Optical cable resource management method and device based on multi-source data, equipment and medium

Abstract

This invention discloses a method, apparatus, equipment, and medium for optical cable resource management based on multi-source data. The method includes: acquiring multi-source data on optical cables and constructing a three-dimensional distribution map of optical cable resources in a utility tunnel based on the multi-source data; acquiring historical optical cable laying records and identifying missing optical cable segments based on the three-dimensional distribution map of optical cable resources in the utility tunnel and the historical optical cable laying records; acquiring and analyzing monitoring data of the missing optical cable segments and load change data of the backhaul optical cables of base stations around the missing optical cable segments to determine optical cable segments with layout changes and abnormal handover time points; identifying high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time points; and generating a list of optical cable segments with unclear responsibility and an integrity verification report for the high-risk areas. This invention can improve the accuracy and effectiveness of optical cable resource management.

Description

Technical Field

[0001] This invention relates to the field of information management technology, and in particular to a method, apparatus, equipment and medium for optical cable resource management based on multi-source data. Background Technology

[0002] As a core component of modern urban infrastructure, the renovation and management of urban underground utility tunnels directly impact the stable operation of communication networks and the continuous optimization of urban functions. Among these, the management of optical fiber resources is particularly crucial due to their concealed and complex nature. With the acceleration of urbanization, the need for optical fiber relocation and low-voltage network reconstruction within underground utility tunnels is increasingly prominent. Ensuring accurate verification of optical fiber resources and clear attribution of responsibility has become an important issue in enhancing urban communication resilience. However, existing optical fiber resource management relies heavily on manual inspections and traditional two-dimensional drawings, which are not only inefficient but also fail to fully reflect the true condition of the optical fibers within the tunnels. This is especially problematic when there are frequent handovers between construction units or multi-party collaborations, leading to issues such as delayed data updates and missing records. These limitations result in discrepancies between the information in the optical fiber resource management system and the physical reality, increasing the difficulty and risk of network maintenance. Summary of the Invention

[0003] To address the above technical problems, this invention provides a method, apparatus, device, and medium for optical cable resource management based on multi-source data, which can improve the accuracy and effectiveness of optical cable resource management.

[0004] This invention provides a method for managing optical cable resources based on multi-source data, including:

[0005] Acquire multi-source data of optical cables and construct a three-dimensional distribution map of optical cable resources in the underground utility tunnel based on the multi-source data; the multi-source data includes optical cable migration data in the underground utility tunnel renovation, municipal engineering progress data, and optical cable monitoring data;

[0006] Historical optical cable laying records are obtained, and based on the three-dimensional distribution map of optical cable resources in the utility tunnel, missing optical cable segments are identified according to the historical optical cable laying records.

[0007] The monitoring data of the missing optical cable section and the load change data of the backhaul optical cable of the base station around the optical cable section are obtained and analyzed to determine the optical cable section with layout changes and the time point of abnormal handover.

[0008] Based on the municipal engineering progress data corresponding to the abnormal handover time points, high-risk areas are identified.

[0009] For the high-risk areas, a list of optical cable segments with unclear responsibility and an integrity verification report are generated.

[0010] As an improvement to the above solution, the step of constructing a three-dimensional distribution map of optical cable resources in the utility tunnel based on the multi-source data includes:

[0011] The multi-source data is cleaned to obtain a structured dataset containing fields for optical cable number, optical cable length, and optical cable location.

[0012] Using 3D modeling technology, the optical cable locations are converted into spatial coordinates based on the structured dataset to generate a 3D distribution map of optical cable resources in the utility tunnel.

[0013] As an improvement to the above solution, the step of identifying missing optical cable segments based on the three-dimensional distribution map of the optical cable resources in the utility tunnel and according to the historical optical cable laying records includes:

[0014] The historical optical cable laying records are analyzed to obtain the actual route segments;

[0015] By comparing the actual route segment with the optical cable segment in the three-dimensional distribution map of optical cable resources in the utility tunnel, the missing optical cable segment is obtained.

[0016] As an improvement to the above solution, the step of acquiring and analyzing monitoring data of the missing optical cable segment and load change data of the backhaul optical cable of the base station around the optical cable segment to determine the optical cable segment with layout changes and the time point of abnormal handover includes:

[0017] Acquire monitoring data of the missing section of the optical cable, and determine the location of the abnormal state in the missing section of the optical cable based on the monitoring data of the missing section of the optical cable;

[0018] Obtain historical inspection images of the locations with abnormal status, and extract the historical optical cable layout from the historical inspection images;

[0019] Obtain the current optical cable thermal image of the location of the abnormal state, and extract the current optical cable layout from the current optical cable thermal image;

[0020] Based on the historical optical cable layout and the current optical cable layout, determine the optical cable segments with layout changes;

[0021] Obtain load change data of the backhaul optical cables of base stations around the optical cable segment with the described layout change;

[0022] The handover anomaly time point is determined based on the load change data.

[0023] As an improvement to the above solution, determining the handover anomaly time point based on the load change data includes:

[0024] Perform time series analysis on the load change data to generate load change curves;

[0025] By analyzing the correlation between the load change curve and the optical cable layout changes, load change patterns and temporal characteristics are extracted;

[0026] Based on the load change pattern and the time characteristics, abnormal time points are selected;

[0027] Based on the abnormal time point, the construction log records for the corresponding time period are retrieved and compared. If the load change at the abnormal time point does not match the construction log records, then the abnormal time point is taken as the handover abnormal time point.

[0028] As an improvement to the above solution, the step of identifying high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time points includes:

[0029] Based on the municipal engineering progress data corresponding to the abnormal handover time points, generate time-series data containing road segment identifiers;

[0030] Based on the time series data, the risk level of each optical cable segment is calculated using the random forest algorithm, and the optical cable segments with a risk level greater than a preset threshold are identified as high-risk optical cable segments.

[0031] Based on the three-dimensional distribution map of optical cable resources in the utility tunnel, and according to the high-risk optical cable segments and the progress data of the municipal engineering project, an integrity risk map of optical cable resources based on road segments and time dimensions is generated to obtain high-risk areas.

[0032] As an improvement to the above solution, the generation of a list of optical cable segments with unclear responsibility and an integrity verification report for the high-risk areas includes:

[0033] Based on the optical cable inspection data and property maintenance records corresponding to the high-risk areas, a data consistency check was performed to determine the missing parts of the records;

[0034] The optical cable segment corresponding to the missing part of the record is marked as the first optical cable segment;

[0035] Based on the first optical cable segment, data matching is performed in the preset responsibility database to filter out the first optical cable segment with no matching data, and the second optical cable segment is obtained.

[0036] Feature analysis was performed on the second optical cable segment to determine the potential correlation between optical cable segments in high-risk areas;

[0037] Based on the second optical cable segment and the potential association, a list of optical cable segments with unclear responsibility is generated;

[0038] Anomalies are extracted from the list of optical cable segments with unclear responsibility, and a preliminary optical cable existence map is generated based on the infrared scanning results of the anomalies.

[0039] Based on the preliminary optical cable existence diagram, analyze the physical state of the optical cable and mark the areas with abnormal physical states as areas to be verified.

[0040] Historical inspection photos of the area to be verified are obtained, and the historical inspection photos of the area to be verified are fused with infrared scanning results to generate an enhanced evidence map;

[0041] Based on the list of optical cable segments with unclear responsibility and the enhanced evidence diagram, an integrity verification report for the optical cable is generated.

[0042] This invention also provides an optical cable resource management device based on multi-source data, comprising:

[0043] The distribution map construction module is used to acquire multi-source data of optical cables and construct a three-dimensional distribution map of optical cable resources in the underground utility tunnel based on the multi-source data; the multi-source data includes optical cable migration data in the underground utility tunnel renovation, municipal engineering progress data, and optical cable monitoring data;

[0044] The missing segment identification module is used to obtain historical optical cable laying records and, based on the three-dimensional distribution map of optical cable resources in the utility tunnel, identify missing optical cable segments according to the historical optical cable laying records.

[0045] The handover anomaly identification module is used to acquire and analyze the monitoring data of the missing optical cable segment and the load change data of the backhaul optical cable of the base station around the optical cable segment to determine the optical cable segment with layout changes and the time point of the handover anomaly.

[0046] The risk area identification module is used to identify high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time points;

[0047] The verification report generation module is used to generate a list of optical cable segments with unclear responsibility and an integrity verification report for the high-risk areas.

[0048] This invention also provides a computer device, including a processor and a memory, wherein the memory stores a computer program and the computer program is configured to be executed by the processor, and the processor executes the computer program to implement the optical cable resource management method based on multi-source data described above.

[0049] This invention also provides a computer-readable storage medium storing a computer program, wherein the computer program, when running, controls the device where the computer-readable storage medium is located to execute the optical cable resource management method based on multi-source data described above.

[0050] Compared with existing technologies, the beneficial effects of the optical cable resource management method, device, equipment, and medium based on multi-source data provided in this invention are as follows: By acquiring multi-source data of optical cables and constructing a three-dimensional distribution map of optical cable resources in the utility tunnel based on the multi-source data, historical optical cable laying records are obtained. Based on the three-dimensional distribution map of optical cable resources in the utility tunnel, missing optical cable segments are identified according to the historical optical cable laying records. Monitoring data of missing optical cable segments and load change data of backhaul optical cables of base stations around the missing optical cable segments are acquired and analyzed to determine optical cable segments with layout changes and abnormal handover time points. High-risk areas are identified based on the municipal engineering progress data corresponding to the abnormal handover time points. For high-risk areas, a list of optical cable segments with unclear responsibility and an integrity verification report are generated. This invention integrates steps such as multi-source data fusion, spatial modeling, missing detection, time series analysis, and risk identification, realizing the visualized management, efficient positioning, and integrity verification of underground optical cable resources by the resource management system, improving resource control and operation and maintenance efficiency, and ensuring the accuracy and timeliness of optical cable resource management. Attached Figure Description

[0051] Figure 1 This is a flowchart illustrating a method for managing optical cable resources based on multi-source data, provided in an embodiment of the present invention.

[0052] Figure 2 This is a schematic diagram of the structure of an optical cable resource management device based on multi-source data provided in an embodiment of the present invention;

[0053] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0054] 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.

[0055] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for managing optical fiber resources based on multi-source data, provided in an embodiment of the present invention. The method for managing optical fiber resources based on multi-source data includes:

[0056] S1: Acquire multi-source data of optical cables and construct a three-dimensional distribution map of optical cable resources in the underground utility tunnel based on the multi-source data; the multi-source data includes optical cable migration data in the underground utility tunnel renovation, municipal engineering progress data, and optical cable monitoring data;

[0057] Specifically, multi-source data on optical cables can be collected through resource management systems, on-site surveys, or equipment logs. Optical cable monitoring data includes operational information for various types of optical cables within the utility tunnel, including both relocated and non-relocated cables.

[0058] As one optional embodiment, constructing a three-dimensional distribution map of optical cable resources in the utility tunnel based on the multi-source data includes:

[0059] The multi-source data is cleaned to obtain a structured dataset containing fields for optical cable number, optical cable length, and optical cable location.

[0060] Using 3D modeling technology, the optical cable locations are converted into spatial coordinates based on the structured dataset to generate a 3D distribution map of optical cable resources in the utility tunnel.

[0061] In a specific example, for a utility tunnel project in a certain area, multi-source data on optical cables is acquired. This includes cable migration data (cable number 01, 5000 meters long, starting point A, ending point B); municipal engineering progress data recording the start and expected completion dates; and cable monitoring data including sensor-collected cable temperature and stress values. This data undergoes data cleaning, such as removing duplicates and outliers and filling in missing values, to create a structured dataset containing fields such as cable number, length, and location. Then, using 3D modeling technology and GIS software, the cable locations are converted into spatial coordinates. For example, the starting coordinates of a cable segment are (x1, y1, z1), and the ending coordinates are (x2, y2, z2). 3D rendering is then used to create a visualized distribution map, resulting in a 3D distribution map of the utility tunnel's optical cable resources in that area. This map includes the distribution information of all optical cables within the utility tunnel.

[0062] S2: Obtain historical optical cable laying records, and based on the three-dimensional distribution map of optical cable resources in the utility tunnel, identify the missing optical cable segments according to the historical optical cable laying records;

[0063] As one optional embodiment, the step of identifying missing optical cable segments based on the three-dimensional distribution map of the optical cable resources in the utility tunnel and according to the historical optical cable laying records includes:

[0064] The historical optical cable laying records are analyzed to obtain the actual route segments;

[0065] By comparing the actual route segment with the optical cable segment in the three-dimensional distribution map of optical cable resources in the utility tunnel, the missing optical cable segment is obtained.

[0066] Specifically, an actual route segment refers to a section of the actual path of the optical cable, such as the path between one equipment site or splice point and another. Historical optical cable laying records contain information on the cable's starting point, ending point, and approximate path, derived from archival records or early manual surveys during the cable laying process. When generating actual route segments using parsing technology, one possible approach is to digitize this record data. For example, scanning paper maps and using image recognition technology to extract the optical cable path, then combining this data with a GIS system to generate specific route segments. For instance, assuming an optical cable record shows a total length of 5 kilometers from point A to point B, parsing can generate several route segments, such as a 1-kilometer segment from A to C, a 2-kilometer segment from C to D, etc.

[0067] Furthermore, by comparing the actual route segment with the optical cable segment information in the 3D distribution map of optical cable resources in the utility tunnel, the discrepancy between the two can be obtained, revealing the missing optical cable segments and connection point information in the 3D distribution map of optical cable resources in the utility tunnel. For example, the distribution map shows that the optical cable from A to B is a single 5-kilometer segment, while the actual route segment data shows that the segment is divided into 3 segments, with a total length of 5 kilometers, but the intermediate nodes C and D are not recorded. The missing optical cable segment CD can be extracted, i.e., the missing optical cable segment.

[0068] In some optional embodiments, after obtaining the missing section of optical cable, the method further includes: obtaining the connection points at both ends of the missing section of optical cable, and determining the connection point as a manhole cover location or an optical distribution box location based on the matching of the optical cable location with the manhole cover location and the optical distribution box location, so as to update the three-dimensional distribution map of optical cable resources in the utility tunnel.

[0069] Specifically, by matching the locations of the connection points at both ends of the missing optical cable section with the locations of the manhole cover and optical distribution box, the connection point is determined to be either a manhole cover or an optical distribution box, and then updated to the three-dimensional distribution map of optical cable resources in the utility tunnel to facilitate subsequent maintenance and troubleshooting.

[0070] S3: Analyze the monitoring data of the missing optical cable section and the load change data of the backhaul optical cable of the base station around the optical cable section to determine the optical cable section with layout changes and the abnormal handover time point.

[0071] As one optional embodiment, the step of acquiring and analyzing monitoring data of the missing optical cable segment and load change data of the backhaul optical cables of base stations around the optical cable segment to determine the optical cable segment with layout changes and the time point of abnormal handover includes:

[0072] Acquire monitoring data of the missing section of the optical cable, and determine the location of the abnormal state in the missing section of the optical cable based on the monitoring data of the missing section of the optical cable;

[0073] Obtain historical inspection images of the locations with abnormal status, and extract the historical optical cable layout from the historical inspection images;

[0074] Obtain the current optical cable thermal image of the location of the abnormal state, and extract the current optical cable layout from the current optical cable thermal image;

[0075] Based on the historical optical cable layout and the current optical cable layout, determine the optical cable segments with layout changes;

[0076] Obtain load change data of the backhaul optical cables of base stations around the optical cable segment with the described layout change;

[0077] The handover anomaly time point is determined based on the load change data.

[0078] Specifically, monitoring data on missing sections of the optical cable is acquired, and real-time status is collected through sensors to obtain the current status information of the optical cable connection. Sensors are typically deployed at key nodes along the optical cable to collect real-time status information such as temperature and stress. For example, in a city's optical cable network, sensors record data every hour, showing that the temperature of a certain section of the optical cable is 40 degrees Celsius and the stress value is 50 Newtons.

[0079] The system extracts the operating parameters of the physical optical cable from the current status information. By comparing these parameters with preset standard parameters, it determines whether there are any abnormal points and obtains the coordinates of these abnormal points in the actual route, thus determining the location of the abnormality. For example, if the operating parameter is an optical attenuation value, assuming the standard optical attenuation value is 0.2 dB / km, and a certain section has a measured value of 0.5 dB / km, exceeding the preset threshold, it indicates a possible abnormality. The abnormal point is then located by combining GPS and the optical cable route map. Furthermore, after obtaining the abnormal points, they are prioritized according to the magnitude of their operating parameters, with higher-priority abnormal points being processed first.

[0080] Furthermore, based on the location of the abnormal status, corresponding historical inspection images are obtained from the historical training database, and the optical cable layout information in the historical inspection images is extracted to obtain the historical optical cable layout. Specifically, the historical inspection images include the wiring of the optical cable in the manhole cover or optical distribution box, recording the physical state at that time; when extracting the optical cable layout information from the historical inspection images, edge detection technology can be used to identify the direction and connection point location of the optical cable to obtain detailed layout feature data.

[0081] Furthermore, the current optical cable thermal image, captured by an infrared camera, shows the temperature distribution of the cable; for example, the middle section of a cable appears as a red high-temperature zone, while the two ends are blue low-temperature zones. Image processing techniques are then used to extract the current optical cable layout from the thermal image.

[0082] Furthermore, by comparing the historical and current optical cable layouts, segments of optical cable whose layouts have changed are extracted. Specifically, if a segment of optical cable in the current layout deviates from its position or length by more than a preset threshold compared to the historical layout, the layout of that segment is considered to have changed. Preferably, the layout change includes temperature-related changes. That is, by comparing the historical and current optical cable layouts, it is found that the connection point positions in the historical layout remain unchanged, but the current thermal imaging shows that the high-temperature area deviates from the uniform distribution of the original layout. For example, in the historical layout, the temperature was uniformly distributed at around 25 degrees Celsius, but in the current layout, the high-temperature area reaches 50 degrees Celsius and the low-temperature area is 20 degrees Celsius. The layout of this segment of optical cable is determined to have changed by using a threshold. This temperature anomaly may be caused by optical cable aging or external pressure. Through trend analysis, if the range of the high-temperature area expands month by month, the potential risk point may evolve into the risk of fiber breakage. This analysis helps to provide early warning.

[0083] As one optional embodiment, determining the handover anomaly time point based on the load change data includes:

[0084] Perform time series analysis on the load change data to generate load change curves;

[0085] By analyzing the correlation between the load change curve and the optical cable layout changes, load change patterns and temporal characteristics are extracted;

[0086] Based on the load change pattern and the time characteristics, abnormal time points are selected;

[0087] Based on the abnormal time point, the construction log records for the corresponding time period are retrieved and compared. If the load change at the abnormal time point does not match the construction log records, then the abnormal time point is taken as the handover abnormal time point.

[0088] Specifically, when obtaining load data of the backhaul optical cables of surrounding base stations due to changes in optical cable layout, traffic records for a specified time period can be extracted from the network management system through database queries. For example, assuming that the optical cable layout in a certain area has changed, the backhaul optical cable load data of three surrounding base stations for the past 30 days can be queried to form a load data set, which includes hourly traffic peaks to reflect the operating status of the base stations.

[0089] Furthermore, based on the load change data, time series analysis is used to plot the load change curve. Specifically, the load data can be arranged in chronological order to generate a line graph. For example, if the load of a base station gradually increases from 450Mbps on Monday to 700Mbps on Friday, the curve will show an upward trend. This method intuitively reflects the change in load over time, facilitating subsequent analysis.

[0090] Furthermore, the correlation between load change curves and optical cable layout changes is analyzed to extract load change patterns and temporal characteristics. Specifically, the correlation coefficient between the load change curves and optical cable layout change data is calculated, which measures the correlation between the two. For example, if after the optical cable layout adjustment, the load curve of one base station increases sharply while the load of another base station remains stable, the calculated correlation coefficients are 0.85 and 0.2, respectively, indicating that the layout change has a greater impact on the former, which also represents different load change patterns. By analyzing the correlation between load change curves and optical cable layout changes, regular features are extracted to obtain temporal characteristics, such as data fluctuation cycles and peak times of the load change curve, for subsequent prediction and analysis. Then, based on the extracted load change patterns and temporal characteristics, abnormal time points are screened. When the optical cable layout changes, its corresponding temporal characteristics usually change as well. Abnormal time points are identified by judging whether the temporal characteristics exceed the corresponding preset thresholds. If the construction log does not contain the optical cable handover record corresponding to the abnormal time point, or the record content is inconsistent with the load change, then the abnormal time point is determined as a handover abnormal time point.

[0091] S4: Based on the municipal engineering progress data corresponding to the abnormal handover time points, high-risk areas are identified;

[0092] As one optional embodiment, identifying high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time point includes:

[0093] Based on the municipal engineering progress data corresponding to the abnormal handover time points, generate time series data containing road segment identifiers;

[0094] Based on the time series data, the risk level of each optical cable segment is calculated using the random forest algorithm, and the optical cable segments with a risk level greater than a preset threshold are identified as high-risk optical cable segments.

[0095] Based on the three-dimensional distribution map of optical cable resources in the utility tunnel, and according to the high-risk optical cable segments and the progress data of the municipal engineering project, an integrity risk map of optical cable resources based on road segments and time dimensions is generated to obtain high-risk areas.

[0096] Specifically, by matching and integrating abnormal handover time points with corresponding municipal engineering progress data, time-series data containing road segment identifiers is obtained. This time-series data is a series of data points arranged chronologically. It mainly includes information related to municipal engineering progress, fiber optic cable load changes, and time-stamped data corresponding to fiber optic cable status and events. This data reflects the changes in the fiber optic cable's operating environment and its own status over time from different perspectives. Furthermore, features in the time-series data, such as construction duration, road segment traffic flow, and historical abnormal frequency, are used as input. A random forest algorithm is employed to calculate the risk level of each fiber optic cable segment, determining the risk level distribution. Fiber optic cable segments with risk levels exceeding a preset threshold are designated as high-risk segments. For example, taking fiber optic cable segment A as an example, assuming a construction duration of 5 days, an average daily traffic flow of 1000 times, and an abnormal frequency of 3 times per month, the random forest algorithm outputs a risk level of 0.75. If the preset threshold is 0.6, then this fiber optic cable segment is determined to be a high-risk segment.

[0097] Furthermore, a dataset containing time, road segment (corresponding to optical cable segment), and project type is generated based on the progress data of high-risk optical cable segments and municipal engineering projects. Then, based on the three-dimensional distribution map of optical cable resources in the utility tunnel, this dataset is mapped to the road segment dimension and the time dimension to generate an optical cable resource integrity risk map based on the road segment and time dimensions, thereby obtaining high-risk areas.

[0098] S5: For the high-risk areas, generate a list of optical cable segments with unclear responsibility and an integrity verification report.

[0099] As one optional embodiment, generating a list of optical cable segments with unclear responsibility and an integrity verification report for the high-risk area includes:

[0100] Based on the optical cable inspection data and property maintenance records corresponding to the high-risk areas, a data consistency check was performed to determine the missing parts of the records;

[0101] The optical cable segment corresponding to the missing part of the record is marked as the first optical cable segment;

[0102] Based on the first optical cable segment, data matching is performed in the preset responsibility database to filter out the first optical cable segment with no matching data, and the second optical cable segment is obtained.

[0103] Feature analysis was performed on the second optical cable segment to determine the potential correlation between optical cable segments in high-risk areas;

[0104] Based on the second optical cable segment and the potential association, a list of optical cable segments with unclear responsibility is generated;

[0105] Anomalies are extracted from the list of optical cable segments with unclear responsibility, and a preliminary optical cable existence map is generated based on the infrared scanning results of the anomalies.

[0106] Based on the preliminary optical cable existence diagram, analyze the physical state of the optical cable and mark the areas with abnormal physical states as areas to be verified.

[0107] Historical inspection photos of the area to be verified are obtained, and the historical inspection photos of the area to be verified are fused with infrared scanning results to generate an enhanced evidence map;

[0108] Based on the list of optical cable segments with unclear responsibility and the enhanced evidence diagram, an integrity verification report for the optical cable is generated.

[0109] Specifically, for high-risk areas, the corresponding fiber optic cable inspection data and property maintenance records are obtained, including information such as fiber optic cable temperature, signal attenuation rate, and maintenance reporting time. By judging data consistency, missing records are identified to determine the first fiber optic cable segment. For example, if the inspection data records an abnormal temperature rise of 50 degrees Celsius for a certain fiber optic cable segment, while the maintenance record shows that users reported network outages during the same period, then the two data are consistent. If five signal attenuation anomalies are detected, but the maintenance record only shows three, it means that two anomalies were not perceived by users, and these are identified as missing records.

[0110] Furthermore, the responsibility database records the responsible unit for each optical cable segment, such as the operator or property management company. If a segment of the first optical cable segment does not match the corresponding responsibility, it is marked as having unclear responsibility, thus obtaining the second optical cable segment.

[0111] Furthermore, when performing feature analysis on the second optical cable segment, a random forest algorithm can be used to determine potential correlations based on input features such as cable length, service life, and anomaly frequency. Spatiotemporal clustering algorithms or association rule mining methods can also be employed to analyze the potential correlations of optical cable segments within high-risk areas. Subsequently, based on the second optical cable segment and its potential correlations, a list of optical cable segments with unclear responsibility is generated, demonstrating the distribution of such segments within high-risk areas. For example, if analysis reveals that two optical cable segments experienced anomalies close in time and are located near the same manhole cover, this could be a potential correlation caused by manhole cover construction, leading to the generation of the final optical cable segment list. This embodiment of the invention effectively locates problem areas and clarifies situations where responsibility is unclear, providing a clear direction for subsequent maintenance. Furthermore, dynamically updating the list enhances the timeliness of risk prevention and control.

[0112] Furthermore, anomalies are extracted from a list of optical cable segments with unclear attribution based on preset screening criteria. These criteria are set according to the anomaly type, such as signal attenuation exceeding 20 dB or temperature exceeding 45 degrees Celsius. Infrared scanning results of the anomalies are obtained using an infrared thermal imager to determine the surface temperature distribution of the optical cable. Then, image processing technology is used to generate a preliminary optical cable presence map for analyzing the physical condition of the cable. Areas with abnormal physical conditions, such as excessively high temperatures or structural deformation, are selected and marked as areas to be verified. For example, if the preliminary optical cable presence map of an anomaly shows a high-temperature band length of 5 meters, exceeding the normal range, it is marked as an area to be verified. Similarly, if the preliminary optical cable presence map of an anomaly shows a broken optical cable outline, it is also marked as an area to be verified, which helps to focus on problem areas.

[0113] Furthermore, historical inspection photos of the area to be verified are obtained. By comparing and fusing these historical inspection photos with infrared scan images, an enhanced evidence map is generated. This map overlays damage markers and temperature distribution, visually reflecting the severity of the problem. Finally, based on the list of fiber optic cable segments with unclear responsibility and the enhanced evidence map, a fiber optic cable integrity verification report is generated. The report displays the integrity of different fiber optic cables. For example, the report lists the status distribution of 10 points, such as 3 damaged segments, 2 interrupted segments, and 5 normal segments. Point A is recorded as "Integrity: Damaged, Cause: Outer Sheath Damage + Overheating," and point B is recorded as "Integrity: Interrupted, Cause: Fracture." The enhanced evidence map in the report is used to locate the root cause of the problem, providing accurate information for maintenance. This invention effectively solves the problems of missing records and unclear responsibility in fiber optic cable resource management, improving the accuracy and efficiency of fiber optic cable resource management.

[0114] This invention acquires multi-source data on optical cables, constructs a three-dimensional distribution map of optical cable resources in utility tunnels based on the multi-source data, obtains historical optical cable laying records, and identifies missing optical cable segments based on the historical optical cable laying records according to the three-dimensional distribution map of optical cable resources in utility tunnels. It then analyzes monitoring data of the missing optical cable segments and load change data of the backhaul optical cables of base stations around the missing segments to determine optical cable segments with layout changes and abnormal handover time points. Based on the municipal engineering progress data corresponding to the abnormal handover time points, high-risk areas are identified. For high-risk areas, a list of optical cable segments with unclear responsibility and an integrity verification report are generated. This invention integrates multi-source data fusion, spatial modeling, missing cable detection, time-series analysis, and risk identification, realizing visualized management, efficient positioning, and integrity verification of underground optical cable resources by the resource management system. This improves resource control and operation and maintenance efficiency, and ensures the accuracy and timeliness of optical cable resource management.

[0115] Accordingly, the present invention also provides an optical cable resource management device based on multi-source data, which can realize all the processes of the optical cable resource management method based on multi-source data in the above embodiments.

[0116] Please see Figure 2 , Figure 2 This is a schematic diagram of a fiber optic cable resource management device based on multi-source data provided in an embodiment of the present invention. The fiber optic cable resource management device based on multi-source data includes:

[0117] The distribution map construction module 201 is used to acquire multi-source data of optical cables and construct a three-dimensional distribution map of optical cable resources in the underground utility tunnel based on the multi-source data; the multi-source data includes optical cable migration data in the underground utility tunnel renovation, municipal engineering progress data, and optical cable monitoring data;

[0118] The missing segment identification module 202 is used to acquire historical optical cable laying records and, based on the three-dimensional distribution map of optical cable resources in the utility tunnel, identify missing optical cable segments according to the historical optical cable laying records.

[0119] The handover anomaly identification module 203 is used to acquire and analyze the monitoring data of the missing optical cable segment and the load change data of the backhaul optical cable of the base station around the optical cable segment to determine the optical cable segment with layout changes and the handover anomaly time point.

[0120] The risk area identification module 204 is used to identify high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time point;

[0121] The verification report generation module 205 is used to generate a list of optical cable segments with unclear responsibility and an integrity verification report for the high-risk areas.

[0122] Preferably, constructing a three-dimensional distribution map of optical cable resources in the utility tunnel based on the multi-source data includes:

[0123] The multi-source data is cleaned to obtain a structured dataset containing fields for optical cable number, optical cable length, and optical cable location.

[0124] Using 3D modeling technology, the optical cable locations are converted into spatial coordinates based on the structured dataset to generate a 3D distribution map of optical cable resources in the utility tunnel.

[0125] Preferably, the step of identifying missing optical cable segments based on the three-dimensional distribution map of the optical cable resources in the utility tunnel and according to the historical optical cable laying records includes:

[0126] The historical optical cable laying records are analyzed to obtain the actual route segments;

[0127] By comparing the actual route segment with the optical cable segment in the three-dimensional distribution map of optical cable resources in the utility tunnel, the missing optical cable segment is obtained.

[0128] Preferably, the step of acquiring and analyzing monitoring data of the missing optical cable segment and load change data of the backhaul optical cables of base stations around the optical cable segment to determine the optical cable segment with layout changes and the time point of abnormal handover includes:

[0129] Acquire monitoring data of the missing section of the optical cable, and determine the location of the abnormal state in the missing section of the optical cable based on the monitoring data of the missing section of the optical cable;

[0130] Obtain historical inspection images of the locations with abnormal status, and extract the historical optical cable layout from the historical inspection images;

[0131] Obtain the current optical cable thermal image of the location of the abnormal state, and extract the current optical cable layout from the current optical cable thermal image;

[0132] Based on the historical optical cable layout and the current optical cable layout, determine the optical cable segments with layout changes;

[0133] Obtain load change data of the backhaul optical cables of base stations around the optical cable segment with the described layout change;

[0134] The handover anomaly time point is determined based on the load change data.

[0135] Preferably, determining the handover anomaly time point based on the load change data includes:

[0136] Perform time series analysis on the load change data to generate load change curves;

[0137] By analyzing the correlation between the load change curve and the optical cable layout changes, load change patterns and temporal characteristics are extracted;

[0138] Based on the load change pattern and the time characteristics, abnormal time points are selected;

[0139] Based on the abnormal time point, the construction log records for the corresponding time period are retrieved and compared. If the load change at the abnormal time point does not match the construction log records, then the abnormal time point is taken as the handover abnormal time point.

[0140] Preferably, identifying high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time points includes:

[0141] Based on the municipal engineering progress data corresponding to the abnormal handover time points, generate time-series data containing road segment identifiers;

[0142] Based on the time series data, the risk level of each optical cable segment is calculated using the random forest algorithm, and the optical cable segments with a risk level greater than a preset threshold are identified as high-risk optical cable segments.

[0143] Based on the three-dimensional distribution map of optical cable resources in the utility tunnel, and according to the high-risk optical cable segments and the progress data of the municipal engineering project, an integrity risk map of optical cable resources based on road segments and time dimensions is generated to obtain high-risk areas.

[0144] Preferably, generating a list of optical cable segments with unclear responsibility and an integrity verification report for the high-risk area includes:

[0145] Based on the optical cable inspection data and property maintenance records corresponding to the high-risk areas, a data consistency check was performed to determine the missing parts of the records;

[0146] The optical cable segment corresponding to the missing part of the record is marked as the first optical cable segment;

[0147] Based on the first optical cable segment, data matching is performed in the preset responsibility database to filter out the first optical cable segment with no matching data, and the second optical cable segment is obtained.

[0148] Feature analysis was performed on the second optical cable segment to determine the potential correlation between optical cable segments in high-risk areas;

[0149] Based on the second optical cable segment and the potential association, a list of optical cable segments with unclear responsibility is generated;

[0150] Anomalies are extracted from the list of optical cable segments with unclear responsibility, and a preliminary optical cable existence map is generated based on the infrared scanning results of the anomalies.

[0151] Based on the preliminary optical cable existence diagram, analyze the physical state of the optical cable and mark the areas with abnormal physical states as areas to be verified.

[0152] Historical inspection photos of the area to be verified are obtained, and the historical inspection photos of the area to be verified are fused with infrared scanning results to generate an enhanced evidence map;

[0153] Based on the list of optical cable segments with unclear responsibility and the enhanced evidence diagram, an integrity verification report for the optical cable is generated.

[0154] In specific implementation, the working principle, control process and technical effects of the optical cable resource management device based on multi-source data provided in the embodiments of the present invention are the same as those of the optical cable resource management method based on multi-source data in the above embodiments, and will not be repeated here.

[0155] See Figure 3 , Figure 3This is a structural block diagram of a computer device provided in an embodiment of the present invention. The computer device includes: a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program, it implements the steps in the above-described embodiment of the optical cable resource management method based on multi-source data. Alternatively, when the processor 301 executes the computer program, it implements the functions of each module / unit in the above-described device embodiments.

[0156] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 302 and executed by the processor 301 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the computer device.

[0157] The computer device may include, but is not limited to, processor 301 and memory 302. Those skilled in the art will understand that the schematic diagram is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than illustrated, or combine certain components, or different components. For example, the computer device may also include input / output devices, network access devices, buses, etc.

[0158] The processor 301 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 301 is the control center of the computer device, connecting various parts of the entire computer device through various interfaces and lines.

[0159] The memory 302 can be used to store the computer programs and / or modules. The processor 301 implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory 302 and calling the data stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0160] Wherein, if the modules / units integrated into the computer device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor 301, it can implement the steps of the various method embodiments described above. Wherein, the computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0161] This invention also provides a computer-readable storage medium, which includes a stored computer program, wherein the computer program, when running, controls the device where the computer-readable storage medium is located to execute the optical cable resource management method based on multi-source data described in any of the above embodiments.

[0162] This invention provides a method, apparatus, device, and storage medium for optical cable resource management based on multi-source data. Its advantages include: acquiring multi-source data on optical cables, constructing a three-dimensional distribution map of optical cable resources in utility tunnels based on the multi-source data, obtaining historical optical cable laying records, and identifying missing optical cable segments based on the historical optical cable laying records using the three-dimensional distribution map; analyzing monitoring data of the missing optical cable segments and load change data of the backhaul optical cables of base stations around the missing segments to determine optical cable segments with layout changes and abnormal handover time points; identifying high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time points; and generating a list of optical cable segments with unclear responsibility and an integrity verification report for high-risk areas. This invention integrates multi-source data fusion, spatial modeling, missing cable detection, time-series analysis, and risk identification, realizing visualized management, efficient positioning, and integrity verification of underground optical cable resources by the resource management system, improving resource control and operation and maintenance efficiency, and ensuring the accuracy and timeliness of optical cable resource management.

[0163] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for managing optical cable resources based on multi-source data, characterized in that, include: Acquire multi-source data of optical cables and construct a three-dimensional distribution map of optical cable resources in the utility tunnel based on the multi-source data; The multi-source data includes fiber optic cable relocation data during the underground utility tunnel renovation, municipal engineering progress data, and fiber optic cable monitoring data. Historical optical cable laying records are obtained, and based on the three-dimensional distribution map of optical cable resources in the utility tunnel, missing optical cable segments are identified according to the historical optical cable laying records. The monitoring data of the missing optical cable section and the load change data of the backhaul optical cable of the base station around the optical cable section are obtained and analyzed to determine the optical cable section with layout changes and the time point of abnormal handover. Based on the municipal engineering progress data corresponding to the abnormal handover time points, high-risk areas are identified. For the high-risk areas, a list of optical cable segments with unclear responsibility and an integrity verification report are generated; The process of acquiring and analyzing monitoring data of the missing optical cable segment and load change data of the backhaul optical cables of base stations around the optical cable segment to determine the optical cable segments with layout changes and abnormal handover time points includes: Acquire monitoring data of the missing section of the optical cable, and determine the location of the abnormal state in the missing section of the optical cable based on the monitoring data of the missing section of the optical cable; Obtain historical inspection images of the locations with abnormal status, and extract the historical optical cable layout from the historical inspection images; Obtain the current optical cable thermal image of the location of the abnormal state, and extract the current optical cable layout from the current optical cable thermal image; Based on the historical optical cable layout and the current optical cable layout, determine the optical cable segments with layout changes; Obtain load change data of the backhaul optical cables of base stations around the optical cable segment with the described layout change; Determine the abnormal handover time point based on the load change data; The step of determining the handover anomaly time point based on the load change data includes: Perform time series analysis on the load change data to generate load change curves; By analyzing the correlation between the load change curve and the optical cable layout changes, load change patterns and temporal characteristics are extracted; Based on the load change pattern and the time characteristics, abnormal time points are selected; Based on the abnormal time point, the construction log records for the corresponding time period are retrieved and compared. If the load change at the abnormal time point does not match the construction log records, then the abnormal time point is taken as the handover abnormal time point.

2. The optical cable resource management method based on multi-source data as described in claim 1, characterized in that, The construction of a three-dimensional distribution map of optical cable resources in the utility tunnel based on the multi-source data includes: The multi-source data is cleaned to obtain a structured dataset containing fields for optical cable number, optical cable length, and optical cable location. Using 3D modeling technology, the optical cable locations are converted into spatial coordinates based on the structured dataset to generate a 3D distribution map of optical cable resources in the utility tunnel.

3. The optical cable resource management method based on multi-source data as described in claim 1, characterized in that, The method of identifying missing optical cable segments based on the three-dimensional distribution map of the optical cable resources in the utility tunnel and according to the historical optical cable laying records includes: The historical optical cable laying records are analyzed to obtain the actual route segments; By comparing the actual route segment with the optical cable segment in the three-dimensional distribution map of optical cable resources in the utility tunnel, the missing optical cable segment is obtained.

4. The optical cable resource management method based on multi-source data as described in claim 1, characterized in that, The step of identifying high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time points includes: Based on the municipal engineering progress data corresponding to the abnormal handover time points, generate time-series data containing road segment identifiers; Based on the time series data, the risk level of each optical cable segment is calculated using the random forest algorithm, and the optical cable segments with a risk level greater than a preset threshold are identified as high-risk optical cable segments. Based on the three-dimensional distribution map of optical cable resources in the utility tunnel, and according to the high-risk optical cable segments and the progress data of the municipal engineering project, an integrity risk map of optical cable resources based on road segments and time dimensions is generated to obtain high-risk areas.

5. The optical cable resource management method based on multi-source data as described in claim 1, characterized in that, For the high-risk areas, the generation of a list of optical cable segments with unclear responsibility and an integrity verification report includes: Based on the optical cable inspection data and property maintenance records corresponding to the high-risk areas, a data consistency check was performed to determine the missing parts of the records; The optical cable segment corresponding to the missing part of the record is marked as the first optical cable segment; Based on the first optical cable segment, data matching is performed in the preset responsibility database to filter out the first optical cable segment with no matching data, and the second optical cable segment is obtained. Feature analysis was performed on the second optical cable segment to determine the potential correlation between optical cable segments in high-risk areas; Based on the second optical cable segment and the potential association, a list of optical cable segments with unclear responsibility is generated; Anomalies are extracted from the list of optical cable segments with unclear responsibility, and a preliminary optical cable existence map is generated based on the infrared scanning results of the anomalies. Based on the preliminary optical cable existence diagram, analyze the physical state of the optical cable and mark the areas with abnormal physical states as areas to be verified. Historical inspection photos of the area to be verified are obtained, and the historical inspection photos of the area to be verified are fused with infrared scanning results to generate an enhanced evidence map; Based on the list of optical cable segments with unclear responsibility and the enhanced evidence diagram, an integrity verification report for the optical cable is generated.

6. A fiber optic cable resource management device based on multi-source data, characterized in that, include: The distribution map construction module is used to acquire multi-source data of optical cables and construct a three-dimensional distribution map of optical cable resources in the underground utility tunnel based on the multi-source data; the multi-source data includes optical cable migration data in the underground utility tunnel renovation, municipal engineering progress data, and optical cable monitoring data; The missing segment identification module is used to obtain historical optical cable laying records and, based on the three-dimensional distribution map of optical cable resources in the utility tunnel, identify missing optical cable segments according to the historical optical cable laying records. The handover anomaly identification module is used to acquire and analyze the monitoring data of the missing optical cable segment and the load change data of the backhaul optical cable of the base station around the optical cable segment to determine the optical cable segment with layout changes and the time point of the handover anomaly. The risk area identification module is used to identify high-risk areas based on the municipal engineering progress data corresponding to the abnormal handover time points; The verification report generation module is used to generate a list of optical cable segments with unclear responsibility and an integrity verification report for the high-risk areas. The process of acquiring and analyzing monitoring data of the missing optical cable segment and load change data of the backhaul optical cables of base stations around the optical cable segment to determine the optical cable segments with layout changes and abnormal handover time points includes: Acquire monitoring data of the missing section of the optical cable, and determine the location of the abnormal state in the missing section of the optical cable based on the monitoring data of the missing section of the optical cable; Obtain historical inspection images of the locations with abnormal status, and extract the historical optical cable layout from the historical inspection images; Obtain the current optical cable thermal image of the location of the abnormal state, and extract the current optical cable layout from the current optical cable thermal image; Based on the historical optical cable layout and the current optical cable layout, determine the optical cable segments with layout changes; Obtain load change data of the backhaul optical cables of base stations around the optical cable segment with the described layout change; Determine the abnormal handover time point based on the load change data; The step of determining the handover anomaly time point based on the load change data includes: Perform time series analysis on the load change data to generate load change curves; By analyzing the correlation between the load change curve and the optical cable layout changes, load change patterns and temporal characteristics are extracted; Based on the load change pattern and the time characteristics, abnormal time points are selected; Based on the abnormal time point, the construction log records for the corresponding time period are retrieved and compared. If the load change at the abnormal time point does not match the construction log records, then the abnormal time point is taken as the handover abnormal time point.

7. A computer device, characterized in that, The method includes a processor and a memory, wherein the memory stores a computer program and the computer program is configured to be executed by the processor, wherein the processor executes the computer program to implement the optical cable resource management method based on multi-source data as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the optical cable resource management method based on multi-source data as described in any one of claims 1 to 5.

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