An unattended optical fiber distribution management method and system

Abstract

The present invention relates to the technical field of optical fiber distribution management, and specifically to an unattended optical fiber distribution management method and system. First, by monitoring the optical fiber lines of the optical fiber distribution frame, key data such as optical power, optical attenuation, signal-to-noise ratio, and bit error rate are obtained, and based on this, fault monitoring of the optical fiber lines is carried out; the specific steps include judging whether the optical power, optical attenuation, signal-to-noise ratio, etc. of the optical fiber line are abnormal, and calculating the transmission anomaly monitoring value; if it exceeds the set threshold, it is determined that there is a fault in the line; if a fault occurs, fault analysis will also be carried out in combination with environmental data to obtain the cause of the fault; if there is no fault in the line, the environmental anomaly degree of the distribution frame is analyzed through environmental data; finally, according to the fault analysis result and the environmental anomaly degree, anomaly early warning is carried out to ensure the normal operation and maintenance of the optical fiber distribution frame. This method can effectively improve the reliability of anomaly monitoring and the fault diagnosis efficiency of the optical fiber distribution frame.

Description

Technical Field

[0001] The present invention relates to the technical field of optical fiber distribution management, and specifically to an unattended optical fiber distribution management method and system. Background Art

[0002] With the continuous development of information technology, optical fiber communication technology has been widely applied in fields such as communication, network, and data transmission. Due to its high-speed, long-distance, and large-capacity transmission characteristics, the optical fiber network has gradually become the core of modern communication systems. However, as the scale of the optical fiber network continues to expand, the management and maintenance of the optical fiber distribution system have become increasingly complex and cumbersome. Traditional optical fiber distribution management methods mostly rely on manual operations and face many challenges, such as difficult personnel management, high maintenance costs, low work efficiency, and other problems.

[0003] In order to improve the automation and intelligence level of optical fiber distribution management, more and more technical solutions have begun to attempt to monitor and manage the optical fiber lines corresponding to optical fiber distribution equipment through computer and Internet of Things technologies. For example, by using devices such as optical fiber sensors, monitoring cameras, and intelligent terminals, real-time monitoring of optical fiber lines is achieved, relevant data is collected, and processed and analyzed through a central control system, thereby improving the management efficiency and reliability of the optical fiber network. However, these existing technical solutions still have some limitations. Optical fiber line failures can be caused not only by the line itself but also by abnormal environments where the optical fiber distribution equipment is located. When the vibration amplitude of the optical fiber distribution equipment is large or the humidity and temperature of the environment where it is located are abnormal, it will cause abnormalities in the interfaces of the optical fiber lines, thereby causing failures in the optical fiber lines. Existing technologies mostly focus on optical fiber lines and ignore the potential impact of optical fiber distribution equipment and its environment on optical fiber transmission performance, resulting in low optical fiber distribution management efficiency.

[0004] Therefore, an unattended optical fiber distribution management method and system are proposed. Summary of the Invention

[0005] The object of the present invention is to provide an unattended optical fiber distribution management method and system. First, by monitoring the optical fiber lines of the optical fiber distribution frame, key data such as optical power, optical attenuation, signal-to-noise ratio, and bit error rate are obtained, and based on this, fault monitoring of the optical fiber lines is carried out; the specific steps include determining whether the optical power, optical attenuation, signal-to-noise ratio, etc. of the optical fiber line are abnormal, and calculating the transmission anomaly monitoring value; if this value exceeds the set threshold, it is determined that the line has a fault; if a fault occurs, fault analysis is also carried out in combination with environmental data to obtain the cause of the fault; if no fault occurs in the line, the environmental anomaly degree of the distribution frame is analyzed through environmental data; finally, according to the fault analysis result and the environmental anomaly degree, anomaly warning is carried out to ensure the normal operation and maintenance of the optical fiber distribution frame.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An unattended optical fiber distribution management method, comprising:

[0008] S10. Monitor the optical fiber distribution frame to obtain the optical fiber device data and the optical fiber distribution frame environment data of the optical fiber distribution frame;

[0009] The optical fiber device data includes [[t dq -t0, t dq the optical power data, optical attenuation data, signal-to-noise ratio data, and bit error rate data of each optical fiber line corresponding to the optical fiber distribution frame within the time period; t dq represents the current time; t0 represents a set time threshold;

[0010] S20. According to the optical fiber device data, perform fault monitoring on each optical fiber line corresponding to the optical fiber distribution frame; the specific steps include: according to the optical fiber device data, obtain the optical power abnormal monitoring value, optical attenuation abnormal monitoring value, and signal-to-noise ratio abnormal monitoring value of each optical fiber line corresponding to the optical fiber distribution frame;

[0011] According to the optical power abnormal monitoring value, the optical attenuation abnormal monitoring value, the signal-to-noise ratio abnormal monitoring value, and the bit error rate of the optical fiber line, calculate the transmission abnormal monitoring value of each optical fiber line;

[0012] When the transmission abnormal monitoring value is greater than the set threshold, determine that the optical fiber line has a fault; otherwise, determine that the optical fiber line has no fault;

[0013] S30. When the optical fiber line has a fault, perform fault analysis according to the transmission abnormal monitoring value and the optical fiber distribution frame environment data to obtain a fault analysis result;

[0014] S40. When all the optical fiber lines have no faults, obtain the environmental abnormal degree of the optical fiber distribution frame according to the optical fiber distribution frame environment data;

[0015] S50. Perform abnormal warning according to the environmental abnormal degree and the fault analysis result.

[0016] Further, the optical fiber distribution frame environment data includes: [t dq -t1, t dq the vibration data of the optical fiber distribution frame, the environmental temperature data of the optical fiber distribution frame, the environmental humidity data of the optical fiber distribution frame, and the dust data of the optical fiber distribution frame within the time period; t1 represents the time interval from the last maintenance of the optical fiber distribution frame to the current time.

[0017] Further, the calculation formula of the optical power abnormal monitoring value is:

[0018]

[0019] Among them, glyc i It is represented by the optical power abnormality monitoring value of the i-th optical fiber line; glpj i and glfc i Respectively expressed as [t dq -t0,t0] the optical power mean and optical power variance of the i-th optical fiber line in the time period; glbz i It is expressed as the average standard optical power corresponding to the i-th optical fiber line; ggl max and ggl min Respectively expressed as [t dq where α1, α2, and α3 represent the optical power mean coefficient, optical power variance coefficient, and optical power fluctuation coefficient, respectively; and exp() represents an exponential function with the natural constant e as the base.

[0020] Furthermore, the process of obtaining the transmission abnormality monitoring value includes:

[0021] The transmission abnormality monitoring value is obtained based on the optical power abnormality monitoring value, optical attenuation abnormality monitoring value, signal-to-noise ratio abnormality monitoring value, and bit error rate. The calculation formula is:

[0022] csyc i =exp(β1*max(glyc i -glbz i ,0)+β2*max(sjyc i -sjbz i ,0)

[0023] +β3*max(xzyc i -xzbz i ,0)+β4*max(wml i -wmbz i ,0));

[0024] Among them, csyc i It is expressed as the transmission abnormality monitoring value of the i-th optical fiber line; glyc i 、sjyc i 、xzyc i and wml i They are respectively represented as the optical power abnormality monitoring value, optical attenuation abnormality monitoring value, signal-to-noise ratio abnormality monitoring value and bit error rate corresponding to the i-th optical fiber line; glbz i 、sjbz i 、xzbz i and wmbz iThey are respectively represented as the standard monitoring values of optical power, optical attenuation, signal-to-noise ratio, and standard bit error rate of the set i-th optical fiber line; β1, β2, β3, and β4 are respectively represented as the optical power anomaly coefficient, optical attenuation anomaly coefficient, signal-to-noise ratio anomaly coefficient, and bit error rate anomaly coefficient.

[0025] Furthermore, based on the transmission anomaly monitoring values and the optical fiber distribution frame environment data, a fault analysis is carried out, and the obtained fault analysis results include:

[0026] Based on the transmission anomaly monitoring values, obtain the proportion of optical fiber lines with anomalies; based on the optical fiber distribution frame environment data, obtain the vibration anomaly value of the optical fiber distribution frame, the environmental temperature anomaly value of the optical fiber distribution frame, the environmental humidity anomaly value of the optical fiber distribution frame, and the dust anomaly value of the optical fiber distribution frame;

[0027] Input the proportion of optical fiber lines with anomalies, the vibration anomaly value of the optical fiber distribution frame, the environmental temperature anomaly value of the optical fiber distribution frame, the environmental humidity anomaly value of the optical fiber distribution frame, and the dust anomaly value of the optical fiber distribution frame into the optical fiber environment non-linear regression model to obtain the environmental anomaly probability of the optical fiber distribution frame; when the environmental anomaly probability of the optical fiber distribution frame is greater than the set probability threshold, the fault analysis result is that the optical fiber distribution frame environment is abnormal; otherwise, the fault analysis result is that the optical fiber distribution frame environment is not abnormal.

[0028] Furthermore, the process of obtaining the vibration anomaly value of the optical fiber distribution frame includes:

[0029] Screen out the abnormal time periods that meet abnormal condition 1 or abnormal condition 2; abnormal condition 1 is that the vibration frequency is greater than the standard vibration frequency; abnormal condition 2 is that the vibration amplitude is greater than the standard vibration amplitude; based on the vibration frequency and vibration amplitude corresponding to each abnormal time period, obtain the vibration anomaly value of the optical fiber distribution frame, and the calculation formula is:

[0030]

[0031] Among them, zdyc represents the vibration anomaly value of the optical fiber distribution frame; M represents the number of vibration abnormal time periods; ycsc j 、zdpl j and zdfd j respectively represent the duration, vibration amplitude of the vibration frequency of the j-th abnormal time period; χ1 and χ2 respectively represent the first vibration anomaly coefficient and the second vibration anomaly coefficient.

[0032] Further, when all the optical fiber lines are free of faults, obtaining the environmental anomaly degree of the optical fiber distribution frame according to the environmental data of the optical fiber distribution frame includes: obtaining the vibration anomaly value of the optical fiber distribution frame, the environmental temperature anomaly value of the optical fiber distribution frame, the environmental humidity anomaly value of the optical fiber distribution frame, and the dust anomaly value of the optical fiber distribution frame according to the environmental data of the optical fiber distribution frame;

[0033] Obtaining the environmental anomaly degree according to the vibration anomaly value of the optical fiber distribution frame, the environmental temperature anomaly value of the optical fiber distribution frame, the environmental humidity anomaly value of the optical fiber distribution frame, and the dust anomaly value of the optical fiber distribution frame.

[0034] An unattended optical fiber distribution management system includes:

[0035] An optical fiber distribution data acquisition unit: used to monitor the optical fiber distribution frame and obtain the optical fiber device data and the environmental data of the optical fiber distribution frame of the optical fiber distribution frame;

[0036] A fault monitoring unit: used to monitor the faults of each optical fiber line corresponding to the optical fiber distribution frame according to the optical fiber device data;

[0037] A fault analysis unit: used to perform fault analysis according to the transmission anomaly monitoring value and the environmental data of the optical fiber distribution frame when the optical fiber line has a fault, and obtain a fault analysis result;

[0038] An environmental anomaly degree acquisition unit: used to identify the environmental anomaly degree of the optical fiber distribution frame according to the environmental data of the optical fiber distribution frame when all the optical fiber lines are free of faults;

[0039] An anomaly warning unit: used to perform anomaly warning according to the environmental anomaly degree and the fault analysis result.

[0040] Further, the optical fiber distribution data acquisition unit includes: the optical fiber device data includes the optical power data, optical attenuation data, signal-to-noise ratio data, and bit error rate data of each optical fiber line corresponding to the optical fiber distribution frame within the time period of [t dq -t0, t dq ; t dq represents the current time; t0 represents the set time threshold; the environmental data of the optical fiber distribution frame includes the vibration data of the optical fiber distribution frame, the environmental temperature data of the optical fiber distribution frame, the environmental humidity data of the optical fiber distribution frame, and the dust data of the optical fiber distribution frame within the time period of [t dq -t1, t dq ; t1 represents the time interval from the last maintenance of the optical fiber distribution frame to the current time.

[0041] Further, the fault monitoring unit includes: obtaining the optical power anomaly monitoring value, optical attenuation anomaly monitoring value, and signal-to-noise ratio anomaly monitoring value of each optical fiber line according to the optical fiber device data; calculating the transmission anomaly monitoring value of each optical fiber line according to the optical power anomaly monitoring value, optical attenuation anomaly monitoring value, signal-to-noise ratio anomaly monitoring value, and bit error rate of the optical fiber line;

[0042] When the transmission anomaly monitoring value is greater than the set threshold, it is determined that the optical fiber line has a fault; otherwise, it is determined that the optical fiber line has no fault.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0044] 1. The present invention obtains the optical power data, optical attenuation data, signal-to-noise ratio data, and bit error rate data of each optical fiber line on the optical fiber distribution frame, calculates the transmission anomaly monitoring value of the optical fiber line based on this, and identifies whether the optical fiber line has a fault. After identifying a fault, fault analysis is performed based on the optical fiber distribution frame environment data to obtain the fault analysis result. This method can accurately identify whether the cause of the fault is the abnormal environment where the optical fiber distribution frame is located based on the state of the optical fiber line and the optical fiber distribution frame environment data, and then manage the optical fiber distribution frame.

[0045] 2. The present invention performs anomaly identification based on the optical power corresponding to the optical fiber line, and obtains the optical power anomaly monitoring value according to the optical power mean value, optical power variance, and optical power extreme value. By combining multiple statistical features such as the mean value, variance, and extreme value, the monitoring system can more comprehensively understand the operating state of the optical fiber line. This multi-dimensional monitoring method can avoid misjudgment caused by a single index, and thus improve the management efficiency of the optical fiber distribution frame.

[0046] 3. The present invention realizes the accurate analysis of the optical fiber line fault by comprehensively considering the transmission anomaly monitoring value and the environment data of the optical fiber distribution frame. According to the transmission anomaly monitoring value of the optical fiber line, calculate the proportion of the optical fiber lines with anomalies; and combine the environment data of the optical fiber distribution frame, including vibration anomaly value, environmental temperature anomaly value, humidity anomaly value, and dust anomaly value, to further analyze the environmental state of the optical fiber distribution frame. This intelligent and automated method improves the accuracy of optical fiber line fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a flowchart of an unattended optical fiber distribution management method of the present invention;

[0048] Figure 2 is a structural diagram of an unattended optical fiber distribution management system of the present invention;

[0049] Figure 3Flowchart for obtaining fault analysis results provided by an embodiment of the present invention. Detailed implementation manners

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] The present invention provides an unattended optical fiber distribution management method, which is applied to an unattended optical fiber distribution management system. For the specific method flowchart and system structure diagram, refer to Figure 1 and Figure 2 .

[0052] Embodiment 1

[0053] Refer to Figure 1 S10 in, and S10 is applied to the optical fiber distribution data acquisition unit of an unattended optical fiber distribution management system.

[0054] Further, the optical fiber device data includes the optical power data, optical attenuation data, signal-to-noise ratio data, and bit error rate data of each optical fiber line corresponding to the optical fiber distribution frame within the time period of [t dq -t0, t dq ; t dq represents the current time; t0 represents a set time threshold, and t0 can be set to 5 minutes, 10 minutes, etc.; the optical fiber distribution frame environment data includes: the vibration data, environmental temperature data, environmental humidity data, and dust data of the optical fiber distribution frame within the time period of [t dq -t1, t dq ; t1 represents the time interval from the last maintenance of the optical fiber distribution frame to the current time;

[0055] The optical fiber lines corresponding to the optical fiber distribution frame include all the optical fiber lines between the optical fiber distribution frame to be managed and the next passing station optical fiber distribution frame;

[0056] The optical power data is the optical power collected at the optical fiber output port of the optical fiber distribution frame at intervals of a set time within the time period of [t dq -t0, t dq through an optical power meter, and the set time can be set to 0.1 s, 0.5 s, 1 s, etc.;

[0057] The optical attenuation data is within the time period of [t dq -t0, t dqThe optical attenuation value of the optical fiber line collected at intervals of the set time within a time period, from the current optical fiber distribution frame to the optical fiber distribution frame of the next passing station; the set time can be set to 0.1s, 0.5s, 1s, etc.

[0058] The signal-to-noise ratio data is [t dq -t0, t dq The optical attenuation value of the optical fiber line collected at intervals of the set time within a time period, from the current optical fiber distribution frame to the optical fiber distribution frame of the next passing station; the set time can be set to 0.1s, 0.5s, 1s, etc.

[0059] In this embodiment, this step provides an all-round perspective on the operating state of the optical fiber distribution frame by monitoring optical fiber device data and environmental data. The optical fiber device data mainly reflects the signal quality, while the environmental data involves the impact of the physical environment on the operation of the device (such as temperature, humidity, vibration, etc.). This dual monitoring can more accurately identify the root cause of line failures.

[0060] Referring to Figure 1 S20 in, S20 is applied to the fault monitoring unit of an unattended optical fiber distribution management system.

[0061] Further, referring to Figure 3 , the specific steps include: obtaining the optical power anomaly monitoring value, optical attenuation anomaly monitoring value, and signal-to-noise ratio anomaly monitoring value of each optical fiber line corresponding to the optical fiber distribution frame according to the optical fiber device data;

[0062] Calculating the transmission anomaly monitoring value of each optical fiber line according to the optical power anomaly monitoring value, the optical attenuation anomaly monitoring value, the signal-to-noise ratio anomaly monitoring value, and the bit error rate of the optical fiber line;

[0063] When the transmission anomaly monitoring value is greater than the set threshold, it is determined that the optical fiber line has a fault; otherwise, it is determined that the optical fiber line has no fault.

[0064] This step of this embodiment obtains the optical power data, optical attenuation data, signal-to-noise ratio data, and bit error rate data of each optical fiber line on the optical fiber distribution frame, calculates the transmission anomaly monitoring value of the optical fiber line based on this, and identifies whether the optical fiber line has a fault. After identifying a fault, fault analysis is performed based on the optical fiber distribution frame environmental data to obtain the fault analysis result. This method can accurately identify whether the cause of the fault is due to the abnormal environment where the optical fiber distribution frame is located based on the state of the optical fiber line and the optical fiber distribution frame environmental data, and then manage the optical fiber distribution frame.

[0065] Further, the calculation formula for the optical power anomaly monitoring value is:

[0066]

[0067] where glyc i represents the abnormal monitoring value of the optical power of the i-th optical fiber line; glpj i and glfc i respectively represent the mean value and variance of the optical power of the i-th optical fiber line within the time period of [t dq -t0, t0]; glbz i represents the standard mean value of the optical power corresponding to the i-th optical fiber line; ggl max and ggl min respectively represent the maximum value and minimum value of the optical power of the i-th optical fiber line within the time period of [t dq -t0, t0]; α1, α2, and α3 respectively represent the optical power mean coefficient, optical power variance coefficient, and optical power fluctuation coefficient; exp() represents the exponential function with the natural constant e as the base; α1, α2, and α3 are defaulted to be Specifically, they can also be changed according to the actual situation.

[0068] This step of this embodiment identifies abnormalities based on the optical power corresponding to the optical fiber line, and obtains the abnormal monitoring value of the optical power based on the mean value of the optical power, the variance of the optical power, and the extreme value of the optical power. By combining multiple statistical features such as the mean value, variance, and extreme value, the monitoring system can more comprehensively understand the operating state of the optical fiber line. This multi-dimensional monitoring method can avoid misjudgment that may be caused by a single indicator, thereby improving the management efficiency of the optical fiber distribution frame.

[0069] Furthermore, the abnormal monitoring value of the optical attenuation is obtained through non-linear regression based on the mean value and variance of the optical attenuation data. In this embodiment, a support vector machine is selected to perform non-linear regression to obtain the abnormal monitoring value of the optical attenuation.

[0070] Furthermore, the abnormal monitoring value of the signal-to-noise ratio is obtained through non-linear regression based on the mean value and variance of the signal-to-noise ratio data. In this embodiment, a support vector machine is selected to perform non-linear regression to obtain the abnormal monitoring value of the signal-to-noise ratio.

[0071] Furthermore, the process of obtaining the abnormal monitoring value of the transmission includes:

[0072] Obtaining the abnormal monitoring value of the transmission based on the abnormal monitoring value of the optical power, the abnormal monitoring value of the optical attenuation, the abnormal monitoring value of the signal-to-noise ratio, and the bit error rate. The calculation formula is:

[0073] csyc i = exp(β1 * max(glyc i - glbz i , 0) + β2 * max(sjyc i - sjbz i , 0)

[0074] +β3 * max(xzyc i -xzbz i , 0) + β4 * max(wml i -wmbz i , 0));

[0075] Wherein, csyc i represents the transmission anomaly monitoring value of the i-th optical fiber line; glyc i , sjyc i , xzyc i and wml i respectively represent the optical power anomaly monitoring value, optical attenuation anomaly monitoring value, signal-to-noise ratio anomaly monitoring value, and bit error rate corresponding to the i-th optical fiber line; glbz i , sjbz i , xzbz i and wmbz i respectively represent the set optical power standard monitoring value, optical attenuation standard monitoring value, signal-to-noise ratio standard monitoring value, and standard bit error rate of the i-th optical fiber line; β1, β2, β3, and β4 respectively represent the optical power anomaly coefficient, optical attenuation anomaly coefficient, signal-to-noise ratio anomaly coefficient, and bit error rate anomaly coefficient; β1, β2, β3, and β4 are defaulted to 0.25, and can also be changed according to the actual situation specifically.

[0076] To verify the effectiveness of the optical fiber line fault identification method provided in this embodiment, this embodiment obtains the optical fiber device data of 5 optical fiber distribution frames at different time periods, and conducts fault monitoring on the optical fiber lines to obtain the fault identification accuracy rate and precision rate, specifically referring to Table 1.

[0077] Table 1 Fault Identification Accuracy Rate and Precision Rate

[0078] Optical fiber distribution frame serial number Accuracy rate Precision rate 1 94.26％ 92.83％ 2 93.79％ 93.70％ 3 93.28％ 93.81％ 4 94.13％ 94.10％ 5 93.55％ 94.05％

[0079] Referring to Table 1, it can be seen that the method provided in this embodiment has an accuracy rate of about 94% and a precision rate of about 93% in identifying optical fiber faults, that is, this method can effectively identify optical fiber faults.

[0080] This step of this embodiment integrates multiple key transmission parameters (including optical power anomaly monitoring value, optical attenuation anomaly monitoring value, signal-to-noise ratio anomaly monitoring value, and bit error rate), and this method can monitor the optical fiber line from multiple dimensions. This multi-dimensional monitoring method can capture the anomalies in the line more comprehensively than the single-parameter monitoring.

[0081] Referring to Figure 1 S30 in, S30 is applied to the fault analysis unit of an unattended optical fiber distribution management system.

[0082] Further, based on the transmission anomaly monitoring value and the fiber optic distribution frame environment data, a fault analysis is performed, and the obtained fault analysis result includes:

[0083] Based on the transmission anomaly monitoring value, obtain the proportion of fiber optic lines with anomalies; based on the fiber optic distribution frame environment data, obtain the vibration anomaly value of the fiber optic distribution frame, the environmental temperature anomaly value of the fiber optic distribution frame, the environmental humidity anomaly value of the fiber optic distribution frame, and the dust anomaly value of the fiber optic distribution frame;

[0084] Input the proportion of fiber optic lines with anomalies, the vibration anomaly value of the fiber optic distribution frame, the environmental temperature anomaly value of the fiber optic distribution frame, the environmental humidity anomaly value of the fiber optic distribution frame, and the dust anomaly value of the fiber optic distribution frame into the fiber optic environment non-linear regression model to obtain the environmental anomaly probability of the fiber optic distribution frame; when the environmental anomaly probability of the fiber optic distribution frame is greater than the set probability threshold, the fault analysis result is that the fiber optic distribution frame environment is abnormal; otherwise, the fault analysis result is that the fiber optic distribution frame environment is not abnormal.

[0085] This step of this embodiment realizes the accurate analysis of fiber optic line faults by comprehensively considering the transmission anomaly monitoring value and the environment data of the fiber optic distribution frame. According to the transmission anomaly monitoring value of the fiber optic line, calculate the proportion of fiber optic lines with anomalies; and in combination with the environment data of the fiber optic distribution frame, including the vibration anomaly value, the environmental temperature anomaly value, the humidity anomaly value, and the dust anomaly value, further analyze the environmental state of the fiber optic distribution frame. This intelligent and automated method can improve the accuracy of fiber optic line fault diagnosis.

[0086] Further, the process of obtaining the vibration anomaly value of the fiber optic distribution frame includes:

[0087] Screen out the abnormal time periods that meet abnormal condition one or abnormal condition two; abnormal condition one is that the vibration frequency is greater than the standard vibration frequency; abnormal condition two is that the vibration amplitude is greater than the standard vibration amplitude; based on the vibration frequency and vibration amplitude corresponding to each abnormal time period, obtain the vibration anomaly value of the fiber optic distribution frame, and the calculation formula is:

[0088]

[0089] where, zdyc represents the vibration anomaly value of the fiber optic distribution frame; M represents the number of vibration abnormal time periods; ycsc j , zdpl j and zdfd j respectively represent the duration, vibration amplitude of the vibration frequency of the j-th abnormal time period; χ1 and χ2 respectively represent the first vibration anomaly coefficient and the second vibration anomaly coefficient; χ1 and χ2 are both defaulted to 0.5, and can also be changed according to the actual situation specifically.

[0090] In this embodiment, by screening out abnormal time periods with vibration frequencies greater than the standard vibration frequency or vibration amplitudes greater than the standard vibration amplitude, it is possible to clearly distinguish normal operations from potential abnormal vibrations. This helps to accurately identify abnormalities in the fiber optic distribution frame, avoid misjudging minor irrelevant vibrations as faults, thereby improving the accuracy of fault monitoring and reducing false alarms and missed alarms.

[0091] Further, the process of obtaining the abnormal value of the environmental temperature of the fiber optic distribution frame includes:

[0092] Screen out abnormal time periods with environmental temperatures greater than the standard environmental temperature; obtain the average environmental temperature corresponding to each abnormal time period, and calculate the abnormal value of the environmental temperature of the fiber optic distribution frame. The calculation formula is:

[0093]

[0094] where wdyc represents the abnormal value of the environmental temperature of the fiber optic distribution frame; Q represents the number of temperature abnormal time periods; wdsc q and wd q represent the duration and average temperature of the q-th temperature abnormal time period respectively; η1 and η2 represent the first temperature abnormal coefficient and the second temperature abnormal coefficient respectively; η1 and η2 are defaulted to 0.5, and can also be changed according to the actual situation specifically.

[0095] Further, the process of obtaining the abnormal value of the environmental humidity of the fiber optic distribution frame and the abnormal value of the dust of the fiber optic distribution frame can refer to the process of obtaining the abnormal value of the environmental temperature of the fiber optic distribution frame.

[0096] Further, in order to verify the effectiveness of the unattended fiber optic distribution management method provided in this embodiment, this embodiment obtains fiber optic device data and fiber optic distribution frame environmental data of 5 fiber optic distribution frames at different time periods, and conducts fault monitoring on the fiber optic lines; after identifying a fault, fault analysis is performed based on the transmission abnormal monitoring value and the fiber optic distribution frame environmental data to obtain the fault analysis accuracy rate and precision rate, specifically referring to Table 2.

[0097] Table 2 Fault analysis accuracy rate and precision rate

[0098] Optical fiber distribution frame serial number Accuracy rate Precision rate 1 90.35％ 91.39％ 2 89.73％ 91.54％ 3 90.16％ 90.73％ 4 89.61％ 91.10％ 5 89.55％ 90.58％

[0099] Referring to Table 2, it can be seen that the method provided in this embodiment has an accuracy rate of about 90% and a precision rate of about 91% in fiber optic fault analysis, that is, this method not only has high accuracy in overall classification, but also performs well in the precision of fault prediction.

[0100] Refer to Figure 1S40 in [the above text] is applied to the environmental anomaly degree acquisition unit of an unattended optical fiber distribution management system.

[0101] Further, when all the optical fiber lines have no faults, obtaining the environmental anomaly degree of the optical fiber distribution frame based on the environmental data of the optical fiber distribution frame includes: obtaining the vibration anomaly value of the optical fiber distribution frame, the environmental temperature anomaly value of the optical fiber distribution frame, the environmental humidity anomaly value of the optical fiber distribution frame, and the dust anomaly value of the optical fiber distribution frame based on the environmental data of the optical fiber distribution frame;

[0102] Based on the vibration anomaly value of the optical fiber distribution frame, the environmental temperature anomaly value of the optical fiber distribution frame, the environmental humidity anomaly value of the optical fiber distribution frame, and the dust anomaly value of the optical fiber distribution frame, obtain the environmental anomaly degree through a non - linear regression model. In this embodiment, a neural network model is selected for non - linear regression to obtain the environmental anomaly degree.

[0103] In this embodiment, by monitoring various environmental factors (including temperature, humidity, vibration, and dust) of the optical fiber distribution frame, potential environmental problems can be identified in advance. This intelligent environmental anomaly monitoring method can greatly improve the management efficiency, reliability, and maintenance effect of the optical fiber distribution frame, providing important support for the stable operation of the optical fiber network.

[0104] Refer to Figure 1 S50 in [the above text] is applied to the anomaly warning unit of an unattended optical fiber distribution management system.

[0105] Further, when the environmental anomaly degree is greater than the set anomaly degree threshold or the fault analysis result is that the environment of the optical fiber distribution frame is abnormal, an anomaly warning for the optical fiber distribution frame is carried out.

[0106] Embodiment 2

[0107] S10. Monitor the optical fiber distribution frame to obtain the optical fiber device data and the environmental data of the optical fiber distribution frame.

[0108] Further, the optical fiber device data includes the optical power data, optical attenuation data, signal - to - noise ratio data, and bit error rate data of each optical fiber line corresponding to the optical fiber distribution frame within the time period of [t dq - t0, t dq ; t dq represents the current time; t0 represents the set time threshold, and t0 can be set to 5 minutes, 10 minutes, etc.; the environmental data of the optical fiber distribution frame includes: [t dq - t1, t dqVibration data, environmental temperature data, environmental humidity data, and dust data of the fiber optic distribution frame within a time period; t1 represents the time interval from the last maintenance of the fiber optic distribution frame to the current time.

[0109] S20. According to the fiber optic device data, perform fault monitoring on each fiber optic line corresponding to the fiber optic distribution frame.

[0110] Further, the specific steps include: according to the fiber optic device data, obtain the optical power anomaly monitoring value, optical attenuation anomaly monitoring value, and signal-to-noise ratio anomaly monitoring value of each fiber optic line corresponding to the fiber optic distribution frame;

[0111] According to the optical power anomaly monitoring value, the optical attenuation anomaly monitoring value, the signal-to-noise ratio anomaly monitoring value, and the bit error rate of the fiber optic line, calculate the transmission anomaly monitoring value of each fiber optic line;

[0112] When the transmission anomaly monitoring value is greater than the set threshold, determine that the fiber optic line has a fault; otherwise, determine that the fiber optic line has no fault.

[0113] Further, the calculation formula of the optical power anomaly monitoring value is:

[0114]

[0115] where glyc i represents the optical power anomaly monitoring value of the i-th fiber optic line; glpj i and glfc i respectively represent the average optical power and the optical power variance of the i-th fiber optic line within the time period [t dq -t0, t0]; glbz i represents the standard average optical power corresponding to the i-th fiber optic line; ggl max and ggl min respectively represent the maximum optical power and the minimum optical power of the i-th fiber optic line within the time period [t dq -t0, t0]; α1, α2, and α3 respectively represent the optical power average coefficient, the optical power variance coefficient, and the optical power fluctuation coefficient; exp() represents the exponential function with the natural constant e as the base.

[0116] Further, the optical attenuation anomaly monitoring value is obtained through non-linear regression based on the mean and variance of the optical attenuation data. In this embodiment, a support vector machine is selected to perform non-linear regression to obtain the optical attenuation anomaly monitoring value.

[0117] Further, the abnormal monitoring value of the signal-to-noise ratio is obtained through non-linear regression based on the mean and variance of the optical attenuation data. In this embodiment, a support vector machine is selected to perform non-linear regression to obtain the abnormal monitoring value of the optical attenuation.

[0118] Further, the process of obtaining the abnormal monitoring value of the transmission includes:

[0119] Obtaining the abnormal monitoring value of the transmission based on the abnormal monitoring value of the optical power, the abnormal monitoring value of the optical attenuation, the abnormal monitoring value of the signal-to-noise ratio, and the bit error rate. The calculation formula is:

[0120]

[0121] where csyc i represents the abnormal monitoring value of the transmission of the i-th optical fiber line; glyc i , sjyc i , xzyc i and wml i respectively represent the abnormal monitoring value of the optical power, the abnormal monitoring value of the optical attenuation, the abnormal monitoring value of the signal-to-noise ratio, and the bit error rate corresponding to the i-th optical fiber line; glbz i , sjbz i , xzbz i and wmbz i respectively represent the standard monitoring value of the optical power, the standard monitoring value of the optical attenuation, the standard monitoring value of the signal-to-noise ratio, and the standard bit error rate set for the i-th optical fiber line; β1, β2, β3, and β4 respectively represent the abnormal coefficient of the optical power, the abnormal coefficient of the optical attenuation, the abnormal coefficient of the signal-to-noise ratio, and the abnormal coefficient of the bit error rate.

[0122] S30. When a fault exists in the optical fiber line, perform fault analysis based on the abnormal monitoring value of the transmission and the optical fiber distribution frame environment data to obtain a fault analysis result.

[0123] Further, performing fault analysis based on the abnormal monitoring value of the transmission and the optical fiber distribution frame environment data to obtain a fault analysis result includes:

[0124] Obtaining the proportion of the optical fiber lines with abnormalities based on the abnormal monitoring value of the transmission; obtaining the abnormal vibration value of the optical fiber distribution frame, the abnormal temperature value of the optical fiber distribution frame environment, the abnormal humidity value of the optical fiber distribution frame environment, and the abnormal dust value of the optical fiber distribution frame based on the optical fiber distribution frame environment data;

[0125] Input the proportion of abnormal optical fiber lines, the abnormal value of the vibration of the optical fiber distribution frame, the abnormal value of the ambient temperature of the optical fiber distribution frame, the abnormal value of the ambient humidity of the optical fiber distribution frame, and the abnormal value of the dust of the optical fiber distribution frame into the non-linear regression model of the optical fiber environment to obtain the abnormal probability of the optical fiber distribution frame environment; when the abnormal probability of the optical fiber distribution frame environment is greater than the set probability threshold, the fault analysis result is that the optical fiber distribution frame environment is abnormal; otherwise, the fault analysis result is that the optical fiber distribution frame environment is not abnormal.

[0126] Further, the process of obtaining the abnormal value of the vibration of the optical fiber distribution frame includes:

[0127] Screen out the abnormal time periods that meet abnormal condition 1 or abnormal condition 2; abnormal condition 1 is that the vibration frequency is greater than the standard vibration frequency; abnormal condition 2 is that the vibration amplitude is greater than the standard vibration amplitude; based on the vibration frequency and vibration amplitude corresponding to each abnormal time period, obtain the abnormal value of the vibration of the optical fiber distribution frame, and the calculation formula is:

[0128]

[0129] Among them, zdyc represents the abnormal value of the vibration of the optical fiber distribution frame; M represents the number of abnormal vibration time periods; ycsc j 、zdpl j and zdfd j respectively represent the duration, vibration amplitude of the vibration frequency of the jth abnormal time period; χ1 and χ2 respectively represent the first vibration abnormal coefficient and the second vibration abnormal coefficient.

[0130] Further, the process of obtaining the abnormal value of the ambient temperature of the optical fiber distribution frame includes:

[0131] Screen out the abnormal time periods when the ambient temperature is greater than the standard ambient temperature; obtain the average ambient temperature corresponding to each abnormal time period, and calculate the abnormal value of the ambient temperature of the optical fiber distribution frame, and the calculation formula is:

[0132]

[0133] Among them, wdyc represents the abnormal value of the ambient temperature of the optical fiber distribution frame; Q represents the number of temperature abnormal time periods; wdsc . q and wd q respectively represent the duration and average temperature of the qth temperature abnormal time period; η1 and η2 respectively represent the first temperature abnormal coefficient and the second temperature abnormal coefficient.

[0134] Further, the process of obtaining the abnormal value of the ambient humidity of the optical fiber distribution frame and the abnormal value of the dust of the optical fiber distribution frame can refer to the process of obtaining the abnormal value of the ambient temperature of the optical fiber distribution frame.

[0135] Further, to verify the effectiveness of the unattended optical fiber distribution management method provided in this embodiment, this embodiment obtains optical fiber device data and optical fiber distribution frame environment data of optical fiber distribution frames in 3 different regions at different time periods, and monitors the faults of optical fiber lines; after identifying a fault, fault analysis is performed based on the transmission anomaly monitoring value and the optical fiber distribution frame environment data to obtain the fault analysis accuracy rate and precision rate, specifically referring to Table 3.

[0136] Table 3 Fault Analysis Accuracy Rate and Precision Rate

[0137] Area serial number Accuracy rate Precision rate 1 90.64％ 92.15％ 2 90.71％ 91.84％ 3 89.93％ 92.34％

[0138] Referring to Table 3, it can be seen that for the optical fiber distribution frames in different regions, the accuracy rate of optical fiber fault analysis by the method provided in this embodiment is about 90%, and the precision rate is about 92%, that is, this method can accurately analyze line faults.

[0139] S40. When all the optical fiber lines have no faults, obtain the environmental anomaly degree of the optical fiber distribution frame based on the optical fiber distribution frame environment data.

[0140] Further, based on the optical fiber distribution frame environment data, obtain the vibration anomaly value of the optical fiber distribution frame, the environmental temperature anomaly value of the optical fiber distribution frame, the environmental humidity anomaly value of the optical fiber distribution frame, and the dust anomaly value of the optical fiber distribution frame;

[0141] Based on the vibration anomaly value of the optical fiber distribution frame, the environmental temperature anomaly value of the optical fiber distribution frame, the environmental humidity anomaly value of the optical fiber distribution frame, and the dust anomaly value of the optical fiber distribution frame, obtain the environmental anomaly degree through a non - linear regression model. In this embodiment, a neural network model is selected for non - linear regression to obtain the environmental anomaly degree.

[0142] S50. Perform anomaly warning based on the environmental anomaly degree and the fault analysis result.

[0143] Further, when the environmental anomaly degree is greater than the set anomaly degree threshold or the fault analysis result is that the optical fiber distribution frame environment is abnormal, perform an optical fiber distribution frame anomaly warning.

[0144] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An unattended optical fiber distribution management method, characterized in that, Including: S10. Monitor the fiber optic distribution frame to obtain the fiber optic device data and the fiber optic distribution frame environment data of the fiber optic distribution frame; The optical fiber device data includes dq -t0, t dq the optical power data, optical attenuation data, signal-to-noise ratio data, and bit error rate data of each optical fiber line corresponding to the optical fiber distribution frame during the time period; t dq represents the current time; t0 represents the set time threshold; S20. Based on the fiber optic device data, perform fault monitoring on each fiber optic line corresponding to the fiber optic distribution frame; The specific steps include: Based on the fiber optic device data, obtain the optical power anomaly monitoring value, the optical attenuation anomaly monitoring value, and the signal-to-noise ratio anomaly monitoring value of each fiber optic line corresponding to the fiber optic distribution frame; Based on the optical power anomaly monitoring value, the optical attenuation anomaly monitoring value, the signal-to-noise ratio anomaly monitoring value, and the bit error rate of the fiber optic line, calculate the transmission anomaly monitoring value of each fiber optic line; When the transmission anomaly monitoring value is greater than the set threshold, determine that the fiber optic line has a fault; otherwise, determine that the fiber optic line has no fault; S30. When the fiber optic line has a fault, perform fault analysis based on the transmission anomaly monitoring value and the fiber optic distribution frame environment data to obtain a fault analysis result; S40. When all the fiber optic lines have no faults, obtain the environmental anomaly degree of the fiber optic distribution frame based on the fiber optic distribution frame environment data; S50. Perform anomaly warning based on the environmental anomaly degree and the fault analysis result.

2. The unattended optical fiber distribution management method according to claim 1, wherein, The environmental data of the optical fiber distribution frame includes: dq - the vibration data of the optical fiber distribution frame, the environmental temperature data of the optical fiber distribution frame, the environmental humidity data of the optical fiber distribution frame, and the dust data of the optical fiber distribution frame within the time period of [t dq ; t1 represents the time interval from the last maintenance of the optical fiber distribution frame to the current time.

3. The unattended optical fiber distribution management method according to claim 1, characterized in that The calculation formula for the optical power anomaly monitoring value is: Among them, glyc i represents the optical power abnormal monitoring value of the i-th optical fiber line; glpj i and glfc i respectively represent the average optical power and the optical power variance of the i-th optical fiber line within the time period of [t dq - t0, t0]; glbz i represents the standard average optical power corresponding to the i-th optical fiber line; ggl max and ggl min respectively represent the maximum optical power and the minimum optical power of the i-th optical fiber line within the time period of [t dq - t0, t0]; α1, α2 and α3 respectively represent the average optical power coefficient, the optical power variance coefficient and the optical power fluctuation coefficient; exp() represents the exponential function with the natural constant e as the base.

4. The unattended optical fiber distribution management method according to claim 1, characterized in that The process of obtaining the transmission anomaly monitoring value includes: Obtain the transmission anomaly monitoring value based on the optical power anomaly monitoring value, the optical attenuation anomaly monitoring value, the signal-to-noise ratio anomaly monitoring value, and the bit error rate. The calculation formula is: Among them, csyc i represents the transmission anomaly monitoring value of the i-th optical fiber line; glyc i , sjyc i , xzyc i and wml i respectively represent the optical power anomaly monitoring value, optical attenuation anomaly monitoring value, signal-to-noise ratio anomaly monitoring value, and bit error rate corresponding to the i-th optical fiber line; glbz i , sjbz i , xzbz i and wmbz i respectively represent the set optical power standard monitoring value, optical attenuation standard monitoring value, signal-to-noise ratio standard monitoring value, and standard bit error rate of the i-th optical fiber line; β1, β2, β3, and β4 respectively represent the optical power anomaly coefficient, optical attenuation anomaly coefficient, signal-to-noise ratio anomaly coefficient, and bit error rate anomaly coefficient.

5. The unattended optical fiber distribution management method according to claim 1, wherein Performing fault analysis based on the transmission anomaly monitoring value and the fiber optic distribution frame environment data to obtain a fault analysis result includes: Based on the transmission anomaly monitoring value, obtain the proportion of fiber optic lines with anomalies; Based on the fiber optic distribution frame environment data, obtain the fiber optic distribution frame vibration anomaly value, the fiber optic distribution frame environment temperature anomaly value, the fiber optic distribution frame environment humidity anomaly value, and the fiber optic distribution frame dust anomaly value; Input the proportion of fiber optic lines with anomalies, the fiber optic distribution frame vibration anomaly value, the fiber optic distribution frame environment temperature anomaly value, the fiber optic distribution frame environment humidity anomaly value, and the fiber optic distribution frame dust anomaly value into the fiber optic environment non-linear regression model to obtain the fiber optic distribution frame environment anomaly probability; When the fiber optic distribution frame environment anomaly probability is greater than the set probability threshold, the fault analysis result is that the fiber optic distribution frame environment is abnormal; otherwise, the fault analysis result is that the fiber optic distribution frame environment is not abnormal.

6. The unattended optical fiber distribution management method according to claim 5, wherein The process of obtaining the fiber optic distribution frame vibration anomaly value includes: Screen out the abnormal time periods that meet abnormal condition 1 or abnormal condition 2; Abnormal condition 1 is that the vibration frequency is greater than the standard vibration frequency; Abnormal condition 2 is that the vibration amplitude is greater than the standard vibration amplitude; Based on the vibration frequency and vibration amplitude corresponding to each abnormal time period, obtain the fiber optic distribution frame vibration anomaly value. The calculation formula is: Among them, zdyc represents the vibration abnormal value of the optical fiber distribution frame; M represents the number of vibration abnormal time periods; ycsc j , zdpl j and zdfd j respectively represent the duration of the j-th abnormal time period, the vibration amplitude of the vibration frequency; χ1 and χ2 respectively represent the first vibration abnormal coefficient and the second vibration abnormal coefficient.

7. The unattended optical fiber distribution management method according to claim 1, wherein When all the fiber optic lines are free of faults, obtaining the environmental anomaly degree of the fiber optic distribution frame based on the environmental data of the fiber optic distribution frame includes: obtaining the vibration anomaly value of the fiber optic distribution frame, the environmental temperature anomaly value of the fiber optic distribution frame, the environmental humidity anomaly value of the fiber optic distribution frame, and the dust anomaly value of the fiber optic distribution frame based on the environmental data of the fiber optic distribution frame; Obtaining the environmental anomaly degree based on the vibration anomaly value of the fiber optic distribution frame, the environmental temperature anomaly value of the fiber optic distribution frame, the environmental humidity anomaly value of the fiber optic distribution frame, and the dust anomaly value of the fiber optic distribution frame.

8. An unattended optical fiber distribution management system, characterized in that Including: Fiber optic distribution data acquisition unit: used to monitor the fiber optic distribution frame and obtain the fiber optic device data and the environmental data of the fiber optic distribution frame; Fault monitoring unit: used to monitor the faults of each fiber optic line corresponding to the fiber optic distribution frame based on the fiber optic device data; Fault analysis unit: used to perform fault analysis based on the transmission anomaly monitoring value and the environmental data of the fiber optic distribution frame when the fiber optic line has a fault, and obtain the fault analysis result; Environmental anomaly degree acquisition unit: used to identify the environmental anomaly degree of the fiber optic distribution frame based on the environmental data of the fiber optic distribution frame when all the fiber optic lines are free of faults; Abnormal warning unit: used to perform abnormal warning based on the environmental anomaly degree and the fault analysis result.

9. The unattended optical fiber distribution management system according to claim 8, wherein, The fiber optic distribution data acquisition unit includes: the fiber optic device data includes dq -t0,t dq the optical power data, optical attenuation data, signal-to-noise ratio data, and bit error rate data of each optical fiber line corresponding to the fiber optic distribution frame during the time period; t dq represents the current time; t0 represents the set time threshold; the fiber optic distribution frame environment data includes dq -t1,t dq the vibration data of the fiber optic distribution frame, the ambient temperature data of the fiber optic distribution frame, the ambient humidity data of the fiber optic distribution frame, and the dust data of the fiber optic distribution frame during the time period; t1 represents the time interval from the last maintenance of the fiber optic distribution frame to the current time.

10. The unattended optical fiber distribution management system according to claim 8, wherein, The fault monitoring unit includes: obtaining the optical power anomaly monitoring value, the optical attenuation anomaly monitoring value, and the signal-to-noise ratio anomaly monitoring value of each fiber optic line based on the fiber optic device data; calculating the transmission anomaly monitoring value of each fiber optic line based on the optical power anomaly monitoring value, the optical attenuation anomaly monitoring value, the signal-to-noise ratio anomaly monitoring value, and the bit error rate of the fiber optic line; When the transmission anomaly monitoring value is greater than the set threshold, it is determined that the fiber optic line has a fault; otherwise, it is determined that the fiber optic line has no fault.

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