Optical attenuation interval positioning method and device of ODN (Optical Distribution Network) and electronic equipment

Abstract

The embodiment of the invention provides an optical attenuation interval positioning method and device of an ODN network and electronic equipment, and relates to the technical field of communication, and the method comprises the steps: obtaining a first regression equation of the length of a line of a cluster of the ODN network and the whole-course actual optical attenuation value of the line of the cluster; determining a whole-course actual light decay value of one line, a whole-course virtual light decay value of the line calculated by the first regression equation of the cluster where the line is located, and a deviation value between the whole-course actual light decay value and the whole-course virtual light decay value; removing a part of lines from all lines of one cluster; obtaining a second regression equation of the length of the line of the cluster and the whole-course actual light attenuation value of the line of the cluster by adopting the line with the line removed from the cluster; acquiring a whole-course actual light attenuation value of the line of the cluster and a third regression equation of a deviation value between the whole-course actual light attenuation value of the line of the cluster and a whole-course virtual light attenuation value of the line of the cluster calculated by the second regression equation of the cluster; and on the basis of the third regression equation of the cluster, the light attenuation interval in the cluster is positioned, so that the light attenuation 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, a device, an electronic device and a readable storage medium for locating an optical attenuation interval of an ODN network. Background Art

[0002] Optical Distribution Network (ODN) is an optical cable network that sends and receives signals through optical transceivers and PON (Passive Optical Network) devices, and transmits 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. The optical attenuation interval is determined and repaired to improve the service quality. Therefore, optical attenuation interval positioning has become an important part of improving the quality of the optical network.

[0004] The traditional method of locating optical attenuation mainly uses on-site measurements with instruments such as OTDR (Optical Time Domain Reflectometer) to determine the optical attenuation interval by comparing the target value. However, the workload of on-site measurements is very large, resulting in low efficiency in locating the optical attenuation interval. Summary of the invention

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

[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 of 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 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 where the line is located;

[0009] From all the lines of 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 of the cluster after the removal and the actual optical attenuation value of the entire path of the lines of the cluster is greater than or equal to a preset correlation coefficient;

[0010] Using the removed lines in the cluster 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 throughout the entire process;

[0011] A third regression equation is used to obtain 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;

[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 acquisition module is used to acquire a first regression equation of the length of a line of a cluster of the 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 determination module, used for determining 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 is located;

[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 throughout the entire process is greater than or equal to a preset correlation coefficient;

[0017] A second regression equation acquisition module, used to acquire a second regression equation of the length of the lines of the cluster and the actual optical attenuation value of the entire process of the lines of the cluster by using the lines removed from the cluster;

[0018] A third regression equation acquisition module, used to acquire a third regression equation of the full-range actual optical attenuation value of the lines of the cluster and a deviation value between the full-range actual optical attenuation value of the lines of the cluster and the full-range virtual optical attenuation value of the lines of the cluster calculated by the second regression equation of the cluster;

[0019] The light attenuation positioning module is used to locate the light attenuation interval in 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 the processor implements the optical attenuation interval positioning method of the above-mentioned ODN network when executing the program.

[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, enable the electronic device to execute the above-mentioned optical attenuation interval positioning method of the ODN network.

[0023] In an embodiment of the present invention, the lines with large optical attenuation offset values ​​are eliminated through the preliminary calculation of the first regression equation, and a second regression equation with strong correlation to the cluster is further calculated based on a cluster of eliminated lines, and a third regression equation of the deviation value between the actual optical attenuation value of the lines in the cluster and the virtual optical attenuation value of the lines in the cluster calculated by the second regression equation is further obtained. The deviation value here can accurately determine the optical attenuation offset, and the third regression equation has a stronger correlation. The optical attenuation interval in the cluster is determined by the third regression equation. On the one hand, the optical attenuation interval positioning of the present application is mainly carried out through data calculation, without the need for a large number of on-site measurements, so the optical attenuation interval positioning efficiency can be improved and the cost can be reduced; on the other hand, since the third regression equation used to determine the optical attenuation interval in the cluster has a stronger correlation with the optical attenuation offset, the optical attenuation interval determined in 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 briefly introduces 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 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 of actual optical attenuation values ​​of lines and line lengths in an ODN network provided by an embodiment of the present invention;

[0027] Figure 3 It is a flowchart of the steps of another optical attenuation interval positioning method of an ODN network provided by an embodiment of the present invention;

[0028] Figure 4 It 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 It is a structural diagram of an optical attenuation interval positioning device of an ODN network provided by an embodiment of the present invention;

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

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Reference Figure 1 , Figure 1 1 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. Figure 1 As shown, the method may include:

[0033] Step 101, obtaining a first regression equation of the length of a line of 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] The 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 through a line, the output port of each optical cross-connect box is connected to multiple primary optical splitters through a line, each primary optical splitter box is connected to multiple secondary optical splitters through a line, and each secondary optical splitter box is connected to multiple user sides through a line. A whole line from the ODN to the user side can be used as a full line, and the multiple sections 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 primary optical splitter, the line segment between the primary optical splitter and the secondary optical splitter, and the line segment from the secondary optical splitter to the user side. The paths between the secondary optical splitters of multiple full lines may have a common line segment. The line here may be a full line or may be multiple full lines, or may be 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, and the line segment connected to the user end or the user side may be the tail of the line.

[0035] The ODN network includes several clusters. It should be noted that the several mentioned in this application refers to one or more. A cluster here contains several lines. There is no limitation on how many clusters the ODN network includes and how many lines a cluster contains. The length of the line refers to the length of the line from the beginning to the end. The actual optical attenuation value of the entire 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 entire line. For example, if the line is a full line, that is, a line from the OLT device to a user side, then the length of the line is the total length of the line from the OLT device to a user side, and the actual optical attenuation value of the entire line is the deviation between the light value of the OLT device and the light value received by the user side of the line.

[0036] The present application can use the least square method to obtain the first regression equation of the length of a line in a cluster of the ODN network and the actual optical attenuation value of the line in the cluster. Specifically, set the line number in a cluster to i, i = (1, 2...n), and the length of a line in the cluster to X i The actual optical attenuation value of the line in the cluster is Y i , then the process of determining the first regression equation of the actual optical attenuation value of the entire line of the cluster can be as follows. Calculate the average value of the length of the line in the cluster respectively And the average value of the actual optical attenuation of the entire line in the cluster in, The first regression equation of the length of the line of the cluster and the actual optical attenuation value of the entire line of the cluster is: Here b is a constant.

[0037] In the present application, other methods for obtaining the first regression equation of the length of a cluster of lines and the actual optical attenuation value of the entire length of the cluster of lines are not limited. Here, one cluster corresponds to one first regression equation, and each cluster corresponds to one first regression equation as many as the number of clusters in the ODN network. For example, if there are 3 clusters in the ODN network, each cluster corresponds to one first regression equation, and 3 first regression equations are obtained.

[0038] Optionally, before the aforementioned step 101, the method may further include: finding line parameters that are correlated with optical attenuation. Specifically, the line length of optical signal transmission, optical signal attenuation value and other parameters may be collected through big data collection results of optical module sources, optical modem probes, etc., and then a scatter plot may be drawn, and a typical illustration method may be used to compare the parameters. Figure 2 As shown, it can be found that the length of the line to be predicted is linearly correlated with the actual optical attenuation value of the entire line, and it is a positively correlated linear relationship. Figure 2 In the figure, the horizontal axis is the length of the line to be predicted, and the vertical axis is the actual optical attenuation value of the entire line.

[0039] Step 102: determine an offset value between an actual optical attenuation value of the 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 where the line is located.

[0040] This step is to calculate the offset value for each line in the cluster. In the case that the ODN network has multiple clusters, here the offset value is calculated for each line in each cluster. For all lines in a cluster, the aforementioned first regression equation of the cluster is used. For example, a cluster contains 50 lines, and the three clusters of the ODN network have a total of 150 lines. Here, the offset value is calculated for each of the 150 lines, and the first regression equation of the cluster is used for all 50 lines in a cluster. For a line in a cluster, the offset value between the actual optical attenuation value of the line and the virtual optical attenuation value of the line calculated by the first regression equation of the cluster where the line is located is

[0041] Step 103, 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 removal and the actual optical attenuation value of the lines in the cluster is greater than or equal to a preset correlation coefficient.

[0042] In a cluster of lines, those with too large offset values ​​can be considered as abnormal lines. Therefore, from all the lines in the cluster, the lines with larger offset values ​​are removed. After the removal, the number of lines in the cluster will be reduced, and the 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 after the removal is greater than or equal to the preset correlation coefficient.

[0043] Assuming that the number of lines in the cluster after elimination is N, the first correlation coefficient r between the length of the lines in the cluster after elimination and the actual optical attenuation value of the lines in the cluster can be determined in the following way, where X i . Among them, L XX is the sum of squares of the lengths of the lines in the cluster after removal, L YY is the square sum of the actual optical attenuation values ​​of the entire line of the cluster after elimination, L XY is the covariance of 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. i It refers to the length of the line numbered i in the cluster after removing some lines. Here, Y i Refers to the actual optical attenuation value of the entire line numbered i in the cluster after removing some lines.

[0044] Generally, for an ODN network, a correlation coefficient less than 0.4 is considered to be weakly correlated, and a correlation coefficient greater than or equal to 0.8 is considered to be strongly correlated. 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 of the length of the line of the cluster after elimination and the actual optical attenuation value of the entire line of the cluster after elimination is greater than or equal to 0.8, indicating that the correlation is very strong. For example, the first correlation coefficient of the length of the line of the cluster after elimination and the actual optical attenuation value of the entire line of the cluster after elimination 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 eliminated lines in each cluster can be equal or unequal, and the first correlation coefficients of the clusters after elimination can be equal, or unequal, or partially equal, and 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 length of the lines of the cluster is usually smaller than the first correlation coefficient between the length of the lines of the cluster and the actual optical attenuation value of the entire length of the lines of the cluster after elimination, 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 value of the entire length of the lines of the cluster; S2, setting 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. Here, S1 is to use the length of each original line in the cluster before removing the line and the actual optical attenuation value of the entire length of the original line in the cluster to obtain the second correlation coefficient corresponding to the cluster. Here, one cluster corresponds to one second correlation coefficient, and the method for obtaining the second correlation coefficient here is similar to the method for obtaining the aforementioned first correlation coefficient, so it will not be repeated here to avoid repetition. Usually, before removing the line, the second correlation coefficient corresponding to the cluster is approximately 0.15 to 0.4, and the correlation is weak. In the process of setting the aforementioned preset correlation coefficient corresponding to a cluster, it is necessary to ensure that for the same cluster, the preset correlation coefficient needs to be greater than the second correlation coefficient, so that such removal is conducive to improving the correlation and further improving the accuracy of subsequent optical attenuation interval positioning.

[0049] Step 104 : using the eliminated lines in the cluster, 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 throughout the entire process.

[0050] After removing irrelevant lines from a cluster, the remaining more relevant lines are used 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. Since irrelevant lines in the cluster are removed, the second regression equation is more accurate.

[0051] The process of obtaining the second regression equation here can be similar to the method of obtaining the first regression equation mentioned above, and 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, a second regression equation obtained for one cluster can be Here Characterizes the actual optical attenuation value of the entire line after the line is removed from the cluster, Characterizes the length of the lines after being removed from the cluster.

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

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

[0054]

[0055] The method of obtaining the third regression equation is similar to the method of obtaining the first regression equation, and will not be described here to avoid repetition. Here, one cluster corresponds to one third regression equation, and 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 deviation value between the actual optical attenuation value of the entire line of the cluster and 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, that is, calculate Y i with ΔY i', the third correlation coefficient is significantly higher than the second correlation coefficient between the length of the line of the cluster and the actual optical attenuation value of the line of the cluster before the line is removed, and the third correlation coefficient is also significantly higher than the first correlation coefficient between the length of the line of the cluster and the actual optical attenuation value of the line of the cluster after the line is removed. It should be noted that for the same cluster, the second correlation coefficient is usually smaller than the first correlation coefficient, and the first correlation coefficient is usually smaller than the third correlation coefficient, indicating that the actual optical attenuation value of the line of the cluster and the deviation value between the actual optical attenuation value of the line of the cluster and the virtual optical attenuation value of the line of the cluster calculated by the second regression equation of the cluster are more correlated, so that the optical attenuation interval can be located more accurately.

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

[0058] A third regression equation is used to calculate 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. 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 the embodiment of the present invention, the lines with large optical attenuation offset values ​​are eliminated through the preliminary calculated first regression equation, and the second regression equation with strong correlation to the cluster is further calculated based on the eliminated lines of a cluster, and the third regression equation of the deviation value between the actual optical attenuation value of the lines of the cluster and the virtual optical attenuation value of the lines of the cluster calculated by the second regression equation is further obtained. 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 carried out through data calculation, without the need for a large number of on-site measurements, so the positioning efficiency of the optical attenuation interval can be improved, and the cost can be reduced; 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 FIG. 1 is a flowchart of another method for locating an 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 in which the lines are located; 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] According to the similarity of the optical attenuation environment of the lines, clustering can make the optical attenuation of each line in the cluster roughly similar. Usually, the construction time and usage of each line that shares the optical signal source are relatively similar. Therefore, according to the source of the optical signal used by the line, the optical attenuation causes of each line in the cluster are relatively similar. The above two clustering methods can improve the accuracy of subsequent optical attenuation interval positioning because the factors related to optical attenuation of each line in the cluster are relatively similar.

[0063] For example, multiple lines of the ODN network can be clustered by sharing a common optical module source, rack, or machine room.

[0064] It should be noted that the multiple lines of the ODN network here may refer to all the lines of the ODN network or to some of the lines of the ODN network, and there is no specific limitation on this. In addition, in addition to the above two clustering methods, the multiple lines of the ODN network may also be clustered according to the optical attenuation characteristics of the lines in different areas, and the specific clustering method is not limited.

[0065] Step 202, obtaining a first regression equation of the length of a line of 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 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 where the line is located.

[0067] Step 204: 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 is greater than or equal to a preset correlation coefficient.

[0068] Step 205 : using the eliminated lines in the cluster, obtaining 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 throughout the entire process.

[0069] Step 206, obtaining the global actual optical attenuation value of the lines of the cluster and a third regression equation of the deviation value between the global actual optical attenuation value of the lines of the cluster and the global virtual optical attenuation value of the lines of the cluster calculated by the second regression equation of the cluster.

[0070] Steps 202 to 206 here can refer to the aforementioned steps 101 to 105, and can achieve the same or similar beneficial effects. In order to avoid repetition, they are not described again here.

[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 the 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, it can be a level one optical splitter, a final optical splitter, and the final optical splitter refers to the optical splitter connected to the user end or the user side. Usually, the final optical splitter is located behind the level one optical splitter. For example, if the level two optical splitter is connected to the user end or the user side, then the level two optical splitter here is the final optical splitter. The number of final optical splitters in a cluster is not limited. This step is to bring the full-length actual optical attenuation value of the line of the cluster equal to the preset threshold value into the third regression equation of the cluster for the aforementioned third regression equation of the cluster, thereby calculating the deviation value between the full-length actual optical attenuation value of the line of the cluster and the full-length virtual optical attenuation value of the line of the cluster calculated by the aforementioned second regression equation of the cluster. The deviation value is the first deviation value here, and the first deviation value roughly reflects the maximum deviation value that can be tolerated between the full-length actual optical attenuation value and the full-length virtual optical attenuation value corresponding to the cluster under the premise of ensuring network quality. Here, one cluster corresponds to one first deviation value.

[0073] The preset threshold value here is set according to actual needs, and can be set according to the network quality requirements of the cluster, etc., and 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 light attenuation interval in 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 splitter. For example, if the splitter is a final-stage splitter, there are many shared line segments before the final-stage splitter, and the line segments from the final-stage 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. When 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 process and the virtual optical attenuation value of the entire process corresponding to the cluster under the premise of ensuring network quality, so that the relative position of the optical attenuation interval in the cluster and the splitter is more accurate.

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

[0077] Optionally, before step 208, the method may further include: for each line in the cluster, calculating the second deviation value corresponding to the line by the third regression equation of the cluster. Step 208 may include: step 2081, 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 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 is to, for each line in the cluster, bring the full-distance actual optical attenuation value of the line into the third regression equation of the cluster where the line is located, and calculate the deviation value between the full-distance actual optical attenuation value of the line and the full-distance virtual optical attenuation value of the line of the cluster calculated by the aforementioned second regression equation of the cluster, and the deviation value is the second deviation value corresponding to the line here. Here, one line corresponds to one second deviation value.

[0079] The step of determining the second deviation value may be performed by calculating a second deviation value corresponding to each line of each cluster in the ODN network in this manner. It may also be performed by calculating a second deviation value corresponding to each line of some clusters in the ODN network in this manner, and there is no specific limitation on this.

[0080] A line from a splitter to a user end connected to it is a line that includes the splitter. The total number of lines of the splitter before the final splitter usually needs to be determined in combination with the subsequent splitter and its connection with the user end. In the case where the splitter is a final splitter, the number of all lines including the final splitter is the number of user ends connected to the final splitter, that is, the number of all lines including the final splitter is equal to the number of user ends connected to the final splitter.

[0081] For a splitter in a cluster, the number of lines containing the splitter and whose second deviation value is greater than the first deviation value corresponding to the cluster is first counted, and then the ratio obtained by dividing the number by the total number of all lines containing the splitter is the ratio of the number of lines containing the splitter in the cluster and whose second deviation value is greater than or equal to the first deviation value corresponding to the cluster to the total number of all 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-range actual optical attenuation value of the lines of the cluster is equal to the preset threshold value and is substituted into the third regression equation. The preset threshold value is set according to the network quality of the cluster, etc. The full-range actual optical attenuation value of the cluster obtained thereby and the deviation value between the full-range actual optical attenuation value of the lines of the cluster and the full-range virtual optical attenuation value of the lines of the cluster can roughly reflect the maximum deviation value of the lines of 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 that contains the splitter in the cluster. According to the proportion of the abnormal lines containing the splitter in the cluster to the total number of all lines containing 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 optical splitter and before it in the cluster as the optical attenuation interval in the cluster; when the ratio is less than the preset ratio, determining the section of the optical splitter in the cluster after it as the optical attenuation interval in 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 optical attenuation location, and the optical attenuation failure of the splitter and its predecessor may be the main cause of these line failures. Therefore, the optical attenuation interval of the cluster is the section before the splitter and its predecessor 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 failure of the splitter and its predecessor is relatively small, and some sections after the splitter are the main optical attenuation locations. 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, 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 the optical splitter in the cluster. Alternatively, when 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 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, 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 it is a positively correlated linear relationship.

[0088] 2. Divide the multiple lines of the ODN network into several clusters according to the sources 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 value 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 where 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 path of the lines in 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, 511 lines corresponding to 511 broadband users under a certain OLT block in the ODN network are divided into a cluster. For this cluster, the second correlation coefficient is 0.32. For this cluster, the linear proportionality coefficient in the first regression equation is 0.1835, and the constant in the first regression equation is 23.7266.

[0098] For each of the 511 lines, the offset value is determined. Specifically, the offset value of each line is calculated using the following formula: Offset value = (Yi - (0.1835Xi + 23.7266)) 2 , where Yi is the actual optical attenuation value of the 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 of the remaining 327 lines are calculated to be 0.80, so the first correlation coefficient between the length of the line of the cluster composed of the remaining 327 users or lines and the actual optical attenuation value of the entire line of the cluster is 0.8.

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

[0102] The regression equation is calculated for the original 511 lines under the OLT section to calculate the full-length optical attenuation (Yi) and deviation value of the line, i.e. ((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, that is, ((Yi-(0.17736Xi+23.8269)) 2 The linear proportionality coefficient in the third regression equation is 0.9305 and the constant is -23.8097. At this time, the positive correlation coefficient is larger.

[0103] According to the current light attenuation control target, 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 the ODN network can be a secondary optical splitter or a primary optical splitter. The second deviation values ​​corresponding to the five lines or users including a secondary optical splitter HPX.XCTC / GF012 / GFH005 / P1 are 0.81, 8.35, 8.42, 0.36, and 0.46 respectively. It is judged that the optical attenuation of the section after the secondary optical splitter in the lines corresponding to 8.35 and 8.42 is large, that is, an optical attenuation interval. The three lines or users corresponding to another secondary optical splitter HPX.XCXW / GF006 / GFH011 / P1 are all greater than 3.1, it is judged that the secondary optical splitter and its predecessor, that is, the secondary optical splitter to the distribution cable side, has a large optical attenuation, which is an optical attenuation interval. In addition, the four secondary optical splitters under the primary optical splitter are all judged to have a large optical attenuation, so it is judged that the primary optical splitter and its trunk optical cable have a large optical attenuation, which is an optical attenuation interval. Among them, HPX.XCTC is the number of an optical cross-connection 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 in the secondary splitter box. HPX.XCXW is the number of another optical cross-connection 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 in the secondary splitter box.

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

[0106] A first regression equation acquisition module 301 is used to acquire a first regression equation of the length of a line of 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;

[0107] An offset value determination module 302 is used 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 where the line is located;

[0108] The elimination module 303 is used 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 acquisition module 304 is used to acquire 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 by using the lines removed from the cluster;

[0110] A third regression equation acquisition module 305, used to acquire the full-range actual optical attenuation value of the lines of the cluster, and a third regression equation of the deviation value between the full-range actual optical attenuation value of the lines of the cluster and the full-range virtual optical attenuation value of the lines 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, configured to calculate a first deviation value corresponding to the cluster according to the third regression equation of the cluster when the actual optical attenuation value of the entire line of the cluster is equal to a preset threshold value;

[0114] The optical attenuation positioning submodule is used to determine the relative position of the optical attenuation interval in the cluster and the optical splitter based on the first deviation value.

[0115] Optionally, the device further comprises:

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

[0117] The optical attenuation positioning submodule comprises:

[0118] The optical attenuation positioning unit is used to determine 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 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 optical attenuation positioning second unit is used to determine the section after the optical splitter in the cluster as the optical attenuation interval in the cluster when the ratio is less than the preset ratio.

[0122] Optionally, the device further comprises:

[0123] A second correlation coefficient acquisition module, used to acquire 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 comprises:

[0126] The clustering module is used to divide the multiple lines of the ODN network into several clusters according to the similarity of the optical attenuation environment in which the lines are located; or divide the multiple lines of the ODN network into several clusters according to the source of the optical signal 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 executable on the processor, and when the processor executes the program, the optical attenuation interval positioning method of the ODN network of the foregoing embodiment is implemented.

[0128] The present invention also provides a readable storage medium. When the 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 execute the steps of any of the aforementioned embodiments of the optical attenuation interval positioning method for 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 such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description of the above specific languages ​​is for disclosing the best mode of the present invention.

[0133] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can 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, the 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 the following intention: that the claimed invention requires more features than the features explicitly recited in each claim. More specifically, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present invention.

[0135] Those skilled in the art will appreciate that the modules in the devices in 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 in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, 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 should be understood 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 in the sorting device according to the present invention. The present invention may also be implemented as a device or apparatus program for executing part 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 the present invention rather than limit it, 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 symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" 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 a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. 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 can 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 protection scope of the present invention.

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

Claims

1. A method for locating an optical attenuation interval of an ODN network, characterized in that: The method comprises: Obtaining a first regression equation between the length of a line of 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 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 where the line is located; From all the lines of 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 of the cluster after the removal and the actual optical attenuation value of the entire path of the lines of the cluster is greater than or equal to a preset correlation coefficient; Using the removed lines in the cluster 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 throughout the entire process; A third regression equation is used to obtain 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; 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 the positioning of the light 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, a first deviation value corresponding to the cluster is calculated according to the third regression equation of the cluster; Based on the first deviation value, a relative position of the light attenuation interval in 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 light attenuation interval in the cluster and the optical splitter based on the first deviation value, the method further includes: For each line in the cluster, a second deviation value corresponding to the line is calculated using the third regression equation of the cluster; The determining, based on the first deviation value, a relative position of the light attenuation interval in the cluster and the optical splitter includes: The relative position of the optical attenuation interval in the cluster and the optical splitter 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 section of 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 light attenuation interval in the cluster.

5. The method according to claim 1, characterized in that 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 plurality 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 acquisition module is used to acquire a first regression equation of the length of a line of a cluster of the 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 determination module, used for determining 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 is located; 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 throughout the entire process is greater than or equal to a preset correlation coefficient; A second regression equation acquisition module, used to acquire a second regression equation of the length of the lines of the cluster and the actual optical attenuation value of the entire process of the lines of the cluster by using the lines removed from the cluster; A third regression equation acquisition module, used to acquire a third regression equation of the full-range actual optical attenuation value of the lines of the cluster and a deviation value between the full-range actual optical attenuation value of the lines of the cluster and the full-range virtual optical attenuation value of the lines of the cluster calculated by the second regression equation of the cluster; The light attenuation positioning module is used to locate the light attenuation interval in 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 any one of the methods of claims 1-6.

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

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