltaic transmission paths are sorted from largest to smallest according to the management assignment GLz, generating a management sorting table.

[0021] In a preferred embodiment, step S2 involves real-time monitoring of data related to the stability of the optical fiber transmission path during communication, and preprocessing the data including the following steps:

[0022] Quality index, attenuation rate, and bandwidth fluctuation coefficient are collected from monitoring equipment, sensors, and network management systems. Missing values ​​are filled using interpolation methods, and detrending operations are performed. The data is smoothed using moving averages, and anomaly detection is conducted to identify and process outliers.

[0023] In a preferred embodiment, the signal quality index is obtained by means of: the signal quality index is related to wireless communication, and in the wireless communication network, real-time information of the signal quality index is obtained by using a signal quality monitoring device.

[0024] In a preferred embodiment, the attenuation rate is obtained as follows: In an optical fiber communication network, the attenuation rate is used to measure signal attenuation. The power of the optical signal is measured by an optical power meter, and the attenuation rate is obtained by using an OTDR to detect reflection and attenuation in the optical fiber.

[0025] In a preferred embodiment, the bandwidth fluctuation coefficient is obtained by using a network performance monitoring tool to monitor network bandwidth usage in real time to obtain the bandwidth fluctuation coefficient, which involves changes in network bandwidth.

[0026] In a preferred embodiment, the method for obtaining the network load rate is as follows: the network load rate refers to the traffic occupancy in the network. The network load rate is monitored in real time using a network monitoring tool. The network device supports the SNMP protocol, and the performance data of the network device, including the load rate, is obtained through the SNMP protocol.

[0027] The present invention also provides a fiber optic transmission management system based on data analysis, including a path acquisition module, an initial sorting module, a path selection module, a prediction module, an automatic control module, and a management module;

[0028] Path acquisition module: The system management port obtains the optical fiber transmission path in the communication network system through the system log and assigns a number to the optical fiber transmission path;

[0029] Initial sorting module: performs initial sorting of all fiber optic transmission paths according to their usage frequency, and generates an initial sorting table;

[0030] Path selection module: When communicating through a communication network system, it selects the first-ranked optical fiber transmission path for communication. During the communication process, it monitors data related to the stability of the optical fiber transmission path in real time and preprocesses the data.

[0031] Prediction module: Based on fiber optic path model analysis data, predict whether anomalies will occur in the fiber optic transmission path in the future;

[0032] Automatic control module: When it is predicted that an anomaly will occur in the current optical fiber transmission path in the future, it will switch to the second ranked optical fiber transmission path in the initial sorting table to continue communication without interrupting communication, and continue to monitor data related to the stability of the optical fiber transmission path and make anomaly predictions.

[0033] Management module: When periodically managing all fiber optic transmission paths, after obtaining the anomaly analysis status of all fiber optic transmission paths through the system management logs, dynamically updates the sorting of all fiber optic transmission paths and generates a management sorting table.

[0034] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0035] This invention monitors data related to the stability of fiber optic transmission paths in real time. After preprocessing the data, it analyzes the data based on a fiber optic path model to predict whether future anomalies will occur in the fiber optic transmission path. When an anomaly is predicted for the current fiber optic transmission path, it switches to the second-ranked fiber optic transmission path in the initial ranking list without interrupting communication. It continues to monitor data related to the stability of fiber optic transmission paths and predict anomalies. During periodic management of all fiber optic transmission paths, it obtains the anomaly analysis status of all fiber optic transmission paths from the management system logs, dynamically updates the ranking of all fiber optic transmission paths, and generates a management ranking table. All fiber optic transmission paths are managed according to this management ranking table. This management system can effectively predict anomalies in fiber optic transmission paths, thereby enabling timely replacement of other fiber optic transmission paths before failures occur, ensuring the stability of network communication. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0037] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Example 1: Please refer to Figure 1 As shown in this embodiment, the fiber optic transmission management method based on data analysis includes the following steps:

[0040] The management system port obtains the fiber optic transmission paths in the communication network system through system logs, numbers the fiber optic transmission paths, and initially sorts them according to their usage frequency to generate an initial sorting table. When communicating through the communication network system, it selects the fiber optic transmission path ranked first in the initial sorting table. During communication, it monitors data related to the stability of the fiber optic transmission paths in real time. After preprocessing the data, it analyzes the data based on the fiber optic path model to predict whether the fiber optic transmission path will experience anomalies in the future. When an anomaly is predicted for the current fiber optic transmission path, it switches to the fiber optic transmission path ranked second in the initial sorting table without interrupting communication and continues to monitor data related to the stability of the fiber optic transmission paths and make anomaly predictions. When managing all fiber optic transmission paths periodically, it obtains the anomaly analysis status of all fiber optic transmission paths through the management system logs, dynamically updates the sorting of all fiber optic transmission paths, generates a management sorting table, and manages all fiber optic transmission paths according to the management sorting table.

[0041] This application monitors data related to the stability of fiber optic transmission paths in real time. After preprocessing the data, it analyzes the data based on a fiber optic path model to predict whether future anomalies will occur in the fiber optic transmission path. When an anomaly is predicted for the current fiber optic transmission path, it switches to the second-ranked fiber optic transmission path in the initial ranking list without interrupting communication. It continues to monitor data related to the stability of fiber optic transmission paths and predict anomalies. During periodic management of all fiber optic transmission paths, it obtains the anomaly analysis status of all fiber optic transmission paths from the management system logs, dynamically updates the ranking of all fiber optic transmission paths, generates a management ranking table, and manages all fiber optic transmission paths according to this table. This management system can effectively predict anomalies in fiber optic transmission paths, thus enabling timely replacement of other fiber optic transmission paths before failures occur, ensuring the stability of network communication.

[0042] The management system port obtains the fiber optic transmission paths in the communication network system through system logs, and assigns numbers to the fiber optic transmission paths, including the following steps:

[0043] Understand the system architecture and equipment: Understand the overall architecture of the communication network system, including fiber optic equipment, switches, routers, etc. Identify the types of equipment related to fiber optic transmission and their relationships.

[0044] Check the system logs: Analyze the system logs to understand events and information related to fiber optic transmission. Confirm whether the system logs contain critical information related to the fiber optic transmission path, such as connection establishment, disconnection, and faults.

[0045] Extract fiber optic transmission path information: Extract key data related to the fiber optic transmission path from the system logs, such as device name, port information, connection time, etc. Confirm whether there are specific keywords or tags identifying the fiber optic path in the logs.

[0046] Establish transmission path mapping: Based on the extracted information, establish a mapping for the fiber optic transmission path. This may involve associating information such as devices and ports. Multiple layers of mapping may need to be considered, such as the physical layer and data link layer.

[0047] Number the transmission path: Establish a numbering system, which can be an incrementing number, a combination of device IDs, etc., to uniquely identify the fiber optic transmission path. Record the mapping relationship between the number and the fiber optic transmission path.

[0048] Maintain the path information database: Create a path information database to record detailed information for each fiber optic transmission path, including the origin, destination, equipment type, port number, etc. Regularly update and maintain the path information database to reflect changes in network topology.

[0049] Real-time monitoring system: A real-time monitoring mechanism is set up to promptly capture new fiber optic transmission path information. When a new path is discovered, it is automatically numbered and the path information database is updated.

[0050] Security and Access Control: Consider security and access control measures to ensure that only authorized users can access and modify fiber optic transmission path information. Prevent potential security threats, such as unauthorized access or tampering.

[0051] The initial sorting of all fiber optic transmission paths based on their frequency of use, and the generation of the initial sorting table, includes the following steps:

[0052] Data Collection: Collect data on the frequency of fiber optic transmission path usage. This can be obtained through system logs, network monitoring tools, or dedicated performance monitoring systems. Record relevant information such as the usage frequency or bandwidth utilization of each fiber optic transmission path.

[0053] Calculate usage frequency: Use the collected data to calculate the usage frequency of each fiber optic transmission path. Usage frequency = current fiber optic transmission path runtime / total runtime of all fiber optic transmission paths.

[0054] Sorting operation: Sort the fiber optic transmission paths according to the calculated usage frequency. You can choose to sort by usage frequency from high to low or from low to high. Use a suitable sorting algorithm, such as bubble sort or quicksort, to sort the paths according to their usage frequency.

[0055] Generate an initial sorting table: Organize the sorted fiber optic transmission path information into a table, including path number, origin, destination, and usage frequency. The table columns can include other path-related information as needed, such as device type and port number.

[0056] Visualization (optional): You can choose to use charts or graphs to visualize the sorted fiber optic transmission path information to more intuitively understand the distribution of usage frequency.

[0057] Verification and Adjustment: Verify the accuracy of the generated initial sorting table to ensure the sorting results meet expectations. Make necessary adjustments and corrections as needed.

[0058] Update the sorting table: Regularly update the sorting table to reflect changes in network usage. An automated update mechanism can be configured to ensure the sorting information is always up-to-date.

[0059] When communicating through a communication network system, selecting the first-ranked optical fiber transmission path involves the following steps:

[0060] View the initial sorting table: Refer to the previously generated initial sorting table to see the fiber optic transmission path that is ranked first. This path is usually the most frequently used path.

[0061] Confirm communication requirements: Before selecting a fiber optic transmission path, confirm the specific communication requirements. This may involve factors such as bandwidth requirements and latency sensitivity.

[0062] Verify path availability: Ensure the top-ranked fiber optic transmission path is currently available. Check the path's status, including connectivity and health. Path availability can be monitored in real-time using network management tools or system monitoring.

[0063] Example 2: During communication, real-time monitoring of data related to the stability of the fiber optic transmission path and preprocessing of the data include the following steps:

[0064] Real-time monitoring of data related to the stability of fiber optic transmission paths, including signal quality index, attenuation rate, bandwidth fluctuation coefficient, and network load rate;

[0065] Preprocessing of quality index, attenuation rate, bandwidth fluctuation factor, and network load rate includes the following steps:

[0066] Data collection: Collect raw data for parameters such as quality index, attenuation rate, bandwidth fluctuation factor, and network load rate. This may include data obtained from monitoring equipment, sensors, network management systems, etc.

[0067] Data cleaning: Detecting and handling missing values, outliers, or noise. This can include filling missing values ​​with interpolation methods, excluding outliers by thresholding or using rules, and applying smoothing algorithms to reduce noise.

[0068] Data normalization: For data of different ranges, normalization is performed to convert them to a similar scale. This helps to avoid certain parameters having an excessive impact on the model.

[0069] Detrending: For time series data that may contain trends, detrending is performed to better capture the volatility and periodicity of the data.

[0070] Smoothing: Smoothing data reduces the impact of instantaneous changes and sudden events. This can be achieved using methods such as moving averages and exponential averages.

[0071] Feature engineering: Based on business needs and model modeling requirements, feature engineering is performed, which may include operations such as feature extraction and dimensionality reduction, in order to improve the performance and generalization ability of the model.

[0072] Standardization: For some algorithms, such as machine learning models, standardization may be necessary to ensure that the mean of the data is 0 and the variance is 1. This helps the model converge and learn better.

[0073] Data splitting: Divide the data into training and test sets for validation during model training and evaluation. Ensure that the data distributions of the training and test sets are similar.

[0074] Anomaly detection: Perform anomaly detection to identify and handle potential outliers to ensure they do not negatively impact model performance.

[0075] Scaling operation: Based on the specific algorithm requirements, certain parameters are scaled to ensure that their weights in the model are appropriate.

[0076] Handling missing values: If missing values ​​exist, take appropriate strategies to handle them, such as filling in missing values, deleting samples containing missing values, or using interpolation methods.

[0077] Real-time monitoring of data related to the stability of fiber optic transmission paths, including signal quality index, attenuation rate, bandwidth fluctuation coefficient, and network load rate;

[0078] Signal-Quality Index: The signal-quality index is usually related to wireless communication. For example, in wireless communication networks, real-time information on the signal-quality index can be obtained by using specialized signal quality monitoring equipment. These devices typically provide information on signal strength, signal-to-noise ratio, bit error rate, etc.

[0079] Attenuation Rate: In optical fiber communication networks, attenuation rate is an important indicator for measuring signal attenuation. Optical power meters can measure the power of optical signals, while OTDRs can be used to detect reflection and attenuation in optical fibers.

[0080] Bandwidth Fluctuation Coefficient: The bandwidth fluctuation coefficient relates to changes in network bandwidth. Professional network performance monitoring tools can be used to monitor network bandwidth usage in real time and calculate the bandwidth fluctuation coefficient.

[0081] Network load rate: Network load rate refers to the traffic usage in a network. Network monitoring tools (such as Wireshark, Nagios, SNMP-based monitoring tools, etc.) can be used to monitor network load rate in real time. Network devices (such as routers and switches) usually support the SNMP protocol, through which performance data of network devices, including load rate, can be obtained.

[0082] Predicting whether future anomalies will occur in fiber optic transmission paths based on fiber optic path model analysis data includes the following steps:

[0083] The anomaly coefficient ycx is calculated after normalizing the signal quality index, attenuation rate, bandwidth fluctuation coefficient, and network load rate. The calculation expression is as follows: In the formula, XHZ is the signal quality index, SJ is the attenuation rate, DKF is the bandwidth fluctuation coefficient, FZ is the network load rate, and α, β, γ, and δ are the proportional coefficients of the signal quality index, attenuation rate, bandwidth fluctuation coefficient, and network load rate, respectively, and α, β, γ, and δ are all greater than 0.

[0084] Anomaly coefficient yc x The larger the value, the more likely the photovoltaic transmission path is to experience anomalies in the future. Therefore, the obtained anomaly coefficient yc x The value is compared with a preset abnormal threshold;

[0085] If the abnormal coefficient yc x If the value is greater than the abnormal threshold, it indicates that the photovoltaic transmission path will experience abnormalities in the future. If the abnormality coefficient yc x If the value is less than or equal to the abnormal threshold, it is predicted that the photovoltaic transmission path will not experience any abnormalities in the future.

[0086] When an anomaly is predicted in the current fiber optic transmission path, communication is switched to the second-ranked fiber optic transmission path in the initial ranking list without interrupting communication. The process of monitoring data related to the stability of the fiber optic transmission path and making anomaly predictions includes the following steps:

[0087] Switching to backup path when an anomaly is triggered: When an anomaly is triggered by the anomaly detection model, the system automatically switches to the second-ranked fiber optic transmission path in the initial sorting table according to preset logic to ensure the continuity of communication.

[0088] Communication path switching logic design: Define switching logic to ensure a smooth transition in communication when switching to an alternative path. This may include strategies such as slow switching, data caching, and notifying users.

[0089] Continue to monitor the backup path: After switching to the backup path, continuously monitor the stability and performance of the backup path to ensure that the backup path can meet the communication requirements;

[0090] Real-time notifications and logging: Notify system administrators and relevant personnel of anomalies in real time and log detailed information about the anomaly, which helps with timely response and future analysis;

[0091] Regular maintenance and updates: The anomaly detection and prediction models should be maintained and updated regularly to adapt to network changes and new data patterns, ensuring the system continues to effectively predict and respond to potential problems.

[0092] After obtaining the anomaly analysis status of all fiber optic transmission paths through the management system logs, the ranking of all fiber optic transmission paths is dynamically updated to generate a management ranking table.

[0093] After obtaining the historical anomaly coefficients of all photovoltaic transmission paths, the average anomaly coefficient Gavg of the photovoltaic transmission paths is calculated, and the historical usage frequency Pjl of the photovoltaic transmission paths is obtained. The average anomaly coefficient Gavg and the historical usage frequency Pjl are combined to calculate the management assignment GLz. The calculation expression is: GLz = 0.7 * Gavg + 0.3 * Pjl, where GLz is the management assignment, Gavg is the average anomaly coefficient of the photovoltaic transmission paths, and Pjl is the historical usage frequency of the photovoltaic transmission paths.

[0094] Then, all photovoltaic transmission paths are sorted from largest to smallest according to the management assignment GLz, generating a management sorting table;

[0095] When managing all fiber optic transmission paths on a regular basis, the administrator manages all fiber optic transmission paths according to the management sorting table.

[0096] Example 3: The fiber optic transmission management system based on data analysis described in this example includes a path acquisition module, an initial sorting module, a path selection module, a prediction module, an automatic control module, and a management module;

[0097] Path acquisition module: The system management port obtains the optical fiber transmission path in the communication network system through the system log, assigns a number to the optical fiber transmission path, and sends the numbering information to the initial sorting module and the management module;

[0098] Initial sorting module: Sorts all fiber optic transmission paths according to their frequency of use, generates an initial sorting table, and sends the initial sorting table to the path selection module;

[0099] Path selection module: When communicating through the communication network system, it selects the first ranked optical fiber transmission path for communication. During the communication process, it monitors data related to the stability of the optical fiber transmission path in real time, preprocesses the data, and then sends the preprocessed data to the prediction module.

[0100] Prediction module: Based on the fiber optic path model analysis data, predict whether there will be any anomalies in the fiber optic transmission path in the future, and send the anomaly analysis status to the management module and the automatic control module;

[0101] Automatic control module: When it is predicted that an anomaly will occur in the current optical fiber transmission path in the future, it will switch to the second ranked optical fiber transmission path in the initial sorting table to continue communication without interrupting communication, and continue to monitor data related to the stability of the optical fiber transmission path and make anomaly predictions.

[0102] Management module: When periodically managing all fiber optic transmission paths, after obtaining the anomaly analysis status of all fiber optic transmission paths through the management system logs, the module dynamically updates the sorting of all fiber optic transmission paths, generates a management sorting table, and manages all fiber optic transmission paths according to the management sorting table.

[0103] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0104] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0105] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data analysis-based optical fiber transmission management method, characterized in that: The management method includes the following steps: S1: The management system port obtains the optical fiber transmission paths in the communication network system through the system log, numbers the optical fiber transmission paths, and performs an initial sorting of all optical fiber transmission paths according to their usage frequency, generating an initial sorting table. S2: When communicating through a communication network system, the first-ranked optical fiber transmission path is selected for communication. During the communication process, data related to the stability of the optical fiber transmission path is monitored in real time. After preprocessing the data, the optical fiber path model is used to analyze the data and predict whether the optical fiber transmission path will experience anomalies in the future. S3: When it is predicted that the current fiber optic transmission path will become abnormal in the future, the fiber optic transmission path will be switched to the second ranked fiber optic transmission path in the initial ranking list without interrupting communication, and communication will continue to be carried out. Data related to the stability of the fiber optic transmission path will continue to be monitored and anomaly prediction will be made. S4: After obtaining the anomaly analysis status of all fiber optic transmission paths through the management system logs, dynamically update the sorting of all fiber optic transmission paths and generate a management sorting table. S5: When managing all fiber optic transmission paths periodically, the administrator manages all fiber optic transmission paths according to the management sorting table.

2. The fiber optic transmission management method based on data analysis according to claim 1, characterized in that: In step S2, the analysis of data based on the fiber optic path model to predict whether future anomalies will occur in the fiber optic transmission path includes the following steps: The anomaly coefficient yc is calculated after normalizing the signal quality index, attenuation rate, bandwidth fluctuation coefficient, and network load rate. x The calculation expression is: In the formula, XHZ is the signal quality index, SJ is the attenuation rate, DKF is the bandwidth fluctuation coefficient, FZ is the network load rate, and α, β, γ, and δ are the proportional coefficients of the signal quality index, attenuation rate, bandwidth fluctuation coefficient, and network load rate, respectively, and α, β, γ, and δ are all greater than 0. Anomaly coefficient yc x The larger the value, the more likely the photovoltaic transmission path will experience anomalies in the future. The obtained anomaly coefficient yc... x The value is compared with a preset abnormal threshold; If the abnormal coefficient yc x If the value is greater than the abnormal threshold, it indicates that the photovoltaic transmission path will experience abnormalities in the future. If the abnormality coefficient yc x If the value is less than or equal to the abnormal threshold, it is predicted that the photovoltaic transmission path will not experience any abnormalities in the future.

3. The fiber optic transmission management method based on data analysis according to claim 2, characterized in that: In step S3, when it is predicted that an anomaly will occur in the current optical fiber transmission path in the future, communication is continued by switching to the second-ranked optical fiber transmission path in the initial ranking list without interrupting communication. The monitoring of data related to the stability of the optical fiber transmission path and the anomaly prediction include the following steps: When the anomaly detection model triggers an anomaly, it automatically switches to the second-ranked fiber optic transmission path in the initial sorting table according to preset logic. Based on the defined switching logic, it switches to the backup path, including slow switching, data caching, and user notification policies. After switching to the backup path, it continuously monitors the stability and performance of the backup path.

4. The fiber optic transmission management method based on data analysis according to claim 3, characterized in that: In step S4, after obtaining the anomaly analysis status of all optical fiber transmission paths through the management system logs, the sorting of all optical fiber transmission paths is dynamically updated to generate a management sorting table, including the following steps. After obtaining the historical anomaly coefficients of all photovoltaic transmission paths, the average anomaly coefficient Gavg of the photovoltaic transmission paths is calculated, and the historical usage frequency Pjl of the photovoltaic transmission paths is obtained. The average anomaly coefficient Gavg and the historical usage frequency Pjl are combined to calculate the management assignment GLz. The calculation expression is: GLz = 0.7 * Gavg + 0.3 * Pjl, where GLz is the management assignment, Gavg is the average anomaly coefficient of the photovoltaic transmission paths, and Pjl is the historical usage frequency of the photovoltaic transmission paths. Then, all photovoltaic transmission paths are sorted from largest to smallest according to the management assignment GLz, generating a management sorting table.

5. The fiber optic transmission management method based on data analysis according to claim 4, characterized in that: In step S2, during the communication process, data related to the stability of the optical fiber transmission path is monitored in real time, and the data preprocessing includes the following steps: Quality index, attenuation rate, and bandwidth fluctuation coefficient are collected from monitoring equipment, sensors, and network management systems. Missing values ​​are filled using interpolation methods, and detrending operations are performed. The data is smoothed using moving averages, and anomaly detection is conducted to identify and process outliers.

6. The fiber optic transmission management method based on data analysis according to claim 5, characterized in that: The method for obtaining the signal quality index is as follows: The signal quality index is related to wireless communication. In a wireless communication network, real-time information of the signal quality index is obtained by using a signal quality monitoring device.

7. The fiber optic transmission management method based on data analysis according to claim 6, characterized in that: The method for obtaining the attenuation rate is as follows: In an optical fiber communication network, the attenuation rate is used to measure signal attenuation. The power of the optical signal is measured by an optical power meter, and the attenuation rate is obtained by using an OTDR to detect reflection and attenuation in the optical fiber.

8. The fiber optic transmission management method based on data analysis according to claim 7, characterized in that: The method for obtaining the bandwidth fluctuation coefficient is as follows: The bandwidth fluctuation coefficient involves changes in network bandwidth, and the bandwidth fluctuation coefficient is obtained by using a network performance monitoring tool to monitor network bandwidth usage in real time.

9. The fiber optic transmission management method based on data analysis according to claim 8, characterized in that: The method for obtaining the network load rate is as follows: the network load rate refers to the traffic usage in the network. The network load rate is monitored in real time using network monitoring tools. The network device supports the SNMP protocol, and the performance data of the network device, including the load rate, is obtained through the SNMP protocol.

10. A data analysis-based fiber optic transmission management system for implementing the management method according to any one of claims 1-9, characterized in that: It includes a path acquisition module, an initial sorting module, a path selection module, a prediction module, an automatic control module, and a management module; Path acquisition module: The system management port obtains the optical fiber transmission path in the communication network system through the system log and assigns a number to the optical fiber transmission path; Initial sorting module: performs initial sorting of all fiber optic transmission paths according to their usage frequency, and generates an initial sorting table; Path selection module: When communicating through a communication network system, it selects the first-ranked optical fiber transmission path for communication. During the communication process, it monitors data related to the stability of the optical fiber transmission path in real time and preprocesses the data. Prediction module: Based on fiber optic path model analysis data, predict whether anomalies will occur in the fiber optic transmission path in the future; Automatic control module: When it is predicted that an anomaly will occur in the current optical fiber transmission path in the future, it will switch to the second ranked optical fiber transmission path in the initial sorting table to continue communication without interrupting communication, and continue to monitor data related to the stability of the optical fiber transmission path and make anomaly predictions. Management module: When periodically managing all fiber optic transmission paths, after obtaining the anomaly analysis status of all fiber optic transmission paths through the system management logs, dynamically updates the sorting of all fiber optic transmission paths and generates a management sorting table.

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