Method and device for determining a line with abnormal optical signal attenuation, and computer equipment

Abstract

The application discloses a line determination method and device for optical signal attenuation anomaly and computer equipment. The method comprises the following steps: acquiring a plurality of line resources in an optical distribution network (ODN), and dividing the plurality of line resources into a plurality of line clusters; acquiring a line length and a total optical attenuation value of each line in a to-be-determined line cluster, and determining an initial total optical attenuation regression equation of each line according to the line length and the total optical attenuation value; determining an optical attenuation offset value of each line according to the initial total optical attenuation regression equation, and splitting the lines in the to-be-determined line cluster into a plurality of groups of lines based on the optical attenuation offset value and a correlation coefficient of each line in the to-be-determined line cluster, wherein the correlation coefficient represents a correlation degree of the line length and the total optical attenuation value; and selecting an optical signal attenuation anomaly line from each group of lines. The application solves the technical problem of a large workload of an optical attenuation judgment method in the related art.

Description

Technical Field

[0001] This application relates to the field of communication technology, and more specifically, to a method, apparatus, and computer device for determining abnormal optical signal attenuation. Background Technology

[0002] ODN networks are the backbone networks of network operators. They transmit and receive signals through optical transceivers and PON equipment, and transmit optical signals through optical fibers and splitters. The degree of optical signal attenuation affects the quality of service for users. Optical attenuation mitigation and network planning and construction have become crucial aspects of ensuring and improving optical network quality. Therefore, quickly identifying and pinpointing nodes with high optical network attenuation can not only improve maintenance quality but also save operators significant maintenance costs. Traditional methods for determining optical attenuation mainly involve on-site measurements using instruments such as OTDRs, comparing target values ​​to determine attenuation nodes. However, traditional methods require on-site measurements, are labor-intensive, and have low efficiency and accuracy. Summary of the Invention

[0003] This application provides a method, apparatus, and computer device for determining abnormal optical signal attenuation, so as to at least solve the technical problem of the large workload in optical attenuation judgment methods in related technologies.

[0004] According to one aspect of the embodiments of this application, a method for determining lines with abnormal optical signal attenuation is provided, comprising: acquiring multiple line resources in an optical distribution network (ODN) and dividing the multiple line resources into multiple line clusters; acquiring the line length and total optical attenuation value of each line in the line clusters to be determined, and determining an initial total optical attenuation regression equation for each line based on the line length and the total optical attenuation value; determining an optical attenuation offset value for each line based on the initial total optical attenuation regression equation, and splitting the lines in the line clusters to be determined into multiple groups of lines based on the optical attenuation offset value and the correlation coefficient of each line in the line clusters to be determined, wherein the correlation coefficient represents the degree of correlation between the line length and the total optical attenuation value; and selecting lines with abnormal optical signal attenuation from the multiple groups of lines respectively.

[0005] Optionally, the correlation coefficient of each line in the line cluster to be determined is determined by the following methods: determining a first coefficient based on the line length of each line in the line cluster to be determined; determining a second coefficient based on the total optical attenuation value of each line in the line cluster to be determined; determining a third coefficient based on the line length and total optical attenuation value of each line in the line cluster to be determined; and determining the correlation coefficient based on the first coefficient, the second coefficient, and the third coefficient.

[0006] Optionally, determining the initial full-range optical attenuation regression equation for each line based on the line length and the full-range optical attenuation value includes: obtaining the average line length and the average full-range optical attenuation value of all lines in the line cluster to be determined; determining the slope of the initial full-range optical attenuation regression equation based on the average line length, the average full-range optical attenuation value, the line length of each line, and the full-range optical attenuation value of each line; and determining the initial full-range optical attenuation regression equation based on the slope of the initial full-range optical attenuation regression equation.

[0007] Optionally, based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, the lines in the line cluster to be determined are split into multiple groups of lines, including: determining the calculated optical attenuation value of each line according to the initial full-range optical attenuation regression equation, and obtaining the actual optical attenuation value of each line; determining the optical attenuation offset value according to the actual optical attenuation value and the calculated optical attenuation value; if the correlation coefficient is not a preset target value, sequentially eliminating lines in the line cluster to be determined in descending order of the optical attenuation offset value until the correlation coefficient is equal to the preset target value, and determining the remaining lines in the line cluster to be determined as the first group of lines in the multiple groups of lines; further grouping the eliminated lines to obtain the remaining groups in the multiple groups of lines.

[0008] Optionally, selecting lines with abnormal optical signal attenuation from multiple groups of lines includes: obtaining the line length and total optical attenuation value of each line in the first group of lines; determining the total optical attenuation regression equation for each line in the first group of lines based on the line length and total optical attenuation value, and defining it as the central regression equation; dividing the eliminated lines into a second group of lines and a third group of lines in the multiple groups of lines based on the optical attenuation offset value; obtaining the total optical attenuation regression equation for the second group of lines and the total optical attenuation regression equation for the third group of lines respectively; selecting an abnormal regression equation from the central regression equation, the total optical attenuation regression equation for the second group of lines, and the total optical attenuation regression equation for the third group of lines, and determining the line corresponding to the abnormal regression equation as the line with abnormal optical signal attenuation.

[0009] Optionally, the rejected lines are divided into a second group and a third group based on the optical attenuation offset value, including: identifying the rejected lines with an optical attenuation offset value greater than zero as the second group; and identifying the rejected lines with an optical attenuation offset value less than zero as the third group.

[0010] Optionally, selecting an abnormal regression equation from the central regression equation, the full-length optical attenuation regression equation of the second group of lines, and the full-length optical attenuation regression equation of the third group of lines includes: obtaining a detection target value, the detection target value including: a slope target value and an optical branch device (OBD) target value; if the detection target value is the slope target value, determining the regression equation with a slope greater than the slope target value as an abnormal regression equation; if the detection target value is the OBD target value, determining the regression equation with an optical attenuation value greater than the OBD target value as an abnormal regression equation.

[0011] According to another aspect of the embodiments of this application, a device for determining lines with abnormal optical signal attenuation is also provided, comprising: a first acquisition module, configured to acquire multiple line resources in an optical distribution network (ODN) and divide the multiple line resources into multiple line clusters; a second acquisition module, configured to acquire the line length and total optical attenuation value of each line in the line clusters to be determined, and determine an initial total optical attenuation regression equation for each line based on the line length and the total optical attenuation value; a grouping module, configured to determine the optical attenuation offset value of each line based on the initial total optical attenuation regression equation, and split the lines in the line clusters to be determined into multiple groups of lines based on the optical attenuation offset value and the correlation coefficient of each line in the line clusters to be determined, wherein the correlation coefficient represents the degree of correlation between the line length and the total optical attenuation value; and a selection module, configured to select lines with abnormal optical signal attenuation from the multiple groups of lines respectively.

[0012] According to another aspect of the embodiments of this application, a computer device is also provided, including: a memory and a processor, wherein the memory is used to store program instructions; the processor is connected to the memory and is used to execute the above-described method for determining the line of optical signal attenuation anomaly.

[0013] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned method for determining abnormal optical signal attenuation by running the computer program.

[0014] According to another aspect of the embodiments of this application, a computer program product is also provided, including computer instructions that, when executed by a processor, implement the above-described method for determining abnormal optical signal attenuation.

[0015] In this embodiment, multiple line resources in the optical distribution network (ODN) are acquired and divided into multiple line clusters. The line length and total optical attenuation value of each line in the line cluster to be determined are acquired, and an initial total optical attenuation regression equation for each line is determined based on the line length and the total optical attenuation value. The optical attenuation offset value of each line is determined based on the initial total optical attenuation regression equation, and the lines in the line cluster to be determined are split into multiple groups of lines based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined. The correlation coefficient represents the degree of correlation between the line length and the total optical attenuation value. Lines with abnormal optical signal attenuation are selected from the multiple groups of lines, thereby achieving the purpose of determining the optical attenuation regression equation based on the correlation between the line length and the total optical attenuation value. This achieves the technical effect of avoiding on-site statistical analysis of optical attenuation and reducing the workload of optical attenuation judgment, thus solving the technical problem of large workload in optical attenuation judgment methods in related technologies. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0017] Figure 1 This is a hardware structure block diagram of a computer terminal for implementing a method for determining abnormal optical signal attenuation according to an embodiment of this application.

[0018] Figure 2 This is a flowchart of a method for determining an optical signal attenuation anomaly according to an embodiment of this application;

[0019] Figure 3 This is a flowchart of a method for determining the regression equation for each line according to an embodiment of this application;

[0020] Figure 4 This is a structural diagram of a line determination device for optical signal attenuation abnormality according to an embodiment of this application. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0023] The information collected in this application embodiment is information and data authorized by the user or fully authorized by all parties. The collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant regions, and necessary confidentiality measures have been taken. It does not violate public order and good morals, and provides corresponding operation entry points for users to choose to authorize or reject the automated decision results. If the user chooses to reject, the process will proceed to the expert decision-making process.

[0024] To facilitate a better understanding of the embodiments of this application by those skilled in the art, some technical terms or nouns involved in the embodiments of this application are explained as follows:

[0025] ODN (Optical Distribution Network) is an FTTH (Fiber To The Home) optical cable network based on PON (Passive Optical Network) equipment. Its main function is to provide an optical transmission channel between OLT (Optical Line Terminal) and ONU (Optical Network Unit). ODN networks use passive optical devices such as optical cables, connectors, and splitters to transmit and distribute optical signals.

[0026] End-to-end optical attenuation: The optical signal attenuation value from the optical module to the user end in the ODN network line, which refers to the difference between the light emitted by the optical module and the light received by the user end.

[0027] Correlation coefficient: Generally expressed as r, it is used to calculate the linear correlation between paired data. Generally, r < 0.4 indicates a weak correlation, and r > 0.8 indicates a strong correlation. The magnitude of the correlation coefficient can be set differently depending on the actual quality requirements.

[0028] To address the problems existing in related technologies, embodiments of this application provide a method for determining lines with abnormal optical signal attenuation. This method can be implemented in... Figure 1 The computer terminal shown is explained below.

[0029] The method for determining abnormal optical signal attenuation provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal for implementing a method to determine optical signal attenuation anomalies is shown. Figure 1 As shown, the computer terminal 10 may include one or more processors (shown as 102a, 102b, ..., 102n in the figure) (the processor may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission module 106 for communication functions connected via wired and / or wireless networks. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, and a BUS bus. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0030] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be implemented wholly or partially as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be wholly or partially integrated into any other element in the computer terminal 10. As involved in the embodiments of this application, the data processing circuits serve as processor control (e.g., selection of a variable resistor termination path connected to an interface).

[0031] The memory 104 can be used to store software programs and modules for application software, such as the program instructions / data storage device corresponding to the optical signal attenuation anomaly line determination method in this embodiment. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned optical signal attenuation anomaly line determination method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0032] The transmission module 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission module 106 includes a network interface controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission module 106 may be a radio frequency (RF) module, used for wireless communication with the Internet.

[0033] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10.

[0034] It should be noted here that, in some optional embodiments, the above... Figure 1 The computer terminal shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 1 This is only one instance of a specific particular instance, and is intended to illustrate the types of components that may exist in the aforementioned computer terminal.

[0035] Under the above operating environment, this application provides an embodiment of a method for determining a line with abnormal optical signal attenuation. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0036] Figure 2 This is a flowchart of a method for determining an abnormal optical signal attenuation according to an embodiment of this application, as shown below. Figure 2 As shown, the method includes the following steps:

[0037] Step S202: Obtain multiple line resources in the optical distribution network (ODN) and divide the multiple line resources into multiple line clusters;

[0038] In step S202, due to the different optical attenuation characteristics of lines in different areas, the line resources of the ODN network are clustered. Depending on the actual situation, clustering is performed by optical modules, racks, equipment rooms, etc. For example, if optical modules are selected as the clustering basis, then all lines connected to the same optical module will be grouped into the same cluster; if equipment rooms are selected, then all lines located in the same equipment room will be grouped into the same cluster. In actual application scenarios, it is generally recommended that each cluster contain 500-1000 users to ensure sufficient data for statistical analysis, while not being too large to cause low computing efficiency.

[0039] Step S204: Obtain the line length and total optical attenuation value of each line in the line cluster to be determined, and determine the initial total optical attenuation regression equation for each line based on the line length and the total optical attenuation value.

[0040] Step S206: Determine the optical attenuation offset value of each line according to the initial full-path optical attenuation regression equation, and based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, split the lines in the line cluster to be determined into multiple groups of lines, wherein the correlation coefficient represents the degree of correlation between the line length and the full-path optical attenuation value;

[0041] Step S208: Select the line with abnormal optical signal attenuation from multiple groups of lines.

[0042] Through steps S202 to S208 above, multiple line resources in the optical distribution network (ODN) are acquired and divided into multiple line clusters. The line length and total optical attenuation value of each line in the line cluster to be determined are obtained, and an initial total optical attenuation regression equation for each line is determined based on the line length and the total optical attenuation value. The optical attenuation offset value of each line is determined based on the initial total optical attenuation regression equation, and based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, the lines in the line cluster to be determined are split into multiple groups of lines, where the correlation coefficient represents the degree of correlation between line length and total optical attenuation value. Lines with abnormal optical signal attenuation are selected from these multiple groups of lines, thereby achieving the goal of determining the optical attenuation regression equation based on the correlation between line length and total optical attenuation value. This achieves the technical effect of avoiding on-site statistical analysis of optical attenuation, reducing the workload of optical attenuation judgment, and thus solving the technical problem of the large workload in optical attenuation judgment methods in related technologies. The following is a detailed explanation.

[0043] In some embodiments of this application, the correlation coefficient of each line in the line cluster to be determined is determined by the following methods: determining a first coefficient based on the line length of each line in the line cluster to be determined; determining a second coefficient based on the total optical attenuation value of each line in the line cluster to be determined; determining a third coefficient based on the line length and total optical attenuation value of each line in the line cluster to be determined; and determining the correlation coefficient based on the first coefficient, the second coefficient, and the third coefficient.

[0044] It should be noted that parameters such as the line length and optical signal attenuation value of the optical signal can be collected through the big data acquisition results of the optical module and the optical modem probe. It can be understood that the line length and the total signal attenuation are linearly correlated. In this embodiment of the application, the line length and the total optical attenuation value are compared for prediction. The prediction method can be obtained by drawing a scatter plot and comparing it with the typical example method, which shows that the line length and the optical signal attenuation are positively correlated.

[0045] Let X be the length of each line in the line cluster to be determined. i The corresponding total optical attenuation value (actual optical attenuation value) is Y. i Taking positive integers i = 1, 2, ..., n as an example, the calculation method of the first coefficient is as follows:

[0046]

[0047] In the formula, L XX represents the first coefficient, and N represents the total number of lines in the line cluster to be determined.

[0048] The second coefficient is calculated as follows:

[0049]

[0050] In the formula, L YY This indicates the second coefficient.

[0051] The third coefficient is calculated as follows:

[0052]

[0053] In the formula, L XY This represents the third coefficient.

[0054] The correlation coefficient r can be determined by the following formula:

[0055]

[0056] In some embodiments of this application, the specific process of determining the initial full-range optical attenuation regression equation for each line based on the line length and the full-range optical attenuation value is as follows: obtaining the average line length and the average full-range optical attenuation of all lines in the line cluster to be determined; determining the slope of the initial full-range optical attenuation regression equation based on the average line length, the average full-range optical attenuation, the line length of each line, and the full-range optical attenuation value of each line; and determining the initial full-range optical attenuation regression equation based on the slope of the initial full-range optical attenuation regression equation.

[0057] Specifically, the calculation method for the full-process optical decay regression equation is as follows:

[0058]

[0059] In some embodiments of this application, the specific steps for splitting the lines in the line cluster to be determined into multiple groups of lines based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined are as follows: The calculated optical attenuation value of each line is determined according to the initial full-range optical attenuation regression equation, and the actual optical attenuation value of each line is obtained; the optical attenuation offset value is determined according to the actual optical attenuation value and the calculated optical attenuation value; if the correlation coefficient is not a preset target value, lines in the line cluster to be determined are sequentially eliminated in descending order of the optical attenuation offset value until the correlation coefficient equals the preset target value, and the remaining lines in the line cluster to be determined are determined as the first group of lines in the multiple groups of lines; the eliminated lines are further grouped to obtain the remaining groups in the multiple groups of lines.

[0060] Understandably, after obtaining the first set of lines, the full optical attenuation regression equation for each line in the first set of lines is calculated based on each line in the first set of lines, where the slope and intercept of the regression equation for the first set of lines are k1 and b1, respectively.

[0061] Specifically, the optical attenuation offset value ΔY i It can be determined by the following formula:

[0062]

[0063] In the formula, Indicates the slope. This represents the intercept.

[0064] Optionally, the optical attenuation offset values ​​can be sorted from largest to smallest, and lines with larger squared optical attenuation offset values ​​can be removed one by one.

[0065] It should be noted that the preset target value can be set according to the actual scenario, for example: 0.8.

[0066] In some embodiments of this application, selecting lines with abnormal optical signal attenuation from multiple groups of lines includes: obtaining the line length and total optical attenuation value of each line in the first group of lines; determining the total optical attenuation regression equation of each line in the first group of lines based on the line length and total optical attenuation value, and defining it as the central regression equation; dividing the eliminated lines into a second group of lines and a third group of lines based on the optical attenuation offset value; obtaining the total optical attenuation regression equation of the second group of lines and the total optical attenuation regression equation of the third group of lines respectively; selecting an abnormal regression equation from the central regression equation, the total optical attenuation regression equation of the second group of lines, and the total optical attenuation regression equation of the third group of lines, and determining the line corresponding to the abnormal regression equation as the line with abnormal optical signal attenuation.

[0067] The specific steps for dividing the rejected lines into the second and third groups of lines based on the optical attenuation offset value are as follows: the lines with an optical attenuation offset value greater than zero among the rejected lines are identified as the second group of lines; the lines with an optical attenuation offset value less than zero among the rejected lines are identified as the third group of lines.

[0068] It should be noted that after dividing the excluded routes into a second group and a third group, the second and third groups can be further subdivided into multiple different groups based on different target correlation coefficient values. The subdivision method is similar to that used to divide the first group, and will not be repeated here. This yields regression equations for multiple groups of routes (including the first group). The slopes and intercepts of the regression equations are as follows: k1, k2…k m b1, b2…b m , m represents the number of multiple lines.

[0069] The selection of abnormal regression equations from the central regression equation, the full-length optical attenuation regression equations of the second group of lines, and the full-length optical attenuation regression equations of the third group of lines includes: obtaining a detection target value, which includes a slope target value and an optical branching device (OBD) target value; when the detection target value is the slope target value, determining the regression equation with a slope greater than the slope target value as an abnormal regression equation; when the detection target value is the OBD target value, determining the regression equation with an optical attenuation value greater than the OBD target value as an abnormal regression equation.

[0070] It should be noted that the OBD target value refers to the optical attenuation value associated with the optical branching device, that is, the target value of the attenuation generated when the optical signal passes through the OBD.

[0071] To further explain the method for determining the path of optical signal attenuation anomalies in this application, the following example is provided:

[0072] Taking a certain optical line terminal connected to 875 broadband users (lines) as an example, by using the correlation coefficient between the line length of each user and the total optical attenuation, r = 0.37, the slope of the regression equation is 0.1933, and the intercept is 23.7321,

[0073] Offset values ​​ΔY for each user i =(Y i -(0.1933X i +23.7321), sort from largest to smallest, and when setting the target value of r, remove users with 328 offset values, leaving 547 users.

[0074] Recalculating for the remaining 547 users yields r = 0.80, with a slope of 0.1842 and an intercept of 23.8119 in the regression equation. At this point, a strongly positively correlated central regression equation is obtained.

[0075] Select the 328 users with larger offset values ​​and press ΔY. i >0 and ΔY i The values ​​<0 are divided into parts, and the slope, intercept, and regression equation are recalculated for each part.

[0076] Repeating the above method of removing lines (users) with large offset values ​​and recalculating the slope, intercept, and regression equation, we finally obtained q regression equations for 875 broadband users:

[0077] y q =k q X+b q .

[0078] Among them, y q k represents the calculated optical attenuation value for the q-th user. q Let b represent the slope of the q-th user. q X represents the intercept value for the q-th user, and X represents the line length.

[0079] Finally, abnormal broadband users were detected.

[0080] Figure 3 It also shows a method for calculating the regression equation for each line, such as... Figure 3As shown, the process includes: determining parameters related to optical signal attenuation; clustering line data; calculating the correlation coefficient between line length and total optical attenuation; calculating the regression equation between the line length and total optical attenuation for each line in the cluster; setting the target value for the required correlation coefficient; calculating the offset between the actual optical attenuation value of each line and the regression equation; removing large offset values ​​based on the target value of the correlation coefficient to form a new regression equation; calculating the regression equation (central regression equation) for the retained data; and splitting the data to establish multiple regression equations.

[0081] Figure 4 This application discloses a line determination device for optical signal attenuation anomalies, comprising:

[0082] The first acquisition module 40 is used to acquire multiple line resources in the optical distribution network (ODN) and divide the multiple line resources into multiple line clusters;

[0083] The second acquisition module 42 is used to acquire the line length and total optical attenuation value of each line in the line cluster to be determined, and to determine the initial total optical attenuation regression equation of each line based on the line length and the total optical attenuation value.

[0084] Grouping module 44 is used to determine the optical attenuation offset value of each line according to the initial full-length optical attenuation regression equation, and to split the lines in the line cluster to be determined into multiple groups of lines based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, wherein the correlation coefficient represents the degree of correlation between the line length and the full-length optical attenuation value;

[0085] Selection module 46 is used to select lines with abnormal optical signal attenuation from multiple groups of lines.

[0086] The aforementioned optical signal attenuation anomaly identification device acquires multiple line resources in the optical distribution network (ODN) and divides these resources into multiple line clusters. It acquires the line length and total optical attenuation value of each line in the cluster to be identified, and determines an initial total optical attenuation regression equation for each line based on these values. It then determines the optical attenuation offset value for each line based on the initial total optical attenuation regression equation, and, based on the optical attenuation offset value and the correlation coefficient between the optical attenuation offset value and each line in the cluster, splits the lines in the cluster into multiple groups of lines. The correlation coefficient represents the degree of correlation between line length and total optical attenuation value. Lines with abnormal optical signal attenuation are selected from these groups, thus achieving the goal of determining the optical attenuation regression equation based on the correlation between line length and total optical attenuation value. This avoids the need for on-site statistical analysis of optical attenuation, reducing the workload of optical attenuation judgment and solving the technical problem of the large workload in related optical attenuation judgment methods.

[0087] The grouping module 44 includes a coefficient submodule, used to determine the correlation coefficient of each line in the line cluster to be determined, which is determined by the following methods: determining a first coefficient based on the line length of each line in the line cluster to be determined; determining a second coefficient based on the total optical attenuation value of each line in the line cluster to be determined; determining a third coefficient based on the line length and total optical attenuation value of each line in the line cluster to be determined; and determining the correlation coefficient based on the first coefficient, the second coefficient, and the third coefficient.

[0088] The coefficient submodule includes an equation unit, used to determine the initial full-range optical attenuation regression equation for each line based on the line length and the full-range optical attenuation value, including: obtaining the average line length and average full-range optical attenuation value of all lines in the line cluster to be determined; determining the slope of the initial full-range optical attenuation regression equation based on the average line length, the average full-range optical attenuation value, the line length of each line, and the full-range optical attenuation value of each line; and determining the initial full-range optical attenuation regression equation based on the slope of the initial full-range optical attenuation regression equation.

[0089] The grouping module 44 further includes a grouping submodule, used to split the lines in the line cluster to be determined into multiple groups of lines based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, including: determining the calculated optical attenuation value of each line according to the initial full-range optical attenuation regression equation, and obtaining the actual optical attenuation value of each line; determining the optical attenuation offset value according to the actual optical attenuation value and the calculated optical attenuation value; when the correlation coefficient is not a preset target value, sequentially removing lines in the line cluster to be determined in descending order of the optical attenuation offset value until the correlation coefficient is equal to the preset target value, and determining the remaining lines in the line cluster to be determined as the first group of lines in the multiple groups of lines; and further grouping the removed lines to obtain the remaining groups in the multiple groups of lines.

[0090] The grouping submodule is used to select lines with abnormal optical signal attenuation from multiple groups of lines, including: obtaining the line length and total optical attenuation value of each line in the first group of lines; determining the total optical attenuation regression equation of each line in the first group of lines based on the line length and total optical attenuation value of each line in the first group of lines, and determining it as the center regression equation; dividing the rejected lines into a second group of lines and a third group of lines based on the optical attenuation offset value; obtaining the total optical attenuation regression equation of the second group of lines and the total optical attenuation regression equation of the third group of lines respectively; selecting the abnormal regression equation from the center regression equation, the total optical attenuation regression equation of the second group of lines, and the total optical attenuation regression equation of the third group of lines, and determining the line corresponding to the abnormal regression equation as the line with abnormal optical signal attenuation.

[0091] The grouping submodule includes a grouping unit and a detection unit. The grouping unit is used to divide the rejected lines into a second group and a third group of lines among the multiple groups of lines according to the optical attenuation offset value. This includes: identifying lines among the rejected lines whose optical attenuation offset value is greater than zero as the second group of lines; and identifying lines among the rejected lines whose optical attenuation offset value is less than zero as the third group of lines.

[0092] The detection unit is used to select abnormal regression equations from the central regression equation, the full-length optical attenuation regression equation of the second group of lines, and the full-length optical attenuation regression equation of the third group of lines. The selection includes: obtaining a detection target value, which includes a slope target value and an optical branch device (OBD) target value; if the detection target value is the slope target value, determining regression equations with a slope greater than the slope target value as abnormal regression equations; and if the detection target value is the OBD target value, determining regression equations with an optical attenuation value greater than the OBD target value as abnormal regression equations.

[0093] It should be noted that, Figure 4 The front-end information acquisition device shown is used to perform Figure 2 The method for determining the line with abnormal optical signal attenuation shown above also applies to the device for determining the line with abnormal optical signal attenuation, and will not be repeated here.

[0094] This application also provides a computer device, including: a memory and a processor, wherein the memory is used to store program instructions; and the processor, connected to the memory, is used to execute the above-described method for determining the line of optical signal attenuation anomaly.

[0095] This application also provides a non-volatile storage medium, which includes a stored computer program, wherein the device containing the non-volatile storage medium executes the above-mentioned method for determining abnormal optical signal attenuation by running the computer program.

[0096] This application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the method for determining abnormal optical signal attenuation in this application.

[0097] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0098] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0100] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0101] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0102] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0103] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for determining a line with abnormal optical signal attenuation, characterized in that, include: Acquire multiple line resources in the optical distribution network (ODN) and divide the multiple line resources into multiple line clusters; Obtain the line length and total optical attenuation value of each line in the line cluster to be determined, and determine the initial total optical attenuation regression equation for each line based on the line length and the total optical attenuation value; The optical attenuation offset value of each line is determined according to the initial full-path optical attenuation regression equation. Based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, the lines in the line cluster to be determined are split into multiple groups of lines. The correlation coefficient represents the degree of correlation between the line length and the full-path optical attenuation value. Lines with abnormal optical signal attenuation are selected from the multiple groups of lines respectively. Based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, the lines in the line cluster to be determined are split into multiple groups of lines, including: determining the calculated optical attenuation value of each line according to the initial full-range optical attenuation regression equation, and obtaining the actual optical attenuation value of each line; determining the optical attenuation offset value according to the actual optical attenuation value and the calculated optical attenuation value; if the correlation coefficient is not a preset target value, sequentially eliminating lines in the line cluster to be determined in descending order of the optical attenuation offset value until the correlation coefficient is equal to the preset target value, and determining the remaining lines in the line cluster to be determined as the first group of lines in the multiple groups of lines; further grouping the eliminated lines to obtain the remaining groups in the multiple groups of lines; Select lines with abnormal optical signal attenuation from multiple groups of lines, including: Obtain the line length and total optical attenuation value of each line in the first group of lines; Based on the line length and total optical attenuation value of each line in the first group of lines, the total optical attenuation regression equation of each line in the first group of lines is determined, and it is determined as the central regression equation; The eliminated lines are divided into a second group and a third group based on the optical attenuation offset value; Obtain the full optical attenuation regression equations for the second group of lines and the full optical attenuation regression equations for the third group of lines, respectively. Select the abnormal regression equation from the central regression equation, the full optical attenuation regression equation of the second group of lines and the full optical attenuation regression equation of the third group of lines, and determine the line corresponding to the abnormal regression equation as the line with abnormal optical signal attenuation. From the central regression equation, the full-length optical attenuation regression equation of the second group of lines, and the full-length optical attenuation regression equation of the third group of lines, select the outlier regression equation, including: Acquire detection target values, including: slope target value and optical branching device (OBD) target value; If the detection target value is the slope target value, the regression equation with a slope greater than the slope target value is identified as an abnormal regression equation; When the detection target value is the OBD target value, the regression equation with a light attenuation value greater than the OBD target value is determined to be an abnormal regression equation.

2. The method according to claim 1, characterized in that, The correlation coefficient of each line in the line cluster to be determined is determined by the following methods: The first coefficient is determined based on the length of each line in the line cluster to be determined; The second coefficient is determined based on the total optical attenuation value of each line in the line cluster to be determined; The third coefficient is determined based on the line length and total optical attenuation value of each line in the line cluster to be determined; The correlation coefficient is determined based on the first coefficient, the second coefficient, and the third coefficient.

3. The method according to claim 2, characterized in that, The initial total optical attenuation regression equation for each line is determined based on the line length and the total optical attenuation value, including: Obtain the average line length and the average optical attenuation of all lines in the line cluster to be determined; The slope of the initial total optical attenuation regression equation is determined based on the average line length, the average total optical attenuation, the line length of each line, and the total optical attenuation value of each line. The initial full-range light decay regression equation is determined based on the slope of the initial full-range light decay regression equation.

4. The method according to claim 1, characterized in that, Based on the optical attenuation offset value, the eliminated lines are divided into a second group and a third group of lines among the multiple groups of lines, including: The lines with optical attenuation offset values ​​greater than zero among the eliminated lines are identified as the second group of lines; The lines whose optical attenuation offset value is less than zero among the eliminated lines are identified as the third group of lines.

5. A device for determining abnormal optical signal attenuation, characterized in that, include: The first acquisition module is used to acquire multiple line resources in the optical distribution network (ODN) and divide the multiple line resources into multiple line clusters; The second acquisition module is used to acquire the line length and total optical attenuation value of each line in the line cluster to be determined, and to determine the initial total optical attenuation regression equation for each line based on the line length and the total optical attenuation value. The grouping module is used to determine the optical attenuation offset value of each line according to the initial full-length optical attenuation regression equation, and to split the lines in the line cluster to be determined into multiple groups of lines based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, wherein the correlation coefficient represents the degree of correlation between the line length and the full-length optical attenuation value; The selection module is used to select lines with abnormal optical signal attenuation from multiple groups of lines; Based on the optical attenuation offset value and the correlation coefficient of each line in the line cluster to be determined, the lines in the line cluster to be determined are split into multiple groups of lines, including: determining the calculated optical attenuation value of each line according to the initial full-range optical attenuation regression equation, and obtaining the actual optical attenuation value of each line; determining the optical attenuation offset value according to the actual optical attenuation value and the calculated optical attenuation value; if the correlation coefficient is not a preset target value, sequentially eliminating lines in the line cluster to be determined in descending order of the optical attenuation offset value until the correlation coefficient is equal to the preset target value, and determining the remaining lines in the line cluster to be determined as the first group of lines in the multiple groups of lines; further grouping the eliminated lines to obtain the remaining groups in the multiple groups of lines; Select lines with abnormal optical signal attenuation from multiple groups of lines, including: Obtain the line length and total optical attenuation value of each line in the first group of lines; Based on the line length and total optical attenuation value of each line in the first group of lines, the total optical attenuation regression equation of each line in the first group of lines is determined, and it is determined as the central regression equation; The eliminated lines are divided into a second group and a third group based on the optical attenuation offset value; Obtain the full optical attenuation regression equations for the second group of lines and the full optical attenuation regression equations for the third group of lines, respectively. Select the abnormal regression equation from the central regression equation, the full optical attenuation regression equation of the second group of lines and the full optical attenuation regression equation of the third group of lines, and determine the line corresponding to the abnormal regression equation as the line with abnormal optical signal attenuation. From the central regression equation, the full-length optical attenuation regression equation of the second group of lines, and the full-length optical attenuation regression equation of the third group of lines, select the outlier regression equation, including: Acquire detection target values, including: slope target value and optical branching device (OBD) target value; If the detection target value is the slope target value, the regression equation with a slope greater than the slope target value is identified as an abnormal regression equation; When the detection target value is the OBD target value, the regression equation with a light attenuation value greater than the OBD target value is determined to be an abnormal regression equation.

6. A computer device, characterized in that, include: A memory and a processor, wherein the memory is used to store program instructions; The processor, connected to the memory, is used to execute the method for determining optical signal attenuation anomalies as described in any one of claims 1-4.

7. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the method for determining optical signal attenuation anomalies as described in any one of claims 1-4.

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