A method and apparatus for identifying a same-route optical cable

Abstract

The application discloses a kind of same route optical cable identification method and device, to solve the problem of low efficiency of identifying same route optical cable.The scheme provided in the present application includes: obtaining the historical optical path data of network to be identified;Determine the frequent pattern set of historical optical path data;Determine the optical cable of the multiple frequent items in the historical optical path data as the optical cable to be tested, which appears with frequency greater than the preset frequency;According to the preset correlation analysis model, the correlation analysis is carried out on the multiple optical cables to be tested to obtain the analysis result representing the correlation between the multiple optical cables to be tested;Determine the multiple optical cables to be tested as same route optical cable, which has greater correlation than the preset correlation.The scheme of the embodiment of the present application determines the frequent pattern set based on the historical optical path data, and preliminarily determines the optical cable to be tested according to the frequent item therein.Subsequently, the correlation analysis is carried out on the optical cable to be tested based on the preset correlation analysis model, which effectively improves the efficiency and accuracy of identifying same route optical cable.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication, and in particular to a same-route optical cable identification method and device. BACKGROUND

[0002] In the operation of the optical cable network of a telecom operator, a resource object directly reachable by optical signals composed of fiber cores connected to each other (including fusion splicing, jumper connection, etc.) is called an optical path. The optical path encapsulates the information of the underlying fiber cores and optical cables, and directly corresponds to the transmission topology or service system, serving as a bridge connecting the communication service information and the optical cable and fiber core information. Therefore, the optical path is an important resource object in pipeline resource management.

[0003] With the increasing complexity of network transmission systems and the increasing diversity of structures, in the actual network construction and service opening process, the same-route optical cable may occur. The same-route optical cable includes at least two cases of same-cable and same-trench. The same-cable refers to at least two different optical paths passing through the same optical cable segment. The same-trench refers to the case that at least two different optical cable segments pass through the same pipeline or pole path. In the case of construction excavation, splicing maintenance, etc., if the service main and backup optical cables are the same-route optical cables, the main and backup lines will be cut off at the same time, which cannot achieve the effect of network service protection, resulting in network service interruption.

[0004] Due to the long mileage, complex routing, complex transmission network structure, and frequent changes of the optical cable network, only manual data-based manual troubleshooting of the same-route hidden danger requires a lot of manpower and time, and the efficiency is low.

[0005] How to efficiently and accurately identify the same-route optical cable in the network is a technical problem to be solved by the present application. SUMMARY

[0006] The purpose of the embodiments of the present application is to provide a same-route optical cable identification method and device to solve the problem of low efficiency in identifying the same-route optical cable.

[0007] In a first aspect, a same-route optical cable identification method is provided, comprising:

[0008] obtaining historical optical path data of a network to be identified;

[0009] determining a frequent pattern set of the historical optical path data, the frequent pattern set including a plurality of frequent items, the frequent item including the frequency of the appearance of an optical cable in the historical optical path data;

[0010] determining the optical cable of the plurality of frequent items whose frequency of appearance in the historical optical path data is greater than a preset frequency as a to-be-inspected optical cable;

[0011] perform correlation analysis on the plurality of the to-be-tested optical cables according to a preset correlation analysis model to obtain an analysis result representing correlation between the plurality of the to-be-tested optical cables;

[0012] determine the plurality of the to-be-tested optical cables with the correlation greater than the preset correlation as the same-route optical cables.

[0013] In a second aspect, a same-route optical cable identification device is provided, comprising:

[0014] an acquisition module configured to acquire historical optical path data of a network to be identified;

[0015] a first determination module configured to determine a frequent pattern set of the historical optical path data, the frequent pattern set including a plurality of frequent items, the frequent item including a frequency of an optical cable appearing in the historical optical path data;

[0016] a second determination module configured to determine, as to-be-tested optical cables, optical cables of the plurality of the frequent items appearing in the historical optical path data with a frequency greater than a preset frequency;

[0017] an execution module configured to perform correlation analysis on the plurality of the to-be-tested optical cables according to a preset correlation analysis model to obtain an analysis result representing correlation between the plurality of the to-be-tested optical cables;

[0018] a third determination module configured to determine the plurality of the to-be-tested optical cables with the correlation greater than the preset correlation as the same-route optical cables.

[0019] In a third aspect, an electronic device is provided, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor, and when the computer program is executed by the processor, the steps of the method of the first aspect are implemented.

[0020] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the method of the first aspect are implemented.

[0021] In the embodiment of the present application, the historical optical path data of the network to be identified is acquired, the frequent pattern set of the historical optical path data is determined, the frequent pattern set includes a plurality of frequent items, the frequent item includes the frequency of the optical cable appearing in the historical optical path data, the optical cable of the plurality of frequent items appearing in the historical optical path data and having a frequency greater than a preset frequency is determined as a cable to be tested, the correlation analysis of the plurality of cables to be tested is performed according to a preset correlation analysis model to obtain an analysis result representing the correlation between the plurality of cables to be tested, and the plurality of cables to be tested having a correlation greater than a preset correlation are determined as the same-route optical cables. The scheme of the embodiment of the present application determines the frequent pattern set based on the historical optical path data, the historical optical path data can represent the characteristics of the optical cable in the historical use process, so each frequent item in the determined frequent pattern set can also represent the frequency of the optical cable appearing in the use process. Then, the plurality of cables to be tested which are possibly the same-route optical cables are preliminarily determined according to the frequent items. Subsequently, the correlation analysis of the plurality of cables to be tested is further performed based on the preset correlation analysis model, so that the plurality of cables to be tested which are closely related are identified as the same-route optical cables, and the identification efficiency and accuracy are effectively improved. BRIEF DESCRIPTION OF DRAWINGS

[0022] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0023] Figure 1a FIG. 1 is a structural schematic diagram of OTN optical path main and backup optical fibers of an embodiment of the present application.

[0024] Figure 1b FIG. 2 is a structural schematic diagram of same-site outgoing optical fibers of an embodiment of the present application.

[0025] Figure 1c FIG. 3 is a structural schematic diagram of protection service optical fibers of an embodiment of the present application.

[0026] Figure 1d FIG. 4 is a structural schematic diagram of same-ring optical fibers of an embodiment of the present application.

[0027] Figure 1e FIG. 5 is a flow schematic diagram of one of a same-route optical cable identification method of an embodiment of the present application.

[0028] Figure 1f FIG. 6 is a system structural schematic diagram of acquiring historical optical path data in an embodiment of the present application.

[0029] Figure 2a FIG. 7 is a flow schematic diagram of another of a same-route optical cable identification method of an embodiment of the present application.

[0030] Figure 2bis a flowchart of a process for determining a frequent pattern set based on a frequent pattern tree according to an embodiment of the present application.

[0031] Figure 3a is a flowchart of a process for identifying a same-route optical cable according to an embodiment of the present application.

[0032] Figure 3b is a structural diagram of a same-cable detection instrument according to an embodiment of the present application.

[0033] Figure 3c is a schematic diagram of the principle of OTDR technology according to an embodiment of the present application.

[0034] Figure 3d is a schematic diagram of the principle of optical detection parameter detection according to an embodiment of the present application.

[0035] Figure 4 is a flowchart of a process for identifying a same-route optical cable according to an embodiment of the present application.

[0036] Figure 5a is a flowchart of a process for identifying a same-route optical cable according to an embodiment of the present application.

[0037] Figure 5b is a schematic diagram of the principle of coherent detection of reference light and Brillouin signals according to an embodiment of the present application.

[0038] Figure 6 is a flowchart of a process for identifying a same-route optical cable according to an embodiment of the present application.

[0039] Figure 7 is a structural diagram of a same-route optical cable identification device according to an embodiment of the present application. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application. The numbering of the drawings in the present application is only used to distinguish each step in the scheme, and is not used to limit the execution order of each step, which is subject to the description in the specification.

[0041] In the field of communication, there are various forms of same-route optical cables, for example, the following four forms of same-route optical cables may cause network service risks: optical transport network (OTN) optical path main and backup optical fibers, same-site outgoing optical fibers, protection service optical fibers, and same-ring optical fibers.

[0042] OTN optical path primary and backup fiber optic cables, such as Figure 1a As shown, the primary and backup optical fibers in the optical path need to be strictly separated in the physical route, such as... Figure 1a The diagram shows that the primary and backup optical fibers between network elements A and B are optical cables with the same route.

[0043] Outgoing fiber optic cable from the same site, such as Figure 1b As shown, in the same network element location, core sites have multiple outgoing ports, while non-core sites have 1-2 outgoing ports. When the number of optical directions exceeds the number of outgoing ports, the outgoing routes will be the same.

[0044] Protecting service fiber optic cables, such as Figure 1c As shown, for the same protection service, the primary and backup links need to be strictly separated physically. Figure 1c The diagram shows that ABD and ACD are not strictly separated, indicating a co-routing issue.

[0045] Co-ring fiber such as Figure 1d As shown, when services are dual-homed, they are typically connected to two different network elements on the ring. If there is a common route in the east-west direction of the ring, the service is at risk. For example... Figure 1d The services are connected to network elements A and B respectively. If fiber optic cable 1 and fiber optic cable 3 are routed together, the services are at risk of being routed together.

[0046] Therefore, co-routing in real-world networks takes many forms. To ensure service stability, it is necessary to detect and identify various types of co-routing. While theoretically co-routing can be detected and identified manually based on data from the asset management system, this method requires significant manpower and time investment and yields minimal results, exhibiting the following drawbacks:

[0047] 1. The data in the asset management system is not detailed enough and is inaccurate, which is insufficient to support accurate identification of the same route, resulting in low identification accuracy.

[0048] 2. The large number of optical cables and the complexity of relays and routing in the network make troubleshooting difficult, time-consuming, and prone to omissions, leading to inaccurate results.

[0049] 3. On-site troubleshooting involves various working environments, a large workload, and often requires interrupting or switching services, affecting network service functions.

[0050] To address the problems existing in the prior art, embodiments of this application provide a method for identifying optical cables with the same route, such as... Figure 1e As shown, it includes:

[0051] S11: Obtain historical optical path data of the network to be identified.

[0052] The historical optical path data in the scheme can specifically include network topology, service routing, historical alarms, historical performance, deep measurement records and the like of the network to be identified. These data can truly reflect the characteristics of the network to be identified in the historical actual application process. Optionally, the various data of the network to be identified are preliminarily processed in a form convenient for subsequent processing by means of screening, classification, formatting and the like, and are summarized as the historical optical path data.

[0053] The optical path name, optical path routing, opening time, optical distribution frame (ODF), optical cable segment, joint box and the like in the historical optical path data can be used to determine the grouping of the optical paths, and are beneficial to determining the same routing scenario in the subsequent steps. The same routing can specifically be divided into two cases of same cable and same trench.

[0054] The same cable refers to two different optical paths passing through the same optical cable segment, that is, the same routing of the two optical paths. If two optical paths with a mutual protection relationship exist, the same cable problem will occur, and once the optical cable segment is interrupted, the two optical paths will be interrupted at the same time, and the protection measure will fail. In the same cable scenario, the same optical cable segment is contained in the two different optical paths, and the same cable scenario can be identified by identifying the same optical cable segment.

[0055] The same trench refers to the case that different optical cable segments pass through a unified pipeline or pole path. When the same trench problem occurs, the same pipeline or pole path appears in the different optical cable segments passed by the two optical paths. In this case, the problem of double interruption leading to protection failure is also prone to occur. The optical cable pipeline, pole path and the like in the historical optical path data can be used to identify the same trench scenario.

[0056] Therefore, based on the same cable and the same trench in the same routing, if the same optical cable segment appears in the routing of the two optical paths, it is determined that the same cable of the two optical paths occurs, and if the same optical cable segment does not appear in the routing of the two optical paths, but the pipeline, pole path passed by the optical cable segments of the two optical paths appears the same segment, it is determined that the same trench of the two optical paths occurs. The same routing can be identified based on the historical alarms, historical performance, deep measurement records and the like in the historical optical path data, and the historical alarms, historical performance, deep measurement records can be further updated synchronously according to the same routing identification result.

[0057] In actual application, the specific way of obtaining the historical optical path data can be selected according to the type and nature of the historical optical path data. For example, the Flink component and related products are introduced in the form of stream processing and batch processing integration to realize real-time reception of network topology, service routing, historical alarms, historical performance, deep measurement records and the like of the network. Based on double stream Join, the correlation analysis of different data streams is realized, the low-latency stream subscription of Flink is used to improve the data synchronization processing capability. The system structure diagram for obtaining the historical optical path data can be as shown in Figure 1f .

[0058] In actual application, processing can be performed on network topology, service routing, historical alarm, historical performance, deep measurement record and other data to obtain historical optical path data such as optical path name, optical path routing, opening time, geographical routing (pipe, pole path, etc.), network element structure. The optical path routing can record the data such as ODF, optical cable section, joint box passed by the optical path, and the historical alarm, historical performance, deep measurement record data therein can provide data basis for subsequent steps.

[0059] S12: Determine a frequent pattern set of the historical optical path data, the frequent pattern set including a plurality of frequent items, and the frequent item including a frequency of appearance of an optical cable in the historical optical path data.

[0060] In the embodiment, the frequency of appearance of each optical cable in the historical optical path data is determined based on the historical optical path data to determine the frequent pattern set. For example, the optical path group can be analyzed by DFP-Max in the association algorithm in the artificial intelligence (AI) algorithm, and the frequently appearing optical cable and the frequency of appearance of the optical cable.

[0061] S13: Determine the optical cable of the plurality of frequent items with the frequency of appearance in the historical optical path data greater than a preset frequency as a to-be-inspected optical cable.

[0062] In this step, the historical optical path data is taken as the data basis, and since the historical optical path data of the same routing optical cable has correlation, the to-be-inspected optical cable that may be the same routing optical cable can be preliminarily screened out based on the frequency of appearance of the data of the optical cable in the historical optical path data.

[0063] For example, based on each frequent item in the frequent pattern set in the above step, a corresponding conditional projection database and a projection generated FP-tree can be constructed for each frequent item. Subsequently, based on the DFP-Max algorithm and the FP-tree, the same routing condition is analyzed according to the frequent routing and the frequent pattern, so as to systematically sort out the optical cable cross-section grouping condition of the network transmission system protection line and the optical cable, and actually find out the current optical cable and optical path basic situation.

[0064] S14: Perform correlation analysis on a plurality of the to-be-inspected optical cables according to a preset correlation analysis model to obtain an analysis result representing the correlation between the plurality of the to-be-inspected optical cables.

[0065] Based on the above steps, the to-be-tested optical cables that are likely to be the same route optical cables can be preliminarily determined, and in this step, the to-be-tested optical cables can be further analyzed based on the correlation analysis model constructed in advance to determine the correlation between the to-be-tested optical cables. Since the correlation between the same route optical cables is close, the analysis result between the to-be-tested optical cables determined by the correlation analysis model can represent the possibility that the to-be-tested optical cables are the same route optical cables.

[0066] For example, in this step, the fiber optical detection can be performed based on the optical properties of the optical cables, the Rayleigh scattering, Raman scattering and Brillouin scattering generation mechanisms are used, and the optical time-domain reflectometer (OTDR) is used to realize the monitoring and analysis of the physical quantities (vibration, stress, temperature) around the optical fiber, so that the correlation analysis can be realized while reducing the adverse effects on the network service.

[0067] Specifically, the AI feature modeling can be performed by a similarity evaluation algorithm based on the optical and mechanical data of the to-be-tested optical cables, and the same cable recognition can be performed by comprehensively collecting the network inventory data and the site geographic information of the NCE / U2000.

[0068] S15: Determine the to-be-tested optical cables with a correlation greater than a preset correlation as the same route optical cables.

[0069] In actual application, the numerical range of the analysis result of the correlation can be [0, 1], wherein the analysis result of the correlation is 0, which indicates that the to-be-tested optical cables for correlation analysis are not correlated, and 1, which indicates that the to-be-tested optical cables are closely correlated. The above-mentioned preset correlation can be preset according to actual needs, for example, the preset correlation is 0.9. Then, the to-be-tested optical cables with a numerical value greater than 0.9 and less than or equal to 1 of the analysis result of the correlation are determined as the same route optical cables.

[0070] Optionally, the preset correlation can also be determined according to the numerical value of the analysis result output in the above-mentioned step. For example, if the number of the output analysis result is multiple, the multiple analysis results can be sorted according to the numerical value, and the to-be-tested optical cables corresponding to the top 10% analysis results with large numerical values are determined as the same route optical cables.

[0071] Based on the scheme provided in the embodiments of the present application, for the identified same route optical cables, targeted rectification can be further performed to exclude the same route problem in the network and ensure the stability of the network service. The identification process of the present scheme is fast, accurate, and the data is checkable, and the identification algorithm and model can be continuously optimized, thereby solving the problems of difficult, time-consuming and laborious and inaccurate troubleshooting.

[0072] In the embodiment of the present application, the historical optical path data of the network to be identified is acquired, a frequent pattern set of the historical optical path data is determined, the frequent pattern set includes a plurality of frequent items, the frequent item includes the frequency of the optical cable appearing in the historical optical path data, the optical cable of the plurality of frequent items appearing in the historical optical path data and having a frequency greater than a preset frequency is determined as a cable to be tested, a correlation analysis is performed on the plurality of cables to be tested according to a preset correlation analysis model to obtain an analysis result representing the correlation between the plurality of cables to be tested, and the plurality of cables to be tested having a correlation greater than a preset correlation are determined as the same route optical cables. The scheme of the embodiment of the present application determines the frequent pattern set based on the historical optical path data, and since the historical optical path data can represent the characteristics of the optical cable in the historical use process, each frequent item in the determined frequent pattern set can also represent the frequency of the optical cable appearing in the use process. Then, the plurality of cables to be tested that are possibly the same route optical cables are preliminarily determined according to the frequent items. Subsequently, the correlation analysis model is further used to perform the correlation analysis on the plurality of cables to be tested based on the preset correlation analysis model, so that the plurality of cables to be tested that are closely related are identified as the same route optical cables, and the identification efficiency and accuracy are effectively improved.

[0073] According to the scheme provided in the above embodiment, optionally, the historical optical path data includes a plurality of optical path identifiers in the network to be identified and optical cable segment identifiers corresponding to the optical path identifiers.

[0074] As shown in the above step S12, the above step S12 includes: Figure 2a

[0075] S21: determining a frequent item corresponding to the optical cable segment identifier according to the historical optical path data, the frequent item including the optical cable segment identifier and the frequency of the optical cable segment identifier appearing in the historical optical path data.

[0076] This step can be implemented based on the DFP-Max algorithm analysis. For example, based on the DFP-Max algorithm, the frequent pattern of each element such as network topology and service routing is acquired, and the frequent pattern reflects the frequency of the element appearing.

[0077] S22: constructing conditional projection data of the frequent item and projecting the frequent pattern tree, the frequent pattern tree representing the combination of the optical cable segment identifiers appearing in the historical optical path data and having a frequency greater than the preset frequency.

[0078] ​Based on the DFP-Max algorithm described above, a conditional projection database and a projected FP-tree are constructed for each frequent item. The FP-tree is used to store the largest frequent itemset discovered during the recursive process and to detect candidate itemsets for the currently discovered largest frequent itemset. Specifically, elements are sorted in descending order by frequent patterns and stored in the item header table, and frequent patterns are selected. When the constructed FP-tree is empty, its prefix is ​​the frequent pattern; when it contains only one path, the frequent pattern is obtained by enumerating all possible combinations and connecting them to the prefix of this tree. The frequent patterns of element combinations are obtained from the frequent pattern tree. Based on the above frequent route mining, frequent route combinations and their frequency of occurrence are obtained.

[0079] S23: Determine the frequent pattern set based on the frequent pattern tree.

[0080] Based on the DFP-Max algorithm and FP-tree, the frequent patterns of each element can be obtained. By obtaining the element combinations and their frequent patterns from the frequent pattern tree, the same routing situation can be analyzed.

[0081] For example, such as Figure 2b As shown, this scheme uses four optical paths as an example for comparison, with each optical path's fiber optic cable segment represented by a numerical code. Through frequent term analysis, we obtain the C1 co-routes table, and further through C2 and C3, we obtain the cases of multiple co-routes. Taking C3 as an example, optical paths coded 20 and 30 show three identical fiber optic cable segments: 2, 3, and 5. In practical applications, if fiber optic cable segments 2, 3, and 5 are consecutive, we will merge these segments, treating them as a single co-routes with a length equal to the sum of the lengths of the segments.

[0082] The solution provided in this application, which combines frequent pattern tree analysis of co-route optical cables, can effectively improve the accuracy of identifying co-route optical cables and avoid the problem of inaccurate identification caused by data omission or duplicate statistics.

[0083] Based on the solutions provided in the above embodiments, optionally, such as Figure 3a As shown, step S14 above includes:

[0084] S31: Obtain optical detection parameters of multiple optical cables to be inspected, including Rayleigh scattering parameters and / or Raman scattering parameters.

[0085] S32: Determine the temperature information of the multiple optical cables to be inspected based on the optical detection parameters.

[0086] S33: Perform correlation analysis on the temperature information of multiple optical cables to be tested to obtain analysis results characterizing the correlation between the temperature information of multiple optical cables to be tested.

[0087] In the present embodiment, the optical detection parameters can be acquired by a same-cable detection instrument, which comprises a Rayleigh scattering and Raman scattering module and a Brillouin scattering module integrated, as shown in Figure 3b .

[0088] The Rayleigh scattering and Raman scattering module is realized based on the distributed optical fiber sensing technology of Rayleigh scattering and Raman scattering. The material of the optical fiber is not completely uniform in composition and density in essence, so that the refractive index of the optical fiber also presents non-uniformity, and the scattering of the propagation in each direction caused thereby is called Rayleigh scattering. Rayleigh scattering belongs to elastic scattering, the frequency of the scattered light is the same as that of the original light wave, and the intensity is proportional to the original light intensity, and the ratio thereof is called the Rayleigh scattering coefficient.

[0089] When the light wave propagates in the optical fiber, the photon collides with the molecules in thermal motion in the optical fiber, and spontaneous Raman scattering is generated. Relative to the frequency of the incident light, the Raman scattering light has two symmetrically distributed frequency shift sidebands, wherein the frequency down-shifted one is called Stokes light, and the frequency up-shifted one is called Anti-Stokes light, which are about 13.2 THz different from the frequency of the incident light. The intensity of the Anti-Stokes light with higher frequency changes significantly with temperature, and the sensitivity to temperature change can reach 0.8% / °C, which is the physical basis for the use of Raman scattering for temperature sensing.

[0090] The optical time domain reflectometry (OTDR) technology senses through the backscattered Rayleigh scattering light intensity of the optical pulse. By measuring the time and power of the Rayleigh scattering light of the pulse light reaching the detector, and combining the speed of light in the optical fiber, the optical power of the Rayleigh scattering light at each position in the optical fiber can be obtained, so as to obtain the loss distribution along the line of the optical fiber.

[0091] Since the Rayleigh scattering light and the Stokes light of the Raman scattering are not affected by temperature, in the distributed temperature sensing system based on Raman scattering, the Anti-Stokes light with higher frequency and temperature sensitivity is used as signal light, and the Stokes light with lower frequency and temperature insensitivity or the Rayleigh scattering light is used as reference light. The ratio of the intensities of the signal light and the reference light is detected, and the temperature information along the line of the optical fiber is demodulated by combining the OTDR technology, so as to realize the sensing of the temperature along the line of the optical fiber. The technology of taking the ratio of the two light signals can also effectively reduce the fluctuation of the intensity of the scattered light caused by the instability of the system, and the system principle is shown in Figure 3c .

[0092] If the same-cable detection instrument is used to acquire the above optical detection parameters, the optical detection step is as follows:

[0093] 1. Carding meets the detection fiber segment, develop detection scheme, according to paragraph detection long fiber connection network element. The optical fiber distance between network elements to be tested is less than or equal to 50 kilometers, using single-end detection, and the optical fiber distance is 50-100 kilometers, using double-end detection.

[0094] 2. Connect the monitoring channel (Optical Supervisory Channel, OSC) monitoring port on the FIU (Facilities Interface Unit) single board of the detection instrument, and the portable machine sends a collection command to the detection instrument, and performs optical detection based on the optical characteristics of the optical cable. Using Rayleigh scattering, Raman scattering distributed optical fiber sensing technology, combined with optical time domain reflectometry (OTDR) demodulation of the temperature information along the optical fiber, so as to realize the sensing of the temperature along the optical fiber. Using Brillouin scattering and optical time domain reflectometry (OTDR), the vibration and stress information around the optical fiber can also be collected, as shown in Figure 3d Subsequently, the detection instrument synchronizes the results to the portable machine, and synchronizes the data of the portable machine to the system for subsequent processing.

[0095] Through the scheme provided by the embodiment of the application, the correlation of the optical cable can be further analyzed based on the temperature along the optical cable, and the accuracy of identifying the same route optical cable is improved.

[0096] Based on the scheme provided by the above embodiment, as shown in Figure 4 The above step S33 includes:

[0097] S41: Constructing a temperature information correlation analysis model according to the Spearman rank correlation algorithm Wherein, ρ s represents the correlation analysis result, x i represents the i-th parameter sample in the optical detection parameter of the first optical cable, y i represents the i-th parameter sample in the optical detection parameter of the second optical cable, represents the mean value of the optical detection parameter of the first optical cable, represents the mean value of the optical detection parameter of the second optical cable;

[0098] S42: Determining the analysis result of the correlation between the temperature information of a plurality of said to be tested optical cables according to the temperature information of a plurality of said to be tested optical cables and the temperature information correlation analysis model.

[0099] In the embodiment, the correlation analysis refers to analyzing two or more variable elements with correlation, so as to measure the correlation closeness of two variable factors. According to the respective optical characteristics of Rayleigh scattering and Raman scattering, a linear correlation analysis is performed based on the rank of the variable by using Spearman's correlation coefficient for ranked data (Spearman), so as to determine the possibility of the same routing of the two optical fibers.

[0100] Firstly, the detection result of the same cable detection instrument is imported. Specifically, the optical cable optical detection Rayleigh scattering and Raman scattering fiber along the line temperature detection result can be automatically imported into the system. Then, the temperature distribution map is generated based on the detection result of the above instrument. Specifically, the distribution map can include a curve representing the temperature of the optical fiber.

[0101] Subsequently, the AI same cable model is established based on the above temperature information. Specifically, the model is built by using Spearman's rank correlation, and a linear correlation analysis is performed based on the rank of the variable. The correlation analysis model is established based on the following formula:

[0102]

[0103] The temperature information of the two optical cables to be tested is input into the above model, and the correlation analysis result output can represent the possibility of the two optical cables to be tested being the same routing optical cable. If the number of optical cables to be tested is greater than 2, the above model can be used to analyze two by two for multiple optical cables to be tested.

[0104] Further, if the correlation of the above optical cables to be tested is greater than the preset correlation, it can be determined that the two optical cables are the same routing optical cable. Further, the length of the same routing optical cable can be further determined based on the same cable length model:

[0105]

[0106] Wherein, l is the length of the optical fiber same cable, v is the speed of light in the optical fiber, and Δt is the time interval between the emission of the pulse and the reception of the signal.

[0107] Through the scheme provided in the embodiment, the correlation analysis of the optical cables to be tested can be performed by using the temperature information correlation analysis model, so as to determine the possibility of the optical cables to be tested being the same routing optical cable, and the accuracy of identifying the same routing optical cable is effectively improved.

[0108] Based on the scheme provided in the above embodiment, as shown in Figure 5a The step S14 includes:

[0109] S51: respectively acquire polarization state parameters of the plurality of to-be-inspected optical cables in a same historical period, the polarization state parameters comprising polarization stress values of the to-be-inspected optical cables in the historical period.

[0110] S52: construct three-dimensional polarization models corresponding to the plurality of to-be-inspected optical cables respectively in the historical period according to the polarization state parameters;

[0111] S53: perform correlation analysis on the plurality of three-dimensional polarization models to obtain a correlation analysis result representing correlations between polarization states of the plurality of to-be-inspected optical cables.

[0112] In the same-cable detector, a Brillouin scattering module is further included, which is implemented based on a distributed sensing technology of Brillouin scattering.

[0113] Brillouin scattering is a non-elastic light scattering caused by interaction between light waves and sound waves during propagation of the light waves and the sound waves in an optical fiber. Like Raman scattering, Brillouin scattering light also has two sidebands, and the difference between the frequencies of the two sidebands and the incident light wave is referred to as Brillouin frequency shift. The frequency shift is essentially dependent on the material and structure of the optical fiber and the frequency of the incident light. For example, the Brillouin frequency shift of a 1550 nm light wave in a quartz optical fiber is about 10-11 GHz. However, under the condition that the intrinsic parameters of the optical fiber are constant, the Brillouin frequency shift will change linearly with the change of the temperature or strain of the optical fiber. By measuring the change of the frequency shift of the Brillouin scattering light in the optical fiber, the temperature or strain condition near the optical fiber can be sensed.

[0114] Brillouin optical time domain reflectometry (BOTDR) is a full-distributed optical fiber sensing system based on Brillouin scattering. The system transmits a pulse from one end of an optical fiber, and detects the backscattered Brillouin signal at the transmitting end. The time delay between the transmission of the pulse and the reception of the scattered signal multiplied by the speed of light can provide the position information of the optical fiber detection. Since the frequency shift and intensity of the Brillouin scattering spectrum have a linear relationship with the temperature and strain of the optical fiber, the distribution information of the temperature and strain of the optical fiber can be obtained by measuring the intensity and frequency shift of the Brillouin signal.

[0115] A microwave electro-optical modulator is used to generate a frequency-adjustable reference light, and a method of coherent detection of the Brillouin signal is used. The basic structure of the detection system can be as follows Figure 5bThe continuous light emitted by the narrow linewidth laser is divided into two paths by the coupler, one of which is used as probe light, first modulated into pulse light of a certain width by the pulse modulator, and then injected into the sensing fiber through the optical amplifier and the coupler. The other laser passes through the electro-optical modulator driven by the about 11GHz microwave, generating the positive and negative first-order sideband light of the laser, which is used as the local reference light and is coherent with the Brillouin scattering light scattered back from the sensing fiber, and is received by the heterodyne light receiver. After photoelectric conversion, a Brillouin scattering spectrum electrical signal with a center frequency of about 100MHz and a full width at half maximum of tens of megahertz is generated. The Brillouin scattering spectrum electrical signal is mixed with the local oscillator in the mixer to obtain the baseband signal of the Brillouin scattering spectrum, which is then filtered, analog-digital converted and accumulated and averaged to obtain the Brillouin scattering signal on the entire sensing fiber, which is sent to the computer for display. If the bandwidth of the filter is less than the Brillouin scattering spectrum width, in order to obtain the entire Brillouin scattering spectrum, the probe pulse light needs to be injected into the fiber multiple times, and the output frequency of the microwave source is changed each time, so that the frequency of the local reference light is changed, so that the signals of different frequency components on the Brillouin scattering spectrum pass through the filter to be detected.

[0116] In the scheme, the correlation analysis can be realized by using the Spearman rank correlation three-dimensional space algorithm based on the millisecond-level polarization state (SOP) acquisition, the similarity of the polarization state at the same time, and the possibility of the same cable of the two optical fibers is determined.

[0117] Firstly, the polarization state parameters are introduced into the system, and then a three-dimensional distribution map is generated based on the polarization state parameters to represent the polarization state of each optical fiber. Then, a model is built by using the Spearman rank correlation three-dimensional space algorithm, as shown in the following formula (1-3), and then a linear correlation analysis is performed based on the rank of the variable.

[0118]

[0119] wherein, p s is the correlation analysis result, x i represents optical fiber 1, y represents optical fiber 2, i is the sample serial number of the optical fiber data (i = 1,..., n), y i1 represent the i-th sample of the vibration data of the two optical fibers respectively, y i2 represent the i-th sample of the stress data of the two optical fibers respectively, are the mean values of the vibration data of the two optical fibers respectively, are the mean values of the stress data of the two optical fibers respectively.

[0120] Subsequently, the same cable length model (1-2) described in the above embodiment can be further used to determine the same cable length.

[0121] Through the scheme provided by the embodiment of the application, the accuracy of identifying the same-routing optical cable can be improved based on the polarization state parameter of the optical fiber.

[0122] According to the scheme provided by the above embodiment, optionally, the historical optical path data of the network to be identified includes at least one of the following: network site geographic information, optical path information of each other as master and backup, network site egress port information, and network element topology information.

[0123] In actual application, more types of data can be obtained according to actual needs to further improve the accuracy of identifying the same-routing optical cable.

[0124] According to the scheme provided by the above embodiment, optionally, after the step S15, as shown in the following step S16, the method further includes: Figure 6

[0125] S61: sending a detection pulse signal from one end of the same-routing optical cable to the same-routing optical cable at a first time;

[0126] S62: obtaining a second time at which the other end of the same-routing optical cable receives the detection pulse signal;

[0127] S63: identifying the length of the same-routing optical cable according to the first time, the second time, and a same-cable length identification model wherein l represents the length of the same-routing optical cable, v is the signal transmission speed in the optical cable, and Δt is the time difference between the first time and the second time.

[0128] After the same-routing optical cable is determined, the length of the same-routing optical cable can be further determined through the scheme provided by the embodiment of the application. The length of the same-routing optical cable is beneficial to repairing and adjusting the same-routing optical cable, thereby guaranteeing the stability of network services.

[0129] In actual application, the same-routing optical cable can also be identified based on the above optical detection parameters, polarization state parameters, or other various optical fiber sensing parameters, to further improve the accuracy of identifying the same-routing optical cable.

[0130] The scheme can quickly and accurately identify the same-routing optical cable, which is beneficial to guiding optical fiber construction, daily operation of inventory same-cable, and other scenarios, can assist in excluding the business master and backup physical same-routing risk of the detectable section, and can also reverse clean the "comprehensive" system data through physical detection data.

[0131] ​The embodiment of the application is based on the Flink "stream batch integration" solution, and the data timeliness is significantly improved. The Flink component and related products are introduced, and based on the above-mentioned "stream batch integration" solution, the network topology, service routing, historical alarm, historical performance, deep measurement record and other live network basic data are connected, and the data timeliness is improved from the original 5 hours to 25 analysis, the efficiency is improved by 500%, and the problems of data dispersion and long collection time are effectively solved.

[0132] The embodiment of the application collects live network basic data, does not depend on asset management and the data is checkable, and is more accurate. The data is based on two aspects, one is based on network topology and service routing basic data, to obtain optical path name, optical path routing, opening time, geographic routing (pipe, pole road, etc.), network element structure, optical fiber distribution frame, optical cable section, junction box and other data; the second is to take historical alarm, historical performance, deep measurement record data as a reference in the identification process and data checking basis. The problem of relatively single data source and uncheckable is solved.

[0133] The same cable detection instrument in the scheme integrates Rayleigh scattering, Raman scattering and Brillouin scattering distributed optical fiber sensing technology, supports three kinds of scattering detection, and is relatively flexible in scene. Moreover, it can feedback real business same routing, can online detect in-use fiber core, feedback real business same routing, can effectively support live network rectification, and eliminate same cable risk. In addition, the scheme can minimize the impact on normal optical cable operation. The instrument performs online detection on the optical fiber through the OSC monitoring port on the FIU type single board. First, the impact on OSC communication: if the network element has a backup communication routing (such as other direction OSC, ESC communication routing), the monitoring can not be interrupted.

[0134] Further, for the correlation analysis model constructed by the scheme, optimization training can also be performed on the model based on the checking result. Specifically, AI feature modeling can be performed according to the NCE / U2000 collected network inventory data and site GIS information, and same cable detection instrument data. The same cable length information and same routing judgment rule are comprehensively used to perform "two recognition and one judgment" identification. It provides a basis for subsequent optical cable management, construction, analysis and decision-making.

[0135] The scheme provided by the embodiment of the application can be applied to various stages such as optical fiber new construction, later maintenance, fault repair, etc. For example, after engineering construction, the newly constructed equipment is checked for optical cable, the physical same routing risk is investigated, the rectification is performed before bearing service, and the engineering quality is ensured. In daily maintenance, annual full OTN network check, quarterly county / city OTN network check, and monthly trunk OTN network check are performed. After network adjustment, the physical same routing risk is investigated after optical cable splicing, migration adjustment, to avoid service damage caused by optical cable interruption. After fault rush-through optical cable is reversed, the physical same routing is investigated, and whether the jump optical fiber is completed reverse operation is investigated, to avoid service damage caused by optical cable interruption.

[0136] To solve the problems in the prior art, the embodiment of the present application further provides a same-route optical cable identification device 70, as shown in the figure, comprising: Figure 7

[0137] An acquisition module 71 acquires historical optical path data of a network to be identified.

[0138] A first determination module 72 determines a frequent pattern set of the historical optical path data, wherein the frequent pattern set comprises a plurality of frequent items, and the frequent item comprises a frequency of an optical cable appearing in the historical optical path data.

[0139] A second determination module 73 determines, as optical cables to be inspected, the optical cables of the plurality of frequent items appearing in the historical optical path data with a frequency greater than a preset frequency.

[0140] An execution module 74 performs correlation analysis on the plurality of optical cables to be inspected according to a preset correlation analysis model to obtain an analysis result representing the correlation between the plurality of optical cables to be inspected.

[0141] A third determination module 75 determines, as same-route optical cables, the plurality of optical cables to be inspected with a correlation greater than a preset correlation.

[0142] Through the device provided by the embodiment of the present application, the historical optical path data of a network to be identified is acquired, the frequent pattern set of the historical optical path data is determined, the frequent pattern set comprises a plurality of frequent items, the frequent item comprises a frequency of an optical cable appearing in the historical optical path data, the optical cables of the plurality of frequent items appearing in the historical optical path data with a frequency greater than a preset frequency are determined as optical cables to be inspected, correlation analysis is performed on the plurality of optical cables to be inspected according to a preset correlation analysis model to obtain an analysis result representing the correlation between the plurality of optical cables to be inspected, and the plurality of optical cables to be inspected with a correlation greater than a preset correlation are determined as same-route optical cables. The scheme of the embodiment of the present application determines the frequent pattern set based on the historical optical path data, and since the historical optical path data can represent the characteristics of the optical cable in the historical use process, each frequent item in the determined frequent pattern set can also represent the frequency of the optical cable in the use process. Then, the plurality of optical cables to be inspected that are possibly same-route optical cables are preliminarily determined according to the frequent items. Subsequently, correlation analysis is further performed on the plurality of optical cables to be inspected based on the preset correlation analysis model, so that the plurality of optical cables to be inspected that are closely related are identified as same-route optical cables, and the identification efficiency and accuracy are effectively improved.

[0143] Preferably, the embodiment of the present application further provides an electronic device comprising a processor, a memory, a computer program stored in the memory and executable on the processor, which, when executed by the processor, implements each process of the above-mentioned same-route optical cable identification method embodiment and achieves the same technical effect. To avoid repetition, details are not described here.​

[0144] The embodiment of the present application further provides a computer readable storage medium, and the computer readable storage medium stores a computer program, the computer program is executed by a processor to realize each process of the above-mentioned one kind of same route optical cable identification method embodiment, and can achieve the same technical effect, to avoid repetition, here is no longer tedious. Wherein, the computer readable storage medium, such as read-only memory (Read-Only Memory, ROM for short), random access memory (Random Access Memory, RAM for short), magnetic disc or optical disc and the like.

[0145] It should be noted that in this paper, the term "include", "contain" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0146] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment method can be realized by means of software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of software product, which is stored in a storage medium (such as ROM / RAM, magnetic disc, optical disc), including a plurality of instructions for making a terminal (which can be a mobile phone, computer, server, air conditioner or network equipment) execute the method described in each embodiment of the present application.

[0147] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the above-mentioned specific embodiments, the above-mentioned specific embodiments are only illustrative, not restrictive, and those skilled in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, which all belong to the protection of the present application.

Claims

1. A method for identifying optical cables on the same route, characterized in that, include: Acquire historical optical path data of the network to be identified; Determine a set of frequent patterns in the historical optical path data. The set of frequent patterns includes multiple frequent items, and the frequent items include the frequency of the optical cable appearing in the historical optical path data. Optical cables with multiple frequent items appearing in the historical optical path data at a frequency greater than a preset frequency are identified as optical cables to be inspected. A correlation analysis is performed on multiple optical cables to be tested according to a preset correlation analysis model to obtain analysis results characterizing the correlation between the multiple optical cables to be tested. Multiple optical cables to be tested with a correlation greater than the preset correlation are identified as optical cables with the same route. The step of performing correlation analysis on multiple optical cables to be tested according to a preset correlation analysis model to obtain analysis results characterizing the correlation between the multiple optical cables to be tested includes: Optical detection parameters of multiple optical cables to be inspected are obtained respectively, including Rayleigh scattering parameters and / or Raman scattering parameters; The temperature information of multiple optical cables to be inspected is determined based on the optical detection parameters. A correlation analysis is performed on the temperature information of multiple optical cables to be tested to obtain the analysis results characterizing the correlation between the temperature information of multiple optical cables to be tested.

2. The method as described in claim 1, characterized in that, The historical optical path data includes multiple optical path identifiers in the network to be identified and the optical cable segment identifiers corresponding to the optical path identifiers; The determination of the frequent pattern set of the historical optical path data includes: Based on the historical optical path data, a frequent item corresponding to the optical cable segment identifier is determined. The frequent item includes the optical cable segment identifier and the frequency of the optical cable segment identifier appearing in the historical optical path data. Construct conditional projection data for the frequent items and project a frequent pattern tree, wherein the frequent pattern tree represents the combination of optical cable segment identifiers that appear more frequently than the preset frequency in the historical optical path data; The frequent pattern set is determined based on the frequent pattern tree.

3. The method as described in claim 1, characterized in that, A correlation analysis is performed on the temperature information of multiple optical cables under test to obtain analysis results characterizing the correlation between the temperature information of the multiple optical cables under test, including: A correlation analysis model for temperature information was constructed based on the Spearman rank correlation algorithm. ,in, This indicates the results of the relevant analysis. The first optical cable's optical detection parameters represent the... Parameter samples, The first of the optical detection parameters of the second optical cable Parameter samples, This represents the average value of the optical detection parameters of the first optical cable. This represents the average value of the optical detection parameters of the second optical cable; The correlation analysis results between the temperature information of the multiple optical cables to be tested are determined based on the temperature information of the multiple optical cables to be tested and the correlation analysis model of the temperature information.

4. The method as described in claim 1, characterized in that, A correlation analysis is performed on multiple optical cables to be tested according to a preset correlation analysis model to obtain analysis results characterizing the correlation between the multiple optical cables to be tested, including: The polarization state parameters of multiple optical cables to be inspected are obtained within the same historical time period, and the polarization state parameters include the polarization stress value of the optical cable to be inspected within the historical time period. Based on the polarization state parameters, construct three-dimensional polarization models corresponding to the multiple optical cables to be inspected during the historical time period; Correlation analysis is performed on multiple three-dimensional polarization models to obtain correlation analysis results characterizing the polarization states of multiple optical cables under test.

5. The method as described in claim 1, characterized in that, The historical optical path data of the network to be identified includes at least one of the following: Network site geographic information, mutual backup optical path information, network site outgoing interface information, and network element topology information.

6. The method according to any one of claims 1 to 5, characterized in that, After identifying multiple optical cables under test with a correlation greater than the preset correlation as optical cables on the same route, the following steps are also included: At the first moment, a detection pulse signal is sent from one end of the optical cable with the same route to the optical cable with the same route; Obtain the second moment at which the other end of the same-route optical cable receives the detection pulse signal; Based on the first time point, the second time point, and the same cable length identification model Determine the length of the co-route optical cable, where l represents the length of the co-route optical cable, v is the signal transmission speed in the optical cable, and ∆t is the time difference between the first time and the second time.

7. A device for identifying optical cables traveling on the same route, characterized in that, include: The acquisition module acquires historical optical path data of the network to be identified; The first determining module determines the set of frequent patterns in the historical optical path data. The set of frequent patterns includes multiple frequent items, and the frequent items include the frequency of the optical cable appearing in the historical optical path data. The second determining module identifies optical cables with a frequency greater than a preset frequency in the historical optical path data as optical cables to be inspected. The execution module performs correlation analysis on multiple optical cables to be tested according to a preset correlation analysis model to obtain analysis results characterizing the correlation between the multiple optical cables to be tested; The third determination module identifies multiple optical cables to be tested that have a correlation greater than the preset correlation as optical cables with the same route. In the execution module, a correlation analysis is performed on multiple optical cables to be inspected according to a preset correlation analysis model to obtain analysis results characterizing the correlation between the multiple optical cables to be inspected, including: Optical detection parameters of multiple optical cables to be inspected are obtained respectively, including Rayleigh scattering parameters and / or Raman scattering parameters; The temperature information of multiple optical cables to be inspected is determined based on the optical detection parameters. A correlation analysis is performed on the temperature information of multiple optical cables to be tested to obtain the analysis results characterizing the correlation between the temperature information of multiple optical cables to be tested.

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

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 6.

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