Optical fiber communication status evaluation method, device, equipment and storage medium

Abstract

The present invention provides a method, device, equipment and storage medium for evaluating the state of optical fiber communication. The method includes: inserting an optical fiber connector in series in an optical fiber link, injecting a dual-wavelength optical signal into each connection point, and measuring optical power, timing jitter and bit error rate under different code types and rates. The error time distribution is statistically analyzed based on the bit error rate result, and the time-related characteristic parameters are generated by combining the optical power mean and the timing jitter peak. During the link communication operation, the connection point is monitored online, the bit error distribution, optical power mean and jitter peak in the current time window are recorded, and the recorded data is compared with the time-related characteristic parameters to obtain the communication state evaluation result. The present invention is able to combine the optical fiber communication state evaluation method of multi-parameter, multi-condition real-time monitoring and time-related characteristic analysis to identify the complex fault characteristics that may occur in the optical fiber link, ensure the stability of the link, and improve the reliability and maintenance efficiency of the communication system.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to an optical fiber communication status evaluation method, device, equipment and storage medium. Background Art

[0002] With the widespread application of fiber-optic communication systems in high-speed data transmission, accurate evaluation of the status of fiber-optic links is crucial to ensuring communication quality and system stability. Traditional fiber-optic link evaluation methods usually rely on single parameter monitoring of bit error rate or optical power, and judge the communication status by monitoring the overall bit error situation of the link. However, this method has low accuracy and reliability in dynamic environments, especially at the connection points of the link, where minor anomalies caused by factors such as connector aging and environmental fluctuations cannot be effectively identified. In addition, single parameter monitoring cannot reflect the time-varying bit error distribution characteristics in the link, making it difficult to promptly warn of potential faults. Therefore, existing technologies cannot achieve comprehensive, dynamic, and real-time status evaluation of fiber-optic links, and cannot meet the increasingly stringent communication quality assurance needs. Summary of the invention

[0003] The main purpose of the present invention is to solve the technical problem that the existing technology cannot realize the all-round and dynamic real-time status evaluation of the optical fiber link and cannot meet the increasingly stringent communication quality assurance requirements;

[0004] A first aspect of the present invention provides a method for evaluating an optical fiber communication state, the method comprising:

[0005] For the fiber optic link, a dual-wavelength optical signal is injected into the connection point corresponding to each connector, and the optical power value, timing jitter value and bit error rate test results under different code types and rates at the connection point are measured;

[0006] According to the bit error rate test results of the connection point, the bit errors under each code type and rate condition are counted to establish a bit error time distribution sequence, and the optical power mean and timing jitter peak in each time window of the bit error time distribution sequence are correspondingly analyzed to obtain time correlation characteristic parameters;

[0007] When the optical fiber link is performing communication operation, the connection point is monitored online, and the bit error distribution, optical power mean value and timing jitter peak value in the current time window are recorded to obtain recorded data;

[0008] The communication status of the optical fiber link is evaluated according to the recorded data and the time-related characteristic parameters to obtain a communication status evaluation result.

[0009] Optionally, in a first implementation of the first aspect of the present invention, the optical fiber link is serially connected to an optical fiber connector, a dual-wavelength optical signal is used to inject the connection point corresponding to each connector, and the optical power value, timing jitter value and bit error rate test results under different code types and rate conditions at the connection point are measured, including:

[0010] Performing dual-wavelength optical time domain reflectometry on the optical fiber link to obtain a reflection characteristic curve of the optical fiber link, and calculating the number and locating the positions of the connection points of the optical fiber link according to the reflection characteristic curve to obtain connection point distribution parameters;

[0011] According to the connection point distribution parameters, the optical fiber link is connected to the optical fiber connector, and the dual-wavelength optical signal is injected into the connection point of each optical fiber connector, and the optical signal parameters are injected;

[0012] Performing optical power sampling detection on the connection point according to the injected optical signal parameters to obtain an optical power time series of the connection point, and performing sliding average calculation on the optical power time series of the connection point to obtain an optical power value of the connection point;

[0013] Performing timing synchronous sampling on the connection point according to the optical power value to obtain a timing jitter sequence of the connection point, and performing window division and statistical analysis on the timing jitter sequence of the connection point to obtain a timing jitter value;

[0014] The code type switching and rate adjustment are performed on the connection point according to the optical power value and the timing jitter value to obtain a code type rate combination scheme, and the bit error rate test is performed on the connection point according to the code type rate combination scheme to obtain a bit error rate test result.

[0015] Optionally, in a second implementation of the first aspect of the present invention, according to the bit error rate test result of the connection point, the bit errors under each code type and rate condition are counted, and a bit error time distribution sequence is established, and at the same time, the optical power mean and timing jitter peak in each time window of the bit error time distribution sequence are correspondingly analyzed, and the time-related characteristic parameters obtained include:

[0016] Classifying and arranging the bit error rate test results by code type and rate to obtain classified bit error data, and performing time series segmentation on each code type and rate combination according to the classified bit error data to obtain a bit error time window sequence;

[0017] Counting and counting the bit errors in each time window according to the bit error time window sequence to obtain a bit error time distribution sequence;

[0018] Performing mean calculation in each time window in the bit error time distribution sequence to obtain an optical power mean sequence;

[0019] Extracting the peak value of the timing jitter in each time window in the bit error time distribution sequence to obtain a timing jitter peak sequence;

[0020] A time correlation mapping is established according to the error time distribution sequence, the optical power mean sequence and the timing jitter peak sequence to obtain a time dimension feature matrix, and a correlation analysis is performed on the time dimension feature matrix to obtain time correlation feature parameters.

[0021] Optionally, in a third implementation manner of the first aspect of the present invention, a time correlation mapping is established according to the error time distribution sequence, the optical power mean sequence, and the timing jitter peak sequence to obtain a time dimension feature matrix, and a correlation analysis is performed on the time dimension feature matrix to obtain time correlation feature parameters including:

[0022] Performing time dimension combined mapping on the bit error time distribution sequence, the optical power mean sequence and the timing jitter peak sequence to obtain an initial feature mapping matrix;

[0023] Cross-pairing the bit error distribution, the optical power mean, and the timing jitter peak value in each time window according to the initial feature mapping matrix to obtain a parameter pairing sequence;

[0024] Calculating the time correlation of the parameter pairing sequence to obtain a set of correlation coefficients, and constructing a time dimension feature matrix according to the set of correlation coefficients;

[0025] Feature vectors are extracted from the time dimension feature matrix to obtain a main feature vector, and correlation strength analysis is performed based on the main feature vector to obtain time correlation feature parameters.

[0026] Optionally, in a fourth implementation of the first aspect of the present invention, when the optical fiber link performs communication operations, the connection point is monitored online, and the bit error distribution, optical power mean, and timing jitter peak value in the current time window are recorded, and the recorded data obtained includes:

[0027] When the optical fiber link is performing communication operations, parallel bit error counting and real-time parameter collection are performed on each connection point of the optical fiber link to obtain a real-time monitoring data stream;

[0028] Perform time segmentation processing according to the real-time monitoring data stream to obtain a time window data group;

[0029] Performing distribution statistics on the bit error data in the time window data group to obtain the bit error distribution in the current time window;

[0030] Performing a mean operation on the optical power sampling values ​​in the time window data group to obtain the optical power mean value in the current time window;

[0031] Performing peak detection on the timing jitter sampling values ​​in the time window data group to obtain the timing jitter peak value in the current time window;

[0032] A data recording table entry is established according to the bit error distribution, the optical power mean value and the timing jitter peak value to obtain recorded data.

[0033] Optionally, in a fifth implementation of the first aspect of the present invention, the performing communication status evaluation on the optical fiber link according to the recorded data and the time-related characteristic parameter to obtain a communication status evaluation result includes:

[0034] Performing feature matching calculation on the recorded data and time-related feature parameters to obtain a feature deviation sequence;

[0035] Performing state distribution mapping on each connection point of the optical fiber link according to the characteristic deviation sequence to obtain a connection point state distribution set;

[0036] Determining the abnormality degree of the connection point state distribution set to obtain a quantitative parameter of the abnormality degree, and locating the connection point fault of the optical fiber link according to the quantitative parameter of the abnormality degree to obtain a probability distribution of the fault position;

[0037] A connection point status cluster analysis is performed on the fault location probability distribution to obtain a connection point status grade, and the optical fiber link communication status is evaluated and graded according to the connection point status grade to obtain a communication status evaluation result.

[0038] Optionally, in a sixth implementation of the first aspect of the present invention, performing a connection point state cluster analysis on the fault location probability distribution to obtain a connection point state level, and evaluating and grading the optical fiber link communication state according to the connection point state level, and obtaining a communication state evaluation result includes:

[0039] Performing multi-dimensional feature extraction on the probability distribution of the fault location to obtain a connection point feature vector, and performing cluster center calculation based on the connection point feature vector to obtain an initial cluster grouping;

[0040] Calculating the connection point state similarity for the initial cluster grouping to obtain a state similarity matrix, and grading the connection points according to the state similarity matrix to obtain connection point state grades;

[0041] The connection points of the connection point status level are sorted according to the priority to obtain a connection point status level sequence, and the communication status is graded and calculated according to the connection point status level sequence to obtain a communication status evaluation result.

[0042] A second aspect of the present invention provides an optical fiber communication status evaluation device, the optical fiber communication status evaluation device comprising:

[0043] The measurement module is used to insert the optical fiber connector into the optical fiber link, inject the dual-wavelength optical signal into the connection point corresponding to each connector, and measure the optical power value, timing jitter value and bit error rate test results under different code types and rate conditions at the connection point;

[0044] A correlation analysis module, which is used to count the bit errors under each code type and rate condition according to the bit error rate test result of the connection point, establish a bit error time distribution sequence, and correspondingly analyze the optical power mean and timing jitter peak in each time window of the bit error time distribution sequence to obtain time correlation characteristic parameters;

[0045] A detection module, used for online monitoring of the connection point when the optical fiber link is performing communication operation, recording the bit error distribution, optical power mean value and timing jitter peak value in the current time window, and obtaining recorded data;

[0046] The evaluation module is used to evaluate the communication status of the optical fiber link according to the recorded data and the time-related characteristic parameters to obtain a communication status evaluation result.

[0047] The third aspect of the present invention provides an optical fiber communication status assessment device, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected via a line; the at least one processor calls the instructions in the memory so that the optical fiber communication status assessment device executes the steps of the above-mentioned optical fiber communication status assessment method.

[0048] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the steps of the above-mentioned optical fiber communication status evaluation method.

[0049] The above-mentioned fiber optic communication status assessment method, device, equipment and storage medium, by inserting a fiber optic connector in series in the fiber optic link, injecting a dual-wavelength optical signal into each connection point, and measuring the optical power, timing jitter and bit error rate under different code types and rates. According to the bit error rate result, the error time distribution is statistically analyzed, and the time-related characteristic parameters are generated by combining the optical power mean and the timing jitter peak. During the link communication operation, the connection point is monitored online, and the bit error distribution, optical power mean and jitter peak in the current time window are recorded. The recorded data is compared with the time-related characteristic parameters to obtain the communication status assessment result. The present invention can combine the fiber optic communication status assessment method of multi-parameter, multi-condition real-time monitoring and time-related characteristic analysis to identify the complex fault characteristics that may occur in the fiber optic link, ensure the stability of the link, and improve the reliability and maintenance efficiency of the communication system.

[0050] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a schematic diagram of a first embodiment of a method for evaluating optical fiber communication status according to an embodiment of the present invention;

[0053] Figure 2 A schematic diagram of an embodiment of an optical fiber communication status evaluation device in an embodiment of the present invention;

[0054] Figure 3 Schematic diagram of an embodiment of an optical fiber communication status evaluation device in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device end including a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or device ends.

[0057] To facilitate understanding of this embodiment, a method for evaluating the state of optical fiber communication disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, the method comprises the following steps:

[0058] 101. Connect the optical fiber link to the optical fiber connector, use the dual-wavelength optical signal to inject the corresponding connection point of each connector, and measure the optical power value, timing jitter value and bit error rate test results under different code types and rates at the connection point;

[0059] In one embodiment of the present invention, the step of stringing an optical fiber link into an optical fiber connector, injecting a dual-wavelength optical signal into a connection point corresponding to each connector, and measuring the optical power value, timing jitter value, and bit error rate test results under different code types and rate conditions at the connection point includes: performing a dual-wavelength optical time domain reflection measurement on the optical fiber link to obtain a reflection characteristic curve of the optical fiber link, and calculating and locating the connection points of the optical fiber link according to the reflection characteristic curve to obtain connection point distribution parameters; stringing an optical fiber link into an optical fiber connector according to the connection point distribution parameters, and injecting a dual-wavelength optical signal into the connection point of each optical fiber connector, and injecting an optical signal signal parameters; perform optical power sampling and detection on the connection point according to the injected optical signal parameters to obtain the optical power time series of the connection point, and perform sliding average calculation on the optical power time series of the connection point to obtain the optical power value of the connection point; perform timing synchronization sampling on the connection point according to the optical power value to obtain the timing jitter sequence of the connection point, and perform window division and statistical analysis on the timing jitter sequence of the connection point to obtain the timing jitter value; perform code switching and rate adjustment on the connection point according to the optical power value and the timing jitter value to obtain the code rate combination scheme, and perform bit error rate test on the connection point according to the code rate combination scheme to obtain the bit error rate test result.

[0060] Specifically, the first step is to string the fiber link into the fiber connector. The installation position of the connector needs to be determined according to the actual communication requirements and the physical length of the fiber link. When stringing the fiber connector, first use a high-precision fiber cleaver to accurately cut the fiber. The cutting angle needs to be strictly controlled during cutting to ensure that the cut surface is perpendicular to the fiber axis. At the same time, the cut surface needs to ensure that the flatness of the end face meets the communication level requirements. After cutting, use a microscope to check the fiber end face to confirm that there are no scratches, debris, cracks, and other defects that affect light transmission. Then, the cut fiber end face is cleaned dust-free to remove dust and contaminants that may exist on the end face. Then, the pre-treated fiber is installed into the connector body, and the fiber is fixed in the connector through a heat curing or cold connection process. The curing process requires strict control of temperature and time parameters to ensure that the fiber fits tightly with the inner wall of the connector ferrule. After the connector is installed, a dual-wavelength laser with wavelengths of 1310nm and 1550nm is used as the light source. The dual-wavelength optical signal is coupled into the same optical fiber channel through the fiber coupler, and the optical signal is injected into the connection point corresponding to each connector to form a complete test optical path. The connection point at this time is the connection between the optical fiber connector and the optical fiber, and the quality of the connection point directly affects the subsequent transmission performance.

[0061] Specifically, after the fiber optic connector is inserted and the dual-wavelength optical signal is injected, the optical signal at the connection point is received by a high-sensitivity photodetector, and the reflection and transmission characteristics of the optical signal at the connection point are recorded. Since the connection point is a non-uniform point in the optical fiber link, Rayleigh scattering and Fresnel reflection will be generated. The detector detects the time domain waveform of these reflection signals to obtain the reflection characteristic curve at each connection point. The reflection characteristic curve records the change of the optical signal at the connection point. The peak on the curve corresponds to the position of the connection point, and the size of the peak reflects the reflection loss of the connection point. By performing time domain analysis on the reflection characteristic curve, the specific position of each connection point can be determined. At the same time, using the transmission characteristics of the dual-wavelength optical signal, the two wavelengths of 1310nm and 1550nm will produce different degrees of reflection at the connection point. This difference can be used to evaluate the quality of the connection point. By comparing the reflection characteristics of the two wavelengths, the interference signals caused by other factors such as optical fiber micro-bending are eliminated, and the real connection point characteristics are extracted. Based on these analysis results, the connection point distribution parameters are obtained, including the precise position of each connection point, reflection loss, insertion loss and other characteristic parameters.

[0062] Specifically, in the process of injecting dual-wavelength optical signals into each connection point according to the connection point distribution parameters, the output parameters of the dual-wavelength light source need to be set first. The dual-wavelength light source uses two working wavelengths of 1310nm and 1550nm, which correspond to the O band and C band in optical fiber communication, respectively, and can fully reflect the transmission characteristics of optical fiber at different wavelengths. Before injecting the optical signal, it is necessary to adjust the optical power output level of the two wavelengths to meet the measurement dynamic range requirements, and at the same time ensure that the power ratio of the two wavelengths is appropriate for subsequent analysis. Parameters such as the modulation bandwidth and pulse width of the optical signal also need to be set according to actual test requirements. The dual-wavelength optical signal is injected into each connection point in turn through the optical switch matrix to ensure that each connection point can receive a stable test optical signal. During the signal injection process, the output stability of the light source needs to be monitored in real time to avoid the influence of light source power fluctuations on the test results. The parameters of the optical signal injected at each connection point need to be recorded in detail, including the specific power values ​​and modulation parameters of the two wavelengths.

[0063] Specifically, according to the parameters of the injected dual-wavelength optical signal, during the process of measuring the optical power of the connection point, a high-precision optical power meter is used to sample and detect the optical power passing through the connection point. In order to obtain accurate power data, the sampling process needs to consider the time characteristics of the signal and set a suitable sampling frequency and sampling time window. A time series is established for the collected optical power data, and the sequence contains complete information on the change of optical power at the connection point over time. In order to eliminate the influence of random noise on the measurement results, the optical power time series is calculated by sliding average. The size of the sliding window needs to be reasonably set according to the signal characteristics, which should ensure that the noise can be effectively suppressed and avoid the loss of effective signal information due to excessive smoothing. Through the sliding average calculation, the steady-state optical power value of each connection point is obtained, and this power value reflects the insertion loss characteristics of the connection point. At the same time, the fluctuation of the optical power time series can also be used to evaluate the stability of the connection point.

[0064] Specifically, when performing timing synchronization sampling based on the obtained optical power value of the connection point, an accurate timing reference is first established. A high-precision clock source is used to generate a reference clock signal, and the frequency and phase stability of the clock signal directly affect the accuracy of subsequent measurements. The reference clock signal is distributed to each measurement module to ensure the timing synchronization of all measurement channels. When performing timing jitter measurement, a high-speed sampler is used to sample the optical signal passing through the connection point, and the sampling rate needs to be much higher than the signal bandwidth to ensure sufficient time resolution. During the sampling process, the amplitude of the optical signal and the corresponding timestamp information are recorded at the same time to form the timing jitter raw data containing the amplitude-time correspondence relationship. The collected data is time-axis calibrated to eliminate the influence of system delay and delay difference between channels, and an accurate timing jitter sequence is obtained. This sequence contains timing characteristic information such as phase noise and delay jitter caused by the connection point. Then the timing jitter sequence is divided into windows, and the selection of the window size needs to consider the periodicity and jitter characteristics of the signal. Statistical analysis is performed in each time window to calculate statistical parameters such as the jitter mean, standard deviation, and peak-to-peak value in the window, and ultimately the timing jitter value that characterizes the timing characteristics of the connection point is obtained.

[0065] Specifically, the signal transmission characteristics are determined according to the optical power value and timing jitter value of the connection point, and the test scheme of the code type and rate is formulated accordingly. First, a transmission performance evaluation model based on the optical power and timing jitter characteristics is constructed. The model takes into account the attenuation, dispersion, reflection and other effects of the optical signal at the connection point. According to the results of the evaluation model, a suitable code type combination is selected, including non-return-to-zero code, return-to-zero code, Manchester code and other encoding methods. Each code type has different spectrum characteristics and anti-interference capabilities. At the same time, based on the timing characteristics of the connection point, a reasonable transmission rate range is determined. The selection of the rate needs to comprehensively consider factors such as system bandwidth and timing jitter margin. By combining different code types and rate parameters, a complete test scheme matrix is ​​formed. The bit error rate test is performed on each code type-rate combination. During the test, a test code element sequence of a predetermined length is sent, the number of error code elements detected by the receiving end is counted, and the bit error rate is calculated. The test results fully reflect the performance characteristics of the connection point under different transmission conditions, providing an important basis for the subsequent communication status evaluation.

[0066] 102. According to the bit error rate test results of the connection point, the bit errors under each code type and rate condition are counted to establish a bit error time distribution sequence, and the optical power mean and timing jitter peak in each time window of the bit error time distribution sequence are analyzed to obtain time correlation characteristic parameters;

[0067] In one embodiment of the present invention, according to the bit error rate test results of the connection points, the bit errors under each code type and rate condition are counted to establish a bit error time distribution sequence, and the optical power mean and timing jitter peak in each time window of the bit error time distribution sequence are correspondingly analyzed to obtain time-related characteristic parameters, including: classifying and arranging the bit error rate test results by code type and rate to obtain classified bit error data, and performing time series segmentation on each code type and rate combination according to the classified bit error data to obtain a bit error time window sequence; counting and counting the bit errors in each time window according to the bit error time window sequence to obtain a bit error time distribution sequence; performing mean calculation in each time window in the bit error time distribution sequence to obtain an optical power mean sequence; performing peak extraction on the timing jitter value in each time window in the bit error time distribution sequence to obtain a timing jitter peak sequence; establishing a time correlation mapping according to the bit error time distribution sequence, the optical power mean sequence and the timing jitter peak sequence to obtain a time dimension feature matrix, and performing correlation analysis on the time dimension feature matrix to obtain time correlation characteristic parameters.

[0068] Specifically, in the process of classifying and arranging the bit error rate test results by code type and rate, it is necessary to establish a classification data structure according to different code types (including non-return-to-zero code, return-to-zero code, Manchester code, etc.) and different transmission rate combinations used in the test scheme. For each code type-rate combination, the corresponding error detection raw data is extracted, including the total number of transmitted code elements, the position of the detected error code elements, the number of error code elements, and other information. These raw data are sorted according to the classification standards of code type and rate to form structured classified error data. Then, the test data of each code type-rate combination is divided into time series according to the classified error data. The division of the time series needs to consider the signal transmission characteristics and the error distribution characteristics, and select the appropriate time window size. The division of the time window must ensure sufficient statistical sample size and reflect the time distribution law of the error. By dividing the test data of each code type-rate combination into time windows, an error time window sequence containing multiple time windows is obtained, and each time window contains complete error information within the time period.

[0069] Specifically, according to the obtained error time window sequence, the errors in each time window are counted in detail. The statistical process first determines the total number of transmitted code elements in the window, and then identifies and records the specific location and number of errors in the window. Each error position is marked, the time when the error occurs is recorded, and the total number of errors and error density in the window are counted. By counting and distributing errors in all time windows, a complete error time distribution sequence is formed, which reflects the distribution law of errors over time and contains the time characteristics and frequency information of the errors.

[0070] Specifically, when calculating the mean value of the optical power values ​​in each time window in the error time distribution sequence, it is necessary to first extract the corresponding optical power sampling data from each time window. Since the sampling frequency of optical power is usually higher than the time window division of error statistics, a bit error statistics window will contain multiple optical power sampling points. Perform arithmetic mean operation on all optical power sampling values ​​in each time window to eliminate the influence of random fluctuations in the sampling process. In the calculation process, it is necessary to eliminate abnormal sampling points that obviously deviate from the normal range to avoid these abnormal values ​​from interfering with the mean calculation. At the same time, it is necessary to consider the time consistency of the optical power data to ensure that the optical power sampling moment corresponds accurately to the bit error statistics window. The calculation process also needs to consider the response characteristics of the optical power measurement system, including the response time of the detector and the bandwidth limitation of the measurement system. The optical power mean is calculated for each time window one by one to form a complete data processing flow. Finally, an optical power mean sequence corresponding to the error time distribution sequence is obtained. This sequence reflects the power characteristics of optical signal transmission in different time windows and provides important parameter basis for subsequent time correlation analysis.

[0071] Specifically, when extracting the peak value of the timing jitter value in each time window, it is necessary to analyze the fluctuation of the timing jitter value in the window. Each time window contains a large number of timing jitter sampling points, which record the real-time changes of the signal phase offset. Before peak extraction, the original timing jitter data needs to be preprocessed, including removing baseline drift and high-frequency noise. By setting a multi-level threshold judgment mechanism, the data is preliminarily screened and possible peak points are identified. Then, the peak detection algorithm is used to identify the real jitter peak value in combination with the physical characteristics of the timing jitter. Peak detection needs to consider the cumulative effect of timing jitter and analyze the change trend between adjacent sampling points. At the same time, it is necessary to combine the clock recovery characteristics of the system to evaluate the effectiveness of the peak. The same peak extraction operation is performed on each time window, and finally a timing jitter peak sequence is formed. The sequence contains the maximum timing offset information in each time window and reflects the dynamic change characteristics of the signal timing stability.

[0072] Furthermore, the method of establishing a time correlation mapping according to the error time distribution sequence, optical power mean sequence and timing jitter peak sequence to obtain a time dimension feature matrix, and performing a correlation analysis on the time dimension feature matrix to obtain time correlation feature parameters includes: performing time dimension combined mapping on the error time distribution sequence, optical power mean sequence and timing jitter peak sequence to obtain an initial feature mapping matrix; cross-pairing the error distribution, optical power mean and timing jitter peak in each time window according to the initial feature mapping matrix to obtain a parameter pairing sequence; performing time correlation calculation on the parameter pairing sequence to obtain a set of correlation coefficients, and constructing a time dimension feature matrix according to the set of correlation coefficients; performing feature vector extraction on the time dimension feature matrix to obtain a main feature vector, and performing correlation strength analysis on the main feature vector to obtain time correlation feature parameters.

[0073] Specifically, when the time dimension combination mapping of the error time distribution sequence, the optical power mean sequence and the timing jitter peak sequence is performed, the three sequences are first aligned according to the time window label to ensure that the data at each time point corresponds one to one. A unified sampling point is established on the time axis, and for each sampling moment, the corresponding error distribution value, optical power mean and timing jitter peak data are extracted. By establishing a three-dimensional data space, the data points of these three types of sequences are mapped to the same coordinate system. The three coordinate components of each data point correspond to the values ​​of the error, optical power and timing jitter. The spatial distribution analysis of the mapped data point set is performed to examine the change law and distribution characteristics of the three parameters. At the same time, the integrity of the data needs to be considered. For data that may be missing at certain time points, the interpolation method is used to supplement it to ensure the continuity of the data. The mapping data of all time windows are arranged in chronological order to construct the initial feature mapping matrix. Each row of the matrix represents the state of a time window, each column corresponds to a parameter type, and the matrix element records the specific value of the parameter. This mapping process realizes the structured representation of the original data and lays the foundation for subsequent correlation analysis.

[0074] Specifically, when performing parameter cross-matching based on the data in the initial feature mapping matrix, it is necessary to combine the three parameters in each time window in pairs. First, pair the bit error distribution with the optical power mean, analyze the corresponding relationship between them, and record the data pairs formed by each pair of parameter values. Then pair the bit error distribution with the timing jitter peak, and also record their corresponding relationship. Finally, pair the optical power mean with the timing jitter peak to complete all possible parameter combinations. In the pairing process, it is also necessary to consider the physical meaning and dimensional relationship of the parameters and unify the parameters of different dimensions. Calculate the covariance and correlation coefficient of each group of paired parameters to evaluate the initial correlation between the parameters. Through this cross-matching method, three groups of parameter pairing sequences are obtained, each of which contains the joint change information of two parameters in the time dimension. Each element in the pairing sequence contains a time label, a parameter type identifier, and a specific parameter value. This structured data form facilitates subsequent correlation analysis.

[0075] Specifically, to calculate the temporal correlation of parameter pairing sequences, it is necessary to first define a suitable correlation calculation method. The grey correlation analysis method is used to calculate the correlation coefficient between each pair of parameters. During the calculation process, the parameter sequence is first dimensionless to eliminate the influence of dimension differences on the correlation calculation. Then the correlation coefficient between the parameter sequences is calculated, and each time point corresponds to a correlation coefficient value. The weighted average of the correlation coefficients of all time points is performed to obtain the overall correlation. At the same time, the mutual information entropy method is used to evaluate the nonlinear correlation between the parameters to obtain the mutual information coefficient. The correlation coefficient and the mutual information coefficient are combined to form a complete set of correlation coefficients. The time dimension feature matrix is ​​constructed based on the set of correlation coefficients. Each element of the matrix reflects the correlation strength between different parameters at different time scales. This feature matrix combines linear and nonlinear correlation characteristics and can fully reflect the interaction relationship between parameters.

[0076] Specifically, the principal component analysis method is used to extract the eigenvectors of the time dimension feature matrix. First, the feature matrix is ​​standardized and the covariance matrix is ​​calculated. The covariance matrix is ​​decomposed by eigenvalue to obtain the eigenvalues ​​and corresponding eigenvectors. The eigenvectors are sorted according to the size of the eigenvalues, and the main eigenvectors are selected as the main eigenvectors. These main eigenvectors represent the main change modes of the system, and each eigenvector corresponds to an independent change mode. The components of the main eigenvectors are physically interpreted, and the weights of different parameters in each principal component are analyzed. The correlation strength analysis is performed based on the main eigenvectors, and the contribution of each parameter to the main change mode is calculated. By comprehensively evaluating the importance of each principal component and the contribution of the parameters, the time-related characteristic parameters reflecting the overall characteristics of the system are obtained. These parameters contain the main characteristics and key change modes of the system, which can effectively guide the subsequent communication status evaluation.

[0077] 103. When the optical fiber link is performing communication operation, the connection point is monitored online, and the bit error distribution, optical power mean value and timing jitter peak value in the current time window are recorded to obtain recorded data;

[0078] In one embodiment of the present invention, when the optical fiber link is performing communication operations, the connection points are monitored online, and the bit error distribution, optical power mean and timing jitter peak value in the current time window are recorded to obtain recorded data, including: when the optical fiber link is performing communication operations, parallel bit error counting and real-time parameter collection are performed on each connection point of the optical fiber link to obtain a real-time monitoring data stream; time segmentation processing is performed according to the real-time monitoring data stream to obtain a time window data group; distribution statistics are performed on the bit error data in the time window data group to obtain the bit error distribution in the current time window; mean calculation is performed on the optical power sampling values ​​in the time window data group to obtain the optical power mean value in the current time window; peak detection is performed on the timing jitter sampling values ​​in the time window data group to obtain the timing jitter peak value in the current time window; data recording table entries are established according to the bit error distribution, optical power mean and timing jitter peak value to obtain recorded data.

[0079] Specifically, when the optical fiber link is communicating, it is necessary to monitor each connection point in real time at the same time. The monitoring system is equipped with an independent error detection unit for each connection point, and a parallel processing architecture is used to realize multi-point synchronous monitoring. The error detection unit collects the digital signal passing through the connection point, detects the error in the signal and counts it in real time. At the same time, an optical power detector and a timing analyzer are arranged at each connection point to collect the optical power value and timing parameters respectively. The optical power detector adopts a high-speed sampling method to continuously sample the intensity of the optical signal passing through the connection point, and the timing analyzer captures the timing characteristics of the signal by triggering sampling. The sampling clocks of these three types of monitoring equipment are synchronized to ensure the time consistency of the data. The data collected by each monitoring point is transmitted to the central processing unit in real time through the data acquisition network, forming a real-time monitoring data stream containing error counts, optical power sampling values ​​and timing parameters.

[0080] Specifically, when the acquired real-time monitoring data stream is processed by time segmentation, it is first necessary to determine the appropriate time window size. The selection of the window size needs to take into account the characteristics of the communication system, including factors such as signal bandwidth, bit error rate level, and system response time. The continuous data stream is divided according to the set time window, and each time window contains a complete set of monitoring data. The data in each time window is synchronously grouped, and the bit error count, optical power sampling value, and timing parameters in the same time window are placed in the same data group. The start and end times of each data group are marked by a timestamp, and a time index of the data is established. In this way, a series of time window data groups arranged in chronological order are obtained, and each data group contains complete monitoring information within a specific time period.

[0081] Specifically, when performing distribution statistics on the bit error data in the time window data group, first normalize the bit error count data in the window. Calculate the number of bit errors per unit time to obtain the time series of the bit error rate. Analyze the time distribution characteristics of the bit errors, and count the frequency and time interval of the bit errors. Establish a histogram of the bit error distribution to reflect the distribution density of the bit errors in the time window. At the same time, analyze the aggregation characteristics of the bit errors to identify whether there are sudden bit errors. Combine these statistical features to form a complete description of the bit error distribution, which reflects the changes in the communication quality in the current time window.

[0082] Specifically, when performing mean calculation on the optical power sampling values ​​in the time window data group, the sampling data needs to be preprocessed first. Eliminate outliers and glitches in the sampling sequence to ensure the validity of the data. Then perform arithmetic mean calculation on the preprocessed sampling sequence to obtain the optical power mean in the time window. This mean reflects the average energy level of the optical signal in the current time window. At the same time, calculate the standard deviation of the sampling value to evaluate the stability of the optical power. When performing peak detection on the timing jitter sampling values ​​in the time window data group, use the sliding window method to scan the timing data. Identify the local maximum point and determine the valid jitter peak value based on the set threshold. Record the detected peaks in chronological order to obtain a peak sequence of timing jitter.

[0083] Specifically, the statistically obtained bit error distribution, optical power mean, and timing jitter peak are organized into record entries according to a predefined data structure. The entries contain the identification information of the time window, the values ​​of various parameters, and necessary status flags. These record entries are stored in chronological order to form complete monitoring record data. The record data not only contains the specific values ​​of each parameter, but also retains the corresponding relationship between the parameters, providing complete data support for subsequent status evaluation.

[0084] 104. Evaluate the communication status of the optical fiber link according to the recorded data and the time-related characteristic parameters to obtain a communication status evaluation result.

[0085] In one embodiment of the present invention, the communication status of the optical fiber link is evaluated according to the characteristic parameters associated with the recorded data and time to obtain a communication status evaluation result, which includes: performing feature matching calculations on the characteristic parameters associated with the recorded data and time to obtain a feature deviation sequence; performing state distribution mapping on each connection point of the optical fiber link according to the characteristic deviation sequence to obtain a connection point state distribution set; determining the degree of abnormality on the connection point state distribution set to obtain a quantitative parameter of the degree of abnormality, and locating the connection point fault of the optical fiber link according to the quantitative parameter of the degree of abnormality to obtain a probability distribution of the fault position; performing connection point state clustering analysis on the fault position probability distribution to obtain a connection point state grade, and evaluating and grading the communication status of the optical fiber link according to the connection point state grade to obtain a communication status evaluation result.

[0086] Specifically, when performing feature matching calculations on recorded data and time-related feature parameters, it is first necessary to align the feature dimensions of the two sets of data to ensure that the error distribution, optical power mean, and timing jitter peak in the recorded data correspond one-to-one to the corresponding dimensions in the time-related feature parameters. In each feature dimension, the difference value between the recorded data and the corresponding time-related feature parameter is calculated to form a preliminary feature difference sequence. The difference sequence is normalized to eliminate the dimensional differences between different feature dimensions so that the difference values ​​of each dimension are comparable. At the same time, considering the different importance of different feature dimensions, a weight coefficient is introduced to weight the difference values ​​of each dimension. By reconstructing the time series of the weighted difference values, a complete feature deviation sequence is obtained. This sequence reflects the degree of deviation of the current recorded data relative to the historical feature parameters, and each element in the sequence contains time information and deviation information of multidimensional features.

[0087] Specifically, when mapping the state distribution of each connection point of the optical fiber link according to the characteristic deviation sequence, it is necessary to first establish a spatial position model of the connection point. The data in the characteristic deviation sequence is reorganized according to the physical position of the connection point to form a spatial distribution sequence. For each connection point position, all characteristic deviation data of the point are collected, including the deviation values ​​of the three dimensions of bit error, optical power and timing jitter. By constructing a multidimensional state space, the characteristic deviation data of each connection point is mapped to a point in the state space. Considering the temporal continuity of the characteristic deviation, the discrete points in the state space are interpolated to form a continuous state distribution surface. The probability density of the state distribution surface is estimated to obtain the state distribution characteristics of each connection point. The final connection point state distribution set contains the state distribution information of all connection points, and each connection point corresponds to a complete state distribution description.

[0088] Specifically, when determining the degree of abnormality of the connection point state distribution set, it is first necessary to establish a normal state benchmark model. Based on the statistical analysis of historical data, determine the normal range of variation of each feature dimension. Compare the current state distribution with the normal state benchmark and calculate the state deviation. Using the multi-dimensional anomaly detection algorithm, comprehensively consider the abnormal characteristics of the three dimensions of bit error rate, optical power and timing jitter to obtain a quantitative index of the degree of abnormality. This quantitative index reflects the degree to which the connection point state deviates from the normal range. According to the quantitative parameters of the degree of abnormality, the fault probability of each connection point of the optical fiber link is evaluated and a fault location model is established. Considering the propagation characteristics of the fault and the mutual influence between the connection points, a probability graph model is used to describe the spatial distribution characteristics of the fault. Through iterative calculation, the fault probability value of each connection point is obtained to form a complete fault location probability distribution.

[0089] Specifically, when performing connection point state clustering analysis on the probability distribution of fault locations, a multidimensional clustering algorithm is used to classify the connection point states. According to the fault probability value, the degree of abnormality, and the distribution of each dimensional feature, the connection point state space is divided into multiple clusters. Each cluster represents a typical state level. By calculating the cluster center and cluster boundary, the discrimination criteria for different state levels are defined. The state parameters of each connection point are graded to determine the state level to which it belongs. Based on the state level distribution of the connection point, an overall state evaluation model for the optical fiber link is established. Considering the location weight and importance of the connection point, the state level of each connection point is weighted and combined. Through the comprehensive evaluation algorithm, the connection point state level is mapped to the communication state level of the optical fiber link, and finally the overall communication state evaluation result is obtained. This evaluation result reflects the overall operating status of the optical fiber link and provides a basis for subsequent maintenance decisions.

[0090] Furthermore, the fault location probability distribution is subjected to connection point status clustering analysis to obtain a connection point status grade, and the optical fiber link communication status is evaluated and graded according to the connection point status grade to obtain a communication status evaluation result, including: multi-dimensional feature extraction is performed on the fault location probability distribution to obtain a connection point feature vector, and cluster center calculation is performed according to the connection point feature vector to obtain an initial cluster grouping; connection point status similarity calculation is performed on the initial cluster grouping to obtain a state similarity matrix, and connection points are graded according to the state similarity matrix to obtain a connection point status grade; each connection point of the connection point status grade is sorted according to priority to obtain a connection point status grade sequence, and communication status grading calculation is performed according to the connection point status grade sequence to obtain a communication status evaluation result.

[0091] Specifically, when extracting multi-dimensional features of the probability distribution of fault locations, it is necessary to extract key features that can characterize the state of the connection points from the probability distribution data. At each connection point, the statistical features of the fault probability are calculated, including the probability mean, variance, peak value, etc. At the same time, the time evolution characteristics of the fault probability are considered, and dynamic information such as the probability change rate and periodic characteristics are extracted. These statistical features and dynamic features are combined to construct the initial feature set. In order to reflect the spatial correlation between connection points, it is also necessary to calculate the correlation of the fault probabilities between adjacent connection points and extract the spatial distribution features. All extracted features are subjected to dimensionality reduction processing, and the most representative feature dimensions are selected through principal component analysis. The connection point feature vector finally obtained contains the main feature information of the probability distribution. According to the distribution characteristics of the feature vector, the K-means clustering algorithm is used to determine the number and position of the initial clustering centers. Through iterative optimization, the positions of the clustering centers are continuously adjusted until the clustering results tend to be stable, and the initial clustering groups are obtained, each of which represents a typical connection point state.

[0092] When calculating the similarity of the connection point states for the initial cluster grouping, it is first necessary to define a suitable similarity metric. Considering the multidimensional characteristics of the connection point states, the weighted Euclidean distance is used as the basic similarity calculation method. The distance of the feature vector is calculated between each pair of connection points, while considering the weight factor of the feature dimension. In addition to the distance in the feature space, it is also necessary to consider the positional relationship of the connection points in the physical space, and introduce the spatial distance attenuation factor. The feature space distance and the physical space distance are combined to obtain a complete similarity calculation formula. The similarity is calculated for all connection point pairs to form a similarity matrix. This matrix is ​​a symmetric matrix, and the matrix elements represent the degree of similarity between the states of the connection points. According to the structural characteristics of the similarity matrix, the spectral clustering algorithm is used to grade the connection points to obtain a more refined classification of the connection point states.

[0093] When prioritizing the connection point status level, multiple factors need to be considered comprehensively. First, the connection points are weighted according to their location importance in the optical fiber link. The connection points close to the key nodes have higher location weights. Considering the fault impact range of the connection point, the fault propagation factor is calculated. The connection point with a larger impact range has a higher priority. Combined with the historical fault records of the connection point, a reliability evaluation index is established. The connection points are comprehensively scored according to these evaluation parameters, and the status of all connection points is sorted according to the scoring results. The sorting results form a connection point status level sequence, which reflects the priority of connection point fault handling. According to the connection point status level sequence, the communication status is graded and calculated, and the number distribution and spatial distribution characteristics of the connection points of each level are considered to establish an overall optical fiber link status evaluation model. By setting the status evaluation threshold, the communication status of the optical fiber link is divided into multiple levels, and finally the communication status evaluation result is obtained, which fully reflects the operation status of the optical fiber link.

[0094] In this embodiment, by inserting a fiber optic connector in series in the fiber optic link, a dual-wavelength optical signal is injected into each connection point to measure the optical power, timing jitter, and bit error rate under different code types and rates. The error time distribution is statistically analyzed based on the bit error rate results, and the time-related characteristic parameters are generated by combining the optical power mean and the timing jitter peak. During the link communication operation, the connection point is monitored online, and the bit error distribution, optical power mean, and jitter peak in the current time window are recorded. The recorded data is compared with the time-related characteristic parameters to obtain the communication status evaluation results. The present invention can combine the optical fiber communication status evaluation method of multi-parameter, multi-condition real-time monitoring and time-related characteristic analysis to identify the complex fault characteristics that may occur in the optical fiber link, ensure the stability of the link, and improve the reliability and maintenance efficiency of the communication system.

[0095] The above describes the optical fiber communication status evaluation method in the embodiment of the present invention. The following describes the optical fiber communication status evaluation device in the embodiment of the present invention. Figure 2 , an embodiment of the optical fiber communication status evaluation device in the embodiment of the present invention includes:

[0096] The measurement module 201 is used to connect the optical fiber link to the optical fiber connector, inject the dual-wavelength optical signal into the connection point corresponding to each connector, and measure the optical power value, timing jitter value and bit error rate test results under different code types and rates at the connection point;

[0097] The correlation analysis module 202 is used to collect statistics on the bit errors under each code type and rate condition according to the bit error rate test result of the connection point, establish a bit error time distribution sequence, and correspondingly analyze the optical power mean and timing jitter peak in each time window of the bit error time distribution sequence to obtain time correlation characteristic parameters;

[0098] The detection module 203 is used to perform online monitoring of the connection point when the optical fiber link is performing communication operations, record the bit error distribution, optical power mean value and timing jitter peak value in the current time window, and obtain recorded data;

[0099] The evaluation module 204 is used to evaluate the communication status of the optical fiber link according to the recorded data and the time-related characteristic parameters to obtain a communication status evaluation result.

[0100] In an embodiment of the present invention, the optical fiber communication status evaluation device runs the above-mentioned optical fiber communication status evaluation method. The optical fiber communication status evaluation device inserts an optical fiber connector in series in the optical fiber link, injects a dual-wavelength optical signal into each connection point, and measures the optical power, timing jitter, and bit error rate under different code types and rates. The error time distribution is statistically calculated based on the bit error rate result, and the time-related characteristic parameters are generated by combining the optical power mean and the timing jitter peak. During the link communication operation, the connection point is monitored online, the bit error distribution, optical power mean and jitter peak in the current time window are recorded, and the recorded data is compared with the time-related characteristic parameters to obtain the communication status evaluation result. The present invention can combine the optical fiber communication status evaluation method of multi-parameter, multi-condition real-time monitoring and time-related characteristic analysis to identify the complex fault characteristics that may occur in the optical fiber link, ensure the stability of the link, and improve the reliability and maintenance efficiency of the communication system.

[0101] above Figure 2 The optical fiber communication status evaluation device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The optical fiber communication status evaluation device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0102] Figure 3 3 is a schematic diagram of the structure of an optical fiber communication status evaluation device provided by an embodiment of the present invention. The optical fiber communication status evaluation device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 310 (for example, one or more processors) and a memory 320, and one or more storage media 330 (for example, one or more mass storage device terminals) storing application programs 333 or data 332. Among them, the memory 320 and the storage medium 330 may be temporary storage or permanent storage. The program stored in the storage medium 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the optical fiber communication status evaluation device 300. Furthermore, the processor 310 may be configured to communicate with the storage medium 330, and execute a series of instruction operations in the storage medium 330 on the optical fiber communication status evaluation device 300 to implement the steps of the above-mentioned optical fiber communication status evaluation method.

[0103] The optical fiber communication status evaluation device 300 may also include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input and output interfaces 360, and / or one or more operating systems 331, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 3The structure of the optical fiber communication status evaluation device shown does not constitute a limitation on the optical fiber communication status evaluation device provided by the present invention, and may include more or less components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0104] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the optical fiber communication status evaluation method.

[0105] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0106] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0107] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating optical fiber communication status, characterized in that: The optical fiber communication status assessment method comprises: The optical fiber link is connected to the optical fiber connector, and a dual-wavelength optical signal is injected into the connection point corresponding to each connector, and the optical power value, timing jitter value and bit error rate test results under different code types and rate conditions at the connection point are measured; the optical fiber link is connected to the optical fiber connector, and a dual-wavelength optical signal is injected into the connection point corresponding to each connector, and the optical power value, timing jitter value and bit error rate test results under different code types and rate conditions at the connection point are measured, including: performing dual-wavelength optical time domain reflection measurement on the optical fiber link to obtain a reflection characteristic curve of the optical fiber link, and calculating the number and position of the connection points of the optical fiber link according to the reflection characteristic curve to obtain connection point distribution parameters; according to the connection point distribution parameters, the optical fiber link is connected to the optical fiber Connector, and inject dual-wavelength optical signals into the connection point of each optical fiber connector, and inject optical signal parameters; perform optical power sampling and detection on the connection point according to the injected optical signal parameters to obtain the optical power time series of the connection point, and perform sliding average calculation on the optical power time series of the connection point to obtain the optical power value of the connection point; perform timing synchronization sampling on the connection point according to the optical power value to obtain the timing jitter sequence of the connection point, and perform window division and statistical analysis on the timing jitter sequence of the connection point to obtain the timing jitter value; perform code switching and rate adjustment on the connection point according to the optical power value and the timing jitter value to obtain a code rate combination scheme, and perform bit error rate test on the connection point according to the code rate combination scheme to obtain the bit error rate test result; According to the bit error rate test result of the connection point, the bit errors under each code type and rate condition are counted to establish a bit error time distribution sequence, and the optical power mean and timing jitter peak value in each time window of the bit error time distribution sequence are correspondingly analyzed to obtain time correlation characteristic parameters; When the optical fiber link is performing communication operation, the connection point is monitored online, and the bit error distribution, optical power mean value and timing jitter peak value in the current time window are recorded to obtain recorded data; The communication status of the optical fiber link is evaluated according to the recorded data and the time-related characteristic parameters to obtain a communication status evaluation result.

2. The optical fiber communication status evaluation method according to claim 1, characterized in that: According to the bit error rate test result of the connection point, the bit errors under each code type and rate condition are counted, and a bit error time distribution sequence is established. At the same time, the optical power mean and timing jitter peak in each time window of the bit error time distribution sequence are correspondingly analyzed to obtain the time-related characteristic parameters including: Classifying and arranging the bit error rate test results by code type and rate to obtain classified bit error data, and performing time series segmentation on each code type and rate combination according to the classified bit error data to obtain a bit error time window sequence; Counting and counting the bit errors in each time window according to the bit error time window sequence to obtain a bit error time distribution sequence; Performing mean calculation in each time window in the bit error time distribution sequence to obtain an optical power mean sequence; Extracting the peak value of the timing jitter in each time window in the bit error time distribution sequence to obtain a timing jitter peak sequence; A time correlation mapping is established according to the error time distribution sequence, the optical power mean sequence and the timing jitter peak sequence to obtain a time dimension feature matrix, and a correlation analysis is performed on the time dimension feature matrix to obtain time correlation feature parameters.

3. The optical fiber communication status evaluation method according to claim 2, characterized in that: The time correlation mapping is established according to the error time distribution sequence, the optical power mean sequence and the timing jitter peak sequence to obtain a time dimension feature matrix, and the time dimension feature matrix is ​​subjected to correlation analysis to obtain time correlation feature parameters, including: Performing time dimension combined mapping on the bit error time distribution sequence, the optical power mean sequence and the timing jitter peak sequence to obtain an initial feature mapping matrix; Cross-pairing the bit error distribution, the optical power mean, and the timing jitter peak value in each time window according to the initial feature mapping matrix to obtain a parameter pairing sequence; Calculating the time correlation of the parameter pairing sequence to obtain a set of correlation coefficients, and constructing a time dimension feature matrix according to the set of correlation coefficients; Feature vectors are extracted from the time dimension feature matrix to obtain a main feature vector, and correlation strength analysis is performed based on the main feature vector to obtain time correlation feature parameters.

4. The optical fiber communication status evaluation method according to claim 1, characterized in that: When the optical fiber link is performing communication operation, the connection point is monitored online, and the error distribution, optical power mean value and timing jitter peak value in the current time window are recorded, and the recorded data obtained include: When the optical fiber link is performing communication operations, parallel bit error counting and real-time parameter collection are performed on each connection point of the optical fiber link to obtain a real-time monitoring data stream; Perform time segmentation processing according to the real-time monitoring data stream to obtain a time window data group; Performing distribution statistics on the bit error data in the time window data group to obtain the bit error distribution in the current time window; Performing a mean operation on the optical power sampling values ​​in the time window data group to obtain the optical power mean value in the current time window; Performing peak detection on the timing jitter sampling values ​​in the time window data group to obtain the timing jitter peak value in the current time window; A data recording table entry is established according to the bit error distribution, the optical power mean value and the timing jitter peak value to obtain recorded data.

5. The optical fiber communication status evaluation method according to claim 1, characterized in that: The communication status evaluation of the optical fiber link is performed according to the recorded data and the time-related characteristic parameters to obtain the communication status evaluation result, which includes: Performing feature matching calculation on the recorded data and time-related feature parameters to obtain a feature deviation sequence; Performing state distribution mapping on each connection point of the optical fiber link according to the characteristic deviation sequence to obtain a connection point state distribution set; Determining the abnormality degree of the connection point state distribution set to obtain a quantitative parameter of the abnormality degree, and locating the connection point fault of the optical fiber link according to the quantitative parameter of the abnormality degree to obtain a probability distribution of the fault position; A connection point status cluster analysis is performed on the fault location probability distribution to obtain a connection point status grade, and the optical fiber link communication status is evaluated and graded according to the connection point status grade to obtain a communication status evaluation result.

6. The optical fiber communication status evaluation method according to claim 5, characterized in that: The performing of connection point status cluster analysis on the probability distribution of the fault location to obtain the connection point status level, and evaluating and grading the optical fiber link communication status according to the connection point status level to obtain the communication status evaluation result includes: Performing multi-dimensional feature extraction on the probability distribution of the fault location to obtain a connection point feature vector, and performing cluster center calculation based on the connection point feature vector to obtain an initial cluster grouping; Calculating the connection point state similarity for the initial cluster grouping to obtain a state similarity matrix, and grading the connection points according to the state similarity matrix to obtain connection point state grades; The connection points of the connection point status level are sorted according to the priority to obtain a connection point status level sequence, and the communication status is graded and calculated according to the connection point status level sequence to obtain a communication status evaluation result.

7. An optical fiber communication status evaluation device, characterized in that: The optical fiber communication status evaluation device comprises: The measuring module is used to string a fiber optic link into a fiber optic connector, inject a dual-wavelength optical signal into a connection point corresponding to each connector, and measure the optical power value, timing jitter value, and bit error rate test results under different code types and rate conditions at the connection point; the fiber optic link is stringed into a fiber optic connector, and the dual-wavelength optical signal is injected into the connection point corresponding to each connector, and the optical power value, timing jitter value, and bit error rate test results under different code types and rate conditions at the connection point are measured, including: performing dual-wavelength optical time domain reflection measurement on the fiber optic link to obtain a reflection characteristic curve of the fiber optic link, and calculating the number and position of the connection points of the fiber optic link according to the reflection characteristic curve to obtain connection point distribution parameters; and performing a measurement on the fiber optic link string according to the connection point distribution parameters. Insert the optical fiber connector, and inject the dual-wavelength optical signal into the connection point of each optical fiber connector, and inject the optical signal parameters; perform optical power sampling and detection on the connection point according to the injected optical signal parameters to obtain the optical power time series of the connection point, and perform sliding average calculation on the optical power time series of the connection point to obtain the optical power value of the connection point; perform timing synchronization sampling on the connection point according to the optical power value to obtain the timing jitter sequence of the connection point, and perform window division and statistical analysis on the timing jitter sequence of the connection point to obtain the timing jitter value; perform code switching and rate adjustment on the connection point according to the optical power value and the timing jitter value to obtain a code rate combination scheme, and perform bit error rate test on the connection point according to the code rate combination scheme to obtain a bit error rate test result; A correlation analysis module, which is used to count the bit errors under each code type and rate condition according to the bit error rate test result of the connection point, establish a bit error time distribution sequence, and correspondingly analyze the optical power mean and timing jitter peak in each time window of the bit error time distribution sequence to obtain time correlation characteristic parameters; A detection module, used for online monitoring of the connection point when the optical fiber link is performing communication operation, recording the bit error distribution, optical power mean value and timing jitter peak value in the current time window, and obtaining recorded data; The evaluation module is used to evaluate the communication status of the optical fiber link according to the recorded data and the time-related characteristic parameters to obtain a communication status evaluation result.

8. An optical fiber communication status assessment device, characterized in that: The optical fiber communication status assessment device comprises: a memory and at least one processor, wherein the memory stores instructions; The at least one processor calls the instructions in the memory to enable the optical fiber communication status evaluation device to perform the steps of the optical fiber communication status evaluation method according to any one of claims 1 to 7.

9. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the steps of the optical fiber communication status evaluation method as described in any one of claims 1 to 7 are implemented.

Images