Intelligent diagnosis and rapid recovery method, system and device for optical path fault, and medium

Abstract

The invention relates to the technical field of communication, and discloses an intelligent diagnosis and rapid recovery method, system and device for optical path faults and a medium. The method comprises the following steps: carrying out grading processing on a data set to obtain optical path fault grade data, carrying out amplifier power adjustment through segmented gain compensation to obtain an optical power adjustment instruction, carrying out optical power compensation through an adjustable optical attenuator to obtain an optical path balance parameter, and carrying out optical power distribution equalization through power gradient calculation to obtain optical path fault grade data. Comprising inter-node power difference calculation and node power correction, power control data is obtained, finally, parameter correction is carried out through stability evaluation, power fluctuation range verification and system margin calculation are carried out, and an optical path regulation and control scheme is obtained. According to the invention, the rapid diagnosis and automatic recovery of the optical path fault are realized, the fault recovery time is improved from an hour level to a minute level, and the stability and reliability of the optical path power are ensured at the same time.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, system, device and medium for intelligent diagnosis and rapid recovery of optical path faults. Background Art

[0002] With the rapid development of fiber-optic communication networks, fiber-optic fault diagnosis and recovery technologies are becoming increasingly important. Traditional fiber-optic fault handling methods rely primarily on manual on-site operations, including manual fiber patching in substation rooms, manual entry of fiber data statistics, and on-site performance testing of spare fiber cores. While some automated solutions currently on the market, such as Huawei's IODN (Intelligent Optical Distribution Network) system, enable visual management of fiber cable counts, they still have limitations in fault recovery. Optical path quality testing technologies are primarily based on optical switching and wavelength division multiplexing. These solutions often require the addition of additional testing equipment to the existing network in practical applications.

[0003] However, the existing technology has the following shortcomings: First, due to the dispersion of computer room sites, personnel entry and exit security management requirements, and the number and professional level of maintenance personnel, even if a large amount of cost is invested, there are still problems such as slow fiber optic patching service activation, inaccurate fiber optic resource statistics, and many potential fiber optic faults; Second, existing automation solutions often only focus on the intelligence of a single link, lacking the ability to dynamically manage and precisely control the entire link of optical power parameters, resulting in optical power fluctuations, unstable signal quality and other problems during fault recovery; Third, most existing fault recovery solutions use fixed threshold judgments and preset compensation strategies, which cannot adapt to complex and changing network environments, making it difficult to achieve fast and accurate fault location and recovery. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present application provides a method, system, equipment and medium for intelligent diagnosis and rapid recovery of optical path faults, which are used to achieve rapid diagnosis and automatic recovery of optical path faults through precise optical power parameter monitoring and automatic adjustment methods when an optical fiber fault occurs, thereby reducing the fault recovery time from "hours" to "minutes" while ensuring the stability and reliability of the optical path power.

[0005] In the first aspect, the present application provides an intelligent diagnosis and rapid recovery method for optical path faults, the method comprising: collecting multi-dimensional optical power characteristics of optical fiber link nodes through an optical power detector array, including optical signal power intensity, port insertion loss, and echo attenuation gradient, to obtain an optical parameter data set; performing hierarchical processing on the optical parameter data set through a dual-threshold division method to obtain optical path fault level data; performing amplifier power adjustment on the optical path fault level data through segmented gain compensation to obtain an optical power adjustment instruction; performing optical power compensation on the optical power adjustment instruction through an adjustable optical attenuator to obtain an optical path balance parameter; performing optical power distribution equalization on the optical path balance parameter through power gradient calculation, including power difference calculation between nodes and node power correction, to obtain power control data; performing parameter correction on the power control data through stability evaluation, including power fluctuation range verification and system margin calculation, to obtain an optical path control scheme.

[0006] Optionally, the optical power detector array is used to collect multi-dimensional optical power characteristics of the optical fiber link node, including optical signal power intensity, port insertion loss, and echo attenuation gradient, to obtain an optical parameter data set, specifically including: Performing power scanning on the optical fiber link node to obtain raw power sampling data, and performing filtering processing on the raw power sampling data to obtain the optical signal power intensity; Performing loss measurement on the access endpoint of the optical fiber link node to obtain port attenuation raw data, and performing calibration processing on the port attenuation raw data to obtain the port insertion loss; Measuring the optical path length of the optical fiber link node to obtain optical path distance data, and performing attenuation calculation on the optical path distance data to obtain the echo attenuation gradient; Performing parameter statistics on the optical signal power intensity, the port insertion loss, and the echo attenuation gradient to obtain characteristic statistical data, and performing numerical processing on the characteristic statistical data to obtain parameter quantization data; Classifying and arranging the parameter quantization data to obtain feature classification data, and arranging the feature classification data in time sequence to obtain parameter sequence data; The parameter sequence data are combined and processed through data synthesis to obtain the optical parameter data set.

[0007] Optionally, the performing grading processing on the optical parameter data set by a dual-threshold division method to obtain optical path fault level data includes: Performing threshold comparison on the optical signal power intensity in the optical parameter data set to obtain power deviation data, and performing double-threshold grading of ±3dB and ±6dB on the power deviation data to obtain power level data; Performing difference statistics on the port insertion losses in the optical parameter data set to obtain loss change data, and performing dual threshold grading of 0.01 dB / km / h and 0.02 dB / km / h on the loss change data to obtain loss level data; performing a benchmark comparison on the echo attenuation gradient in the optical parameter data set to obtain attenuation distribution data, and performing a dual-threshold classification on the attenuation distribution data to obtain attenuation level data; Cross-analyzing the power level data and the loss level data to obtain a light path basic level, and correlating the light path basic level with the attenuation level data to obtain a light path comprehensive level; Performing a zone check on the comprehensive level of the optical path to obtain fault interval data, and classifying the fault interval data to obtain fault classification data; The fault classification data and the optical path comprehensive level are combined and processed to obtain the optical path fault level data.

[0008] Optionally, performing amplifier power adjustment on the optical path fault level data through segmented gain compensation to obtain an optical power adjustment instruction includes: Extracting the power parameters in the optical path fault level data in sections to obtain section power data, and performing gain requirement calculation on the section power data to obtain gain compensation data; Performing path division on the optical fiber attenuation parameters in the optical path fault level data to obtain segmented attenuation data, and performing compensation amount calculation on the segmented attenuation data to obtain attenuation compensation data; Performing compensation synthesis on the gain compensation data and the attenuation compensation data to obtain amplifier adjustment parameters, and performing hierarchical setting on the amplifier adjustment parameters to obtain hierarchical adjustment data; Performing coarse adjustment control parameter calculation on the hierarchical adjustment data to obtain coarse adjustment parameter data, and performing fine adjustment control parameter calculation on the coarse adjustment parameter data to obtain fine adjustment parameter data; Converting the fine-tuning parameter data to obtain instruction format data, and performing node matching on the instruction format data to obtain instruction allocation data; The instruction allocation data and the hierarchical adjustment data are combined and processed to obtain the optical power adjustment instruction.

[0009] Optionally, performing optical power compensation on the optical power adjustment instruction by using an adjustable optical attenuator to obtain an optical path balance parameter includes: Parsing the compensation parameters in the optical power adjustment instruction, extracting the compensation amount, timing, and priority information in the instruction and converting them into a control format recognizable by the attenuator to obtain attenuator control parameters, and splitting the attenuator control parameters by compensation amount to obtain segmented compensation data; Performing attenuator channel allocation on the segmented compensation data to obtain channel compensation data, and performing step amount calculation on the channel compensation data to obtain compensation step length data; Performing a reference compensation calculation on the compensation step data to obtain a pre-compensation parameter, and performing feedback correction on the pre-compensation parameter to obtain compensation correction data; Performing signal quality detection on the compensation correction data to obtain compensation effect data, and performing deviation analysis on the compensation effect data to obtain balance compensation data; Performing parameter sorting on the balance compensation data to obtain a compensation parameter sequence, and performing time sequence arrangement on the compensation parameter sequence to obtain balance sequence data; The balance sequence data is combined and processed to obtain the optical path balance parameters.

[0010] Optionally, performing optical power distribution balancing on the optical path balance parameters by power gradient calculation, including inter-node power difference calculation and node power correction, to obtain power control data, includes: Performing difference extraction on adjacent node parameters in the optical path balance parameters to obtain node power difference data, and performing three-point gradient calculation on the node power difference data to obtain power gradient data; Performing a ±0.5 dB threshold division on the fluctuation amount in the power gradient data to obtain fluctuation interval data, and performing segmented compensation calculation on the fluctuation interval data to obtain node compensation data; Performing three-node sliding grouping on the node compensation data to obtain intra-group compensation data, and performing inter-group coupling analysis on the intra-group compensation data to obtain compensation balance data; Performing nonlinear correction coefficient calculation on the compensation and equalization data to obtain a power correction amount, and performing bidirectional recursive distribution on the power correction amount to obtain node correction data; Performing link power reconstruction on the node correction data to obtain power distribution data, and performing harmonic analysis on the power distribution data to obtain distribution verification data; The distribution verification data and the node correction data are jointly processed through adaptive weighted fusion to obtain the power control data.

[0011] Optionally, performing parameter correction on the power control data through stability evaluation, including power fluctuation range verification and system margin calculation, to obtain an optical path control scheme, includes: Sliding the power control data in a time window with a sampling period of 500ms to obtain power time series data, and performing a ±0.2dB fluctuation threshold detection on the power time series data to obtain fluctuation range data; Performing continuous fluctuation statistics of three time windows on the fluctuation range data to obtain fluctuation statistical data, and performing quantization processing of the fluctuation statistical data with a step length of 0.1 dB to obtain fluctuation quantization data; Performing a 5 dB system margin analysis on the fluctuation quantization data to obtain margin interval data, and performing discrete sampling at 0.5 dB intervals on the margin interval data to obtain margin sampling data; Performing double-threshold cross validation on the residual sampling data to obtain verification result data, and performing 3-point median filtering on the verification result data to obtain stability data; Performing node parameter linkage analysis on the stability data to obtain linkage correction data, and performing a 2dB safety margin constraint on the linkage correction data to obtain parameter constraint data; The parameter constraint data and the linkage correction data are homogenized by segmented interpolation compensation to obtain the optical path control scheme.

[0012] In a second aspect, the present application provides an intelligent diagnosis and rapid recovery system for optical path faults, the system comprising: An acquisition module is used to acquire multi-dimensional optical power characteristics of optical fiber link nodes through an optical power detector array, including optical signal power intensity, port insertion loss, and echo attenuation gradient, to obtain an optical parameter data set; a grading module, configured to perform grading processing on the optical parameter data set by a dual-threshold division method to obtain optical path fault grade data; an adjustment module, configured to adjust the amplifier power of the optical path fault level data by segmented gain compensation to obtain an optical power adjustment instruction; a compensation module, configured to perform optical power compensation on the optical power adjustment instruction through an adjustable optical attenuator to obtain an optical path balance parameter; A balancing module is used to balance the optical power distribution of the optical path balance parameters by power gradient calculation, including power difference calculation between nodes and node power correction, to obtain power control data; The correction module is used to perform parameter correction on the power control data through stability evaluation, including power fluctuation range verification and system margin calculation, to obtain an optical path control solution.

[0013] In a third aspect, the present application provides an electronic device, comprising: a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, the method described in the first aspect is implemented.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enables the computer to execute the method described in the first aspect above.

[0015] The technical solution provided by this application uses an optical power detector array to collect multidimensional optical power characteristics at fiber link nodes, enabling comprehensive monitoring of optical signal power intensity, port insertion loss, and echo attenuation gradient, improving the accuracy and completeness of fault location. A dual-threshold partitioning method is used to hierarchically process the optical parameter data set, achieving precise fault classification and providing a reliable decision-making basis for subsequent troubleshooting. Amplifier power adjustment using segmented gain compensation ensures the accuracy and stability of power compensation, avoiding overshoot or undershoot during the compensation process. Combining optical power compensation with an adjustable optical attenuator enables fine-tuning of power balance, ensuring transmission quality of the optical path. Power gradient calculation is used to equalize optical power distribution based on optical path balance parameters. Node-to-node power difference calculation and node power correction achieve overall optimization of the optical path power distribution. Finally, stability assessment is used to calibrate the power control data parameters. Combined with power fluctuation range verification and system margin calculation, the reliability and security of the optical path control solution are ensured. This reduces fault recovery time from the traditional "hours" to "minutes," significantly improving the reliability and maintenance efficiency of optical communication networks. This method realizes the intelligent operation and maintenance of optical fiber communication networks and significantly reduces manual maintenance costs.

[0016] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are provided for a better understanding of the present invention and do not constitute a limitation of the present application. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, among which: Figure 1 A schematic diagram of an embodiment of a method for intelligent diagnosis and rapid recovery of optical path faults in an embodiment of the present application; Figure 2 This is a schematic diagram of an embodiment of an intelligent diagnosis and rapid recovery system for optical path faults in an embodiment of the present application; Figure 3 This is a schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0018] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In one embodiment of the present application, an intelligent diagnosis and rapid recovery method for optical path faults includes: Step S101: collecting multi-dimensional optical power characteristics of optical fiber link nodes using an optical power detector array, including optical signal power intensity, port insertion loss, and echo attenuation gradient, to obtain an optical parameter data set; Step S102: performing classification processing on the optical parameter data set by a dual-threshold division method to obtain optical path fault level data; Step S103: performing amplifier power adjustment on the optical path fault level data through segmented gain compensation to obtain an optical power adjustment instruction; Step S104: performing optical power compensation on the optical power adjustment instruction through an adjustable optical attenuator to obtain an optical path balance parameter; Step S105: performing optical power distribution equalization on the optical path balance parameters by power gradient calculation, including calculation of power difference between nodes and correction of node power, to obtain power control data; Step S106: Parameter correction is performed on the power control data through stability evaluation, including power fluctuation range verification and system margin calculation, to obtain an optical path control solution.

[0021] It is understandable that the execution subject of the present application can be an intelligent diagnosis and rapid recovery system for optical path failures, or a terminal or a server, which is not limited here. The embodiment of the present application is described by taking a server as the execution subject as an example.

[0022] Specifically, in this intelligent diagnosis and rapid recovery method for optical path faults, an optical power detector array is first used to collect multi-dimensional optical power characteristics of fiber link nodes. The optical power detector array consists of multiple optical power detectors evenly distributed along the fiber link, each responsible for collecting data on the optical signal power intensity, port insertion loss, and echo attenuation gradient in a local area. During the acquisition process, a power sweep is performed on the fiber link nodes with a sampling period of 10ms. The optical signal power value is recorded at each sampling point and then filtered through a sliding average of 50 sampling points to obtain the optical signal power intensity. Simultaneously, loss measurements are performed at the fiber connection ports, recording the power difference between the input and output ends. The port insertion loss value is then calibrated using a reference light source. For the echo attenuation gradient, the relationship between the optical signal's transmission delay and distance in the fiber is measured to calculate the rate of change of the attenuation value per unit length. After collecting the optical parameter data set, a dual-threshold classification method is used for grading. Two thresholds, ±3dB and ±6dB, are set for the optical signal power intensity, classifying power deviations into three levels: slight, moderate, and severe. Port insertion loss is graded using thresholds of 0.01dB / km / h and 0.02dB / km / h to determine the severity of the loss change. The echo attenuation gradient is compared with a standard attenuation curve and classified as normal, abnormal, and severely abnormal. The grading results for these three dimensions are cross-analyzed to generate optical path fault level data.

[0023] Based on the optical path fault level data, segmented gain compensation is performed to adjust the amplifier power. The optical path is divided into multiple power compensation segments, each with a different compensation strategy based on the fault level. For minor faults, gradual adjustment is performed with small steps (0.5dB), moderate faults with 1dB steps, and severe faults with rapid adjustment with 2dB steps. The compensation process is divided into two stages: coarse adjustment, which quickly approaches the target value range, and fine adjustment, which ensures stability near the target value.

[0024] Optical power compensation is performed using an adjustable optical attenuator. Optical power adjustment commands are parsed into specific attenuator control parameters, and each optical path segment is independently compensated. The compensation process consists of two stages: pre-compensation and real-time compensation. Pre-compensation pre-sets a baseline compensation value based on historical data, while real-time compensation is dynamically adjusted based on feedback. The compensation step size is set to 0.1dB to ensure accurate adjustment. To achieve balanced optical power distribution, a three-point gradient calculation method is used to process the optical path balance parameters. The power difference between adjacent nodes is calculated, and a ±0.5dB fluctuation threshold is set. Nodes exceeding the threshold are compensated. A three-node sliding grouping method is used to ensure local power balance, and inter-group coupling analysis is used to ensure global power distribution balance. Power correction uses a bidirectional recursive method, gradually adjusting from the fault point toward both ends until the entire optical path reaches a balanced state.

[0025] Finally, a stability assessment was conducted, detecting power fluctuations using a sliding time window with a 500ms sampling period. A ±0.2dB fluctuation threshold was set, and fluctuations were continuously monitored over three time windows. Fluctuation data was recorded using a 0.1dB quantization step size. System margin analysis used a 5dB benchmark, assessing system margins through discrete sampling at 0.5dB intervals and setting a 2dB safety margin constraint.

[0026] For example, when a fiber link fails, the optical power detector array detects a drop in optical signal power from 10dBm to 15dBm at the first node, an increase in port insertion loss from 0.3dB / km to 0.5dB / km, and an increase in echo attenuation gradient from 0.35dB / km to 0.45dB / km. Using a dual-threshold classification system, these conditions are identified as moderate power deviation (exceeding ±3dB but less than ±6dB), severe loss variation (exceeding 0.02dB / km / h), and abnormal attenuation gradient. Segmented gain compensation is adjusted in 1dB steps, restoring the optical power to 11dBm after three adjustments. The variable optical attenuator applies 0.8dB of compensation to this optical path, reducing the port insertion loss to 0.35dB / km. Power gradient calculations reveal a 0.6dB power difference between adjacent nodes, exceeding the ±0.5dB threshold. After bidirectional recursive correction, the difference is reduced to 0.4dB. The stability assessment showed that the corrected power fluctuation amplitude was ±0.15dB, and the system margin was maintained at 3.5dB, meeting the 2dB safety margin requirement. The entire fault diagnosis and recovery process was completed within 3 minutes.

[0027] In the embodiments of the present application, an optical power detector array is used to collect multidimensional optical power characteristics of optical fiber link nodes, enabling comprehensive monitoring of optical signal power intensity, port insertion loss, and echo attenuation gradient, thereby improving the accuracy and completeness of fault location. A dual-threshold partitioning method is used to hierarchically process the optical parameter data set, achieving precise fault classification and providing a reliable decision-making basis for subsequent fault handling. Amplifier power adjustment is performed through segmented gain compensation, ensuring the accuracy and stability of power compensation and avoiding overshoot or undershoot during the compensation process. Combining optical power compensation with an adjustable optical attenuator enables fine-tuning of power balance, ensuring the transmission quality of the optical path. Power gradient calculation is used to equalize the optical power distribution of optical path balance parameters. By calculating the power difference between nodes and correcting node power, overall optimization of the optical path power distribution is achieved. Finally, stability assessment is used to calibrate the power control data parameters. Combined with power fluctuation range verification and system margin calculation, the reliability and security of the optical path control scheme are ensured. Fault recovery time is reduced from the traditional "hours" to "minutes," significantly improving the reliability and maintenance efficiency of optical communication networks. This method realizes the intelligent operation and maintenance of optical fiber communication networks and significantly reduces manual maintenance costs.

[0028] In a specific embodiment, the process of executing step S101 may specifically include the following steps: (1) performing power scanning on the optical fiber link node to obtain raw power sampling data, and performing filtering processing on the raw power sampling data to obtain the optical signal power intensity; (2) measuring the loss of the access endpoint of the optical fiber link node to obtain raw port attenuation data, and calibrating the raw port attenuation data to obtain the port insertion loss; (3) measuring the optical path length of the optical fiber link node to obtain optical path distance data, and performing attenuation calculation on the optical path distance data to obtain the echo attenuation gradient; (4) performing parameter statistics on the optical signal power intensity, the port insertion loss, and the echo attenuation gradient to obtain characteristic statistical data, and performing numerical processing on the characteristic statistical data to obtain parameter quantization data; (5) classifying and arranging the parameter quantization data to obtain feature classification data, and arranging the feature classification data in time series to obtain parameter sequence data; (6) Combining and processing the parameter sequence data through data synthesis to obtain the optical parameter data set.

[0029] Specifically, an array of optical power detectors is used to perform power scans at fiber link nodes. Each detector continuously samples the optical signal with a sampling period of 10ms. The raw power sampled data contains the real-time power value of the optical signal during transmission, but this data contains random noise and interference. To accurately obtain the optical signal power intensity, the raw sampled data is filtered using a 50-point sliding average filter. The filter window moves point by point across the data sequence, and the arithmetic mean of the data within each window is taken to eliminate the influence of short-term fluctuations. The filtered data more accurately reflects the optical signal power intensity level. When measuring the loss of fiber link nodes, the power variation at the access point is particularly important. Optical power detectors are placed at the input and output of the optical fiber connection port, and the power values of the optical signal before and after passing through the connection point are measured to obtain the raw port attenuation data. Due to the inherent measurement error of the detector, it is calibrated using a standard light source. The calibration process uses a reference optical signal of known power to establish a correspondence between the measured value and the actual value. After linear calibration, an accurate port insertion loss value is obtained.

[0030] To measure optical path length, an optical time-domain reflectometer (OTDR) is used to measure the transmission delay of optical signals in optical fibers. The optical path distance is calculated using the round-trip transmission time of the optical signal and the propagation speed of light in the fiber. Based on this, sampling points are taken every 100 meters along the fiber length, and the optical power values at each point are recorded. The rate of change in power attenuation per unit length is calculated to obtain the echo attenuation gradient. This segmented measurement method accurately locates points of abnormal attenuation in the optical fiber link. Parameter statistics are collected for the three types of data: optical signal power intensity, port insertion loss, and echo attenuation gradient. These statistics include characteristic quantities such as the mean, standard deviation, maximum, and minimum values. These characteristic statistical data are digitized to normalize parameters of different dimensions into a standard range, facilitating subsequent comprehensive analysis. This digitization utilizes the MinMax normalization method, mapping each parameter to the [0, 1] interval to maintain the relative relationships between the data.

[0031] Parameter quantization data is categorized into three groups: power, loss, and attenuation, generating feature-classified data. Each data type includes corresponding timestamp information to facilitate time series analysis. The feature-classified data is then arranged in time series, sorted by sampling time, to generate parameter sequence data with complete time series information. Finally, the parameter sequence data is combined to form an optical parameter dataset. This combination preserves the data's multidimensional characteristics and time series relationships, facilitating subsequent fault analysis and diagnosis. Each data point contains complete information on the three dimensions of optical power, loss, and attenuation at that moment.

[0032] For example, a fiber optic link is 10 kilometers long. During optical power characterization, the optical power detector array continuously collects 500 raw power sampling points at a 10ms sampling period. The raw data shows power values fluctuating between 12.5dBm and 11.5dBm. After filtering with a 50-point sliding average, the stabilized optical signal power intensity value is 12.0dBm. At one access point of the link, the input power is measured at 12.0dBm, and the output power is measured at 12.4dBm. Calibration with a standard light source determines the insertion loss at this port to be 0.4dB. Optical power is measured every 100 meters along the fiber. The typical power difference between two adjacent points is approximately 0.035dB, resulting in a calculated echo attenuation gradient of 0.35dB / km. Statistical analysis of these three types of data revealed a standard deviation of 0.05 dB for optical power, a mean loss variation of 0.4 dB per connection point, and a fluctuation range of 0.32 to 0.38 dB / km for attenuation gradient. After data normalization, a power value of 12.0 dBm was mapped to 0.5, a loss of 0.4 dB to 0.4, and an attenuation gradient of 0.35 dB / km to 0.6. The resulting optical parameter dataset contains the standardized power, loss, and attenuation values at each sampling moment.

[0033] In a specific embodiment, the process of executing step S102 may specifically include the following steps: (1) performing threshold comparison on the optical signal power intensity in the optical parameter data set to obtain power deviation data, and performing double threshold grading of ±3 dB and ±6 dB on the power deviation data to obtain power level data; (2) performing difference statistics on the port insertion losses in the optical parameter data set to obtain loss change data, and performing dual threshold grading of 0.01 dB / km / h and 0.02 dB / km / h on the loss change data to obtain loss level data; (3) performing a baseline comparison on the echo attenuation gradient in the optical parameter data set to obtain attenuation distribution data, and performing a double threshold classification on the attenuation distribution data to obtain attenuation level data; (4) performing cross analysis on the power level data and the loss level data to obtain the optical path basic level, and performing correlation calculation on the optical path basic level and the attenuation level data to obtain the optical path comprehensive level; (5) performing a zone check on the optical path comprehensive level to obtain fault interval data, and classifying the fault interval data to obtain fault classification data; (6) Combining the fault classification data and the optical path comprehensive level to obtain the optical path fault level data.

[0034] Specifically, a multi-level dual-threshold analysis method is used to grade the optical parameter data set. First, the optical signal power intensity data is threshold-matched. By setting a standard power reference value as a reference point, the deviation between the measured power value and the reference value is calculated to obtain the power deviation data. The deviation data is graded using ±3dB and ±6dB as dual thresholds, and the power deviation is divided into three levels: when the deviation is within ±3dB, it is a slight deviation, marked as level 1; when the deviation is between ±3dB and ±6dB, it is a moderate deviation, marked as level 2; when the deviation exceeds ±6dB, it is a severe deviation, marked as level 3. This grading method fully considers the tolerance of the optical communication system to power fluctuations. When processing the port insertion loss, the loss change rate per unit time is first calculated to obtain the loss change data. Loss change data is graded using dual thresholds of 0.01dB / km / h and 0.02dB / km / h: a loss change rate less than 0.01dB / km / h indicates normal change, designated Level 1; a loss change rate between 0.01dB / km / h and 0.02dB / km / h indicates abnormal change, designated Level 2; and a loss change rate exceeding 0.02dB / km / h indicates severe change, designated Level 3. This grading standard is based on the sensitivity of optical fiber communication networks to loss changes. The echo attenuation gradient is processed using a benchmark comparison method, comparing the measured attenuation gradient with the attenuation characteristic curve of a standard optical fiber to generate attenuation distribution data. The attenuation distribution data also uses a dual-threshold grading method, with the thresholds set to 1.2 times and 1.5 times the standard attenuation value: when the measured value does not exceed 1.2 times the standard value, it is normal attenuation and is marked as Level 1; when the measured value is between 1.2 and 1.5 times the standard value, it is abnormal attenuation and is marked as Level 2; when the measured value exceeds 1.5 times the standard value, it is severe attenuation and is marked as Level 3.

[0035] After obtaining the grading data of the three dimensions, the power level data and loss level data are first cross-analyzed, and the preliminary basic level of the optical path is determined using a level mapping matrix. In the matrix, the higher value of the level of the two dimensions is taken as the basic level, and then the basic level is associated with the attenuation level data. The association calculation uses a weighted average method, where the basic level weight is 0.6 and the attenuation level weight is 0.4. The calculation result forms the comprehensive level of the optical path. The comprehensive level of the optical path is checked by partitioning, and the optical path is divided into multiple monitoring intervals, each with a length of 1 km. The distribution of the comprehensive level is statistically analyzed in each interval, and the frequency and distribution range of the level values are recorded to form the fault interval data. The fault interval data is classified by level, and the fault type of the interval is determined based on the dominant level in the interval to obtain the fault classification data.

[0036] Finally, the fault classification data is combined with the optical path comprehensive grade, taking into account the spatial distribution and severity of the faults to generate optical path fault grade data. This combined processing uses a hierarchical weighted approach, assigning different weights to the fault severity in different intervals, ensuring that the final fault grade data accurately reflects the overall status of the optical path.

[0037] For example, during fault diagnosis of a fiber link, the power of a fiber section was measured to vary from the standard value of 10dBm to 14.5dBm. The calculated power deviation was 4.5dB. Since this value exceeded ±3dB but did not reach ±6dB, it was determined to be a Level 2 fault. Simultaneously, the insertion loss of the fiber section was monitored to increase from 0.3dB / km to 0.35dB / km within one hour. The calculated loss change rate was 0.015dB / km / h, which is between 0.01dB / km / h and 0.02dB / km / h, thus determining a Level 2 fault. The measured echo attenuation gradient was 0.45dB / km, while the standard attenuation for this type of fiber is 0.35dB / km. The measured value was 1.29 times the standard value, between 1.2 and 1.5 times, thus determining a Level 2 fault. By cross-analyzing the power level (Level 2) and loss level (Level 2), the optical path's basic level is determined to be Level 2. This basic level (weight 0.6) is then weighted averaged with the attenuation level 2 (weight 0.4): 2 × 0.6 + 2 × 0.4 = 2, resulting in an overall optical path level of 2. During the zoning verification process, the fiber is divided into monitoring sections of 1 km each. Within the 2-kilometer section containing the fault point, the probability of a Level 2 fault is 80%, thus determining this section as a moderate fault zone. Finally, through combined processing, the optical path's fault level is determined to be Level 2, indicating a moderate fault requiring prompt attention.

[0038] In a specific embodiment, the process of executing step S103 may specifically include the following steps: (1) extracting the power parameters in the optical path fault level data in sections to obtain section power data, and performing gain demand calculation on the section power data to obtain gain compensation data; (2) performing path division on the optical fiber attenuation parameters in the optical path fault level data to obtain segmented attenuation data, and performing compensation calculation on the segmented attenuation data to obtain attenuation compensation data; (3) performing compensation synthesis on the gain compensation data and the attenuation compensation data to obtain amplifier adjustment parameters, and performing graded setting on the amplifier adjustment parameters to obtain graded adjustment data; (4) performing coarse adjustment control parameter calculation on the hierarchical adjustment data to obtain coarse adjustment parameter data, and performing fine adjustment control parameter calculation on the coarse adjustment parameter data to obtain fine adjustment parameter data; (5) converting the fine-tuning parameter data to obtain instruction format data, and performing node matching on the instruction format data to obtain instruction allocation data; (6) Combining and processing the instruction allocation data and the hierarchical adjustment data to obtain the optical power adjustment instruction.

[0039] Specifically, the optical path fault level data is segmented and divided into a power compensation segment for every kilometer of physical distance, and power parameters are extracted for each segment. The segmented power data includes the power at the starting point, the power at the ending point, and the power attenuation trend within the segment. The gain requirement calculation is performed on the segmented power data, taking into account the fiber attenuation characteristics, connection point loss, and environmental factors to obtain the gain compensation required for each segment. The fiber attenuation parameters are processed using the path division method, which is divided into multiple attenuation compensation intervals according to the physical topology of the fiber. Attenuation compensation amount The calculation uses the following formula: in: represents the basic attenuation value of the i-th segment, represents the temperature coefficient of the i-th segment, represents the bending loss factor of the i-th segment, represents the loss of the connection point of the i-th segment, represents the aging coefficient of the optical fiber in the i-th section, and n represents the total number of attenuation compensation intervals.

[0040] The gain compensation data and attenuation compensation data are combined using a weighted average method, with a gain compensation weight of 0.6 and an attenuation compensation weight of 0.4. Based on the combined compensation amount, the amplifier adjustment parameters are divided into three levels: level 1 for adjustments within 2dB, level 2 for adjustments above 24dB, and level 3 for adjustments above 4dB.

[0041] Coarse control parameters The calculation uses the following formula: in: Indicates the j-th level coarse adjustment reference value, represents the j-th step size coefficient, represents the j-th level correction factor, represents the j-th level feedback coefficient, Indicates the basic compensation amount, and m indicates the number of coarse adjustment levels.

[0042] Fine-tuning control parameters The calculation uses the following formula: in: Indicates the kth fine-tuning step value, represents the kth stability coefficient, represents the kth compensation coefficient, represents the kth time factor, represents the attenuation constant, and q represents the number of fine-tuning times.

[0043] Fine-tuning parameter data is converted into a standard instruction format. The instruction format includes information such as the target value, adjustment step size, and execution timing. Node matching is performed on the instruction format data to determine the specific execution node for each adjustment instruction and generate instruction allocation data. Finally, the instruction allocation data is combined with the hierarchical adjustment data to generate a complete optical power adjustment instruction. This combination ensures the correct execution order and timing of the instructions.

[0044] For example, a 10-kilometer-long optical fiber link experiences a fault. Segmented power analysis reveals a power anomaly at the 3rd kilometer, where the power drops from 10dBm to 15dBm. The attenuation parameters show that the attenuation of this fiber segment increases from 0.3dB / km to 0.5dB / km. Calculations indicate that a 5dB power loss compensation is required at this location. The formula calculates the attenuation compensation to be 0.2dB / km, corresponding to a total compensation of 2dB. After compensation synthesis, the amplifier adjustment parameter is 4.2dB, representing a three-step adjustment. The coarse adjustment process is completed in three steps: first, by 2.5dB, then by 1dB, and finally by 0.5dB. Fine adjustment is performed in 0.1dB steps. After five adjustments, the power stabilizes at 10.2dBm. The resulting adjustment command contains the complete adjustment process and parameter settings. The entire adjustment process is completed within two minutes, achieving rapid restoration of optical path power.

[0045] In a specific embodiment, the process of executing step S104 may specifically include the following steps: (1) parsing the compensation parameters in the optical power adjustment instruction, extracting the compensation amount, timing and priority information in the instruction and converting them into a control format recognizable by the attenuator, obtaining the attenuator control parameters, and splitting the attenuator control parameters by compensation amount to obtain segmented compensation data; (2) performing attenuator channel allocation on the segmented compensation data to obtain channel compensation data, and performing step amount calculation on the channel compensation data to obtain compensation step length data; (3) performing a reference compensation calculation on the compensation step data to obtain a pre-compensation parameter, and performing feedback correction on the pre-compensation parameter to obtain compensation correction data; (4) performing signal quality detection on the compensation correction data to obtain compensation effect data, and performing deviation analysis on the compensation effect data to obtain balance compensation data; (5) arranging the balance compensation data into parameters to obtain a compensation parameter sequence, and arranging the compensation parameter sequence in a time sequence to obtain balance sequence data; (6) Combining and processing the balance sequence data to obtain the optical path balance parameters.

[0046] Specifically, processing optical power adjustment commands begins with compensation parameter parsing. Optical power adjustment commands are typically transmitted in data packets, consisting of a command header, parameter fields, and a checksum. The parsing process involves format verification and integrity checks on the command packets. Key information is then extracted from the parameter fields, including the total compensation value (in dB), compensation execution timing (in milliseconds), and compensation priority level (levels 1-3). Based on the target attenuator model and communication interface specifications, the extracted parameters are converted into corresponding control bytecodes. These include the binary encoding of the compensation value, the timer setting value for timing control, and the execution queue identifier corresponding to the priority level. This ultimately generates a standard control parameter format that meets the attenuator hardware interface requirements.

[0047] After obtaining the attenuator control parameters through the above analysis, the total compensation amount is divided into multiple compensation segments according to the physical link characteristics. Each segment corresponds to a specific attenuator adjustment unit, forming segmented compensation data. The segmented compensation data is processed using a channel allocation mechanism to assign compensation tasks to different attenuator channels. The step amount of each channel is The calculation uses the following formula: in: represents the reference step size of the i-th channel, represents the response coefficient of the i-th channel, represents the load factor of the i-th channel, represents the stability coefficient of the i-th channel, Indicates the remaining compensation amount, Indicates the total compensation amount, and e indicates the number of channels.

[0048] The result of the step size calculation forms compensation step size data, which is used to control the specific adjustment amplitude of each attenuator channel. Next, a baseline compensation calculation is performed on the compensation step size data, and the pre-compensation parameters for each channel are determined based on historical compensation experience. The pre-compensation parameters are corrected through real-time feedback and dynamically adjusted based on the actual compensation effect to generate compensation correction data. The compensation correction data requires signal quality testing, including measurements of indicators such as optical power level, signal-to-noise ratio, and bit error rate. The test results form compensation effect data. By comparing and analyzing the compensation results with the target compensation value, the compensation deviation is calculated to generate balanced compensation data. The balanced compensation data is then parameterized and sorted according to compensation amount, priority, and timing requirements to form a compensation parameter sequence.

[0049] The compensation parameter sequence is time-sequenced to ensure that the execution order of each compensation action meets the optical path stability requirements. This time-sequence arrangement takes into account the mutual influence of compensation actions to avoid power fluctuations or oscillations during the compensation process. The arranged data forms a balanced sequence data, which is finally combined and processed to generate the complete optical path balance parameters.

[0050] For example, a fiber link experiences a 5dB power attenuation. Analysis reveals that compensation requires three steps: 2dB, 2dB, and 1dB. The compensation task is assigned to three attenuator channels. Based on the step size calculation formula, taking into account the first channel's 0.5dB reference step size, 0.8 response coefficient, 1.2 load factor, and 0.9 stability factor, the calculated step size for each channel is 0.43dB. Adjustments are performed four times, four times, and two times on the three channels, respectively, with 100ms intervals between each adjustment. Pre-compensation parameters are set to 90% of the actual compensation value, and after feedback correction, they reach 95% of the target value. Signal quality testing indicates that the power level reaches 10.2dBm, within an acceptable deviation from the target value of 10dBm. The resulting optical path balance parameters contain complete compensation process parameters and timing information, and the entire balancing process is completed within one minute.

[0051] In a specific embodiment, the process of executing step S105 may specifically include the following steps: (1) performing difference extraction on adjacent node parameters in the optical path balance parameters to obtain node power difference data, and performing three-point gradient calculation on the node power difference data to obtain power gradient data; (2) dividing the fluctuation amount in the power gradient data into ±0.5dB thresholds to obtain fluctuation interval data, and calculating the segmented compensation amount for the fluctuation interval data to obtain node compensation data; (3) performing three-node sliding grouping on the node compensation data to obtain intra-group compensation data, and performing inter-group coupling analysis on the intra-group compensation data to obtain compensation balance data; (4) performing nonlinear correction coefficient calculation on the compensation and equalization data to obtain a power correction amount, and performing bidirectional recursive distribution on the power correction amount to obtain node correction data; (5) performing link power reconstruction on the node correction data to obtain power distribution data, and performing harmonic analysis on the power distribution data to obtain distribution verification data; (6) The distribution verification data and the node correction data are jointly processed by adaptive weighted fusion to obtain the power control data.

[0052] Specifically, the power values of adjacent nodes in the optical path balance parameters are calculated differentially, and the power difference between each pair of adjacent nodes is extracted and recorded as node power difference data. A three-point gradient calculation method is used for these difference data, that is, three consecutive nodes are selected, with the middle node as the center, to calculate the power change trend of the previous and next nodes. The three-point gradient calculation takes into account the power change rate and change direction between nodes, and obtains power gradient data that reflects the power distribution characteristics of the optical path. Then, a fluctuation analysis is performed on the power gradient data, and ±0.5dB is set as the fluctuation threshold value. When the power gradient of a certain point exceeds this threshold range, it is marked as a fluctuation point that needs to be compensated, and the fluctuation interval data is obtained by statistics. The fluctuation interval data is segmented and the compensation amount is calculated, and the specific compensation value required for each fluctuation point is calculated to form the node compensation data. The compensation amount calculation takes into account the power level and fluctuation trend of adjacent nodes to ensure that the power distribution after compensation is more uniform.

[0053] To achieve more accurate power balancing, a three-node sliding grouping method is used to process node compensation data. Each group contains three consecutive nodes, with one node overlapping between adjacent groups. This grouping method helps maintain a smooth transition of local power. The compensation data within each group is analyzed to determine the power compensation strategy within the group and obtain the compensation data within the group. Subsequently, an inter-group coupling analysis is performed to study the power influence relationship between adjacent groups, and the compensation amount of each group is adjusted to achieve coordination and consistency, thereby obtaining the compensation balance data. A nonlinear correction mechanism is introduced to the compensation balance data to calculate the power correction coefficient. The nonlinear correction takes into account the nonlinear effects in optical fiber transmission, such as four-wave mixing and stimulated scattering, to obtain a more accurate power correction amount. A bidirectional recursive method is used to distribute the power correction amount, gradually adjusting the power level of each node from the fault point to both ends to ensure the smoothness of the overall power distribution and form the node correction data.

[0054] The link power distribution is reconstructed based on the node correction data to generate power distribution data. Harmonic analysis is performed on this data to check for periodic fluctuations or abnormal oscillations in the power distribution, ensuring the stability and reliability of the corrected power distribution. This generates distribution verification data. Finally, an adaptive weighted fusion algorithm is used to combine the distribution verification data and the node correction data. The weighting coefficients are dynamically adjusted based on the reliability of the data, ensuring that the resulting power control data meets both balance requirements and exhibits strong anti-interference capabilities.

[0055] For example, ten power monitoring nodes were installed along a 10-kilometer optical fiber link. The power values at nodes 4, 5, and 6 were detected as 12.5 dBm, 14.2 dBm, and 13.1 dBm, respectively. Three-point gradient calculation revealed a power gradient of 1.7 dB / km and +1.1 dB / km at node 5, exceeding the ±0.5 dB fluctuation threshold. Segmented compensation calculations indicated that a 1.5 dB power compensation should be added to node 5. Using a three-node sliding grouping approach, nodes 4, 5, and 6 were grouped together, resulting in group compensation values of +0.2 dB, +1.5 dB, and 0.3 dB, respectively. To account for nonlinear effects, a correction factor of 0.9 was set, resulting in power corrections of +0.18 dB, +1.35 dB, and 0.27 dB. After bidirectional recursive allocation, adjacent nodes also made small adjustments to smooth the power transition. Harmonic analysis confirmed no significant periodic fluctuations in the corrected power distribution, and the maximum power fluctuation was kept within ±0.3dB, meeting network transmission requirements. The entire equalization process was completed within 2 minutes, enabling rapid recovery and optimization of optical path power.

[0056] In a specific embodiment, the process of executing step S106 may specifically include the following steps: (1) Sliding the time window of the power control data with a sampling period of 500ms to obtain power time series data, and performing a ±0.2dB fluctuation threshold detection on the power time series data to obtain fluctuation range data; (2) performing continuous fluctuation statistics of three time windows on the fluctuation range data to obtain fluctuation statistical data, and performing quantization processing on the fluctuation statistical data with a step length of 0.1 dB to obtain fluctuation quantization data; (3) performing a 5 dB system margin analysis on the fluctuation quantization data to obtain margin interval data, and performing discrete sampling of the margin interval data at 0.5 dB intervals to obtain margin sampling data; (4) performing double-threshold cross-validation on the residual sampling data to obtain verification result data, and performing 3-point median filtering on the verification result data to obtain stability data; (5) performing node parameter linkage analysis on the stability data to obtain linkage correction data, and performing a 2dB safety margin constraint on the linkage correction data to obtain parameter constraint data; (6) The parameter constraint data and the linkage correction data are homogenized by segmented interpolation compensation to obtain the optical path control scheme.

[0057] Specifically, the stability assessment of power control data begins with a sliding time window analysis. A basic sampling period of 500ms is used, and optical power data is collected within each time window. The sliding window moves continuously, covering new data points with each movement while retaining some historical data, forming continuous power time series data. A ±0.2dB fluctuation threshold is set for this time series data. Fluctuation points exceeding the threshold are recorded, and the amplitude and duration of the fluctuations are statistically analyzed to generate fluctuation range data. Further processing of the fluctuation range data utilizes a continuous observation method using three time windows. Each observation window contains 10 sampling points, with five points overlapping between adjacent windows. This overlapping design helps capture the continuous nature of power fluctuations. Fluctuations within each window are statistically analyzed, with the number of fluctuations, mean amplitude, and standard deviation recorded to generate fluctuation statistics. The fluctuation statistics are quantized in steps of 0.1dB, discretizing the continuous fluctuation values into fixed-interval levels to generate quantized fluctuation data.

[0058] System margin analysis is performed on the fluctuation quantization data, with 5dB being used as the overall system margin for evaluation. This margin analysis takes into account various loss factors within the optical fiber link, including intrinsic fiber loss, connection point loss, and bending loss. Different margin intervals are defined based on the combined effects of these factors. Within each interval, discrete sampling is performed at 0.5dB intervals, and the power status at each sampling point is recorded to generate margin sampling data. This margin sampling data is then verified using a dual-threshold cross-validation mechanism, with the upper threshold set at the target power value + 0.3dB and the lower threshold set at 0.3dB. When the power value at a sampling point meets both thresholds, it is marked as a valid data point. The validated data is then subjected to a three-point median filter to remove abnormal fluctuation points, resulting in stability data reflecting the stability of the optical path.

[0059] A node parameter linkage analysis is performed on the stability data to study the correlation of power changes between adjacent nodes. This linkage analysis includes both positive and negative impacts. The power coupling coefficient between nodes is calculated, the impact range of power adjustment is determined, and linkage correction data is generated. A 2dB safety margin constraint is applied to the linkage correction data to ensure sufficient power adjustment capacity under various operating conditions, thus forming parameter-constrained data. Finally, a segmented interpolation compensation method is used to homogenize the parameter-constrained data and linkage correction data. The interpolation process uses a cubic spline interpolation algorithm to ensure data continuity while achieving a smooth transition of power distribution, ultimately generating a complete optical path control solution.

[0060] For example, during the fault recovery process of a fiber link, power data was collected using a sliding window with a 500ms sampling period. During the 15-second observation period, a typical series of power fluctuations was recorded: 10.1dBm, 10.3dBm, 10.2dBm, 9.9dBm, and 10.4dBm. Two points exceeded the ±0.2dB threshold. Statistical analysis of these data across three time windows revealed a standard deviation of 0.18dB. After quantization in 0.1dB steps, the fluctuation levels were classified into five levels. System margin analysis revealed that the current total link loss was 3.5dB, leaving 1.5dB of margin within the 5dB system margin. Sampling was performed at 0.5dB intervals, resulting in four key sampling points. Double-threshold verification demonstrated that 90% of the sampling points fell within the ±0.3dB tolerance. After three-point median filtering, power fluctuations were significantly suppressed, with the maximum amplitude reduced to 0.15dB. Node linkage analysis revealed a power coupling coefficient of approximately 0.3 between adjacent nodes, leading to the design of a linkage compensation strategy. Taking into account a 2dB safety margin, the final control scheme stabilized the power within a range of 10.0±0.2dB. The entire evaluation and control process was completed within 30 seconds.

[0061] The above describes the intelligent diagnosis and rapid recovery method of the optical path fault in the embodiment of the present application. The following describes the intelligent diagnosis and rapid recovery system of the optical path fault in the embodiment of the present application. Figure 2 In one embodiment of the present application, an intelligent diagnosis and rapid recovery system for optical path faults includes: The acquisition module 201 is used to collect multi-dimensional optical power characteristics of optical fiber link nodes through an optical power detector array, including optical signal power intensity, port insertion loss, and echo attenuation gradient, to obtain an optical parameter data set; A classification module 202 is configured to classify the optical parameter data set using a dual-threshold division method to obtain optical path fault grade data; An adjustment module 203 is configured to adjust the amplifier power of the optical path fault level data by segmented gain compensation to obtain an optical power adjustment instruction; The compensation module 204 is configured to perform optical power compensation on the optical power adjustment instruction through an adjustable optical attenuator to obtain an optical path balance parameter; The balancing module 205 is configured to balance the optical power distribution of the optical path balance parameters by power gradient calculation, including calculation of power differences between nodes and correction of node power, to obtain power control data; The correction module 206 is configured to perform parameter correction on the power control data through stability evaluation, including power fluctuation range verification and system margin calculation, to obtain an optical path control solution.

[0062] Through the collaborative efforts of the aforementioned components, an optical power detector array collects multi-dimensional optical power characteristics at fiber link nodes, enabling comprehensive monitoring of optical signal power intensity, port insertion loss, and echo attenuation gradients, improving the accuracy and completeness of fault location. A dual-threshold partitioning method is used to hierarchically process the optical parameter dataset, achieving precise fault classification and providing a reliable basis for subsequent troubleshooting. Segmented gain compensation is used to adjust amplifier power, ensuring accuracy and stability, and avoiding overshoot or undershoot during the compensation process. Combining optical power compensation with an adjustable optical attenuator enables fine-tuning of power balance, ensuring transmission quality along the optical path. Power gradient calculation is used to balance optical path parameters, and inter-node power difference calculation and node power correction optimize the overall power distribution along the optical path. Finally, stability assessment is used to calibrate the power control data parameters. Combined with power fluctuation range verification and system margin calculation, the reliability and security of the optical path control solution are ensured. This reduces fault recovery time from traditional hours to minutes, significantly improving the reliability and maintenance efficiency of optical communication networks. This method realizes the intelligent operation and maintenance of optical fiber communication networks and significantly reduces manual maintenance costs.

[0063] Figure 3 A schematic block diagram of an electronic device 300 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0064] The electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a ROM 302 or a computer program loaded from a storage unit 308 into a RAM 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0065] Multiple components in the electronic device 300 are connected to the I / O interface 305, including an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a magnetic disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0066] The computing unit 301 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the method for intelligent diagnosis and rapid recovery of optical path faults. For example, in some embodiments, the method for intelligent diagnosis and rapid recovery of optical path faults can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed into the electronic device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the method for intelligent diagnosis and rapid recovery of optical path faults described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to execute the intelligent diagnosis and rapid recovery method for optical path faults in any other appropriate manner (eg, by means of firmware).

[0067] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0068] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. Such program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow charts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0069] In the context of this application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0070] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0071] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0072] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0073] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this application can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this application can be achieved. This is not a limitation herein.

[0074] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. An intelligent diagnosis and rapid recovery method for optical path faults, characterized in that: The method comprises: The optical power detector array is used to collect multi-dimensional optical power characteristics of the optical fiber link nodes, including optical signal power intensity, port insertion loss, and echo attenuation gradient, to obtain an optical parameter data set. Performing classification processing on the optical parameter data set by a double-threshold division method to obtain optical path fault grade data; Performing amplifier power adjustment on the optical path fault level data through segmented gain compensation to obtain an optical power adjustment instruction; Performing optical power compensation on the optical power adjustment instruction by using an adjustable optical attenuator to obtain an optical path balance parameter; Perform optical power distribution balancing on the optical path balance parameters by power gradient calculation, including power difference calculation between nodes and node power correction, to obtain power control data; The power control data is subjected to parameter correction through stability evaluation, including power fluctuation range verification and system margin calculation, to obtain an optical path control scheme.

2. The intelligent diagnosis and rapid recovery method for optical path faults according to claim 1, characterized in that: The optical power detector array is used to collect multi-dimensional optical power characteristics of the optical fiber link node, including optical signal power intensity, port insertion loss, and echo attenuation gradient, to obtain an optical parameter data set, specifically including: Performing power scanning on the optical fiber link node to obtain raw power sampling data, and performing filtering processing on the raw power sampling data to obtain the optical signal power intensity; Performing loss measurement on the access endpoint of the optical fiber link node to obtain port attenuation raw data, and performing calibration processing on the port attenuation raw data to obtain the port insertion loss; Measuring the optical path length of the optical fiber link node to obtain optical path distance data, and performing attenuation calculation on the optical path distance data to obtain the echo attenuation gradient; Performing parameter statistics on the optical signal power intensity, the port insertion loss, and the echo attenuation gradient to obtain characteristic statistical data, and performing numerical processing on the characteristic statistical data to obtain parameter quantization data; Classifying and arranging the parameter quantization data to obtain feature classification data, and arranging the feature classification data in time sequence to obtain parameter sequence data; The parameter sequence data are combined and processed through data synthesis to obtain the optical parameter data set.

3. The intelligent diagnosis and rapid recovery method for optical path faults according to claim 1, characterized in that: The step of performing classification processing on the optical parameter data set by a dual-threshold division method to obtain optical path fault level data includes: Performing threshold comparison on the optical signal power intensity in the optical parameter data set to obtain power deviation data, and performing double-threshold grading of ±3dB and ±6dB on the power deviation data to obtain power level data; Performing difference statistics on the port insertion losses in the optical parameter data set to obtain loss change data, and performing dual threshold grading of 0.01 dB / km / h and 0.02 dB / km / h on the loss change data to obtain loss level data; performing a benchmark comparison on the echo attenuation gradient in the optical parameter data set to obtain attenuation distribution data, and performing a dual-threshold classification on the attenuation distribution data to obtain attenuation level data; Cross-analyzing the power level data and the loss level data to obtain a light path basic level, and correlating the light path basic level with the attenuation level data to obtain a light path comprehensive level; Performing a zone check on the comprehensive level of the optical path to obtain fault interval data, and classifying the fault interval data to obtain fault classification data; The fault classification data and the optical path comprehensive level are combined and processed to obtain the optical path fault level data.

4. The intelligent diagnosis and rapid recovery method for optical path faults according to claim 1, characterized in that: The step of performing amplifier power adjustment on the optical path fault level data through segmented gain compensation to obtain an optical power adjustment instruction includes: Extracting the power parameters in the optical path fault level data in sections to obtain section power data, and performing gain requirement calculation on the section power data to obtain gain compensation data; Performing path division on the optical fiber attenuation parameters in the optical path fault level data to obtain segmented attenuation data, and performing compensation amount calculation on the segmented attenuation data to obtain attenuation compensation data; Performing compensation synthesis on the gain compensation data and the attenuation compensation data to obtain amplifier adjustment parameters, and performing hierarchical setting on the amplifier adjustment parameters to obtain hierarchical adjustment data; Performing coarse adjustment control parameter calculation on the hierarchical adjustment data to obtain coarse adjustment parameter data, and performing fine adjustment control parameter calculation on the coarse adjustment parameter data to obtain fine adjustment parameter data; Converting the fine-tuning parameter data to obtain instruction format data, and performing node matching on the instruction format data to obtain instruction allocation data; The instruction allocation data and the hierarchical adjustment data are combined and processed to obtain the optical power adjustment instruction.

5. The intelligent diagnosis and rapid recovery method for optical path faults according to claim 1, characterized in that: The step of performing optical power compensation on the optical power adjustment instruction by using an adjustable optical attenuator to obtain an optical path balance parameter includes: Parsing the compensation parameters in the optical power adjustment instruction, extracting the compensation amount, timing and priority information in the instruction and converting them into a control format recognizable by the attenuator to obtain attenuator control parameters, and splitting the attenuator control parameters by compensation amount to obtain segmented compensation data; Performing attenuator channel allocation on the segmented compensation data to obtain channel compensation data, and performing step amount calculation on the channel compensation data to obtain compensation step length data; Performing a reference compensation calculation on the compensation step data to obtain a pre-compensation parameter, and performing feedback correction on the pre-compensation parameter to obtain compensation correction data; Performing signal quality detection on the compensation correction data to obtain compensation effect data, and performing deviation analysis on the compensation effect data to obtain balance compensation data; Performing parameter sorting on the balance compensation data to obtain a compensation parameter sequence, and performing time sequence arrangement on the compensation parameter sequence to obtain balance sequence data; The balance sequence data is combined and processed to obtain the optical path balance parameters.

6. The intelligent diagnosis and rapid recovery method for optical path faults according to claim 1, characterized in that: The optical power distribution balancing of the optical path balance parameters by power gradient calculation includes inter-node power difference calculation and node power correction to obtain power control data, including: Performing difference extraction on adjacent node parameters in the optical path balance parameters to obtain node power difference data, and performing three-point gradient calculation on the node power difference data to obtain power gradient data; Performing a ±0.5 dB threshold division on the fluctuation amount in the power gradient data to obtain fluctuation interval data, and performing segmented compensation calculation on the fluctuation interval data to obtain node compensation data; Performing three-node sliding grouping on the node compensation data to obtain intra-group compensation data, and performing inter-group coupling analysis on the intra-group compensation data to obtain compensation balance data; Performing nonlinear correction coefficient calculation on the compensation and equalization data to obtain a power correction amount, and performing bidirectional recursive distribution on the power correction amount to obtain node correction data; Performing link power reconstruction on the node correction data to obtain power distribution data, and performing harmonic analysis on the power distribution data to obtain distribution verification data; The distribution verification data and the node correction data are jointly processed through adaptive weighted fusion to obtain the power control data.

7. The intelligent diagnosis and rapid recovery method for optical path faults according to claim 1, characterized in that: The power control data is subjected to parameter correction through stability evaluation, including power fluctuation range verification and system margin calculation, to obtain an optical path control scheme, including: Sliding the power control data in a time window with a sampling period of 500ms to obtain power time series data, and performing a ±0.2dB fluctuation threshold detection on the power time series data to obtain fluctuation range data; Performing continuous fluctuation statistics of three time windows on the fluctuation range data to obtain fluctuation statistical data, and performing quantization processing of the fluctuation statistical data with a step length of 0.1 dB to obtain fluctuation quantization data; Performing a 5 dB system margin analysis on the fluctuation quantization data to obtain margin interval data, and performing discrete sampling at 0.5 dB intervals on the margin interval data to obtain margin sampling data; Performing double-threshold cross validation on the residual sampling data to obtain verification result data, and performing 3-point median filtering on the verification result data to obtain stability data; Performing node parameter linkage analysis on the stability data to obtain linkage correction data, and performing a 2dB safety margin constraint on the linkage correction data to obtain parameter constraint data; The parameter constraint data and the linkage correction data are homogenized by segmented interpolation compensation to obtain the optical path control scheme.

8. An intelligent diagnosis and rapid recovery system for optical path faults, used to implement the intelligent diagnosis and rapid recovery method for optical path faults according to any one of claims 1 to 7, characterized in that: The system comprises: An acquisition module is used to acquire multi-dimensional optical power characteristics of optical fiber link nodes through an optical power detector array, including optical signal power intensity, port insertion loss, and echo attenuation gradient, to obtain an optical parameter data set; a grading module, configured to perform grading processing on the optical parameter data set by a dual-threshold division method to obtain optical path fault grade data; an adjustment module, configured to adjust the amplifier power of the optical path fault level data by segmented gain compensation to obtain an optical power adjustment instruction; a compensation module, configured to perform optical power compensation on the optical power adjustment instruction through an adjustable optical attenuator to obtain an optical path balance parameter; A balancing module is used to balance the optical power distribution of the optical path balance parameters by power gradient calculation, including power difference calculation between nodes and node power correction, to obtain power control data; The correction module is used to perform parameter correction on the power control data through stability evaluation, including power fluctuation range verification and system margin calculation, to obtain an optical path control solution.

9. A computer device, characterized in that: include: A processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the computer device is running, the processor and the memory communicate via the bus. When the machine-readable instructions are executed by the processor, the steps of the intelligent diagnosis and rapid recovery method for optical path faults according to any one of claims 1 to 7 are performed.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the intelligent diagnosis and rapid recovery method for optical path faults according to any one of claims 1 to 7 is implemented.

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