CN109756263B - Optical fiber aging prediction method and device - Google Patents
Optical fiber aging prediction method and device Download PDFInfo
- Publication number
- CN109756263B CN109756263B CN201811562348.4A CN201811562348A CN109756263B CN 109756263 B CN109756263 B CN 109756263B CN 201811562348 A CN201811562348 A CN 201811562348A CN 109756263 B CN109756263 B CN 109756263B
- Authority
- CN
- China
- Prior art keywords
- historical
- sampling
- optical power
- optical
- optical fiber
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Optical Communication System (AREA)
Abstract
The application provides an optical fiber aging prediction method and device, wherein the method comprises the following steps: acquiring an alarm threshold value of an optical signal which can be received by an optical fiber module to be tested; acquiring a plurality of historical optical power sampling values which are received by an optical fiber module to be tested and meet preset conditions and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values; performing polynomial regression calculation according to the plurality of historical optical power sampling values and the plurality of historical sampling time points to obtain a prediction model; and calculating the aging limit time point when the optical power of the optical signal received by the optical fiber module to be tested is reduced to the alarm threshold value through the prediction model. Therefore, the aging limit time point can be estimated according to the actual aging condition of the optical fiber accessed to the optical fiber module to be detected, so that the estimation on the usable life of the optical fiber is more accurate and reliable.
Description
Technical Field
The application relates to the technical field of photoelectric communication, in particular to a method and a device for predicting optical fiber aging.
Background
Optical communication is widely applied as a communication mode with long transmission distance, strong anti-interference capability and low cost at present. In optical communication, signal propagation depends on an optical fiber cable, and the state of the optical fiber cable directly affects the quality of optical communication. With the increase of the service life, the optical fiber is gradually aged, so that a large amount of energy is lost in the transmission process of the optical signal, which causes the power of the optical signal received by the signal receiving end to be insufficient, and the optical signal cannot be correctly identified. Therefore, maintenance personnel often need to replace the fiber optic cable before it reaches its end of life.
Disclosure of Invention
In a first aspect, the present application provides a method for predicting fiber aging, the method comprising:
acquiring an alarm threshold value of an optical signal which can be received by an optical fiber module to be tested;
acquiring a plurality of historical optical power sampling values which are received by the optical fiber module to be tested and meet preset conditions and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values;
performing polynomial regression calculation according to the plurality of historical optical power sampling values and the plurality of historical sampling time points to obtain a prediction model;
and calculating the aging limit time point when the optical power of the optical signal received by the optical fiber module to be tested is reduced to the alarm threshold value through the prediction model.
Optionally, in the above method, the method further comprises:
acquiring a current optical power sampling value and a current sampling time point which are obtained by new sampling;
updating the prediction model according to the current optical power sampling value, the historical optical power sampling value, the current sampling time point and the plurality of historical sampling time points;
and calculating an aging limit time point according to the updated prediction model.
Optionally, in the method, the step of obtaining a plurality of historical optical power sampling values that satisfy a preset condition and are received by the optical fiber module to be tested, and a plurality of historical sampling time points that are in one-to-one correspondence with the historical optical power sampling values includes:
according to a preset power interval, sequentially recording a plurality of historical optical power sampling values which are compared with the last recorded optical power sampling value, have the sampling value descending amplitude larger than or equal to the power interval, and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values; or,
according to a preset power interval, a plurality of historical optical power sampling values and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values are obtained from a historical sampling database in sequence, wherein the historical optical power sampling values are compared with the last obtained optical power sampling value, the descending amplitude of the sampling values is larger than or equal to the power interval, and the historical optical power sampling values correspond to the historical optical power sampling values.
Optionally, in the above method, the method further comprises:
taking the optical power sampling value of the optical signal received by the optical fiber module recorded for the first time as reference optical power;
calculating to obtain the power reduction amplitude of the optical fiber module to be tested according to the reference optical power and the alarm threshold;
and calculating according to the power reduction amplitude and a preset sampling interval proportion to obtain the power interval.
Optionally, in the method, the step of obtaining a plurality of historical optical power sampling values that satisfy a preset condition and are received by the optical fiber module to be tested, and a plurality of historical sampling time points that are in one-to-one correspondence with the historical optical power sampling values includes:
and according to a preset time interval, sequentially recording a plurality of historical sampling time points and a plurality of historical optical power sampling values which are in one-to-one correspondence with the historical sampling time points.
In a second aspect, the present application provides an optical fiber aging prediction apparatus, the apparatus comprising:
the threshold value acquisition module is used for acquiring an alarm threshold value of a receivable optical signal of the optical fiber module to be detected;
the sampling module is used for acquiring a plurality of historical optical power sampling values which are received by the optical fiber module to be tested and meet preset conditions and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values;
the model establishing module is used for performing polynomial regression calculation according to the plurality of historical light power sampling values and the plurality of historical sampling time points to obtain a prediction model;
and the aging prediction module is used for calculating the aging limit time point when the optical power of the optical signal received by the optical fiber module to be tested is reduced to the alarm threshold value through the prediction model.
Alternatively, in the above-described apparatus,
the sampling module is also used for acquiring a current optical power sampling value and a current sampling time point which are obtained by new sampling;
the model establishing module is further configured to update the prediction model according to the current optical power sampling value, the historical optical power sampling value, the current sampling time point, and the plurality of historical sampling time points;
the aging prediction module is further used for calculating an aging limit time point according to the updated prediction model.
Optionally, in the above apparatus, the sampling module is specifically configured to record, according to a preset power interval, a plurality of historical optical power sampling values, which are compared with the last recorded optical power sampling value, whose sampling value drop amplitude is greater than or equal to the power interval, and a plurality of historical sampling time points corresponding to the historical optical power sampling values one to one; or according to a preset power interval, sequentially acquiring a plurality of historical optical power sampling values which are compared with the last acquired optical power sampling value, have the sampling value descending amplitude larger than or equal to the power interval and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values from a historical sampling database.
Optionally, in the above apparatus, the apparatus further comprises:
the reference power acquisition module is used for taking the optical power sampling value of the optical signal received by the optical fiber module recorded for the first time as reference optical power;
the power interval calculation module is used for calculating the power reduction amplitude of the optical fiber module to be tested according to the reference optical power and the alarm threshold; and calculating according to the power reduction amplitude and a preset sampling proportion coefficient to obtain the power interval.
Optionally, in the above apparatus, the sampling module is specifically configured to record, according to a preset time interval, a plurality of historical sampling time points and a plurality of historical optical power sampling values corresponding to the historical sampling time points one to one in sequence.
Compared with the prior art, the method has the following beneficial effects:
according to the optical fiber aging prediction method and device, a prediction model is obtained by obtaining historical optical power sampling values of optical signals received by a plurality of historical sampling time points from an optical fiber module to be tested and performing polynomial regression calculation, and an aging limit time point of the optical power of the optical signals received by the optical fiber module to be tested, which is reduced to an acceptable alarm threshold value due to optical fiber aging, is calculated according to the prediction model. Therefore, the aging limit time point can be estimated according to the actual aging condition of the optical fiber connected to the optical fiber module to be detected, so that the estimation on the service life of the optical fiber is more accurate and reliable, and operation and maintenance personnel can replace the optical fiber in time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic flowchart of a method for predicting fiber aging according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a polynomial regression model principle of an optical fiber aging prediction method according to an embodiment of the present disclosure;
FIG. 3 is a second flowchart illustrating a method for predicting fiber aging according to an embodiment of the present disclosure;
fig. 4 is a schematic hardware structure diagram of a network device according to an embodiment of the present application;
fig. 5 is a schematic interaction diagram of a control device and a network device according to an embodiment of the present application;
fig. 6 is a schematic hardware structure diagram of a control device according to an embodiment of the present application;
fig. 7 is a functional block diagram of an aging prediction apparatus according to an embodiment of the present disclosure;
fig. 8 is a second functional block diagram of an aging prediction apparatus according to the present embodiment.
Icon: 100-a network device; 120-a first machine-readable storage medium; 130-a first processor; 140 — first system bus; 200-a control device; 220-a second machine-readable storage medium; 230-a second processor; 240-second system bus; 310-a fiber aging prediction device; 311-a threshold acquisition module; 312-a sampling module; 313-a model building module; 314-an aging prediction module; 315-reference power acquisition module; 316-power interval calculation module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Currently, maintenance personnel often maintain the replacement cycle of the optical fiber according to the theoretical service life provided by the optical fiber supplier. However, the theoretical useful life of an optical fiber is a theoretical value estimated by a supplier based on various characteristics of the optical fiber, assuming that the optical fiber is used in a specific environment. However, the aging speed of the optical fiber may vary according to the actual usage environment of the optical fiber, for example, the optical fiber ages faster in a place with strong acidity and alkalinity, strong illumination or high temperature, but ages slower in an environment with suitable acidity and alkalinity and suitable temperature. This results in greater discrepancy between the theoretical and actual useful life of the fiber. In addition, some process problems may occur during the manufacturing of the optical fiber, resulting in the theoretical useful life estimated from the overall characteristics of the optical fiber not being consistent with the actual useful life of each individual optical fiber.
Due to the fact that the theoretical service life of the optical fiber and the actual service life of the optical fiber are different and larger, maintenance personnel cannot correctly estimate the time for maintaining and replacing the optical fiber. Too late a replacement may occur when some fibers have reached the limit of use within their theoretical useful life, thereby causing communication failures and affecting service operation. Premature replacement may result in some fibers still being usable, but being replaced prematurely, wasting costs.
In view of the above, the present embodiment provides a solution for dynamically estimating the aging condition of the optical fiber according to the actual usage condition of the optical fiber, and the solution provided by the present embodiment is described in detail below.
Referring to fig. 1, the present embodiment provides a method for predicting fiber aging, and the following steps of the method are described in detail.
Step S110, an alarm threshold of the receivable optical signal of the optical fiber module to be tested is obtained.
The optical fiber module is a module which is used for being connected with an optical fiber and converting an optical signal transmitted by the optical fiber into an electrical signal, the optical fiber module has a limited power range of the optical signal which can be identified, the attenuation of the optical signal in the transmission process is increased along with the aging of the optical fiber, when the optical power of the optical signal received by the optical fiber module is lower than a certain threshold (such as a minimum optical power threshold), the optical fiber module cannot correctly convert the optical signal into the electrical signal, and the minimum optical power threshold refers to a lower limit value of the power of the optical signal which can be received by one optical fiber module.
Step S120, obtaining a plurality of historical optical power sampling values meeting preset conditions and a plurality of historical sampling time points corresponding to the historical optical power sampling values one to one, which are received by the optical fiber module to be tested.
And step S130, performing polynomial regression calculation according to the plurality of historical optical power sampling values and the plurality of historical sampling time points to obtain a prediction model.
Step S140, calculating the aging limit time point when the optical power of the optical signal received by the optical fiber module to be tested is reduced to the alarm threshold value through the prediction model.
The polynomial regression calculation may express the nonlinear variation relationship between the independent variable and the dependent variable by a polynomial of an independent variable, for example, in the present embodiment, the historical sampling time point may be used as the independent variable x, and the corresponding historical optical power sampling value may be used as the dependent variable y, and then the dependent variable y may be expressed as a univariate m-degree polynomial of the independent variable x, as follows,
y＝a0+a1x+a2x2+…+amxm
referring to fig. 2, a is obtained by inputting the historical optical power sampling values corresponding to the plurality of historical sampling time points into the polynomial to perform regression calculation0To amTo obtain a curve of the optical power decreasing trend with time, i.e. the curve shown in fig. 2 can be fitted. Further, the alarm threshold may be used as a dependent variable to reversely deduce an aging limit time point as an independent variable, that is, the time corresponding to the alarm threshold on the curve shown in fig. 2 may be used as the aging limit time point.
Among them, the polynomial regression calculation can be solved by changing the variable transformation into the multiple linear regression problem. For the above-mentioned unary m-th order polynomial regression equation, let x1＝x，x2＝x2，…，xm＝xmThen the univariate m-th order polynomial is converted into m-linear regression equations:
y＝a0+a1x1+a2x2+…+amxm
the transformation may be followed by solving using least squares or gradient descent methods. The more the polynomial degree, the more accurate the result obtained by the prediction model, the more the required calculation amount, and in this embodiment, the degree of the polynomial may be set to about 10 by considering the accuracy and the calculation amount together.
Based on the above design, in the method provided in this embodiment, the prediction model is established according to the actual historical optical power sampling value obtained from the optical fiber module to be tested, so that the aging transformation trend of the optical fiber accessed to the optical fiber module to be tested in the current use scene can be more accurately reflected, and the aging limit time point predicted according to the prediction model is more accurate and reliable.
Optionally, after the prediction model is established, the data analysis device may further obtain a current optical power sampling value and a current sampling time point obtained by new sampling, update the prediction model according to the current optical power sampling value, the historical optical power sampling value, the current sampling time point and the plurality of historical sampling time points, and calculate the aging limit time point according to the updated prediction model.
By the method, the prediction model can be continuously updated according to the result of continuous sampling, so that the prediction result of the prediction model can be in accordance with the current state of the optical fiber, and the prediction accuracy is improved.
Optionally, since the optical fiber modules provided by different suppliers may have different capabilities of identifying optical signals, each type of optical fiber module has a corresponding minimum receivable optical power threshold, that is, if the power of an optical signal received by one optical fiber module is greater than or equal to the minimum optical power threshold corresponding to the one optical fiber module, the one optical fiber module may correctly convert the received optical signal into an electrical signal, and if the power of the optical signal received by the one optical fiber module is less than the minimum optical power threshold corresponding to the one optical fiber module, the one optical fiber module may not correctly convert the received optical signal into the electrical signal. In this embodiment, for different optical fiber modules to be tested, the corresponding lowest optical power threshold may be used as the alarm threshold.
The optical fiber module is usually an integrated module, and may perform command interaction with the optical fiber module to be tested through an operating system operated by the network device itself to obtain a minimum optical power threshold of an optical signal that can be received by the optical fiber module to be tested. For example, each item of performance data of the optical fiber module to be tested may be read by issuing a transceiver interface [ port type ] [ port number ] to the optical fiber module to be tested, and the lowest optical power threshold of the optical fiber module to be tested is obtained therefrom as the alarm threshold.
Alternatively, the alarm threshold may be a preset value manually set by a maintenance person. For example, in some specific application scenarios, the alarm threshold may be set to: is larger than the lowest optical power threshold by a specified value or is smaller than the lowest optical power by a specified value.
In this embodiment, a prediction model needs to be established according to historical optical power sampling values obtained at a plurality of historical sampling time points on an optical fiber module to be tested, and in actual use, aging of an optical fiber is very slow, so that optical power change of an optical signal received by the optical fiber module to be tested is also very slow, so as to avoid influence on construction of the prediction model due to high repetition rate of the obtained historical optical power sampling values, reduce modeling efficiency, and need to obtain a plurality of historical optical power sampling values and corresponding historical sampling time points which meet preset conditions.
Optionally, in an implementation manner of this embodiment, in step S120, according to a preset power interval, a plurality of historical optical power sampling values, which are decreased by a magnitude greater than or equal to the power interval compared to the last recorded optical power sampling value, and a plurality of historical sampling time points corresponding to the historical optical power sampling values one by one, are sequentially recorded.
For example, an initial sampling is first performed, and a sampling time point and an optical power sampling value are recorded as a first historical sampling time point and a historical optical power sampling value. And then, continuously detecting the optical power of the received optical signal, recording the current time point and the current optical power as a second historical sampling time point and a historical optical power sampling value when the current optical power is detected to be greater than or equal to a preset N decibel milliwatt (dBm) compared with that recorded by the initial sampling, recording the current time point and the current optical power as a third historical sampling time point and a historical optical power sampling value when the current optical power is detected to be greater than or equal to a preset N decibel milliwatt (dBm) compared with that recorded by the second sampling. And analogizing in turn, recording a plurality of sampling points of which the sampling value descending amplitude is larger than N decibel milliwatts compared with the last sampling.
Optionally, in another implementation manner of this embodiment, some optical modules to be tested that have been operated for a period of time may store a record of periodic sampling, for example, there is a historical sampling database, and the historical sampling database records the optical power received by the optical module and the corresponding time thereof based on a preset recording period (e.g., once per day). The data analysis equipment can sequentially acquire a plurality of historical optical power sampling values which are compared with the last acquired optical power sampling value and have the descending amplitude larger than or equal to the power interval and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values from the historical sampling database according to a preset power interval.
For example, for an optical module to be tested that has been operated for a period of time, a plurality of sampling point records of the optical module have been recorded in the historical sampling database, in step S120, the optical power of the optical signal recorded for the first time may be selected from the records as the reference optical power, then a plurality of sampling points are selected from the stored sampling point records according to N decibel milliwatts (dBm) preset for each drop of the optical power, and a historical sampling time point and a historical optical power sampling value of the selected sampling point are obtained. Further, referring to fig. 3, in the above embodiment, before step S120, the method may further include step S210 to step S230.
Step S210, using the first recorded optical power sampling value of the optical signal received by the optical fiber module as a reference optical power.
In this embodiment, the reference optical power may be an optical power of an optical signal that is first received by the optical fiber module to be tested under a normal working condition. For example, when the optical fiber module under test receives the optical signal for the first time, the optical power of the received optical signal may be recorded as the reference optical power. The reference optical power may also be the optical power of an optical signal recorded on the optical module to be measured for the first time. For example, in the recording of a plurality of sampling points of the optical module to be measured, the optical power of the first recorded sampling point is used as the reference optical power.
Step S220, calculating according to the reference optical power and the alarm threshold value to obtain the power reduction range of the optical fiber module to be tested.
Step S230, calculating to obtain a power interval according to the power reduction range and a preset sampling scaling factor.
In this embodiment, the reference optical power is denoted as PnormalRecording the alarm threshold value of the port to be tested as T1Let the power reduction be T2Then, in step S220, the power down amplitude is calculated,
T2＝Pnormal-T1
in addition, in the present embodiment, the sampling scale factor may be set to 5%, at step S2The power interval calculated in 30 is T2·5％。
Therefore, the power interval obtained from the step S210 to the step S230 is used for sampling, so that the obtained sampling points are distributed more uniformly, and the construction of a prediction model is facilitated.
Optionally, in another implementation manner of this embodiment, a plurality of historical sampling time points and a plurality of historical optical power sampling values corresponding to the historical sampling time points in a one-to-one manner may also be sequentially recorded according to a preset time interval. For example, sampling is performed every 15 days, and historical sampling time points and historical optical power sampling values are recorded.
Since the aging of the optical fiber continues along with the advancing of time, and the aging speed is slow, in the embodiment, the sampling granularity of the historical sampling time points is in a unit of common days, the recording form of the historical sampling time points is usually year-month-day, but the recording form of year-month-day is not a numerical value continuous change recording form, for example, the time point representing 11, month and 30 days in 2018 is usually 20181130, the time point representing 12, month and 30 days in 2018 is usually 20181230, the time interval from 11, month and 30 days in 2018 to 12, month and 30 days in 2018 is actually 30 days, but the recorded numerical value is 20181230 and 20181130 is 100, so the difference between the numerical values of 20181130 and 20181230 cannot represent the actual time interval, and the result of polynomial regression performed by using the numerical value of the discontinuous change rule is incorrect.
Therefore, optionally, before performing the polynomial regression calculation according to the historical sampling time point and the historical optical power sampling value in step S130, the table format of the values at the historical sampling time point needs to be converted into the expression format in which the numerical value changes continuously, and in this embodiment, the values at the historical sampling time point may be converted into the number of days away from a certain reference time. For example, taking 2018, 1/2018 as a reference time, the value 20181130 of the historical sampling time point 2018, 11/30/2018 is converted into the number of days from the reference time, namely 333 days; the value 20181230 for 12 months and 30 days in 2018 at the historical sampling time point is converted to days from the reference time, i.e., 363 days. Thus, 363-.
It should be noted that the above-mentioned number of days for converting the historical sampling time point into the distance reference time is only one exemplary way for converting the historical sampling time point into the continuously changing value in this embodiment, and in other embodiments of this embodiment, other conversion ways may also be adopted, which are not described herein again.
Alternatively, in an implementation manner of this embodiment, the network device itself may perform an action of obtaining historical optical power sampling values at a plurality of historical sampling time points, then performing polynomial regression calculation to obtain a prediction model, and calculating and obtaining the historical sampling time points according to the prediction model.
Referring to fig. 4, fig. 4 is a schematic diagram of a network device 100 according to this embodiment. The network device 100 may include a first processor 130 and a first machine-readable storage medium 120. The first processor 130 and the first machine-readable storage medium 120 may communicate via a first system bus 140. Also, the first machine-readable storage medium 120 stores machine-executable instructions, and the processor may execute the methods of steps S110 to S130 described above by reading and executing the machine-executable instructions corresponding to the fiber aging prediction logic in the first machine-readable storage medium 120.
Optionally, referring to fig. 5, in another implementation manner of this embodiment, the optical power of the optical signal received by the optical fiber module to be tested of the network device 100 may also be sent to one control device 200 through a network, the control device 200 performs an operation of recording historical optical power sampling values of a plurality of historical sampling time points, then performing polynomial regression calculation to obtain a prediction model, and calculating an action of obtaining a historical sampling time point according to the prediction model.
Referring to fig. 6, fig. 6 is a schematic diagram of a control device 200 according to the present embodiment. The control device 200 may include a second processor 230 and a second machine-readable storage medium 220. The second processor 230 and the second machine-readable storage medium 220 may communicate via a second system bus 240. Also, the second machine-readable storage medium 220 stores machine-executable instructions, and the processor may execute the above-described methods of steps S110 to S130 by reading and executing the machine-executable instructions corresponding to the fiber aging prediction logic in the second machine-readable storage medium 220.
A machine-readable storage medium as referred to herein may be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, and the like. For example, the machine-readable storage medium may be: a RAM (random Access Memory), a volatile Memory, a non-volatile Memory, a flash Memory, a storage drive (e.g., a hard drive), a solid state drive, any type of storage disk (e.g., an optical disk, a dvd, etc.), or similar storage medium, or a combination thereof.
Referring to fig. 7, the present embodiment further provides an optical fiber aging prediction apparatus 310, where the optical fiber aging prediction apparatus 310 includes at least one functional module that can be stored in the form of software in the first machine-readable storage medium 130 of the network device 100 shown in fig. 4 or the second machine-readable storage medium 210 of the control device 200 shown in fig. 6. Functionally, the fiber aging prediction apparatus 310 may include a threshold acquisition module 311, a sampling module 312, a model building module 313, and an aging prediction module 314.
The threshold obtaining module 311 is configured to obtain an alarm threshold of the optical fiber module to be tested.
In this embodiment, the threshold obtaining module 311 may be configured to execute step S110 shown in fig. 1, and reference may be made to the description of step S110 for a detailed description of the threshold obtaining module 311.
The sampling module 312 is configured to obtain a plurality of historical optical power sampling values that meet preset conditions and are received by the optical fiber module to be tested, and a plurality of historical sampling time points that are in one-to-one correspondence with the historical optical power sampling values.
In this embodiment, the sampling module 312 may be configured to perform step S120 shown in fig. 1, and reference may be made to the description of step S120 for a detailed description of the sampling module 312.
The model establishing module 313 is configured to perform polynomial regression calculation according to the plurality of historical optical power sampling values and the plurality of historical sampling time points to obtain a prediction model.
In this embodiment, the model building module 313 may be configured to execute step S130 shown in fig. 1, and reference may be made to the description of step S130 for the detailed description of the model building module 313.
The aging prediction module 314 is configured to calculate an aging limit time point at which the optical power of the optical signal received by the optical fiber module to be tested decreases to the alarm threshold through the prediction model.
In this embodiment, the aging prediction module 314 can be used to execute step S140 shown in fig. 1, and the detailed description about the aging prediction module 314 can refer to the description about step S140.
Optionally, in this embodiment, the sampling module 312 is further configured to obtain a current optical power sampling value obtained by new sampling and a current sampling time point.
The model building module 313 is further configured to update the prediction model according to the current optical power sampling value, the historical optical power sampling value, the current sampling time point, and a plurality of historical sampling time points.
The aging prediction module 314 is further configured to calculate an aging limit time point according to the updated prediction model.
Optionally, in this embodiment, the sampling module 312 is specifically configured to sequentially record, according to a preset power interval, a plurality of historical optical power sampling values, which are compared with the last recorded optical power sampling value, have a descending amplitude greater than or equal to the power interval, and a plurality of historical sampling time points corresponding to the historical optical power sampling values one to one; or according to a preset power interval, sequentially acquiring a plurality of historical optical power sampling values which are compared with the last acquired optical power sampling value, have the descending amplitude larger than or equal to the power interval, and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values from the historical sampling database.
Optionally, in this embodiment, referring to fig. 8, the optical fiber aging prediction apparatus 310 may further include a reference power obtaining module 315 and a power interval calculating module 316.
The reference power obtaining module 315 is configured to use the first recorded optical power sampling value of the optical signal received by the optical fiber module as the reference optical power.
In this embodiment, the reference power obtaining module 315 may be configured to execute step S210 shown in fig. 3, and reference may be made to the description of step S210 for a detailed description of the reference power obtaining module 315.
The power interval calculation module 316 is used for a power interval calculation module, and is used for calculating the power reduction amplitude of the optical fiber module to be measured according to the reference optical power and the alarm threshold; and calculating to obtain the power interval according to the power reduction amplitude and a preset sampling proportion coefficient.
In this embodiment, the power interval calculation module 316 can be used to execute the steps S220 and S230 shown in fig. 3, and the detailed description of the power interval calculation module 316 can refer to the description of the steps S220 and S230.
Optionally, in this embodiment, the sampling module 312 is specifically configured to sequentially record a plurality of historical sampling time points and a plurality of historical optical power sampling values corresponding to the historical sampling time points one to one according to a preset time interval.
In summary, according to the optical fiber aging prediction method and apparatus provided by the present application, a prediction model is obtained by obtaining a plurality of historical optical power sampling values of optical signals received at a historical sampling time point from an optical fiber module to be tested and performing polynomial regression calculation, and an aging limit time point at which the optical power of the optical signals received by the optical fiber module to be tested is reduced to an acceptable alarm threshold due to optical fiber aging is calculated according to the prediction model. Therefore, the aging limit time point can be estimated according to the actual aging condition of the optical fiber accessed to the optical fiber module to be detected, so that the estimation on the service life of the optical fiber is more accurate and reliable.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only for various embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present application, and all such changes or substitutions are included in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for predicting fiber aging, the method comprising:
performing command interaction with an optical fiber module to be tested through an operating system operated by network equipment, reading various performance data of the optical fiber module to be tested, and acquiring a minimum optical power threshold of the optical fiber module to be tested as an alarm threshold of an optical signal which can be received by the optical fiber module to be tested;
acquiring a plurality of historical optical power sampling values which are received by the optical fiber module to be tested and meet preset conditions and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values;
performing polynomial regression calculation according to the plurality of historical optical power sampling values and the plurality of historical sampling time points to obtain a prediction model;
and calculating the aging limit time point when the optical power of the optical signal received by the optical fiber module to be tested is reduced to the alarm threshold value through the prediction model.
2. The method of claim 1, further comprising:
acquiring a current optical power sampling value and a current sampling time point which are obtained by new sampling;
updating the prediction model according to the current optical power sampling value, the historical optical power sampling value, the current sampling time point and the plurality of historical sampling time points;
and calculating an aging limit time point according to the updated prediction model.
3. The method according to claim 1, wherein the step of obtaining a plurality of historical optical power sampling values that satisfy a preset condition and a plurality of historical sampling time points that are in one-to-one correspondence with the historical optical power sampling values, which are received by the optical fiber module under test, comprises:
according to a preset power interval, sequentially recording a plurality of historical optical power sampling values which are compared with the last recorded optical power sampling value, have the sampling value descending amplitude larger than or equal to the power interval, and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values; or,
according to a preset power interval, a plurality of historical optical power sampling values and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values are obtained from a historical sampling database in sequence, wherein the historical optical power sampling values are compared with the last obtained optical power sampling value, the descending amplitude of the sampling values is larger than or equal to the power interval, and the historical optical power sampling values correspond to the historical optical power sampling values.
4. The method of claim 3, further comprising:
taking the optical power sampling value of the optical signal received by the optical fiber module recorded for the first time as reference optical power;
calculating to obtain the power reduction amplitude of the optical fiber module to be tested according to the reference optical power and the alarm threshold;
and calculating according to the power reduction amplitude and a preset sampling interval proportion to obtain the power interval.
5. The method according to claim 1, wherein the step of obtaining a plurality of historical optical power sampling values that satisfy a preset condition and a plurality of historical sampling time points that are in one-to-one correspondence with the historical optical power sampling values, which are received by the optical fiber module under test, comprises:
and according to a preset time interval, sequentially recording a plurality of historical sampling time points and a plurality of historical optical power sampling values which are in one-to-one correspondence with the historical sampling time points.
6. An optical fiber aging prediction apparatus, comprising:
the threshold value acquisition module is used for performing command interaction with the optical fiber module to be tested through an operating system operated by the network equipment, reading various performance data of the optical fiber module to be tested, and acquiring the lowest optical power threshold value of the optical fiber module to be tested as an alarm threshold value of a receivable optical signal of the optical fiber module to be tested;
the sampling module is used for acquiring a plurality of historical optical power sampling values which are received by the optical fiber module to be tested and meet preset conditions and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values;
the model establishing module is used for performing polynomial regression calculation according to the plurality of historical light power sampling values and the plurality of historical sampling time points to obtain a prediction model;
and the aging prediction module is used for calculating the aging limit time point when the optical power of the optical signal received by the optical fiber module to be tested is reduced to the alarm threshold value through the prediction model.
7. The apparatus of claim 6,
the sampling module is also used for acquiring a current optical power sampling value and a current sampling time point which are obtained by new sampling;
the model establishing module is further configured to update the prediction model according to the current optical power sampling value, the historical optical power sampling value, the current sampling time point, and the plurality of historical sampling time points;
the aging prediction module is further used for calculating an aging limit time point according to the updated prediction model.
8. The apparatus according to claim 6, wherein the sampling module is configured to sequentially record, according to a preset power interval, a plurality of historical optical power sampling values, which are lower than the last recorded optical power sampling value by an amount greater than or equal to the power interval, and a plurality of historical sampling time points corresponding to the historical optical power sampling values one to one; or according to a preset power interval, sequentially acquiring a plurality of historical optical power sampling values which are compared with the last acquired optical power sampling value, have the sampling value descending amplitude larger than or equal to the power interval and a plurality of historical sampling time points which are in one-to-one correspondence with the historical optical power sampling values from a historical sampling database.
9. The apparatus of claim 8, further comprising:
the reference power acquisition module is used for taking the optical power sampling value of the optical signal received by the optical fiber module recorded for the first time as reference optical power;
the power interval calculation module is used for calculating the power reduction amplitude of the optical fiber module to be tested according to the reference optical power and the alarm threshold; and calculating according to the power reduction amplitude and a preset sampling proportion coefficient to obtain the power interval.
10. The apparatus according to claim 6, wherein the sampling module is specifically configured to record, according to a preset time interval, a plurality of historical sampling time points and a plurality of historical optical power sampling values corresponding to the historical sampling time points one to one.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811562348.4A CN109756263B (en) | 2018-12-20 | 2018-12-20 | Optical fiber aging prediction method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811562348.4A CN109756263B (en) | 2018-12-20 | 2018-12-20 | Optical fiber aging prediction method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109756263A CN109756263A (en) | 2019-05-14 |
| CN109756263B true CN109756263B (en) | 2021-01-01 |
Family
ID=66402980
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811562348.4A Active CN109756263B (en) | 2018-12-20 | 2018-12-20 | Optical fiber aging prediction method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109756263B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111750925B (en) * | 2019-12-24 | 2022-11-08 | 广州极飞科技股份有限公司 | Equipment aging prediction system, method and device |
| CN112311454B (en) * | 2020-11-04 | 2022-04-12 | 中国联合网络通信集团有限公司 | State determination method, device and equipment of optical module |
| CN114037117B (en) * | 2021-10-08 | 2024-11-05 | 苏州热工研究院有限公司 | A predictive management method for photoelectric converters in nuclear power plants |
| CN115549781A (en) * | 2022-09-30 | 2022-12-30 | 联想(北京)有限公司 | Optical power abnormality prediction method, device, electronic equipment and storage medium |
| CN116296295A (en) * | 2023-04-10 | 2023-06-23 | 广东思沃激光科技有限公司 | Light path aging test method and system based on artificial intelligence |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0407009A2 (en) * | 1989-05-05 | 1991-01-09 | Tektronix, Inc. | Estimation of fiber loss and return signal power |
| CN103152095A (en) * | 2013-01-29 | 2013-06-12 | 华为技术有限公司 | Life forecast method and life forecast device of optical module |
| CN104158585A (en) * | 2014-07-29 | 2014-11-19 | 国家电网公司 | Establishment method for optical fiber fault ageing model |
| CN107171722A (en) * | 2017-07-26 | 2017-09-15 | 青岛海信宽带多媒体技术有限公司 | A kind of monitoring method, device and the terminal of optical module received optical power |
| CN107222254A (en) * | 2016-03-21 | 2017-09-29 | 中兴通讯股份有限公司 | A kind of detection method and device of optical fiber state |
| CN108667513A (en) * | 2018-04-08 | 2018-10-16 | 四川微迪智控科技有限公司 | A kind of the optical fiber link management system and service life predictor method of the DDM functions based on SFP modules |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5056549B2 (en) * | 2008-04-04 | 2012-10-24 | 日亜化学工業株式会社 | Optical semiconductor element lifetime prediction method and optical semiconductor element driving apparatus |
-
2018
- 2018-12-20 CN CN201811562348.4A patent/CN109756263B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0407009A2 (en) * | 1989-05-05 | 1991-01-09 | Tektronix, Inc. | Estimation of fiber loss and return signal power |
| CN103152095A (en) * | 2013-01-29 | 2013-06-12 | 华为技术有限公司 | Life forecast method and life forecast device of optical module |
| CN104158585A (en) * | 2014-07-29 | 2014-11-19 | 国家电网公司 | Establishment method for optical fiber fault ageing model |
| CN107222254A (en) * | 2016-03-21 | 2017-09-29 | 中兴通讯股份有限公司 | A kind of detection method and device of optical fiber state |
| CN107171722A (en) * | 2017-07-26 | 2017-09-15 | 青岛海信宽带多媒体技术有限公司 | A kind of monitoring method, device and the terminal of optical module received optical power |
| CN108667513A (en) * | 2018-04-08 | 2018-10-16 | 四川微迪智控科技有限公司 | A kind of the optical fiber link management system and service life predictor method of the DDM functions based on SFP modules |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109756263A (en) | 2019-05-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109756263B (en) | Optical fiber aging prediction method and device | |
| CN109885469B (en) | Capacity expansion method, prediction model creation method, device, equipment and medium | |
| EP2813978A1 (en) | Industrial asset health model update | |
| CN108009692A (en) | Maintenance of equipment information processing method, device, computer equipment and storage medium | |
| CN105593864B (en) | Analytical device degradation for maintenance device | |
| JP2012205385A (en) | Reserve power calculation device and method, and computer program | |
| CN106503841B (en) | method and device for determining index threshold | |
| CN109844665B (en) | Information processing method, information processing apparatus, computer-readable storage medium, and information processing system | |
| KR20210127735A (en) | Battery Residual Value Determination System | |
| JP7108214B2 (en) | Hydrogen embrittlement progress evaluation method and hydrogen embrittlement progress evaluation device | |
| CN109087008A (en) | A kind of equipment fault early-warning method and device | |
| CN103152095A (en) | Life forecast method and life forecast device of optical module | |
| US9319030B2 (en) | Integrated circuit failure prediction using clock duty cycle recording and analysis | |
| CN112599182A (en) | Nonvolatile storage life prediction method, device, equipment and medium | |
| CN115794342A (en) | Method and device for estimating remaining time of pipeline task and electronic equipment | |
| CN112032031A (en) | Cloud data analysis method, device and system for air compressor | |
| US11262272B2 (en) | Adaptive remaining useful life estimation method using constraint convex regression from degradation measurement | |
| CN113986700B (en) | Data acquisition frequency optimization method, system, device and storage medium | |
| KR20220103497A (en) | Method for calculating life of electronic device | |
| CN116627342A (en) | Method, device, equipment and medium for predicting residual service life of solid state disk | |
| CN110058810B (en) | Disk cleaning method and device for distributed system and distributed system | |
| KR20180129496A (en) | Method for predicting electric power demand and apparatus for the same | |
| JP6717304B2 (en) | Prediction device, prediction system, prediction method and program | |
| RU2336570C1 (en) | Determination method for optimal maintenance period of equipment | |
| CN116011677A (en) | Time sequence data prediction method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |