An AI-based fiber optic equipment lifecycle monitoring system and method

Abstract

This invention discloses an artificial intelligence-based fiber optic equipment lifecycle monitoring system and method, relating to the field of artificial intelligence technology. The system includes: acquiring monitoring information records; determining whether a monitoring information record is a record to be detected; if the monitoring information record is a record to be detected, obtaining the reference transmission distance in the record to be detected, and obtaining a reference distance segment based on all reference transmission distances; obtaining the distance segment to be detected based on the reference distance segment, and determining the first abnormal distance and the second abnormal distance within the distance segment to be detected; obtaining a deviation coefficient based on the reference transmission distance, the first abnormal distance, and the second abnormal distance, and obtaining the aging degree coefficient of the target fiber optic equipment, and then performing different processing. This invention, by determining the aging degree of the fiber optic equipment, allows for the replacement or repair of aging fiber optic equipment, thereby improving the accuracy of fault location and ensuring the reliability of data monitoring of the fiber optic equipment.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, specifically to an artificial intelligence-based fiber optic equipment lifecycle monitoring system and method. Background Technology

[0002] An optical time domain reflectometer (OTDR) is a fiber optic device used to test the characteristics of optical communication networks. It is primarily used to detect, locate, and measure events at any point in a fiber optic link, playing a crucial role in ensuring the stable operation of communication systems and providing strong data support for locating faults. The laser in an OTDR is the key component that emits optical pulses, while the photodetector receives backscattered light (Rayleigh scattering) and reflected light signals (Fresnel reflection) and converts them into electrical signals. The basic principle of the laser and photodetector working together is that the laser emits a high-energy laser beam according to preset parameters such as wavelength, pulse width, and power, and then the photodetector detects changes in the beam to obtain information.

[0003] If a laser ages, its output optical power becomes unstable, leading to uneven energy distribution in some emitted optical pulses. This degrades the photodetector's response to optical signals, potentially causing the loss of some optical signal details during measurement, resulting in incomplete data, missing or abnormal data, and affecting the detection of minor fiber optic losses and short-distance fault points. Therefore, it is necessary to analyze this data, determine the degree of laser aging based on the missing or abnormal signals, and replace or repair the aging laser to improve fault location accuracy and ensure the reliability of data monitoring. Summary of the Invention

[0004] The purpose of this invention is to provide an artificial intelligence-based fiber optic equipment lifecycle monitoring system and method to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An artificial intelligence-based method for monitoring the lifecycle of fiber optic equipment includes the following steps:

[0007] Step S100: Obtain monitoring information records, extract the changes in characteristic parameters of the laser in the test optical fiber with transmission distance from the monitoring information records, and determine whether the monitoring information records are records to be detected;

[0008] Step S200: If the monitoring information record is the record to be detected, obtain all the reference transmission distances based on the data changes of the feature parameters with the transmission distance, and obtain all the reference distance segments based on the reference transmission distances;

[0009] Step S300: Take the distance between any two adjacent reference distance segments as the distance segment to be detected, and determine the first abnormal distance and the second abnormal distance in the distance segment to be detected based on the characteristic parameters of each transmission distance in the distance segment to be detected.

[0010] Step S400: Based on the reference transmission distance, the first abnormal distance, and the second abnormal distance, obtain the deviation coefficient corresponding to the record to be detected. Based on the deviation coefficient, obtain the aging degree coefficient of the target optical fiber device, and perform different processing on the target optical fiber device according to the aging degree coefficient.

[0011] Furthermore, step S100 includes:

[0012] Step S110: Acquire the monitoring information records corresponding to the target fiber optic device and the reference fiber optic device respectively. The monitoring information record is the information record of data monitoring during the process of the fiber optic device emitting laser into the test fiber with the emission point in the test fiber as the starting point. The monitoring information record of the reference fiber optic device is used as the reference information record, and the monitoring information record of the target fiber optic device is used as the target information record. Before emitting the laser, the parameter information of the laser emission of the two fiber optic devices is set to be consistent. The parameter information includes angle, wavelength, pulse width and power.

[0013] Feature parameters corresponding to each transmission distance are extracted from the baseline information record and the target information record respectively. The feature parameters include luminous intensity and wavelength. A function graph of luminous intensity changing with transmission distance is established, and the first broken line corresponding to the baseline information record and the second broken line corresponding to the target information record are plotted in the function graph.

[0014] It should be noted that the angle, wavelength, pulse width, and power need to be set to be consistent here because: the angle determines the direction of laser emission; different wavelengths of light have different transmission characteristics in optical fibers, and different wavelengths have different transmission scenarios; the pulse width determines the duration of the light pulse, and different pulse widths have different energies; the emission power directly affects the energy of the light pulse transmitted in the optical fiber, and sufficient power can ensure that the light pulse can be transmitted a long enough distance in the optical fiber and generate a detectable signal strength when it encounters reflection or scattering points.

[0015] The difference between backscattered light (Rayleigh scattering) and reflected light (Fresnel reflection) lies in the following: Rayleigh scattering is caused by minute inhomogeneities within the fiber material (such as microscopic fluctuations in density and refractive index). As light propagates through the fiber, it interacts with these microscopic inhomogeneities, causing the light to scatter in various directions. Some of this scattered light propagates back along the fiber and is detected. Fresnel reflection, on the other hand, occurs when light travels from one medium to another with a different refractive index, and reflection occurs at the interface between the two media, such as at the fiber's endpoint (the interface between the fiber and air) or at points of abrupt change in refractive index within the fiber. Therefore, the test fiber used in this scheme is a crease-free and break-free fiber, ensuring that the received signal is Rayleigh scattering.

[0016] Step S120: Randomly obtain several location points in the test fiber, and ensure that the transmission distance between two adjacent location points in the test fiber is not less than a preset distance threshold, and use all location points as calibration points.

[0017] Randomly select any two locations a and b in the test fiber. Add the transmission distance between a calibration point and a to the transmission distance between a calibration point and b to obtain the comprehensive distance of the calibration point. Obtain the comprehensive distance of each calibration point. Select the calibration point with the smallest comprehensive distance as F. Extract the coordinate point P corresponding to calibration point F in the first broken line.

[0018] N detection points are randomly selected from points a and b, and the detection coordinates of each detection point in the second broken line are obtained. Then, in the function relationship graph, with coordinate point P as the starting point and each detection coordinate point as the ending point, several coordinate vectors are obtained, and a vector set is established.

[0019] Step S130: If there exists a corresponding vector in the vector set that does not satisfy... If the target information record is determined to be the record to be detected, then r is the ratio threshold, and v k v k+1 and v k+2 Let N be the k-th, k+1-th, and k+2-th coordinate vectors in the vector set, where 1 ≤ k < k+1 < k+2 ≤ N.

[0020] It should be noted that under normal circumstances, the luminous intensity gradually decreases as the transmission distance increases. This process is slow. When there is a sudden change in luminous intensity, it indicates that there is an anomaly in the target information record. The target information record needs to be recorded as a record to be detected and further judgment needs to be made.

[0021] Furthermore, step S200 includes:

[0022] Step S210: Perform a first marking on the transmission distances corresponding to the coordinate points where the first broken line and the second broken line intersect in the function relationship diagram. Perform a second marking on the transmission distances with the same wavelength in the reference information record and the target information record. Take the transmission distances that are marked with both the first marking and the second marking as the reference transmission distances;

[0023] Respectively obtain a reference transmission distance g and an adjacent transmission distance h that is not a reference transmission distance in the reference information record. Take the coordinate points corresponding to g and h in the first broken line as P g and P h . Take the length between P g and P h as Lg h. Take the area in the function relationship diagram with the coordinate point P g as the center and k * Lg h as the radius as the characteristic area, where k is the area coefficient and k ≥ 1;

[0024] Step S220: If the transmission distance h is marked with the second marking and the coordinate point corresponding to h in the second broken line is within the characteristic area, then take h as the reference transmission distance; further, according to Step S200, obtain all the reference transmission distances, and gather all adjacent reference transmission distances as a reference distance segment to obtain all the reference distance segments.

[0025] Further, Step S300 includes:

[0026] Step S310: Obtain two adjacent reference distance segments A and B. Take the maximum transmission distance in A as X1 and the minimum transmission distance in B as X2, and X1 < X2; Take the distance segment between X1 and X2 as the to-be-detected distance segment C;

[0027] Evenly divide the to-be-detected distance segment C into M sub-distance segments. Obtain the curve corresponding to each sub-distance segment in the first broken line, and according to the coordinate points at both ends of each curve, obtain the slope corresponding to each curve, and calculate the variance of all the slopes. Take the variance as the distance coefficient Y corresponding to the to-be-detected distance segment C;

[0028] Step S320: Take the curve corresponding to the to-be-detected distance segment C in the first broken line as the reference curve. Take the range with a length of K Y *Y*e -|R-X| on both sides perpendicular to the tangent line at each coordinate point on the reference curve as the reference area, where K Y is the preset area coefficient, R is the transmission distance in the middle of the to-be-detected distance segment C, and X is a certain transmission distance between X1 and X2;

[0029] If the coordinate point corresponding to a certain transmission distance in the distance segment C to be detected is within the reference area in the second broken line, the transmission distance is taken as the first abnormal distance; if it is not within the reference area, the transmission distance is taken as the second abnormal distance, and so on, thus obtaining all the first and second abnormal distances.

[0030] If the slope values ​​of each sub-distance segment differ significantly, it indicates that the difference in luminous intensity corresponding to each sub-distance segment in the detection distance segment C is greater. In this scheme, the distance coefficient is used to characterize the difference value, and the variance is used to characterize the magnitude of the difference value. The larger the variance, the greater the difference value. And the greater this difference value, the larger the distance coefficient, and thus the larger the range of the reference area should be. The size of the reference area directly affects the judgment of the first abnormal distance and the second abnormal distance.

[0031] The transmission distance of the first abnormal distance is a value with a smaller deviation, and the transmission distance of the second abnormal distance is a value with a larger deviation. Since the reference area is the main influencing factor in determining the first and second abnormal distances, and since the luminous intensity represents the signal energy intensity received at a certain transmission distance, a sudden change in luminous intensity is an abnormal phenomenon. Therefore, the reference area should be set in a pattern where the reference area range is smaller when close to X1 and X2, and larger when close to R. X is a certain transmission distance between X1 and X2. The smaller |RX| is, the closer the value of RX is to 0, indicating that X is closer to R, and the reference area range is larger at this time. The function y=e -x Since a smaller x-axis corresponds to a larger y-axis, e is used in this scheme. -|R-X| To carry out the design.

[0032] Furthermore, step S400 includes:

[0033] Step S410: Obtain the distance segments corresponding to the baseline transmission distance, the first abnormal distance, and the second abnormal distance in the target information record, respectively. The lengths of each distance segment are S0, S1, and S2, respectively. Add them together to obtain S. sum Remove S from S0, S1 and S2 um The ratios L0, L1, and L2 are obtained, and the weights of the baseline transmission distance, the first abnormal distance, and the second abnormal distance are set to W0, W1, and W2, respectively, with W1 + W2 = 1 and W2 > W1 > 0 > W0.

[0034] Based on the ratio and weight, the deviation coefficient Z of the record to be detected is obtained, and the formula is: k Z To adjust the coefficient, k Z >1, e is the natural index, when Z<0, let Z=0;

[0035] Step S420: Obtain T records to be monitored by the target fiber optic device, and sort the records according to the chronological order of data monitoring, where the weight of the t-th record is W. t =t / ∑T d=1d; Calculate the deviation coefficient for each record to be tested. Based on the weight and deviation coefficient of each record to be tested, obtain the aging coefficient of the target fiber optic equipment Q=∑T t=1Z. t *W t Z t Let W be the deviation coefficient of the t-th record to be detected. t Let t be the weight of the t-th record to be detected.

[0036] An artificial intelligence-based fiber optic equipment lifecycle monitoring system includes a record to be detected judgment module, a reference distance segment determination module, an abnormal distance type classification module, and an aging degree coefficient calculation module.

[0037] The module for judging the record to be tested is used to acquire monitoring information records, extract the changes of characteristic parameters of the laser in the test optical fiber with the transmission distance, and determine whether the monitoring information record is a record to be tested.

[0038] Reference distance segment determination module: If the monitoring information record is a record to be detected, the reference distance segment determination module is used to obtain all reference transmission distances based on the data changes of characteristic parameters with transmission distance, and to obtain all reference distance segments among them based on the reference transmission distances;

[0039] Anomaly distance type classification module: used to take the distance between any two adjacent reference distance segments as the distance segment to be detected, and determine the first anomaly distance and the second anomaly distance in the distance segment to be detected based on the characteristic parameters of each transmission distance in the distance segment to be detected;

[0040] Aging degree coefficient calculation module: It is used to obtain the deviation coefficient corresponding to the record to be tested based on the reference transmission distance, the first abnormal distance and the second abnormal distance, obtain the aging degree coefficient of the target optical fiber equipment based on the deviation coefficient, and perform different processing on the target optical fiber equipment according to the aging degree coefficient.

[0041] Furthermore, the detection record judgment module includes a function relationship graph establishment unit, a vector set establishment unit, and a detection record judgment unit;

[0042] Function Relationship Graph Establishment Unit: Used to acquire monitoring information records corresponding to the target fiber optic device and the reference fiber optic device respectively; and obtain the reference information record and the target information record; establish a function relationship graph of the change of light intensity with transmission distance, and draw the first broken line and the second broken line in the function relationship graph;

[0043] Vector set establishment unit: used to obtain calibration points in the test fiber; randomly obtain several detection position points within any two position points in the test fiber, obtain the detection coordinate points corresponding to each detection position point in the second broken line, obtain each vector, and establish a vector set;

[0044] The record to be detected judgment unit is used to determine whether the target information record is a record to be detected based on the vector set.

[0045] Furthermore, the abnormal distance type classification module includes a distance coefficient calculation unit and a distance type classification unit;

[0046] Distance coefficient calculation unit: used to obtain two adjacent reference distance segments, obtain the distance segment to be detected, divide the distance segment to be detected evenly into several sub-distance segments, and obtain the distance coefficient corresponding to the distance segment to be detected;

[0047] Distance type classification unit: used to take the curve corresponding to the distance segment to be detected in the first broken line as the reference curve, obtain the reference area, and determine the first abnormal distance and the second abnormal distance in the distance segment to be detected.

[0048] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention provides an artificial intelligence-based fiber optic equipment lifecycle monitoring system and method, comprising: acquiring monitoring information records; determining whether the monitoring information record is a record to be detected; if the monitoring information record is a record to be detected, obtaining the reference transmission distance in the record to be detected, and obtaining the reference distance segment based on all reference transmission distances; obtaining the distance segment to be detected based on the reference distance segment, and determining the first abnormal distance and the second abnormal distance in the distance segment to be detected; obtaining the deviation coefficient based on the reference transmission distance, the first abnormal distance, and the second abnormal distance, and obtaining the aging degree coefficient of the target fiber optic equipment, and then performing different processing. This invention, by determining the aging degree of the fiber optic equipment, replaces or repairs the aging fiber optic equipment, thereby improving the accuracy of fault location and ensuring the reliability of data monitoring of the fiber optic equipment. Attached Figure Description

[0049] Figure 1 This is a flowchart illustrating an artificial intelligence-based fiber optic equipment lifecycle monitoring method according to the present invention.

[0050] Figure 2 This is a structural diagram of an artificial intelligence-based fiber optic equipment lifecycle monitoring system according to the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Example: Figure 1 As shown, this invention provides a technical solution for a fiber optic equipment lifecycle monitoring system and method based on artificial intelligence, comprising the following steps:

[0053] Step S100: Obtain monitoring information records, extract the characteristic parameters of the laser in the test optical fiber that change with the transmission distance from the monitoring information records, and determine whether the monitoring information records are records to be tested.

[0054] Step S110: Acquire the monitoring information records corresponding to the target fiber optic device and the reference fiber optic device respectively. The monitoring information record is the information record of data monitoring during the process of the fiber optic device emitting laser into the test fiber with the emission point in the test fiber as the starting point. The monitoring information record of the reference fiber optic device is used as the reference information record, and the monitoring information record of the target fiber optic device is used as the target information record. Before emitting the laser, the parameter information of the laser emission of the two fiber optic devices is set to be consistent. The parameter information includes angle, wavelength, pulse width and power.

[0055] Feature parameters corresponding to each transmission distance are extracted from the baseline information record and the target information record respectively. The feature parameters include luminous intensity and wavelength. A function graph of luminous intensity changing with transmission distance is established, and the first broken line corresponding to the baseline information record and the second broken line corresponding to the target information record are plotted in the function graph.

[0056] Step S120: Randomly obtain several location points in the test fiber, and ensure that the transmission distance between two adjacent location points in the test fiber is not less than a preset distance threshold, and use all location points as calibration points.

[0057] Randomly select any two locations a and b in the test fiber. Add the transmission distance between a calibration point and a to the transmission distance between a calibration point and b to obtain the comprehensive distance of the calibration point. Obtain the comprehensive distance of each calibration point. Select the calibration point with the smallest comprehensive distance as F. Extract the coordinate point P corresponding to calibration point F in the first broken line.

[0058] N detection points are randomly selected from points a and b, and the detection coordinates of each detection point in the second broken line are obtained. Then, in the function relationship graph, with coordinate point P as the starting point and each detection coordinate point as the ending point, several coordinate vectors are obtained, and a vector set is established.

[0059] Step S130: If there exists a corresponding vector in the vector set that does not satisfy... If the target information record is determined to be the record to be detected, then r is the ratio threshold, and v k v k+1 and v k+2 Let N be the k-th, k+1-th, and k+2-th coordinate vectors in the vector set, where 1 ≤ k < k+1 < k+2 ≤ N.

[0060] It should be noted that under normal circumstances, the luminous intensity gradually decreases as the transmission distance increases. This process is slow. When there is a sudden change in luminous intensity, it indicates that there is an anomaly in the target information record. The target information record needs to be recorded as a record to be detected and further judgment needs to be made.

[0061] Step S200: If the monitoring information record is the record to be detected, obtain all the reference transmission distances based on the data changes of the characteristic parameters with the transmission distance, and obtain all the reference distance segments based on the reference transmission distances.

[0062] Step S210: Mark the transmission distance corresponding to the coordinate point where the first broken line and the second broken line intersect in the function relationship graph; mark the transmission distance with the same wavelength in the reference information record and the target information record; and take the transmission distance marked with the first and second marks at the same time as the reference transmission distance.

[0063] Obtain the reference transmission distance g and the adjacent non-reference transmission distance h from the reference information record respectively, and take the coordinate points corresponding to g and h in the first polyline as P. g and P h , will P g and P h The length between them is taken as Lg h, and the function relationship graph is plotted with coordinate point P. g The region centered at k*Lg h with radius k is the feature region, where k is the region coefficient and k≥1;

[0064] Step S220: If the transmission distance h is marked a second time, and the coordinate point corresponding to h in the second broken line is within the feature area, then h is taken as the reference transmission distance; then according to step S200, all reference transmission distances are obtained, and all adjacent reference transmission distances are aggregated into a reference distance segment to obtain all reference distance segments.

[0065] Step S300: Take the distance between any two adjacent reference distance segments as the distance segment to be detected, and determine the first abnormal distance and the second abnormal distance in the distance segment to be detected based on the characteristic parameters of each transmission distance in the distance segment to be detected.

[0066] Step S310: Obtain two adjacent reference distance segments A and B. Take the maximum transmission distance in A as X1, and the minimum transmission distance in B as X2, and X1 < X2. Take the distance segment between X1 and X2 as the to-be-detected distance segment C.

[0067] Divide the to-be-detected distance segment C evenly into M sub-distance segments. Obtain the corresponding curve of each sub-distance segment in the first broken line, and based on the coordinate points at both ends of each curve, obtain the slope corresponding to each curve, and calculate the variance of all slopes. Take the variance as the distance coefficient Y corresponding to the to-be-detected distance segment C.

[0068] Step S320: Take the curve corresponding to the to-be-detected distance segment C in the first broken line as the reference curve. With each coordinate point on the reference curve as the center, perpendicular to the tangent line of each coordinate point, and the lengths on both sides are both K Y *Y*e -|R-X| The range of is used as the reference area, K Y is the preset area coefficient, R is the transmission distance in the middle of the to-be-detected distance segment C, and X is a certain transmission distance between X1 and X2.

[0069] If the coordinate point corresponding to a certain transmission distance in the to-be-detected distance segment C in the second broken line is within the reference area, take the certain transmission distance as the first abnormal distance. If it is not within the reference area, take the certain transmission distance as the second abnormal distance, and then obtain all the first abnormal distances and second abnormal distances.

[0070] If the slope values of each sub-distance segment vary greatly, it means that the difference values of the luminous intensities corresponding to each sub-distance segment in the to-be-detected distance segment C are greater. In this solution, the distance coefficient is used to characterize the difference value, and the variance is used to characterize the size of the difference value. The greater the variance, the greater the difference value. And the greater this difference value, that is, the greater the distance coefficient, and then the range of the reference area should also be larger. The size of the reference area directly affects the judgment of the first abnormal distance and the second abnormal distance.

[0071] The transmission distance of the first abnormal distance is a value with a smaller deviation, and the transmission distance of the second abnormal distance is a value with a larger deviation. Since the reference area is the key to judging the first abnormal distance and the second abnormal distance, and since the luminous intensity represents the signal energy intensity at a certain transmission distance received, and a sudden change in the luminous intensity belongs to an abnormal phenomenon, the reference area should be set in a rule that the reference area range close to X1 and X2 is smaller, and the reference area range close to R is larger. And X is a certain transmission distance between X1 and X2. The smaller |R - X| is, the closer the value of R - X is to 0, which means that X is closer to R at this time, and the range of the reference area is larger at this time. And for the function y = e -x the smaller the abscissa, the larger the ordinate. So in this solution, e -|R-X| is used for design.

[0072] Step S400: Based on the reference transmission distance, the first abnormal distance, and the second abnormal distance, obtain the deviation coefficient corresponding to the record to be detected. Based on the deviation coefficient, obtain the aging degree coefficient of the target optical fiber device, and perform different processing on the target optical fiber device according to the aging degree coefficient.

[0073] Step S410: Obtain the distance segments corresponding to the baseline transmission distance, the first abnormal distance, and the second abnormal distance in the target information record, respectively. The lengths of each distance segment are S0, S1, and S2, respectively. Add them together to obtain S. sum Remove S from S0, S1 and S2 um The ratios L0, L1, and L2 are obtained, and the weights of the baseline transmission distance, the first abnormal distance, and the second abnormal distance are set to W0, W1, and W2, respectively, with W1 + W2 = 1 and W2 > W1 > 0 > W0.

[0074] Assuming the total distance in the target information record is 1000m, where the distance segment corresponding to the baseline transmission distance is S0=800m, the distance segment corresponding to the first abnormal distance is S1=150m, and the distance segment corresponding to the second abnormal distance is S2=50m, then the distances L0, L1, and L2 are 0.8, 0.15, and 0.05, respectively.

[0075] Based on the ratio and weight, the deviation coefficient Z of the record to be detected is obtained, and the formula is: k Z To adjust the coefficient, k Z >1, e is the natural index, when Z<0, let Z=0;

[0076] Step S420: Obtain T records to be monitored by the target fiber optic device, and sort the records according to the chronological order of data monitoring, where the weight of the t-th record is W. t =t / ∑T d=1d; Calculate the deviation coefficient for each record to be tested. Based on the weight and deviation coefficient of each record to be tested, obtain the aging coefficient of the target fiber optic equipment Q=∑T t=1Z. t *W t Z t Let W be the deviation coefficient of the t-th record to be detected. t Let t be the weight of the t-th record to be detected.

[0077] In this embodiment, W1=0.4, W2=0.6, W0=-0.05, and the specific values ​​should be determined according to the actual situation; the function y=1-e -xWhen x is x≥0, y is in [0,1), but y will not equal 1. Therefore, the deviation coefficient Z in this scheme is in the range of [0,1), and the aging degree coefficient Q is also in the range of [0,1). The larger the aging degree coefficient Q is, the more serious the aging degree of the target optical fiber equipment. In this embodiment, when the aging degree coefficient is [0,0.3), the aging degree is judged to be relatively light, and simple maintenance operations such as cleaning and maintenance are performed on the target optical fiber equipment. When the aging degree coefficient is [0.3,0.6), the aging degree is judged to be moderate, and a moderate repair and adjustment strategy is implemented on the target optical fiber equipment. When the aging degree coefficient is [0.6,1), the aging degree is judged to be relatively serious, and a major repair, replacement, or scrapping decision is made for the target optical fiber equipment.

[0078] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for monitoring the lifecycle of fiber optic equipment based on artificial intelligence, characterized in that, Includes the following steps: Step S100: Obtain monitoring information records, extract the changes in characteristic parameters of the laser in the test optical fiber with transmission distance from the monitoring information records, and determine whether the monitoring information records are records to be detected; Step S200: If the monitoring information record is the record to be detected, obtain all the reference transmission distances based on the data changes of the feature parameters with the transmission distance, and obtain all the reference distance segments based on the reference transmission distances; Step S300: Take the distance between any two adjacent reference distance segments as the distance segment to be detected, and determine the first abnormal distance and the second abnormal distance in the distance segment to be detected based on the characteristic parameters of each transmission distance in the distance segment to be detected. Step S400: Based on the reference transmission distance, the first abnormal distance, and the second abnormal distance, obtain the deviation coefficient corresponding to the record to be detected, obtain the aging degree coefficient of the target optical fiber device based on the deviation coefficient, and perform different processing on the target optical fiber device based on the aging degree coefficient. Step S100 includes: Step S110: Obtain the monitoring information records corresponding to the target fiber optic device and the reference fiber optic device respectively. The monitoring information records are the information records of data monitoring during the process of the fiber optic device emitting laser into the test fiber from the emission point in the test fiber as the starting point. The monitoring information record of the reference fiber optic device is used as the reference information record, and the monitoring information record of the target fiber optic device is used as the target information record. Before emitting the laser, the parameter information of the laser emission of the two fiber optic devices is set to be consistent. The parameter information includes angle, wavelength, pulse width and power. Feature parameters corresponding to each transmission distance are extracted from the baseline information record and the target information record, respectively. The feature parameters include luminous intensity and wavelength. A function graph of luminous intensity changing with transmission distance is established, and a first broken line corresponding to the baseline information record and a second broken line corresponding to the target information record are plotted in the function graph. Step S120: Randomly obtain several location points in the test fiber, and ensure that the transmission distance between two adjacent location points in the test fiber is not less than a preset distance threshold, and use all location points as calibration points. Randomly select any two locations a and b in the test fiber. Add the transmission distance between a calibration point and a to the transmission distance between the calibration point and b to obtain the comprehensive distance of the calibration point. Obtain the comprehensive distance of each calibration point. Select the calibration point with the smallest comprehensive distance as F. Extract the coordinate point P corresponding to the calibration point F in the first broken line. N detection points are randomly selected from points a and b, and the detection coordinates of each detection point in the second broken line are obtained. Then, in the function relationship graph, with coordinate point P as the starting point and each detection coordinate point as the ending point, several coordinate vectors are obtained, and a vector set is established. Step S130: If there exists a corresponding vector in the vector set that does not satisfy... If the target information record is determined to be the record to be detected, then r is the ratio threshold, and v k v k+1 and v k+2 Let N be the k-th, k+1-th, and k+2-th coordinate vectors in the vector set, where 1 ≤ k < k+1 < k+2 ≤ N.

2. The method for monitoring the lifecycle of optical fiber equipment based on artificial intelligence according to claim 1, characterized in that, Step S200 includes: Step S210: In the function relationship diagram, perform a first mark on the transmission distance corresponding to the coordinate point where the first broken line intersects the second broken line. In the reference information record and the target information record, perform a second mark on the transmission distances with the same wavelength. Take the transmission distances that are marked with both the first mark and the second mark as the reference transmission distances; Obtain the reference transmission distance g and the adjacent non-reference transmission distance h from the reference information record respectively, and take the coordinate points corresponding to g and h in the first polyline as P. g and P h , will P g and P h The length between them is used as The function graph is plotted with coordinate point P. g With the center of the circle, The region with radius is taken as the feature region, k is the region coefficient, and k≥1; Step S220: If the second mark is performed on the transmission distance h, and the coordinate point corresponding to h in the second broken line is within the characteristic region, then take h as the reference transmission distance; furthermore, according to Step S200, obtain all the reference transmission distances, and gather all adjacent reference transmission distances as a reference distance segment to obtain all the reference distance segments.

3. The method for monitoring the lifecycle of optical fiber equipment based on artificial intelligence according to claim 2, characterized in that, Step S300 includes: Step S310: Obtain two adjacent reference distance segments A and B. Take the maximum transmission distance in A as X1, and the minimum transmission distance in B as X2, and X1 < X2; take the distance segment between X1 and X2 as the to-be-detected distance segment C; Divide the to-be-detected distance segment C evenly into M sub-distance segments. Obtain the curve corresponding to each sub-distance segment in the first broken line, and according to the coordinate points at both ends of each curve, obtain the slope corresponding to each curve, and calculate the variance of all the slopes. Take the variance as the distance coefficient Y corresponding to the to-be-detected distance segment C; Step S320: Take the curve corresponding to the distance segment C to be detected in the first broken line as the reference curve, and draw a line perpendicular to the tangent at each coordinate point on the reference curve, with both sides having a length of K. Y *Y*e -|R-X| The range is used as the reference area, K Y R is the preset area coefficient, R is the transmission distance in the middle of the distance segment C to be detected, and X is a certain transmission distance between X1 and X2; If the coordinate point corresponding to a certain transmission distance in the to-be-detected distance segment C in the second broken line is within the reference region, take the certain transmission distance as the first abnormal distance; if it is not within the reference region, take the certain transmission distance as the second abnormal distance, and thus obtain all the first abnormal distances and the second abnormal distances.

4. The method for monitoring the lifecycle of fiber optic equipment based on artificial intelligence according to claim 3, characterized in that, Step S400 includes: Step S410: Obtain the distance segments corresponding to the baseline transmission distance, the first abnormal distance, and the second abnormal distance in the target information record, respectively. The lengths of each distance segment are S0, S1, and S2, respectively. Add them together to obtain S. sum Remove S from S0, S1 and S2 um The ratios L0, L1, and L2 are obtained, and the weights of the baseline transmission distance, the first abnormal distance, and the second abnormal distance are set to W0, W1, and W2, respectively, with W1 + W2 = 1 and W2 > W1 > 0 > W0. According to the ratio and the weight, obtain that the deviation coefficient of the to-be-detected record is Z. When Z < 0, let Z = 0; Step S420: Obtain T records to be monitored by the target fiber optic device, and sort the records according to the order of data monitoring time, where the weight of the t-th record is... Calculate the deviation coefficient for each record to be tested, and obtain the aging coefficient of the target optical fiber equipment based on the weight and deviation coefficient of each record to be tested. Z t Let W be the deviation coefficient of the t-th record to be detected. t Let t be the weight of the t-th record to be detected.

5. A fiber optic equipment lifecycle monitoring system, used to execute the artificial intelligence-based fiber optic equipment lifecycle monitoring method according to any one of claims 1-4, characterized in that, The system includes a to-be-detected record judgment module, a reference distance segment determination module, an abnormal distance type classification module, and an aging degree coefficient calculation module; The to-be-detected record judgment module: is used to obtain the monitoring information record, extract the change situation of the characteristic parameters corresponding to the laser in the test optical fiber in the monitoring information record with respect to the transmission distance, and judge whether the monitoring information record is a to-be-detected record; The reference distance segment determination module: If the monitoring information record is a to-be-detected record, the reference distance segment determination module is used to obtain all the reference transmission distances according to the data change of the characteristic parameters with respect to the transmission distance, and obtain all the reference distance segments among them according to the reference transmission distances; The abnormal distance type classification module: is used to take the distance segment between any two adjacent reference distance segments as the to-be-detected distance segment, and determine the first abnormal distance and the second abnormal distance in the to-be-detected distance segment according to the characteristic parameters of each transmission distance in the to-be-detected distance segment; The aging degree coefficient calculation module: is used to obtain the deviation coefficient corresponding to the to-be-detected record according to the reference transmission distance, the first abnormal distance, and the second abnormal distance, obtain the aging degree coefficient of the target optical fiber device according to the deviation coefficient, and perform different processing on the target optical fiber device according to the aging degree coefficient.

6. The fiber optic equipment lifecycle monitoring system according to claim 5, characterized in that, The to-be-detected record judgment module includes a function relationship diagram establishment unit, a vector set establishment unit, and a to-be-detected record judgment unit; Function Relationship Graph Establishment Unit: Used to acquire monitoring information records corresponding to the target fiber optic device and the reference fiber optic device respectively; and obtain the reference information record and the target information record; establish a function relationship graph of the change of light intensity with transmission distance, and draw the first broken line and the second broken line in the function relationship graph; Vector set establishment unit: used to obtain calibration points in the test fiber; randomly obtain several detection position points within any two position points in the test fiber, obtain the detection coordinate points corresponding to each detection position point in the second broken line, obtain each vector, and establish a vector set; The record to be detected judgment unit is used to determine whether the target information record is a record to be detected based on the vector set.

7. The fiber optic equipment lifecycle monitoring system according to claim 6, characterized in that, The abnormal distance type classification module includes a distance coefficient calculation unit and a distance type classification unit; Distance coefficient calculation unit: used to obtain two adjacent reference distance segments, obtain the distance segment to be detected, divide the distance segment to be detected evenly into several sub-distance segments, and obtain the distance coefficient corresponding to the distance segment to be detected; Distance type classification unit: used to take the curve corresponding to the distance segment to be detected in the first broken line as the reference curve, obtain the reference area, and determine the first abnormal distance and the second abnormal distance in the distance segment to be detected.

Images