Non-intrusive optical fiber link power abnormity positioning method and non-intrusive optical fiber link power abnormity positioning system

Abstract

The invention discloses a non-intrusive optical fiber link power anomaly positioning method and system, and belongs to the technical field of optical fiber communication, and the method comprises the steps: determining initial parameters which comprise a first stage step length delta z1, a first stage scanning range R1, an Mth stage step length delta zM and a preset stage number M; in the R1, monitoring points are deployed with delta z1, and an abnormal positioning result of the first stage is determined based on a power profile estimation (PPE) algorithm; based on the abnormal positioning result of the first stage, performing abnormal positioning stage by stage based on a PPE algorithm by adopting a strategy of reducing the step length and the scanning range stage by stage until an abnormal positioning result of the (M-1) th stage is obtained; and based on the abnormal positioning result of the (M-1) th stage, deploying monitoring points with delta zM in the scanning range RM of the Mth stage, and determining a final abnormal positioning result based on a PPE algorithm through the deployed monitoring points. According to the invention, high-precision positioning under limited computing resources can be realized.

Description

Technical Field

[0001] The present invention relates to the field of optical fiber communication technology, and in particular to a non-invasive optical fiber link power anomaly positioning method and system. Background Art

[0002] The PPE (Power Profile Estimation) method uses the non-commutative relationship between dispersion and nonlinear self-phase modulation operators in optical fiber transmission. It can achieve non-invasive monitoring of the power evolution process in the link only through DSP processing of the received signal. The PPE method greatly reduces the deployment cost of using hardware equipment (such as OTDR (Optical Time-Domain Reflectometer)) to perform invasive monitoring of the link power. The core idea of the PPE algorithm is to simulate the transmission process of the transmitted signal on different nonlinear paths. By constructing multiple mirror paths corresponding to specific positions of the actual nonlinear path, the corresponding output result of the transmitted signal after passing through the mirror path is correlated with the receiving end signal obtained from the actual transmission link, thereby completing the extraction of power information in the path. The algorithm flow is as follows: Figure 1 shown.

[0003] exist Figure 1 middle, is the time domain expression of the linear dispersion filter operator corresponding to the distance from z1 to z2, that is in, is the Fourier operator, ω is the angular frequency. N represents the nonlinear operator function, expressed as N = |·| 2 (·). L is the total length of the link. The construction of the mirror path is very important for extracting link power information. Each mirror path consists of three operation modules with fixed order, namely a front-end dispersion operator module A nonlinear module A backend dispersion operator module The first dispersion filter operator module The corresponding end position z k = kΔz and position z in the link k There is a unique mapping relationship. By looping through k = 0, 1, 2 ... N + 1, where N = L / Δz, a series of mirror paths associated with different positions of the transmission link are constructed. By performing correlation calculation with the received signal A[L,n], the power information of each position in the link can be extracted.

[0004] The location information of abnormal power changes is hidden in the slope change of the PPE output power profile. The power anomaly in the link can be detected by extracting the most obvious location of the slope change. i (z),i∈{ref,mon} is the output of PPE, where γ ref (z) is the PPE output training result obtained when the link is normal, γ mon (z) is the PPE output result when the link is in the monitoring mode where anomalies may occur. Let z represent the monitoring points deployed at intervals of Δz, i.e. z = 0, Δz, 2Δz, …, L total , L total is the overall length of the link. Define the difference curve γ dif (z) as follows:

[0005] γ dif (z) = γ ref (z)-γ mon (z)#(1)

[0006] Subsequently, the γ dif (z) Perform backward difference to extract γ mon (z) and γ ref The trend changes between (z) are as follows:

[0007] Δγ dif (z) = γ dif (z)-γ dif (z-Δz)#(2)

[0008] Where z≥Δz, i.e. z=Δz,2Δz,…,L total , Δγ dif The position indicated by the peak of (z) is the power anomaly position in the link, and we will dif (z) is defined as the abnormal location indicator. In order to show the whole process more clearly, γ ref (z), γ mon (z), γ dif (z), Δγ dif (z) The graphical representation of the 240 km link is as follows Figure 2 .

[0009] The positioning accuracy of the above-mentioned anomaly positioning method depends on the size of the PPE step size Δz. Higher positioning accuracy requires a smaller Δz. However, the smaller Δz is, the more steps need to be performed. Figure 1The loop structure of "partial dispersion compensation - partial nonlinear compensation - residual dispersion compensation" significantly increases the computational complexity required for anomaly location. Because the entire algorithm is completely DSP-based, excessive computational complexity significantly increases the load on the DSP module. Therefore, existing methods struggle to achieve high-precision location with limited computing resources. Summary of the Invention

[0010] The present invention provides a non-invasive optical fiber link power anomaly positioning method and system to solve the technical problem that existing anomaly positioning methods are highly complex and difficult to achieve high-precision positioning under limited computing resources.

[0011] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0012] In one aspect, the present invention provides a non-invasive method for locating anomaly power in an optical fiber link, comprising:

[0013] Determine the initial parameters; wherein, the initial parameters include: the first stage step Δz1, the first stage scanning range R1, the Mth stage step Δz M and the preset number of stages M;

[0014] In the first phase scanning range R1, monitoring points are deployed with the first phase step size Δz1. The anomaly positioning results of the first phase are determined based on the power profile estimation (PPE) algorithm through the deployed monitoring points.

[0015] Based on the anomaly localization results of the first stage, the strategy of reducing the step size and scanning range in each stage is adopted, and the anomaly localization is performed based on the PPE algorithm in each stage until the anomaly localization results of the M-1 stage are obtained;

[0016] Based on the abnormal location results of the M-1 stage, the scanning range R in the M stage M Inside, with Δz M Deploy monitoring points and determine the final anomaly location results based on the PPE algorithm through the deployed monitoring points.

[0017] Furthermore, the value of Δz1 is L / 2, where L is the length of a single span; and the value of R1 is the entire link range.

[0018] Furthermore, Δz M The value of matches the expected anomaly location accuracy.

[0019] Furthermore, based on the anomaly localization results of the first stage, the strategy of reducing the step size and scanning range in each stage is adopted, and the anomaly localization is performed based on the PPE algorithm in each stage until the anomaly localization results of the M-1 stage are obtained, including:

[0020] Based on the abnormal positioning results and step size of the i-1 stage, determine the scanning range R of the i stage i and the step length Δz of stage i i ; Among them, i=2,3,...,M-1; Δz1>Δz2>...>Δz M ; R i =[P i-1 -Δz i-1 ,P i-1 +Δz i-1 ]; among them, P i-1 is the abnormality positioning result of the i-1th stage; Δz i-1 is the step length of the i-1th stage;

[0021] In the i-th stage, the scanning range R i Within, with the step size Δz of stage i i Deploy monitoring points and determine the anomaly location results of the i-th stage based on the power profile estimation (PPE) algorithm through the deployed monitoring points.

[0022] Furthermore, the step length Δz in stage i is i The method of determining is:

[0023] Calculate the functional relationship between the overall computational complexity of the algorithm and the step length of the i-th stage to obtain the function curve;

[0024] Screening a spatial step length that is divisible by the scanning range of the i-th stage on the function curve as a candidate step length;

[0025] A spatial step length that minimizes the overall computational complexity of the algorithm is selected from the candidate step lengths as the step length value of the i-th stage.

[0026] On the other hand, the present invention also provides a non-intrusive optical fiber link power anomaly locating system, comprising:

[0027] Initialization module, used to determine the initial parameters; wherein, the initial parameters include: the first stage step Δz1, the first stage scanning range R1, the Mth stage step Δz M and the preset number of stages M;

[0028] The coarse positioning module is used to deploy monitoring points within the first-stage scanning range R1 with a first-stage step size Δz1, and determine the first-stage anomaly positioning results based on the power profile estimation (PPE) algorithm through the deployed monitoring points;

[0029] The focus optimization module is used to locate anomalies based on the anomaly localization results of the first stage, adopting a strategy of reducing the step size and scanning range stage by stage, and performing anomaly localization based on the PPE algorithm stage by stage until the anomaly localization results of the M-1 stage are obtained;

[0030] The precise positioning module is used to locate the abnormality in the M-1 stage based on the scanning range R in the M stage. M Inside, with Δz M Deploy monitoring points and determine the final anomaly location results based on the PPE algorithm through the deployed monitoring points.

[0031] Furthermore, the value of Δz1 is L / 2, where L is the length of a single span; and the value of R1 is the entire link range.

[0032] Furthermore, Δz M The value of matches the expected anomaly location accuracy.

[0033] Furthermore, the focus optimization module is specifically used to:

[0034] Based on the abnormal positioning results and step size of the i-1 stage, determine the scanning range R of the i stage i and the step length Δz of stage i i ; Among them, i=2,3,...,M-1; Δz1>Δz2>...>Δz M ; R i =[P i-1 -Δz i-1 ,P i-1 +Δz i-1 ]; among them, P i-1 is the abnormality positioning result of the i-1th stage; Δz i-1 is the step length of the i-1th stage;

[0035] In the i-th stage, the scanning range R i Within, with the step size Δz of stage i i Deploy monitoring points and determine the anomaly location results of the i-th stage based on the power profile estimation (PPE) algorithm through the deployed monitoring points.

[0036] Furthermore, the step length Δz in stage i is i The method of determining is:

[0037] Calculate the functional relationship between the overall computational complexity of the algorithm and the step length of the i-th stage to obtain the function curve;

[0038] Screening a spatial step length that is divisible by the scanning range of the i-th stage on the function curve as a candidate step length;

[0039] A spatial step length that minimizes the overall computational complexity of the algorithm is selected from the candidate step lengths as the step length value of the i-th stage.

[0040] On the other hand, the present invention further provides an electronic device, comprising a processor and a memory; wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the above method.

[0041] In yet another aspect, the present invention further provides a computer-readable storage medium, wherein the storage medium stores at least one instruction, and the instruction is loaded and executed by a processor to implement the above method.

[0042] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0043] The present invention deploys monitoring points within the first stage scanning range R1 with the first stage step size Δz1, and determines the first stage abnormality positioning result based on the power profile estimation PPE algorithm; based on the abnormality positioning result of the first stage, adopts the strategy of reducing the step size and scanning range step by step, and performs abnormality positioning based on the PPE algorithm step by step until the abnormality positioning result of the M-1 stage is obtained; based on the abnormality positioning result of the M-1 stage, the abnormality positioning result of the M stage scanning range R1 is obtained. M Inside, with Δz M Deploy monitoring points and determine the final anomaly location results. By gradually reducing the step size and scanning range, the algorithm significantly reduces the computational complexity while maintaining the accuracy of traditional anomaly location methods, achieving high-precision positioning with limited computing resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 It is the PPE algorithm flow chart;

[0046] Figure 2 Yes ref (z), γ mon (z), γ dif (z), Δγ dif (z) Graphical representation of a 240 km link; where (a) is the PPE output γ ref (z) and γ mon (z); (b) is the difference curve γ dif (z); (c) is the abnormal location indicator Δγ dif (z);

[0047] Figure 3This is a flow chart of a non-invasive optical fiber link power anomaly locating method provided by an embodiment of the present invention;

[0048] Figure 4 is a simulation system diagram provided by an embodiment of the present invention;

[0049] Figure 5 Schematic diagram of selecting the optimal Δz2 provided by an embodiment of the present invention;

[0050] Figure 6 is the Δγ obtained in the first stage provided by the embodiment of the present invention dif (z) Schematic diagram;

[0051] Figure 7 is the Δγ obtained in the second stage provided by the embodiment of the present invention dif (z) Schematic diagram;

[0052] Figure 8 is the Δγ obtained in the third stage provided by the embodiment of the present invention dif (z) Schematic diagram;

[0053] Figure 9 is the complexity optimization rate R in the N*L link provided by the embodiment of the present invention opt Schematic diagram;

[0054] Figure 10 is the different Δz provided by the embodiment of the present invention M Schematic diagram of the optimal complexity saving rate under L;

[0055] Figure 11 This is a system block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0057] First, it should be noted that in the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "exemplarily" is intended to present concepts in a concrete manner. In addition, in the embodiments of the present invention, the meaning of "and / or" can be both or either of the two.

[0058] First embodiment

[0059] This embodiment provides a non-invasive method for locating optical fiber link power anomalies. The method can be implemented by an electronic device, which can be a terminal or a server. The method includes the following steps:

[0060] S1, determine the initial parameters; wherein, the initial parameters include: the first stage step Δz1, the first stage scanning range R1, the Mth stage step Δz M and the preset number of stages M;

[0061] It should be noted that in order to ensure that the information of each span of the link is fully obtained without missing any information and to save computing resources as much as possible, for the N*L link scenario, the value of Δz1 should be selected as L / 2, and the value of R1 should be the entire link range. M The value should be determined by the expected anomaly positioning accuracy. For example, if the expected anomaly positioning accuracy is within 1 km, then Δz M It should be set to 1km.

[0062] S2, within the first-stage scanning range R1, monitoring points are deployed with the first-stage step size Δz1. The anomaly location results of the first stage are determined based on the power profile estimation (PPE) algorithm through the deployed monitoring points;

[0063] It should be noted that this step is a rough positioning process. In this step, the algorithm consists of a stage, using a larger step size to scan the entire link. By deploying relatively dispersed monitoring points across the entire link range, the approximate location range of the anomaly can be quickly determined with low computing resources, thus providing a basis for subsequent precise positioning. Specifically, the algorithm will deploy monitoring points with a step size of Δz1 across the entire link range to calculate γ mon (z), and with γ ref (z) Get the positioning curve Δγ dif (z) Using the 3σ criterion, an alarm threshold is established. If this threshold is exceeded, the approximate location of the anomaly, P1, can be preliminarily determined, providing a basis for focused optimization in subsequent stages. In actual monitoring deployments, this process can be performed periodically to complete the monitoring task.

[0064] S3, based on the anomaly localization results of the first stage, adopt the strategy of reducing the step size and scanning range stage by stage, and perform anomaly localization based on the PPE algorithm stage by stage until the anomaly localization results of the M-1 stage are obtained;

[0065] It should be noted that this step is the focus optimization process, assuming Δz i (i=1,2,3,...,M) is the step size of the i-th stage, and satisfies Δz1>Δz2>…>Δz M ,P i(i=1,2,3,...,M) is the positioning result obtained in the i-th stage, then the scanning range R of the i-th stage is i (i=1,2,3,...,M) can be defined as:

[0066] R i =[P i-1 -Δz i-1 ,P i-1 +Δz i-1 ]#(3)

[0067] According to the scanning range defined by formula (3), the algorithm can narrow the scanning interval in each stage according to the positioning results obtained in the previous stage, thereby concentrating limited computing resources near the abnormal position and achieving high-precision positioning. In this step, the algorithm further focuses on the abnormal position based on the positioning results obtained in the first stage to optimize the overall algorithm complexity. Specifically, this step contains (M-2) sub-stages, in which the step size gradually decreases and the scanning range continues to shrink. At the end of this step, the (M-1) stage uses Δz M-1 Scanning range R M-1 , and obtain P M-1 Δz i (i=2,3,…,M-1) should be determined in Δz1, Δz M After and M, a global optimization selection is made based on the overall complexity of the algorithm. The details are as follows:

[0068] Assume that the length of the link is L×N (where L is the length of a single span and N is the number of spans). Assume that the complexity of stage i is O i (i=1,2,3). Since the monitoring method used is based on a loop structure, to simplify the analysis, we assume that C represents the complexity of each iteration of the PPE algorithm. Based on this assumption, we can further analyze the execution of the algorithm at each stage as follows:

[0069] 1 st -stage: The length of the scanning range R1 in this stage is L×N, Δz1=L / 2, and the complexity of this stage is O1=(2N+1)×C.

[0070] 2 nd -stage: The length of the scanning range R2 in this stage is L, the step length taken is Δz2, and the complexity of this stage is O2 = (L / Δz2+2)×C.

[0071] M th -stage: Scan range R at this stage M =2×Δz M-1 , the complexity of this stage

[0072] After mathematical induction, for any M, we can get the overall complexity of the algorithm O total ,have:

[0073]

[0074] From formula (4), we can see that minimizing O total The step size Δz of the second stage is selected i (i=2,3,…,M-1) is independent of the linear term N and the constant C. For different values of M, we can always use the ergodic method to select the corresponding R i Δz that is divisible by (i=2,3,…,M-1) i (i=2,3,…,M-1) to minimize the overall complexity O total , specifically, by (2Δz i-1 / Δz i ) is an integer, Δz1>Δz2>…>Δz M These two conditions, combined with the set Δz1, Δz M , traverse to obtain multiple possible Δz i (i=2,3,…,M-1) as candidates, and then from the obtained several candidates Δz i (i=2, 3, ..., M-1), the overall complexity O of the multi-stage anomaly localization method proposed in this embodiment is determined by formula (4): total Lowest Δz i (i=2,3,…,M-1).

[0075] S4, based on the abnormality positioning results of the M-1 stage, scan the range R in the M stage M Inside, with Δz M Deploy monitoring points and determine the final anomaly location results based on the PPE algorithm through the deployed monitoring points.

[0076] It should be noted that this step is a precise positioning process. In this step, based on the focus optimization result P obtained in the previous step, M-1 , the algorithm will further narrow the scanning range to R M , using the smallest step size Δz M Deploy monitoring points to achieve accurate positioning of anomalies. The purpose of this stage is to achieve the final accurate positioning of anomalies with a controllable step size, Δz M The selection of should be determined by the expected abnormal positioning accuracy. For example, if the expected positioning accuracy is within 1km, then Δz M Should be set to 1km. M Nearby Δz MDeploy monitoring points for the step length and obtain the final precise positioning result P M .

[0077] Next, an actual case is used to verify the effect of the method of the present invention.

[0078] In this embodiment, a 3dB power attenuation error is inserted at 10.255km starting from the 8th span in a link with a length of 80km / span*15 spans. After passing through a coherent receiver and digital signal processing, the proposed multi-step PPE locates the anomaly in the link. The γ ref (z) should be trained in advance and stored in memory, and the final positioning result P should be output. M , the simulation system diagram is as follows Figure 4 shown.

[0079] Specific implementation of the algorithm and the abnormal location indicator Δγ obtained in each step dif (z) The results are as follows:

[0080] 1. Determine the initial parameters:

[0081] According to the link background, it can be determined Set z M =0.005km, M=3, the overall computational complexity O can be obtained according to formula (4): total The functional relationship with Δz2 is as follows Figure 5 shown.

[0082] First, select the spatial step Δz2 that can be divided by R2 from this curve, and then select the spatial step that makes O total The minimum optimal spatial step size Δz2 = 0.5 km.

[0083] 2. Rough positioning

[0084] For the range R1 = [0km, 1200km], deploy γ with Δz1 = 40km mon At the monitoring point (z), perform the operations of equations (1) and (2) to obtain the abnormal location indicator Δγ of this stage dif (z) Figure 6 shown.

[0085] The anomaly location indicator Δγ obtained from the first stage dif (z), it can be determined that the abnormal positioning result of the first stage is P1 = 600 km.

[0086] 3. Focus on optimization

[0087] From the P1 obtained in the previous stage, combined with Δz1 = 40km, the scanning range of the second stage can be obtained as R2 = [560km, 640km] through formula (3). Monitoring points are deployed in this range with Δz2 = 0.5km, and the operations of formulas (1) and (2) are performed to obtain Δγ of this stage. dif (z) Figure 7 shown.

[0088] Δγ obtained from the second stage dif (z), it can be determined that the abnormal positioning result of the second stage is P2 = 570.5 km.

[0089] 4. Accurate positioning

[0090] From the P1 obtained in the previous stage, combined with Δz2 = 0.5 km, the scanning range of the second stage can be obtained as R3 = [570 km, 571 km] through formula (3). Monitoring points are deployed in this range with Δz3 = 0.005 km, and the operations of formulas (1) and (2) are performed to obtain Δγ of this stage. dif (z) Figure 8 shown.

[0091] The Δγ obtained from this stage dif (z), the final anomaly positioning result P3 = 570.22 km can be determined.

[0092] Substituting N = 15, L = 80 km, M = 3, Δz2 = 0.5 km and Δz3 = 0.005 km into formula (4), we can obtain that in this scenario, the theoretical complexity of the multi-stage PPE method proposed in this embodiment is 395C. The traditional positioning method requires a complexity of 240001C to scan the entire link range with a step size of 0.005 km. By comparison, it can be seen that the multi-stage method saves 99.84% of the computational complexity in this case. In addition, since the method uses a pre-set step size Δz in the final stage, the computational complexity of the multi-stage PPE method is 240001C. M The traditional positioning method is performed in a local area, so the positioning accuracy of the traditional method can be maintained.

[0093] Assume the complexity of this multi-step method is O total , assuming Δz M The complexity of the traditional positioning method with the step size (same accuracy) is O trad , we define the complexity saving rate as:

[0094]

[0095] In links with different N*L (N is the number of spans, L is the length of each span) configurations, when M=3 and Δz3=0.005km, this method has a good complexity saving effect, such as Figure 9 shown.

[0096] For different M, increasing M to a certain extent can increase the operation space of "focus optimization" to further save complexity. However, increasing M too much may also make "focus optimization" too complicated, which will increase the complexity of the algorithm. Therefore, in the variables L and Δz M Under certain circumstances, we can obtain the optimal M with the lowest complexity reduction effect under the corresponding circumstances, and the optimal complexity reduction effect under different circumstances can be obtained as follows Figure 10 shown.

[0097] From the above analysis, it can be seen that the method provided by the present invention has a good complexity saving effect in different link environments through a strategy of gradually narrowing the scanning range by combining multiple stages and large and small steps.

[0098] Second embodiment

[0099] This embodiment provides a non-intrusive optical fiber link power anomaly location system, including the following modules:

[0100] Initialization module, used to determine the initial parameters; wherein, the initial parameters include: the first stage step Δz1, the first stage scanning range R1, the Mth stage step Δz M and the preset number of stages M;

[0101] The coarse positioning module is used to deploy monitoring points within the first-stage scanning range R1 with a first-stage step size Δz1, and determine the first-stage anomaly positioning results based on the power profile estimation (PPE) algorithm through the deployed monitoring points;

[0102] The focus optimization module is used to locate anomalies based on the anomaly localization results of the first stage, adopting a strategy of reducing the step size and scanning range stage by stage, and performing anomaly localization based on the PPE algorithm stage by stage until the anomaly localization results of the M-1 stage are obtained;

[0103] The precise positioning module is used to locate the abnormality in the M-1 stage based on the scanning range R in the M stage. M Inside, with Δz M Deploy monitoring points and determine the final anomaly location results based on the PPE algorithm through the deployed monitoring points.

[0104] Among them, it should be noted that the non-invasive optical fiber link power anomaly locating system of this embodiment corresponds to the non-invasive optical fiber link power anomaly locating method of the above-mentioned first embodiment; among them, the functions implemented by each functional module in the non-invasive optical fiber link power anomaly locating system of this embodiment correspond one-to-one to each process step in the above-mentioned non-invasive optical fiber link power anomaly locating method; therefore, they will not be repeated here.

[0105] Third embodiment

[0106] This embodiment provides an electronic device, such as Figure 11 As shown, the electronic device includes: a processor and a memory; wherein the processor and the memory can be connected via a communication bus; the memory stores at least one instruction, which is loaded and executed by the processor to implement the method of the first embodiment described above. In addition, the electronic device may also include a transceiver; the processor and the transceiver can be connected via a communication bus, and the transceiver is used to communicate with other devices.

[0107] Next, combine Figure 11 A detailed introduction to the various components of the electronic device is given below:

[0108] Among them, the processor is the control center of the electronic device, and the electronic device may include multiple processors, each of which may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here can be a processor or a general term for multiple processing elements. For example, the processor is one or more central processing units (CPUs), or other general-purpose processors, application specific integrated circuits (ASICs), or one or more integrated circuits configured to implement an embodiment of the present invention, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor can perform various functions of the electronic device by running or executing software programs stored in the memory and calling data stored in the memory.

[0109] In a specific implementation, as an embodiment, the processor may include one or more CPUs, such as Figure 11 The CPU0 and CPU1 shown in FIG are, of course, only exemplary.

[0110] The memory is used to store the software program for executing the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can refer to the above method embodiment and will not be repeated here.

[0111] Optionally, the memory may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory may be integrated with the processor or exist independently and accessed through the interface circuit ( Figure 11 (not shown) is coupled to the processor, which is not specifically limited in this embodiment of the present invention.

[0112] The transceiver may include a receiver and a transmitter ( Figure 11 The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function. The transceiver can be integrated with the processor or exist independently and communicate with the electronic device through the interface circuit ( Figure 11 (not shown) is coupled to the processor, which is not specifically limited in this embodiment of the present invention.

[0113] In addition, it should be noted that Figure 11 The structure of the electronic device shown in the figure does not constitute a limitation on the device. The actual device may include more or fewer components than shown, or may combine certain components, or arrange the components differently. In addition, the technical effects achieved by the electronic device when executing the method of the first embodiment can refer to the technical effects described in the first embodiment above, and therefore will not be repeated here.

[0114] Fourth embodiment

[0115] This embodiment provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement the method of the first embodiment described above. The computer-readable storage medium may be a ROM, random access memory, CD-ROM, magnetic tape, floppy disk, or optical data storage device. The instructions stored therein can be loaded by a processor in a terminal to execute the method described above.

[0116] Furthermore, it should be noted that the present invention may be provided as a method, apparatus, or computer program product. Therefore, embodiments of the present invention may take the form of a fully or partially hardware embodiment, a fully or partially software embodiment, or an embodiment combining software and hardware aspects. Furthermore, when implemented using software, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present invention are fully or partially generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired connection (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium. The semiconductor medium may be a solid state drive.

[0117] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0119] It should also be noted that, in this document, relational terms such as first and second are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any actual relationship or order between these entities or operations. The terms "include," "comprises," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or terminal device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. Without further limitation, an element defined by the phrase "comprising a..." does not preclude the presence of other identical elements in the process, method, article, or terminal device comprising the element. In addition, the term "and / or" is merely a description of an associative relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: the presence of A alone, the presence of A and B simultaneously, or the presence of B alone, where A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding. "At least one" means one or more, and "more" means two or more. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0120] In addition, it can be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0121] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0122] In the several embodiments provided herein, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of functional modules / units is merely a logical functional division. In actual implementation, other division methods may be used, such as multiple units or components being combined or integrated into another device, or some features being ignored or not implemented. Furthermore, the coupling or direct coupling or communication connection shown or discussed between each other may be through some interface, indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of the present embodiment according to actual needs. In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0123] If the method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0124] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention. It should be noted that, although preferred embodiments of the present invention have been described, those skilled in the art, once understanding the basic inventive concepts of the present invention, may make various improvements and modifications without departing from the principles of the present invention. Such improvements and modifications should also be considered within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as covering the preferred embodiments and all variations and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A non-invasive optical fiber link power anomaly location method, characterized in that: include: Determine the initial parameters; wherein, the initial parameters include: the first stage step Δz1, the first stage scanning range R1, the Mth stage step Δz M and the preset number of stages M; In the first phase scanning range R1, monitoring points are deployed with the first phase step size Δz1. The anomaly positioning results of the first phase are determined based on the power profile estimation (PPE) algorithm through the deployed monitoring points. Based on the anomaly localization results of the first stage, the strategy of reducing the step size and scanning range in each stage is adopted, and the anomaly localization is performed based on the PPE algorithm in each stage until the anomaly localization results of the M-1 stage are obtained; Based on the abnormal location results of the M-1 stage, the scanning range R in the M stage M Inside, with Δz M Deploy monitoring points and determine the final anomaly location results based on the PPE algorithm through the deployed monitoring points.

2. The non-invasive optical fiber link power anomaly locating method according to claim 1, wherein: The value of Δz1 is L / 2, where L is the length of a single span; the value of R1 is the entire link range.

3. The non-invasive optical fiber link power anomaly locating method according to claim 1, wherein: Δz M The value of matches the expected anomaly location accuracy.

4. The non-invasive optical fiber link power anomaly locating method according to claim 1, wherein: Based on the anomaly localization results of the first phase, the strategy of gradually reducing the step size and scanning range is adopted, and anomaly localization is performed based on the PPE algorithm step by step until the anomaly localization results of the M-1 phase are obtained, including: Based on the abnormal positioning results and step size of the i-1 stage, determine the scanning range R of the i stage i and the step length Δz of stage i i ; Among them, i=2,3,...,M-1; Δz1>Δz2>...>Δz M ; R i =[P i-1 -Δz i-1 ,P i-1 +Δz i-1 ]; among them, P i-1 is the abnormality positioning result of the i-1th stage; Δz i-1 is the step length of the i-1th stage; In the i-th stage, the scanning range R i Within, with the step size Δz of stage i i Deploy monitoring points and determine the anomaly location results of the i-th stage based on the power profile estimation (PPE) algorithm through the deployed monitoring points.

5. The non-invasive optical fiber link power anomaly locating method according to claim 4, wherein: The step length Δz of stage i i The method of determining is: Calculate the functional relationship between the overall computational complexity of the algorithm and the step length of the i-th stage to obtain the function curve; Screening a spatial step length that is divisible by the scanning range of the i-th stage on the function curve as a candidate step length; A spatial step length that minimizes the overall computational complexity of the algorithm is selected from the candidate step lengths as the step length value of the i-th stage.

6. A non-intrusive optical fiber link power anomaly positioning system, characterized in that: include: Initialization module, used to determine the initial parameters; wherein, the initial parameters include: the first stage step Δz1, the first stage scanning range R1, the Mth stage step Δz M and the preset number of stages M; The coarse positioning module is used to deploy monitoring points within the first-stage scanning range R1 with a first-stage step size Δz1, and determine the first-stage anomaly positioning results based on the power profile estimation (PPE) algorithm through the deployed monitoring points; The focus optimization module is used to locate anomalies based on the anomaly localization results of the first stage, adopting a strategy of reducing the step size and scanning range stage by stage, and performing anomaly localization based on the PPE algorithm stage by stage until the anomaly localization results of the M-1 stage are obtained; The precise positioning module is used to locate the abnormality in the M-1 stage based on the scanning range R in the M stage. M Inside, with Δz M Deploy monitoring points and determine the final anomaly location results based on the PPE algorithm through the deployed monitoring points.

7. The non-intrusive optical fiber link power anomaly locating system according to claim 6, characterized in that: The value of Δz1 is L / 2, where L is the length of a single span; the value of R1 is the entire link range.

8. The non-intrusive optical fiber link power anomaly locating system according to claim 6, wherein: Δz M The value of matches the expected anomaly location accuracy.

9. The non-intrusive optical fiber link power anomaly locating system according to claim 6, wherein: The focus optimization module is specifically used for: Based on the abnormal positioning results and step size of the i-1 stage, determine the scanning range R of the i stage i and the step length Δz of stage i i ; Among them, i=2,3,...,M-1; Δz1>Δz2>...>Δz M ; R i =[P i-1 -Δz i-1 ,P i-1 +Δz i-1 ]; among them, P i-1 is the abnormality positioning result of the i-1th stage; Δz i-1 is the step length of the i-1th stage; In the i-th stage, the scanning range R i Within, with the step size Δz of stage i i Deploy monitoring points and determine the anomaly location results of the i-th stage based on the power profile estimation (PPE) algorithm through the deployed monitoring points.

10. The non-intrusive optical fiber link power anomaly locating system according to claim 9, characterized in that: The step length Δz of stage i i The method of determining is: Calculate the functional relationship between the overall computational complexity of the algorithm and the step length of the i-th stage to obtain the function curve; Screening a spatial step length that is divisible by the scanning range of the i-th stage on the function curve as a candidate step length; A spatial step length that minimizes the overall computational complexity of the algorithm is selected from the candidate step lengths as the step length value of the i-th stage.

Images