Submarine cable fault online diagnosis and positioning method and system based on optical fiber sensing technology

Abstract

The invention discloses a submarine cable fault online diagnosis and positioning method and system based on an optical fiber sensing technology, and relates to the technical field of optical fiber sensing, and the method comprises the steps: obtaining a real-time strain data flow of a submarine cable through a distributed optical fiber strain measurement device; carrying out space-time alignment and abnormal value correction processing on the original data set, and constructing a target data set; coordinate mapping is carried out on the target data set and a geographic information system of a submarine cable laying line, and a fault diagnosis layer with multi-dimensional visualization features is generated; an interactive fault analysis panel is generated on a geographic information system interface, and the deviation ratio between the strain theoretical threshold value and the actual measurement value of each monitoring point in the target data set is calculated; according to the submarine cable fault online diagnosis and positioning method and system based on the optical fiber sensing technology, rapid positioning of fault features is achieved, the fault response efficiency is improved, and long-term stable operation of a submarine communication network is ensured.

Description

Technical Field

[0001] This application relates to the field of fiber optic sensing technology, and particularly to an online fault diagnosis and location method and system for submarine cables based on fiber optic sensing technology. Background Art

[0002] In the prior art, submarine cables usually adopt a multi-layer protection structure, including an insulating coating layer, a steel pipe pressure-resistant layer, a high-strength steel wire armor layer, and a polyethylene outer sheath to ensure their reliability in complex marine environments. Modern submarine optical cables use optical fibers as signal transmission media, and during the manufacturing process, the optical fibers need to be embedded in a gel-like compound to prevent performance degradation caused by seawater penetration. Although such structural designs can resist water pressure and corrosion to a certain extent, they may still fail due to factors such as mechanical damage, chemical corrosion, or geological activities during long-term operation. Traditional detection methods mainly rely on regular manual inspections or local sensor monitoring, which have problems such as response lag and insufficient positioning accuracy.

[0003] Although distributed fiber optic sensing technology can achieve strain and temperature monitoring of submarine cables, due to problems such as signal attenuation of the optical fibers themselves and environmental noise interference, the directly obtained sensing data often has deviations. In addition, the prior art lacks the ability to perform collaborative analysis of multi-dimensional data (such as strain, vibration, temperature) and extract fault characteristics, resulting in a high false alarm rate for fault diagnosis. Especially in complex marine environments, it is difficult to accurately distinguish cable self-abnormalities from external environmental interferences with a single sensing parameter. There is an urgent need for a high-precision online diagnosis method that integrates multi-source information to improve the reliability and timeliness of fault location. Summary of the Invention

[0004] To overcome the deficiencies of the above prior art, this application provides an online fault diagnosis and location method and system for submarine cables based on fiber optic sensing technology.

[0005] In a first aspect, an online fault diagnosis and location method for submarine cables based on fiber optic sensing technology provided by this application includes: Obtain the real-time strain data stream of the submarine cable through a distributed fiber optic strain measurement device, and use the signal processing module of the distributed fiber optic strain measurement device to extract an original data set including strain amplitude, strain change rate, temperature compensation coefficient, and vibration characteristic parameters from the strain data stream; Perform spatio-temporal alignment and outlier correction processing on the original data set to construct a target data set including the three-dimensional spatial coordinates of the submarine cable, the strain distribution heat map, and the fault characteristic fingerprint; Perform coordinate mapping on the target data set and the geographic information system of the submarine cable laying route to generate a fault diagnosis layer with multi-dimensional visualization characteristics, where the color of the warning area in the fault diagnosis layer changes gradually according to a preset color scale rule according to the degree of strain abnormality, and the area of the warning area is in direct proportion to the strain abnormality range; Generate an interactive fault analysis panel on the geographical information system interface. When detecting the selected operation of the operator on the fault diagnosis layer, display the submarine cable burial depth information, strain historical change curve, deviation value from the nearest maintenance record, and surrounding marine environment parameters of the currently selected section. Based on the material parameters, laying years, and real-time marine environment data of the submarine cable, calculate the deviation rate between the theoretical strain threshold and the actual measured value of each monitoring point in the target dataset. When the deviation rate exceeds the first preset threshold, generate a fault warning message and mark the precise longitude and latitude coordinates of the potential fault point.

[0006] Preferably, collect the fiber optic backscattering spectrum through the Brillouin optical time domain analysis module of the distributed fiber optic strain measurement device. Analyze the frequency shift amount, power spectral width, and signal-to-noise ratio parameters in the backscattering spectrum. For the section containing abnormal vibration characteristics, extract its vibration frequency spectrum characteristics and time domain energy distribution. Convert the analysis results into a structured data set including timestamp, spatial position encoding, strain tensor matrix, temperature compensation coefficient, and vibration feature vector.

[0007] Preferably, set the color gradient according to the strain anomaly degree, so that each additional standard deviation corresponds to adjusting the preset color scale value. Add a periodic flashing mark to the section with historical maintenance records, and the flashing frequency is positively correlated with the number of maintenance times. Draw a dynamic warning boundary at the boundary of the section with potential anchor damage risk, and the flashing interval of the boundary is dynamically adjusted according to the real-time sea current speed. Use the spatial interpolation algorithm to grid the discrete monitoring point data, and superimpose and display a composite identifier including the strain change trend arrow and risk level score in each grid cell.

[0008] Preferably, when detecting that the strain change rate exceeds a preset multiple of the material fatigue coefficient, mark it as a material aging risk. For the monitoring points located in the submarine geological activity zone, calculate the deviation degree between the strain accumulation amount and the geological settlement model. When the deviation degree exceeds the second preset threshold, mark it as affected by geological activities. When the strain gradient between adjacent monitoring points exceeds a preset ratio of the cable bending radius limit, trigger a mechanical damage warning. Conduct statistical analysis on the strain residuals after temperature compensation. When the residual standard deviation exceeds the third preset threshold, mark it as an abnormal fiber optic sensing system.

[0009] Preferably, establish a data synchronization channel with multiple submarine cable monitoring stations to obtain the strain measurement data and environmental monitoring data of multiple submarine cable monitoring stations in real time. A comparison heat map of multiple monitoring stations is displayed side by side on the geographic information system interface, and the difference regions of the strain distribution of multiple monitoring stations are superimposed and displayed on the comparison heat map. When an abnormal strain appears in a specific section is detected, a set of environmental parameters of the section is extracted, historical fault cases are matched based on parameter similarity, and maintenance strategy suggestions are generated.

[0010] Preferably, an autonomous underwater vehicle captures visual inspection data of the submarine cable at a preset inspection cycle. According to the spatial alignment result of the visual inspection data and the strain measurement data, a first sampling density strategy is implemented for high-risk sections, and a second sampling density strategy is implemented for other sections. When the duration of the abnormality in the same section exceeds the first preset time threshold, the strain evolution history record of the section is displayed on the interactive fault analysis panel, and the corresponding laying parameters are located in the submarine cable as-built drawing. Calculate the cable health index based on the strain spatial distribution characteristics. When the index exceeds the preset risk threshold, decision-making suggestions including the maintenance priority ranking and the selection of maintenance plans are generated.

[0011] Preferably, a full life cycle database of the submarine cable is established to record the strain baseline data, fault characteristics and corresponding maintenance records after each maintenance. When the similarity between the current strain abnormality characteristics and historical fault cases exceeds the preset similarity threshold, the associated historical maintenance plan and verification test data are pushed. Construct a time series prediction model based on deep learning, input the current strain time series data and the set of environmental parameters into the prediction model, and output the potential fault type identifier and its occurrence probability. Verify the effectiveness and implementation cost of the maintenance suggestions in the simulation environment, and after passing the verification, issue them to the relevant responsible units through the operation and maintenance management system.

[0012] In a second aspect, an on-line fault diagnosis and location system for submarine cables based on fiber optic sensing technology, comprising: A data extraction unit for obtaining the real-time strain data stream of the submarine cable through a distributed fiber optic strain measurement device, and using the signal processing module of the distributed fiber optic strain measurement device to extract an original data set including strain amplitude, strain change rate, temperature compensation coefficient and vibration characteristic parameters from the strain data stream. A target data set construction unit for performing spatio-temporal alignment and outlier correction processing on the original data set, and constructing a target data set including the three-dimensional spatial coordinates of the submarine cable, the strain distribution heat map and the fault characteristic fingerprint. A mapping unit for mapping the coordinates of the target data set with the geographical information system of the submarine cable laying route to generate a fault diagnosis layer with multi-dimensional visualization features, wherein the color of the warning area in the fault diagnosis layer gradually changes according to a preset color scale rule according to the strain anomaly degree, and the area of the warning area is in direct proportion to the strain anomaly range; A display unit for generating an interactive fault analysis panel on the geographical information system interface, and when it detects the selected operation of the operator on the fault diagnosis layer, it displays the submarine cable burial depth information, the strain historical change curve, the deviation value from the nearest maintenance record, and the surrounding marine environment parameters of the currently selected section; An early warning unit for calculating the deviation rate between the theoretical strain threshold and the actual measured value of each monitoring point in the target data set based on the material parameters, laying years and real-time marine environment data of the submarine cable, and generating a fault warning message and marking the precise longitude and latitude coordinates of potential fault points when the deviation rate exceeds the first preset threshold.

[0013] Compared with the prior art, the present invention has the following characteristics and beneficial effects: First, the strain data stream of the submarine cable is obtained in real time through a distributed optical fiber strain measurement device, and multi-dimensional characteristic parameters are extracted from it, solving the limitations of traditional detection methods that rely on discrete sampling and manual analysis, ensuring the continuity and integrity of data collection, and providing a high-precision data basis for fault diagnosis. Secondly, the original data is subjected to spatio-temporal alignment and outlier correction processing to construct a target data set containing three-dimensional coordinates and a strain heat map, effectively eliminating environmental noise interference, improving data reliability, and enhancing the accuracy of fault identification through feature fingerprint extraction. Further, the target data set is mapped with the geographical information system to generate a multi-dimensional visual diagnosis layer, and the strain anomaly distribution is intuitively displayed by color gradient and dynamic warning areas, reducing the analysis difficulty of maintenance personnel and realizing the rapid positioning of fault characteristics. Combining with the real-time feedback function of the interactive fault analysis panel, when a specific section is selected, the burial depth information, the historical strain curve and the environmental parameters are dynamically associated and displayed, forming a closed-loop operation and maintenance process of "anomaly discovery - data analysis - decision support", greatly improving the fault response efficiency. In addition, based on the dynamic deviation rate calculation model of material characteristics, laying years and environmental parameters, potential fault risks can be identified in the early stage, and targeted maintenance can be guided by accurately marking the longitude and latitude coordinates of the fault points, preventing cable breakage or performance deterioration from the root cause, and ensuring the long-term stable operation of the submarine communication network. Description of the Drawings

[0014] Figure 1 It is a step block diagram of a method for on-line diagnosis and positioning of submarine cable faults mainly embodied in this embodiment based on optical fiber sensing technology.

[0015] Figure 2It is a structural block diagram of an on-line fault diagnosis and location system for submarine cables based on fiber optic sensing technology, which is mainly reflected in this embodiment. Specific implementation mode

[0016] The present invention will be further described in detail below in conjunction with the following embodiments.

[0017] Refer to Figure 1 , an on-line fault diagnosis and location method for submarine cables based on fiber optic sensing technology, the method comprising the following steps: S1. Obtain the real-time strain data stream of the submarine cable through a distributed fiber optic strain measurement device, and use the signal processing module of the distributed fiber optic strain measurement device to extract the original data set including strain amplitude, strain change rate, temperature compensation coefficient and vibration characteristic parameters from the strain data stream.

[0018] S2. Perform spatio-temporal alignment and outlier correction processing on the original data set to construct a target data set including the three-dimensional spatial coordinates of the submarine cable, the strain distribution heat map and the fault characteristic fingerprint.

[0019] S3. Map the coordinates of the target data set to the geographic information system of the submarine cable laying route to generate a fault diagnosis layer with multi-dimensional visualization features, where the color of the warning area in the fault diagnosis layer changes gradually according to the preset color scale rule according to the strain anomaly degree, and the area of the warning area is in direct proportion to the strain anomaly range.

[0020] S4. Generate an interactive fault analysis panel on the geographic information system interface. When it is detected that the operator makes a selection operation on the fault diagnosis layer, display the submarine cable burial depth information, the strain historical change curve, the deviation value from the nearest maintenance record and the surrounding marine environment parameters of the currently selected section.

[0021] S5. Based on the material parameters, laying years and real-time marine environment data of the submarine cable, calculate the deviation rate between the theoretical strain threshold and the actual measured value of each monitoring point in the target data set. When the deviation rate exceeds the first preset threshold, generate a fault warning message and mark the precise longitude and latitude coordinates of the potential fault point.

[0022] Specifically, first, the strain data stream of the submarine cable is obtained in real time through a distributed optical fiber strain measurement device, and multi-dimensional characteristic parameters are extracted from it, solving the limitations of traditional detection methods that rely on discrete sampling and manual analysis, ensuring the continuity and integrity of data acquisition, and providing a high-precision data basis for fault diagnosis. Secondly, the original data is subjected to spatio-temporal alignment and outlier correction processing to construct a target data set containing three-dimensional coordinates and strain heat maps, effectively eliminating environmental noise interference, improving data reliability, and enhancing the accuracy of fault recognition through feature fingerprint extraction. Further, the target data set is subjected to coordinate mapping with a geographic information system to generate a multi-dimensional visual diagnostic layer, intuitively displaying the abnormal strain distribution with color gradients and dynamic warning areas, reducing the analysis difficulty of maintenance personnel, and achieving rapid positioning of fault characteristics. Combining with the real-time feedback function of the interactive fault analysis panel, when a specific section is selected, the burial depth information, historical strain curve, and environmental parameters are dynamically associated and displayed, forming a closed-loop operation and maintenance process of "abnormality discovery - data analysis - decision support", greatly improving the fault response efficiency. In addition, based on the dynamic deviation rate calculation model of material properties, laying years, and environmental parameters, potential fault risks can be identified in the early stage, and targeted maintenance can be guided by accurately marking the longitude and latitude coordinates of the fault points, preventing cable breakage or performance degradation from the source, and ensuring the long-term stable operation of the submarine communication network.

[0023] Specific step S1 includes the following sub-steps: Collect the fiber backscattering spectrum through the Brillouin optical time domain analysis module of the distributed optical fiber strain measurement device; Analyze the frequency shift amount, power spectral width, and signal-to-noise ratio parameters in the backscattering spectrum; For the section containing abnormal vibration characteristics, extract its vibration frequency spectrum characteristics and time-domain energy distribution; Convert the analysis results into a structured data set containing time stamps, spatial position codes, strain tensor matrices, temperature compensation coefficients, and vibration feature vectors.

[0024] Specifically, the Brillouin optical time domain analysis module of the distributed optical fiber strain measurement device is used to collect the optical fiber backscattering spectrum. This technology can achieve long-distance and high-precision strain measurement, overcoming the coverage limitation of traditional point sensors. The frequency shift amount, power spectral width, and signal-to-noise ratio parameters in the backscattering spectrum are analyzed. These parameters can comprehensively reflect the strain state and signal quality of the optical fiber. For the section containing abnormal vibration characteristics, the vibration frequency spectrum characteristics and time-domain energy distribution are extracted. These characteristics help to distinguish normal working conditions from abnormal events. The analysis results are converted into a structured data set containing timestamps, spatial position codes, strain tensor matrices, temperature compensation coefficients, and vibration feature vectors, providing a standardized data input for subsequent analysis. For example, in practical applications, by analyzing the backscattering spectrum, the system finds that there is an abnormal change in the frequency shift amount of a certain section of cable. The system can extract the vibration characteristics of this section and convert them into structured data for in-depth analysis in subsequent steps.

[0025] Specifically, the process of step S2 can be as follows: perform spatio-temporal alignment and outlier correction on the original data set to construct a target data set containing the three-dimensional spatial coordinates of the submarine cable, the heat map of strain distribution, and the fault feature fingerprints. First, use the time series alignment algorithm to eliminate the time delay between different monitoring points to ensure the time consistency of the data. Then, apply the spatial interpolation method to fill in the data missing due to measurement blind spots to ensure spatial continuity. Identify and correct abnormal data points through statistical analysis methods to improve data quality. Finally, extract fingerprint features that can characterize the health state of the cable, such as strain gradient, main vibration frequency, etc., to form a target data set with diagnostic value. For example, in a certain actual monitoring, the system found that there was a time offset in the strain data of a certain section of cable through spatio-temporal alignment processing. After correction, an accurate three-dimensional strain distribution map was constructed, providing a reliable basis for subsequent fault diagnosis.

[0026] Specifically, step S3 includes the following sub-steps: Set the color gradient according to the degree of strain abnormality, so that each additional standard deviation corresponds to an adjustment of the preset color scale value; Add a periodic flashing mark to the section with historical maintenance records. The flashing frequency is positively correlated with the number of maintenance times; Draw a dynamic warning boundary at the boundary of the section with potential anchor damage risk. The flashing interval of the boundary is dynamically adjusted according to the real-time sea current speed; Use the spatial interpolation algorithm to grid the discrete monitoring point data, and superimpose a composite identifier containing the strain change trend arrow and risk level score on each grid cell.

[0027] Specifically, a color gradient is set according to the degree of strain anomaly, such that each additional standard deviation corresponds to an adjustment of the preset color scale value. This visualization method can intuitively reflect the spatial distribution law of strain anomalies. Periodic blinking markers are added to sections with historical maintenance records, and the blinking frequency is positively correlated with the number of maintenance times. This design can highlight key sections with recurring problems. A dynamic warning boundary is drawn at the boundary of sections with potential anchor damage risks, and the blinking interval of the boundary is dynamically adjusted according to the real-time sea current speed to achieve real-time visualization of the risk level. The spatial interpolation algorithm is used to grid the discrete monitoring point data, and a composite identifier containing a strain change trend arrow and a risk level score is superimposed and displayed in each grid cell to provide multi-dimensional diagnostic information. For example, during a submarine cable inspection, the system successfully identified a high-risk section threatened by fishing boat anchor damage through the dynamic warning boundary, providing a clear repair target for the operation and maintenance personnel.

[0028] Specifically, the process of step S4 can be to generate an interactive fault analysis panel in the geographic information system interface. When it detects the selected operation of the operator on the fault diagnosis layer, it displays the submarine cable burial depth information, the historical strain change curve, the deviation value from the nearest maintenance record, and the surrounding marine environment parameters of the currently selected section. Specifically, the system will listen for the user's interactive operations on the GIS interface in real time. When it detects a region selection event, it automatically retrieves the complete operation and maintenance file of this section from the database. The historical evolution trend of the strain data is displayed through a visualization chart to help analysts judge the process of fault development. At the same time, it displays the data deviation of this section from the time of the most recent maintenance to evaluate the persistence of the maintenance effect. The surrounding marine environment parameters, such as water temperature, salinity, sea current speed, etc., are integrally displayed to provide an environmental background for fault cause analysis. For example, during a certain fault diagnosis, the analyst found through the interactive panel that the strain anomaly in a certain section was highly correlated with the change of environmental parameters, thus accurately judging the inducing factors of the fault.

[0029] Specifically, step S5 includes the following sub-steps:

[0030] When it detects that the strain change rate exceeds a preset multiple of the material fatigue coefficient, it is marked as a material aging risk; For the monitoring points located in the submarine geological activity zone, calculate the deviation degree between the accumulated strain and the geological subsidence model. When the deviation degree exceeds the second preset threshold, it is marked as affected by geological activities; When the strain gradient between adjacent monitoring points exceeds a preset ratio of the cable bending radius limit, a mechanical damage warning is triggered; Statistical analysis is performed on the strain residuals after temperature compensation. When the residual standard deviation exceeds the third preset threshold, it is marked as an abnormal optical fiber sensing system.

[0031] Specifically, when the detected strain change rate exceeds a preset multiple of the material fatigue coefficient, it is marked as a material aging risk. This early warning mechanism can detect the performance degradation of cable materials in advance. For the monitoring points located in the submarine geological activity zone, calculate the deviation degree between the accumulated strain and the geological settlement model. When the deviation degree exceeds the second preset threshold, it is marked as the influence of geological activities. This analysis method can distinguish between faults caused by human damage and natural factors. When the strain gradient between adjacent monitoring points exceeds a preset ratio of the cable bending radius limit, a mechanical damage early warning is triggered to prevent permanent damage to the cable caused by excessive bending. Conduct statistical analysis on the strain residuals after temperature compensation. When the residual standard deviation exceeds the third preset threshold, it is marked as an abnormality in the fiber optic sensing system to ensure the reliability of the measurement system itself. For example, in a certain monitoring, the system successfully warned of an impending cable bending damage by analyzing the strain gradient, avoiding a major communication interruption accident.

[0032] The temperature compensation strain calculation formula is as follows: : The true strain value after temperature compensation (unit: ) : The original measured strain value (unit: ) Among them, microstrain ( ) is the standard unit of engineering strain, representing one millionth of the relative deformation of the material; (dimensionless strain) The unit of the second term on the right side of the temperature compensation strain calculation formula is , which is exactly the same as the unit on the left side, and the formula is dimensionally consistent; : Fiber optic temperature sensitivity coefficient (unit: ), typical value 1.2× / ℃; Distributed fiber optic sensors (such as BOTDR / BOTDA) directly output strain values with the unit of . Temperature compensation is corrected based on the original measured value ( ), so the unit of the compensated strain needs to be the same as the unit of the original data; : Temperature change amount (unit: ℃), obtained through distributed temperature sensing (DTS); The strain anomaly index (SAI) formula is as follows: : Strain anomaly index, used to quantify the degree of local anomaly : The number of data points within the sliding window (default n = 50) : The average strain within the window : The standard deviation of strain within the window : The strain change rate (unit: ) : The material fatigue threshold (unit: ).

[0033] In strain-controlled fatigue, in high-cycle fatigue (high frequency and low strain), it is commonly used , for example, the fatigue threshold of aerospace alloys may be between 200 - 500 ; When the material fatigue mechanism is dominated by micro cyclic strain (such as submarine cables under high-frequency vibration), using is more intuitive; In some embodiments, the on-line fault diagnosis and location method for submarine cables based on fiber optic sensing technology may further include the following steps: Establish a data synchronization channel with multiple submarine cable monitoring stations to obtain the strain measurement data and environmental monitoring data of multiple submarine cable monitoring stations in real time; Display the comparison heat maps of multiple monitoring stations side by side on the geographic information system interface, and the comparison heat maps are superimposed to display the strain distribution difference regions of multiple monitoring stations; When an abnormal strain is detected in a specific section, extract the set of environmental parameters of the section, match the historical fault cases based on the parameter similarity, and generate maintenance strategy suggestions.

[0034] Specifically, establish a data synchronization channel with multiple submarine cable monitoring stations to obtain the strain measurement data and environmental monitoring data of multiple submarine cable monitoring stations in real time, realizing the collaborative monitoring of the cable health status within a wide area. Display the comparison heat maps of multiple monitoring stations side by side on the geographic information system interface, and the comparison heat maps are superimposed to display the strain distribution difference regions of multiple monitoring stations, helping analysts quickly locate the abnormal sections. When an abnormal strain is detected in a specific section, extract the set of environmental parameters of the section, match the historical fault cases based on the parameter similarity, and generate maintenance strategy suggestions, improving the efficiency and accuracy of fault handling. For example, in a certain cross-regional cable monitoring, the system accurately identified a cable anomaly caused by a regional geological activity by comparing the data of multiple monitoring stations, providing a basis for formulating targeted protection measures.

[0035] In some embodiments, the on-line fault diagnosis and location method for submarine cables based on fiber optic sensing technology may further include the following steps: Capturing visual inspection data of submarine cables by an autonomous underwater vehicle at a preset inspection cycle; Implementing a first sampling density strategy for high-risk sections and a second sampling density strategy for other sections according to the spatial alignment result of visual inspection data and strain measurement data; When it is detected that the abnormal duration of the same section exceeds the first preset time threshold, display the strain evolution history record of the section on the interactive fault analysis panel and locate the corresponding laying parameters in the submarine cable as-built drawing; Calculating the cable health index based on the strain spatial distribution characteristics, and generating decision suggestions including the sorting of maintenance priorities and the selection of maintenance plans when the index exceeds the preset risk threshold.

[0036] Specifically, capturing visual inspection data of submarine cables by an autonomous underwater vehicle at a preset inspection cycle to make up for the deficiency of fiber optic sensing in surface defect detection. Implementing a first sampling density strategy for high-risk sections and a second sampling density strategy for other sections according to the spatial alignment result of visual inspection data and strain measurement data to optimize the allocation of inspection resources. When it is detected that the abnormal duration of the same section exceeds the first preset time threshold, display the strain evolution history record of the section on the interactive fault analysis panel and locate the corresponding laying parameters in the submarine cable as-built drawing to provide a complete information chain for fault tracing. Calculating the cable health index based on the strain spatial distribution characteristics, and generating decision suggestions including the sorting of maintenance priorities and the selection of maintenance plans when the index exceeds the preset risk threshold to achieve the precise allocation of operation and maintenance resources. For example, in a certain joint inspection, the surface damage found by the AUV highly coincides with the strain anomaly monitored by the fiber optic, and the system gives a suggestion to repair immediately accordingly, avoiding potential communication interruption.

[0037] In some embodiments, the online fault diagnosis and location method for submarine cables based on fiber optic sensing technology may further include the following steps: Establishing a full life cycle database for submarine cables, recording the strain baseline data, fault characteristics and corresponding maintenance records after each repair; When it is detected that the similarity between the current strain anomaly characteristics and historical fault cases exceeds the preset similarity threshold, pushing the associated historical maintenance plans and verification test data; Constructing a time series prediction model based on deep learning, inputting the current strain time series data and environmental parameter set into the prediction model, and outputting the potential fault type identifier and its occurrence probability; Verifying the effectiveness and implementation cost of the maintenance suggestions in a simulation environment, and issuing them to the relevant responsible units through the operation and maintenance management system after passing the verification.

[0038] Specifically, a full - life - cycle database of submarine cables is established to record the strain baseline data, fault characteristics, and corresponding maintenance records after each repair, forming a complete cable health file. When the similarity between the currently detected abnormal strain characteristics and historical fault cases exceeds a preset similarity threshold, the associated historical maintenance plans and verification test data are pushed to achieve the effective reuse of empirical knowledge. A time - series prediction model based on deep learning is constructed. The current strain time - series data and environmental parameter set are input into the prediction model, and potential fault type identifiers and their occurrence probabilities are output to enhance the foresight of fault warning. The effectiveness and implementation cost of maintenance suggestions are verified in a simulation environment. After passing the verification, they are sent to relevant responsible units through the operation and maintenance management system to ensure the scientificity and feasibility of repair decisions. For example, by analyzing historical data, the system successfully predicted the aging fault of a cable joint, and the preventive replacement arranged in advance avoided significant losses.

[0039] In this way, a full - process automated processing from data acquisition to fault warning is realized through distributed fiber optic sensing technology. The system adopts advanced spectral analysis technology to achieve high - precision distributed monitoring, greatly improving the data acquisition efficiency. Through intelligent data - processing algorithms, the signal quality and abnormal recognition ability are significantly improved. The innovative visualization technology enables operation and maintenance personnel to quickly locate high - risk sections, greatly enhancing the diagnosis efficiency. The interactive analysis function significantly shortens the fault diagnosis time and improves the decision - making accuracy through intelligent data processing and display methods. The intelligent warning system integrates multiple prediction models to achieve early warning and precise positioning of faults. The system also has the ability of multi - station collaborative monitoring, supporting cross - regional data synchronization and analysis, and significantly accelerating the discovery speed of regional faults. The collaborative operation with autonomous underwater vehicles realizes supplementary detection of the cable surface state. The full - life - cycle management function effectively extends the cable service life and reduces the operation and maintenance cost through intelligent data analysis and prediction. This method has been successfully applied to multiple important engineering projects, significantly reducing the fault occurrence rate. A single set of system can achieve continuous monitoring of a large - range cable and support the collaborative work of multiple monitoring stations, providing innovative technical guarantees for the safe operation of submarine communication infrastructure.

[0040] An on - line fault diagnosis and location system for submarine cables based on fiber optic sensing technology, by applying an on - line fault diagnosis and location method for submarine cables based on fiber optic sensing technology as described above, includes a data extraction unit, a target data set construction unit, a mapping unit, a display unit, and a warning unit, referring to Figure 2, the data extraction unit obtains the real-time strain data stream of the submarine cable through the distributed optical fiber strain measurement device, and the signal processing module of the distributed optical fiber strain measurement device extracts the original data set including strain amplitude, strain change rate, temperature compensation coefficient and vibration characteristic parameters from the strain data stream; the target data set construction unit performs spatio-temporal alignment and outlier correction processing on the original data set to construct a target data set including the three-dimensional spatial coordinates of the submarine cable, the strain distribution heat map and the fault characteristic fingerprint; the mapping unit maps the target data set with the geographic information system of the submarine cable laying route to generate a fault diagnosis layer with multi-dimensional visualization characteristics, wherein the color of the warning area in the fault diagnosis layer changes gradually according to the preset color scale rule according to the strain anomaly degree, and the area of the warning area is in direct proportion to the strain anomaly range; the display unit generates an interactive fault analysis panel on the geographic information system interface, and when it detects the selected operation of the operator on the fault diagnosis layer, it displays the submarine cable burial depth information, the strain historical change curve, the deviation value from the nearest maintenance record and the surrounding marine environment parameters of the current selected section; the warning unit calculates the deviation rate between the theoretical strain threshold value and the actual measured value of each monitoring point in the target data set based on the material parameters of the submarine cable, the laying years and the real-time marine environment data, and generates a fault warning information and marks the precise longitude and latitude coordinates of the potential fault point when the deviation rate exceeds the first preset threshold value.

[0041] The above are all the preferred embodiments of this application, and the protection scope of this application is not limited accordingly. Therefore, all equivalent changes made according to the structure, shape and principle of this application should be covered within the protection scope of this application.

Claims

1. An on-line fault diagnosis and location method for submarine cables based on optical fiber sensing technology, characterized in that Including the following steps: Obtain the real-time strain data stream of the submarine cable through a distributed optical fiber strain measurement device, and use the signal processing module of the distributed optical fiber strain measurement device to extract the original data set from the strain data stream; Perform spatio-temporal alignment and outlier correction processing on the original data set to construct a target data set; Perform coordinate mapping on the target data set and the geographic information system of the submarine cable laying route to generate a fault diagnosis layer with multi-dimensional visualization features; Generate an interactive fault analysis panel on the geographic information system interface. When it is detected that the operator makes a selection operation on the fault diagnosis layer, display the submarine cable burial depth information, strain historical change curve, deviation value from the nearest maintenance record, and surrounding marine environment parameters of the currently selected section; Based on the material parameters, laying years, and real-time marine environment data of the submarine cable, calculate the deviation rate between the theoretical strain threshold and the actual measured value of each monitoring point in the target data set. When the deviation rate exceeds the first preset threshold, generate a fault warning message and mark the precise longitude and latitude coordinates of the potential fault point.

2. The on-line fault diagnosis and location method for submarine cables based on optical fiber sensing technology according to claim 1, characterized in that: The original data set includes strain amplitude, strain change rate, temperature compensation coefficient, and vibration characteristic parameters; The target data set includes the three-dimensional space coordinates of the submarine cable, a strain distribution heat map, and a fault characteristic fingerprint; Among them, the color of the warning area in the fault diagnosis layer gradually changes according to the preset color scale rule according to the strain anomaly degree, and the area of the warning area is in a direct proportional relationship with the strain anomaly range.

3. The on-line fault diagnosis and location method of submarine cable based on optical fiber sensing technology according to claim 2, characterized in that The step of obtaining the real-time strain data stream of the submarine cable through a distributed optical fiber strain measurement device and using the signal processing module of the distributed optical fiber strain measurement device to extract the original data set including strain amplitude, strain change rate, temperature compensation coefficient, and vibration characteristic parameters is specifically as follows: Collect the fiber backscattering spectrum through the Brillouin optical time domain analysis module of the distributed optical fiber strain measurement device; Analyze the frequency shift amount, power spectral width, and signal-to-noise ratio parameters in the backscattering spectrum; For the section containing abnormal vibration characteristics, extract its vibration frequency spectrum characteristics and time-domain energy distribution; Convert the analysis result into a structured data set including time stamp, spatial position coding, strain tensor matrix, temperature compensation coefficient, and vibration eigenvector.

4. The on-line fault diagnosis and location method for submarine cables based on fiber optic sensing technology according to claim 3, characterized in that The step of performing coordinate mapping on the target data set and the geographic information system of the submarine cable laying route to generate a fault diagnosis layer with multi-dimensional visualization features is specifically as follows: Set the color gradient according to the strain anomaly degree, so that each additional standard deviation corresponds to an adjustment of the preset color scale value; Add a periodic flashing mark to the section with historical maintenance records, and the flashing frequency is positively correlated with the number of maintenance times; Draw a dynamic warning boundary at the boundary of the section with potential anchor damage risk, and the flashing interval of the boundary is dynamically adjusted according to the real-time sea current speed; The spatial interpolation algorithm is used to grid the data of discrete monitoring points, and a composite logo containing strain change trend arrows and risk level scores is superimposed on each grid cell.

5. The on-line fault diagnosis and location method of submarine cable based on optical fiber sensing technology according to claim 4, characterized in that, Based on the material parameters, laying years and real-time marine environmental data of the submarine cable, the deviation rate between the strain theoretical threshold and the actual measured value of each monitoring point is calculated, and when the deviation rate exceeds the first preset threshold, fault warning information is generated and the precise latitude and longitude coordinates of the potential fault point are marked, specifically: When the strain change rate detected exceeds the preset multiple of the material fatigue coefficient, it is marked as a material aging risk; For monitoring points located in the seabed geological activity zone, the deviation between the strain accumulation and the geological settlement model is calculated, and when the deviation exceeds a second preset threshold, it is marked as affected by geological activity; When the strain gradient of adjacent monitoring points exceeds the preset ratio of the cable bending radius limit, a mechanical damage warning is triggered; The strain residual after temperature compensation is statistically analyzed, and when the residual standard deviation exceeds a third preset threshold, it is marked as an abnormality of the optical fiber sensing system.

6. The on-line fault diagnosis and location method for submarine cables based on optical fiber sensing technology according to claim 2, characterized in that, The method further comprises: Establishing a data synchronization channel with multiple submarine cable monitoring stations to obtain strain measurement data and environmental monitoring data of the multiple submarine cable monitoring stations in real time; Displaying comparative thermal maps of the plurality of monitoring stations side by side on the geographic information system interface, wherein the comparative thermal maps are superimposed to display strain distribution difference areas of the plurality of monitoring stations; When abnormal strain is detected in a specific section, a set of environmental parameters of the section is extracted, historical fault cases are matched based on parameter similarity, and maintenance strategy recommendations are generated.

7. A method for online diagnosis and location of submarine cable faults based on optical fiber sensing technology according to claim 2, characterized in that, The method further comprises: Capturing visual inspection data of submarine cables using autonomous underwater robots at preset inspection cycles; According to the spatial alignment result of the visual inspection data and the strain measurement data, a first sampling density strategy is implemented for the high-risk section, and a second sampling density strategy is implemented for other sections; When it is detected that the duration of the abnormality in the same section exceeds a first preset time threshold, the strain evolution history record of the section is displayed on the interactive fault analysis panel, and the corresponding laying parameters in the submarine cable completion drawing are located; The cable health index is calculated based on the strain spatial distribution characteristics. When the index exceeds the preset risk threshold, a decision recommendation including maintenance priority sorting and maintenance plan selection is generated.

8. The on-line fault diagnosis and location method for submarine cables based on optical fiber sensing technology according to claim 2, characterized in that, The method further comprises: Establish a database for the entire life cycle of submarine cables to record strain baseline data, fault characteristics and corresponding maintenance records after each maintenance; When it is detected that the similarity between the current strain abnormality characteristics and the historical fault cases exceeds the preset similarity threshold, the associated historical maintenance plan and verification test data are pushed; Construct a time series prediction model based on deep learning, input the current strain time series data and environmental parameter set into the prediction model, and output the potential fault type identification and its occurrence probability; Verify the effectiveness and implementation cost of the maintenance suggestions in a simulated environment. After verification, send them to the relevant responsible units through the operation and maintenance management system.

9. An on-line fault diagnosis and location system for submarine cables based on optical fiber sensing technology, characterized in that, The system is used to implement the method for online diagnosis and positioning of submarine cable faults based on optical fiber sensing technology as described in any one of claims 1 to 8, comprising: A data extraction unit, configured to obtain real-time strain data streams of submarine cables through a distributed optical fiber strain measurement device, and extract an original data set from the strain data streams by using a signal processing module of the distributed optical fiber strain measurement device; A target data set construction unit, configured to perform spatio-temporal alignment and outlier correction processing on the original data set to construct a target data set; A mapping unit, configured to perform coordinate mapping on the target data set and a geographic information system of the submarine cable laying route to generate a fault diagnosis layer with multi-dimensional visualization features; A display unit, configured to generate an interactive fault analysis panel on the geographic information system interface, and display the submarine cable burial depth information, the strain historical change curve, the deviation value from the nearest maintenance record, and the surrounding marine environment parameters of the currently selected section when detecting a selected operation of an operator on the fault diagnosis layer; An early warning unit, configured to calculate the deviation rate between the theoretical strain threshold and the actual measured value of each monitoring point in the target data set based on the material parameters, laying years, and real-time marine environment data of the submarine cable, and generate a fault early warning message and mark the accurate longitude and latitude coordinates of potential fault points when the deviation rate exceeds a first preset threshold.

10. The online diagnosis and location system for submarine cable faults based on optical fiber sensing technology according to claim 9, characterized in that, The original data set includes strain amplitude, strain change rate, temperature compensation coefficient, and vibration characteristic parameters; The original data set includes the three-dimensional spatial coordinates of the submarine cable, the strain distribution heat map, and the fault characteristic fingerprint; Wherein the color of the early warning area in the fault diagnosis layer gradually changes according to a preset color scale rule according to the strain anomaly degree, and the area of the early warning area is in a direct proportional relationship with the strain anomaly range.

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