An optical fade interval positioning method, device and electronic equipment of an ODN network

Abstract

The embodiment of the application provides an optical decay interval positioning method and device of an ODN network and electronic equipment, relates to the technical field of communication, and comprises the following steps: obtaining a first regression equation of the length of a line of a cluster of an ODN network and the actual optical decay value of the line of the cluster; determining the offset value between the actual optical decay value of a line and the virtual optical decay value of the line calculated by the first regression equation of the cluster to which the line belongs; removing part of the lines from all the lines of the cluster; obtaining a second regression equation of the length of the line of the cluster and the actual optical decay value of the line of the cluster by using the removed lines in the cluster; obtaining a third regression equation of the actual optical decay value of the line of the cluster and the deviation value between the actual optical decay value of the line of the cluster and the virtual optical decay value of the line of the cluster calculated by the second regression equation of the cluster; and positioning the optical decay interval in the cluster based on the third regression equation of the cluster, so that the optical decay interval positioning is more accurate.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and in particular relates to a method, device, electronic device and readable storage medium for locating an optical attenuation interval of an ODN network. Background Art

[0002] An Optical Distribution Network (ODN) is a fiber optic cable network that sends and receives signals through optical transceivers and PON (Passive Optical Network) devices, transmitting optical signals through optical fibers and splitters.

[0003] However, during the transmission process of the ODN network, optical signals will attenuate. The degree of optical signal attenuation affects the user's service quality. By determining the optical attenuation interval and repairing and rectifying the optical attenuation interval to improve the service quality, optical attenuation interval positioning has become an important part of improving the quality of the optical network.

[0004] Traditional optical attenuation location methods mainly use on-site measurements with instruments such as OTDR (Optical Time Domain Reflectometer) to determine the optical attenuation range by comparing it with the target value. However, the workload of on-site measurements is very large, resulting in low efficiency in locating the optical attenuation range. Summary of the Invention

[0005] The present invention provides a method, device, electronic device and readable storage medium for locating an optical attenuation interval of an ODN network, so as to solve the technical problem of low efficiency in locating optical attenuation intervals in related technologies.

[0006] In a first aspect, the present invention provides a method for locating an optical attenuation interval of an ODN network, the method comprising:

[0007] Obtaining a first regression equation between the length of a line in a cluster of an ODN network and the actual optical attenuation value of the entire line of the cluster; the ODN network includes a plurality of clusters, and the cluster includes a plurality of lines;

[0008] Determine an offset value between an actual optical attenuation value of the entire line and a virtual optical attenuation value of the entire line calculated by the first regression equation of the cluster where the line belongs;

[0009] Eliminate some of the lines from all the lines in a cluster in descending order of the offset values, so that a first correlation coefficient between the length of the lines in the cluster after the elimination and the actual optical attenuation value of the lines in the cluster over the entire distance is greater than or equal to a preset correlation coefficient;

[0010] Using the lines removed from the cluster to obtain a second regression equation of the length of the lines in the cluster and the actual optical attenuation values ​​of the lines in the cluster over the entire process;

[0011] obtaining a third regression equation for the entire actual optical attenuation value of the lines of the cluster and a deviation value between the entire actual optical attenuation value of the lines of the cluster and the entire virtual optical attenuation value of the lines of the cluster calculated by the second regression equation of the cluster;

[0012] Based on the third regression equation of the cluster, the light attenuation interval within the cluster is located.

[0013] In a second aspect, the present invention provides an optical attenuation interval positioning device for an ODN network, the device comprising:

[0014] A first regression equation obtaining module is configured to obtain a first regression equation of the length of a line in a cluster of an ODN network and the actual optical attenuation value of the entire line of the cluster; the ODN network includes a plurality of clusters, and the cluster includes a plurality of lines;

[0015] an offset value determining module, configured to determine an offset value between an actual optical attenuation value of the entire line and a virtual optical attenuation value of the entire line calculated by the first regression equation of the cluster to which the line belongs;

[0016] a removal module, configured to remove some of the lines from all the lines in a cluster in descending order of the offset values, so that a first correlation coefficient between the length of the lines in the cluster after removal and the actual optical attenuation value of the lines in the cluster over the entire distance is greater than or equal to a preset correlation coefficient;

[0017] A second regression equation obtaining module, configured to obtain a second regression equation of the length of the lines in the cluster and the actual optical attenuation value of the lines in the cluster using the lines removed from the cluster;

[0018] a third regression equation obtaining module, configured to obtain a third regression equation for obtaining the actual optical attenuation value of the entire line of the cluster and a deviation value between the actual optical attenuation value of the entire line of the cluster and the virtual optical attenuation value of the entire line of the cluster calculated by the second regression equation of the cluster;

[0019] The light attenuation positioning module is configured to locate the light attenuation interval within the cluster based on the third regression equation of the cluster.

[0020] In a third aspect, the present invention provides an electronic device comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the optical attenuation interval positioning method of the ODN network is implemented.

[0021] In a fourth aspect, the present invention provides a readable storage medium. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the above-mentioned optical attenuation interval positioning method of the ODN network.

[0022] In a fifth aspect, the present invention provides a computer program product comprising instructions, which, when executed by a processor in an electronic device, enables the electronic device to execute the above-mentioned optical attenuation interval positioning method for an ODN network.

[0023] In an embodiment of the present invention, lines with large optical attenuation offset values ​​are eliminated through a preliminary calculated first regression equation, and a second regression equation with strong correlation to a cluster of eliminated lines is further calculated to obtain the actual optical attenuation value of the entire cluster of lines and a third regression equation for the deviation between the actual optical attenuation value of the entire cluster of lines and the virtual optical attenuation value of the entire cluster of lines calculated by the second regression equation. The deviation value here can accurately determine the optical attenuation offset, and the third regression equation has a stronger correlation. The optical attenuation interval within the cluster is determined by the third regression equation. On the one hand, the optical attenuation interval positioning of the present application is mainly performed through data calculation, without the need for a large amount of on-site measurement, thereby improving the efficiency of optical attenuation interval positioning and reducing costs. On the other hand, since the third regression equation used to determine the optical attenuation interval within the cluster has a stronger correlation with the optical attenuation offset, the optical attenuation interval determined within the cluster is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 This is a flowchart of the steps of a method for locating an optical attenuation interval of an ODN network provided by an embodiment of the present invention;

[0026] Figure 2 This is a schematic diagram of the correlation distribution between the actual optical attenuation value of a line and the length of the line in an ODN network provided by an embodiment of the present invention;

[0027] Figure 3 This is a flowchart of another method for locating optical attenuation intervals in an ODN network provided by an embodiment of the present invention;

[0028] Figure 4 This is a flowchart of the steps of another method for locating an optical attenuation interval of an ODN network provided by an embodiment of the present invention;

[0029] Figure 5 This is a structural diagram of an optical attenuation interval positioning device for an ODN network provided by an embodiment of the present invention;

[0030] Figure 6 This is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0032] Reference Figure 1 , Figure 1 This is a flowchart of a method for locating an optical attenuation interval of an ODN network provided by an embodiment of the present invention. Figure 1 As shown, the method may include:

[0033] Step 101: Obtain a first regression equation of the length of a line in a cluster of an ODN network and the actual optical attenuation value of the entire line of the cluster; the ODN network includes a plurality of clusters, and the cluster includes a plurality of lines.

[0034] An ODN network may generally include an OLT (Optical Line Terminal) device. The output port of the OLT device is connected to multiple optical cross-connect boxes via a line. The output port of each optical cross-connect box is connected to multiple first-level optical splitters via a line. Each first-level optical splitter box is connected to multiple second-level optical splitters via a line. Each second-level optical splitter box is connected to multiple user sides via a line. An entire line from the ODN to the user side may be considered as a full line. The multiple line segments of each full line include the line between the OLT device and the optical cross-connect box, the line segment between the optical cross-connect box and the first-level optical splitter, the line segment between the first-level optical splitter and the second-level optical splitter, and the line segment from the second-level optical splitter to the user side. The paths of multiple full lines between the second-level optical splitters may have a common line segment. The line here may be one full line or multiple full lines, or a partial line segment of a full line, etc., and there is no specific limitation on this. The line here may include a line segment connected to the user end or the user side. The line segment connected to the user end or the user side may be the tail of the line.

[0035] The ODN network comprises a plurality of clusters. It is to be noted that the plurality of clusters mentioned in the present application means one or more. A cluster herein comprises a plurality of lines. The ODN network comprises a specific number of clusters, and each cluster comprises a specific number of lines. The length of a line refers to the length of the line from the beginning to the end. The actual optical loss of the whole line refers to the deviation between the light value emitted by the head of the line and the light value received by the tail of the line, which reflects the actual loss of the whole line. For example, the line is a whole line, that is, a line from the OLT device to a user side. The length of the line is the total length of the line from the OLT device to the user side. The actual optical loss of the whole line is the deviation between the light value emitted by the OLT device and the light value received by the user side of the line.

[0036] The present application can obtain a first regression equation of the length of the line of a cluster of the ODN network and the actual optical loss of the whole line of the cluster by using the least square method. Specifically, the line number in a cluster is set as i, i = (1, 2, …, n), the length of a line in the cluster is X i , and the actual optical loss of the whole line of the line in the cluster is Y i . The determination process of the first regression equation of the actual optical loss of the whole line of the cluster can be as follows. The average value of the length of the line in the cluster is calculated as , and the average value of the actual optical loss of the whole line of the line in the cluster is calculated as , wherein The first regression equation of the length of the line of the cluster and the actual optical loss of the whole line of the cluster is , wherein b is a constant.

[0037] In the present application, other obtaining methods of the first regression equation of the length of the line of a cluster and the actual optical loss of the whole line of the cluster are not limited. One first regression equation corresponds to one cluster. The ODN network has a plurality of clusters, and each cluster corresponds to one first regression equation. For example, the ODN network has three clusters, and each cluster corresponds to one first regression equation, thereby obtaining three first regression equations.

[0038] Optionally, before the step 101, the method can further comprise: finding a line parameter related to optical loss. Specifically, the line length, optical signal number decay value and other parameters of optical signal transmission can be collected through the big data collection results of optical module sources, optical cat probes and the like. By drawing a scatter plot and comparing with a typical legend method, as shown in FIG. 1, it can be found that the line length of the line to be predicted and the actual optical loss of the whole line of the line are in a linear correlation relationship, and the linear correlation relationship is positive. Figure 2 Figure 2 In the figure, the abscissa is the line length to be predicted, and the ordinate is the actual optical loss of the whole line of the line.

[0039] ​Step 102, determine the offset value between the actual optical attenuation value of the whole length of a line and the virtual optical attenuation value of the whole length of the line calculated by the first regression equation of the cluster where the line is located.

[0040] This step is to determine the offset value for each line in the cluster. In the case of multiple clusters in the ODN network, this step is to determine the offset value for each line in each cluster. The first regression equation of the cluster is used for all lines in the cluster. For example, a cluster contains 50 lines, and there are 150 lines in 3 clusters of the ODN network. This step is to determine the offset value for each of the 150 lines, and the first regression equation of the cluster is used for the 50 lines in the cluster. For a line in a cluster, the offset value between the actual optical attenuation value of the whole length of the line and the virtual optical attenuation value of the whole length of the line calculated by the first regression equation of the cluster where the line is located

[0041] Step 103, from all the lines in a cluster, remove part of the lines in the order of the offset value from large to small, so that the first correlation coefficient between the length of the lines in the cluster after removal and the actual optical attenuation value of the whole length of the lines in the cluster is greater than or equal to a preset correlation coefficient.

[0042] In a cluster of lines, lines with too large offset values can be considered as abnormal lines. Therefore, from all the lines in the cluster, remove the lines with larger offset values. After removal, the number of lines in the cluster will decrease, and the first correlation coefficient between the length of the lines in the cluster after removal and the actual optical attenuation value of the whole length of the lines in the cluster is greater than or equal to a preset correlation coefficient.

[0043] Suppose the number of lines in the cluster after removal is N, then the first correlation coefficient r between the length of the lines in the cluster after removal and the actual optical attenuation value of the whole length of the lines in the cluster can be determined in the following way, where X i . Where L XX is the sum of squared deviations of the length of the lines in the cluster after removal, L YY is the sum of squared deviations of the actual optical attenuation value of the whole length of the lines in the cluster after removal, and L XY is the covariance of the length of the lines in the cluster after removal and the actual optical attenuation value of the whole length of the lines in the cluster after removal. Here, X i refers to the length of the i-th line in the cluster after removing part of the lines, and Y i refers to the actual optical attenuation value of the whole length of the i-th line in the cluster after removing part of the lines.

[0044] Generally, for an ODN network, a correlation coefficient less than 0.4 is considered weak correlation, and a correlation coefficient greater than or equal to 0.8 is considered strong correlation. The preset correlation coefficient here can be set according to actual needs.

[0045] Optionally, the preset correlation coefficient here can be 0.8, then the first correlation coefficient between the length of the line of the cluster after removal and the actual optical attenuation value of the entire line of the cluster after removal is greater than or equal to 0.8, indicating that the correlation is very strong. For example, the first correlation coefficient between the length of the line of the cluster after removal and the actual optical attenuation value of the entire line of the cluster after removal can be 0.8, 0.82, 0.85, 0.87, 0.89, 0.9, 0.91, 0.95, 0.96, etc. It should be noted that when the ODN network contains multiple clusters, the number of lines removed in each cluster can be equal or unequal, and the first correlation coefficients of the clusters after removal can be equal, or unequal, or partially equal, or partially unequal, and there is no specific limitation on this.

[0046] When the ODN network has multiple clusters, each cluster is eliminated so that a first correlation coefficient between the length of the line of each cluster after elimination and the actual optical attenuation value of the entire line of the cluster after elimination is greater than or equal to a preset correlation coefficient.

[0047] It should be noted that, before being eliminated, the second correlation coefficient between the length of a cluster of lines and the actual optical attenuation value of the entire line of the cluster is usually smaller than the first correlation coefficient between the length of the cluster of lines and the actual optical attenuation value of the entire line of the cluster after being eliminated. That is, for the same cluster, the first correlation coefficient is greater than the second correlation coefficient.

[0048] Optionally, before step 103, the method may further include: S1, obtaining a second correlation coefficient between the length of a cluster of lines and the actual optical attenuation values ​​of the lines in the cluster over their entire length; S2, setting a preset correlation coefficient corresponding to the cluster based on the second correlation coefficient corresponding to the cluster; for the same cluster, the preset correlation coefficient is greater than the second correlation coefficient. Here, S1 uses the lengths of the existing lines in the cluster before line removal and the actual optical attenuation values ​​of the existing lines in the cluster over their entire length to obtain the second correlation coefficient for the cluster. Each cluster corresponds to a second correlation coefficient. The method for obtaining the second correlation coefficient is similar to the method for obtaining the first correlation coefficient, and will not be described here to avoid repetition. Typically, before line removal, the second correlation coefficient for the cluster is approximately 0.15 to 0.4, indicating a weak correlation. When setting the preset correlation coefficient for a cluster, it is necessary to ensure that the preset correlation coefficient is greater than the second correlation coefficient for the same cluster. This elimination method will help improve correlation and further enhance the accuracy of subsequent optical attenuation interval positioning.

[0049] Step 104, obtaining a second regression equation of the length of the line in the cluster and the actual optical attenuation value of the whole journey of the line in the cluster by using the line in the cluster after the irrelevant line is removed.

[0050] After the irrelevant line in a cluster is removed, the more relevant line is left to obtain the second regression equation of the length of the line in the cluster and the actual optical attenuation value of the whole journey of the line in the cluster. Since the irrelevant line in the cluster is removed, the second regression equation obtained is more accurate.

[0051] The process of obtaining the second regression equation here can be similar to the way of obtaining the first regression equation described above, which will not be repeated here. Here, one cluster corresponds to one second regression equation. The ODN network contains several clusters, and several second regression equations are obtained. For example, one second regression equation obtained for a cluster can be The second regression equation here is characterizing the actual optical attenuation value of the whole journey of the line in the cluster after the irrelevant line is removed, characterizing the length of the line in the cluster after the irrelevant line is removed.

[0052] Step 105, obtaining a third regression equation of the actual optical attenuation value of the whole journey of the line in the cluster and the deviation value between the actual optical attenuation value of the whole journey of the line in the cluster and the virtual optical attenuation value of the whole journey of the line in the cluster calculated by the second regression equation of the cluster.

[0053] In this step, one cluster corresponds to one third regression equation. The actual optical attenuation value used to obtain the third regression equation is the actual optical attenuation value of each line in the cluster before being removed, and the deviation value used is also calculated according to the second regression equation of the cluster. For example, for a line in a cluster, the deviation value here is

[0054]

[0055] The way of obtaining the third regression equation is similar to the way of obtaining the first regression equation described above, which will not be repeated here. Here, one cluster corresponds to one third regression equation. The ODN network contains several clusters, and several third regression equations are obtained.

[0056] It should be noted that the present application can also calculate the third correlation coefficient of the actual optical attenuation value of the whole journey of the line in the cluster and the deviation value between the actual optical attenuation value of the whole journey of the line in the cluster and the virtual optical attenuation value of the whole journey of the line in the cluster calculated by the second regression equation of the cluster, that is, to calculate Y i and ΔY iThe third correlation coefficient is significantly higher than the second correlation coefficient between the length of the cluster's lines and the actual optical attenuation values ​​of the cluster's lines before the lines are removed. This third correlation coefficient is also significantly higher than the first correlation coefficient between the length of the cluster's lines and the actual optical attenuation values ​​of the cluster's lines after the lines are removed. It should be noted that for the same cluster, the second correlation coefficient is typically lower than the first correlation coefficient, and the first correlation coefficient is typically lower than the third correlation coefficient. This indicates that the actual optical attenuation values ​​of the cluster's lines are more highly correlated with the deviation between the actual optical attenuation values ​​of the cluster's lines and the virtual optical attenuation values ​​of the cluster's lines calculated by the second regression equation for the cluster, resulting in more accurate positioning of the optical attenuation interval.

[0057] Step 106: Position the light attenuation interval within the cluster based on the third regression equation of the cluster.

[0058] A third regression equation is formed based on the actual optical attenuation value of the entire line of the cluster and the deviation between the actual optical attenuation value of the entire line of the cluster and the virtual optical attenuation value of the entire line of the cluster calculated by the second regression equation. The deviation value here can accurately offset the optical attenuation, and the third regression equation has a stronger correlation. The optical attenuation range within the cluster is determined by the third regression equation.

[0059] In summary, in an embodiment of the present invention, lines with large optical attenuation offset values ​​are eliminated through a preliminary calculated first regression equation, and a second regression equation with strong correlation to a cluster of eliminated lines is further calculated to further obtain the actual optical attenuation value of the entire cluster of lines and a third regression equation for the deviation between the actual optical attenuation value of the entire cluster of lines and the virtual optical attenuation value of the entire cluster of lines calculated by the second regression equation. The deviation value here can accurately determine the optical attenuation offset, and the correlation of the third regression equation is stronger. The optical attenuation interval within the cluster is determined by the third regression equation. On the one hand, the optical attenuation interval positioning of the present application is mainly performed through data calculation, without the need for a large amount of on-site measurement, thereby improving the efficiency of optical attenuation interval positioning and reducing costs. On the other hand, since the third regression equation used to determine the optical attenuation interval within the cluster has a stronger correlation with the optical attenuation offset, the optical attenuation interval determined within the cluster is more accurate.

[0060] Reference Figure 3 , Figure 3 This is a flowchart of another method for locating the optical attenuation interval of an ODN network provided by an embodiment of the present invention. Figure 3 As shown, the method may include:

[0061] Step 201 : Divide the multiple lines of the ODN network into a plurality of clusters according to the similarity of the optical attenuation environments of the lines; or divide the multiple lines of the ODN network into a plurality of clusters according to the sources of the optical signals used by the lines.

[0062] Clustering can be done by aligning the optical attenuation environments of the lines within a cluster to roughly match the optical attenuation levels of each line within it. Typically, lines sharing a common optical signal source have similar construction times and usage. Therefore, clustering based on the optical signal source of each line within a cluster can help to identify similar optical attenuation factors within the cluster. These two clustering methods improve the accuracy of subsequent optical attenuation interval location by aligning the optical attenuation-related factors of each line within the cluster.

[0063] For example, multiple lines of the ODN network can be clustered using shared optical module sources, racks, and computer rooms.

[0064] It should be noted that the "multiple lines" of the ODN network herein can refer to all or part of the lines of the ODN network, without any specific limitation. Furthermore, in addition to the two aforementioned clustering methods, multiple lines of the ODN network can also be clustered based on, for example, the optical attenuation characteristics of lines in different regions, without any specific limitation on the clustering method.

[0065] Step 202: Obtain a first regression equation of the length of a line in a cluster of an ODN network and the actual optical attenuation value of the entire line of the cluster; the ODN network includes a plurality of clusters, and the cluster includes a plurality of lines.

[0066] Step 203: Determine an offset value between an actual optical attenuation value of the entire line and a virtual optical attenuation value of the entire line calculated by the first regression equation of the cluster where the line belongs.

[0067] Step 204 : From all the lines in a cluster, some of the lines are removed in descending order of the offset values, so that a first correlation coefficient between the length of the lines in the cluster after the removal and the actual optical attenuation value of the entire line of the cluster is greater than or equal to a preset correlation coefficient.

[0068] Step 205 : Using the lines removed from the cluster, a second regression equation is obtained for the length of the lines in the cluster and the actual optical attenuation values ​​of the lines in the cluster over the entire distance.

[0069] Step 206: Obtain a third regression equation for the actual optical attenuation value of the entire line of the cluster and the deviation value between the actual optical attenuation value of the entire line of the cluster and the virtual optical attenuation value of the entire line of the cluster calculated by the second regression equation of the cluster.

[0070] Steps 202 to 206 herein may refer to the aforementioned steps 101 to 105 and can achieve the same or similar beneficial effects. To avoid repetition, they will not be described again herein.

[0071] Step 207 : The cluster includes a plurality of optical splitters. When the actual optical attenuation value of the entire line of the cluster is equal to a preset threshold value, a first deviation value corresponding to the cluster is calculated according to the third regression equation of the cluster.

[0072] The optical splitter here can refer to any level of optical splitter in the ODN network, for example, a level one optical splitter. A level two optical splitter is a splitter connected to the user end or user side, and is typically located after the level one optical splitter. For example, if a level two optical splitter is connected to the user end or user side, then the level two optical splitter here is the level two optical splitter. The number of level two optical splitters within a cluster is not limited. This step involves substituting the full-path actual optical attenuation value of the cluster's lines, which is equal to a preset threshold value, into the third regression equation for the cluster. This calculation yields the deviation between the full-path actual optical attenuation value of the cluster's lines and the full-path virtual optical attenuation value of the cluster's lines calculated by the second regression equation for the cluster. This deviation is referred to as the first deviation value here, which generally reflects the maximum tolerable deviation between the full-path actual optical attenuation value and the full-path virtual optical attenuation value corresponding to the cluster while ensuring network quality. Here, each cluster corresponds to one first deviation value.

[0073] The preset threshold value here is set according to actual needs, and can be set specifically according to the network quality requirements of the cluster, etc. There is no limitation on the actual size of the preset threshold value. For example, the preset threshold value can be set to 29DB.

[0074] Step 208: Determine the relative position of the optical attenuation interval within the cluster and the optical splitter based on the first deviation value.

[0075] In a cluster, there are usually many shared line segments before the optical splitter. For example, if the optical splitter is a final optical splitter, there are many shared line segments before the final optical splitter, and the line segments from the final optical splitter to the user end are usually independent line segments. Therefore, the present application uses the intersection of the shared line segments in a cluster as the boundary to accurately determine whether the optical attenuation interval in the cluster is in that shared line segment or in those independent line segments. In the case where the optical attenuation interval in the cluster is located in the shared line segment, repeated positioning can also be reduced. At the same time, the first deviation value roughly reflects the maximum deviation value that can be tolerated between the actual optical attenuation value of the entire cluster and the virtual optical attenuation value of the entire cluster under the premise of ensuring network quality. The relative position of the optical attenuation interval and the optical splitter in the cluster thus located is more accurate.

[0076] For example, if the optical splitter is a final optical splitter, there are many shared line segments before the final optical splitter, and the line segments from the final optical splitter to the user end are usually independent line segments. In this case, the boundary between the shared line segments and the independent line segments is used as the dividing line, so that it can be accurately determined whether the optical attenuation interval within the cluster is a shared line segment or an independent line segment, that is, whether the optical attenuation interval within the cluster is located before or after the final optical splitter.

[0077] Optionally, before step 208, the method may further include: calculating, for each line in the cluster, a second deviation value corresponding to the line using the third regression equation for the cluster. Step 208 may include: step 2081, determining the relative position of the optical attenuation interval within the cluster and the optical splitter based on the ratio of the number of lines in the cluster that contain one optical splitter and whose second deviation value is greater than or equal to the first deviation value to the total number of all lines that contain the optical splitter.

[0078] Specifically, the step of determining the second deviation value involves, for each line in the cluster, substituting the actual optical attenuation value of the line into the third regression equation of the cluster to which the line belongs, and calculating the deviation between the actual optical attenuation value of the line and the virtual optical attenuation value of the lines in the cluster calculated by the second regression equation for the cluster. This deviation value is the second deviation value corresponding to the line. Here, one second deviation value corresponds to each line.

[0079] The step of determining the second deviation value may be performed by calculating the second deviation value corresponding to each line in each cluster of the ODN network using this method. Alternatively, the step of calculating the second deviation value corresponding to each line in some clusters of the ODN network using this method may be performed, and this is not specifically limited.

[0080] A line from an optical splitter to a connected user end is considered a line that includes that optical splitter. The total number of lines for an optical splitter before the final optical splitter is typically determined in conjunction with the subsequent optical splitter and its connections to the user ends. If the optical splitter is a final optical splitter, the number of lines including that final optical splitter is the same as the number of user ends connected to that final optical splitter. In other words, the number of lines including that final optical splitter is equal to the number of user ends connected to it.

[0081] For each optical splitter within a cluster, the number of lines containing the splitter whose second deviation value is greater than the first deviation value corresponding to the cluster is first counted. This number is then divided by the total number of lines containing the splitter to obtain the ratio of the number of lines containing the splitter within the cluster whose second deviation value is greater than or equal to the first deviation value corresponding to the cluster to the total number of lines containing the splitter. The first deviation value of a cluster is calculated based on the aforementioned third regression equation, which has a high accuracy rate. The full-path actual optical attenuation value of the lines in the cluster is equal to a preset threshold value, which is set based on the network quality of the cluster. The resulting full-path actual optical attenuation value of the cluster and the deviation between the full-path actual optical attenuation value of the lines in the cluster and the full-path virtual optical attenuation value of the lines in the cluster can roughly reflect the maximum deviation value of the lines in the cluster. The line in the cluster that contains a splitter and whose second deviation value is greater than the first deviation value is the abnormal line in the cluster that contains the splitter. Based on the ratio of the abnormal lines in the cluster that contain the splitter to the total number of all lines that contain the splitter in the cluster, it can be accurately determined whether the optical attenuation interval in the cluster is located before or after the splitter.

[0082] Optionally, step 2081 may include: when the ratio is greater than or equal to a preset ratio, determining the section of the road before and the optical splitter in the cluster as the optical attenuation interval within the cluster; when the ratio is less than the preset ratio, determining the section of the road after the optical splitter in the cluster as the optical attenuation interval within the cluster.

[0083] Specifically, a cluster contains a splitter, and the lines whose second deviation value is greater than or equal to the first deviation value corresponding to the cluster are usually abnormal lines in the cluster. The number of such abnormal lines is large, indicating that the section after the splitter is no longer the main location of optical attenuation. It is possible that the optical attenuation fault of the splitter and its preceding sections is the main cause of these line failures. Therefore, the optical attenuation interval of the cluster is the section before the splitter in the cluster. A cluster contains a splitter, and the lines whose second deviation value is greater than or equal to the first deviation value corresponding to the cluster are usually abnormal lines in the cluster. The number of such abnormal lines is small, indicating that the fault of the splitter and its preceding sections is relatively small. Some sections after the splitter are the main locations of optical attenuation. Therefore, the optical attenuation interval of the cluster is the section after the splitter in the cluster. Since the second deviation value is strongly correlated with the optical attenuation anomaly, the determined optical attenuation interval is more accurate.

[0084] The preset ratio here is set according to actual needs. For example, the preset ratio can be set to 1. That is, when the ratio is 1, if the cluster contains one optical splitter and the number of lines with a second deviation value greater than or equal to the first deviation value corresponding to the cluster is equal to the total number of all lines containing the optical splitter, the optical attenuation interval in the cluster is located as the section before and including the optical splitter in the cluster. Alternatively, if the cluster contains one optical splitter and the number of lines with a second deviation value greater than or equal to the first deviation value corresponding to the cluster is less than the total number of all lines containing the optical splitter, the optical attenuation interval in the cluster is located as the section after the optical splitter in the cluster.

[0085] In summary, the present application can accurately locate the position of the light attenuation interval through the aforementioned multiple regression equations without the need for a large number of on-site measurements, thereby improving the efficiency of locating the light attenuation interval and reducing costs; at the same time, since the third regression equation is used to determine the light attenuation interval within the cluster, the third regression equation has a stronger correlation with the light attenuation offset, and therefore, the determined light attenuation interval within the cluster is more accurate, and the position of the light attenuation interval is clearer.

[0086] Reference Figure 4 , the present application is further explained below in conjunction with specific embodiments.

[0087] 1. Find the line parameters that are correlated with optical attenuation, refer to Figure 2 , it is concluded that the length of the line to be predicted is linearly correlated with the actual optical attenuation value of the entire line, and the linear relationship is positively correlated.

[0088] 2. Divide the multiple lines of the ODN network into several clusters based on the source of the optical signals used by the lines.

[0089] 3. Obtain a second correlation coefficient between the length of a cluster of lines and the entire actual optical attenuation value of the cluster of lines.

[0090] 4. Obtain the first regression equation.

[0091] 5. Determine the preset correlation coefficient.

[0092] 6. Determine the offset between the actual optical attenuation value of a line and the virtual optical attenuation value of the line calculated by the first regression equation of the cluster to which the line belongs.

[0093] 7. Eliminate the lines so that a first correlation coefficient between the length of the lines in the cluster after elimination and the actual optical attenuation value of the entire line of the cluster is greater than or equal to a preset correlation coefficient.

[0094] 8. Obtain the second regression equation.

[0095] 9. Obtain the third regression equation.

[0096] 10. Light attenuation positioning.

[0097] For example, consider a cluster of 511 lines serving 511 broadband users under an OLT module in an ODN network. The second correlation coefficient for this cluster is 0.32. The linear proportionality coefficient in the first regression equation for this cluster is 0.1835, and the constant in the first regression equation is 23.7266.

[0098] For each of the 511 lines, determine the offset value. Specifically, use the following formula to calculate the offset value for each line: Offset value = (Yi - (0.1835Xi + 23.7266)) 2 , where Yi is the actual optical attenuation value of the entire line numbered i, Xi is the length of the line numbered i, and the value of i ranges from 1 to 511.

[0099] Then, for the 511 lines, 184 users or lines are eliminated in descending order of offset values, leaving 327 users or 327 lines.

[0100] The correlation coefficients for the remaining 327 lines are calculated to be 0.80. Therefore, the first correlation coefficient between the lengths of the lines of the cluster consisting of the remaining 327 users or lines and the actual optical attenuation values ​​of the entire line of the cluster is 0.8.

[0101] The remaining 327 lines were used to calculate the second regression equation for this cluster, and the linear proportional coefficient in the second regression equation was 0.17736, and the constant was 23.8269. At this point, a strong positive correlation regression equation was obtained.

[0102] A regression equation is calculated for the original 511 lines under the OLT module to calculate the full-length optical attenuation (Yi) and the deviation value of the line, namely ((Yi-(0.17736Xi+23.8269)) 2 The third correlation coefficient is 0.96, and the full-length optical attenuation (Yi) and deviation value of the line are calculated, namely ((Yi-(0.17736Xi+23.8269)) 2 The linear proportionality coefficient in the third regression equation is 0.9305 and the constant is -23.8097. In this case, the positive correlation coefficient is even greater.

[0103] According to the current light attenuation control goal, the preset threshold value is 28DB, and the first deviation value corresponding to the cluster is calculated to be 3.1.

[0104] The optical splitter in this ODN network can be a secondary splitter or a primary splitter. If the second deviation values ​​for the five lines or users containing a secondary splitter HPX.XCTC / GF012 / GFH005 / P1 are 0.81, 8.35, 8.42, 0.36, and 0.46, respectively, the optical attenuation of the line sections after the secondary splitter corresponding to lines 8.35 and 8.42 is determined to be high, representing an optical attenuation interval. If the second deviation values ​​for the three lines or users corresponding to another secondary splitter HPX.XCXW / GF006 / GFH011 / P1 all exceed 3.1, the optical attenuation of the secondary splitter and its immediate vicinity, that is, from the secondary splitter to the distribution cable side, is determined to be high, representing an optical attenuation interval. Furthermore, if the four secondary splitters connected to the primary splitter are all determined to have high optical attenuation, the optical attenuation of the primary splitter and its trunk optical cable is determined to be high, representing an optical attenuation interval. HPX.XCTC is the number of an optical cross-connect box, GF012 is the number of a primary splitter box, GFH005 is the number of a secondary splitter box, and P1 is a secondary splitter within the secondary splitter box. HPX.XCXW is the number of another optical cross-connect box, GF006 is the number of another primary splitter box, GFH011 is the number of another secondary splitter box, and P1 is a secondary splitter within that secondary splitter box.

[0105] Reference Figure 5 , Figure 5 This is a structural diagram of an optical attenuation interval positioning device for an ODN network provided by an embodiment of the present invention. The device may include:

[0106] A first regression equation obtaining module 301 is configured to obtain a first regression equation between the length of a line in a cluster of an ODN network and the actual optical attenuation value of the lines in the cluster over the entire distance; the ODN network includes a plurality of clusters, each of which includes a plurality of lines;

[0107] An offset value determining module 302 is configured to determine an offset value between an actual optical attenuation value of a line over the entire distance and a virtual optical attenuation value of the line over the entire distance calculated by the first regression equation of the cluster to which the line belongs;

[0108] The elimination module 303 is configured to eliminate some of the lines from all the lines in a cluster in descending order of the offset values, so that a first correlation coefficient between the length of the lines in the cluster after elimination and the actual optical attenuation value of the lines in the cluster is greater than or equal to a preset correlation coefficient;

[0109] A second regression equation obtaining module 304 is configured to obtain a second regression equation of the length of the lines in the cluster and the actual optical attenuation value of the lines in the cluster using the lines removed from the cluster;

[0110] A third regression equation obtaining module 305 is configured to obtain a third regression equation for obtaining the actual optical attenuation value of the entire line of the cluster and the deviation value between the actual optical attenuation value of the entire line of the cluster and the virtual optical attenuation value of the entire line of the cluster calculated by the second regression equation of the cluster;

[0111] The light attenuation positioning module 306 is configured to locate the light attenuation interval within the cluster based on the third regression equation of the cluster.

[0112] Optionally, the cluster includes a plurality of optical splitters; the optical attenuation positioning module 306 includes:

[0113] A first deviation value calculation submodule is configured to calculate, when the entire actual optical attenuation value of the lines of the cluster is equal to a preset threshold value, a first deviation value corresponding to the cluster according to the third regression equation of the cluster;

[0114] The optical attenuation positioning submodule is configured to determine a relative position between the optical attenuation interval within the cluster and the optical splitter based on the first deviation value.

[0115] Optionally, the device further includes:

[0116] A second deviation value calculation submodule is configured to calculate, for each line in the cluster, a second deviation value corresponding to the line using the third regression equation of the cluster;

[0117] The optical attenuation locating submodule includes:

[0118] an optical attenuation positioning unit, configured to determine a relative position of the optical attenuation interval within the cluster and the optical splitter based on a ratio of the number of lines within the cluster that contain one optical splitter and whose second deviation value is greater than or equal to the first deviation value to the total number of all lines that contain the optical splitter.

[0119] Optionally, the light attenuation positioning unit includes:

[0120] a first optical attenuation positioning unit, configured to determine the optical splitter in the cluster and the section before it as an optical attenuation interval in the cluster when the ratio is greater than or equal to a preset ratio;

[0121] The second optical attenuation positioning unit is configured to determine, when the ratio is less than the preset ratio, a road section after the optical splitter in the cluster as an optical attenuation interval in the cluster.

[0122] Optionally, the device further includes:

[0123] A second correlation coefficient acquisition module is used to obtain a second correlation coefficient between the length of a cluster of lines and the entire actual optical attenuation value of the lines of the cluster;

[0124] The preset correlation coefficient setting module is used to set the preset correlation coefficient corresponding to the cluster according to the second correlation coefficient corresponding to the cluster; for the same cluster, the preset correlation coefficient is greater than the second correlation coefficient.

[0125] Optionally, the device further includes:

[0126] The clustering module is configured to divide the multiple lines of the ODN network into a plurality of clusters according to the similarity of the optical attenuation environments in which the lines are located; or to divide the multiple lines of the ODN network into a plurality of clusters according to the sources of the optical signals used by the lines.

[0127] Reference Figure 6 , the present invention also provides a structural diagram of an electronic device, such as Figure 6 As shown, it includes: a processor 1101, a memory 1102, and a computer program 11021 stored in the memory and capable of running on the processor, and when the processor executes the program, the optical attenuation interval positioning method of the ODN network of the above embodiment is implemented.

[0128] The present invention also provides a readable storage medium. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the optical attenuation interval positioning method of the ODN network of the aforementioned embodiment.

[0129] The present invention also provides a computer program product, comprising instructions, which, when executed by a processor in an electronic device, enable the electronic device to perform the steps of any of the aforementioned embodiments of the method for locating optical attenuation intervals in an ODN network.

[0130] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0131] It should be noted that the various information and data obtained in the embodiments of the present invention are all obtained with the authorization of the information / data holder.

[0132] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general-purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing this type of system. In addition, the present invention is not directed to any specific programming language. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the above description of specific languages ​​is for the purpose of disclosing the best mode of the present invention.

[0133] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0134] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Accordingly, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the present invention.

[0135] Those skilled in the art will appreciate that the modules in the devices of the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and further may be divided into a plurality of submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device so disclosed may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0136] The various component embodiments of the present invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or digital signal processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components of the sorting device according to the present invention. The present invention may also be implemented as an apparatus or device program for performing a portion or all of the methods described herein. Such a program for implementing the present invention may be stored on a computer-readable medium, or may be in the form of one or more signals. Such a signal may be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0137] It should be noted that the above embodiments illustrate rather than limit the invention, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

[0138] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0139] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0140] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for locating optical attenuation intervals in an ODN network, characterized in that: The method comprises: Obtaining a first regression equation between the length of a line in a cluster of an ODN network and the actual optical attenuation value of the entire line of the cluster; the ODN network includes a plurality of clusters, and the cluster includes a plurality of lines; Determine an offset value between an actual optical attenuation value of the entire line and a virtual optical attenuation value of the entire line calculated by the first regression equation of the cluster where the line belongs; Eliminate some of the lines from all the lines in a cluster in descending order of the offset values, so that a first correlation coefficient between the length of the lines in the cluster after the elimination and the actual optical attenuation value of the lines in the cluster over the entire distance is greater than or equal to a preset correlation coefficient; Using the lines removed from the cluster to obtain a second regression equation of the length of the lines in the cluster and the actual optical attenuation values ​​of the lines in the cluster over the entire process; obtaining a third regression equation for the entire actual optical attenuation value of the lines of the cluster and a deviation value between the entire actual optical attenuation value of the lines of the cluster and the entire virtual optical attenuation value of the lines of the cluster calculated by the second regression equation of the cluster; Based on the third regression equation of the cluster, the light attenuation interval within the cluster is located.

2. The method according to claim 1, characterized in that The cluster includes a plurality of optical splitters; and locating the optical attenuation interval within the cluster based on the third regression equation of the cluster includes: When the actual optical attenuation value of the entire line of the cluster is equal to the preset threshold value, calculating the first deviation value corresponding to the cluster according to the third regression equation of the cluster; Based on the first deviation value, a relative position of the optical attenuation interval within the cluster and the optical splitter is determined.

3. The method according to claim 2, characterized in that Before determining the relative position of the optical attenuation interval within the cluster and the optical splitter based on the first deviation value, the method further includes: For each route in the cluster, calculating a second deviation value corresponding to the route using the third regression equation of the cluster; The determining, based on the first deviation value, a relative position of the optical attenuation interval within the cluster and the optical splitter includes: The relative position of the optical attenuation interval and the optical splitter in the cluster is determined according to the ratio of the number of lines in the cluster that include one optical splitter and whose second deviation value is greater than or equal to the first deviation value to the total number of all lines that include the optical splitter.

4. The method according to claim 3, characterized in that Determining the relative position of the optical attenuation interval in the cluster and the optical splitter according to the ratio of the number of lines in the cluster that include one optical splitter and whose second deviation value is greater than or equal to the first deviation value to the total number of all lines that include the optical splitter includes: When the ratio is greater than or equal to a preset ratio, determining the optical splitter and the section before it in the cluster as the optical attenuation interval in the cluster; When the ratio is smaller than the preset ratio, the section after the optical splitter in the cluster is determined as the optical attenuation interval in the cluster.

5. The method according to claim 1, wherein The method further comprises: Obtaining a second correlation coefficient between the length of a cluster of lines and the entire actual optical attenuation value of the lines of the cluster; The preset correlation coefficient corresponding to the cluster is set according to the second correlation coefficient corresponding to the cluster; for the same cluster, the preset correlation coefficient is greater than the second correlation coefficient.

6. The method according to claim 1, characterized in that Before obtaining the first regression equation, the method further includes: Dividing the multiple lines of the ODN network into a plurality of clusters according to the similarity of the optical attenuation environments in which the lines are located; or, The multiple lines of the ODN network are divided into a number of clusters according to sources of optical signals used by the lines.

7. An optical attenuation interval positioning device for an ODN network, characterized in that: The device comprises: A first regression equation obtaining module is configured to obtain a first regression equation of the length of a line in a cluster of an ODN network and the actual optical attenuation value of the entire line of the cluster; the ODN network includes a plurality of clusters, and the cluster includes a plurality of lines; an offset value determining module, configured to determine an offset value between an actual optical attenuation value of the entire line and a virtual optical attenuation value of the entire line calculated by the first regression equation of the cluster to which the line belongs; a removal module, configured to remove some of the lines from all the lines in a cluster in descending order of the offset values, so that a first correlation coefficient between the length of the lines in the cluster after removal and the actual optical attenuation value of the lines in the cluster over the entire distance is greater than or equal to a preset correlation coefficient; A second regression equation obtaining module, configured to obtain a second regression equation of the length of the lines in the cluster and the actual optical attenuation value of the lines in the cluster using the lines removed from the cluster; a third regression equation obtaining module, configured to obtain a third regression equation for obtaining the actual optical attenuation value of the entire line of the cluster and a deviation value between the actual optical attenuation value of the entire line of the cluster and the virtual optical attenuation value of the entire line of the cluster calculated by the second regression equation of the cluster; The light attenuation positioning module is configured to locate the light attenuation interval within the cluster based on the third regression equation of the cluster.

8. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the program.

9. A readable storage medium, characterized in that: When the instructions in the readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises instructions, which, when executed by a processor in an electronic device, enable the electronic device to execute the method according to any one of claims 1 to 6.

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